Initial import of Microtracking project
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Fernando Dávalos Hernández committed
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# Local credentials and agent state
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.kilo/
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.env
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.env.*
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!.env.example
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wifi_credentials.h
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cloud_credentials.h
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*.token
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*.secret
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# Generated files and dependencies
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__pycache__/
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*.py[cod]
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.pio/
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build/
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node_modules/
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.venv/
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venv/
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*.tmp
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*.swp
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# Private hub state and generated firmware
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/docker_tracker_hub/state/
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/docker_tracker_hub/data_logs/
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/docker_tracker_hub/firmware/*
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!/docker_tracker_hub/firmware/README.md
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# LaTeX intermediates; keep PDFs and experimental logs
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/articulo/*.aux
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/articulo/*.log
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/articulo/*.bcf
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/articulo/*.blg
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/articulo/*.run.xml
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/articulo/*.spl
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/articulo/*.synctex.gz
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LOG:[2025-09-19 16:22:11] X:50334,Y:105000,C:10434,V:429442,P:459304,S:24330,er:1000
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LOG:[2025-09-19 16:22:11] FineTune: dC=1856, dynE=1000, e=1000, near=0, Cmax=15494
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LOG:[2025-09-19 16:22:13] X:50334,Y:105000,C:10409,V:429667,P:463251,S:24332,er:1000
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LOG:[2025-09-19 16:22:13] FineTune: dC=1881, dynE=1000, e=1000, near=0, Cmax=15494
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import re, statistics
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path = r'logs_nuevos/log_2026-10-14.txt'
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lines = open(path, encoding='utf-8', errors='ignore').read().splitlines()
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pat = re.compile(r'\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] X:(-?\d+),Y:(-?\d+),C:(\d+),V:(\d+)')
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rows = [] # (time, x, y, c, v)
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for l in lines:
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m = pat.search(l)
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if m:
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rows.append((m.group(1), int(m.group(2)), int(m.group(3)), int(m.group(4)), int(m.group(5))))
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# Ventana donde X casi no se mueve pero C cae lentamente -> evidencia deriva termica
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# buscar tramo donde X dentro de +/-500 pasos durante muchos samples
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print('--- ventana con poca variacion en X pero caida de C ---')
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best_start = None; best_len = 0
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i = 0
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n = len(rows)
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while i < n - 60:
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window = rows[i:i+60]
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xs = [r[1] for r in window]; cs = [r[3] for r in window]
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x_spread = max(xs)-min(xs)
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c_drop = statistics.mean(cs[:15]) - statistics.mean(cs[-15:])
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if x_spread < 1500 and c_drop > 3000:
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if best_len < 60:
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best_len = 60; best_start = i
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i += 1
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else:
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i += 60
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if best_start is not None:
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w = rows[best_start:best_start+60]
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print('inicio:', w[0][0], 'X rango:', min(r[1] for r in w), max(r[1] for r in w))
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print('C primero/ultimo:', w[0][3], w[-1][3])
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for j, r in enumerate(w):
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if j % 6 == 0:
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print('%s X:%7d Y:%7d C:%8d V:%8d' % (r[0][11:], r[1], r[2], r[3], r[4]))
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import re, statistics
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from datetime import datetime
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path = r'logs_nuevos/log_2026-10-15.txt'
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lines = open(path, encoding='utf-8', errors='ignore').read().splitlines()
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# X/Y/C/V/P/er samples
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samp = re.compile(r'\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] X:(-?\d+),Y:(-?\d+),C:(-?\d+),V:(\d+),P:(\d+),S:(\d+),er:(-?\d+)')
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# FineTune lines
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ft = re.compile(r'\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2})\] FineTune: dC=(-?\d+), dynE=(-?\d+), e=(-?\d+), near=(\d+), CmaxN=(\d+), norm=(-?\d+), prox=([\d.]+)')
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rows = []
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fts = []
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for l in lines:
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m = samp.search(l)
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if m:
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rows.append((m.group(1), int(m.group(2)), int(m.group(3)), int(m.group(4)), int(m.group(5)), int(m.group(6)), int(m.group(7))))
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continue
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m = ft.search(l)
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if m:
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fts.append((m.group(1), int(m.group(2)), int(m.group(3)), int(m.group(4)), int(m.group(5)), int(m.group(6)), int(m.group(7)), float(m.group(8))))
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print("samples=%d finetune=%d" % (len(rows), len(fts)))
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print("rango:", rows[0][0], "->", rows[-1][0])
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def parse(t):
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return datetime.strptime(t, '%Y-%m-%d %H:%M:%S')
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# --- 1) Deteccion dia/noche por piranometro (P raw) ---
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# P raw ~ 16777000 = saturado negativo (noche). Dia: P pequeno (<~2M?)
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print("\n=== P (piranometro raw) estadisticas por hora ===")
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byhour = {}
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for r in rows:
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h = r[0][11:13]
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byhour.setdefault(h, []).append(r[5])
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for h in sorted(byhour):
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vals = byhour[h]
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print(" %s: n=%5d P_med=%9d P_min=%9d P_max=%9d" % (h, len(vals), int(statistics.median(vals)), min(vals), max(vals)))
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# --- 2) CmaxN evolucion (valor de pico normalizado) ---
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print("\n=== CmaxN: transiciones a nuevo maximo (solo cambios) ===")
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prev = None
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changes = 0
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for t, dC, dynE, e, near, cmax, norm, prox in fts:
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if prev is None or cmax != prev:
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if cmax >= 5000000 or (prev is not None and prev >= 5000000 and cmax < prev):
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print(" %s CmaxN %s -> %d norm=%d prox=%.2f" % (t[11:], str(prev), cmax, norm, prox))
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changes += 1
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prev = cmax
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print(" (transiciones grandes mostradas: %d)" % changes)
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# --- 3) Encontrar cuando CmaxN explota ---
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print("\n=== Primer momento en que CmaxN supera 5M / 10M / 18M ===")
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for thr in (5000000, 10000000, 18400000):
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for t, dC, dynE, e, near, cmax, norm, prox in fts:
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if cmax >= thr:
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print(" CmaxN>=%d en %s (norm=%d prox=%.2f dC=%d)" % (thr, t[11:], norm, prox, dC))
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break
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# --- 4) Contexto: irradiancia (P) en la explosion ---
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# buscar la muestra mas cercana antes de 14:41:57
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t_exp = '14:41:57'
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close = None
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for r in rows:
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if r[0][11:] <= t_exp:
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close = r
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print("\n=== Contexto poco antes de la explosion (14:41:57) ===")
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idx = rows.index(close)
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for r in rows[max(0, idx-6):idx+3]:
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print(" %s C=%6d V=%8d P=%9d" % (r[0][11:], r[3], r[4], r[5]))
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# --- 5) Movimiento nocturno: pasos acumulados cuando no hay sol (P saturado) ---
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print("\n=== Movimiento por hora (pasos = |dX|+|dY| entre muestras) ===")
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def steps_hour():
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res = {}
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for i in range(1, len(rows)):
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h = rows[i][0][11:13]
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d = abs(rows[i][1]-rows[i-1][1]) + abs(rows[i][2]-rows[i-1][2])
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res.setdefault(h, 0)
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res[h] += d
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return res
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sh = steps_hour()
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for h in sorted(sh):
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tag = ""
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med = int(statistics.median(byhour.get(h, [0])))
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if med > 16000000: tag = " <== NOCHE (piranometro saturado)"
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print(" %s: pasos=%9d P_med=%9d%s" % (h, sh[h], med, tag))
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# --- 6) Dinamica del error el dia (resumen) ---
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print("\n=== Error dinamico: distribucion de e segun prox ===")
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bins = [(0,0.05),(0.05,0.15),(0.15,0.30),(0.30,0.50),(0.50,1.01)]
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for lo,hi in bins:
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es = [e for (_,_,_,e,_,_,_,prox) in fts if lo<=prox<hi]
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if es:
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print(" prox[%.2f-%.2f): n=%5d e_med=%5d e_min=%d e_max=%d" % (lo,hi,len(es),int(statistics.median(es)),min(es),max(es)))
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"""Reproducible, quality-flagged analysis of the 3 November 2026 field log.
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Run with Python 3.12. Use --inspect for a read-only diagnostic summary.
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Raw ADC observations are never overwritten or reconstructed from clipped data.
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"""
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import argparse
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import hashlib
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import json
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import re
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import sys
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from pathlib import Path
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import matplotlib
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matplotlib.use("Agg")
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import matplotlib.dates as mdates
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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BASE = Path(__file__).resolve().parent
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SOURCE = BASE / "logs_nuevos" / "log_2026-11-03.txt"
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OUT = BASE / "figures" / "2026-11-03"
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ADC_MAX = 8388607
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VREF = 2.048
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GAIN = 20.0
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AREA = 0.002497
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FF = 0.82
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CHANGE_BEFORE = pd.Timestamp("2026-11-03 12:38:07")
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CHANGE_AFTER = pd.Timestamp("2026-11-03 12:46:01")
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READY = pd.Timestamp("2026-11-03 10:56:04")
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MAX_GAP_S = 15.0
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MAIN = re.compile(
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r"LOG:\[(?P<timestamp>[^\]]+)\] X:(?P<x_steps>-?\d+),Y:(?P<y_steps>-?\d+),"
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r"C:(?P<c_raw>-?\d+),V:(?P<v_raw>-?\d+),P:(?P<p_raw>-?\d+),"
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r"S:(?P<uptime_s>\d+),er:(?P<er>\d+)"
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)
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TEL = re.compile(
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r"LOG:\[(?P<timestamp>[^\]]+)\] TEL: t=(?P<uptime_s>\d+)s, "
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r"steps=(?P<steps>\d+)\(\+?(?P<delta>\d+)\)"
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)
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EVENT = re.compile(r"LOG:\[(?P<timestamp>[^\]]+)\] (?P<message>.*)")
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def sign24(value):
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value = np.asarray(value, dtype=np.int64) & 0xFFFFFF
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return np.where(value & 0x800000, value - 0x1000000, value)
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def parse_log(path):
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samples, telemetry, events = [], [], []
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with path.open(encoding="utf-8-sig") as stream:
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for line_number, line in enumerate(stream, 1):
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match = MAIN.search(line)
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if match:
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record = match.groupdict()
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record = {k: pd.Timestamp(v) if k == "timestamp" else int(v)
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for k, v in record.items()}
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record["source_line"] = line_number
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samples.append(record)
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continue
|
||||
match = TEL.search(line)
|
||||
if match:
|
||||
record = match.groupdict()
|
||||
record = {k: pd.Timestamp(v) if k == "timestamp" else int(v)
|
||||
for k, v in record.items()}
|
||||
record["source_line"] = line_number
|
||||
telemetry.append(record)
|
||||
continue
|
||||
match = EVENT.search(line)
|
||||
if match:
|
||||
message = match["message"]
|
||||
if not message.startswith("FineTune:"):
|
||||
events.append({"timestamp": pd.Timestamp(match["timestamp"]),
|
||||
"source_line": line_number, "message": message})
|
||||
frame = pd.DataFrame(samples)
|
||||
if frame.empty or not frame.timestamp.is_monotonic_increasing:
|
||||
raise ValueError("Missing samples or non-monotonic source timestamps")
|
||||
return frame, pd.DataFrame(telemetry), pd.DataFrame(events)
|
||||
|
||||
|
||||
def calibrate(frame):
|
||||
frame = frame.copy()
|
||||
frame["c_signed"] = sign24(frame.c_raw)
|
||||
frame["v_signed"] = sign24(frame.v_raw)
|
||||
frame["p_signed"] = sign24(frame.p_raw)
|
||||
frame["shunt_ohm"] = np.where(frame.timestamp >= CHANGE_AFTER, 0.130, 0.260)
|
||||
frame["isc_observed_A"] = frame.c_signed / ADC_MAX * VREF / GAIN / frame.shunt_ohm
|
||||
frame["voc_V"] = frame.v_signed / ADC_MAX * VREF * 2
|
||||
frame["irradiance_W_m2"] = frame.p_signed / ADC_MAX * VREF * 1000 / 0.2
|
||||
frame["adc_clipped"] = (frame.c_signed.abs() >= ADC_MAX) | (frame.v_signed.abs() >= ADC_MAX) | (frame.p_signed.abs() >= ADC_MAX)
|
||||
frame["near_current_rail"] = frame.c_signed.abs() >= 0.99 * ADC_MAX
|
||||
frame["setup"] = frame.timestamp < READY
|
||||
frame["transition_uncertain"] = (frame.timestamp > CHANGE_BEFORE) & (frame.timestamp < CHANGE_AFTER)
|
||||
frame["invalid_polarity"] = (frame.c_signed < 0) | (frame.v_signed < 0) | (frame.p_signed < 0)
|
||||
frame["electrical_valid"] = ~(frame.adc_clipped | frame.near_current_rail | frame.setup |
|
||||
frame.transition_uncertain | frame.invalid_polarity)
|
||||
frame["isc_A"] = frame.isc_observed_A.where(frame.electrical_valid)
|
||||
frame["power_FF_W"] = frame.isc_A * frame.voc_V * FF
|
||||
frame["illuminated"] = frame.irradiance_W_m2 > 50
|
||||
frame["aperture_efficiency_pct"] = (
|
||||
100 * frame.power_FF_W / (AREA * frame.irradiance_W_m2)
|
||||
).where(frame.electrical_valid & frame.illuminated)
|
||||
frame["responsivity_A_m2_W"] = (frame.isc_A / frame.irradiance_W_m2).where(frame.illuminated)
|
||||
frame["quality_flags"] = [
|
||||
";".join(name for name in ("setup", "transition_uncertain", "adc_clipped",
|
||||
"near_current_rail", "invalid_polarity") if row[name]) or "accepted"
|
||||
for row in frame.to_dict("records")
|
||||
]
|
||||
return frame
|
||||
|
||||
|
||||
def interval_mask(frame, selected, max_gap=MAX_GAP_S):
|
||||
"""Select edges, not filtered rows: never bridge missing or rejected samples."""
|
||||
dt = frame.timestamp.diff().dt.total_seconds().to_numpy()[1:]
|
||||
selected = np.asarray(selected, dtype=bool)
|
||||
same_shunt = frame.shunt_ohm.to_numpy()[1:] == frame.shunt_ohm.to_numpy()[:-1]
|
||||
reboot = frame.uptime_s.to_numpy()[1:] < frame.uptime_s.to_numpy()[:-1]
|
||||
return selected[:-1] & selected[1:] & (dt > 0) & (dt <= max_gap) & same_shunt & ~reboot
|
||||
|
||||
|
||||
def integrate(frame, values, edges):
|
||||
values = np.asarray(values, dtype=float)
|
||||
dt = frame.timestamp.diff().dt.total_seconds().to_numpy()[1:]
|
||||
return float(np.sum(((values[:-1] + values[1:]) * 0.5 * dt)[edges]) / 3600)
|
||||
|
||||
|
||||
def window_metrics(frame, selected, reference, telemetry, events, max_gap=MAX_GAP_S):
|
||||
selected = np.asarray(selected, dtype=bool) & frame.electrical_valid & frame.illuminated
|
||||
observed = frame.loc[selected]
|
||||
if len(observed) < 2:
|
||||
raise ValueError("Insufficient valid illuminated data")
|
||||
edges = interval_mask(frame, selected, max_gap)
|
||||
seconds = frame.timestamp.diff().dt.total_seconds().to_numpy()[1:]
|
||||
duration = float(seconds[edges].sum())
|
||||
power_ref = reference * frame.irradiance_W_m2 * frame.voc_V * FF
|
||||
energy = integrate(frame, frame.power_FF_W, edges)
|
||||
irradiation = integrate(frame, frame.irradiance_W_m2, edges)
|
||||
ref_energy = integrate(frame, power_ref, edges)
|
||||
peak_current = observed.isc_A.max()
|
||||
on = frame.isc_A >= 0.8 * peak_current
|
||||
normalized_on = frame.responsivity_A_m2_W >= 0.8 * reference
|
||||
# Occupancy time uses trapezoidal interpolation of endpoint indicators only.
|
||||
on_hours = integrate(frame, on.astype(float), edges)
|
||||
normalized_on_hours = integrate(frame, normalized_on.astype(float), edges)
|
||||
dx = frame.x_steps.diff().abs().to_numpy()[1:]
|
||||
dy = frame.y_steps.diff().abs().to_numpy()[1:]
|
||||
sx, sy = int(dx[edges].sum()), int(dy[edges].sum())
|
||||
motion_wh = (sx * 1.2 / 6000 + sy * 2.5 / 6000) / 3600
|
||||
# TEL increments describe fine-tune motion only, and are not a total-travel counter.
|
||||
t0, t1 = observed.timestamp.iloc[0], observed.timestamp.iloc[-1]
|
||||
tel_selected = (telemetry.timestamp >= t0) & (telemetry.timestamp <= t1)
|
||||
td = telemetry.timestamp.diff().dt.total_seconds().to_numpy()[1:]
|
||||
tel_pair = tel_selected.to_numpy()[:-1] & tel_selected.to_numpy()[1:]
|
||||
tel_pair &= (td > 0) & (td <= max_gap)
|
||||
tel_pair &= telemetry.uptime_s.diff().to_numpy()[1:] >= 0
|
||||
increments = telemetry.steps.diff().to_numpy()[1:]
|
||||
tel_pair &= increments >= 0
|
||||
# Require both TEL endpoints to lie inside an accepted coordinate edge.
|
||||
ts_ns = frame.timestamp.astype("int64").to_numpy()
|
||||
tel_ns = telemetry.timestamp.astype("int64").to_numpy()
|
||||
covered = np.zeros(len(telemetry) - 1, dtype=bool)
|
||||
starts = np.flatnonzero(edges & ~np.r_[False, edges[:-1]])
|
||||
stops = np.flatnonzero(edges & ~np.r_[edges[1:], False]) + 1
|
||||
for start, stop in zip(starts, stops):
|
||||
covered |= (tel_ns[:-1] >= ts_ns[start]) & (tel_ns[1:] <= ts_ns[stop])
|
||||
tel_steps = int(increments[tel_pair & covered].sum())
|
||||
f5 = events.loc[(events.timestamp >= t0) & (events.timestamp <= t1) & events.message.str.startswith("F5:")]
|
||||
span = (t1 - t0).total_seconds()
|
||||
peak_power = observed.loc[observed.power_FF_W.idxmax()]
|
||||
return {
|
||||
"start": str(t0), "end": str(t1), "accepted_illuminated_samples": len(observed),
|
||||
"integrated_intervals": int(edges.sum()), "integrated_duration_h": duration / 3600,
|
||||
"elapsed_span_h": span / 3600, "valid_interval_coverage_pct": 100 * duration / span,
|
||||
"estimated_energy_Wh": energy, "irradiation_Wh_m2": irradiation,
|
||||
"incident_aperture_energy_Wh": AREA * irradiation,
|
||||
"energy_weighted_aperture_efficiency_pct": 100 * energy / (AREA * irradiation),
|
||||
"reference_energy_Wh": ref_energy, "empirical_tracking_efficiency_pct": 100 * energy / ref_energy,
|
||||
"power_MAE_W": float(np.abs(power_ref[selected] - observed.power_FF_W).mean()),
|
||||
"peak_isc_A": float(peak_current), "peak_voc_V": float(observed.voc_V.max()),
|
||||
"peak_irradiance_W_m2": float(observed.irradiance_W_m2.max()),
|
||||
"peak_estimated_power_W": float(observed.power_FF_W.max()),
|
||||
"peak_power_timestamp": str(peak_power.timestamp),
|
||||
"peak_power_isc_A": float(peak_power.isc_A), "peak_power_voc_V": float(peak_power.voc_V),
|
||||
"peak_power_irradiance_W_m2": float(peak_power.irradiance_W_m2),
|
||||
"median_aperture_efficiency_pct": float(observed.aperture_efficiency_pct.median()),
|
||||
"peak_aperture_efficiency_pct": float(observed.aperture_efficiency_pct.max()),
|
||||
"current_threshold_on_target_sample_pct": float(100 * on[selected].mean()),
|
||||
"current_threshold_on_target_time_pct": 100 * on_hours / (duration / 3600),
|
||||
"responsivity_on_target_sample_pct": float(100 * normalized_on[selected].mean()),
|
||||
"responsivity_on_target_time_pct": 100 * normalized_on_hours / (duration / 3600),
|
||||
"sampled_x_travel_steps": sx, "sampled_y_travel_steps": sy,
|
||||
"estimated_sampled_motion_energy_Wh": motion_wh,
|
||||
"fine_tune_TEL_steps_in_accepted_edges": tel_steps,
|
||||
"F5_events_in_elapsed_span": len(f5),
|
||||
}
|
||||
|
||||
|
||||
def calculate(frame, telemetry, events):
|
||||
valid = frame.electrical_valid & frame.illuminated
|
||||
reference = float(frame.loc[valid, "responsivity_A_m2_W"].max())
|
||||
reference_p99 = float(frame.loc[valid, "responsivity_A_m2_W"].quantile(0.99))
|
||||
frame = frame.copy()
|
||||
frame["reference_power_W"] = (reference * frame.irradiance_W_m2 * frame.voc_V * FF).where(valid)
|
||||
frame["normalized_response"] = frame.responsivity_A_m2_W / reference
|
||||
frame["integrate_from_previous"] = np.r_[False, interval_mask(frame, valid)]
|
||||
frame["integration_duration_s"] = frame.timestamp.diff().dt.total_seconds().where(frame.integrate_from_previous)
|
||||
windows = {
|
||||
"all_valid": pd.Series(True, index=frame.index),
|
||||
"pre_change_unclipped": frame.timestamp <= CHANGE_BEFORE,
|
||||
"post_change": frame.timestamp >= CHANGE_AFTER,
|
||||
"fixed_hour_13_14": (frame.timestamp >= pd.Timestamp("2026-11-03 13:00")) &
|
||||
(frame.timestamp < pd.Timestamp("2026-11-03 14:00")),
|
||||
}
|
||||
metrics = {name: window_metrics(frame, mask, reference, telemetry, events)
|
||||
for name, mask in windows.items()}
|
||||
for name, mask in windows.items():
|
||||
sensitivity = window_metrics(frame, mask, reference_p99, telemetry, events)
|
||||
metrics[name]["tracking_efficiency_p99_reference_pct"] = sensitivity["empirical_tracking_efficiency_pct"]
|
||||
sensitivity = []
|
||||
for limit in (10, 15, 30, 60):
|
||||
result = window_metrics(frame, windows["post_change"], reference, telemetry, events, limit)
|
||||
sensitivity.append({"max_gap_s": limit, "duration_h": result["integrated_duration_h"],
|
||||
"energy_Wh": result["estimated_energy_Wh"],
|
||||
"aperture_efficiency_pct": result["energy_weighted_aperture_efficiency_pct"],
|
||||
"tracking_efficiency_pct": result["empirical_tracking_efficiency_pct"]})
|
||||
return frame, metrics, {"maximum_A_m2_W": reference, "p99_A_m2_W": reference_p99}, sensitivity
|
||||
|
||||
|
||||
def save_figure(fig, name):
|
||||
for extension in ("pdf", "png"):
|
||||
fig.savefig(OUT / f"{name}.{extension}", dpi=220, bbox_inches="tight")
|
||||
plt.close(fig)
|
||||
|
||||
|
||||
def time_axes(ax):
|
||||
ax.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M"))
|
||||
ax.xaxis.set_major_locator(mdates.MinuteLocator(byminute=[0, 30]))
|
||||
ax.set_xlabel("Local log time")
|
||||
ax.grid(alpha=0.2)
|
||||
|
||||
|
||||
def figures(frame, metrics, reference):
|
||||
plt.rcParams.update({"font.family": "DejaVu Sans", "font.size": 9,
|
||||
"axes.spines.top": False, "axes.spines.right": False,
|
||||
"pdf.fonttype": 42, "ps.fonttype": 42})
|
||||
t = frame.timestamp
|
||||
gap_breaks = frame.timestamp.diff().dt.total_seconds() > MAX_GAP_S
|
||||
fig, axes = plt.subplots(3, 1, figsize=(9, 8), sharex=True, layout="constrained")
|
||||
axes[0].plot(t, (frame.c_signed / 1e6).mask(gap_breaks), color="#425466", lw=0.65)
|
||||
axes[0].axhline(ADC_MAX / 1e6, color="#b84335", ls="--", label="ADC positive rail")
|
||||
axes[0].scatter(t[frame.adc_clipped], frame.loc[frame.adc_clipped, "c_signed"] / 1e6,
|
||||
s=5, color="#b84335", label="Clipped observations", zorder=3)
|
||||
axes[0].set_ylabel("Current channel\n[$10^6$ ADC counts]")
|
||||
axes[0].legend(loc="lower right", fontsize=8)
|
||||
axes[1].plot(t, (1000 * frame.isc_A).mask(gap_breaks), color="#167d8d", lw=0.7, label="Accepted current")
|
||||
axes[1].plot(t[frame.adc_clipped], 1000 * frame.loc[frame.adc_clipped, "isc_observed_A"],
|
||||
".", color="#b84335", ms=2, label="Clipped lower bounds (not corrected)")
|
||||
axes[1].set_ylabel("$I_{sc}$ [mA]")
|
||||
axes[1].legend(loc="lower left", fontsize=8)
|
||||
axes[2].plot(t, frame.irradiance_W_m2.mask(gap_breaks), color="#c17a20", lw=0.7)
|
||||
axes[2].set_ylabel("Irradiance\n[W m$^{-2}$]")
|
||||
for ax in axes:
|
||||
ax.axvspan(CHANGE_BEFORE, CHANGE_AFTER, color="#c17a20", alpha=0.18)
|
||||
time_axes(ax)
|
||||
axes[0].set_title("3 November 2026: acquisition quality and piecewise shunt calibration", loc="left")
|
||||
axes[1].text(0.02, 0.94, "260 m$\\Omega$ before gap; 130 m$\\Omega$ after gap",
|
||||
transform=axes[1].transAxes, va="top", fontsize=8)
|
||||
save_figure(fig, "quality_and_calibration")
|
||||
|
||||
post = frame.timestamp >= CHANGE_AFTER
|
||||
light = frame.electrical_valid & frame.illuminated & post
|
||||
# Insert NaNs at rejected edges so lines do not visually bridge acquisition gaps.
|
||||
displayed = frame.copy()
|
||||
breaks = np.r_[False, ~interval_mask(frame, frame.electrical_valid)]
|
||||
cols = ["power_FF_W", "reference_power_W", "normalized_response", "aperture_efficiency_pct"]
|
||||
displayed.loc[breaks, cols] = np.nan
|
||||
fig, axes = plt.subplots(3, 1, figsize=(9, 8), sharex=True, layout="constrained")
|
||||
axes[0].plot(t[post], displayed.loc[post, "reference_power_W"], color="#8995a2", lw=0.8,
|
||||
label="Empirical same-record reference")
|
||||
axes[0].plot(t[post], displayed.loc[post, "power_FF_W"], color="#167d8d", lw=0.8,
|
||||
label="Estimated MPP power ($FF=0.82$)")
|
||||
axes[0].set_ylabel("Estimated power [W]")
|
||||
axes[0].legend(loc="lower left", fontsize=8)
|
||||
axes[1].plot(t[post], displayed.loc[post, "normalized_response"], color="#5367a0", lw=0.7)
|
||||
axes[1].axhline(0.8, ls="--", color="#b84335", lw=0.8, label="80% normalized-response threshold")
|
||||
axes[1].set_ylabel("$(I_{sc}/G)/R_{ref}$")
|
||||
axes[1].set_ylim(0, 1.08)
|
||||
axes[1].legend(loc="lower left", fontsize=8)
|
||||
axes[2].plot(t[post], displayed.loc[post, "aperture_efficiency_pct"], color="#19734f", lw=0.7)
|
||||
axes[2].set_ylabel("Aperture efficiency [%]")
|
||||
for ax in axes:
|
||||
time_axes(ax)
|
||||
axes[0].set_title("Post-change performance, including the late low-output period", loc="left")
|
||||
save_figure(fig, "post_change_performance")
|
||||
|
||||
fig, axes = plt.subplots(1, 2, figsize=(10, 4), layout="constrained")
|
||||
sc = axes[0].scatter(frame.loc[light, "irradiance_W_m2"], frame.loc[light, "isc_A"] * 1000,
|
||||
c=mdates.date2num(t[light]), cmap="viridis", s=8, alpha=0.7, rasterized=True)
|
||||
g = np.linspace(50, frame.loc[light, "irradiance_W_m2"].max(), 200)
|
||||
axes[0].plot(g, 1000 * g * reference["maximum_A_m2_W"], "--", color="#b84335", lw=1,
|
||||
label="Same-record maximum responsivity")
|
||||
axes[0].set(xlabel="Irradiance [W m$^{-2}$]", ylabel="$I_{sc}$ [mA]", title="Irradiance-normalized response")
|
||||
axes[0].legend(fontsize=7)
|
||||
bar = fig.colorbar(sc, ax=axes[0], label="Log time")
|
||||
bar.ax.yaxis.set_major_formatter(mdates.DateFormatter("%H:%M"))
|
||||
binned = frame.loc[post].copy()
|
||||
binned["on"] = (binned.normalized_response >= 0.8).where(binned.electrical_valid & binned.illuminated)
|
||||
grouped = binned.set_index("timestamp").on.resample("15min").agg(["mean", "count"])
|
||||
axes[1].bar(grouped.index + pd.Timedelta(minutes=7.5), grouped["mean"] * 100,
|
||||
width=12 / 1440, color="#167d8d")
|
||||
axes[1].plot(grouped.index + pd.Timedelta(minutes=7.5), grouped["mean"] * 100,
|
||||
"o", color="#167d8d", ms=3)
|
||||
axes[1].set(ylabel="Normalized on-target samples [%]", ylim=(0, 105), title="15-minute bins; illuminated samples")
|
||||
time_axes(axes[1])
|
||||
axes[0].grid(alpha=0.2)
|
||||
save_figure(fig, "response_and_occupancy")
|
||||
|
||||
|
||||
def write_outputs(frame, telemetry, events, metrics, reference, sensitivity):
|
||||
OUT.mkdir(parents=True, exist_ok=True)
|
||||
curated = SOURCE.with_name("log_2026-11-03_curated.csv")
|
||||
frame.to_csv(curated, index=False, float_format="%.12g")
|
||||
source_lines = SOURCE.read_text(encoding="utf-8-sig").splitlines()
|
||||
headers = [
|
||||
"# Curated observations from log_2026-11-03.txt; original raw ADC codes retained.",
|
||||
"# Calibration: Vref=2.048 V; AD8418 gain=20; Voc divider=2; pyranometer=0.2 mV/(W/m2).",
|
||||
"# Shunt=0.260 ohm through 12:38:07; shunt=0.130 ohm from 12:46:01; change occurred in missing interval.",
|
||||
"# Setup before 10:56:04, clipping, >=99% current rail and invalid polarity excluded.",
|
||||
"# No clipped current reconstruction, no interpolation over gaps; see curated CSV for rejected rows and source lines.",
|
||||
"# Use the full CSV integrate_from_previous flag; accepted-only rows cannot identify every rejected interval.",
|
||||
"# Do not apply a single-shunt legacy converter to this file. Low-output observations are retained.",
|
||||
]
|
||||
accepted_lines = [source_lines[int(i) - 1] for i in frame.loc[frame.electrical_valid, "source_line"]]
|
||||
SOURCE.with_name("log_2026-11-03_curated.txt").write_text(
|
||||
"\n".join(headers + accepted_lines) + "\n", encoding="utf-8")
|
||||
events.to_csv(OUT / "source_events.csv", index=False)
|
||||
pd.DataFrame(metrics).T.to_csv(OUT / "metrics.csv", float_format="%.10g")
|
||||
pd.DataFrame(sensitivity).to_csv(OUT / "gap_sensitivity.csv", index=False)
|
||||
source_info = {
|
||||
"source": str(SOURCE.relative_to(BASE)), "sha256": hashlib.sha256(SOURCE.read_bytes()).hexdigest(),
|
||||
"analysis_sha256": hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),
|
||||
"source_line_count": len(source_lines), "main_observations": len(frame),
|
||||
"accepted_electrical_observations": int(frame.electrical_valid.sum()),
|
||||
"flags_nonexclusive": {name: int(frame[name].sum()) for name in
|
||||
("setup", "adc_clipped", "near_current_rail", "invalid_polarity", "transition_uncertain")},
|
||||
"current_clip_first": str(frame.loc[frame.adc_clipped, "timestamp"].min()),
|
||||
"current_clip_last": str(frame.loc[frame.adc_clipped, "timestamp"].max()),
|
||||
"shunt_change_bracket": [str(CHANGE_BEFORE), str(CHANGE_AFTER)],
|
||||
"change_bracket_is_inferred": True,
|
||||
"setup_exclusion_before": str(READY),
|
||||
"firmware_diagnostic_caveat": "Logged irradiance diagnostics use about one tenth of the corrected offline scale; controller decisions were not recalculated.",
|
||||
"software": {"python": sys.version.split()[0], "numpy": np.__version__,
|
||||
"pandas": pd.__version__, "matplotlib": matplotlib.__version__},
|
||||
"calibration": {"vref_V": VREF, "adc_positive_full_scale": ADC_MAX, "current_amplifier_gain": GAIN,
|
||||
"voc_divider": 2, "pyranometer_mV_per_W_m2": 0.2,
|
||||
"shunt_before_ohm": 0.260, "shunt_after_ohm": 0.130,
|
||||
"aperture_area_m2": AREA, "assumed_fill_factor": FF,
|
||||
"current_rail_rejection_fraction": 0.99, "max_gap_s": MAX_GAP_S},
|
||||
"empirical_reference": reference, "metrics": metrics, "gap_sensitivity": sensitivity,
|
||||
}
|
||||
(OUT / "analysis.json").write_text(json.dumps(source_info, indent=2, allow_nan=False) + "\n", encoding="utf-8")
|
||||
return source_info
|
||||
|
||||
|
||||
def write_report(frame, metrics, info):
|
||||
post = metrics["post_change"]
|
||||
noon = metrics["fixed_hour_13_14"]
|
||||
pre = metrics["pre_change_unclipped"]
|
||||
labels = {"all_valid": "All accepted segments", "pre_change_unclipped": "Before change (unclipped only)",
|
||||
"post_change": "After change (all illuminated)", "fixed_hour_13_14": "Fixed hour, 13:00--14:00"}
|
||||
rows = []
|
||||
for key, m in metrics.items():
|
||||
rows.append(
|
||||
f"{labels[key]} & {m['accepted_illuminated_samples']} & {m['integrated_duration_h']:.3f} & "
|
||||
f"{m['estimated_energy_Wh']:.3f} & {m['energy_weighted_aperture_efficiency_pct']:.2f} & "
|
||||
f"{m['empirical_tracking_efficiency_pct']:.2f} \\\\"
|
||||
)
|
||||
table_rows = "\n".join(rows)
|
||||
first = frame.loc[frame.adc_clipped, "timestamp"].min().strftime("%H:%M:%S")
|
||||
last = frame.loc[frame.adc_clipped, "timestamp"].max().strftime("%H:%M:%S")
|
||||
reference = info["empirical_reference"]
|
||||
text = rf"""% Generated by analyze_2026_11_03.py. Do not hand-edit numerical results.
|
||||
% Intended compilation directory: articulo. This file does not modify PRINCIPAL.tex.
|
||||
\subsection{{Quality-Controlled Outdoor Evaluation on 3 November 2026}}
|
||||
\label{{subsec:nov03_curated}}
|
||||
|
||||
\paragraph{{Acquisition quality and shunt intervention}}
|
||||
The firmware 1.1.3-ws record contains {len(frame)} coordinate/electrical observations
|
||||
between 10:44:20 and 15:40:42 on 3 November 2026. Times are the local log clock;
|
||||
the file does not encode a time zone. Initial commissioning includes manual
|
||||
coordinate changes and parameter commands. Observations before 10:56:04, the
|
||||
logged initial sampling-delay configuration, are conservatively marked as setup.
|
||||
Subsequent controller parameter changes through 11:41:03 are retained and disclosed;
|
||||
the pre-intervention segment is not a fixed-parameter benchmark.
|
||||
|
||||
The experimenter reported adding a second resistor in parallel with the
|
||||
260~m$\Omega$ current shunt, reducing its nominal resistance to 130~m$\Omega$.
|
||||
The exact soldering time is not recorded. The change is assigned to the
|
||||
unobserved interval between 12:38:07 and 12:46:01 (474~s), supported by the
|
||||
reset of the uptime/counter and the approximately halved current-channel codes
|
||||
after the gap, while irradiance remains comparable. No sample is assigned an
|
||||
invented intervention timestamp inside this interval. The first returned
|
||||
observations, including reacquisition at low current, are retained rather than
|
||||
discarded to improve performance.
|
||||
|
||||
The current channel reaches the positive ADC rail of 8,388,607 counts in
|
||||
{int(frame.adc_clipped.sum())} observations, from {first} to {last}.
|
||||
Clipped values provide only lower bounds on current; they cannot be restored by
|
||||
multiplying the trace or changing the shunt calibration. A conservative
|
||||
99\%-of-rail guard additionally excludes near-rail current observations
|
||||
({int((frame.near_current_rail & ~frame.adc_clipped).sum())} beyond the clipped set).
|
||||
The audit CSV retains all observations, original ADC codes, source line numbers,
|
||||
the applicable nominal shunt value and nonexclusive quality flags; rejected
|
||||
current/power estimates are blank. An explicit \texttt{{integrate\_from\_previous}}
|
||||
column marks usable full-record integration edges; additional window filtering
|
||||
must still require both endpoints inside the chosen window.
|
||||
The companion curated text log contains
|
||||
accepted raw observations only, with calibration metadata, and is not suitable
|
||||
for a legacy single-shunt converter. Low-output, cloud/standby and later
|
||||
drift-correction periods are not removed solely for poor performance.
|
||||
|
||||
\paragraph{{Calibration and modeled electrical output}}
|
||||
Using signed 24-bit codes $C$, $V$ and $P$, positive full scale $D=8,388,607$,
|
||||
and the 2.048-V reference, the offline conversions are
|
||||
\begin{{align}}
|
||||
I_{{sc}} &= \frac{{2.048 C}}{{20 D R_s}}, &
|
||||
V_{{oc}} &= \frac{{2(2.048)V}}{{D}}, &
|
||||
G &= \frac{{2048 P}}{{0.2 D}}.
|
||||
\end{{align}}
|
||||
Here $I_{{sc}}$ is in A, $V_{{oc}}$ in V, $G$ in W\,m$^{{-2}}$, and $R_s$
|
||||
is 0.260~$\Omega$ before the intervention gap and 0.130~$\Omega$ after it.
|
||||
The factor 20 is the external current-amplifier gain; the factor 2 accounts
|
||||
for the open-circuit voltage divider. The pyranometer scale is
|
||||
0.2~mV/(W\,m$^{{-2}}$), not the obsolete divisor 2.0.
|
||||
The corresponding nominal current full scales are 393.85 and 787.69~mA.
|
||||
This is an offline calibration correction, not a modification of the firmware
|
||||
or of the control decisions actually made during the experiment.
|
||||
The log's firmware irradiance diagnostics remain on a different scale: at
|
||||
10:51:15 the recorded $P=689473$ converts to approximately
|
||||
842~W\,m$^{{-2}}$, whereas the accompanying auto-start message reports
|
||||
84~W\,m$^{{-2}}$. Thus, logged firmware irradiance thresholds and standby messages
|
||||
must not be interpreted directly on the corrected offline axis. Correcting
|
||||
the exported irradiance does not retroactively correct those control decisions.
|
||||
A nominal firmware threshold of 10~W\,m$^{{-2}}$ therefore corresponds to
|
||||
approximately 100~W\,m$^{{-2}}$ on the corrected axis. The primary evaluation
|
||||
includes returned low-light observations even when the controller is in standby.
|
||||
|
||||
Electrical output is estimated as
|
||||
\begin{{equation}}
|
||||
\widehat{{P}}_{{\mathrm{{MPP}}}}=V_{{oc}} I_{{sc}} FF,\qquad FF=0.82.
|
||||
\end{{equation}}
|
||||
The fixed fill factor follows the manuscript model, not a new outdoor I--V
|
||||
measurement. Since the device alternates open- and short-circuit sensing,
|
||||
this quantity estimates available MPP power under approximately unchanged
|
||||
conditions across the sampling cycle; it is not measured power delivered to
|
||||
a load or harvested energy. Fast irradiance changes can violate that
|
||||
approximation. No cell-temperature, spectral-mismatch or fill-factor correction
|
||||
is inferred from this log.
|
||||
|
||||
With lens aperture $A_L=0.002497$~m$^2$, the aperture-referenced estimate is
|
||||
\begin{{equation}}
|
||||
\widehat{{\eta}}_{{\mathrm{{ap}}}}(t)=
|
||||
\frac{{\widehat{{P}}_{{\mathrm{{MPP}}}}(t)}}{{A_L G(t)}}\,100\%,\qquad
|
||||
\widehat{{\eta}}_{{\mathrm{{ap}},E}}=
|
||||
\frac{{\int\widehat{{P}}_{{\mathrm{{MPP}}}}\,dt}}{{A_L\int G\,dt}}\,100\%.
|
||||
\end{{equation}}
|
||||
This describes the combined lens/receiver system relative to the measured
|
||||
pyranometric irradiance. It is not intrinsic cell conversion efficiency:
|
||||
separating the cell requires the optical power incident on its active area
|
||||
(or validated optical throughput), which was not recorded. The pyranometer's
|
||||
global irradiance is not a direct-normal irradiance measurement and includes
|
||||
diffuse light that the concentrator may not collect. Reference-sensor alignment,
|
||||
incidence geometry and optical losses therefore remain part of this estimate.
|
||||
|
||||
\paragraph{{Accepted integration support and tracking indicators}}
|
||||
All energy, irradiation and reference-power integrals use the same
|
||||
adjacent accepted illuminated observations ($G>50$~W\,m$^{{-2}}$). An interval is
|
||||
included only if both endpoints are accepted, its duration is at most 15~s,
|
||||
the shunt does not change and uptime does not decrease. Trapezoidal integration
|
||||
never bridges rejected rows, reboots or long missing intervals. The tabulated
|
||||
duration is the sum of included intervals, not the elapsed window length.
|
||||
Unobserved or clipped periods are neither zero-filled nor reconstructed;
|
||||
the all-segments result is not a full-session energy estimate.
|
||||
In particular, selecting only unclipped pre-change points preferentially
|
||||
removes high-current periods and biases that subset; it cannot establish a
|
||||
causal performance improvement from the resistor intervention.
|
||||
|
||||
For comparison with the manuscript's responsivity approach, an empirical
|
||||
same-record reference is defined by
|
||||
\begin{{equation}}
|
||||
R_{{\mathrm{{ref}}}}=\max_{{\mathrm{{accepted}},\,G>50}}(I_{{sc}}/G)
|
||||
={reference['maximum_A_m2_W']:.7f}~\mathrm{{A\,m^2\,W^{{-1}}}},\quad
|
||||
\widehat{{P}}_{{\mathrm{{ref}}}}=R_{{\mathrm{{ref}}}}G V_{{oc}} FF.
|
||||
\end{{equation}}
|
||||
The empirical tracking indicator is
|
||||
$\widehat{{\eta}}_{{\mathrm{{tr}}}}=100\int\widehat{{P}}_{{\mathrm{{MPP}}}}dt/
|
||||
\int\widehat{{P}}_{{\mathrm{{ref}}}}dt$ on the same accepted support.
|
||||
It is an internal relative-yield benchmark, not independently validated ideal
|
||||
alignment efficiency or angular pointing accuracy. Irradiance geometry,
|
||||
temperature, spectrum and electrical offsets can also change $I_{{sc}}/G$.
|
||||
The reference reuses the measured $V_{{oc}}$, so it does not independently
|
||||
quantify voltage losses relative to a perfectly aligned receiver.
|
||||
No astronomical-angle accuracy or unambiguous cloud-recovery time is claimed.
|
||||
Replacing the maximum by the 99th-percentile responsivity
|
||||
({reference['p99_A_m2_W']:.7f}~A\,m$^2$\,W$^{{-1}}$) provides a reference sensitivity
|
||||
check; the resulting ratio is not clipped to 100\% and is not a strict ceiling.
|
||||
|
||||
Two sample-occupancy measures are kept separate:
|
||||
(i) $I_{{sc}}\geq0.8 I_{{sc,\max}}$ within each specified window, and
|
||||
(ii) $(I_{{sc}}/G)/R_{{\mathrm{{ref}}}}\geq0.8$ using the common reference.
|
||||
Both use accepted illuminated samples as their denominator, unlike the October
|
||||
criterion whose denominator includes every observation in its selected window.
|
||||
Neither is interchangeable with energy-based tracking efficiency.
|
||||
|
||||
\begin{{table}}[htbp]
|
||||
\centering
|
||||
\small
|
||||
\caption{{Results on accepted illuminated integration support. Energy and aperture
|
||||
efficiency are FF-based estimates; tracking efficiency uses a same-record
|
||||
empirical reference. Missing and clipped intervals are not integrated.}}
|
||||
\label{{tab:nov03_metrics}}
|
||||
\begin{{tabular}}{{@{{}}lrrrrr@{{}}}}
|
||||
\toprule
|
||||
Window & Samples & Hours & $\widehat{{E}}$ [Wh] & $\widehat{{\eta}}_{{\mathrm{{ap}},E}}$ [\%] & $\widehat{{\eta}}_{{\mathrm{{tr}}}}$ [\%] \\
|
||||
\midrule
|
||||
{table_rows}
|
||||
\bottomrule
|
||||
\end{{tabular}}
|
||||
\end{{table}}
|
||||
|
||||
\paragraph{{Post-intervention results and limitations}}
|
||||
The primary post-change evaluation retains the entire returned record,
|
||||
{post['start'].split()[1]}--{post['end'].split()[1]}, including the late low-output period.
|
||||
It contains {post['accepted_illuminated_samples']} accepted illuminated samples and
|
||||
{post['integrated_duration_h']:.3f}~h of integrated support
|
||||
({post['valid_interval_coverage_pct']:.2f}\% of its elapsed span).
|
||||
The estimated electrical energy is {post['estimated_energy_Wh']:.3f}~Wh for
|
||||
{post['irradiation_Wh_m2'] / 1000:.3f}~kWh\,m$^{{-2}}$ of irradiation on that support,
|
||||
giving {post['energy_weighted_aperture_efficiency_pct']:.2f}\% energy-weighted
|
||||
aperture efficiency. Peak current is {post['peak_isc_A'] * 1000:.1f}~mA, and
|
||||
peak modeled power is {post['peak_estimated_power_W']:.3f}~W; maxima of different
|
||||
variables need not be simultaneous. At the modeled power peak
|
||||
({post['peak_power_timestamp'].split()[1]}), the simultaneous log record gives
|
||||
$I_{{sc}}={post['peak_power_isc_A'] * 1000:.1f}$~mA,
|
||||
$V_{{oc}}={post['peak_power_voc_V']:.3f}$~V and
|
||||
$G={post['peak_power_irradiance_W_m2']:.1f}$~W\,m$^{{-2}}$.
|
||||
The median instantaneous aperture estimate
|
||||
is {post['median_aperture_efficiency_pct']:.2f}\%, and its peak is
|
||||
{post['peak_aperture_efficiency_pct']:.2f}\%, neither being a daily efficiency.
|
||||
The empirical tracking ratio is {post['empirical_tracking_efficiency_pct']:.2f}\%,
|
||||
with a sample-mean absolute power deviation of {post['power_MAE_W'] * 1000:.1f}~mW
|
||||
from the internal reference. The 99th-percentile reference changes this ratio
|
||||
to {post['tracking_efficiency_p99_reference_pct']:.2f}\%.
|
||||
Current-threshold and irradiance-normalized on-target sample fractions are
|
||||
{post['current_threshold_on_target_sample_pct']:.2f}\% and
|
||||
{post['responsivity_on_target_sample_pct']:.2f}\%, respectively; the corresponding
|
||||
endpoint-interpolated time fractions are
|
||||
{post['current_threshold_on_target_time_pct']:.2f}\% and
|
||||
{post['responsivity_on_target_time_pct']:.2f}\% on accepted intervals.
|
||||
|
||||
For a conventional fixed one-hour comparison rather than an automatically
|
||||
selected best interval, 13:00--14:00 gives
|
||||
{noon['energy_weighted_aperture_efficiency_pct']:.2f}\% aperture efficiency and
|
||||
{noon['empirical_tracking_efficiency_pct']:.2f}\% empirical tracking efficiency,
|
||||
with {noon['estimated_energy_Wh']:.3f}~Wh over {noon['integrated_duration_h']:.3f}~h
|
||||
of integrated support. This favourable subset must not replace the full
|
||||
post-change result. The pre-change unclipped subset has only
|
||||
{pre['valid_interval_coverage_pct']:.2f}\% valid interval coverage of its elapsed
|
||||
span and is reported for audit, not as an unbiased control experiment.
|
||||
|
||||
Sampled coordinate differences on post-change accepted illuminated intervals
|
||||
total {post['sampled_x_travel_steps']:,} $X$ steps and
|
||||
{post['sampled_y_travel_steps']:,} $Y$ steps. With the manuscript's bench costs
|
||||
(1.2~W and 2.5~W at approximately 6000 commanded steps/s), the corresponding
|
||||
sampled-motion estimate is {post['estimated_sampled_motion_energy_Wh']:.4f}~Wh.
|
||||
The independently differenced TEL counter contributes
|
||||
{post['fine_tune_TEL_steps_in_accepted_edges']:,} fine-tune steps on intervals
|
||||
fully covered by accepted coordinate runs. TEL does not count all motion.
|
||||
Sparse coordinate differences can miss intermediate reversals; neither count
|
||||
measures total motor/board consumption, and a total parasitic ratio or net
|
||||
electrical yield cannot be inferred. There are
|
||||
{post['F5_events_in_elapsed_span']} logged F5 corrections in the elapsed
|
||||
post-change span, including low-light operation outside some integration support.
|
||||
|
||||
All estimated powers, energies and aperture efficiencies scale linearly with
|
||||
the assumed $FF$: multiply by $FF'/0.82$ for another assumption. A common
|
||||
constant $FF$ cancels from the tracking ratio. No statistical or calibration
|
||||
confidence interval is assigned without resistance tolerances, reference-sensor
|
||||
uncertainty and outdoor I--V data. Results at 10-, 15-, 30- and 60-s maximum
|
||||
integration gaps are exported as a gap-policy sensitivity check.
|
||||
|
||||
\begin{{figure}}[p]
|
||||
\centering
|
||||
\includegraphics[width=0.95\linewidth,height=0.78\textheight,keepaspectratio]{{../figures/2026-11-03/quality_and_calibration.pdf}}
|
||||
\caption{{Quality control and piecewise current calibration on 3 November 2026.
|
||||
Red marks identify ADC-clipped observations, not recovered measurements.
|
||||
The shaded interval brackets the unobserved 260-to-130-m$\Omega$ shunt intervention.
|
||||
Accepted low-output observations remain in the record.}}
|
||||
\label{{fig:nov03_quality}}
|
||||
\end{{figure}}
|
||||
|
||||
\begin{{figure}}[p]
|
||||
\centering
|
||||
\includegraphics[width=0.95\linewidth,height=0.78\textheight,keepaspectratio]{{../figures/2026-11-03/post_change_performance.pdf}}
|
||||
\caption{{Post-intervention modeled MPP power, same-record normalized current
|
||||
response and lens-aperture-referenced efficiency. $FF=0.82$ and
|
||||
$A_L=0.002497$~m$^2$ are assumed. The late low-output period is retained;
|
||||
these are not direct load-power or intrinsic-cell-efficiency measurements.}}
|
||||
\label{{fig:nov03_performance}}
|
||||
\end{{figure}}
|
||||
|
||||
\begin{{figure}}[p]
|
||||
\centering
|
||||
\includegraphics[width=\linewidth]{{../figures/2026-11-03/response_and_occupancy.pdf}}
|
||||
\caption{{Post-change current versus irradiance (colour encodes log time),
|
||||
and occupancy of the 80\%-of-reference responsivity criterion in 15-min bins.
|
||||
Only accepted observations with $G>50$~W\,m$^{{-2}}$ enter the sample denominator;
|
||||
the reference is the maximum accepted responsivity of the same record.}}
|
||||
\label{{fig:nov03_response}}
|
||||
\end{{figure}}
|
||||
"""
|
||||
report_dir = BASE / "articulo"
|
||||
(report_dir / "results_2026_11_03.tex").write_text(text, encoding="utf-8")
|
||||
wrapper = r"""\documentclass[11pt]{article}
|
||||
\usepackage[margin=22mm]{geometry}
|
||||
\usepackage{graphicx,amsmath,amssymb,booktabs}
|
||||
\usepackage[T1]{fontenc}
|
||||
\usepackage{lmodern}
|
||||
\title{Quality-Controlled Field Analysis: 3 November 2026}
|
||||
\author{WiT-CPV experimental analysis}
|
||||
\date{}
|
||||
\begin{document}
|
||||
\maketitle
|
||||
\noindent Reproducible analysis of \texttt{log\_2026-11-03.txt}.
|
||||
Generated with \texttt{analyze\_2026\_11\_03.py}. The following subsection is
|
||||
provided as a standalone insertion for the manuscript; the principal article
|
||||
has not been modified.
|
||||
\section{Field Evaluation}
|
||||
\input{results_2026_11_03.tex}
|
||||
\clearpage
|
||||
\end{document}
|
||||
"""
|
||||
(report_dir / "analysis_2026_11_03.tex").write_text(wrapper, encoding="utf-8")
|
||||
|
||||
|
||||
def inspect(frame, telemetry, events):
|
||||
print("Samples:", len(frame), "TEL:", len(telemetry))
|
||||
print("Span:", frame.timestamp.min(), frame.timestamp.max())
|
||||
for name in ("adc_clipped", "near_current_rail", "setup", "invalid_polarity"):
|
||||
print(name, int(frame[name].sum()))
|
||||
print("First rail:", frame.loc[frame.adc_clipped, "timestamp"].min())
|
||||
columns = ["c_signed", "isc_observed_A", "voc_V", "irradiance_W_m2", "aperture_efficiency_pct", "responsivity_A_m2_W"]
|
||||
print(frame.set_index("timestamp")[columns].resample("15min").median().to_string())
|
||||
gaps = frame.timestamp.diff().dt.total_seconds()
|
||||
print("GAPS >15 s:")
|
||||
print(frame.loc[gaps > 15, ["timestamp", "uptime_s", "source_line"]].assign(gap_s=gaps[gaps > 15]).to_string(index=False))
|
||||
print("EVENTS:")
|
||||
print(events.loc[events.message.str.contains("CLOUD|Standby|F5|Auto-arranque")].to_string(index=False))
|
||||
resets = telemetry.uptime_s.diff() < 0
|
||||
print("TEL resets:", telemetry.loc[resets].to_string(index=False))
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--inspect", action="store_true")
|
||||
args = parser.parse_args()
|
||||
frame, telemetry, events = parse_log(SOURCE)
|
||||
frame = calibrate(frame)
|
||||
if args.inspect:
|
||||
inspect(frame, telemetry, events)
|
||||
return
|
||||
frame, metrics, reference, sensitivity = calculate(frame, telemetry, events)
|
||||
info = write_outputs(frame, telemetry, events, metrics, reference, sensitivity)
|
||||
figures(frame, metrics, reference)
|
||||
write_report(frame, metrics, info)
|
||||
columns = ["accepted_illuminated_samples", "integrated_duration_h", "estimated_energy_Wh",
|
||||
"energy_weighted_aperture_efficiency_pct", "empirical_tracking_efficiency_pct"]
|
||||
print(pd.DataFrame(metrics).T[columns].to_string())
|
||||
print("Outputs:", OUT)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,698 @@
|
||||
"""Reproducible read-and-report analysis of the 4 November 2026 field log."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import re
|
||||
import sys
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
import matplotlib
|
||||
|
||||
matplotlib.use("Agg")
|
||||
import matplotlib.dates as mdates
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
|
||||
BASE = Path(__file__).resolve().parent
|
||||
SOURCE = BASE / "logs_nuevos" / "log_2026-11-04.txt"
|
||||
SUNCALC_SOURCE = BASE / "logs_nuevos" / "suncalc_log_2026-11-04.pdf"
|
||||
OUT = BASE / "figures" / "2026-11-04"
|
||||
RESULT_TEX = BASE / "articulo" / "results_2026_11_04.tex"
|
||||
METRICS_TEX = BASE / "articulo" / "metrics_2026_11_04.tex"
|
||||
|
||||
ADC_MAX = 8_388_607
|
||||
VREF_V = 2.048
|
||||
CURRENT_GAIN = 20.0
|
||||
SHUNT_OHM = 0.130
|
||||
PYRANOMETER_MV_PER_W_M2 = 0.2
|
||||
APERTURE_M2 = 0.002497
|
||||
FILL_FACTOR = 0.82
|
||||
MAX_GAP_S = 15.0
|
||||
MIN_IRRADIANCE_W_M2 = 50.0
|
||||
SAMPLE_RE = re.compile(
|
||||
r"LOG:\[(?P<timestamp>[^\]]+)\] X:(?P<x>-?\d+),Y:(?P<y>-?\d+),"
|
||||
r"C:(?P<c>-?\d+),V:(?P<v>-?\d+),P:(?P<p>-?\d+),"
|
||||
r"S:(?P<uptime>\d+),er:(?P<error>\d+)"
|
||||
)
|
||||
TEL_RE = re.compile(
|
||||
r"LOG:\[(?P<timestamp>[^\]]+)\] TEL: t=(?P<uptime>\d+)s, "
|
||||
r"steps=(?P<steps>\d+)\(\+?(?P<delta>\d+)\)"
|
||||
)
|
||||
EVENT_RE = re.compile(r"LOG:\[(?P<timestamp>[^\]]+)\] (?P<message>.*)")
|
||||
|
||||
# Exact 15-minute values transcribed from the supplied SunCalc PDF.
|
||||
SUNCALC_ROWS = [
|
||||
("07:00",106.87,.82),("07:15",108.31,3.91),("07:30",109.82,7.12),("07:45",111.41,10.34),
|
||||
("08:00",113.08,13.54),("08:15",114.86,16.70),("08:30",116.76,19.83),("08:45",118.80,22.90),
|
||||
("09:00",120.98,25.91),("09:15",123.34,28.85),("09:30",125.90,31.71),("09:45",128.67,34.47),
|
||||
("10:00",131.69,37.13),("10:15",134.98,39.66),("10:30",138.57,42.04),("10:45",142.49,44.24),
|
||||
("11:00",146.75,46.26),("11:15",151.37,48.04),("11:30",156.34,49.57),("11:45",161.64,50.82),
|
||||
("12:00",167.22,51.75),("12:15",173.01,52.35),("12:30",178.93,52.59),("12:45",184.86,52.47),
|
||||
("13:00",190.71,51.99),("13:15",196.37,51.18),("13:30",201.77,50.04),("13:45",206.86,48.60),
|
||||
("14:00",211.60,46.90),("14:15",215.98,44.96),("14:30",220.01,42.81),("14:45",223.71,40.49),
|
||||
("15:00",227.10,38.01),("15:15",230.21,35.40),("15:30",233.06,32.67),("15:45",235.69,29.84),
|
||||
("16:00",238.11,26.93),("16:15",240.35,23.94),("16:30",242.43,20.89),("16:45",244.37,17.78),
|
||||
("17:00",246.18,14.63),("17:15",247.89,11.44),("17:30",249.50,8.23),("17:45",251.03,5.01),
|
||||
("18:00",252.49,1.85),("18:15",253.88,-1.05),
|
||||
]
|
||||
|
||||
|
||||
def signed24(value: int) -> int:
|
||||
value &= 0xFFFFFF
|
||||
return value - 0x1000000 if value & 0x800000 else value
|
||||
|
||||
|
||||
def parse_log(path: Path = SOURCE):
|
||||
samples, telemetry, events = [], [], []
|
||||
raw = path.read_bytes()
|
||||
for line_number, line in enumerate(raw.decode("utf-8-sig").splitlines(), 1):
|
||||
match = SAMPLE_RE.search(line)
|
||||
if match:
|
||||
d = match.groupdict()
|
||||
samples.append({
|
||||
"timestamp": pd.Timestamp(d["timestamp"]),
|
||||
"x_steps": int(d["x"]), "y_steps": int(d["y"]),
|
||||
"c_raw": int(d["c"]), "v_raw": int(d["v"]), "p_raw": int(d["p"]),
|
||||
"uptime_s": int(d["uptime"]), "error": int(d["error"]),
|
||||
"source_line": line_number,
|
||||
})
|
||||
continue
|
||||
match = TEL_RE.search(line)
|
||||
if match:
|
||||
d = match.groupdict()
|
||||
telemetry.append({"timestamp": pd.Timestamp(d["timestamp"]),
|
||||
"uptime_s": int(d["uptime"]), "steps": int(d["steps"]),
|
||||
"delta": int(d["delta"]), "source_line": line_number})
|
||||
continue
|
||||
match = EVENT_RE.search(line)
|
||||
if match:
|
||||
events.append({"timestamp": pd.Timestamp(match["timestamp"]),
|
||||
"message": match["message"], "source_line": line_number})
|
||||
frame = pd.DataFrame(samples)
|
||||
if frame.empty or not frame.timestamp.is_monotonic_increasing:
|
||||
raise ValueError("No electrical samples or non-monotonic source timestamps")
|
||||
frame.attrs["firmware_versions"] = sorted(set(re.findall(r"VER:([\w.-]+)", raw.decode("utf-8-sig"))))
|
||||
return frame, pd.DataFrame(telemetry), pd.DataFrame(events), hashlib.sha256(raw).hexdigest()
|
||||
|
||||
|
||||
def calibrate(frame: pd.DataFrame, fill_factor: float = FILL_FACTOR) -> pd.DataFrame:
|
||||
if not 0 < fill_factor <= 1:
|
||||
raise ValueError("Fill factor must be in (0, 1]")
|
||||
result = frame.copy()
|
||||
for raw_col, signed_col in (("c_raw", "c_signed"), ("v_raw", "v_signed"), ("p_raw", "p_signed")):
|
||||
result[signed_col] = result[raw_col].map(signed24)
|
||||
result["isc_A"] = result.c_signed / ADC_MAX * VREF_V / CURRENT_GAIN / SHUNT_OHM
|
||||
result["voc_V"] = result.v_signed / ADC_MAX * VREF_V * 2
|
||||
result["irradiance_W_m2"] = result.p_signed / ADC_MAX * VREF_V * 1000 / PYRANOMETER_MV_PER_W_M2
|
||||
result["assumed_fill_factor"] = fill_factor
|
||||
result["adc_clipped"] = result[["c_signed", "v_signed", "p_signed"]].abs().ge(ADC_MAX).any(axis=1)
|
||||
result["near_current_rail"] = result.c_signed.abs().ge(0.99 * ADC_MAX)
|
||||
result["invalid_polarity"] = result[["c_signed", "v_signed", "p_signed"]].lt(0).any(axis=1)
|
||||
result["illuminated"] = result.irradiance_W_m2 > MIN_IRRADIANCE_W_M2
|
||||
result["accepted"] = ~(result.adc_clipped | result.near_current_rail | result.invalid_polarity)
|
||||
result["quality_flag"] = np.select(
|
||||
[result.adc_clipped, result.near_current_rail, result.invalid_polarity],
|
||||
["adc_clipped", "near_current_rail", "invalid_polarity"], default="accepted")
|
||||
result["estimated_mpp_W"] = (result.isc_A * result.voc_V * fill_factor).where(result.accepted)
|
||||
valid_response = result.accepted & result.illuminated
|
||||
result["instant_aperture_efficiency_pct"] = (
|
||||
100 * result.estimated_mpp_W / (APERTURE_M2 * result.irradiance_W_m2)
|
||||
).where(valid_response)
|
||||
result["responsivity_A_m2_W"] = (result.isc_A / result.irradiance_W_m2).where(valid_response)
|
||||
return result
|
||||
|
||||
|
||||
def accepted_edges(frame: pd.DataFrame, selected=None, max_gap_s: float = MAX_GAP_S):
|
||||
"""Return a boolean mask for adjacent accepted sample pairs only."""
|
||||
n = len(frame)
|
||||
keep = np.ones(n, dtype=bool) if selected is None else np.asarray(selected, dtype=bool)
|
||||
dt = frame.timestamp.diff().dt.total_seconds().to_numpy()
|
||||
reboot = frame.uptime_s.diff().lt(0).to_numpy()
|
||||
edge = np.zeros(n, dtype=bool)
|
||||
edge[1:] = (keep[1:] & keep[:-1] & frame.accepted.to_numpy()[1:] & frame.accepted.to_numpy()[:-1]
|
||||
& frame.illuminated.to_numpy()[1:] & frame.illuminated.to_numpy()[:-1]
|
||||
& (dt[1:] > 0) & (dt[1:] <= max_gap_s) & ~reboot[1:])
|
||||
return edge
|
||||
|
||||
|
||||
def integrate_edges(frame: pd.DataFrame, values, edge_mask) -> float:
|
||||
values = np.asarray(values, dtype=float)
|
||||
seconds = frame.timestamp.diff().dt.total_seconds().to_numpy()
|
||||
right = np.flatnonzero(edge_mask)
|
||||
left = right - 1
|
||||
return float(np.sum((values[left] + values[right]) * 0.5 * seconds[right]) / 3600)
|
||||
|
||||
|
||||
def metrics(frame: pd.DataFrame, start=None, end=None, max_gap_s=MAX_GAP_S):
|
||||
t = frame.timestamp
|
||||
selected = np.ones(len(frame), dtype=bool)
|
||||
if start is not None:
|
||||
selected &= (t >= pd.Timestamp(start)).to_numpy()
|
||||
if end is not None:
|
||||
selected &= (t < pd.Timestamp(end)).to_numpy()
|
||||
edges = accepted_edges(frame, selected, max_gap_s)
|
||||
accepted = selected & frame.accepted.to_numpy() & frame.illuminated.to_numpy()
|
||||
obs = frame.loc[accepted]
|
||||
support_s = float(frame.timestamp.diff().dt.total_seconds().to_numpy()[edges].sum())
|
||||
elapsed_s = ((min(t.max(), pd.Timestamp(end)) if end is not None else t.max()) -
|
||||
(max(t.min(), pd.Timestamp(start)) if start is not None else t.min())).total_seconds()
|
||||
energy = integrate_edges(frame, frame.estimated_mpp_W, edges)
|
||||
irradiation = integrate_edges(frame, frame.irradiance_W_m2, edges)
|
||||
ref_resp = float(frame.loc[frame.accepted & frame.illuminated, "responsivity_A_m2_W"].max())
|
||||
p99_resp = float(frame.loc[frame.accepted & frame.illuminated, "responsivity_A_m2_W"].quantile(.99))
|
||||
# Reference powers use observed Voc and the same common irradiance support.
|
||||
max_ref_power = ref_resp * frame.irradiance_W_m2 * frame.voc_V * frame.assumed_fill_factor
|
||||
p99_ref_power = p99_resp * frame.irradiance_W_m2 * frame.voc_V * frame.assumed_fill_factor
|
||||
max_ref_energy = integrate_edges(frame, max_ref_power, edges)
|
||||
p99_ref_energy = integrate_edges(frame, p99_ref_power, edges)
|
||||
peak = obs.loc[obs.estimated_mpp_W.idxmax()] if not obs.empty else None
|
||||
peak_isc = obs.loc[obs.isc_A.idxmax()] if not obs.empty else None
|
||||
peak_g = obs.loc[obs.irradiance_W_m2.idxmax()] if not obs.empty else None
|
||||
si_19 = irradiation * APERTURE_M2 * .19
|
||||
si_21 = irradiation * APERTURE_M2 * .21
|
||||
return {
|
||||
"start": str(obs.timestamp.min()) if not obs.empty else "",
|
||||
"end": str(obs.timestamp.max()) if not obs.empty else "",
|
||||
"sample_count": int(selected.sum()), "accepted_illuminated_samples": int(accepted.sum()),
|
||||
"integrated_intervals": int(edges.sum()), "elapsed_span_h": elapsed_s / 3600,
|
||||
"integrated_support_h": support_s / 3600,
|
||||
"coverage_pct": 100 * support_s / elapsed_s if elapsed_s > 0 else float("nan"),
|
||||
"irradiation_Wh_m2": irradiation, "incident_aperture_energy_Wh": irradiation * APERTURE_M2,
|
||||
"estimated_mpp_energy_Wh": energy,
|
||||
"energy_weighted_aperture_efficiency_pct": 100 * energy / (APERTURE_M2 * irradiation) if irradiation else float("nan"),
|
||||
"median_instant_aperture_efficiency_pct": float(obs.instant_aperture_efficiency_pct.median()) if not obs.empty else float("nan"),
|
||||
"peak_instant_aperture_efficiency_pct": float(obs.instant_aperture_efficiency_pct.max()) if not obs.empty else float("nan"),
|
||||
"empirical_max_reference_A_m2_W": ref_resp, "empirical_p99_reference_A_m2_W": p99_resp,
|
||||
"max_reference_ratio_pct": 100 * energy / max_ref_energy if max_ref_energy else float("nan"),
|
||||
"p99_reference_ratio_pct": 100 * energy / p99_ref_energy if p99_ref_energy else float("nan"),
|
||||
"silicon_19_energy_Wh": si_19, "silicon_21_energy_Wh": si_21,
|
||||
"cpv_to_silicon_19_ratio_pct": 100 * energy / si_19 if si_19 else float("nan"),
|
||||
"cpv_to_silicon_21_ratio_pct": 100 * energy / si_21 if si_21 else float("nan"),
|
||||
"peak_power_timestamp": str(peak.timestamp) if peak is not None else "",
|
||||
"peak_power_W": float(peak.estimated_mpp_W) if peak is not None else float("nan"),
|
||||
"aperture_efficiency_at_peak_power_pct": float(peak.instant_aperture_efficiency_pct) if peak is not None else float("nan"),
|
||||
"peak_power_isc_A": float(peak.isc_A) if peak is not None else float("nan"),
|
||||
"peak_power_voc_V": float(peak.voc_V) if peak is not None else float("nan"),
|
||||
"peak_power_irradiance_W_m2": float(peak.irradiance_W_m2) if peak is not None else float("nan"),
|
||||
"peak_isc_timestamp": str(peak_isc.timestamp) if peak_isc is not None else "",
|
||||
"peak_isc_A": float(peak_isc.isc_A) if peak_isc is not None else float("nan"),
|
||||
"peak_irradiance_timestamp": str(peak_g.timestamp) if peak_g is not None else "",
|
||||
"peak_irradiance_W_m2": float(peak_g.irradiance_W_m2) if peak_g is not None else float("nan"),
|
||||
}
|
||||
|
||||
|
||||
def suncalc_frame():
|
||||
day = pd.Timestamp("2026-11-04")
|
||||
return pd.DataFrame([{"timestamp": day + pd.Timedelta(hours=int(t[:2]), minutes=int(t[3:])),
|
||||
"azimuth_deg": az, "solar_elevation_deg": el,
|
||||
"latitude_deg": 21.87304, "longitude_deg": -102.28282,
|
||||
"source": "SunCalc PDF, printed local time; 2026-11-04"}
|
||||
for t, az, el in SUNCALC_ROWS])
|
||||
|
||||
|
||||
def make_events(events: pd.DataFrame, frame: pd.DataFrame, telemetry: pd.DataFrame):
|
||||
relevant = events[events.message.str.contains(
|
||||
r"\[CLOUD\]|F1:|F5:|Standby|Auto-arranque|Ejecutando comando|VER:", regex=True, na=False)].copy()
|
||||
relevant["event_type"] = np.select(
|
||||
[relevant.message.str.contains("Set Coords", na=False),
|
||||
relevant.message.str.contains("[CLOUD]", regex=False, na=False),
|
||||
relevant.message.str.contains(r"F1:|F5:", regex=True, na=False)],
|
||||
["manual_coordinate_command", "remote_parameter_or_status_command", "controller_event"], default="logged_event")
|
||||
# Add algorithmic gaps with exact endpoints and source-line references.
|
||||
dt = frame.timestamp.diff().dt.total_seconds()
|
||||
gaps = []
|
||||
for i in np.flatnonzero(dt.to_numpy() > MAX_GAP_S):
|
||||
gaps.append({"timestamp": frame.timestamp.iloc[i], "message": f"Sampling gap: {dt.iloc[i]:.0f} s; no bridge in integration",
|
||||
"source_line": int(frame.source_line.iloc[i]), "event_type": "sampling_gap",
|
||||
"previous_source_line": int(frame.source_line.iloc[i - 1]),
|
||||
"uptime_decreased": bool(frame.uptime_s.iloc[i] < frame.uptime_s.iloc[i - 1])})
|
||||
if not telemetry.empty:
|
||||
tel_dt = telemetry.timestamp.diff().dt.total_seconds()
|
||||
for i in np.flatnonzero(tel_dt.to_numpy() > MAX_GAP_S):
|
||||
gaps.append({"timestamp": telemetry.timestamp.iloc[i], "message": f"TEL telemetry gap: {tel_dt.iloc[i]:.0f} s",
|
||||
"source_line": int(telemetry.source_line.iloc[i]), "event_type": "tel_sampling_gap",
|
||||
"previous_source_line": int(telemetry.source_line.iloc[i - 1]),
|
||||
"uptime_decreased": bool(telemetry.uptime_s.iloc[i] < telemetry.uptime_s.iloc[i - 1])})
|
||||
for i in np.flatnonzero(telemetry.uptime_s.diff().lt(0).to_numpy()):
|
||||
gaps.append({"timestamp": telemetry.timestamp.iloc[i], "message": "TEL uptime decreased",
|
||||
"source_line": int(telemetry.source_line.iloc[i]), "event_type": "tel_uptime_decrease",
|
||||
"previous_source_line": int(telemetry.source_line.iloc[i - 1]),
|
||||
"uptime_decreased": True})
|
||||
relevant = relevant.assign(previous_source_line=np.nan, uptime_decreased=np.nan)
|
||||
return pd.concat([relevant, pd.DataFrame(gaps)], ignore_index=True, sort=False).sort_values("timestamp")
|
||||
|
||||
|
||||
def add_solar_context(frame: pd.DataFrame, sun: pd.DataFrame):
|
||||
# Linear interpolation is only for plotting context; no extrapolation outside table.
|
||||
result = frame.copy()
|
||||
x = sun.timestamp.astype("int64").to_numpy()
|
||||
tq = result.timestamp.astype("int64").to_numpy()
|
||||
for col in ("azimuth_deg", "solar_elevation_deg"):
|
||||
result[col] = np.interp(tq, x, sun[col].to_numpy(), left=np.nan, right=np.nan)
|
||||
result.loc[(tq < x[0]) | (tq > x[-1]), col] = np.nan
|
||||
return result
|
||||
|
||||
|
||||
def gap_breaks(frame):
|
||||
dt = frame.timestamp.diff().dt.total_seconds().to_numpy()
|
||||
return np.r_[False, (dt[1:] > MAX_GAP_S)] | ~frame.accepted.to_numpy()
|
||||
|
||||
|
||||
def plot_outputs(frame, events, sun, summary):
|
||||
OUT.mkdir(parents=True, exist_ok=True)
|
||||
plt.rcParams.update({"font.family": "DejaVu Sans", "font.size": 9,
|
||||
"axes.spines.top": False, "axes.spines.right": False,
|
||||
"pdf.fonttype": 42, "ps.fonttype": 42})
|
||||
time = frame.timestamp
|
||||
breaks = gap_breaks(frame)
|
||||
fig, ax = plt.subplots(5, 1, figsize=(10, 10), sharex=True, layout="constrained")
|
||||
ax[0].plot(time, frame.irradiance_W_m2.mask(breaks), color="#d09128", lw=.65)
|
||||
ax[0].set_ylabel("Aperture-plane\nirradiance [W m$^{-2}$]")
|
||||
ax[1].plot(time, (1000 * frame.isc_A).mask(breaks), color="#167d8d", lw=.65)
|
||||
ax[1].set_ylabel("Short-circuit\ncurrent [mA]")
|
||||
ax[2].plot(time, frame.voc_V.mask(breaks), color="#7356a5", lw=.65)
|
||||
ax[2].set_ylabel("Open-circuit\nvoltage [V]")
|
||||
ax[3].plot(time, frame.estimated_mpp_W.mask(breaks), color="#167d8d", lw=.65, label="Estimated MPP power")
|
||||
ax[3].set_ylabel("Estimated power\n[W]")
|
||||
ax2 = ax[3].twinx(); ax2.plot(time, frame.instant_aperture_efficiency_pct.mask(breaks), color="#27824e", lw=.55, alpha=.8)
|
||||
ax2.set_ylabel("Aperture estimate [%]", color="#27824e")
|
||||
ax[4].plot(time, frame.x_steps.mask(breaks), color="#285b9a", lw=.6, label="X (azimuth axis)")
|
||||
ax[4].plot(time, frame.y_steps.mask(breaks), color="#c05b43", lw=.6, label="Y (elevation axis)")
|
||||
ax[4].set_ylabel("Logged coordinate\n[steps]"); ax[4].legend(ncol=2, frameon=False)
|
||||
for a in ax:
|
||||
a.grid(alpha=.2); a.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M"))
|
||||
for g in pd.to_datetime(summary["gap_starts"]): a.axvline(g, color="#555555", lw=.6, ls=":", alpha=.6)
|
||||
for ts in pd.to_datetime(summary["command_times"]):
|
||||
for a in ax: a.axvline(ts, color="#ad3e38", lw=.55, ls="--", alpha=.5)
|
||||
ax[-1].set_xlabel("Local log clock (time-zone offset not encoded)")
|
||||
fig.suptitle("4 November 2026 field record: complete acquired span", x=.02, ha="left", fontsize=12)
|
||||
save_figure(fig, "field_day_overview")
|
||||
|
||||
fig, ax = plt.subplots(2, 1, figsize=(9, 6), sharex=True, layout="constrained")
|
||||
ax[0].plot(sun.timestamp, sun.azimuth_deg, "o-", color="#3468a8", ms=2.5, lw=1)
|
||||
ax[0].set_ylabel("Sun azimuth [deg]")
|
||||
ax[1].plot(sun.timestamp, sun.solar_elevation_deg, "o-", color="#d27c25", ms=2.5, lw=1)
|
||||
ax[1].set_ylabel("Solar elevation [deg]"); ax[1].set_xlabel("SunCalc printed local time (15-min entries)")
|
||||
for a in ax:
|
||||
a.axvspan(frame.timestamp.min(), frame.timestamp.max(), color="#555555", alpha=.08, label="Acquired interval")
|
||||
a.grid(alpha=.2); a.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M"))
|
||||
ax[0].set_title("SunCalc context, Aguascalientes (21.87304° N, 102.28282° W)", loc="left")
|
||||
fig.text(.01, -.01, "Solar direction is not measured receiver pointing error or collector incidence.", fontsize=8)
|
||||
save_figure(fig, "solar_position_context")
|
||||
|
||||
ctx = add_solar_context(frame, sun)
|
||||
colors = plt.colormaps["viridis"].with_extremes(over="#ad3e38")
|
||||
color_limit = summary["reference_p99"] * 1e3
|
||||
fig, ax = plt.subplots(2, 1, figsize=(10, 7), sharex=True, layout="constrained")
|
||||
sc = ax[0].scatter(ctx.timestamp, ctx.azimuth_deg, c=ctx.responsivity_A_m2_W * 1e3,
|
||||
cmap=colors, vmin=0, vmax=color_limit, s=7, rasterized=True)
|
||||
ax[0].set_ylabel("Sun azimuth [deg]")
|
||||
cb = fig.colorbar(sc, ax=ax, pad=.01, extend="max"); cb.set_label("$I_{sc}/G$ [mA m$^2$ W$^{-1}$]")
|
||||
ax[1].scatter(ctx.timestamp, ctx.solar_elevation_deg, c=ctx.responsivity_A_m2_W * 1e3,
|
||||
cmap=colors, vmin=0, vmax=color_limit, s=7, rasterized=True)
|
||||
ax[1].set_ylabel("Solar elevation [deg]"); ax[1].set_xlabel("Local log clock; SunCalc values linearly interpolated")
|
||||
for a in ax:
|
||||
a.grid(alpha=.2); a.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M"))
|
||||
ax[0].set_title("Solar position and measured normalized response", loc="left")
|
||||
fig.text(.01, -.01, "Ephemeris context only; not angular error. Red values exceed the P99 color scale; observations are retained.", fontsize=8)
|
||||
save_figure(fig, "solar_response_alignment")
|
||||
|
||||
fig, ax = plt.subplots(2, 1, figsize=(9, 6), sharex=True, layout="constrained")
|
||||
response = frame.responsivity_A_m2_W * 1e3
|
||||
ax[0].plot(time, response.mask(breaks), color="#285b9a", lw=.65, label="$I_{sc}/G$")
|
||||
max_ref = summary["reference_max"] * 1e3; p99_ref = summary["reference_p99"] * 1e3
|
||||
for a in ax:
|
||||
a.axhline(max_ref, color="#b53d35", ls="--", lw=1, label="Full-record maximum reference")
|
||||
a.axhline(p99_ref, color="#27824e", ls="--", lw=1, label="Full-record P99 sensitivity")
|
||||
ax[1].plot(time, response.mask(breaks), color="#285b9a", lw=.65)
|
||||
anomaly = summary["anomaly_time"]
|
||||
ax[0].scatter([pd.Timestamp(anomaly)], [summary["anomaly_resp"] * 1e3], color="#b53d35", zorder=4, s=28)
|
||||
ax[0].set_ylim(0, max_ref * 1.08); ax[1].set_ylim(0, p99_ref * 1.35)
|
||||
ax[0].set_ylabel("Full range\n[mA m$^2$ W$^{-1}$]")
|
||||
ax[1].set_ylabel("Typical range\n[mA m$^2$ W$^{-1}$]"); ax[1].set_xlabel("Local log clock")
|
||||
ax[0].set_title("Irradiance-normalized response; full record retained", loc="left")
|
||||
for a in ax:
|
||||
for g in pd.to_datetime(summary["gap_starts"]): a.axvline(g, color="#555", lw=.6, ls=":")
|
||||
a.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M")); a.grid(alpha=.2)
|
||||
ax[0].legend(frameon=False, ncol=2, fontsize=8)
|
||||
save_figure(fig, "response_reference_sensitivity")
|
||||
|
||||
fig, ax = plt.subplots(figsize=(8, 5), layout="constrained")
|
||||
labels = ["WiT-CPV estimated\nFF-based output", "Silicon scenario\n19% constant", "Silicon scenario\n21% constant"]
|
||||
vals = [summary["full"]["estimated_mpp_energy_Wh"], summary["full"]["silicon_19_energy_Wh"], summary["full"]["silicon_21_energy_Wh"]]
|
||||
colors = ["#167d8d", "#8798aa", "#b0bac5"]
|
||||
bars = ax.bar(labels, vals, color=colors, width=.62)
|
||||
ax.bar_label(bars, fmt="%.2f Wh", padding=3)
|
||||
ax.set_ylabel("Integrated scenario energy [Wh]"); ax.set_ylim(0, max(vals) * 1.2)
|
||||
ax.set_title("Equal-area scenarios in the measured aperture plane", loc="left")
|
||||
ax.text(.02, .96, "A = 0.002497 m²; coplanar irradiance; constant ηSi.\nNo temperature correction; not a measured panel comparison.",
|
||||
transform=ax.transAxes, va="top", fontsize=8)
|
||||
ax.grid(axis="y", alpha=.2)
|
||||
save_figure(fig, "fixed_silicon_scenario")
|
||||
|
||||
|
||||
def save_figure(fig, stem):
|
||||
fig.savefig(OUT / f"{stem}.pdf", bbox_inches="tight")
|
||||
fig.savefig(OUT / f"{stem}.png", dpi=220, bbox_inches="tight")
|
||||
plt.close(fig)
|
||||
|
||||
|
||||
def write_result_tex(summary, gap_text):
|
||||
m = summary["full"]
|
||||
macros = {
|
||||
"NovSamples": f"{summary['sample_count']:,}".replace(",", "{,}"),
|
||||
"NovHours": f"{m['integrated_support_h']:.3f}",
|
||||
"NovEnergy": f"{m['estimated_mpp_energy_Wh']:.3f}",
|
||||
"NovIrradiation": f"{m['irradiation_Wh_m2'] / 1000:.3f}",
|
||||
"NovEfficiency": f"{m['energy_weighted_aperture_efficiency_pct']:.2f}",
|
||||
"NovPeakPower": f"{m['peak_power_W']:.3f}",
|
||||
"NovApertureAtPeakPower": f"{m['aperture_efficiency_at_peak_power_pct']:.2f}",
|
||||
"NovPeakCurrent": f"{m['peak_power_isc_A'] * 1000:.1f}",
|
||||
"NovPeakVoltage": f"{m['peak_power_voc_V']:.3f}",
|
||||
"NovPeakIrradiance": f"{m['peak_power_irradiance_W_m2']:.1f}",
|
||||
"NovRelativeMax": f"{m['max_reference_ratio_pct']:.2f}",
|
||||
"NovRelativePercentile": f"{m['p99_reference_ratio_pct']:.2f}",
|
||||
"NovSiliconStandardRatio": f"{m['cpv_to_silicon_19_ratio_pct'] / 100:.3f}",
|
||||
"NovSiliconPremiumRatio": f"{m['cpv_to_silicon_21_ratio_pct'] / 100:.3f}",
|
||||
"NovSteadyEfficiency": f"{summary['phases'][2]['energy_weighted_aperture_efficiency_pct']:.2f}",
|
||||
}
|
||||
METRICS_TEX.write_text(
|
||||
"% Generated by analyze_2026_11_04.py.\n" + "\n".join(
|
||||
"\\newcommand{\\" + name + "}{" + value + "}" for name, value in macros.items()
|
||||
) + "\n", encoding="utf-8")
|
||||
tex = rf"""% Generated by analyze_2026_11_04.py; do not hand-edit numerical values.
|
||||
\subsection{{Acquisition coverage and operating chronology}}
|
||||
|
||||
The acquired span is 09:52:50--16:05:13, comprising \NovSamples{{}}
|
||||
electrical/coordinate observations and {summary['tel_records']:,} separate
|
||||
telemetry messages. All main observations pass the ADC quality checks and
|
||||
exceed the analysis illumination threshold. There are no duplicate main
|
||||
timestamps or decreasing main-sample uptimes. Five gaps exceed 15~s:
|
||||
{gap_text}. Excluding these gaps gives \NovHours{{}}~h of integration
|
||||
support out of {m['elapsed_span_h']:.3f}~h elapsed, or {m['coverage_pct']:.2f}\%
|
||||
coverage. The audit retains every acquired observation; no clipped samples
|
||||
or unobserved intervals are reconstructed.
|
||||
|
||||
The complete overview in Fig.~\ref{{fig:nov04_overview}} connects electrical
|
||||
response with stage motion. There are {summary['cloud_commands']} logged remote
|
||||
commands, including early tuning and repositioning. For example,
|
||||
\texttt{{Delay=4}} was logged at 12:27:20, before the 12:32 boundary. Three event boundaries
|
||||
divide the record without selecting a favorable performance threshold:
|
||||
\texttt{{ErrMax=1100}} at 12:32:02, \texttt{{ErrMax=1000}} at 13:53:00,
|
||||
and the first late manual-coordinate command at 15:12:42. All four sequential
|
||||
phases are retained in Table~\ref{{tab:nov04_phases}}. No additional remote
|
||||
commands are recorded inside the 12:32--13:53 phase; periodic controller
|
||||
reference resets continue. This is an interval without logged operator
|
||||
interventions, not a controlled comparison of firmware or settings.
|
||||
|
||||
\subsection{{Electrical output and aperture estimate}}
|
||||
|
||||
Applying Eqs.~\eqref{{eq:power_estimate}}--\eqref{{eq:aperture}} over the
|
||||
complete accepted support yields \NovEnergy{{}}~Wh of estimated available-MPP
|
||||
energy from \NovIrradiation{{}}~kWh\,m$^{{-2}}$ of measured aperture-plane irradiation,
|
||||
with an energy-weighted aperture estimate of \NovEfficiency\%.
|
||||
Table~\ref{{tab:nov04_hourly}} shows every acquired clock-hour bin, including
|
||||
the initial low response and late decline, rather than replacing the complete
|
||||
record with a midday-only integral.
|
||||
|
||||
At the maximum of the power estimate ({m['peak_power_timestamp']}), the
|
||||
sequentially recorded values in that observation were
|
||||
$I_{{sc}}={m['peak_power_isc_A']*1000:.1f}$ mA,
|
||||
$V_{{oc}}={m['peak_power_voc_V']:.3f}$ V and $G={m['peak_power_irradiance_W_m2']:.1f}$ W m$^{{-2}}$,
|
||||
giving {m['peak_power_W']:.3f}~W estimated output and an instantaneous aperture
|
||||
estimate of \NovApertureAtPeakPower\% at that observation. Separate maxima are not combined
|
||||
into a synthetic operating point. The 12:32--13:53 phase contributes
|
||||
{summary['phases'][2]['estimated_mpp_energy_Wh']:.3f}~Wh over
|
||||
{summary['phases'][2]['integrated_support_h']:.3f}~h, with an aperture estimate
|
||||
of \NovSteadyEfficiency\%. The 15:00--16:00 clock-hour estimate falls to
|
||||
{summary['hourly'][6]['energy_weighted_aperture_efficiency_pct']:.2f}\%, and
|
||||
the phase after the first 15:12 manual command gives
|
||||
{summary['phases'][4]['energy_weighted_aperture_efficiency_pct']:.2f}\%.
|
||||
The record shows deterioration before and after that command, not evidence
|
||||
that the command alone caused it.
|
||||
|
||||
\begin{{table}}[htbp]
|
||||
\centering\small
|
||||
\caption{{Complete acquisition and fixed clock-hour summaries. $H$ is aperture-plane
|
||||
irradiation, $\widehat E$ is FF-based available energy and
|
||||
$\widehat\eta_{{\mathrm{{ap}},E}}$ is the energy-weighted aperture estimate.
|
||||
Bins contain only acquired observations. Both edge endpoints must lie inside a
|
||||
bin, so subdivided integrals omit boundary-crossing edges and need not sum
|
||||
exactly to the full-record integral.}}
|
||||
\label{{tab:nov04_hourly}}
|
||||
\begin{{tabular}}{{lrrrrr}}
|
||||
\toprule
|
||||
Window & $N$ & Support [h] & $H$ [kWh\,m$^{{-2}}$] & $\widehat E$ [Wh] & $\widehat\eta_{{\mathrm{{ap}},E}}$ [\%] \\
|
||||
\midrule
|
||||
{summary['table_rows']}
|
||||
\bottomrule
|
||||
\end{{tabular}}
|
||||
\end{{table}}
|
||||
|
||||
\begin{{table}}[htbp]
|
||||
\centering\small
|
||||
\caption{{All sequential event-defined phases. Internal command boundaries
|
||||
belong to the following phase; the final acquired sample is retained.
|
||||
As in Table~\ref{{tab:nov04_hourly}},
|
||||
edges crossing a boundary are omitted. Phases describe operation; they are not
|
||||
matched experimental treatments.}}
|
||||
\label{{tab:nov04_phases}}
|
||||
\begin{{tabular}}{{lrrrr}}
|
||||
\toprule
|
||||
Phase boundary clocks & $N$ & Support [h] & $\widehat E$ [Wh] & $\widehat\eta_{{\mathrm{{ap}},E}}$ [\%] \\
|
||||
\midrule
|
||||
{summary['phase_table_rows']}
|
||||
\bottomrule
|
||||
\end{{tabular}}
|
||||
\end{{table}}
|
||||
|
||||
\subsection{{Relative response and solar-position context}}
|
||||
|
||||
An empirical same-record $I_{{sc}}/G$ reference is highly sensitive to one point:
|
||||
the maximum is {summary['reference_max']:.6f} A m$^2$ W$^{{-1}}$ at
|
||||
{summary['anomaly_time']}, where $G={summary['anomaly_G']:.1f}$ W m$^{{-2}}$ and
|
||||
$I_{{sc}}={summary['anomaly_I']*1000:.1f}$ mA; the P99 reference is
|
||||
{summary['reference_p99']:.6f} A m$^2$ W$^{{-1}}$. The anomalous sample is retained.
|
||||
In its four-minute neighborhood, median irradiance is
|
||||
{summary['anomaly_neighborhood']['irradiance_median']:.1f} W m$^{{-2}}$
|
||||
({summary['anomaly_neighborhood']['count']} samples), consistent with an isolated
|
||||
irradiance dip rather than sustained low irradiance; the cause remains unresolved.
|
||||
Across the accepted illuminated samples, median $I_{{sc}}/G$ is
|
||||
{summary['responsivity_distribution']['median']:.6f} A m$^2$ W$^{{-1}}$
|
||||
(interquartile range {summary['responsivity_distribution']['q25']:.6f}--
|
||||
{summary['responsivity_distribution']['q75']:.6f}).
|
||||
Full-record integrated relative-yield indicators are
|
||||
{m['max_reference_ratio_pct']:.1f}\% (maximum reference) and
|
||||
{m['p99_reference_ratio_pct']:.1f}\% (P99 sensitivity). These are internal,
|
||||
reference-dependent indicators rather than independently validated tracking
|
||||
efficiencies. Figure~\ref{{fig:nov04_response}} displays both the full
|
||||
responsivity range and a typical-range view; the anomalous observation remains
|
||||
in the analysis.
|
||||
|
||||
Interpolated SunCalc positions at the first and last observations are
|
||||
{summary['solar_context']['first_azimuth_deg']:.2f}$^\circ$ and
|
||||
{summary['solar_context']['last_azimuth_deg']:.2f}$^\circ$ azimuth, with elevations
|
||||
{summary['solar_context']['first_elevation_deg']:.2f}$^\circ$ and
|
||||
{summary['solar_context']['last_elevation_deg']:.2f}$^\circ$, respectively.
|
||||
The printed table reaches {summary['solar_context']['maximum_elevation_deg']:.2f}$^\circ$
|
||||
elevation at 12:30. Figure~\ref{{fig:nov04_solar_response}} relates this
|
||||
trajectory to the measured normalized response. Logged coordinates span
|
||||
$X={summary['coordinates']['x_min']:,}$--${summary['coordinates']['x_max']:,}$
|
||||
and $Y={summary['coordinates']['y_min']:,}$--${summary['coordinates']['y_max']:,}$
|
||||
steps. These are observed solar and coordinate ranges, not independently
|
||||
validated acceptance angles or rated mechanical limits.
|
||||
|
||||
\subsection{{Conditional fixed-silicon reference}}
|
||||
The coplanar, equal-area scenarios of Eq.~\eqref{{eq:silicon_scenario}}
|
||||
yield
|
||||
{m['silicon_19_energy_Wh']:.3f} and {m['silicon_21_energy_Wh']:.3f} Wh, respectively;
|
||||
the corresponding estimated-CPV-to-scenario ratios are
|
||||
\NovSiliconStandardRatio{{}} and \NovSiliconPremiumRatio{{}}.
|
||||
Figure~\ref{{fig:nov04_silicon}} illustrates these assumptions, not measured
|
||||
comparative yields. Changing the assumed CPV fill factor from 0.82 to 0.70 or
|
||||
0.90 would change the full-record energy estimate to
|
||||
{m['estimated_mpp_energy_Wh']*.70/FILL_FACTOR:.3f} or
|
||||
{m['estimated_mpp_energy_Wh']*.90/FILL_FACTOR:.3f}~Wh, respectively.
|
||||
This sensitivity range is illustrative, not a measured uncertainty interval.
|
||||
|
||||
\begin{{figure}}[htbp]\centering
|
||||
\includegraphics[width=0.98\linewidth]{{../figures/2026-11-04/field_day_overview.pdf}}
|
||||
\caption{{Complete 4 November acquisition. Vertical dotted lines mark sampling
|
||||
gaps; dashed lines mark the three selected phase-boundary commands. Raw trends are not smoothed, and gaps are
|
||||
not bridged. Electrical output is estimated using $FF=0.82$.}}
|
||||
\label{{fig:nov04_overview}}\end{{figure}}
|
||||
|
||||
\begin{{figure}}[htbp]\centering
|
||||
\includegraphics[width=0.92\linewidth]{{../figures/2026-11-04/solar_response_alignment.pdf}}
|
||||
\caption{{SunCalc azimuth/elevation context aligned to the measured response.
|
||||
SunCalc entries are spaced 15 minutes; intermediate positions are linearly
|
||||
interpolated for plotting. Color encodes $I_{{sc}}/G$, not pointing error;
|
||||
values above P99 remain plotted in the red over-range color.}}
|
||||
\label{{fig:nov04_solar_response}}\end{{figure}}
|
||||
|
||||
\begin{{figure}}[htbp]\centering
|
||||
\includegraphics[width=0.88\linewidth]{{../figures/2026-11-04/response_reference_sensitivity.pdf}}
|
||||
\caption{{Irradiance-normalized response for the full record. The maximum
|
||||
reference is dominated by a retained anomalous observation; P99 is shown only as
|
||||
a sensitivity analysis. Neither line is an independent ideal-tracking standard.}}
|
||||
\label{{fig:nov04_response}}\end{{figure}}
|
||||
|
||||
\begin{{figure}}[htbp]\centering
|
||||
\includegraphics[width=0.75\linewidth]{{../figures/2026-11-04/fixed_silicon_scenario.pdf}}
|
||||
\caption{{Conditional equal-area scenarios using the measured aperture-plane irradiance.
|
||||
Silicon efficiency is held constant at 19\% or 21\%; no panel,
|
||||
temperature correction or measured head-to-head comparison is represented.}}
|
||||
\label{{fig:nov04_silicon}}\end{{figure}}
|
||||
|
||||
"""
|
||||
RESULT_TEX.write_text(tex, encoding="utf-8")
|
||||
|
||||
|
||||
def run():
|
||||
frame, telemetry, events, source_hash = parse_log()
|
||||
frame = calibrate(frame)
|
||||
sun = suncalc_frame()
|
||||
frame = add_solar_context(frame, sun)
|
||||
frame["integrate_from_previous"] = accepted_edges(frame)
|
||||
frame["interval_from_previous_s"] = frame.timestamp.diff().dt.total_seconds()
|
||||
event_table = make_events(events, frame, telemetry)
|
||||
OUT.mkdir(parents=True, exist_ok=True)
|
||||
summary_full = metrics(frame)
|
||||
gaps = event_table[event_table.event_type == "sampling_gap"]
|
||||
commands = events[events.message.str.contains(r"\[CLOUD\]", regex=True, na=False)]
|
||||
# Phases use logged cut points, not a performance-selected window.
|
||||
milestones = []
|
||||
for message in ("[CLOUD] ErrMax=1100", "[CLOUD] ErrMax=1000",
|
||||
"[CLOUD] Set Coords X:115000, Y:79000"):
|
||||
matches = events.loc[events.message.eq(message)]
|
||||
if len(matches) != 1:
|
||||
raise ValueError(f"Expected exactly one phase-boundary event: {message}")
|
||||
milestones.append(matches.iloc[0])
|
||||
boundaries = [event.timestamp for event in milestones]
|
||||
end = frame.timestamp.max() + pd.Timedelta(seconds=1)
|
||||
phase_defs = [("Full acquired record", frame.timestamp.min(), end),
|
||||
("Initial tuning and repositioning", frame.timestamp.min(), boundaries[0]),
|
||||
("After 12:32 ErrMax update", boundaries[0], boundaries[1]),
|
||||
("After 13:53 ErrMax update", boundaries[1], boundaries[2]),
|
||||
("After 15:12 manual coordinates", boundaries[2], end)]
|
||||
rows = []
|
||||
for name, start, end in phase_defs:
|
||||
m = metrics(frame, start, end)
|
||||
m["window"] = name
|
||||
m["window_start"] = str(start)
|
||||
m["window_end"] = str(min(end, frame.timestamp.max()))
|
||||
rows.append(m)
|
||||
# Fixed clock-hour bins retain late-session deterioration and expose support.
|
||||
hourly = []
|
||||
for h in range(9, 17):
|
||||
start = pd.Timestamp(f"2026-11-04 {h:02d}:00:00")
|
||||
m = metrics(frame, start, start + pd.Timedelta(hours=1))
|
||||
m["window"] = f"{h:02d}:00--{h+1:02d}:00"
|
||||
hourly.append(m)
|
||||
# Common thresholds and gap policies are explicit sensitivity checks.
|
||||
sensitivity = []
|
||||
for gap_limit in (10, 15, 30, 60):
|
||||
for light_limit in (0, 50, 100):
|
||||
saved = frame["illuminated"].copy()
|
||||
frame["illuminated"] = frame.irradiance_W_m2 > light_limit
|
||||
m = metrics(frame, max_gap_s=gap_limit)
|
||||
sensitivity.append({"max_gap_s": gap_limit, "minimum_irradiance_W_m2": light_limit,
|
||||
"support_h": m["integrated_support_h"], "energy_Wh": m["estimated_mpp_energy_Wh"],
|
||||
"aperture_efficiency_pct": m["energy_weighted_aperture_efficiency_pct"]})
|
||||
frame["illuminated"] = saved
|
||||
reference = frame.loc[frame.accepted & frame.illuminated, "responsivity_A_m2_W"]
|
||||
anomaly_idx = frame.responsivity_A_m2_W.idxmax()
|
||||
anomaly = frame.loc[anomaly_idx]
|
||||
anomaly_neighbor = frame.loc[(frame.timestamp >= anomaly.timestamp - pd.Timedelta(minutes=2)) &
|
||||
(frame.timestamp <= anomaly.timestamp + pd.Timedelta(minutes=2))]
|
||||
anomaly_neighbor_stats = {"count": len(anomaly_neighbor), "irradiance_min": float(anomaly_neighbor.irradiance_W_m2.min()),
|
||||
"irradiance_median": float(anomaly_neighbor.irradiance_W_m2.median()),
|
||||
"irradiance_max": float(anomaly_neighbor.irradiance_W_m2.max()),
|
||||
"responsivity_median": float(anomaly_neighbor.responsivity_A_m2_W.median())}
|
||||
summary = {
|
||||
"source": str(SOURCE.relative_to(BASE)), "source_sha256": source_hash,
|
||||
"suncalc_source_sha256": hashlib.sha256(SUNCALC_SOURCE.read_bytes()).hexdigest(),
|
||||
"analysis_source_sha256": hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),
|
||||
"source_bytes": SOURCE.stat().st_size, "source_lines": len(SOURCE.read_text(encoding="utf-8-sig").splitlines()),
|
||||
"sample_count": len(frame), "first_time": str(frame.timestamp.min()), "last_time": str(frame.timestamp.max()),
|
||||
"firmware": ", ".join(frame.attrs["firmware_versions"]), "cloud_commands": len(commands),
|
||||
"phase_boundary_events": [{"timestamp": str(event.timestamp), "message": event.message,
|
||||
"source_line": int(event.source_line)} for event in milestones],
|
||||
"tel_records": len(telemetry), "uptime_decreases": int(frame.uptime_s.diff().lt(0).sum()),
|
||||
"tel_uptime_decreases": int(telemetry.uptime_s.diff().lt(0).sum()),
|
||||
"tel_gaps_over_15s": int(telemetry.timestamp.diff().dt.total_seconds().gt(MAX_GAP_S).sum()),
|
||||
"tel_negative_step_deltas": int(telemetry.delta.lt(0).sum()),
|
||||
"duplicate_timestamps": int(frame.timestamp.duplicated().sum()),
|
||||
"gap_starts": [str(x) for x in gaps.timestamp],
|
||||
"gap_records": gaps[["timestamp", "message", "source_line", "previous_source_line", "uptime_decreased"]].to_dict("records"),
|
||||
"flags": {k: int(frame[k].sum()) for k in ("adc_clipped", "near_current_rail", "invalid_polarity", "illuminated", "accepted")},
|
||||
"full": summary_full, "phases": rows, "hourly": hourly,
|
||||
"solar_context": {"first_azimuth_deg": float(frame.azimuth_deg.iloc[0]),
|
||||
"last_azimuth_deg": float(frame.azimuth_deg.iloc[-1]),
|
||||
"first_elevation_deg": float(frame.solar_elevation_deg.iloc[0]),
|
||||
"last_elevation_deg": float(frame.solar_elevation_deg.iloc[-1]),
|
||||
"maximum_elevation_deg": float(sun.solar_elevation_deg.max()),
|
||||
"clock_alignment": "Assumed log clock matches printed SunCalc local time; UTC offset unencoded"},
|
||||
"coordinates": {"x_min": int(frame.x_steps.min()), "x_max": int(frame.x_steps.max()),
|
||||
"y_min": int(frame.y_steps.min()), "y_max": int(frame.y_steps.max())},
|
||||
"reference_max": float(reference.max()), "reference_p99": float(reference.quantile(.99)),
|
||||
"anomaly_time": str(anomaly.timestamp), "anomaly_line": int(anomaly.source_line),
|
||||
"anomaly_G": float(anomaly.irradiance_W_m2), "anomaly_I": float(anomaly.isc_A),
|
||||
"anomaly_resp": float(anomaly.responsivity_A_m2_W), "anomaly_neighborhood": anomaly_neighbor_stats,
|
||||
"responsivity_distribution": {
|
||||
"median": float(reference.median()), "q25": float(reference.quantile(.25)),
|
||||
"q75": float(reference.quantile(.75)), "p95": float(reference.quantile(.95)),
|
||||
},
|
||||
"calibration": {"adc_positive_full_scale": ADC_MAX, "vref_V": VREF_V, "current_gain": CURRENT_GAIN,
|
||||
"shunt_ohm": SHUNT_OHM, "pyranometer_mV_per_W_m2": PYRANOMETER_MV_PER_W_M2,
|
||||
"aperture_m2": APERTURE_M2, "fill_factor": FILL_FACTOR,
|
||||
"max_gap_s": MAX_GAP_S, "minimum_irradiance_W_m2": MIN_IRRADIANCE_W_M2},
|
||||
"irradiance_geometry": {"pyranometer_coplanar_with_lens": True,
|
||||
"provenance": "Experimenter confirmation on 2026-11-04",
|
||||
"measured_quantity": "Global irradiance in the fixed lens-aperture plane",
|
||||
"extra_cosine_factor_applied": False},
|
||||
"silicon_scenario": {"area_m2": APERTURE_M2, "efficiencies": [.19, .21],
|
||||
"basis": "constant-efficiency equal-area coplanar silicon scenario with measured aperture-plane irradiance; no temperature correction; not measured panel"},
|
||||
"software": {"python": sys.version.split()[0], "numpy": np.__version__, "pandas": pd.__version__, "matplotlib": matplotlib.__version__},
|
||||
}
|
||||
# Text rows show complete record plus fixed clock bins without selecting a best interval.
|
||||
tab = [summary_full] + hourly
|
||||
summary["table_rows"] = "\n".join(
|
||||
f"{r['window'] if 'window' in r else 'Full acquired record'} & {r['accepted_illuminated_samples']} & "
|
||||
f"{r['integrated_support_h']:.3f} & {r['irradiation_Wh_m2'] / 1000:.3f} & {r['estimated_mpp_energy_Wh']:.4f} & "
|
||||
f"{r['energy_weighted_aperture_efficiency_pct']:.2f} " + "\\" * 2 for r in tab)
|
||||
phase_rows = rows[1:]
|
||||
summary["phase_table_rows"] = "\n".join(
|
||||
f"{pd.Timestamp(r['window_start']).strftime('%H:%M:%S')}--{pd.Timestamp(r['window_end']).strftime('%H:%M:%S')} & "
|
||||
f"{r['accepted_illuminated_samples']} & {r['integrated_support_h']:.3f} & "
|
||||
f"{r['estimated_mpp_energy_Wh']:.3f} & {r['energy_weighted_aperture_efficiency_pct']:.2f} " + "\\" * 2
|
||||
for r in phase_rows)
|
||||
# Mark command milestones relevant to phase boundaries without obscuring traces.
|
||||
summary["command_times"] = [str(t) for t in boundaries]
|
||||
summary["reference_max"] = float(reference.max()); summary["reference_p99"] = float(reference.quantile(.99))
|
||||
frame.to_csv(OUT / "audit_samples.csv", index=False, float_format="%.12g")
|
||||
event_table.to_csv(OUT / "event_chronology.csv", index=False)
|
||||
sun = suncalc_frame()
|
||||
sun.to_csv(OUT / "suncalc_2026-11-04.csv", index=False, float_format="%.5f")
|
||||
pd.DataFrame(rows + hourly).to_csv(OUT / "window_metrics.csv", index=False, float_format="%.10g")
|
||||
pd.DataFrame(sensitivity).to_csv(OUT / "sensitivity.csv", index=False, float_format="%.10g")
|
||||
(OUT / "analysis_summary.json").write_text(json.dumps(summary, indent=2, default=str, allow_nan=False) + "\n", encoding="utf-8")
|
||||
gap_text = "; ".join(
|
||||
f"{frame.loc[frame.source_line == int(g.previous_source_line), 'timestamp'].iloc[0].strftime('%H:%M:%S')}--"
|
||||
f"{pd.Timestamp(g.timestamp).strftime('%H:%M:%S')} ({int(float(g.message.split()[2]))} s)"
|
||||
for g in gaps.itertuples() if g.event_type == "sampling_gap")
|
||||
write_result_tex(summary, gap_text)
|
||||
plot_outputs(frame, event_table, sun, summary)
|
||||
return summary
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
result = run()
|
||||
print(json.dumps({"samples": result["sample_count"], "full": result["full"],
|
||||
"gaps": result["gap_records"], "source_sha256": result["source_sha256"]},
|
||||
indent=2, default=str))
|
||||
@@ -0,0 +1,126 @@
|
||||
$ErrorActionPreference='Stop'
|
||||
$root='c:\Users\fdavalos\OneDrive - up.edu.mx\microtracking\MicrotrackingFer'
|
||||
$logRe='^(?:LOG:)?\[([\d\-/ :]+)\] X:(-?\d+),Y:(-?\d+),C:(\d+),V:(\d+),P:(\d+),S:(\d+),er:(\d+)$'
|
||||
$ftRe='^(?:LOG:)?\[([\d\-/ :]+)\] FineTune: dC=(\d+), dynE=(\d+), e=(\d+), near=(\d), Cmax=(\d+)$'
|
||||
|
||||
function ParseLog([string]$path){
|
||||
$o=@{}
|
||||
foreach($t in @('X','Y','C','V','P','S','E','ftDc','ftDynE','ftE','ftNear','ftCmax')){$o[$t]=New-Object 'System.Collections.Generic.List[long]'}
|
||||
$o.ts=New-Object 'System.Collections.Generic.List[string]'
|
||||
$o.ftTs=New-Object 'System.Collections.Generic.List[string]'
|
||||
$o.spec=@{}
|
||||
$o.other=New-Object 'System.Collections.Generic.List[string]'
|
||||
$o.posVals=@{}
|
||||
$o.posSamples=New-Object 'System.Collections.Generic.List[string]'
|
||||
$o.cloud=New-Object 'System.Collections.Generic.List[string]'
|
||||
$lines=[IO.File]::ReadAllLines($path)
|
||||
$o.total=$lines.Count
|
||||
$o.lines_ref=$lines[0]; $o.last_ref=$lines[$lines.Count-1]
|
||||
foreach($ln in $lines){
|
||||
if($ln -match $logRe){
|
||||
$o.ts.Add($matches[1])
|
||||
$o.X.Add([long]$matches[2]); $o.Y.Add([long]$matches[3]); $o.C.Add([long]$matches[4])
|
||||
$o.V.Add([long]$matches[5]); $o.P.Add([long]$matches[6]); $o.S.Add([long]$matches[7]); $o.E.Add([long]$matches[8])
|
||||
} elseif($ln -match $ftRe){
|
||||
$o.ftTs.Add($matches[1])
|
||||
$o.ftDc.Add([long]$matches[2]); $o.ftDynE.Add([long]$matches[3]); $o.ftE.Add([long]$matches[4]); $o.ftNear.Add([long]$matches[5]); $o.ftCmax.Add([long]$matches[6])
|
||||
} else {
|
||||
$t2=$ln.Trim()
|
||||
if($t2 -eq ''){ $o.spec['empty']=1+[int]$o.spec['empty'] }
|
||||
elseif($ln -match 'COM READY'){ $o.spec['COM READY']=1+[int]$o.spec['COM READY']; $o.cloud.Add(('COMREADY | '+$ln)) }
|
||||
elseif($ln -match 'WS cerrado'){ $o.spec['WS cerrado']=1+[int]$o.spec['WS cerrado']; $o.cloud.Add(('WSCLOSED | '+$ln)) }
|
||||
elseif($ln -match 'Desconectado'){ $o.spec['Desconectado']=1+[int]$o.spec['Desconectado']; $o.cloud.Add(('DISCON | '+$ln)) }
|
||||
elseif($ln -match 'Servidor'){ $o.spec['Servidor']=1+[int]$o.spec['Servidor']; $o.cloud.Add(('SERV | '+$ln)) }
|
||||
elseif($ln -match '^POS:(\d+):(\d+)$'){ $o.spec['POS:']=1+[int]$o.spec['POS:']; $v=$matches[1]+':'+$matches[2]; $o.posVals[$v]=1+[int]$o.posVals[$v]; if($o.posSamples.Count -lt 4){$o.posSamples.Add($ln)} }
|
||||
else { $o.spec['other']=1+[int]$o.spec['other']; if($o.other.Count -lt 6){ $o.other.Add($ln) } }
|
||||
}
|
||||
}
|
||||
return $o
|
||||
}
|
||||
#MORE1
|
||||
function Analyze($o){
|
||||
$n=$o.ts.Count
|
||||
if($n -eq 0){ Write-Host ' (sin muestras LOG)'; return }
|
||||
$t=@($o.ts | %{ [datetime]::Parse($_) })
|
||||
Write-Host (" lineasTotales={0} LOG={1} FT={2}" -f $o.total,$n,$o.ftTs.Count)
|
||||
Write-Host (" ventana: {0} -> {1} (span {2} min)" -f $t[0].ToString('yyyy-MM-dd HH:mm:ss'),$t[$n-1].ToString('HH:mm:ss'),[int]($t[$n-1]-$t[0]).TotalMinutes)
|
||||
Write-Host (" 1a linea: "+$o.lines_ref)
|
||||
Write-Host (" ul linea: "+$o.last_ref)
|
||||
$dts=New-Object 'double[]' ($n-1)
|
||||
for($i=1;$i -lt $n;$i++){$dts[$i-1]=($t[$i]-$t[$i-1]).TotalSeconds}
|
||||
$med=$dts|Sort-Object|Select-Object -Index [int]($dts.Count/2)
|
||||
$g=1..($n-1) | ?{ ($t[$_] - $t[$_-1]).TotalSeconds -gt 15 }
|
||||
Write-Host (" dt(s): min={0} med={1} max={2} gaps>15s: {3}" -f [int]($dts|Measure-Object -Minimum).Minimum,[int]$med,[int]($dts|Measure-Object -Maximum).Maximum,$g.Count)
|
||||
if($g.Count -gt 0){ Write-Host (" gaps: "+(($g|select -First 10)|%{ $t[$_].ToString('HH:mm:ss')+"(+"+[int]($t[$_]-$t[$_-1]).TotalSeconds+"s)" }) -join ' | ') }
|
||||
$back=1..($n-1) | ?{ $o.S[$_] -lt $o.S[$_-1] }
|
||||
$dup=1..($n-1) | ?{ $o.S[$_] -eq $o.S[$_-1] }
|
||||
Write-Host (" S: {0} -> {1} ({2} u/s) S-back={3} S-dup={4}" -f $o.S[0],$o.S[$n-1],([math]::Round(($o.S[$n-1]-$o.S[0])/($t[$n-1]-$t[0]).TotalSeconds,3)),$back.Count,$dup.Count)
|
||||
Write-Host (" spec: "+(($o.spec.GetEnumerator() | ?{$_.Value -gt 0} | %{$_.Key+"="+$_.Value}) -join ', '))
|
||||
if($o.posVals.Count -gt 0){
|
||||
$top=$o.posVals.GetEnumerator()|Sort-Object Value -Descending|Select-Object -First 12
|
||||
Write-Host (" POS: distintos={0} top: {1}" -f $o.posVals.Count,(($top|%{"$($_.Key)x$($_.Value)"}) -join ' '))
|
||||
foreach($s in $o.posSamples){ Write-Host (" sample: "+$s) }
|
||||
}
|
||||
if($o.other.Count -gt 0){ foreach($s in $o.other){ Write-Host (" other: "+$s.Substring(0,[Math]::Min(90,$s.Length))) } }
|
||||
if($o.cloud.Count -gt 0){
|
||||
Write-Host (" cloud ({0} eventos) 1ro: "+$o.cloud[0])
|
||||
Write-Host (" cloud ultimo: "+$o.cloud[$o.cloud.Count-1])
|
||||
}
|
||||
$runs=New-Object 'System.Collections.Generic.List[string]'
|
||||
$cur=$o.E[0]; $st=0
|
||||
for($i=1;$i -le $n;$i++){
|
||||
if($i -lt $n -and $o.E[$i] -eq $cur){ continue }
|
||||
$runs.Add( ("er="+$cur+": "+$t[$st].ToString('HH:mm:ss')+"->"+$t[$i-1].ToString('HH:mm:ss')+" (n="+($i-$st)+")") )
|
||||
if($i -lt $n){ $cur=$o.E[$i]; $st=$i }
|
||||
}
|
||||
Write-Host (" er(t): "+($runs -join ' '))
|
||||
$nPos=@{}
|
||||
for($i=0;$i -lt $n;$i++){$k=$o.X[$i].ToString()+':'+$o.Y[$i].ToString(); $nPos[$k]=1+[int]$nPos[$k]}
|
||||
$fm=(1..($n-1) | ?{ $o.X[$_] -ne $o.X[0] -or $o.Y[$_] -ne $o.Y[0] } | select -First 1)
|
||||
$fmS=if($null -ne $fm){ $t[$fm].ToString('HH:mm:ss') } else { 'nunca' }
|
||||
Write-Host (" X: {0}..{1} Y: {2}..{3} pos.distintas={4} 1er.mov={5}" -f ($o.X|Measure-Object -Minimum).Minimum,($o.X|Measure-Object -Maximum).Maximum,($o.Y|Measure-Object -Minimum).Minimum,($o.Y|Measure-Object -Maximum).Maximum,$nPos.Count,$fmS)
|
||||
$topPos=$nPos.GetEnumerator()|Sort-Object Value -Descending|Select-Object -First 5
|
||||
Write-Host (" pos.mas estacionadas: "+(($topPos|%{"$($_.Key) x$($_.Value)"}) -join ' '))
|
||||
$idx=@(0,[int]($n/4),[int]($n/2),[int](3*$n/4),($n-1))
|
||||
Write-Host ' checkpoints (hora | X:Y | C | V | P | er):'
|
||||
foreach($i in $idx){ Write-Host (" "+$t[$i].ToString('HH:mm:ss')+" | "+$o.X[$i]+":"+$o.Y[$i]+" | C="+$o.C[$i]+" V="+$o.V[$i]+" P="+$o.P[$i]+" er="+$o.E[$i]) }
|
||||
Write-Host (" C: min={0} max={1} mean={2} P max={3}" -f ($o.C|Measure-Object -Minimum).Minimum,($o.C|Measure-Object -Maximum).Maximum,[int]($o.C|Measure-Object -Average).Average,($o.P|Measure-Object -Maximum).Maximum)
|
||||
$drop=1..($n-1) | ?{ ($o.C[$_] - $o.C[$_-1]) -lt -10000 }
|
||||
Write-Host (" saltos grandes C (>10k uA): "+$drop.Count)
|
||||
if($drop.Count -gt 0){ $drop | Sort-Object { $o.C[$_] - $o.C[$_-1] } | select -First 6 | %{ Write-Host (" "+$t[$_].ToString('HH:mm:ss')+" C "+$o.C[$_-1]+" -> "+$o.C[$_]+" (d="+($o.C[$_]-$o.C[$_-1])+")") } }
|
||||
$m=$o.ftTs.Count
|
||||
if($m -gt 0){
|
||||
$near0=(0..($m-1) | ?{ $o.ftNear[$_] -eq 0 }).Count
|
||||
Write-Host (" FT: near=0 en {0}/{1} ({2}%) dC max={3} dynE: {4}..{5} e top: {6}" -f $near0,$m,[math]::Round(100*$near0/$m,1),($o.ftDc|Measure-Object -Maximum).Maximum,($o.ftDynE|Measure-Object -Minimum).Minimum,($o.ftDynE|Measure-Object -Maximum).Maximum,((($o.ftE|Group-Object|Sort-Object {$_.Count} -Descending|select -First 6)|%{"$($_.Name)x$($_.Count)"}) -join ', '))
|
||||
}
|
||||
}
|
||||
#MORE2
|
||||
$files=@('full_log_21082025.txt','log(3).txt','gyuggyhoy.txt')
|
||||
$logs=@{}
|
||||
foreach($f in $files){
|
||||
Write-Host ("########## $f ##########")
|
||||
$o=ParseLog (Join-Path $root $f)
|
||||
$logs[$f]=$o
|
||||
Analyze $o
|
||||
Write-Host ''
|
||||
}
|
||||
Write-Host '########## CROSS-CHECK log(3) vs gyuggyhoy (ambos 14/09) ##########'
|
||||
$a=$logs['log(3).txt']; $b=$logs['gyuggyhoy.txt']
|
||||
$da=@{}; for($i=0;$i -lt $a.ts.Count;$i++){$da[$a.ts[$i]]=@($a.X[$i],$a.Y[$i],$a.C[$i])}
|
||||
$db=@{}; for($i=0;$i -lt $b.ts.Count;$i++){$db[$b.ts[$i]]=@($b.X[$i],$b.Y[$i],$b.C[$i])}
|
||||
$common=@($da.Keys | ?{ $db.ContainsKey($_) } | Sort-Object)
|
||||
Write-Host (" log(3): "+$a.ts[0]+" -> "+$a.ts[$a.ts.Count-1])
|
||||
Write-Host (" gyuggyhoy: "+$b.ts[0]+" -> "+$b.ts[$b.ts.Count-1])
|
||||
if($common.Count -gt 0){
|
||||
Write-Host (" ventana comun: "+$common.Count+" ts ("+$common[0]+" -> "+$common[$common.Count-1]+")")
|
||||
$xm=0; $cm=0; $samps=@()
|
||||
foreach($ts in $common){
|
||||
if($da[$ts][0] -ne $db[$ts][0] -or $da[$ts][1] -ne $db[$ts][1]){$xm++}
|
||||
if($da[$ts][2] -ne $db[$ts][2]){$cm++; if($samps.Count -lt 5){ $samps.Add(("$ts log3 X/Y="+$da[$ts][0]+":"+$da[$ts][1]+" C="+$da[$ts][2]+" | guggy X/Y="+$db[$ts][0]+":"+$db[$ts][1]+" C="+$db[$ts][2])) } }
|
||||
}
|
||||
Write-Host (" mismatches en ventana comun: X/Y="+$xm+" C="+$cm)
|
||||
foreach($s in $samps){ Write-Host (" "+$s) }
|
||||
} else { Write-Host ' ventana comun: vacia' }
|
||||
Write-Host (" boot estimado log(3): "+([datetime]::Parse($a.ts[0]).AddSeconds(-[long]$a.S[0])).ToString('HH:mm:ss')+" (S0="+$a.S[0]+" @ "+$a.ts[0]+")")
|
||||
Write-Host (" boot estimado gyuggyhoy: "+([datetime]::Parse($b.ts[0]).AddSeconds(-[long]$b.S[0])).ToString('HH:mm:ss')+" (S0="+$b.S[0]+" @ "+$b.ts[0]+")")
|
||||
Write-Host '########## FIN ##########'
|
||||
@@ -0,0 +1,718 @@
|
||||
% $ biblatex auxiliary file $
|
||||
% $ biblatex bbl format version 3.3 $
|
||||
% Do not modify the above lines!
|
||||
%
|
||||
% This is an auxiliary file used by the 'biblatex' package.
|
||||
% This file may safely be deleted. It will be recreated by
|
||||
% biber as required.
|
||||
%
|
||||
\begingroup
|
||||
\makeatletter
|
||||
\@ifundefined{ver@biblatex.sty}
|
||||
{\@latex@error
|
||||
{Missing 'biblatex' package}
|
||||
{The bibliography requires the 'biblatex' package.}
|
||||
\aftergroup\endinput}
|
||||
{}
|
||||
\endgroup
|
||||
|
||||
|
||||
\refsection{0}
|
||||
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Binary file not shown.
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|
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|
||||
\author[inst4]{Rosa C. Anguiano Cota}
|
||||
\author[inst1]{Pedro M. Rodrigo}
|
||||
\author[inst5]{María A. Ceballos}
|
||||
\author[inst5]{Álvaro Valera-Albacete}
|
||||
\author[inst5]{Florencia Almonacid}
|
||||
\author[inst5]{Eduardo F. Fernández}
|
||||
|
||||
\affiliation[inst1]{organization={Universidad Panamericana, Facultad de Ingeniería},
|
||||
addressline={Jose María Escrivá de Balaguer 101, Villas Bonaterra},city={Aguascalientes},
|
||||
postcode={20296},state={Aguascalientes},country={Mexico}}
|
||||
\affiliation[inst2]{organization={SECIHTI -- Centro de Investigaciones en Óptica, A.C., Unidad Aguascalientes},
|
||||
addressline={Prol. Constitución 607, Fracc. Reserva Loma Bonita},city={Aguascalientes},
|
||||
postcode={20200},state={Aguascalientes},country={Mexico}}
|
||||
\affiliation[inst3]{organization={Laboratory of Energy Innovation and Intelligent and Sustainable Agriculture (LEIISA), Universidad Tecnológica de San Juan del Río},
|
||||
addressline={Av La Palma No 125 Vista Hermosa},city={San Juan del Río},postcode={76800},
|
||||
state={Querétaro},country={Mexico}}
|
||||
\affiliation[inst4]{organization={Facultad de Ingeniería, Universidad Autónoma de Baja California (UABC)},
|
||||
addressline={Blvd. Benito Juárez SN},city={Mexicali},postcode={21280},
|
||||
state={Baja California},country={Mexico}}
|
||||
\affiliation[inst5]{organization={Advances in Photovoltaic Technology (AdPVTech), CEACTEMA, University of Jaén},
|
||||
addressline={Las Lagunillas Campus},city={Jaén},postcode={23071},state={Jaén},country={Spain}}
|
||||
\cortext[cor1]{Corresponding author. Email: fdavalos@up.edu.mx}
|
||||
|
||||
\begin{abstract}
|
||||
Tracking-integrated concentrator photovoltaics preserve fixed external optics
|
||||
while moving the receiver to follow the evolving focal region. Their field
|
||||
performance therefore depends on both optical collection and internal
|
||||
positioning, rather than on external solar pointing alone. This work
|
||||
characterizes a photocurrent-feedback controller and custom ESP32 acquisition
|
||||
system for a wide-acceptance-angle tracking-integrated micro-concentrator
|
||||
photovoltaic (WiT-CPV) prototype. The principal experiment is the 4 November
|
||||
2026 outdoor record in Aguascalientes, Mexico: \NovSamples{} observations
|
||||
between 09:52 and 16:05, with \NovHours{} h of accepted integration support
|
||||
and no ADC clipping. Sequential short-circuit-current and open-circuit-voltage
|
||||
measurements yield an estimated available maximum-power-point energy of
|
||||
\NovEnergy{} Wh for an assumed fill factor of 0.82. Relative to the
|
||||
0.002497-m$^2$ lens aperture and the coplanar pyranometric irradiation of
|
||||
\NovIrradiation{} kWh\,m$^{-2}$, the energy-weighted efficiency estimate is
|
||||
\NovEfficiency\%. The command-delimited 12:32--13:53 post-tuning phase yields
|
||||
an aperture estimate of \NovSteadyEfficiency\% without additional logged
|
||||
operator commands. Solar-position data contextualize the operating trajectory,
|
||||
while the complete record retains tuning interventions and late response
|
||||
degradation. Reference sensitivity is examined rather than treated as an
|
||||
independent tracking-accuracy measurement. An equal-aperture silicon comparison
|
||||
is reported as a conditional constant-efficiency scenario, not a simultaneous
|
||||
panel experiment. The results establish an aperture-referenced field
|
||||
characterization and identify the measurements needed to validate delivered
|
||||
power, net energy and angular tracking accuracy.
|
||||
\end{abstract}
|
||||
|
||||
\begin{highlights}
|
||||
\item A \NovSamples{}-sample field record characterizes internal focal tracking
|
||||
\item Estimated aperture efficiency is \NovEfficiency\% over \NovHours{} h of accepted support
|
||||
\item A post-tuning phase yields a \NovSteadyEfficiency\% aperture estimate
|
||||
\item Solar-position context and late response losses define observed operation
|
||||
\item Fixed-silicon scenarios use equal aperture and explicitly stated assumptions
|
||||
\end{highlights}
|
||||
|
||||
\begin{keyword}
|
||||
Tracking-integrated CPV \sep Focal tracking \sep Photocurrent feedback \sep
|
||||
Aperture efficiency \sep Outdoor characterization \sep Silicon photovoltaic benchmark
|
||||
\end{keyword}
|
||||
\end{frontmatter}
|
||||
|
||||
\section{Introduction}
|
||||
\label{sec:introduction}
|
||||
|
||||
Photovoltaic energy collection depends on the relationship between solar
|
||||
direction, collector orientation and device response. Conventional
|
||||
one- and two-axis trackers improve this relationship by moving the module
|
||||
or concentrator as a whole, at the cost of actuation, support and control
|
||||
requirements \cite{mousazadeh2009review,hafez2018solar,fuentes2020control}.
|
||||
In concentrating photovoltaics (CPV), optical alignment is especially
|
||||
important because displacement of the focal distribution can reduce the
|
||||
fraction intercepted by a small receiver \cite{iqbal2023optical}.
|
||||
|
||||
Tracking-integrated CPV transfers part or all of the required motion inside
|
||||
the module \cite{ceballos2023tracking}. Microtracking lens arrays, internally
|
||||
translated receivers and hybrid diffuse-light collection illustrate different
|
||||
ways of decoupling focal alignment from large external motion
|
||||
\cite{ito2018optical,askins2019performance,younes2022realizing}.
|
||||
This distinction matters when interpreting field performance: moving a
|
||||
receiver beneath fixed optics does not make the optical aperture normal to
|
||||
the Sun, nor does it eliminate the finite angular and mechanical operating
|
||||
range of the assembly.
|
||||
|
||||
The wide-acceptance-angle tracking-integrated micro-concentrator photovoltaic
|
||||
(WiT-CPV) prototype studied here was previously reported with its optical and
|
||||
mechanical design, azimuthal cell rotation and first-generation controller
|
||||
\cite{diasponce2025development}. Its receiver follows the moving focal region
|
||||
of a biconvex aspheric lens along a mechanically constrained trajectory.
|
||||
Knowledge of solar position alone does not establish the corresponding
|
||||
receiver coordinates: optical geometry, mounting and kinematics must also
|
||||
be known. Photocurrent provides a useful local feedback signal, although
|
||||
irradiance, temperature and spectrum can change it independently of alignment.
|
||||
|
||||
The present contribution is a field characterization of this coupled system
|
||||
using the complete acquired record of 4 November 2026. It connects measured
|
||||
electrical signals and stage coordinates to an explicitly estimated
|
||||
aperture-level output, places the response in solar-position context, and
|
||||
discloses data gaps and operational interventions. A fixed-silicon scenario
|
||||
provides an area-normalized engineering reference without substituting a
|
||||
simulation for an unperformed experiment. This focus replaces comparisons
|
||||
between heterogeneous development sessions with a traceable principal case;
|
||||
it does not constitute a controlled comparison of controller versions or
|
||||
a validation of net energy production.
|
||||
|
||||
\section{System and Control}
|
||||
\label{sec:system}
|
||||
|
||||
\subsection{Optical and mechanical architecture}
|
||||
|
||||
The prototype combines fixed primary optics, a multi-junction photovoltaic
|
||||
receiver and a two-axis actuated stage. Guided mechanical motion follows
|
||||
the curved focal trajectory associated with the Petzval surface; the detailed
|
||||
optomechanical construction is described in \cite{diasponce2025development}.
|
||||
The lens aperture used in the present analysis is
|
||||
$A_L=0.002497$~m$^2$. Coordinates $X$ and $Y$ denote the project's azimuth
|
||||
and elevation axes, respectively. They are commanded step coordinates,
|
||||
not independently measured solar or receiver angles. The acquisition does
|
||||
not provide a calibrated steps-to-angle transformation or an independent
|
||||
measurement of focal-position error.
|
||||
|
||||
\subsection{Controller and measurement chain}
|
||||
|
||||
An ESP32-based controller provides wireless command/telemetry interfaces
|
||||
and commands two TMC2209 stepper drivers. A 24-bit ADS122C04 converter
|
||||
acquires the photocurrent, pyranometer and cell-voltage channels. The
|
||||
photocurrent chain uses a nominal 0.130-$\Omega$ shunt for the evaluated
|
||||
PCB V2 configuration, an external gain of 20 and a 2.048-V reference.
|
||||
Open-circuit voltage is acquired through a factor-of-two divider, and an
|
||||
Apogee SP-212 provides the irradiance reference. The functional measurement
|
||||
and control paths are summarized in Fig.~\ref{fig:architecture}.
|
||||
|
||||
\begin{figure}[htbp]
|
||||
\centering
|
||||
\begin{tikzpicture}[>=Latex,font=\small,
|
||||
box/.style={draw,rounded corners=2pt,align=center,minimum height=11mm,text width=40mm},
|
||||
node distance=11mm and 20mm]
|
||||
\node[box] (optics) {Fixed primary lens\\$A_L=0.002497$ m$^2$};
|
||||
\node[box,right=of optics] (cell) {Moving receiver\\$X$: azimuth; $Y$: elevation};
|
||||
\node[box,below=of cell] (adc) {Sequential ADC acquisition\\$I_{sc}$, $G$, $V_{oc}$};
|
||||
\node[box,left=of adc] (control) {ESP32 and motor drivers\\Photocurrent feedback};
|
||||
\node[box,below=of adc] (analysis) {Logged observations\\Offline calibration\\and analysis};
|
||||
\draw[->] (optics) -- node[above]{Focal region} (cell);
|
||||
\draw[->] (cell) -- (adc);
|
||||
\draw[->] (adc) -- node[above]{$C$ feedback} (control);
|
||||
\draw[->] (control.west) -- ++(-7mm,0) |- ([yshift=8mm]cell.north) -- (cell.north);
|
||||
\node[above=8mm of cell,font=\scriptsize] {Internal motion};
|
||||
\draw[->] (adc) -- (analysis);
|
||||
\end{tikzpicture}
|
||||
\caption{Functional architecture of the evaluated system. Only the receiver
|
||||
is repositioned; internal tracking does not reorient the external aperture.
|
||||
Electrical channels are acquired sequentially, and the offline power estimate
|
||||
is not feedback from a measured MPP load.}
|
||||
\label{fig:architecture}
|
||||
\end{figure}
|
||||
|
||||
The cell is switched between short-circuit-current and open-circuit-voltage
|
||||
measurement states. Current, irradiance and voltage therefore represent
|
||||
sequential conversions rather than a simultaneous electrical operating
|
||||
point. The periodic \texttt{TEL} messages contain separate telemetry averages
|
||||
and fine-tuning counters; they are not interchangeable with the coordinate/
|
||||
electrical observations used for the quantitative analysis.
|
||||
|
||||
\subsection{Evaluated control and implementation provenance}
|
||||
\label{sec:control_provenance}
|
||||
|
||||
The raw record identifies the deployed firmware as \texttt{1.1.3-ws}.
|
||||
The controller performs photocurrent-feedback fine tuning, with configurable
|
||||
step bounds, current-change thresholds, peak-proximity settings and
|
||||
axis-search cycles. Its log reports adaptive-step diagnostics and periodic
|
||||
reference resets. Pyranometer input supports illumination-related operating
|
||||
logic, but the offline $I_{sc}/G$ ratio used below must not be interpreted
|
||||
as a verified samplewise feedback law of the evaluated firmware.
|
||||
|
||||
The available development source has subsequently changed; in particular,
|
||||
later revisions address current-change, near-peak and deadband behavior.
|
||||
Those later equations and features are not attributed to the recorded
|
||||
deployment. Accordingly, this article describes the evaluated controller at
|
||||
the level supported by version identifiers and logged behavior, rather than
|
||||
presenting unverified branch equations as an exact specification of its binary.
|
||||
The experiment includes parameter updates and manual positioning commands.
|
||||
It is an operational field characterization with disclosed tuning, not a
|
||||
fixed-parameter autonomous trial, an ablation study or proof that each
|
||||
protective control regime operates as intended.
|
||||
|
||||
\section{Experimental and Analytical Methods}
|
||||
\label{sec:methods}
|
||||
|
||||
\subsection{Site, acquisition and solar-position reference}
|
||||
|
||||
The principal acquisition took place on 4 November 2026 in Aguascalientes,
|
||||
Mexico. The supplied SunCalc printout identifies latitude
|
||||
$21.87304^\circ$ N and longitude $102.28282^\circ$ W and tabulates solar
|
||||
azimuth and elevation at 15-min intervals \cite{suncalc2026}.
|
||||
The field conditions were described as clear by the experimenter; this is
|
||||
a field observation, not an independently measured classification of direct
|
||||
and diffuse irradiance. Brief irradiance anomalies are retained and examined.
|
||||
|
||||
Time plots use the local acquisition clock. The log has no encoded time-zone
|
||||
offset, so matching to the supplied local-time SunCalc table is an explicit
|
||||
clock-alignment assumption, not an independent timing calibration.
|
||||
Linear interpolation between the printed solar positions supplies context
|
||||
at observation times. It does not improve the ephemeris resolution or measure
|
||||
stage accuracy. Azimuth is measured clockwise from north and elevation above
|
||||
the horizon. Neither absolute solar azimuth nor its span equals the collector
|
||||
incidence angle. The acquisition package does not establish absolute external-optics
|
||||
tilt/azimuth, so conversion to a validated
|
||||
optical acceptance envelope is not attempted.
|
||||
|
||||
\subsection{Offline calibration and data-quality rules}
|
||||
|
||||
Let $C$, $V$ and $P$ denote the signed 24-bit photocurrent, voltage and
|
||||
pyranometer codes, with positive full scale $D=8{,}388{,}607$. Offline conversion is
|
||||
\begin{align}
|
||||
I_{sc}&=\frac{2.048 C}{20D R_s}, &
|
||||
V_{oc}&=\frac{2(2.048)V}{D}, &
|
||||
G&=\frac{2048P}{0.2D},\quad R_s=0.130~\Omega.
|
||||
\label{eq:calibration}
|
||||
\end{align}
|
||||
The resulting units are A, V and W\,m$^{-2}$. The pyranometer sensitivity
|
||||
is 0.2~mV/(W\,m$^{-2}$); using 2.0 would understate irradiance tenfold.
|
||||
The raw channels are not exchanged: \texttt{C} is photocurrent and
|
||||
\texttt{P} is pyranometer output. The same physical shunt applies throughout
|
||||
this record; a software conversion update at the hub does not define a
|
||||
physical shunt change in the raw acquisition.
|
||||
|
||||
The experimenter confirms that the SP-212 was mounted in the same plane as
|
||||
the concentration lens. Thus $G$ is measured global irradiance in the fixed
|
||||
lens-aperture plane, and $G A_L$ estimates incident solar power on that
|
||||
aperture. No additional cosine projection is applied: the beam's geometric
|
||||
projection onto the receiving plane is already represented in the coplanar
|
||||
irradiance measurement. This quantity is not direct-normal irradiance.
|
||||
The SP-212's spectral and angular responses differ from those of concentrating
|
||||
multi-junction optics \cite{apogee_sp212_manual}; its calibration and angular
|
||||
response, and the concentrator's limited collection of diffuse light, remain
|
||||
relevant to the uncertainty and interpretation.
|
||||
Offline scaling also does not retroactively correct firmware irradiance
|
||||
thresholds or change historical control decisions.
|
||||
No experiment-specific uncertainty budget is available for shunt resistance,
|
||||
amplifier gain, voltage reference or irradiance calibration. Reported decimal
|
||||
places identify reproducible calculations, not a demonstrated metrological
|
||||
precision or confidence interval.
|
||||
|
||||
Every observation retains its source line, raw codes and quality flags.
|
||||
Checks include signed conversion, channel clipping, a 99\%-of-current-rail
|
||||
guard, negative channels, timestamps and uptime discontinuities. For integration,
|
||||
both adjacent endpoints must be electrically accepted and illuminated
|
||||
($G>50$~W\,m$^{-2}$), their separation must be positive and at most 15~s,
|
||||
and uptime must not decrease. Rejected observations and long gaps are never
|
||||
bridged. Low output and manual interventions are retained, not excluded
|
||||
because they reduce a performance score. Clock-hour subdivisions are
|
||||
descriptive and accompany, rather than replace, the complete acquired record.
|
||||
|
||||
\subsection{Estimated output and aperture-referenced performance}
|
||||
|
||||
The instantaneous available-MPP proxy and its energy integral are
|
||||
\begin{equation}
|
||||
\widehat P_{\mathrm{MPP}}=I_{sc}V_{oc}FF,\qquad
|
||||
\widehat E=\int_{\mathcal S}\widehat P_{\mathrm{MPP}}\,dt,
|
||||
\qquad FF=0.82,
|
||||
\label{eq:power_estimate}
|
||||
\end{equation}
|
||||
where $\mathcal S$ is the union of accepted adjacent intervals and time is
|
||||
expressed in hours for Wh. A fixed fill factor is assumed; no outdoor I--V
|
||||
curve, MPP converter or delivered-load power is inferred. Sequential sensing
|
||||
further assumes approximately stable conditions across the conversion cycle,
|
||||
which can fail during rapid changes. Thus $\widehat E$ estimates available
|
||||
electrical energy, not harvested or net system energy.
|
||||
|
||||
On the identical temporal support, define
|
||||
\begin{equation}
|
||||
H=\int_{\mathcal S}G\,dt,\qquad
|
||||
\widehat\eta_{\mathrm{ap},E}=\frac{\widehat E}{A_L H},\qquad
|
||||
\widehat\eta_{\mathrm{ap}}(t)=\frac{\widehat P_{\mathrm{MPP}}(t)}{A_LG(t)}.
|
||||
\label{eq:aperture}
|
||||
\end{equation}
|
||||
The integrated ratio, reported as a percentage, is not the mean of the
|
||||
instantaneous ratios. With the confirmed coplanar irradiance measurement,
|
||||
it estimates the complete lens/receiver combination's electrical conversion
|
||||
relative to solar energy incident on its aperture, not intrinsic cell efficiency.
|
||||
Optical losses that reduce the measured cell response are already reflected
|
||||
in the numerator; no additional lens-transmission factor is applied to that output.
|
||||
For any alternative constant $FF'$, $\widehat E$ and
|
||||
$\widehat\eta_{\mathrm{ap},E}$ scale by $FF'/0.82$; this is sensitivity
|
||||
to an assumption, not a calibrated uncertainty interval.
|
||||
|
||||
\subsection{Relative response without an ideal-alignment claim}
|
||||
|
||||
To describe electrical response relative to a common empirical reference,
|
||||
let $R(t)=I_{sc}(t)/G(t)$ and consider both its full-record maximum
|
||||
$R_{\max}$ and 99th percentile $R_{99}$. For either reference $R_*$,
|
||||
\begin{equation}
|
||||
\widehat P_{\mathrm{ref}}(t;R_*)=R_*G(t)V_{oc}(t)FF,\qquad
|
||||
\rho_E(R_*)=\frac{\int_{\mathcal S}\widehat P_{\mathrm{MPP}}dt}
|
||||
{\int_{\mathcal S}\widehat P_{\mathrm{ref}}(t;R_*)dt}.
|
||||
\label{eq:relative_yield}
|
||||
\end{equation}
|
||||
This is a record-specific relative-yield indicator, not independently
|
||||
validated tracking efficiency or angular accuracy. Neither reference removes
|
||||
temperature, spectral, geometry or asynchronous-sensing effects. The P99
|
||||
reference is not a strict ceiling; ratios are not clipped to 100\%.
|
||||
Sensitivity to reference choice is part of the result, not a reason to select
|
||||
the reference that produces the most favorable number.
|
||||
|
||||
\subsection{Equal-area fixed-silicon reference scenario}
|
||||
\label{sec:silicon_methods}
|
||||
|
||||
No simultaneous silicon reference measurement accompanies the acquisition.
|
||||
We therefore define a conditional equal-area scenario for a hypothetical fixed
|
||||
silicon surface coplanar with the lens, using the measured plane-of-aperture
|
||||
irradiance and the accepted temporal support of the CPV estimate:
|
||||
\begin{equation}
|
||||
P_{\mathrm{Si,scenario}}(t)=A_L\eta_{\mathrm{Si}}G(t),\qquad
|
||||
E_{\mathrm{Si,scenario}}=A_L\eta_{\mathrm{Si}}H,\qquad
|
||||
B=\frac{\widehat E}{E_{\mathrm{Si,scenario}}}.
|
||||
\label{eq:silicon_scenario}
|
||||
\end{equation}
|
||||
PVWatts lists approximate nominal module efficiencies of 19\% and 21\%
|
||||
for its Standard and Premium crystalline-silicon categories, respectively
|
||||
\cite{pvwatts_module_type}. These two assumptions provide model-based context,
|
||||
not upper/lower bounds on silicon technology or specifications of a tested
|
||||
panel. The equivalent area is a normalization, not a fabricated 0.002497-m$^2$
|
||||
module. This scenario does not assume equal rated power or equal cell area.
|
||||
Since $B=\widehat\eta_{\mathrm{ap},E}/\eta_{\mathrm{Si}}$ under these
|
||||
assumptions, the comparison is an algebraic restatement of the aperture
|
||||
estimate, not independent experimental evidence.
|
||||
|
||||
Holding silicon efficiency constant isolates the area/irradiation comparison;
|
||||
it does not predict temperature-corrected field yield. A physical module model
|
||||
would additionally require module-specific optical corrections to the measured
|
||||
plane irradiance, cell temperature and thermal mounting conditions
|
||||
\cite{sandia_poa,sandia_pvwatts}. PVWatts' corresponding nominal
|
||||
power-temperature coefficients are $-0.37$ and $-0.35$\%/K, but no unmeasured
|
||||
silicon temperature is assigned here. Coplanarity supports the common incident
|
||||
irradiance basis, but does not equate absorbed effective irradiance or measured
|
||||
electrical output for the two technologies. Values of $B$ are conditional
|
||||
arithmetic comparisons, not measured energy gains over silicon.
|
||||
|
||||
\section{Field Results}
|
||||
\label{sec:results}
|
||||
\input{results_2026_11_04}
|
||||
|
||||
\section{Discussion}
|
||||
\label{sec:discussion}
|
||||
|
||||
\subsection{What the principal experiment establishes}
|
||||
|
||||
The principal result is a single, traceable operating characterization that
|
||||
connects internal motion, electrical response and solar-position context.
|
||||
The unsaturated current channel permits analysis of the acquired daytime
|
||||
span without reconstructing clipped high-current observations. The
|
||||
\NovEfficiency\% integrated aperture estimate retains initialization,
|
||||
tuning and degraded response; it is therefore more informative about this
|
||||
record than a favorable midday peak alone. The useful output during changing
|
||||
solar direction supports the feasibility of internal receiver tracking,
|
||||
but does not isolate the controller's contribution from manual intervention
|
||||
or establish an ideal focal trajectory.
|
||||
|
||||
The lower late response is part of the demonstrated behavior, not a discarded
|
||||
outlier. Finite travel, optical acceptance, alignment, temperature and
|
||||
control settings could all contribute. Solar ephemerides and commanded
|
||||
coordinates alone cannot separate them. Establishing an angular operating
|
||||
envelope requires known external-optics orientation and an independent
|
||||
mapping between receiver position, incidence angle and optical response.
|
||||
|
||||
\subsection{Why relative tracking and aperture efficiency differ}
|
||||
|
||||
The aperture metric compares estimated electrical output with measured
|
||||
reference irradiation; the relative-yield metric instead compares against
|
||||
a same-record electrical responsivity. They answer different questions.
|
||||
An anomalously low irradiance reading can inflate both instantaneous aperture
|
||||
efficiency and a maximum-responsivity reference while depressing the
|
||||
maximum-referenced full-record ratio. A stable-looking current trace does
|
||||
not resolve whether a brief discrepancy arose from weather, sensor shading,
|
||||
electrical acquisition or different sensor/device response.
|
||||
|
||||
Consequently, the reference sensitivity must not be compressed into one
|
||||
unqualified tracking-efficiency headline. Even a robust percentile reference
|
||||
remains empirical, reuses the measured voltage and cannot independently
|
||||
measure perfect alignment. Irradiance normalization also cannot distinguish
|
||||
thermal drift from small alignment-induced changes. The record does not
|
||||
validate cloud-recovery time or the causal benefit of a specific protective
|
||||
branch; those require controlled perturbations or independently characterized
|
||||
disturbances.
|
||||
|
||||
\subsection{Interpreting the silicon comparison and next validation}
|
||||
|
||||
The shared-reference scenario places the aperture estimate alongside
|
||||
transparent nominal silicon-efficiency assumptions, without treating the
|
||||
CPV aperture as externally tracked at normal incidence. Its dependencies are
|
||||
the assumed fill factor and silicon efficiency, together with unmeasured
|
||||
temperature and module-specific optical response. The confirmed coplanar sensor
|
||||
provides the incident-irradiance basis for the equal-plane scenario. Different diffuse,
|
||||
spectral and angular responses prevent extrapolating the scenario to annual
|
||||
yield or arbitrary weather. No economic or lifecycle advantage is inferred.
|
||||
|
||||
A simultaneous experiment should measure silicon DC output at MPP, document
|
||||
module area and datasheet parameters, and record tilt, azimuth, coplanar
|
||||
irradiance and module temperature. Equivalent delivered-energy claims also
|
||||
require CPV operation into a measured load rather than alternating
|
||||
$I_{sc}/V_{oc}$ sensing. For net energy, the complete board and motor supply
|
||||
must be logged. Fine-tuning counters omit other moves, and sampled coordinate
|
||||
differences can miss reversals; neither substitutes for supply-energy
|
||||
measurement. The most useful next campaign therefore combines those
|
||||
measurements with fixed documented settings and repeated days, followed by
|
||||
controlled controller-version comparisons.
|
||||
|
||||
\section{Conclusions}
|
||||
\label{sec:conclusions}
|
||||
|
||||
The 4 November 2026 acquisition provides a coherent principal field case for
|
||||
the tracking-integrated WiT-CPV prototype: \NovSamples{} observations,
|
||||
\NovHours{} h of accepted integration support, and no ADC clipping. With
|
||||
a nominal 0.130-$\Omega$ shunt, corrected pyranometer scaling and an assumed
|
||||
$FF=0.82$, the available-MPP energy estimate is \NovEnergy{} Wh for
|
||||
\NovIrradiation{} kWh\,m$^{-2}$ of reference irradiation. The resulting
|
||||
energy-weighted, aperture-referenced estimate is \NovEfficiency\%.
|
||||
These quantities characterize the lens/receiver system against the recorded
|
||||
irradiance, rather than intrinsic cell efficiency or measured harvested energy.
|
||||
|
||||
Linking the response to the solar-position reference and stage trajectory
|
||||
reveals useful operation as well as late degradation. The event-defined
|
||||
12:32--13:53 phase has no additional logged remote commands and yields an
|
||||
aperture estimate of \NovSteadyEfficiency\%, providing a post-tuning operating
|
||||
case alongside the complete-record result. Retaining tuning
|
||||
commands and low-output periods makes the result a characterization of
|
||||
observed operation, not a claim of autonomous full-day lock. A pronounced
|
||||
irradiance anomaly also demonstrates why a same-record maximum cannot be
|
||||
treated as an independently validated ideal-tracking reference.
|
||||
|
||||
Under the shared-pyranometer, constant-efficiency assumptions, the estimated
|
||||
CPV energy corresponds to ratios of \NovSiliconStandardRatio{} and
|
||||
\NovSiliconPremiumRatio{} relative to the 19\% and 21\% equal-area silicon
|
||||
scenarios. These are arithmetic scenario ratios, not measured comparative
|
||||
yields or evidence of superiority over a fixed panel. The decisive next validation is
|
||||
simultaneous delivered-MPP and parasitic-power measurement, with matched receiving
|
||||
planes, measured temperature and fixed control settings. This would turn the present
|
||||
aperture-level characterization into a test of repeatable net system benefit.
|
||||
|
||||
\section*{Reproducibility}
|
||||
The companion analysis retains the raw observations, source-line references,
|
||||
quality flags, accepted integration edges and command chronology. Its
|
||||
machine-readable summary records source hashes and assumptions; the supplied
|
||||
SunCalc table is transcribed separately. Numerical tests cover calibration,
|
||||
gap handling, integration and scenario scaling. All result tables and field
|
||||
figures are regenerated from these inputs, without modifying the raw log.
|
||||
|
||||
\printbibliography
|
||||
\end{document}
|
||||
@@ -0,0 +1,718 @@
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|
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|
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\documentclass[final,1p,times]{elsarticle}
|
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|
||||
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|
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|
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|
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|
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|
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|
||||
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|
||||
@@ -0,0 +1,511 @@
|
||||
@ARTICLE{Fortunato2010,
|
||||
author = {Fortunato, S.},
|
||||
title = {Community detection in graphs},
|
||||
journal = {Phys. Rep.-Rev. Sec. Phys. Lett.},
|
||||
volume = {486},
|
||||
year = {2010},
|
||||
pages = {75-174}
|
||||
}
|
||||
|
||||
@ARTICLE{NewmanGirvan2004,
|
||||
author = {Newman, M. E. J. and Girvan, M.},
|
||||
title = {Finding and evaluating community structure in networks},
|
||||
journal = {Phys. Rev. E.},
|
||||
volume = {69},
|
||||
year = {2004},
|
||||
pages = {026113}
|
||||
}
|
||||
|
||||
@ARTICLE{Vehlowetal2013,
|
||||
author = {Vehlow, C. and Reinhardt, T. and Weiskopf, D.},
|
||||
title = {Visualizing Fuzzy Overlapping Communities in Networks},
|
||||
journal = {IEEE Trans. Vis. Comput. Graph.},
|
||||
volume = {19},
|
||||
year = {2013},
|
||||
pages = {2486-2495}
|
||||
}
|
||||
|
||||
@ARTICLE{Raghavanetal2007,
|
||||
author = {Raghavan, U. and Albert, R. and Kumara, S.},
|
||||
title = {Near linear time algorithm to detect community structures in large-scale networks},
|
||||
journal = {Phys. Rev E.},
|
||||
volume = {76},
|
||||
year = {2007},
|
||||
pages = {036106}
|
||||
}
|
||||
|
||||
@ARTICLE{SubeljBajec2011a,
|
||||
author = {\v{S}ubelj, L. and Bajec, M.},
|
||||
title = {Robust network community detection using balanced propagation},
|
||||
journal = {Eur. Phys. J. B.},
|
||||
volume = {81},
|
||||
year = {2011},
|
||||
pages = {353-362}
|
||||
}
|
||||
|
||||
@ARTICLE{Louetal2013,
|
||||
author = {Lou, H. and Li, S. and Zhao, Y.},
|
||||
title = {Detecting community structure using label propagation with weighted coherent neighborhood propinquity},
|
||||
journal = {Physica A.},
|
||||
volume = {392},
|
||||
year = {2013},
|
||||
pages = {3095-3105}
|
||||
}
|
||||
|
||||
@ARTICLE{Clausetetal2004,
|
||||
author = {Clauset, A. and Newman, M. E. J. and Moore, C.},
|
||||
title = {Finding community structure in very large networks},
|
||||
journal = {Phys. Rev. E.},
|
||||
volume = {70},
|
||||
year = {2004},
|
||||
pages = {066111}
|
||||
}
|
||||
|
||||
@ARTICLE{Blondeletal2008,
|
||||
author = {Blondel, V. D. and Guillaume, J. L. and Lambiotte, R. and Lefebvre, E.},
|
||||
title = {Fast unfolding of communities in large networks},
|
||||
journal = {J. Stat. Mech.-Theory Exp.},
|
||||
volume = {2008},
|
||||
year = {2008},
|
||||
pages = {P10008}
|
||||
}
|
||||
|
||||
@ARTICLE{SobolevskyCampari2014,
|
||||
author = {Sobolevsky, S. and Campari, R.},
|
||||
title = {General optimization technique for high-quality community detection in complex networks},
|
||||
journal = {Phys. Rev. E.},
|
||||
volume = {90},
|
||||
year = {2014},
|
||||
pages = {012811}
|
||||
}
|
||||
|
||||
@ARTICLE{FortunatoBarthelemy2007,
|
||||
author = {Fortunato, S. and Barthelemy, M.},
|
||||
title = {Resolution limit in community detection},
|
||||
journal = {Proc. Natl. Acad. Sci. U. S. A.},
|
||||
volume = {104},
|
||||
year = {2007},
|
||||
pages = {36-41}
|
||||
}
|
||||
|
||||
@ARTICLE{SubeljBajec2011b,
|
||||
author = {\v{S}ubelj, L. and Bajec, M.},
|
||||
title = {Unfolding communities in large complex networks: Combining defensive and offensive label propagation for core extraction},
|
||||
journal = {Phys. Rev. E.},
|
||||
volume = {83},
|
||||
year = {2011},
|
||||
pages = {036103}
|
||||
}
|
||||
|
||||
@ARTICLE{WangLi2013,
|
||||
author = {Wang, X. and Li, J.},
|
||||
title = {Detecting communities by the core-vertex and intimate degree in complex networks},
|
||||
journal = {Physica A.},
|
||||
volume = {392},
|
||||
year = {2013},
|
||||
pages = {2555-2563}
|
||||
}
|
||||
|
||||
@ARTICLE{Lietal2013,
|
||||
author = {Li, J. and Wang, X. and Eustace, J.},
|
||||
title = {Detecting overlapping communities by seed community in weighted complex networks},
|
||||
journal = {Physica A.},
|
||||
volume = {392},
|
||||
year = {2013},
|
||||
pages = {6125-6134}
|
||||
}
|
||||
|
||||
@ARTICLE{Fabioetal2013,
|
||||
author = {Fabio, D. R. and Fabio, D. and Carlo, P.},
|
||||
title = {Profiling core-periphery network structure by random walkers},
|
||||
journal = {Sci. Rep.},
|
||||
volume = {3},
|
||||
year = {2013},
|
||||
pages = {1467}
|
||||
}
|
||||
|
||||
@ARTICLE{Chenetal2013,
|
||||
author = {Chen, Q. and Wu, T. T. and Fang, M.},
|
||||
title = {Detecting local community structure in complex networks based on local degree central nodes},
|
||||
journal = {Physica A.},
|
||||
volume = {392},
|
||||
year = {2013},
|
||||
pages = {529-537}
|
||||
}
|
||||
|
||||
@ARTICLE{Zhangetal2007,
|
||||
author = {Zhang, S. and Wang, R. and Zhang, X.},
|
||||
title = {Identification of overlapping community structure in complex networks using fuzzy c-means clustering},
|
||||
journal = {Physica A.},
|
||||
volume = {374},
|
||||
year = {2007},
|
||||
pages = {483-490}
|
||||
}
|
||||
|
||||
@ARTICLE{Nepuszetal2008,
|
||||
author = {Nepusz, T. and Petr\'oczi, A. and N\'egyessy, L. and Bazs\'o, F.},
|
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|
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}
|
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|
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@ARTICLE{FabricioLiang2013,
|
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author = {Fabricio, B. and Liang, Z.},
|
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|
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journal = {Soft Comput.},
|
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|
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|
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|
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}
|
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|
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@ARTICLE{Sunetal2011,
|
||||
author = {Sun, P. and Gao, L. and Han, S.},
|
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|
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|
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|
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|
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}
|
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|
||||
@ARTICLE{Wangetal2013,
|
||||
author = {Wang, W. and Liu, D. and Liu, X. and Pan, L.},
|
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|
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|
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|
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}
|
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|
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@ARTICLE{Psorakisetal2011,
|
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author = {Psorakis, I. and Roberts, S. and Ebden, M. and Sheldon, B.},
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}
|
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|
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@CONFERENCE{ZhangYeung2012,
|
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|
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|
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|
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|
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@ARTICLE{Havensetal2013,
|
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|
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}
|
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|
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@misc{Newman2013,
|
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|
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howpublished = "\url{http://www-personal.umich.edu/~mejn/netdata/}",
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|
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}
|
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|
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@ARTICLE{SubeljBajec2012,
|
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author = {\v{S}ubelj, L. and Bajec, M.},
|
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|
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|
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|
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|
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}
|
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|
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@ARTICLE{Lancichinettietal2008,
|
||||
author = {Lancichinetti, A. and Fortunato, S. and Radicchi, F.},
|
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|
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|
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}
|
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|
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@ARTICLE{Liuetal2014,
|
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|
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|
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|
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|
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|
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|
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}
|
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|
||||
@ARTICLE{Danonetal2005,
|
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|
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}
|
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|
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@ARTICLE{Gregory2011,
|
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|
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title = {Fuzzy overlapping communities in networks},
|
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journal = {J. Stat. Mech.-Theory Exp.},
|
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volume = {},
|
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year = {2011},
|
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pages = {P02017}
|
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}
|
||||
|
||||
@ARTICLE{LancichinettiFortunato2009,
|
||||
author = {Lancichinetti, A. and Fortunato, S.},
|
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title = {Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities},
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journal = {Phys. Rev. E.},
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|
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year = {2009},
|
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pages = {016118}
|
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}
|
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|
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@CONFERENCE{HullermeierRifqi2009,
|
||||
author = {Hullermeier, E. and Rifqi, M.},
|
||||
title = {A Fuzzy Variant of the Rand Index for Comparing Clustering Structures},
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booktitle = {in Proc. IFSA/EUSFLAT Conf.},
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year = {2009},
|
||||
pages = {1294-1298}
|
||||
}
|
||||
|
||||
|
||||
%%%
|
||||
|
||||
@article{frydrychowicz2013influence,
|
||||
title={The influence of external conditions and orientation of PV module on the energetic gain},
|
||||
author={Frydrychowicz-Jastrz{\k{e}}bska, Gra{\.z}yna and Buga{\l}a, Artur},
|
||||
journal={Computer Applications in Electrical Engineering},
|
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volume={11},
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pages={423--439},
|
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year={2013},
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publisher={Politechnika Pozna{\'n}ska. Wydawnictwo Politechniki Pozna{\'n}skiej}
|
||||
}
|
||||
|
||||
@article{nadia2018advances,
|
||||
title={Advances in solar photovoltaic tracking systems: A review},
|
||||
author={Nadia, AL-Rousan and Isa, Nor Ashidi Mat and Desa, Mohd Khairunaz Mat},
|
||||
journal={Renewable and sustainable energy reviews},
|
||||
volume={82},
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|
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year={2018},
|
||||
publisher={Elsevier}
|
||||
}
|
||||
|
||||
@article{mousazadeh2009review,
|
||||
title={A review of principle and sun-tracking methods for maximizing solar systems output},
|
||||
author={Mousazadeh, Hossein and Keyhani, Alireza and Javadi, Arzhang and Mobli, Hossein and Abrinia, Karen and Sharifi, Ahmad},
|
||||
journal={Renewable and sustainable energy reviews},
|
||||
volume={13},
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|
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pages={1800--1818},
|
||||
year={2009},
|
||||
publisher={Elsevier},
|
||||
doi={10.1016/j.rser.2009.01.022}
|
||||
}
|
||||
|
||||
@article{hafez2018solar,
|
||||
title={Solar tracking systems: Technologies and trackers drive types--A review},
|
||||
author={Hafez, AZ and Yousef, AM and Harag, NM},
|
||||
journal={Renewable and Sustainable Energy Reviews},
|
||||
volume={91},
|
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pages={754--782},
|
||||
year={2018},
|
||||
publisher={Elsevier},
|
||||
doi={10.1016/j.rser.2018.03.094}
|
||||
}
|
||||
|
||||
@article{awasthi2020review,
|
||||
title={Review on sun tracking technology in solar PV system},
|
||||
author={Awasthi, Anshul and Shukla, Akash Kumar and SR, Murali Manohar and Dondariya, Chandrakant and Shukla, KN and Porwal, Deepak and Richhariya, Geetam},
|
||||
journal={Energy Reports},
|
||||
volume={6},
|
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pages={392--405},
|
||||
year={2020},
|
||||
publisher={Elsevier}
|
||||
}
|
||||
|
||||
@article{sadeghi2025review,
|
||||
title={A review and comparative analysis of solar tracking systems},
|
||||
author={Sadeghi, Reza and Parenti, Mattia and Memme, Samuele and Fossa, Marco and Morchio, Stefano},
|
||||
journal={Energies},
|
||||
volume={18},
|
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number={10},
|
||||
pages={2553},
|
||||
year={2025},
|
||||
publisher={MDPI}
|
||||
}
|
||||
|
||||
@article{fuentes2020control,
|
||||
title={Control algorithms applied to active solar tracking systems: A review},
|
||||
author={Fuentes-Morales, Rosa F and Diaz-Ponce, Arturo and Pe{\~n}a-Cruz, Manuel I and Rodrigo, Pedro M and Valent{\'\i}n-Coronado, Luis M and Martell-Chavez, Fernando and Pineda-Arellano, Carlos A},
|
||||
journal={Solar Energy},
|
||||
volume={212},
|
||||
pages={203--219},
|
||||
year={2020},
|
||||
publisher={Elsevier},
|
||||
doi={10.1016/j.solener.2020.10.071}
|
||||
}
|
||||
|
||||
@article{sumathi2017solar,
|
||||
title={Solar tracking methods to maximize PV system output--A review of the methods adopted in recent decade},
|
||||
author={Sumathi, Vijayan and Jayapragash, R and Bakshi, Abhinav and Akella, Praveen Kumar},
|
||||
journal={Renewable and Sustainable Energy Reviews},
|
||||
volume={74},
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||||
pages={130--138},
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||||
year={2017},
|
||||
publisher={Elsevier}
|
||||
}
|
||||
|
||||
@article{antonini2010photovoltaic,
|
||||
title={Photovoltaic Concentrators-Fundamentals, Applications, Market \& Prospective},
|
||||
author={Antonini, Andrea},
|
||||
journal={Sol. Collect. Panels, Theory Appl., Sciyo},
|
||||
pages={31--54},
|
||||
year={2010}
|
||||
}
|
||||
|
||||
@article{iqbal2023optical,
|
||||
title={Optical developments in concentrator photovoltaic systems—a review},
|
||||
author={Iqbal, Waseem and Ullah, Irfan and Shin, Seoyong},
|
||||
journal={Sustainability},
|
||||
volume={15},
|
||||
number={13},
|
||||
pages={10554},
|
||||
year={2023},
|
||||
publisher={MDPI},
|
||||
doi={10.3390/su151310554}
|
||||
}
|
||||
|
||||
@article{ceballos2023tracking,
|
||||
title={Tracking-Integrated {CPV} Technology: State-of-the-Art and Classification},
|
||||
author={Ceballos, Maria A and P{\'e}rez-Higueras, Pedro J and Fern{\'a}ndez, Eduardo F and Almonacid, Florencia M},
|
||||
journal={Energies},
|
||||
volume={16},
|
||||
number={15},
|
||||
pages={5605},
|
||||
year={2023},
|
||||
publisher={MDPI},
|
||||
doi={10.3390/en16155605}
|
||||
}
|
||||
|
||||
@article{angulo2022development,
|
||||
title={Development and accuracy assessment of a high-precision dual-axis pre-commercial solar tracker for concentrating photovoltaic modules},
|
||||
author={Angulo-Calder{\'o}n, Marthoz and Salgado-Tr{\'a}nsito, Iv{\'a}n and Trejo-Z{\'u}{\~n}iga, Iv{\'a}n and Paredes-Orta, Carlos and Kesthkar, Sajjad and D{\'\i}az-Ponce, Arturo},
|
||||
journal={Applied Sciences},
|
||||
volume={12},
|
||||
number={5},
|
||||
pages={2625},
|
||||
year={2022},
|
||||
publisher={MDPI}
|
||||
}
|
||||
|
||||
@article{ito2018optical,
|
||||
title={Optical design and demonstration of microtracking {CPV} module with bi-convex aspheric lens array},
|
||||
author={Ito, Atsushi and Sato, Daisuke and Yamada, Noboru},
|
||||
journal={Optics Express},
|
||||
volume={26},
|
||||
number={18},
|
||||
pages={A879--A891},
|
||||
year={2018},
|
||||
publisher={OSA},
|
||||
doi={10.1364/OE.26.00A879}
|
||||
}
|
||||
|
||||
@inproceedings{askins2019performance,
|
||||
title={Performance of hybrid micro-concentrator module with integrated planar tracking and diffuse light collection},
|
||||
author={Askins, S. and Petri, D. and Levrat, J. and Faes, A. and
|
||||
Champliaud, J. and Despeisse, M. and Dominguez, C. and Anton, I. and
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||||
Jost, N. and Aguilar, A. F. and Anglade, L. and Nardin, G. and
|
||||
Duchemin, M. and Gerlich, F. and Ackerman, M. and Coulot, L.},
|
||||
booktitle={2019 IEEE 46th Photovoltaic Specialists Conference (PVSC)},
|
||||
pages={2507--2512},
|
||||
year={2019},
|
||||
organization={IEEE},
|
||||
doi={10.1109/PVSC40753.2019.8980519}
|
||||
}
|
||||
|
||||
@article{younes2022realizing,
|
||||
title={Realizing high photovoltaic power densities with tracking-integrated concentrator photovoltaics},
|
||||
author={Younes, Kareem and Apostoleris, Harry and Bin Saad, Majed and Al Ghaferi, Amal and Chiesa, Matteo},
|
||||
journal={Frontiers in Energy Research},
|
||||
volume={10},
|
||||
pages={842201},
|
||||
year={2022},
|
||||
publisher={Frontiers Media SA},
|
||||
doi={10.3389/fenrg.2022.842201}
|
||||
}
|
||||
|
||||
@article{maestro2025fabrication,
|
||||
title={Fabrication and experimental validation of a building-integrated microtracking CPV system},
|
||||
author={Maestro, Santiago and Chemisana, D and Baig, Hasan},
|
||||
journal={Renewable Energy},
|
||||
pages={124508},
|
||||
year={2025},
|
||||
publisher={Elsevier}
|
||||
}
|
||||
|
||||
@article{diasponce2025development,
|
||||
title={Development of a proof-of-concept concentrating photovoltaic module with integrated tracking and azimuthal cell rotation},
|
||||
author={D{\'i}az-Ponce, Arturo and Trejo-Z{\'u}{\~n}iga, Iv{\'a}n and D{\'a}valos Hern{\'a}ndez, Fernando and Rodrigo, Pedro M and Ceballos, Mar{\'\i}a A and Valera-Albacete, {\'A}lvaro and Almonacid, Florencia and Fern{\'a}ndez, Eduardo F},
|
||||
journal={Results in Engineering},
|
||||
volume={27},
|
||||
pages={106735},
|
||||
year={2025},
|
||||
publisher={Elsevier},
|
||||
doi={10.1016/j.rineng.2025.106735}
|
||||
}
|
||||
|
||||
@online{pvwatts_module_type,
|
||||
author = {{PVWatts}},
|
||||
title = {Module Type},
|
||||
url = {https://pvwatts.nlr.gov/docs/help_module_type.php},
|
||||
urldate = {2026-11-04},
|
||||
note = {Standard and Premium crystalline-silicon module assumptions}
|
||||
}
|
||||
|
||||
@online{sandia_poa,
|
||||
author = {{Sandia National Laboratories}},
|
||||
title = {Plane of Array ({POA}) Irradiance},
|
||||
organization = {PV Performance Modeling Collaborative},
|
||||
url = {https://pvpmc.sandia.gov/modeling-guide/1-weather-design-inputs/plane-of-array-poa-irradiance/},
|
||||
urldate = {2026-11-04}
|
||||
}
|
||||
|
||||
@online{sandia_pvwatts,
|
||||
author = {{Sandia National Laboratories}},
|
||||
title = {{PVWatts}},
|
||||
organization = {PV Performance Modeling Collaborative},
|
||||
url = {https://pvpmc.sandia.gov/modeling-guide/2-dc-module-iv/point-value-models/pvwatts/},
|
||||
urldate = {2026-11-04}
|
||||
}
|
||||
|
||||
@manual{apogee_sp212_manual,
|
||||
author = {{Apogee Instruments}},
|
||||
title = {{SP-212/SP-215} Pyranometer Instruction Manual},
|
||||
url = {https://www.apogeeinstruments.com/content/SP-212-215-manual.pdf},
|
||||
urldate = {2026-11-04}
|
||||
}
|
||||
|
||||
@misc{suncalc2026,
|
||||
author = {Hoffmann, Torsten},
|
||||
title = {{SunCalc}: Daily Solar-Position Data for Aguascalientes, 4 November 2026},
|
||||
year = {2026},
|
||||
url = {https://www.suncalc.org/},
|
||||
urldate = {2026-11-04},
|
||||
note = {Supplied printout at latitude 21.87304 degrees N and longitude
|
||||
102.28282 degrees W; local-time azimuth and elevation at 15-minute intervals}
|
||||
}
|
||||
@@ -0,0 +1,418 @@
|
||||
[
|
||||
{
|
||||
"file": "hasta la 1pm 020925.txt",
|
||||
"label": "02 Sep 11:27-13:00",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-02 11:28:46",
|
||||
"t_fin": "2025-09-02 13:30:54",
|
||||
"n_samples": 2289,
|
||||
"eta_tr_pct": 33.59,
|
||||
"MAE_P_mW": 85.04,
|
||||
"E_Wh": 0.089,
|
||||
"H_kWh_m2": 0.9187,
|
||||
"ratio_P_Pref_median": 0.131,
|
||||
"frac_P_above_095Pref": 0.018,
|
||||
"G_max_Wm2": 1007.7,
|
||||
"n_clip": 0,
|
||||
"clip_pct_day": 0.0,
|
||||
"clip_min": 0.0,
|
||||
"R_opt_uA_per_Wm2": 157.3,
|
||||
"R_opt_unc_uA_per_Wm2": 157.3,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 33.59,
|
||||
"n_cloud_events": 4
|
||||
},
|
||||
{
|
||||
"file": "esp_1223_02092025.txt",
|
||||
"label": "02 Sep 12:23-..",
|
||||
"fmt": "old",
|
||||
"error": "KeyError: 'cmd'"
|
||||
},
|
||||
{
|
||||
"file": "log(3).txt",
|
||||
"label": "14 Sep (manana)",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-14 10:03:36",
|
||||
"t_fin": "2025-09-14 14:15:37",
|
||||
"n_samples": 7544,
|
||||
"eta_tr_pct": 49.36,
|
||||
"MAE_P_mW": 138.77,
|
||||
"E_Wh": 0.56,
|
||||
"H_kWh_m2": 2.5917,
|
||||
"ratio_P_Pref_median": 0.288,
|
||||
"frac_P_above_095Pref": 0.029,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 1189,
|
||||
"clip_pct_day": 15.8,
|
||||
"clip_min": 39.6,
|
||||
"R_opt_uA_per_Wm2": 232.7,
|
||||
"R_opt_unc_uA_per_Wm2": 213.0,
|
||||
"inflation_factor": 1.0929,
|
||||
"eta_tr_pct_Ropt_corrected": 53.94,
|
||||
"n_cloud_events": 10
|
||||
},
|
||||
{
|
||||
"file": "gyuggyhoy.txt",
|
||||
"label": "14 Sep 10:28-..",
|
||||
"fmt": "old",
|
||||
"t_inicio": "2025-09-14 10:28:12",
|
||||
"t_fin": "2025-09-14 14:57:34",
|
||||
"n_samples": 8076,
|
||||
"eta_tr_pct": 52.33,
|
||||
"MAE_P_mW": 136.72,
|
||||
"E_Wh": 0.674,
|
||||
"H_kWh_m2": 2.9318,
|
||||
"ratio_P_Pref_median": 0.418,
|
||||
"frac_P_above_095Pref": 0.009,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 1189,
|
||||
"clip_pct_day": 14.7,
|
||||
"clip_min": 39.6,
|
||||
"R_opt_uA_per_Wm2": 232.7,
|
||||
"R_opt_unc_uA_per_Wm2": 213.0,
|
||||
"inflation_factor": 1.0929,
|
||||
"eta_tr_pct_Ropt_corrected": 57.19,
|
||||
"n_cloud_events": 10
|
||||
},
|
||||
{
|
||||
"file": "10092025.txt",
|
||||
"label": "10 Sep",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-10 10:17:05",
|
||||
"t_fin": "2025-09-10 16:39:04",
|
||||
"n_samples": 9055,
|
||||
"eta_tr_pct": 48.3,
|
||||
"MAE_P_mW": 109.38,
|
||||
"E_Wh": 0.659,
|
||||
"H_kWh_m2": 3.0884,
|
||||
"ratio_P_Pref_median": 0.092,
|
||||
"frac_P_above_095Pref": 0.012,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 1577,
|
||||
"clip_pct_day": 17.4,
|
||||
"clip_min": 52.6,
|
||||
"R_opt_uA_per_Wm2": 250.9,
|
||||
"R_opt_unc_uA_per_Wm2": 250.9,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 48.3,
|
||||
"n_cloud_events": 7
|
||||
},
|
||||
{
|
||||
"file": "15092025.txt",
|
||||
"label": "15 Sep",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-15 11:40:37",
|
||||
"t_fin": "2025-09-15 14:53:18",
|
||||
"n_samples": 4641,
|
||||
"eta_tr_pct": 56.0,
|
||||
"MAE_P_mW": 73.47,
|
||||
"E_Wh": 0.3,
|
||||
"H_kWh_m2": 1.3408,
|
||||
"ratio_P_Pref_median": 0.075,
|
||||
"frac_P_above_095Pref": 0.077,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 1186,
|
||||
"clip_pct_day": 25.6,
|
||||
"clip_min": 39.5,
|
||||
"R_opt_uA_per_Wm2": 231.5,
|
||||
"R_opt_unc_uA_per_Wm2": 200.3,
|
||||
"inflation_factor": 1.1556,
|
||||
"eta_tr_pct_Ropt_corrected": 64.71,
|
||||
"n_cloud_events": 5
|
||||
},
|
||||
{
|
||||
"file": "19092025_.txt",
|
||||
"label": "19 Sep",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-19 09:36:54",
|
||||
"t_fin": "2025-09-19 16:34:12",
|
||||
"n_samples": 11395,
|
||||
"eta_tr_pct": 33.94,
|
||||
"MAE_P_mW": 222.87,
|
||||
"E_Wh": 0.804,
|
||||
"H_kWh_m2": 3.6224,
|
||||
"ratio_P_Pref_median": 0.081,
|
||||
"frac_P_above_095Pref": 0.016,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 2212,
|
||||
"clip_pct_day": 19.4,
|
||||
"clip_min": 73.7,
|
||||
"R_opt_uA_per_Wm2": 373.2,
|
||||
"R_opt_unc_uA_per_Wm2": 373.2,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 33.94,
|
||||
"n_cloud_events": 7
|
||||
},
|
||||
{
|
||||
"file": "20092025_desde1pm.txt",
|
||||
"label": "20 Sep (desde 13:44)",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-20 13:44:52",
|
||||
"t_fin": "2025-09-20 15:08:30",
|
||||
"n_samples": 3640,
|
||||
"eta_tr_pct": 69.65,
|
||||
"MAE_P_mW": 72.21,
|
||||
"E_Wh": 0.243,
|
||||
"H_kWh_m2": 1.0505,
|
||||
"ratio_P_Pref_median": 0.66,
|
||||
"frac_P_above_095Pref": 0.018,
|
||||
"G_max_Wm2": 979.7,
|
||||
"n_clip": 0,
|
||||
"clip_pct_day": 0.0,
|
||||
"clip_min": 0.0,
|
||||
"R_opt_uA_per_Wm2": 181.6,
|
||||
"R_opt_unc_uA_per_Wm2": 181.6,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 69.65,
|
||||
"n_cloud_events": 1
|
||||
},
|
||||
{
|
||||
"file": "21092025.txt",
|
||||
"label": "21 Sep (paper)",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-21 10:40:58",
|
||||
"t_fin": "2025-09-21 17:02:34",
|
||||
"n_samples": 11206,
|
||||
"eta_tr_pct": 67.28,
|
||||
"MAE_P_mW": 72.39,
|
||||
"E_Wh": 0.927,
|
||||
"H_kWh_m2": 3.3291,
|
||||
"ratio_P_Pref_median": 0.433,
|
||||
"frac_P_above_095Pref": 0.102,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 3011,
|
||||
"clip_pct_day": 26.9,
|
||||
"clip_min": 100.4,
|
||||
"R_opt_uA_per_Wm2": 228.9,
|
||||
"R_opt_unc_uA_per_Wm2": 221.7,
|
||||
"inflation_factor": 1.0324,
|
||||
"eta_tr_pct_Ropt_corrected": 69.46,
|
||||
"n_cloud_events": 5
|
||||
},
|
||||
{
|
||||
"file": "21092025_2PM.txt",
|
||||
"label": "21 Sep (parcial, dup.)",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-21 10:40:58",
|
||||
"t_fin": "2025-09-21 13:56:04",
|
||||
"n_samples": 5830,
|
||||
"eta_tr_pct": 72.43,
|
||||
"MAE_P_mW": 91.74,
|
||||
"E_Wh": 0.788,
|
||||
"H_kWh_m2": 2.5026,
|
||||
"ratio_P_Pref_median": 0.636,
|
||||
"frac_P_above_095Pref": 0.186,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 2614,
|
||||
"clip_pct_day": 44.8,
|
||||
"clip_min": 87.1,
|
||||
"R_opt_uA_per_Wm2": 228.9,
|
||||
"R_opt_unc_uA_per_Wm2": 221.7,
|
||||
"inflation_factor": 1.0324,
|
||||
"eta_tr_pct_Ropt_corrected": 74.77,
|
||||
"n_cloud_events": 1
|
||||
},
|
||||
{
|
||||
"file": "23092025.txt",
|
||||
"label": "23 Sep",
|
||||
"fmt": "new",
|
||||
"t_inicio": "2025-09-23 10:27:26",
|
||||
"t_fin": "2025-09-23 15:18:57",
|
||||
"n_samples": 8694,
|
||||
"eta_tr_pct": 60.91,
|
||||
"MAE_P_mW": 146.42,
|
||||
"E_Wh": 1.11,
|
||||
"H_kWh_m2": 3.9028,
|
||||
"ratio_P_Pref_median": 0.555,
|
||||
"frac_P_above_095Pref": 0.0,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 3043,
|
||||
"clip_pct_day": 35.0,
|
||||
"clip_min": 101.4,
|
||||
"R_opt_uA_per_Wm2": 248.6,
|
||||
"R_opt_unc_uA_per_Wm2": 248.6,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 60.91,
|
||||
"n_cloud_events": 7
|
||||
},
|
||||
{
|
||||
"file": "full_log_21082025.txt",
|
||||
"label": "21 Ago (log completo)",
|
||||
"fmt": "old",
|
||||
"t_inicio": "2025-08-21 11:24:01",
|
||||
"t_fin": "2025-08-21 13:17:47",
|
||||
"n_samples": 5533,
|
||||
"eta_tr_pct": 57.17,
|
||||
"MAE_P_mW": 92.05,
|
||||
"E_Wh": 0.223,
|
||||
"H_kWh_m2": 0.991,
|
||||
"ratio_P_Pref_median": 0.353,
|
||||
"frac_P_above_095Pref": 0.057,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 316,
|
||||
"clip_pct_day": 5.7,
|
||||
"clip_min": 5.3,
|
||||
"R_opt_uA_per_Wm2": 207.1,
|
||||
"R_opt_unc_uA_per_Wm2": 206.1,
|
||||
"inflation_factor": 1.0047,
|
||||
"eta_tr_pct_Ropt_corrected": 57.44,
|
||||
"n_cloud_events": 5
|
||||
},
|
||||
{
|
||||
"file": "esp32_log_20250821_102525.txt",
|
||||
"label": "21 Ago 10:25",
|
||||
"fmt": "old",
|
||||
"t_inicio": "2025-08-21 11:24:01",
|
||||
"t_fin": "2025-08-21 11:54:47",
|
||||
"n_samples": 1732,
|
||||
"eta_tr_pct": 71.07,
|
||||
"MAE_P_mW": 63.16,
|
||||
"E_Wh": 0.086,
|
||||
"H_kWh_m2": 0.3349,
|
||||
"ratio_P_Pref_median": 0.715,
|
||||
"frac_P_above_095Pref": 0.238,
|
||||
"G_max_Wm2": 915.9,
|
||||
"n_clip": 0,
|
||||
"clip_pct_day": 0.0,
|
||||
"clip_min": 0.0,
|
||||
"R_opt_uA_per_Wm2": 181.3,
|
||||
"R_opt_unc_uA_per_Wm2": 181.3,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 71.07,
|
||||
"n_cloud_events": 3
|
||||
},
|
||||
{
|
||||
"file": "esp32_log_20250821_1143.txt",
|
||||
"label": "21 Ago 11:43",
|
||||
"fmt": "old",
|
||||
"error": "ValueError: Sin muestras X,Y,C,V,P en el log."
|
||||
},
|
||||
{
|
||||
"file": "esp32_log_20250826_114833.txt",
|
||||
"label": "26 Ago 11:48",
|
||||
"fmt": "old",
|
||||
"error": "KeyError: 'cmd'"
|
||||
},
|
||||
{
|
||||
"file": "esp32_log_20250827_095607.txt",
|
||||
"label": "27 Ago 09:56",
|
||||
"fmt": "old",
|
||||
"t_inicio": "2025-08-27 09:58:22",
|
||||
"t_fin": "2025-08-27 10:37:00",
|
||||
"n_samples": 983,
|
||||
"eta_tr_pct": 21.3,
|
||||
"MAE_P_mW": 29.22,
|
||||
"E_Wh": 0.005,
|
||||
"H_kWh_m2": 0.234,
|
||||
"ratio_P_Pref_median": 0.159,
|
||||
"frac_P_above_095Pref": 0.002,
|
||||
"G_max_Wm2": 948.4,
|
||||
"n_clip": 0,
|
||||
"clip_pct_day": 0.0,
|
||||
"clip_min": 0.0,
|
||||
"R_opt_uA_per_Wm2": 61.5,
|
||||
"R_opt_unc_uA_per_Wm2": 61.5,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 21.3,
|
||||
"n_cloud_events": 1
|
||||
},
|
||||
{
|
||||
"file": "esp32_log_20250827_110728.txt",
|
||||
"label": "27 Ago 11:07",
|
||||
"fmt": "old",
|
||||
"t_inicio": "2025-08-27 11:07:56",
|
||||
"t_fin": "2025-08-27 14:02:46",
|
||||
"n_samples": 5104,
|
||||
"eta_tr_pct": 40.63,
|
||||
"MAE_P_mW": 158.59,
|
||||
"E_Wh": 0.317,
|
||||
"H_kWh_m2": 2.0504,
|
||||
"ratio_P_Pref_median": 0.035,
|
||||
"frac_P_above_095Pref": 0.154,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 2175,
|
||||
"clip_pct_day": 42.6,
|
||||
"clip_min": 72.5,
|
||||
"R_opt_uA_per_Wm2": 229.5,
|
||||
"R_opt_unc_uA_per_Wm2": 206.4,
|
||||
"inflation_factor": 1.112,
|
||||
"eta_tr_pct_Ropt_corrected": 45.18,
|
||||
"n_cloud_events": 9
|
||||
},
|
||||
{
|
||||
"file": "esp32_log_20250827_449pm.txt",
|
||||
"label": "27 Ago 16:49",
|
||||
"fmt": "old",
|
||||
"t_inicio": "2025-08-27 16:37:21",
|
||||
"t_fin": "2025-08-27 16:47:54",
|
||||
"n_samples": 309,
|
||||
"eta_tr_pct": 38.35,
|
||||
"MAE_P_mW": 13.15,
|
||||
"E_Wh": 0.001,
|
||||
"H_kWh_m2": 0.074,
|
||||
"ratio_P_Pref_median": 0.342,
|
||||
"frac_P_above_095Pref": 0.023,
|
||||
"G_max_Wm2": 891.9,
|
||||
"n_clip": 0,
|
||||
"clip_pct_day": 0.0,
|
||||
"clip_min": 0.0,
|
||||
"R_opt_uA_per_Wm2": 32.4,
|
||||
"R_opt_unc_uA_per_Wm2": 32.4,
|
||||
"inflation_factor": 1.0,
|
||||
"eta_tr_pct_Ropt_corrected": 38.35,
|
||||
"n_cloud_events": 1
|
||||
},
|
||||
{
|
||||
"file": "log_26082025.txt",
|
||||
"label": "26 Ago (corto)",
|
||||
"fmt": "old",
|
||||
"error": "KeyError: 'cmd'"
|
||||
},
|
||||
{
|
||||
"file": "log_2608205_2.txt",
|
||||
"label": "26 Ago (corto)",
|
||||
"fmt": "old",
|
||||
"t_inicio": "2025-08-26 11:48:51",
|
||||
"t_fin": "2025-08-26 13:26:53",
|
||||
"n_samples": 928,
|
||||
"eta_tr_pct": 31.01,
|
||||
"MAE_P_mW": 92.79,
|
||||
"E_Wh": 0.067,
|
||||
"H_kWh_m2": 0.6262,
|
||||
"ratio_P_Pref_median": 0.107,
|
||||
"frac_P_above_095Pref": 0.088,
|
||||
"G_max_Wm2": 1024.0,
|
||||
"n_clip": 103,
|
||||
"clip_pct_day": 11.1,
|
||||
"clip_min": 3.4,
|
||||
"R_opt_uA_per_Wm2": 208.6,
|
||||
"R_opt_unc_uA_per_Wm2": 204.2,
|
||||
"inflation_factor": 1.0215,
|
||||
"eta_tr_pct_Ropt_corrected": 31.68,
|
||||
"n_cloud_events": 2
|
||||
},
|
||||
{
|
||||
"file": "nuevolog}.txt",
|
||||
"label": "26 Ago 13:28",
|
||||
"fmt": "old",
|
||||
"error": "KeyError: 'cmd'"
|
||||
},
|
||||
{
|
||||
"file": "test_2108.txt",
|
||||
"label": "21 Ago (test)",
|
||||
"fmt": "old",
|
||||
"error": "KeyError: 'cmd'"
|
||||
},
|
||||
{
|
||||
"file": "test_3.txt",
|
||||
"label": "21 Ago (test)",
|
||||
"fmt": "old",
|
||||
"error": "KeyError: 'cmd'"
|
||||
},
|
||||
{
|
||||
"file": "test_$.txt",
|
||||
"label": "21 Ago (test)",
|
||||
"fmt": "old",
|
||||
"error": "KeyError: 'cmd'"
|
||||
}
|
||||
]
|
||||
@@ -0,0 +1 @@
|
||||
Tectonic 0.17.0
|
||||
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|
||||
**
|
||||
(pcbtoplvl.tex
|
||||
LaTeX2e <2021-11-15> patch level 1
|
||||
L3 programming layer <2022-02-24> (standalone.cls
|
||||
Document Class: standalone 2018/03/26 v1.3a Class to compile TeX sub-files stan
|
||||
dalone
|
||||
(shellesc.sty
|
||||
Package: shellesc 2019/11/08 v1.0c unified shell escape interface for LaTeX
|
||||
|
||||
|
||||
Package shellesc Warning: Shell escape disabled on input line 73.
|
||||
|
||||
) (ifluatex.sty
|
||||
Package: ifluatex 2019/10/25 v1.5 ifluatex legacy package. Use iftex instead.
|
||||
(iftex.sty
|
||||
Package: iftex 2022/02/03 v1.0f TeX engine tests
|
||||
)) (xkeyval.sty
|
||||
Package: xkeyval 2020/11/20 v2.8 package option processing (HA)
|
||||
(xkeyval (xkvutils
|
||||
\XKV@toks=\toks16
|
||||
\XKV@tempa@toks=\toks17
|
||||
(keyval))
|
||||
\XKV@depth=\count181
|
||||
File: xkeyval.tex 2014/12/03 v2.7a key=value parser (HA)
|
||||
))
|
||||
\sa@internal=\count182
|
||||
\c@sapage=\count183
|
||||
|
||||
(standalone.cfg
|
||||
File: standalone.cfg 2018/03/26 v1.3a Default configuration file for 'standalon
|
||||
e' class
|
||||
) (article.cls
|
||||
Document Class: article 2021/10/04 v1.4n Standard LaTeX document class
|
||||
(size10.clo
|
||||
File: size10.clo 2021/10/04 v1.4n Standard LaTeX file (size option)
|
||||
)
|
||||
\c@part=\count184
|
||||
\c@section=\count185
|
||||
\c@subsection=\count186
|
||||
\c@subsubsection=\count187
|
||||
\c@paragraph=\count188
|
||||
\c@subparagraph=\count189
|
||||
\c@figure=\count190
|
||||
\c@table=\count191
|
||||
\abovecaptionskip=\skip47
|
||||
\belowcaptionskip=\skip48
|
||||
\bibindent=\dimen138
|
||||
)
|
||||
\sa@box=\box50
|
||||
) (inputenc.sty
|
||||
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<recently read> \text
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l.30 ...\text{I}^2\text{C}$ (SDA, SCL)} (esp.west)
|
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% Generated by analyze_2026_11_04.py.
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% !TEX program = pdflatex
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\begin{document}
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\begin{tikzpicture}[american, font=\sffamily\small, >=Latex]
|
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|
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% ==========================================
|
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% 1. ENTRADAS A LA IZQUIERDA (CPV Cell)
|
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% ==========================================
|
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|
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(0,0) node[left, font=\bfseries] {HCPV Cell (-)} to[short, o-*] (2,0) node[ground]{};
|
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|
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% ==========================================
|
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% 2. PRIMERA ETAPA: DIVISOR DE VOLTAJE (Voc)
|
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% ==========================================
|
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\draw (2,4) to[R, l=$R_1\ (10\text{ k}\Omega)$, *-*] (2,2)
|
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to[R, l=$R_2\ (10\text{ k}\Omega)$, *-*] (2,0);
|
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|
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% Salida de Voc directamente hacia la derecha
|
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\draw (2,2) to[short, *-o] (11.5,2)
|
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node[right, font=\bfseries\color{blue!80!black}] {To ADS122C04 AIN3 ($V_{oc}$)};
|
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|
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% ==========================================
|
||||
% 3. SEGUNDA ETAPA: TRANSISTOR Q1 (INVERTIDO EN Y) Y GATE DRIVER
|
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% ==========================================
|
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% MOSFET Q1 invertido en el eje Y mediante yscale=-1
|
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\node[right=1cm of Q1] {\textbf{$Q_1$}\\[-2pt]\scriptsize DMN62D0UW-7};
|
||||
|
||||
% Gate Driver MIC5019 (Directamente ARRIBA del MOSFET)
|
||||
\node[draw, rectangle, rounded corners=3pt, fill=blue!10, minimum width=2.4cm, minimum height=1.2cm, align=center, line width=0.8pt]
|
||||
(mic) at (5.95,5.5) {\textbf{Gate Driver}\\\footnotesize MIC5019};
|
||||
|
||||
% Entrada de señal de control (A LA DERECHA del Gate Driver)
|
||||
\draw[<-, line width=1pt, color=blue!80!black] (mic.east) -- (10.0, 5.5)
|
||||
node[right, font=\bfseries] {From ESP32 (\texttt{PIN\_VOC})};
|
||||
|
||||
% Conexión de salida del Driver a la Gate del MOSFET
|
||||
\draw[->, line width=0.8pt] (mic.south) |- (Q1.G);
|
||||
|
||||
% Bus CPV(+) conectado al terminal superior del MOSFET
|
||||
\draw (2,4) -- (5,4) -- (Q1.S);
|
||||
|
||||
% Conexión del terminal inferior del MOSFET a la Resistencia Shunt
|
||||
\draw (Q1.D) -- (5,1.8)
|
||||
to[R, l=$R_{\text{shunt}}\ (75\text{ m}\Omega)$, *-*] (5,0) -- (2,0);
|
||||
|
||||
% ==========================================
|
||||
% 4. TERCERA ETAPA: SHUNT Y AMPLIFICADOR AD8418
|
||||
% ==========================================
|
||||
% Amplificador AD8418 (A LA DERECHA de la Shunt)
|
||||
\node[draw, rectangle, rounded corners=3pt, fill=orange!10, minimum width=2.5cm, minimum height=1.4cm, align=center, line width=0.8pt]
|
||||
(ad) at (8.8,0.9) {\textbf{AD8418}\\[-2pt]\footnotesize Current Sense Amp};
|
||||
|
||||
% Lectura Diferencial sobre la Shunt
|
||||
\draw (5,1.8) -- (7.0,1.8) |- (ad.west |- 0,1.2);
|
||||
\draw (5,0.2) -- (7.0,0.2) |- (ad.west |- 0,0.6);
|
||||
|
||||
% Salida de Isc directamente hacia la derecha
|
||||
\draw[->, line width=1pt] (ad.east) -- (11.5,0.9)
|
||||
node[right, font=\bfseries\color{orange!80!black}] {To ADS122C04 AIN0/1 ($I_{sc}$)};
|
||||
|
||||
\end{tikzpicture}
|
||||
|
||||
\end{document}
|
||||
@@ -0,0 +1,93 @@
|
||||
% !TEX program = pdflatex
|
||||
\documentclass{standalone}
|
||||
\usepackage[utf8]{inputenc}
|
||||
\usepackage{amsmath}
|
||||
\usepackage{tikz}
|
||||
\usetikzlibrary{shapes.geometric, positioning, arrows.meta, calc, fit, backgrounds}
|
||||
|
||||
\begin{document}
|
||||
|
||||
\begin{tikzpicture}[
|
||||
font=\sffamily\small,
|
||||
>=Latex,
|
||||
mcu/.style={draw=blue!80!black, rectangle, rounded corners=4pt, fill=blue!10, minimum width=3.6cm, minimum height=4.2cm, align=center, line width=1.2pt},
|
||||
adc/.style={draw=orange!80!black, rectangle, rounded corners=4pt, fill=orange!10, minimum width=2.8cm, minimum height=3.6cm, align=center, line width=1pt},
|
||||
block/.style={draw, rectangle, rounded corners=3pt, fill=yellow!10, minimum width=3.4cm, minimum height=1.1cm, align=center, line width=0.8pt},
|
||||
driver/.style={draw=green!60!black, rectangle, rounded corners=3pt, fill=green!10, minimum width=2.6cm, minimum height=1.1cm, align=center, line width=0.8pt},
|
||||
cloud/.style={draw=cyan!80!black, ellipse, fill=cyan!10, minimum width=3.6cm, minimum height=1.4cm, align=center, line width=1pt},
|
||||
motor/.style={draw=purple!80!black, circle, fill=purple!10, minimum size=1.1cm, align=center, line width=0.8pt},
|
||||
bus/.style={line width=1.2pt, <->},
|
||||
sig/.style={line width=0.8pt, ->}
|
||||
]
|
||||
|
||||
% ==========================================
|
||||
% 1. NÚCLEO CENTRAL (ESP32 y ADC)
|
||||
% ==========================================
|
||||
\node[mcu] (esp) {\textbf{ESP32 MCU}\\[3pt]\footnotesize Dual-Core 32-bit\\[2pt]\scriptsize WebServer \& WebSockets\\[1pt]\scriptsize NVS Memory};
|
||||
|
||||
\node[adc, below=-3.14cm of esp, left=2.26cm of esp] (adc) {\textbf{ADS122C04}\\[2pt]\footnotesize 24-Bit $\Delta\Sigma$ ADC};
|
||||
|
||||
% Bus I2C entre ADC y ESP32
|
||||
\draw[bus] (-4.1,0) -- node[above, font=\scriptsize] {$\text{I}^2\text{C}$ (SDA, SCL)} (esp.west);
|
||||
|
||||
% ==========================================
|
||||
% 2. NUBE Y TELEMETRÍA (ARRIBA)
|
||||
% ==========================================
|
||||
\node[cloud, above=1.8cm of esp] (cloud) {\textbf{Cloud Platform}\\[-1pt]\footnotesize Monitoring \& Backup};
|
||||
\draw[bus, dashed, cyan!80!black] (esp.north) -- node[right, font=\scriptsize, text=cyan!80!black, near end] {WiFi / HTTP / WS} (cloud.south);
|
||||
|
||||
% ==========================================
|
||||
% 3. SENSORES E INSUMOS (COLUMNA IZQUIERDA)
|
||||
% ==========================================
|
||||
\node[block, anchor=north east, below=2.09cm of adc.north west, left=2.18cm of adc.north west] (pira) {\textbf{Pyranometer}\\[-1pt]\scriptsize (Apogee SP-212)};
|
||||
|
||||
\node[block, fill=red!10, draw=red!70!black, above=0.31cm of pira] (cpv) {\textbf{HCPV Sensing Circuit}\\[-2pt]\scriptsize $I_{sc}$ / $V_{oc}$ Switching \& Cond.};
|
||||
|
||||
|
||||
% Conexiones analógicas al ADC
|
||||
\draw[sig] (pira.east) -- node[above=1pt, font=\scriptsize, pos=0.42] {AIN2 ($G_{POA}$)} (adc.west |- pira.east);
|
||||
\draw[sig] ($(cpv.east)+(0,0.2)$) -- node[above, font=\scriptsize, pos=0.44] {AIN0/1 ($I_{sc}$)} ($(adc.west |- cpv.east)+(0,0.2)$);
|
||||
\draw[sig] ($(cpv.east)+(0,-0.2)$) -- node[below, font=\scriptsize, pos=0.43] {AIN3 ($V_{oc}$)} ($(adc.west |- cpv.east)+(0,-0.2)$);
|
||||
% \draw[sig, gray, dashed] (curr.east) -- node[above, font=\scriptsize, gray, pos=0.45] {AINx (N.C.)} (adc.west |- curr.east);
|
||||
% (disabled: no 'curr' node exists in this schematic)
|
||||
|
||||
% LÍNEA DE CONTROL PIN_VOC (Limpia y bordeando por abajo)
|
||||
\draw[sig, red!80!black, line width=1pt]
|
||||
(esp.south west) -- (esp.south west |- 0,-2.6) -- node[below, pos=0.4, font=\scriptsize, text=red!80!black] {\texttt{PIN\_VOC} (Gate Driver Control)} ($(cpv.west)+(-0.35,0)$) -- (cpv.west);
|
||||
|
||||
% ==========================================
|
||||
% 4. DRIVERS Y MOTORES (ABAJO)
|
||||
% ==========================================
|
||||
\node[driver, below=1.36cm of esp.south, left=0.15cm of esp.south] (tmcX) {\textbf{TMC2209}\\[-2pt]\scriptsize Driver (X-Axis)};
|
||||
\node[driver, below=1.34cm of esp.south, right=0.12cm of esp.south] (tmcY) {\textbf{TMC2209}\\[-2pt]\scriptsize Driver (Y-Axis)};
|
||||
|
||||
\node[motor, below=0.8cm of tmcX] (motX) {\textbf{M1}\\[-3pt]\tiny Zenith};
|
||||
\node[motor, below=0.8cm of tmcY] (motY) {\textbf{M2}\\[-3pt]\tiny Azimuth};
|
||||
|
||||
% Conexiones de Control a los Drivers
|
||||
\draw[sig] (esp.south -| tmcX.north) -- node[left, font=\scriptsize, align=right] {UART /\\STEP / DIR} (tmcX.north);
|
||||
\draw[sig] (esp.south -| tmcY.north) -- node[right, font=\scriptsize, align=left] {UART /\\STEP / DIR} (tmcY.north);
|
||||
|
||||
% Conexiones a Motores
|
||||
\draw[sig, line width=1pt] (tmcX.south) -- node[right, font=\scriptsize] {NEMA 11} (motX.north);
|
||||
\draw[sig, line width=1pt] (tmcY.south) -- node[right, font=\scriptsize] {NEMA 11} (motY.north);
|
||||
|
||||
% ==========================================
|
||||
% 5. MARCO DE LA TARJETA
|
||||
% ==========================================
|
||||
\begin{scope}[
|
||||
on background layer,
|
||||
yshift=6pt,
|
||||
yscale=0.9
|
||||
]
|
||||
\node[draw=blue!50, line width=1pt, dashed, rounded corners=6pt, fill=blue!2,
|
||||
fit=(esp) (adc) (tmcX) (tmcY),
|
||||
inner sep=14pt,
|
||||
label={[blue!80!black, font=\bfseries\small, label distance=0pt]north west:Controller Board (WiT-CPV)}] (board) {};
|
||||
\end{scope}
|
||||
|
||||
\draw[thick, solid] (-1.8,1.5) -- (-10.81,1.5)node[font=\scriptsize, pos=0.31, above, north] {PIN-CTRL (HIGH $\rightarrow I_{sc}$, LOW $\rightarrow V_{oc}$)};
|
||||
\draw[->, thick, solid] (-10.81,1.5) -- (cpv.north);
|
||||
\end{tikzpicture}
|
||||
|
||||
\end{document}
|
||||
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"tag": "10092025",
|
||||
"model": "G_cs = A*exp(-B*AM) + C, Ajustado al sobre-ensvolvente claro no saturado",
|
||||
"model_scale_A_Wm2": 920.0,
|
||||
"model_B": 0.03,
|
||||
"model_C": 115.0,
|
||||
"model_rms_clear_Wm2": 57.2,
|
||||
"n_fit_clear": 138,
|
||||
"model_peak_Wm2": 1006.0,
|
||||
"G_max_measured_Wm2": 1024.0,
|
||||
"G_max_estimated_Wm2": 1024.0,
|
||||
"n_clipped": 1577,
|
||||
"clipped_pct_log": 17.4,
|
||||
"H_kWh_m2_full_measured": 3.0884,
|
||||
"H_kWh_m2_full_corrected": 3.0884,
|
||||
"R_opt_uA_per_Wm2_measured": 250.9,
|
||||
"R_opt_uA_per_Wm2_corrected": 250.9,
|
||||
"eta_tr_pct_full_measured": 48.3,
|
||||
"eta_tr_pct_full_corrected": 48.3,
|
||||
"eta_tr_pct_clear_measured": 42.24,
|
||||
"eta_tr_pct_clear_corrected": 42.24,
|
||||
"MAE_I_mA_clear_measured": 66.63,
|
||||
"MAE_I_mA_clear_corrected": 96.45,
|
||||
"MAE_P_mW_clear_measured": 182.97,
|
||||
"MAE_P_mW_clear_corrected": 182.97,
|
||||
"ratio_P_Pref_median_clear_measured": 0.649,
|
||||
"ratio_P_Pref_median_clear_corrected": 0.649,
|
||||
"location": "Aguascalientes, Ags., Mexico (21.8756 N, 102.2854 W, 1896 m, UTC-6)"
|
||||
}
|
||||
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"tag": "15092025",
|
||||
"model": "G_cs = A*exp(-B*AM) + C, Ajustado al sobre-ensvolvente claro no saturado",
|
||||
"model_scale_A_Wm2": 1550.0,
|
||||
"model_B": 0.61,
|
||||
"model_C": 130.0,
|
||||
"model_rms_clear_Wm2": 51.2,
|
||||
"n_fit_clear": 66,
|
||||
"model_peak_Wm2": 940.0,
|
||||
"G_max_measured_Wm2": 1024.0,
|
||||
"G_max_estimated_Wm2": 1024.0,
|
||||
"n_clipped": 1186,
|
||||
"clipped_pct_log": 25.55,
|
||||
"H_kWh_m2_full_measured": 1.3408,
|
||||
"H_kWh_m2_full_corrected": 1.3408,
|
||||
"R_opt_uA_per_Wm2_measured": 231.5,
|
||||
"R_opt_uA_per_Wm2_corrected": 231.5,
|
||||
"eta_tr_pct_full_measured": 56.0,
|
||||
"eta_tr_pct_full_corrected": 56.0,
|
||||
"eta_tr_pct_clear_measured": 42.34,
|
||||
"eta_tr_pct_clear_corrected": 42.34,
|
||||
"MAE_I_mA_clear_measured": 47.19,
|
||||
"MAE_I_mA_clear_corrected": 63.39,
|
||||
"MAE_P_mW_clear_measured": 119.76,
|
||||
"MAE_P_mW_clear_corrected": 119.76,
|
||||
"ratio_P_Pref_median_clear_measured": 0.799,
|
||||
"ratio_P_Pref_median_clear_corrected": 0.799,
|
||||
"location": "Aguascalientes, Ags., Mexico (21.8756 N, 102.2854 W, 1896 m, UTC-6)"
|
||||
}
|
||||
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"tag": "19092025_",
|
||||
"model": "G_cs = A*exp(-B*AM) + C, Ajustado al sobre-ensvolvente claro no saturado",
|
||||
"model_scale_A_Wm2": 1550.0,
|
||||
"model_B": 0.57,
|
||||
"model_C": 170.0,
|
||||
"model_rms_clear_Wm2": 21.0,
|
||||
"n_fit_clear": 197,
|
||||
"model_peak_Wm2": 1010.0,
|
||||
"G_max_measured_Wm2": 1024.0,
|
||||
"G_max_estimated_Wm2": 1024.0,
|
||||
"n_clipped": 2212,
|
||||
"clipped_pct_log": 19.41,
|
||||
"H_kWh_m2_full_measured": 3.6224,
|
||||
"H_kWh_m2_full_corrected": 3.6224,
|
||||
"R_opt_uA_per_Wm2_measured": 373.2,
|
||||
"R_opt_uA_per_Wm2_corrected": 373.2,
|
||||
"eta_tr_pct_full_measured": 33.94,
|
||||
"eta_tr_pct_full_corrected": 33.94,
|
||||
"eta_tr_pct_clear_measured": 31.97,
|
||||
"eta_tr_pct_clear_corrected": 31.97,
|
||||
"MAE_I_mA_clear_measured": 130.83,
|
||||
"MAE_I_mA_clear_corrected": 220.57,
|
||||
"MAE_P_mW_clear_measured": 408.12,
|
||||
"MAE_P_mW_clear_corrected": 408.12,
|
||||
"ratio_P_Pref_median_clear_measured": 0.391,
|
||||
"ratio_P_Pref_median_clear_corrected": 0.391,
|
||||
"location": "Aguascalientes, Ags., Mexico (21.8756 N, 102.2854 W, 1896 m, UTC-6)"
|
||||
}
|
||||
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"tag": "20092025_desde1pm",
|
||||
"model": "G_cs = A*exp(-B*AM) + C, Ajustado al sobre-ensvolvente claro no saturado",
|
||||
"model_scale_A_Wm2": 1550.0,
|
||||
"model_B": 0.61,
|
||||
"model_C": 170.0,
|
||||
"model_rms_clear_Wm2": 18.8,
|
||||
"n_fit_clear": 306,
|
||||
"model_peak_Wm2": 960.0,
|
||||
"G_max_measured_Wm2": 979.7,
|
||||
"G_max_estimated_Wm2": 979.7,
|
||||
"n_clipped": 0,
|
||||
"clipped_pct_log": 0.0,
|
||||
"H_kWh_m2_full_measured": 1.0505,
|
||||
"H_kWh_m2_full_corrected": 1.0505,
|
||||
"R_opt_uA_per_Wm2_measured": 181.6,
|
||||
"R_opt_uA_per_Wm2_corrected": 181.6,
|
||||
"eta_tr_pct_full_measured": 69.65,
|
||||
"eta_tr_pct_full_corrected": 69.65,
|
||||
"eta_tr_pct_clear_measured": 70.71,
|
||||
"eta_tr_pct_clear_corrected": 70.71,
|
||||
"MAE_I_mA_clear_measured": 43.0,
|
||||
"MAE_I_mA_clear_corrected": 48.56,
|
||||
"MAE_P_mW_clear_measured": 89.24,
|
||||
"MAE_P_mW_clear_corrected": 89.24,
|
||||
"ratio_P_Pref_median_clear_measured": 0.737,
|
||||
"ratio_P_Pref_median_clear_corrected": 0.737,
|
||||
"location": "Aguascalientes, Ags., Mexico (21.8756 N, 102.2854 W, 1896 m, UTC-6)"
|
||||
}
|
||||
File diff suppressed because it is too large.
Load diff
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"tag": "21092025",
|
||||
"model": "G_cs = A*exp(-B*AM) + C, Ajustado al sobre-ensvolvente claro no saturado",
|
||||
"model_scale_A_Wm2": 1480.0,
|
||||
"model_B": 0.33,
|
||||
"model_C": 0.0,
|
||||
"model_rms_clear_Wm2": 23.3,
|
||||
"n_fit_clear": 261,
|
||||
"model_peak_Wm2": 1036.0,
|
||||
"G_max_measured_Wm2": 1024.0,
|
||||
"G_max_estimated_Wm2": 1036.2,
|
||||
"n_clipped": 3011,
|
||||
"clipped_pct_log": 23.5,
|
||||
"H_kWh_m2_full_measured": 3.3291,
|
||||
"H_kWh_m2_full_corrected": 3.3424,
|
||||
"R_opt_uA_per_Wm2_measured": 228.9,
|
||||
"R_opt_uA_per_Wm2_corrected": 226.3,
|
||||
"eta_tr_pct_full_measured": 67.28,
|
||||
"eta_tr_pct_full_corrected": 67.76,
|
||||
"eta_tr_pct_clear_measured": 64.59,
|
||||
"eta_tr_pct_clear_corrected": 65.05,
|
||||
"MAE_I_mA_clear_measured": 38.96,
|
||||
"MAE_I_mA_clear_corrected": 60.85,
|
||||
"MAE_P_mW_clear_measured": 118.29,
|
||||
"MAE_P_mW_clear_corrected": 115.56,
|
||||
"ratio_P_Pref_median_clear_measured": 0.728,
|
||||
"ratio_P_Pref_median_clear_corrected": 0.73,
|
||||
"location": "Aguascalientes, Ags., Mexico (21.8756 N, 102.2854 W, 1896 m, UTC-6)"
|
||||
}
|
||||
@@ -0,0 +1,231 @@
|
||||
{
|
||||
"tag": "21092025",
|
||||
"log": "21092025.txt",
|
||||
"session_start": "2025-09-21 10:40:58",
|
||||
"session_end": "2025-09-21 17:49:22",
|
||||
"R_opt_max_mA_per_Wm2": 0.229,
|
||||
"FF_used": 0.82,
|
||||
"full_session": {
|
||||
"label": "Full session (G > 50 W/m2)",
|
||||
"n_samples": 11206,
|
||||
"t_inicio": "2025-09-21 10:40:58",
|
||||
"t_fin": "2025-09-21 17:02:34",
|
||||
"E_Wh": 0.927,
|
||||
"H_kWh_m2": 3.3291,
|
||||
"E_norm_Wh_per_kWhm2": 0.278,
|
||||
"eta_tr_pct": 67.28,
|
||||
"MAE_I_mA": 43.37,
|
||||
"MAE_P_mW": 72.39,
|
||||
"P_CPV_mean_mW": 148.6,
|
||||
"P_ref_mean_mW": 220.5,
|
||||
"S_el_usteps": 1667716,
|
||||
"S_az_usteps": 1615691,
|
||||
"S_tot_usteps": 3283407,
|
||||
"S_tot_deg": 4956.1
|
||||
},
|
||||
"daylight": {
|
||||
"label": "Daylight (G > 200 W/m2)",
|
||||
"n_samples": 7062,
|
||||
"t_inicio": "2025-09-21 10:40:58",
|
||||
"t_fin": "2025-09-21 15:19:27",
|
||||
"E_Wh": 0.945,
|
||||
"H_kWh_m2": 3.2573,
|
||||
"E_norm_Wh_per_kWhm2": 0.29,
|
||||
"eta_tr_pct": 67.55,
|
||||
"MAE_I_mA": 55.87,
|
||||
"MAE_P_mW": 105.35,
|
||||
"P_CPV_mean_mW": 234.6,
|
||||
"P_ref_mean_mW": 339.3,
|
||||
"S_el_usteps": 1364762,
|
||||
"S_az_usteps": 1319052,
|
||||
"S_tot_usteps": 2683814,
|
||||
"S_tot_deg": 4051.0
|
||||
},
|
||||
"tracking_active": {
|
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|
||||
"t_start": "2025-09-14 12:13:48",
|
||||
"dur_s": 132,
|
||||
"G_base_Wm2": 994.0,
|
||||
"G_min_Wm2": 263.0,
|
||||
"depth_pct": 73.5,
|
||||
"t95_G_s": 136.0
|
||||
},
|
||||
{
|
||||
"t_start": "2025-09-14 12:42:00",
|
||||
"dur_s": 126,
|
||||
"G_base_Wm2": 252.0,
|
||||
"G_min_Wm2": 244.0,
|
||||
"depth_pct": 3.4,
|
||||
"t95_G_s": 126.0
|
||||
},
|
||||
{
|
||||
"t_start": "2025-09-14 13:27:56",
|
||||
"dur_s": 128,
|
||||
"G_base_Wm2": 679.0,
|
||||
"G_min_Wm2": 228.0,
|
||||
"depth_pct": 66.4,
|
||||
"t95_G_s": 128.0
|
||||
},
|
||||
{
|
||||
"t_start": "2025-09-14 14:06:28",
|
||||
"dur_s": 120,
|
||||
"G_base_Wm2": 328.0,
|
||||
"G_min_Wm2": 189.0,
|
||||
"depth_pct": 42.2,
|
||||
"t95_G_s": 172.0
|
||||
},
|
||||
{
|
||||
"t_start": "2025-09-14 14:12:38",
|
||||
"dur_s": 132,
|
||||
"G_base_Wm2": 169.0,
|
||||
"G_min_Wm2": 152.0,
|
||||
"depth_pct": 9.9,
|
||||
"t95_G_s": 132.0
|
||||
}
|
||||
],
|
||||
"position_errors": [
|
||||
{
|
||||
"t_reticle": "2025-09-14 13:04:46",
|
||||
"az_corr": 195.6,
|
||||
"alt_corr": 93.6,
|
||||
"errX0_deg": 0.0,
|
||||
"errY0_deg": 0.0,
|
||||
"errX0_usteps": 0,
|
||||
"errY0_usteps": 0,
|
||||
"errX_ss_deg": 0.376,
|
||||
"errY_ss_deg": 2.711
|
||||
}
|
||||
],
|
||||
"er_progression": [
|
||||
{
|
||||
"t": "2025-09-14T12:50:59.000000",
|
||||
"e": 800
|
||||
}
|
||||
],
|
||||
"at_recommendations": [
|
||||
{
|
||||
"timestamp": "2025-09-14 12:50:58",
|
||||
"small": 3561.0,
|
||||
"abrupt": 10683.0,
|
||||
"reset": 21366.0,
|
||||
"peak": 0.01
|
||||
},
|
||||
{
|
||||
"timestamp": "2025-09-14 12:51:07",
|
||||
"small": 3561.0,
|
||||
"abrupt": 10683.0,
|
||||
"reset": 21366.0,
|
||||
"peak": 0.01
|
||||
}
|
||||
]
|
||||
}
|
||||
File diff suppressed because it is too large.
Load diff
@@ -0,0 +1,242 @@
|
||||
% Generated by analyze_2026_11_03.py. Do not hand-edit numerical results.
|
||||
% Intended compilation directory: articulo. This file does not modify PRINCIPAL.tex.
|
||||
\subsection{Quality-Controlled Outdoor Evaluation on 3 November 2026}
|
||||
\label{subsec:nov03_curated}
|
||||
|
||||
\paragraph{Acquisition quality and shunt intervention}
|
||||
The firmware 1.1.3-ws record contains 3429 coordinate/electrical observations
|
||||
between 10:44:20 and 15:40:42 on 3 November 2026. Times are the local log clock;
|
||||
the file does not encode a time zone. Initial commissioning includes manual
|
||||
coordinate changes and parameter commands. Observations before 10:56:04, the
|
||||
logged initial sampling-delay configuration, are conservatively marked as setup.
|
||||
Subsequent controller parameter changes through 11:41:03 are retained and disclosed;
|
||||
the pre-intervention segment is not a fixed-parameter benchmark.
|
||||
|
||||
The experimenter reported adding a second resistor in parallel with the
|
||||
260~m$\Omega$ current shunt, reducing its nominal resistance to 130~m$\Omega$.
|
||||
The exact soldering time is not recorded. The change is assigned to the
|
||||
unobserved interval between 12:38:07 and 12:46:01 (474~s), supported by the
|
||||
reset of the uptime/counter and the approximately halved current-channel codes
|
||||
after the gap, while irradiance remains comparable. No sample is assigned an
|
||||
invented intervention timestamp inside this interval. The first returned
|
||||
observations, including reacquisition at low current, are retained rather than
|
||||
discarded to improve performance.
|
||||
|
||||
The current channel reaches the positive ADC rail of 8,388,607 counts in
|
||||
334 observations, from 11:36:55 to 12:35:37.
|
||||
Clipped values provide only lower bounds on current; they cannot be restored by
|
||||
multiplying the trace or changing the shunt calibration. A conservative
|
||||
99\%-of-rail guard additionally excludes near-rail current observations
|
||||
(24 beyond the clipped set).
|
||||
The audit CSV retains all observations, original ADC codes, source line numbers,
|
||||
the applicable nominal shunt value and nonexclusive quality flags; rejected
|
||||
current/power estimates are blank. An explicit \texttt{integrate\_from\_previous}
|
||||
column marks usable full-record integration edges; additional window filtering
|
||||
must still require both endpoints inside the chosen window.
|
||||
The companion curated text log contains
|
||||
accepted raw observations only, with calibration metadata, and is not suitable
|
||||
for a legacy single-shunt converter. Low-output, cloud/standby and later
|
||||
drift-correction periods are not removed solely for poor performance.
|
||||
|
||||
\paragraph{Calibration and modeled electrical output}
|
||||
Using signed 24-bit codes $C$, $V$ and $P$, positive full scale $D=8,388,607$,
|
||||
and the 2.048-V reference, the offline conversions are
|
||||
\begin{align}
|
||||
I_{sc} &= \frac{2.048 C}{20 D R_s}, &
|
||||
V_{oc} &= \frac{2(2.048)V}{D}, &
|
||||
G &= \frac{2048 P}{0.2 D}.
|
||||
\end{align}
|
||||
Here $I_{sc}$ is in A, $V_{oc}$ in V, $G$ in W\,m$^{-2}$, and $R_s$
|
||||
is 0.260~$\Omega$ before the intervention gap and 0.130~$\Omega$ after it.
|
||||
The factor 20 is the external current-amplifier gain; the factor 2 accounts
|
||||
for the open-circuit voltage divider. The pyranometer scale is
|
||||
0.2~mV/(W\,m$^{-2}$), not the obsolete divisor 2.0.
|
||||
The corresponding nominal current full scales are 393.85 and 787.69~mA.
|
||||
This is an offline calibration correction, not a modification of the firmware
|
||||
or of the control decisions actually made during the experiment.
|
||||
The log's firmware irradiance diagnostics remain on a different scale: at
|
||||
10:51:15 the recorded $P=689473$ converts to approximately
|
||||
842~W\,m$^{-2}$, whereas the accompanying auto-start message reports
|
||||
84~W\,m$^{-2}$. Thus, logged firmware irradiance thresholds and standby messages
|
||||
must not be interpreted directly on the corrected offline axis. Correcting
|
||||
the exported irradiance does not retroactively correct those control decisions.
|
||||
A nominal firmware threshold of 10~W\,m$^{-2}$ therefore corresponds to
|
||||
approximately 100~W\,m$^{-2}$ on the corrected axis. The primary evaluation
|
||||
includes returned low-light observations even when the controller is in standby.
|
||||
|
||||
Electrical output is estimated as
|
||||
\begin{equation}
|
||||
\widehat{P}_{\mathrm{MPP}}=V_{oc} I_{sc} FF,\qquad FF=0.82.
|
||||
\end{equation}
|
||||
The fixed fill factor follows the manuscript model, not a new outdoor I--V
|
||||
measurement. Since the device alternates open- and short-circuit sensing,
|
||||
this quantity estimates available MPP power under approximately unchanged
|
||||
conditions across the sampling cycle; it is not measured power delivered to
|
||||
a load or harvested energy. Fast irradiance changes can violate that
|
||||
approximation. No cell-temperature, spectral-mismatch or fill-factor correction
|
||||
is inferred from this log.
|
||||
|
||||
With lens aperture $A_L=0.002497$~m$^2$, the aperture-referenced estimate is
|
||||
\begin{equation}
|
||||
\widehat{\eta}_{\mathrm{ap}}(t)=
|
||||
\frac{\widehat{P}_{\mathrm{MPP}}(t)}{A_L G(t)}\,100\%,\qquad
|
||||
\widehat{\eta}_{\mathrm{ap},E}=
|
||||
\frac{\int\widehat{P}_{\mathrm{MPP}}\,dt}{A_L\int G\,dt}\,100\%.
|
||||
\end{equation}
|
||||
This describes the combined lens/receiver system relative to the measured
|
||||
pyranometric irradiance. It is not intrinsic cell conversion efficiency:
|
||||
separating the cell requires the optical power incident on its active area
|
||||
(or validated optical throughput), which was not recorded. The pyranometer's
|
||||
global irradiance is not a direct-normal irradiance measurement and includes
|
||||
diffuse light that the concentrator may not collect. Reference-sensor alignment,
|
||||
incidence geometry and optical losses therefore remain part of this estimate.
|
||||
|
||||
\paragraph{Accepted integration support and tracking indicators}
|
||||
All energy, irradiation and reference-power integrals use the same
|
||||
adjacent accepted illuminated observations ($G>50$~W\,m$^{-2}$). An interval is
|
||||
included only if both endpoints are accepted, its duration is at most 15~s,
|
||||
the shunt does not change and uptime does not decrease. Trapezoidal integration
|
||||
never bridges rejected rows, reboots or long missing intervals. The tabulated
|
||||
duration is the sum of included intervals, not the elapsed window length.
|
||||
Unobserved or clipped periods are neither zero-filled nor reconstructed;
|
||||
the all-segments result is not a full-session energy estimate.
|
||||
In particular, selecting only unclipped pre-change points preferentially
|
||||
removes high-current periods and biases that subset; it cannot establish a
|
||||
causal performance improvement from the resistor intervention.
|
||||
|
||||
For comparison with the manuscript's responsivity approach, an empirical
|
||||
same-record reference is defined by
|
||||
\begin{equation}
|
||||
R_{\mathrm{ref}}=\max_{\mathrm{accepted},\,G>50}(I_{sc}/G)
|
||||
=0.0004651~\mathrm{A\,m^2\,W^{-1}},\quad
|
||||
\widehat{P}_{\mathrm{ref}}=R_{\mathrm{ref}}G V_{oc} FF.
|
||||
\end{equation}
|
||||
The empirical tracking indicator is
|
||||
$\widehat{\eta}_{\mathrm{tr}}=100\int\widehat{P}_{\mathrm{MPP}}dt/
|
||||
\int\widehat{P}_{\mathrm{ref}}dt$ on the same accepted support.
|
||||
It is an internal relative-yield benchmark, not independently validated ideal
|
||||
alignment efficiency or angular pointing accuracy. Irradiance geometry,
|
||||
temperature, spectrum and electrical offsets can also change $I_{sc}/G$.
|
||||
The reference reuses the measured $V_{oc}$, so it does not independently
|
||||
quantify voltage losses relative to a perfectly aligned receiver.
|
||||
No astronomical-angle accuracy or unambiguous cloud-recovery time is claimed.
|
||||
Replacing the maximum by the 99th-percentile responsivity
|
||||
(0.0004567~A\,m$^2$\,W$^{-1}$) provides a reference sensitivity
|
||||
check; the resulting ratio is not clipped to 100\% and is not a strict ceiling.
|
||||
|
||||
Two sample-occupancy measures are kept separate:
|
||||
(i) $I_{sc}\geq0.8 I_{sc,\max}$ within each specified window, and
|
||||
(ii) $(I_{sc}/G)/R_{\mathrm{ref}}\geq0.8$ using the common reference.
|
||||
Both use accepted illuminated samples as their denominator, unlike the October
|
||||
criterion whose denominator includes every observation in its selected window.
|
||||
Neither is interchangeable with energy-based tracking efficiency.
|
||||
|
||||
\begin{table}[htbp]
|
||||
\centering
|
||||
\small
|
||||
\caption{Results on accepted illuminated integration support. Energy and aperture
|
||||
efficiency are FF-based estimates; tracking efficiency uses a same-record
|
||||
empirical reference. Missing and clipped intervals are not integrated.}
|
||||
\label{tab:nov03_metrics}
|
||||
\begin{tabular}{@{}lrrrrr@{}}
|
||||
\toprule
|
||||
Window & Samples & Hours & $\widehat{E}$ [Wh] & $\widehat{\eta}_{\mathrm{ap},E}$ [\%] & $\widehat{\eta}_{\mathrm{tr}}$ [\%] \\
|
||||
\midrule
|
||||
All accepted segments & 2921 & 4.034 & 2.067 & 27.31 & 79.80 \\
|
||||
Before change (unclipped only) & 836 & 1.144 & 0.659 & 25.32 & 70.63 \\
|
||||
After change (all illuminated) & 2085 & 2.890 & 1.408 & 28.34 & 84.97 \\
|
||||
Fixed hour, 13:00--14:00 & 714 & 0.989 & 0.746 & 30.67 & 89.62 \\
|
||||
\bottomrule
|
||||
\end{tabular}
|
||||
\end{table}
|
||||
|
||||
\paragraph{Post-intervention results and limitations}
|
||||
The primary post-change evaluation retains the entire returned record,
|
||||
12:46:01--15:40:42, including the late low-output period.
|
||||
It contains 2085 accepted illuminated samples and
|
||||
2.890~h of integrated support
|
||||
(99.27\% of its elapsed span).
|
||||
The estimated electrical energy is 1.408~Wh for
|
||||
1.989~kWh\,m$^{-2}$ of irradiation on that support,
|
||||
giving 28.34\% energy-weighted
|
||||
aperture efficiency. Peak current is 477.6~mA, and
|
||||
peak modeled power is 0.891~W; maxima of different
|
||||
variables need not be simultaneous. At the modeled power peak
|
||||
(12:53:11), the simultaneous log record gives
|
||||
$I_{sc}=477.6$~mA,
|
||||
$V_{oc}=2.274$~V and
|
||||
$G=1027.9$~W\,m$^{-2}$.
|
||||
The median instantaneous aperture estimate
|
||||
is 28.70\%, and its peak is
|
||||
34.70\%, neither being a daily efficiency.
|
||||
The empirical tracking ratio is 84.97\%,
|
||||
with a sample-mean absolute power deviation of 86.4~mW
|
||||
from the internal reference. The 99th-percentile reference changes this ratio
|
||||
to 86.54\%.
|
||||
Current-threshold and irradiance-normalized on-target sample fractions are
|
||||
37.31\% and
|
||||
58.94\%, respectively; the corresponding
|
||||
endpoint-interpolated time fractions are
|
||||
37.34\% and
|
||||
59.02\% on accepted intervals.
|
||||
|
||||
For a conventional fixed one-hour comparison rather than an automatically
|
||||
selected best interval, 13:00--14:00 gives
|
||||
30.67\% aperture efficiency and
|
||||
89.62\% empirical tracking efficiency,
|
||||
with 0.746~Wh over 0.989~h
|
||||
of integrated support. This favourable subset must not replace the full
|
||||
post-change result. The pre-change unclipped subset has only
|
||||
67.28\% valid interval coverage of its elapsed
|
||||
span and is reported for audit, not as an unbiased control experiment.
|
||||
|
||||
Sampled coordinate differences on post-change accepted illuminated intervals
|
||||
total 656,576 $X$ steps and
|
||||
643,068 $Y$ steps. With the manuscript's bench costs
|
||||
(1.2~W and 2.5~W at approximately 6000 commanded steps/s), the corresponding
|
||||
sampled-motion estimate is 0.1109~Wh.
|
||||
The independently differenced TEL counter contributes
|
||||
1,293,457 fine-tune steps on intervals
|
||||
fully covered by accepted coordinate runs. TEL does not count all motion.
|
||||
Sparse coordinate differences can miss intermediate reversals; neither count
|
||||
measures total motor/board consumption, and a total parasitic ratio or net
|
||||
electrical yield cannot be inferred. There are
|
||||
2 logged F5 corrections in the elapsed
|
||||
post-change span, including low-light operation outside some integration support.
|
||||
|
||||
All estimated powers, energies and aperture efficiencies scale linearly with
|
||||
the assumed $FF$: multiply by $FF'/0.82$ for another assumption. A common
|
||||
constant $FF$ cancels from the tracking ratio. No statistical or calibration
|
||||
confidence interval is assigned without resistance tolerances, reference-sensor
|
||||
uncertainty and outdoor I--V data. Results at 10-, 15-, 30- and 60-s maximum
|
||||
integration gaps are exported as a gap-policy sensitivity check.
|
||||
|
||||
\begin{figure}[p]
|
||||
\centering
|
||||
\includegraphics[width=0.95\linewidth,height=0.78\textheight,keepaspectratio]{../figures/2026-11-03/quality_and_calibration.pdf}
|
||||
\caption{Quality control and piecewise current calibration on 3 November 2026.
|
||||
Red marks identify ADC-clipped observations, not recovered measurements.
|
||||
The shaded interval brackets the unobserved 260-to-130-m$\Omega$ shunt intervention.
|
||||
Accepted low-output observations remain in the record.}
|
||||
\label{fig:nov03_quality}
|
||||
\end{figure}
|
||||
|
||||
\begin{figure}[p]
|
||||
\centering
|
||||
\includegraphics[width=0.95\linewidth,height=0.78\textheight,keepaspectratio]{../figures/2026-11-03/post_change_performance.pdf}
|
||||
\caption{Post-intervention modeled MPP power, same-record normalized current
|
||||
response and lens-aperture-referenced efficiency. $FF=0.82$ and
|
||||
$A_L=0.002497$~m$^2$ are assumed. The late low-output period is retained;
|
||||
these are not direct load-power or intrinsic-cell-efficiency measurements.}
|
||||
\label{fig:nov03_performance}
|
||||
\end{figure}
|
||||
|
||||
\begin{figure}[p]
|
||||
\centering
|
||||
\includegraphics[width=\linewidth]{../figures/2026-11-03/response_and_occupancy.pdf}
|
||||
\caption{Post-change current versus irradiance (colour encodes log time),
|
||||
and occupancy of the 80\%-of-reference responsivity criterion in 15-min bins.
|
||||
Only accepted observations with $G>50$~W\,m$^{-2}$ enter the sample denominator;
|
||||
the reference is the maximum accepted responsivity of the same record.}
|
||||
\label{fig:nov03_response}
|
||||
\end{figure}
|
||||
@@ -0,0 +1,175 @@
|
||||
% Generated by analyze_2026_11_04.py; do not hand-edit numerical values.
|
||||
\subsection{Acquisition coverage and operating chronology}
|
||||
|
||||
The acquired span is 09:52:50--16:05:13, comprising \NovSamples{}
|
||||
electrical/coordinate observations and 5,026 separate
|
||||
telemetry messages. All main observations pass the ADC quality checks and
|
||||
exceed the analysis illumination threshold. There are no duplicate main
|
||||
timestamps or decreasing main-sample uptimes. Five gaps exceed 15~s:
|
||||
09:53:10--09:53:51 (41 s); 09:54:11--09:57:17 (186 s); 10:34:38--10:34:59 (21 s); 16:03:43--16:04:23 (40 s); 16:04:43--16:05:01 (18 s). Excluding these gaps gives \NovHours{}~h of integration
|
||||
support out of 6.206~h elapsed, or 98.63\%
|
||||
coverage. The audit retains every acquired observation; no clipped samples
|
||||
or unobserved intervals are reconstructed.
|
||||
|
||||
The complete overview in Fig.~\ref{fig:nov04_overview} connects electrical
|
||||
response with stage motion. There are 61 logged remote
|
||||
commands, including early tuning and repositioning. For example,
|
||||
\texttt{Delay=4} was logged at 12:27:20, before the 12:32 boundary. Three event boundaries
|
||||
divide the record without selecting a favorable performance threshold:
|
||||
\texttt{ErrMax=1100} at 12:32:02, \texttt{ErrMax=1000} at 13:53:00,
|
||||
and the first late manual-coordinate command at 15:12:42. All four sequential
|
||||
phases are retained in Table~\ref{tab:nov04_phases}. No additional remote
|
||||
commands are recorded inside the 12:32--13:53 phase; periodic controller
|
||||
reference resets continue. This is an interval without logged operator
|
||||
interventions, not a controlled comparison of firmware or settings.
|
||||
|
||||
\subsection{Electrical output and aperture estimate}
|
||||
|
||||
Applying Eqs.~\eqref{eq:power_estimate}--\eqref{eq:aperture} over the
|
||||
complete accepted support yields \NovEnergy{}~Wh of estimated available-MPP
|
||||
energy from \NovIrradiation{}~kWh\,m$^{-2}$ of measured aperture-plane irradiation,
|
||||
with an energy-weighted aperture estimate of \NovEfficiency\%.
|
||||
Table~\ref{tab:nov04_hourly} shows every acquired clock-hour bin, including
|
||||
the initial low response and late decline, rather than replacing the complete
|
||||
record with a midday-only integral.
|
||||
|
||||
At the maximum of the power estimate (2026-11-04 12:27:40), the
|
||||
sequentially recorded values in that observation were
|
||||
$I_{sc}=502.0$ mA,
|
||||
$V_{oc}=2.361$ V and $G=1172.1$ W m$^{-2}$,
|
||||
giving 0.972~W estimated output and an instantaneous aperture
|
||||
estimate of \NovApertureAtPeakPower\% at that observation. Separate maxima are not combined
|
||||
into a synthetic operating point. The 12:32--13:53 phase contributes
|
||||
1.126~Wh over
|
||||
1.349~h, with an aperture estimate
|
||||
of \NovSteadyEfficiency\%. The 15:00--16:00 clock-hour estimate falls to
|
||||
11.51\%, and
|
||||
the phase after the first 15:12 manual command gives
|
||||
6.97\%.
|
||||
The record shows deterioration before and after that command, not evidence
|
||||
that the command alone caused it.
|
||||
|
||||
\begin{table}[htbp]
|
||||
\centering\small
|
||||
\caption{Complete acquisition and fixed clock-hour summaries. $H$ is aperture-plane
|
||||
irradiation, $\widehat E$ is FF-based available energy and
|
||||
$\widehat\eta_{\mathrm{ap},E}$ is the energy-weighted aperture estimate.
|
||||
Bins contain only acquired observations. Both edge endpoints must lie inside a
|
||||
bin, so subdivided integrals omit boundary-crossing edges and need not sum
|
||||
exactly to the full-record integral.}
|
||||
\label{tab:nov04_hourly}
|
||||
\begin{tabular}{lrrrrr}
|
||||
\toprule
|
||||
Window & $N$ & Support [h] & $H$ [kWh\,m$^{-2}$] & $\widehat E$ [Wh] & $\widehat\eta_{\mathrm{ap},E}$ [\%] \\
|
||||
\midrule
|
||||
Full acquired record & 5049 & 6.121 & 6.408 & 3.7463 & 23.41 \\
|
||||
09:00--10:00 & 41 & 0.056 & 0.046 & 0.0002 & 0.21 \\
|
||||
10:00--11:00 & 717 & 0.993 & 0.945 & 0.4629 & 19.61 \\
|
||||
11:00--12:00 & 718 & 0.998 & 1.100 & 0.7387 & 26.90 \\
|
||||
12:00--13:00 & 807 & 1.000 & 1.173 & 0.8094 & 27.65 \\
|
||||
13:00--14:00 & 900 & 0.999 & 1.165 & 0.8004 & 27.51 \\
|
||||
14:00--15:00 & 900 & 0.999 & 1.104 & 0.6887 & 24.97 \\
|
||||
15:00--16:00 & 900 & 0.999 & 0.838 & 0.2409 & 11.51 \\
|
||||
16:00--17:00 & 66 & 0.070 & 0.029 & 0.0004 & 0.58 \\
|
||||
\bottomrule
|
||||
\end{tabular}
|
||||
\end{table}
|
||||
|
||||
\begin{table}[htbp]
|
||||
\centering\small
|
||||
\caption{All sequential event-defined phases. Internal command boundaries
|
||||
belong to the following phase; the final acquired sample is retained.
|
||||
As in Table~\ref{tab:nov04_hourly},
|
||||
edges crossing a boundary are omitted. Phases describe operation; they are not
|
||||
matched experimental treatments.}
|
||||
\label{tab:nov04_phases}
|
||||
\begin{tabular}{lrrrr}
|
||||
\toprule
|
||||
Phase boundary clocks & $N$ & Support [h] & $\widehat E$ [Wh] & $\widehat\eta_{\mathrm{ap},E}$ [\%] \\
|
||||
\midrule
|
||||
09:52:50--12:32:02 & 1863 & 2.584 & 1.601 & 23.61 \\
|
||||
12:32:02--13:53:00 & 1215 & 1.349 & 1.126 & 28.47 \\
|
||||
13:53:00--15:12:42 & 1195 & 1.327 & 0.903 & 24.95 \\
|
||||
15:12:42--16:05:13 & 776 & 0.859 & 0.114 & 6.97 \\
|
||||
\bottomrule
|
||||
\end{tabular}
|
||||
\end{table}
|
||||
|
||||
\subsection{Relative response and solar-position context}
|
||||
|
||||
An empirical same-record $I_{sc}/G$ reference is highly sensitive to one point:
|
||||
the maximum is 0.001078 A m$^2$ W$^{-1}$ at
|
||||
2026-11-04 13:01:07, where $G=313.0$ W m$^{-2}$ and
|
||||
$I_{sc}=337.2$ mA; the P99 reference is
|
||||
0.000420 A m$^2$ W$^{-1}$. The anomalous sample is retained.
|
||||
In its four-minute neighborhood, median irradiance is
|
||||
1186.6 W m$^{-2}$
|
||||
(61 samples), consistent with an isolated
|
||||
irradiance dip rather than sustained low irradiance; the cause remains unresolved.
|
||||
Across the accepted illuminated samples, median $I_{sc}/G$ is
|
||||
0.000335 A m$^2$ W$^{-1}$
|
||||
(interquartile range 0.000250--
|
||||
0.000376).
|
||||
Full-record integrated relative-yield indicators are
|
||||
28.9\% (maximum reference) and
|
||||
74.1\% (P99 sensitivity). These are internal,
|
||||
reference-dependent indicators rather than independently validated tracking
|
||||
efficiencies. Figure~\ref{fig:nov04_response} displays both the full
|
||||
responsivity range and a typical-range view; the anomalous observation remains
|
||||
in the analysis.
|
||||
|
||||
Interpolated SunCalc positions at the first and last observations are
|
||||
130.25$^\circ$ and
|
||||
238.89$^\circ$ azimuth, with elevations
|
||||
35.86$^\circ$ and
|
||||
25.89$^\circ$, respectively.
|
||||
The printed table reaches 52.59$^\circ$
|
||||
elevation at 12:30. Figure~\ref{fig:nov04_solar_response} relates this
|
||||
trajectory to the measured normalized response. Logged coordinates span
|
||||
$X=0$--$114,000$
|
||||
and $Y=1,800$--$104,965$
|
||||
steps. These are observed solar and coordinate ranges, not independently
|
||||
validated acceptance angles or rated mechanical limits.
|
||||
|
||||
\subsection{Conditional fixed-silicon reference}
|
||||
The coplanar, equal-area scenarios of Eq.~\eqref{eq:silicon_scenario}
|
||||
yield
|
||||
3.040 and 3.360 Wh, respectively;
|
||||
the corresponding estimated-CPV-to-scenario ratios are
|
||||
\NovSiliconStandardRatio{} and \NovSiliconPremiumRatio{}.
|
||||
Figure~\ref{fig:nov04_silicon} illustrates these assumptions, not measured
|
||||
comparative yields. Changing the assumed CPV fill factor from 0.82 to 0.70 or
|
||||
0.90 would change the full-record energy estimate to
|
||||
3.198 or
|
||||
4.112~Wh, respectively.
|
||||
This sensitivity range is illustrative, not a measured uncertainty interval.
|
||||
|
||||
\begin{figure}[htbp]\centering
|
||||
\includegraphics[width=0.98\linewidth]{../figures/2026-11-04/field_day_overview.pdf}
|
||||
\caption{Complete 4 November acquisition. Vertical dotted lines mark sampling
|
||||
gaps; dashed lines mark the three selected phase-boundary commands. Raw trends are not smoothed, and gaps are
|
||||
not bridged. Electrical output is estimated using $FF=0.82$.}
|
||||
\label{fig:nov04_overview}\end{figure}
|
||||
|
||||
\begin{figure}[htbp]\centering
|
||||
\includegraphics[width=0.92\linewidth]{../figures/2026-11-04/solar_response_alignment.pdf}
|
||||
\caption{SunCalc azimuth/elevation context aligned to the measured response.
|
||||
SunCalc entries are spaced 15 minutes; intermediate positions are linearly
|
||||
interpolated for plotting. Color encodes $I_{sc}/G$, not pointing error;
|
||||
values above P99 remain plotted in the red over-range color.}
|
||||
\label{fig:nov04_solar_response}\end{figure}
|
||||
|
||||
\begin{figure}[htbp]\centering
|
||||
\includegraphics[width=0.88\linewidth]{../figures/2026-11-04/response_reference_sensitivity.pdf}
|
||||
\caption{Irradiance-normalized response for the full record. The maximum
|
||||
reference is dominated by a retained anomalous observation; P99 is shown only as
|
||||
a sensitivity analysis. Neither line is an independent ideal-tracking standard.}
|
||||
\label{fig:nov04_response}\end{figure}
|
||||
|
||||
\begin{figure}[htbp]\centering
|
||||
\includegraphics[width=0.75\linewidth]{../figures/2026-11-04/fixed_silicon_scenario.pdf}
|
||||
\caption{Conditional equal-area scenarios using the measured aperture-plane irradiance.
|
||||
Silicon efficiency is held constant at 19\% or 21\%; no panel,
|
||||
temperature correction or measured head-to-head comparison is represented.}
|
||||
\label{fig:nov04_silicon}\end{figure}
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
Tectonic 0.17.0
|
||||
+317
@@ -0,0 +1,317 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Estimacion de la irradiancia global REAL (correccion de la saturacion
|
||||
del piranometro en 1024 W/m2) para una sesion de campo.
|
||||
|
||||
Ubicacion de las pruebas: Aguascalientes, Aguascalientes, Mexico.
|
||||
lat = +21.8756, lon = -102.2854, alt = 1896 m, TZ = UTC-6 (sin DST)
|
||||
|
||||
Metodo:
|
||||
1) Posicion solar por formulas estandar (declinacion de Cooper,
|
||||
ecuacion de tiempo de Spencer, correccion de longitud respecto al
|
||||
meridiano del huso UTC-6 a 90 W, masa de aire de Kasten-Young).
|
||||
2) Modelo de cielo despejado G_cs = A*exp(-B*AM) + C (transmisividad
|
||||
de Beer sobre la masa de aire + difuso de cielo claro), ajustado SOLO
|
||||
a muestras de cielo claro SIN saturar (el clipping a 1024 W/m2
|
||||
sesgaria el ajuste hacia abajo). Para anclar la forma de la curva,
|
||||
el ajuste se toma sobre el sobre-ensvolvente de la medida (muestra
|
||||
cercana al maximo movil de 30 min), porque las nubes solo bajan la
|
||||
curva de cielo despejado, nunca la suben.
|
||||
3) La correccion es MONOTONICA: a las muestras saturadas (G >= 1024)
|
||||
se les asigna G_est = max(1024, G_cs) (la correccion nunca baja la
|
||||
meda); al resto se les conserva la medida (nubes incluidas).
|
||||
4) Se recalculan con la misma ventana que el articulo (G > 50 W/m2, y
|
||||
G > 600 para las estadisticas de cielo claro): H, R_opt, P_ref,
|
||||
eta_tr, mediana P/Pref, fraccion P >= 0.95 P_ref y t95.
|
||||
|
||||
Uso: py -3.12 clearsky.py <tag> [nofig]
|
||||
Salida: articulo/resultados_<tag>/preview_irradiance_est.png
|
||||
articulo/resultados_<tag>/irradiance_est_<tag>.json
|
||||
"""
|
||||
|
||||
import json
|
||||
import sys
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
import matplotlib
|
||||
matplotlib.use("Agg")
|
||||
import matplotlib.dates as mdates
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
import parse_log as pl
|
||||
|
||||
ROOT = Path(__file__).resolve().parent
|
||||
|
||||
# Aguascalientes, Ags.
|
||||
LAT = 21.8756
|
||||
LON_W = 102.2854 # longitud oeste positiva
|
||||
ALT_M = 1896.0
|
||||
L_STD_W = 90.0 # meridiano del huso UTC-6
|
||||
G_CLIP = 1023.9 # ADC a tope => G = 1024.0 W/m2
|
||||
|
||||
|
||||
def solar_geometry(ts: pd.Series):
|
||||
"""Elevacion solar y masa de aire (Kasten-Young) a partir de la hora local."""
|
||||
n = (ts.dt.dayofyear.values * 86400.0
|
||||
+ ts.dt.hour.values * 3600.0 + ts.dt.minute.values * 60.0
|
||||
+ ts.dt.second.values) / 86400.0
|
||||
rad = np.pi / 180.0
|
||||
phi = LAT * rad
|
||||
B = 2 * np.pi / 365.0 * (n - 81.0)
|
||||
delta = 23.45 * rad * np.sin(2 * np.pi / 365.0 * (n + 284.0))
|
||||
eot_min = 229.18 * (0.000075 + 0.001868 * np.cos(B)
|
||||
- 0.032077 * np.sin(B)
|
||||
- 0.014615 * np.cos(2 * B)
|
||||
- 0.040849 * np.sin(2 * B))
|
||||
clock_min = (ts.dt.hour.values * 3600 + ts.dt.minute.values * 60
|
||||
+ ts.dt.second.values) / 60.0
|
||||
l_corr = 4.0 * (LON_W - L_STD_W) # minutos (+ si esta al oeste)
|
||||
hour_angle = 15.0 * ((clock_min - l_corr + eot_min) / 60.0 - 12.0)
|
||||
sin_el = (np.sin(phi) * np.sin(delta)
|
||||
+ np.cos(phi) * np.cos(delta) * np.cos(hour_angle * rad))
|
||||
el = np.degrees(np.arcsin(np.clip(sin_el, -1, 1)))
|
||||
z = 90.0 - el
|
||||
m_air = np.where(z < 75.0,
|
||||
1.0 / (np.cos(z * rad) + 0.14 * (93.85 - z) ** (-1.375)),
|
||||
np.inf)
|
||||
return el, m_air
|
||||
|
||||
|
||||
def fit_clearsky(el_deg, am, G, cloud_mask, t_idx):
|
||||
"""Ajusta el modelo G_cs = A*exp(-B*AM) + C a las muestras claras no saturadas.
|
||||
|
||||
Conjunto de ajuste: el sobre-ensvolvente de la medida (muestra >= 0.98
|
||||
del maximo movil de 30 min), fuera de transitorios nubosos, sin
|
||||
saturar (G < 1015) y con el sol por encima de 12 grados. Al anclarse
|
||||
en la parte alta de la curva, la extrapolacion al pico (que cae en la
|
||||
zona saturada del piranometro) es corta y confiable.
|
||||
"""
|
||||
roll = pd.Series(G, index=pd.DatetimeIndex(t_idx)).rolling(
|
||||
"30min", center=True, min_periods=5).max().values
|
||||
fitm = ((el_deg > 12.0) & (G > 500.0) & (G < 1015.0)
|
||||
& (~cloud_mask) & (G >= 0.98 * roll))
|
||||
Gs = G[fitm]
|
||||
AMs = am[fitm]
|
||||
n_fit = int(fitm.sum())
|
||||
if n_fit < 20:
|
||||
raise RuntimeError("Muy pocas muestras claras para ajustar el modelo "
|
||||
f"(n={n_fit}).")
|
||||
|
||||
def sse_of(A, Bc, C):
|
||||
return float(np.sum((Gs - (A * np.exp(-Bc * AMs) + C)) ** 2))
|
||||
|
||||
best = None
|
||||
for A in range(900, 1501, 50):
|
||||
for Bc in np.arange(0.05, 0.61, 0.02):
|
||||
for C in range(0, 301, 10):
|
||||
s = sse_of(A, Bc, C)
|
||||
if best is None or s < best[0]:
|
||||
best = (s, float(A), float(Bc), float(C))
|
||||
# refinamiento local
|
||||
_, A0, B0, C0 = best
|
||||
for A in range(int(A0) - 50, int(A0) + 51, 10):
|
||||
for Bc in np.arange(B0 - 0.02, B0 + 0.021, 0.005):
|
||||
for C in range(int(C0) - 10, int(C0) + 11, 5):
|
||||
if A <= 0 or Bc <= 0 or C < 0:
|
||||
continue
|
||||
s = sse_of(A, Bc, C)
|
||||
if best is not None and s < best[0]:
|
||||
best = (s, float(A), float(Bc), float(C))
|
||||
sse, A, Bc, C = best
|
||||
rms = float(np.sqrt(sse / n_fit))
|
||||
am_finite = np.isfinite(am)
|
||||
am_safe = np.where(am_finite, am, 0.0)
|
||||
# La curva solo se evalua donde la masa de aire es finita (el>=15). Para
|
||||
# 0<el<15 la formula de Kasten-Young diverge (am=inf); reportar
|
||||
# A*exp(-B*0)=A ahi seria fisicamente incorrecto.
|
||||
curve = np.where((el_deg > 0.0) & am_finite,
|
||||
A * np.exp(-Bc * am_safe) + C, 0.0)
|
||||
# Pico del modelo a mediodia (masa de aire minima) = irradiancia maxima
|
||||
# de cielo despejado en el sitio.
|
||||
if am_finite.any():
|
||||
am_min = float(np.min(am[am_finite]))
|
||||
else:
|
||||
am_min = 1.0
|
||||
model_peak = A * np.exp(-Bc * am_min) + C
|
||||
return A, Bc, C, rms, n_fit, curve, model_peak
|
||||
|
||||
|
||||
def run(tag, nofig=False):
|
||||
from compare_sessions import normalize
|
||||
src = ROOT / f"{tag}.txt"
|
||||
if not src.exists():
|
||||
raise SystemExit(f"Log {src.name} no encontrado en la raiz.")
|
||||
tmp = Path(tempfile.gettempdir()) / (tag + "_clearsky.txt")
|
||||
normalize(src, tmp)
|
||||
df_s, df_e = pl.parse_log(tmp)
|
||||
df, ph = pl.build_physical(df_s, df_e)
|
||||
|
||||
G = df["G_POA"].values
|
||||
Voc = df["Voc"].values
|
||||
Isc = df["Isc"].values
|
||||
Pc = df["P_CPV"].values
|
||||
t = df["timestamp"]
|
||||
|
||||
el, am = solar_geometry(df["timestamp"])
|
||||
ces = pl.cloud_events(df)
|
||||
cloud_mask = np.zeros(len(df), dtype=bool)
|
||||
for c in ces:
|
||||
t0 = pd.Timestamp(c["t_start"])
|
||||
t1 = t0 + pd.Timedelta(seconds=c["dur_s"])
|
||||
cloud_mask |= (df["timestamp"] >= t0) & (df["timestamp"] <= t1)
|
||||
|
||||
A, Bc, C, rms, n_fit, curve, model_peak = fit_clearsky(
|
||||
el, am, G, cloud_mask, t.values)
|
||||
clipped = G >= G_CLIP
|
||||
n_clip = int(clipped.sum())
|
||||
dt_med = float(np.median(df["dt_s"]))
|
||||
|
||||
# correccion monotona: lo saturado toma el modelo (nunca por debajo
|
||||
# de los 1024 medidos); lo demas conserva la medida
|
||||
G_est = np.where(clipped, np.maximum(1024.0, curve), G)
|
||||
|
||||
# R_opt y P_ref: con y sin correccion
|
||||
lit = G > 600
|
||||
R_now = float((Isc[lit] / G[lit]).max())
|
||||
P_ref_now = df["P_ref"].values
|
||||
litc = G_est > 600
|
||||
R_corr = float((Isc[litc] / G_est[litc]).max())
|
||||
P_ref_corr = R_corr * G_est * Voc * pl.FF
|
||||
|
||||
# ventanas identicas a las del articulo (metrics.json)
|
||||
m_full = pl.window_metrics(df, "Full (G>50)")
|
||||
m_clear = pl.window_metrics(df[df["G_POA"] > 600], "Clear (G>600)")
|
||||
df_c = df.copy()
|
||||
df_c["G_POA"] = G_est
|
||||
df_c["P_ref"] = P_ref_corr
|
||||
m_full_c = pl.window_metrics(df_c, "Full (G>50)")
|
||||
m_clear_c = pl.window_metrics(df_c[df_c["G_POA"] > 600], "Clear (G>600)")
|
||||
|
||||
df_mod = df.copy()
|
||||
df_mod["P_ref"] = P_ref_corr
|
||||
t95_now = pl.recovery_t95(df, df_e)
|
||||
t95_corr = pl.recovery_t95(df_mod, df_e)
|
||||
|
||||
# MAE con la referencia corregida (ventana de cielo claro del articulo)
|
||||
Isc_ref_corr = R_corr * G_est
|
||||
wc = (G > 600)
|
||||
MAE_I_now = float(np.mean(np.abs((R_now * G) - Isc)) * 1000.0)
|
||||
MAE_I_corr = float(np.mean(np.abs(Isc_ref_corr - Isc)[wc])) * 1000.0
|
||||
MAE_P_now = m_clear["MAE_P_mW"]
|
||||
MAE_P_corr = float(np.mean(np.abs(P_ref_corr - Pc)[wc])) * 1000.0
|
||||
|
||||
print("\n" + "=" * 72)
|
||||
print(f" CORRECCION DE SATURACION (1024 W/m2) - {tag}")
|
||||
print(f" Aguascalientes, Ags., Mexico (21.8756 N, 102.2854 W, 1896 m)")
|
||||
print("=" * 72)
|
||||
print(f" Modelo cielo despejado: G_cs = {A:.0f} * exp(-{Bc:.3f} * AM) + {C:.0f}")
|
||||
print(f" rms sobre n={n_fit} muestras claras no saturadas: {rms:.0f} W/m2")
|
||||
print(f" Pico: medido = {G.max():.0f} W/m2 (tope del ADC) | "
|
||||
f"estimado = {G_est.max():.0f} W/m2")
|
||||
print(f" Muestras saturadas: {n_clip} "
|
||||
f"({100.0 * n_clip / len(df):.1f} % del log, ~{n_clip * dt_med / 60:.0f} min)")
|
||||
print(f" H (kWh/m2, G>50): {m_full['H_kWh_m2']} -> "
|
||||
f"{m_full_c['H_kWh_m2']} "
|
||||
f"(+{100.0 * (m_full_c['H_kWh_m2'] / m_full['H_kWh_m2'] - 1):.1f} %)")
|
||||
print(f" R_opt (uA/W/m2): {R_now * 1e6:.0f} -> {R_corr * 1e6:.0f}")
|
||||
print(f" eta_tr (G>50): {m_full['eta_tr_pct']} % -> "
|
||||
f"{m_full_c['eta_tr_pct']} %")
|
||||
print(f" eta_tr (G>600): {m_clear['eta_tr_pct']} % -> "
|
||||
f"{m_clear_c['eta_tr_pct']} %")
|
||||
print(f" MAE_I (G>600): {MAE_I_now:.1f} mA -> "
|
||||
f"{MAE_I_corr:.1f} mA")
|
||||
print(f" MAE_P (G>600): {MAE_P_now} mW -> {MAE_P_corr:.1f} mW")
|
||||
print(f" med P/Pref (G>600): {m_clear['ratio_P_Pref_median'] if 'ratio_P_Pref_median' in m_clear else float(np.median(Pc[wc] / P_ref_now[wc])):.3f} -> "
|
||||
f"{float(np.median(Pc[wc] / P_ref_corr[wc])):.3f}")
|
||||
if len(t95_now) == len(t95_corr) and len(t95_now):
|
||||
print("\n t95 (s): antes -> corregido")
|
||||
for a, b in zip(t95_now.itertuples(), t95_corr.itertuples()):
|
||||
print(f" {a.trigger:>14} @ {str(a.t_trigger)[11:19]}: "
|
||||
f"{a.t95_s} -> {b.t95_s}")
|
||||
|
||||
if not nofig:
|
||||
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12.5, 4.4),
|
||||
sharex=True)
|
||||
ax1.plot(t, Pc * 1000, color="tab:red", lw=0.8, label="P_CPV")
|
||||
ax1.plot(t, P_ref_now * 1000, color="k", lw=1.1,
|
||||
label="P_ref (G medida)")
|
||||
ax1.plot(t, P_ref_corr * 1000, color="tab:blue", ls="--", lw=1.1,
|
||||
label="P_ref (G corregida)")
|
||||
ax1.set_ylabel("Potencia (mW)")
|
||||
ax1.set_xlabel("Hora local (UTC-6)")
|
||||
ax1.legend(fontsize=8)
|
||||
ax1.grid(alpha=0.3)
|
||||
|
||||
if n_clip:
|
||||
idx = np.where(clipped)[0]
|
||||
start = 0
|
||||
for j in range(1, len(idx) + 1):
|
||||
if j == len(idx) or idx[j] != idx[j - 1] + 1:
|
||||
ax2.axvspan(t.iloc[idx[start]], t.iloc[idx[j - 1]],
|
||||
color="tab:orange", alpha=0.18)
|
||||
start = j
|
||||
ax2.plot(t, G, color="tab:orange", lw=0.8, label="G medida")
|
||||
ax2.plot(t, G_est, color="tab:orange", ls="--", lw=1.3,
|
||||
label="G estimada (corregida)")
|
||||
ax2.plot(t, curve, color="gray", ls=":", lw=0.8,
|
||||
label="Modelo cielo despejado")
|
||||
ax2.axhline(1024, color="gray", ls="-.", lw=0.8)
|
||||
ax2.text(t.iloc[1], 1030, "saturacion 1024 W/m2",
|
||||
fontsize=8, color="dimgray")
|
||||
ax2.set_ylabel("Irradiancia global (W/m2)")
|
||||
ax2.set_xlabel("Hora local (UTC-6)")
|
||||
ax2.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M"))
|
||||
ax2.legend(fontsize=8, loc="upper right")
|
||||
ax2.grid(alpha=0.3)
|
||||
fig.tight_layout()
|
||||
|
||||
outdir = ROOT / "articulo" / f"resultados_{tag}"
|
||||
outdir.mkdir(parents=True, exist_ok=True)
|
||||
fig.savefig(outdir / "preview_irradiance_est.png", dpi=150)
|
||||
|
||||
res = {
|
||||
"tag": tag,
|
||||
"model": "G_cs = A*exp(-B*AM) + C, Ajustado al sobre-ensvolvente "
|
||||
"claro no saturado",
|
||||
"model_scale_A_Wm2": round(A, 1), "model_B": round(Bc, 4), "model_C": C,
|
||||
"model_rms_clear_Wm2": round(rms, 1), "n_fit_clear": n_fit,
|
||||
"model_peak_Wm2": round(model_peak, 0),
|
||||
"G_max_measured_Wm2": round(float(G.max()), 1),
|
||||
"G_max_estimated_Wm2": round(float(G_est.max()), 1),
|
||||
"n_clipped": n_clip,
|
||||
"clipped_pct_log": round(100 * n_clip / len(df), 2),
|
||||
"H_kWh_m2_full_measured": m_full["H_kWh_m2"],
|
||||
"H_kWh_m2_full_corrected": m_full_c["H_kWh_m2"],
|
||||
"R_opt_uA_per_Wm2_measured": round(R_now * 1e6, 1),
|
||||
"R_opt_uA_per_Wm2_corrected": round(R_corr * 1e6, 1),
|
||||
"eta_tr_pct_full_measured": m_full["eta_tr_pct"],
|
||||
"eta_tr_pct_full_corrected": m_full_c["eta_tr_pct"],
|
||||
"eta_tr_pct_clear_measured": m_clear["eta_tr_pct"],
|
||||
"eta_tr_pct_clear_corrected": m_clear_c["eta_tr_pct"],
|
||||
"MAE_I_mA_clear_measured": round(MAE_I_now, 2),
|
||||
"MAE_I_mA_clear_corrected": round(MAE_I_corr, 2),
|
||||
"MAE_P_mW_clear_measured": MAE_P_now,
|
||||
"MAE_P_mW_clear_corrected": round(MAE_P_corr, 2),
|
||||
"ratio_P_Pref_median_clear_measured":
|
||||
round(float(np.median(Pc[wc] / P_ref_now[wc])), 3),
|
||||
"ratio_P_Pref_median_clear_corrected":
|
||||
round(float(np.median(Pc[wc] / P_ref_corr[wc])), 3),
|
||||
"location": "Aguascalientes, Ags., Mexico "
|
||||
"(21.8756 N, 102.2854 W, 1896 m, UTC-6)",
|
||||
}
|
||||
outdir = ROOT / "articulo" / f"resultados_{tag}"
|
||||
outdir.mkdir(parents=True, exist_ok=True)
|
||||
(outdir / f"irradiance_est_{tag}.json").write_text(
|
||||
json.dumps(res, indent=2, ensure_ascii=False), encoding="utf-8")
|
||||
print(f"\n[ok] JSON (y figura) en {outdir}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
tag = sys.argv[1] if len(sys.argv) > 1 else "21092025"
|
||||
nofig = len(sys.argv) > 2 and sys.argv[2] == "nofig"
|
||||
run(tag, nofig=nofig)
|
||||
@@ -0,0 +1,171 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Comparacion de todas las sesiones de campo disponibles (logs en la raiz
|
||||
del repositorio).
|
||||
|
||||
Por log se reporta:
|
||||
* ventana temporal y numero de muestras
|
||||
* eta_tr, MAE_P, energia, irradiancia acumulada (metricas del parser)
|
||||
* mediana P/Pref y fraccion de muestras con P >= 0.95*P_ref
|
||||
* SATURACION del piranometro: el ADC se topa a 1024 W/m2
|
||||
- n / fraccion de muestras saturadas (G >= 1023.9)
|
||||
- minutos acumulados saturados
|
||||
- R_opt (max Isc/G) del pipeline actual vs R_opt sin muestras
|
||||
saturadas -> factor de inflacion de P_ref por el clipping
|
||||
- eta_tr estimado si R_opt se calcula sin muestras saturadas
|
||||
* n transitorios nubosos detectados
|
||||
|
||||
Uso: py -3.12 compare_sessions.py
|
||||
Salida: articulo/comparacion_sesiones.json + tabla en consola
|
||||
"""
|
||||
|
||||
import json
|
||||
import re
|
||||
import sys
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
import parse_log as pl
|
||||
|
||||
ROOT = Path(__file__).resolve().parent
|
||||
|
||||
# (archivo en la raiz, etiqueta, formato)
|
||||
LOGS = [
|
||||
("hasta la 1pm 020925.txt", "02 Sep 11:27-13:00", "new"),
|
||||
("esp_1223_02092025.txt", "02 Sep 12:23-..", "old"),
|
||||
("log(3).txt", "14 Sep (manana)", "new"),
|
||||
("gyuggyhoy.txt", "14 Sep 10:28-..", "old"),
|
||||
("10092025.txt", "10 Sep", "new"),
|
||||
("15092025.txt", "15 Sep", "new"),
|
||||
("19092025_.txt", "19 Sep", "new"),
|
||||
("20092025_desde1pm.txt", "20 Sep (desde 13:44)", "new"),
|
||||
("21092025.txt", "21 Sep (paper)", "new"),
|
||||
("21092025_2PM.txt", "21 Sep (parcial, dup.)", "new"),
|
||||
("23092025.txt", "23 Sep", "new"),
|
||||
("full_log_21082025.txt", "21 Ago (log completo)", "old"),
|
||||
("esp32_log_20250821_102525.txt", "21 Ago 10:25", "old"),
|
||||
("esp32_log_20250821_1143.txt", "21 Ago 11:43", "old"),
|
||||
("esp32_log_20250826_114833.txt", "26 Ago 11:48", "old"),
|
||||
("esp32_log_20250827_095607.txt", "27 Ago 09:56", "old"),
|
||||
("esp32_log_20250827_110728.txt", "27 Ago 11:07", "old"),
|
||||
("esp32_log_20250827_449pm.txt", "27 Ago 16:49", "old"),
|
||||
("log_26082025.txt", "26 Ago (corto)", "old"),
|
||||
("log_2608205_2.txt", "26 Ago (corto)", "old"),
|
||||
("nuevolog}.txt", "26 Ago 13:28", "old"),
|
||||
("test_2108.txt", "21 Ago (test)", "old"),
|
||||
("test_3.txt", "21 Ago (test)", "old"),
|
||||
("test_$.txt", "21 Ago (test)", "old"),
|
||||
]
|
||||
|
||||
G_CLIP = 1023.9 # umbral: ADC en tope => G = 1024.0 W/m2
|
||||
|
||||
|
||||
def normalize(path: Path, tmp: Path):
|
||||
"""Copia el log normalizando el prefijo 'LOG:' del firmware antiguo."""
|
||||
with open(path, "r", encoding="utf-8", errors="replace") as f:
|
||||
lines = f.readlines()
|
||||
out = []
|
||||
for line in lines:
|
||||
line = line.rstrip("\n")
|
||||
if line.startswith("LOG:"):
|
||||
line = line[4:]
|
||||
out.append(line)
|
||||
tmp.write_text("\n".join(out) + "\n", encoding="utf-8")
|
||||
|
||||
|
||||
def session_report(path: Path, label: str, fmt: str):
|
||||
if not path.exists():
|
||||
return {"file": path.name, "label": label, "error": "archivo inexistente"}
|
||||
tmp = Path(tempfile.gettempdir()) / (path.stem + "_norm.txt")
|
||||
try:
|
||||
normalize(path, tmp)
|
||||
df_s, df_e = pl.parse_log(tmp)
|
||||
df, ph = pl.build_physical(df_s, df_e)
|
||||
except Exception as exc:
|
||||
return {"file": path.name, "label": label, "fmt": fmt,
|
||||
"error": f"{type(exc).__name__}: {exc}"}
|
||||
|
||||
m = pl.window_metrics(df, "full")
|
||||
if m["n_samples"] == 0:
|
||||
return {"file": path.name, "label": label, "fmt": fmt,
|
||||
"error": "sin muestras validas"}
|
||||
|
||||
day = df[df["G_POA"] > 50]
|
||||
n_clip = int((df["G_POA"] >= G_CLIP).sum())
|
||||
dt_med = float(np.median(df["dt_s"])) if "dt_s" in df else 2.0
|
||||
clip_min = n_clip * dt_med / 60.0 if n_clip else 0.0
|
||||
|
||||
lit = df[df["G_POA"] > 600]
|
||||
R_full = float((lit["Isc"] / lit["G_POA"]).max()) if len(lit) else float("nan")
|
||||
unc = df[(df["G_POA"] > 600) & (df["G_POA"] < 1015)]
|
||||
R_unc = float((unc["Isc"] / unc["G_POA"]).max()) if len(unc) else float("nan")
|
||||
infl = (R_full / R_unc) if (R_unc == R_unc and R_unc > 0) else None
|
||||
|
||||
w = df[df["G_POA"] > 50]
|
||||
ratio = (w["P_CPV"] / w["P_ref"]).values
|
||||
return {
|
||||
"file": path.name,
|
||||
"label": label,
|
||||
"fmt": fmt,
|
||||
"t_inicio": m["t_inicio"],
|
||||
"t_fin": m["t_fin"],
|
||||
"n_samples": m["n_samples"],
|
||||
"eta_tr_pct": m["eta_tr_pct"],
|
||||
"MAE_P_mW": m["MAE_P_mW"],
|
||||
"E_Wh": m["E_Wh"],
|
||||
"H_kWh_m2": m["H_kWh_m2"],
|
||||
"ratio_P_Pref_median": round(float(np.median(ratio)), 3),
|
||||
"frac_P_above_095Pref": round(float(np.mean(w["P_CPV"].values >= 0.95 * w["P_ref"].values)), 3),
|
||||
"G_max_Wm2": round(float(df["G_POA"].max()), 1),
|
||||
"n_clip": n_clip,
|
||||
"clip_pct_day": round(100.0 * n_clip / len(day), 1) if len(day) else 0.0,
|
||||
"clip_min": round(clip_min, 1),
|
||||
"R_opt_uA_per_Wm2": round(R_full * 1e6, 1),
|
||||
"R_opt_unc_uA_per_Wm2": round(R_unc * 1e6, 1) if R_unc == R_unc else None,
|
||||
"inflation_factor": round(infl, 4) if infl else None,
|
||||
"eta_tr_pct_Ropt_corrected": round(m["eta_tr_pct"] * infl, 2) if (infl and m["eta_tr_pct"]) else None,
|
||||
"n_cloud_events": len(pl.cloud_events(df)),
|
||||
}
|
||||
|
||||
|
||||
def main():
|
||||
rows = []
|
||||
for name, label, fmt in LOGS:
|
||||
rep = session_report(ROOT / name, label, fmt)
|
||||
rows.append(rep)
|
||||
if "error" in rep:
|
||||
print(f"[x] {label:<26} {rep['error']}")
|
||||
ok = [r for r in rows if r.get("eta_tr_pct")]
|
||||
ok.sort(key=lambda r: r["eta_tr_pct"], reverse=True)
|
||||
|
||||
print("\n" + "=" * 118)
|
||||
print(f"{'sesion':<24} {'horario':<19} {'n':>5} {'eta%':>6} {'MAE_P':>7} "
|
||||
f"{'E Wh':>6} {'H kWh/m2':>9} {'med P/Pref':>10} {'%>=0.95':>8} "
|
||||
f"{'Gmax':>5} {'nClip':>5} {'%clip':>5} {'minClip':>7} {'Ropt(uA/Wm2)':>13} {'infl':>6} {'nNub':>4}")
|
||||
print("=" * 118)
|
||||
for r in ok:
|
||||
infl = f"{r['inflation_factor']}x" if r["inflation_factor"] else " -"
|
||||
print(f"{r['label']:<24} {r['t_inicio'][11:16]}-{r['t_fin'][11:16]} "
|
||||
f"{r['n_samples']:>5} {r['eta_tr_pct']:>6} {r['MAE_P_mW']:>7.1f} "
|
||||
f"{r['E_Wh']:>6} {r['H_kWh_m2']:>9} {r['ratio_P_Pref_median']:>10} "
|
||||
f"{100 * r['frac_P_above_095Pref']:>7.0f}% {r['G_max_Wm2']:>5.0f} "
|
||||
f"{r['n_clip']:>5} {r['clip_pct_day']:>5.1f} {r['clip_min']:>7.0f} "
|
||||
f"{r['R_opt_uA_per_Wm2']:>13.0f} {infl:>6} {r['n_cloud_events']:>4}")
|
||||
print("=" * 118)
|
||||
print("NOTA: infl = R_opt(clips incluidos)/R_opt(sin clips); el clipping "
|
||||
"INFLA P_ref y subestima eta, por lo que eta (corregido) = eta * infl\n")
|
||||
for r in ok:
|
||||
if r.get("eta_tr_pct_Ropt_corrected"):
|
||||
print(f" {r['label']:<24} eta corregido (solo R_opt) ~ {r['eta_tr_pct_Ropt_corrected']} %")
|
||||
|
||||
out = ROOT / "articulo" / "comparacion_sesiones.json"
|
||||
out.write_text(json.dumps(rows, indent=2, ensure_ascii=False), encoding="utf-8")
|
||||
print(f"\n[ok] tabla guardada en {out}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Binary file not shown.
+37
@@ -0,0 +1,37 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
# diag_x0.py — characterize the spurious X~0 points in the 14/09 captures
|
||||
from datetime import datetime
|
||||
import numpy as np
|
||||
import plot_logs as pl
|
||||
|
||||
A = pl.LOGS[1][1] # log(3)
|
||||
B = pl.LOGS[2][1] # gyuggyhoy
|
||||
print('log(3) window: 10:03:36 -> 14:15:37 | gyuggyhoy window: 10:28:12 -> 14:57:34')
|
||||
print('common/overlap window: 10:28:12 -> 14:15:37')
|
||||
g_lo = datetime(2025, 9, 14, 10, 28, 12)
|
||||
g_hi = datetime(2025, 9, 14, 14, 57, 34)
|
||||
|
||||
for name, path in [('21aug', pl.LOGS[0][1]), ('log(3)', A), ('gyuggyhoy', B)]:
|
||||
L = pl.parse_log(path)
|
||||
X, Y = L['X'], L['Y']
|
||||
print('\n== %s (n=%d) ==' % (name, len(X)))
|
||||
print(' X==0: %d X<1000: %d X<5000: %d min X=%d' % ((X == 0).sum(), (X < 1000).sum(), (X < 5000).sum(), int(X.min())))
|
||||
print(' Y==0: %d Y<1000: %d min Y=%d' % ((Y == 0).sum(), (Y < 1000).sum(), int(Y.min())))
|
||||
|
||||
print('\n--- detail: log(3) samples with X<1000 (max 30 shown) ---')
|
||||
L = pl.parse_log(A)
|
||||
X, Y, C, er, t = L['X'], L['Y'], L['C'], L['er'], L['t']
|
||||
z = np.where(X < 1000)[0]
|
||||
print('total X<1000 :', len(z))
|
||||
print('inside gyuggyhoy overlap [10:28:12..14:57:34]:', int(sum(1 for i in z if g_lo <= t[i] <= g_hi)))
|
||||
print('in pre-overlap tail [10:03:36..10:28:12] :', int(sum(1 for i in z if t[i] < g_lo)))
|
||||
shown = 0
|
||||
for i in z:
|
||||
if shown >= 30:
|
||||
break
|
||||
win = 'OVERLAP' if (g_lo <= t[i] <= g_hi) else ('pre-10:28' if t[i] < g_lo else 'post-14:15')
|
||||
pv = '(X=%d,Y=%d)' % (X[i - 1], Y[i - 1]) if i > 0 else '-'
|
||||
nx = '(X=%d,Y=%d)' % (X[i + 1], Y[i + 1]) if i + 1 < len(X) else '-'
|
||||
print(' %s X=%-6d Y=%-6d C=%-7d er=%-4d [%-10s] prev %s next %s' % (
|
||||
t[i].strftime('%H:%M:%S'), X[i], Y[i], C[i], er[i], win, pv, nx))
|
||||
shown += 1
|
||||
@@ -0,0 +1,16 @@
|
||||
state/
|
||||
.deploy_backups/
|
||||
data_logs/
|
||||
firmware/
|
||||
**/__pycache__/
|
||||
**/*.pyc
|
||||
.pytest_cache/
|
||||
.git/
|
||||
.env
|
||||
.env.*
|
||||
*.sqlite3*
|
||||
*.token
|
||||
*.secret
|
||||
*.bak
|
||||
*_test.py
|
||||
*_test.cjs
|
||||
@@ -0,0 +1,25 @@
|
||||
FROM python:3.11-slim
|
||||
|
||||
ENV TZ=Etc/GMT+6
|
||||
RUN apt-get update && apt-get install -y --no-install-recommends tzdata \
|
||||
&& ln -snf /usr/share/zoneinfo/$TZ /etc/localtime \
|
||||
&& echo $TZ > /etc/timezone \
|
||||
&& rm -rf /var/lib/apt-get/lists/*
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY requirements.txt /app/requirements.txt
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
|
||||
# Copiar el paquete modular
|
||||
COPY app /app/app
|
||||
COPY static /app/static
|
||||
|
||||
RUN mkdir -p /app/data_logs /app/firmware /app/state
|
||||
VOLUME ["/app/data_logs", "/app/firmware", "/app/state"]
|
||||
|
||||
EXPOSE 8000
|
||||
|
||||
# Socket ownership is in memory; multiple workers need an external coordinator.
|
||||
HEALTHCHECK --interval=10s --timeout=3s --start-period=10s --retries=3 CMD ["python", "-c", "import json,urllib.request; raise SystemExit(not json.load(urllib.request.urlopen('http://127.0.0.1:8000/health',timeout=2))['ok'])"]
|
||||
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "1", "--ws-max-size", "16384"]
|
||||
@@ -0,0 +1,212 @@
|
||||
// Dependency-free state/routing tests for the existing inline dashboard script.
|
||||
const assert = require('node:assert/strict');
|
||||
const fs = require('node:fs');
|
||||
const vm = require('node:vm');
|
||||
const path = require('node:path');
|
||||
|
||||
class Element {
|
||||
constructor() {
|
||||
this.children = []; this.style = {}; this.value = ''; this.files = [];
|
||||
this.disabled = false; this.checked = false; this._text = '';
|
||||
this.classList = {toggle() {}};
|
||||
}
|
||||
set textContent(value) { this._text = String(value); this.children = []; }
|
||||
get textContent() { return this._text; }
|
||||
get firstChild() { return this.children[0] || null; }
|
||||
appendChild(child) { this.children.push(child); return child; }
|
||||
removeChild(child) { this.children.splice(this.children.indexOf(child), 1); }
|
||||
}
|
||||
|
||||
const elements = new Map();
|
||||
const element = id => {
|
||||
if (!elements.has(id)) elements.set(id, new Element());
|
||||
return elements.get(id);
|
||||
};
|
||||
const sockets = [], requests = [], timers = [], confirmations = [];
|
||||
let responseOverride = null;
|
||||
class Socket {
|
||||
constructor(url) { this.url = url; this.readyState = 1; this.sent = []; sockets.push(this); }
|
||||
send(message) { this.sent.push(message); }
|
||||
close() { this.readyState = 3; if (this.onclose) this.onclose(); }
|
||||
emit(message) { this.onmessage({data: message}); }
|
||||
}
|
||||
const context = vm.createContext({
|
||||
console, AbortController, DOMException, Date, Number, JSON,
|
||||
document: {
|
||||
getElementById: element,
|
||||
createElement: () => new Element(),
|
||||
querySelectorAll: () => [element('calPyrano'), element('pcbSel'), element('otaFile'), element('otaVersion')],
|
||||
},
|
||||
window: {addEventListener() {}},
|
||||
location: {protocol: 'https:', host: 'test.invalid'},
|
||||
localStorage: {setItem() {}, getItem() { return ''; }},
|
||||
WebSocket: Socket,
|
||||
fetch: async (url, options = {}) => {
|
||||
requests.push({url, options});
|
||||
if (responseOverride) {
|
||||
const override = responseOverride(url, options);
|
||||
if (override) return override;
|
||||
}
|
||||
const body = url.endsWith('/logs') || url === '/api/devices' ? [] : {ok: true};
|
||||
return {ok: true, json: async () => body};
|
||||
},
|
||||
setTimeout: callback => { timers.push(callback); return timers.length; },
|
||||
clearTimeout() {}, setInterval() {},
|
||||
confirm: message => { confirmations.push(message); return true; },
|
||||
alert: message => { throw new Error('Unexpected alert: ' + message); },
|
||||
});
|
||||
const html = fs.readFileSync(path.join(__dirname, 'static', 'index.html'), 'utf8');
|
||||
const scripts = [...html.matchAll(/<script(?:\s[^>]*)?>([\s\S]*?)<\/script>/g)];
|
||||
vm.runInContext(scripts.map(match => match[1]).join('\n'), context);
|
||||
const A = 'esp32-001122aabbcc', B = 'esp32-001122aabbdd';
|
||||
context.fleet = [{device_id: A, alias: 'Tracker A'}, {device_id: B, alias: 'Tracker B'}];
|
||||
context.charts.traj = {options: {scales: {x: {type: 'linear', min: 0, max: 106000}}}};
|
||||
const config = id => 'CONFIG:' + JSON.stringify({device_id: id, pyrano: 0.2, azdev: 5, pcb_version: 'V1'});
|
||||
const axisAck = (id, x, y, base) => 'AXISCFG:' + JSON.stringify({device_id:id, x, y, base, x_budget:x*base, y_budget:y*base});
|
||||
const flush = async () => { for (let i = 0; i < 5; i++) await new Promise(resolve => setImmediate(resolve)); };
|
||||
|
||||
async function run() {
|
||||
context.selectDevice(A);
|
||||
assert.equal(context.charts.traj.options.scales.x.max, 106000, 'trajectory uses motor steps, not time');
|
||||
const old = sockets.at(-1);
|
||||
assert(old.url.endsWith('device_id=' + A));
|
||||
assert.equal(context.deviceReady, false);
|
||||
old.emit(config(A));
|
||||
assert.equal(context.deviceReady, true);
|
||||
old.emit('DATA:' + JSON.stringify({device_id: A, ts: 100, pcpv_mw: 590, x: 12, y: 34}));
|
||||
assert.equal(context.samples.length, 1);
|
||||
old.emit('DATA:' + JSON.stringify({device_id: B, ts: 101}));
|
||||
assert.equal(context.samples.length, 1, 'foreign payload must be ignored');
|
||||
|
||||
// Axis controls retain desired values while partial ACKs describe actual board state.
|
||||
old.emit('STATUS:ONLINE');
|
||||
old.emit(axisAck(A, 3, 1, 4));
|
||||
assert(element('axisSchedule').textContent.includes('12 X y luego 4 Y'));
|
||||
element('axisXFactor').value = '5'; element('axisYFactor').value = '2';
|
||||
context.sendAxisFactors();
|
||||
assert.deepEqual(old.sent, ['SET_PARAM:axisXFactor=5', 'SET_PARAM:axisYFactor=2']);
|
||||
assert(context.axisRequested);
|
||||
old.emit(axisAck(A, 5, 1, 4));
|
||||
assert(context.axisRequested, 'first ACK must not confirm the second, still-pending factor');
|
||||
assert(element('axisSchedule').textContent.includes('Solicitud pendiente'));
|
||||
assert.equal(element('axisYFactor').value, '2', 'partial ACK must not overwrite requested Y');
|
||||
old.emit(axisAck(B, 5, 2, 4));
|
||||
assert(context.axisRequested, 'foreign ACK must not confirm a request');
|
||||
old.emit('AXISCFG:' + JSON.stringify({device_id:A,x:5,y:2,base:4,x_budget:1,y_budget:8}));
|
||||
assert(context.axisRequested, 'inconsistent budgets must be rejected');
|
||||
old.emit(axisAck(A, 5, 2, 4));
|
||||
assert.equal(context.axisRequested, null);
|
||||
assert(element('axisSchedule').textContent.includes('20 X y luego 8 Y'));
|
||||
element('inCicleMax').value = '3'; context.sendParam('cicleMax', 'inCicleMax');
|
||||
old.emit(axisAck(A, 5, 2, 4));
|
||||
assert(context.axisRequested, 'a stale base ACK must not confirm the newly requested base');
|
||||
old.emit(axisAck(A, 5, 2, 3));
|
||||
assert.equal(context.axisRequested, null);
|
||||
element('inCicleMax').value = '0';
|
||||
assert.throws(() => context.sendParam('cicleMax', 'inCicleMax'), /entero entre 1 y 64/);
|
||||
element('inCicleMax').value = '64';
|
||||
assert.throws(() => context.sendParam('cicleMax', 'inCicleMax'), /superar 64 ciclos/);
|
||||
element('axisXFactor').value = '2.5';
|
||||
assert.throws(() => context.sendAxisFactors(), /enteros entre 1 y 8/);
|
||||
old.emit('STATUS:OFFLINE');
|
||||
assert.equal(context.axisConfirmed, null, 'board disconnect must clear confirmation even while browser WS stays open');
|
||||
const beforeOffline = old.sent.length;
|
||||
element('axisXFactor').value = '3'; element('axisYFactor').value = '1';
|
||||
context.sendAxisFactors();
|
||||
assert.equal(old.sent.length, beforeOffline, 'axis request must not be sent to an offline board');
|
||||
old.emit(axisAck(A, 3, 1, 4));
|
||||
assert.equal(context.axisConfirmed, null, 'late ACK while board is offline must be ignored');
|
||||
old.emit('STATUS:ONLINE');
|
||||
context.sendAxisFactors();
|
||||
assert.equal(context.axisConfirmed, null, 'old firmware without ACK must remain unconfirmed');
|
||||
assert(context.axisRequested);
|
||||
old.emit(axisAck(A, 3, 1, 4));
|
||||
old.sent.length = 0;
|
||||
await flush();
|
||||
|
||||
// An HTTP response initiated for A must never populate B after switching.
|
||||
let finish;
|
||||
responseOverride = url => url === '/api/devices/' + A + '/calib'
|
||||
? new Promise(resolve => { finish = resolve; }) : null;
|
||||
element('calPyrano').value = '0.3';
|
||||
context.applyCalib();
|
||||
const request = requests.at(-1);
|
||||
context.selectDevice(B);
|
||||
assert.equal(context.axisConfirmed, null, 'device selection must clear the previous board confirmation');
|
||||
assert.equal(context.axisRequested, null);
|
||||
assert.equal(context.samples.length, 0);
|
||||
assert.equal(context.telSamples.length, 0);
|
||||
assert.equal(element('t_power').textContent, '--');
|
||||
assert.equal(element('inPosX').value, '');
|
||||
assert.equal(context.deviceReady, false);
|
||||
assert.equal(request.options.signal.aborted, true);
|
||||
const current = sockets.at(-1);
|
||||
old.emit(config(A));
|
||||
old.emit('POS:999:999');
|
||||
old.close();
|
||||
assert.equal(element('posX').textContent, '--');
|
||||
assert.equal(context.ws, current);
|
||||
current.emit(config(B));
|
||||
current.emit('STATUS:ONLINE');
|
||||
current.emit(axisAck(A, 3, 1, 4));
|
||||
assert.equal(context.axisConfirmed, null, 'selected B must not accept an A acknowledgement');
|
||||
current.emit(axisAck(B, 1, 1, 4));
|
||||
assert(element('axisSchedule').textContent.includes('4 X y luego 4 Y'));
|
||||
finish({ok: true, json: async () => ({mV_per_WM2: 12345})});
|
||||
await flush();
|
||||
assert(!element('calNote').textContent.includes('12345'));
|
||||
assert.equal(context.cfg.device_id, B);
|
||||
responseOverride = null;
|
||||
|
||||
// Manual OTA explicitly captures selected ID and the image that was confirmed.
|
||||
const sha256 = 'a'.repeat(64);
|
||||
current.emit('OTA_STATE:' + JSON.stringify({device_id: B, connected: true,
|
||||
device: '1.0', available: {version: '2.0', sha256}, auto: false}));
|
||||
assert.equal(element('otaPush').disabled, false);
|
||||
context.pushOta();
|
||||
const push = requests.at(-1);
|
||||
assert.equal(push.url, '/api/devices/' + B + '/ota/push');
|
||||
assert.equal(JSON.parse(push.options.body).sha256, sha256);
|
||||
assert(confirmations.at(-1).includes('Tracker B [' + B + ']'));
|
||||
assert(confirmations.at(-1).includes('2.0'));
|
||||
await flush();
|
||||
assert(element('otaStatus').textContent.includes('Pendiente de confirmar'));
|
||||
context.sendRaw('CMD:10');
|
||||
assert.deepEqual(current.sent, ['CMD:10']);
|
||||
assert.deepEqual(old.sent, []);
|
||||
assert(requests.every(r => !['/api/calib', '/api/pcb', '/ota/push'].includes(r.url)));
|
||||
|
||||
responseOverride = url => url.endsWith('/pcb') || url.endsWith('/ota/auto')
|
||||
? Promise.resolve({ok: false, status: 503, json: async () => ({detail: 'storage unavailable'})}) : null;
|
||||
element('pcbSel').value = 'V2';
|
||||
context.applyPcb();
|
||||
await flush();
|
||||
assert.equal(element('pcbSel').value, 'V1', 'failed PCB save must not display an unpersisted version');
|
||||
assert(element('pcbNote').textContent.includes('storage unavailable'));
|
||||
element('otaAuto').checked = true;
|
||||
context.saveOtaAuto();
|
||||
await flush();
|
||||
assert.equal(element('otaAuto').checked, false, 'failed auto-OTA save must restore server state');
|
||||
assert(element('otaStatus').textContent.includes('storage unavailable'));
|
||||
responseOverride = null;
|
||||
|
||||
// Failed loads must not retain controls for an old connection or overwrite a new one.
|
||||
current.close();
|
||||
assert.equal(context.axisConfirmed, null, 'browser disconnect also clears the board confirmation');
|
||||
assert.equal(context.deviceReady, false);
|
||||
context.sendRaw('CMD:4');
|
||||
assert.deepEqual(current.sent, ['CMD:10']);
|
||||
context.selectDevice('');
|
||||
current.emit('FW:old-firmware');
|
||||
assert.equal(element('otaDevice').textContent, 'sin informar');
|
||||
assert.equal(context.activeDevice, '');
|
||||
assert.equal(element('otaPush').disabled, true);
|
||||
await flush();
|
||||
const repeated = Array.from({length: 16000}, () => ({ts: 100, x: 1, y: 2}));
|
||||
context.seedHistory(repeated);
|
||||
context.seedTel(repeated);
|
||||
assert.equal(context.samples.length, 15000, 'sample cap must hold even for repeated timestamps');
|
||||
assert.equal(context.telSamples.length, 15000, 'telemetry cap must hold even for repeated timestamps');
|
||||
console.log('OK: dashboard selection, stale HTTP/WS isolation, axis ACK/pending/bounds/offline state, control guards and targeted OTA confirmation.');
|
||||
}
|
||||
run().catch(error => { console.error(error); process.exitCode = 1; });
|
||||
@@ -0,0 +1,674 @@
|
||||
"""Isolated integration tests. Requires httpx in the test environment only.
|
||||
|
||||
Run: python -m unittest -v _fleet_test
|
||||
All devices, credentials, logs and OTA files are disposable simulations.
|
||||
"""
|
||||
import json
|
||||
import asyncio
|
||||
import ast
|
||||
import io
|
||||
import logging
|
||||
import re
|
||||
import os
|
||||
from pathlib import Path
|
||||
import subprocess
|
||||
import sqlite3
|
||||
import sys
|
||||
import tempfile
|
||||
import time
|
||||
import unittest
|
||||
from unittest.mock import patch
|
||||
from urllib.parse import urlsplit
|
||||
|
||||
import anyio
|
||||
from fastapi.testclient import TestClient
|
||||
from starlette.websockets import WebSocketDisconnect
|
||||
|
||||
|
||||
ROOT = Path(__file__).resolve().parent
|
||||
A = "esp32-001122aabbcc"
|
||||
B = "esp32-001122aabbdd"
|
||||
ORIGIN = "http://localhost:4000"
|
||||
TEL = ("LOG:[2026-10-30 10:34:03] TEL: t=246s, steps=29825(+1000), "
|
||||
"avgC=5469365, avgV=5160269, avgP=679686, LPF=4338597, "
|
||||
"prox=0.00, CmaxN=53643680, X=-9827, Y=-65788")
|
||||
SAMPLE = "LOG:[2026-10-30 10:34:07] X:54810,Y:48890,C:5469365,V:5160269,P:679686,S:17,er:1500"
|
||||
|
||||
|
||||
class FleetTests(unittest.TestCase):
|
||||
@classmethod
|
||||
def setUpClass(cls):
|
||||
cls.temp = tempfile.TemporaryDirectory(prefix="fleet-test-")
|
||||
cls.directory = Path(cls.temp.name)
|
||||
cls.environment = {
|
||||
"STATE_DIR": str(cls.directory / "state"),
|
||||
"LOGS_DIR": str(cls.directory / "logs"),
|
||||
"FIRMWARE_DIR": str(cls.directory / "firmware"),
|
||||
"ALLOWED_ORIGINS": ORIGIN,
|
||||
"PRIMARY_DEVICE_ID": "",
|
||||
"CREDENTIAL_POLL_SECONDS": "0.1",
|
||||
}
|
||||
cls.original_env = {key: os.environ.get(key) for key in cls.environment}
|
||||
os.environ.update(cls.environment)
|
||||
cls.tokens = {}
|
||||
for device, alias in ((A, "Tracker A"), (B, "Tracker B")):
|
||||
token_file = cls.directory / "state" / "provision" / (device + ".v1.token")
|
||||
cls.cli("add", "--device-id", device, "--alias", alias)
|
||||
cls.tokens[device] = token_file.read_text(encoding="utf-8").strip()
|
||||
# Import only after redirecting every persistent path.
|
||||
from app import config
|
||||
for key in ("STATE_DIR", "LOGS_DIR", "FIRMWARE_DIR"):
|
||||
assert Path(getattr(config, key)).resolve() == Path(cls.environment[key]).resolve()
|
||||
from app.main import app
|
||||
cls.client_context = TestClient(app)
|
||||
cls.client = cls.client_context.__enter__()
|
||||
|
||||
@classmethod
|
||||
def tearDownClass(cls):
|
||||
cls.client_context.__exit__(None, None, None)
|
||||
for key, value in cls.original_env.items():
|
||||
if value is None:
|
||||
os.environ.pop(key, None)
|
||||
else:
|
||||
os.environ[key] = value
|
||||
cls.temp.cleanup()
|
||||
|
||||
@classmethod
|
||||
def cli(cls, *arguments):
|
||||
result = subprocess.run(
|
||||
[sys.executable, "-m", "app.devices", *arguments], cwd=ROOT,
|
||||
env=os.environ.copy(), capture_output=True, text=True, timeout=15,
|
||||
)
|
||||
if result.returncode:
|
||||
raise AssertionError("CLI failed: " + result.stderr)
|
||||
return result
|
||||
|
||||
def api(self, device, suffix):
|
||||
return "/api/devices/" + device + suffix
|
||||
|
||||
def esp(self, device, token=None):
|
||||
return self.client.websocket_connect(
|
||||
"/ws/esp32?device_id=" + device,
|
||||
headers={"Authorization": "Bearer " + (token or self.tokens[device])},
|
||||
)
|
||||
|
||||
def browser(self, device):
|
||||
return self.client.websocket_connect(
|
||||
"/ws/client?device_id=" + device, headers={"Origin": ORIGIN},
|
||||
)
|
||||
|
||||
def receive_text(self, socket, timeout=8):
|
||||
# Starlette's synchronous receive has no deadline; bound its async stream.
|
||||
async def bounded():
|
||||
with anyio.fail_after(timeout):
|
||||
return await socket._send_rx.receive()
|
||||
message = socket.portal.call(bounded)
|
||||
socket._raise_on_close(message)
|
||||
return message["text"]
|
||||
|
||||
def until(self, socket, prefix, containing=None):
|
||||
deadline = time.monotonic() + 8
|
||||
for _ in range(60):
|
||||
remaining = deadline - time.monotonic()
|
||||
self.assertGreater(remaining, 0, "Deadline waiting for " + prefix)
|
||||
message = self.receive_text(socket, remaining)
|
||||
if message.startswith(prefix) and (containing is None or containing in message):
|
||||
return message[len(prefix):]
|
||||
self.fail("Expected browser prefix " + prefix)
|
||||
|
||||
def test_01_registry_and_rejections(self):
|
||||
rows = self.client.get("/api/devices").json()
|
||||
self.assertEqual({r["device_id"] for r in rows}, {A, B})
|
||||
self.assertTrue(all("token" not in key and "hash" not in key for r in rows for key in r))
|
||||
security_log = io.StringIO()
|
||||
handler = logging.StreamHandler(security_log)
|
||||
logger = logging.getLogger("tracker_hub")
|
||||
logger.addHandler(handler)
|
||||
try:
|
||||
for device, token in ((A, "invalid"), (B, self.tokens[A]), ("esp32-000000000000", self.tokens[A])):
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
with self.esp(device, token):
|
||||
self.fail("unauthenticated connection accepted")
|
||||
finally:
|
||||
logger.removeHandler(handler)
|
||||
self.assertIn("esp32_auth_failed", security_log.getvalue())
|
||||
for token in self.tokens.values():
|
||||
self.assertNotIn(token, security_log.getvalue())
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
with self.client.websocket_connect("/ws/esp32?device_id=" + A):
|
||||
self.fail("anonymous device accepted")
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
with self.client.websocket_connect("/ws/client?device_id=" + A, headers={"Origin": "https://evil.invalid"}):
|
||||
self.fail("foreign browser origin accepted")
|
||||
self.assertEqual(self.client.get(self.api("esp32-000000000000", "/status")).status_code, 404)
|
||||
self.assertGreaterEqual(self.client.get("/api/status").status_code, 400)
|
||||
|
||||
def test_02_two_devices_and_scoped_commands(self):
|
||||
with self.esp(A) as a, self.esp(B) as b, self.browser(A) as ca, self.browser(B) as cb:
|
||||
self.assertEqual(json.loads(self.until(ca, "CONFIG:"))["device_id"], A)
|
||||
self.assertEqual(json.loads(self.until(cb, "CONFIG:"))["device_id"], B)
|
||||
a.send_text(TEL)
|
||||
point_a = json.loads(self.until(ca, "TEL:"))
|
||||
b.send_text(TEL.replace("X=-9827", "X=-100"))
|
||||
point_b = json.loads(self.until(cb, "TEL:"))
|
||||
self.assertEqual((point_a["device_id"], point_a["x"]), (A, 9827))
|
||||
self.assertEqual((point_b["device_id"], point_b["x"]), (B, 100))
|
||||
a.send_text(SAMPLE)
|
||||
self.assertEqual(json.loads(self.until(ca, "DATA:"))["device_id"], A)
|
||||
b.send_text("VER:test-B")
|
||||
self.assertEqual(self.until(cb, "FW:"), "test-B")
|
||||
ca.send_text("CMD:10")
|
||||
self.assertEqual(self.receive_text(a), "CMD:10")
|
||||
for invalid in ("OTA:https://evil.invalid/payload.bin", "SET_COORDS:nan:0", "SET_PARAM:errMax=inf"):
|
||||
ca.send_text(invalid)
|
||||
self.until(ca, "LOG:", containing="ERROR")
|
||||
ca.send_text("CMD:10")
|
||||
self.assertEqual(self.receive_text(a), "CMD:10", "invalid commands must not reach the device")
|
||||
cb.send_text("SET_COORDS:12:34")
|
||||
self.assertEqual(self.receive_text(b), "SET_COORDS:12:34")
|
||||
status_a = self.client.get(self.api(A, "/status")).json()
|
||||
status_b = self.client.get(self.api(B, "/status")).json()
|
||||
self.assertNotEqual(status_a["firmware_device"], status_b["firmware_device"])
|
||||
self.assertEqual(status_b["firmware_device"], "test-B")
|
||||
for device in (A, B):
|
||||
rows = self.client.get(self.api(device, "/logs")).json()
|
||||
self.assertTrue(rows)
|
||||
response = self.client.get(self.api(device, "/logs/" + rows[0]["filename"]))
|
||||
self.assertEqual(response.status_code, 200)
|
||||
if device == A:
|
||||
self.assertNotIn("test-B", response.text)
|
||||
|
||||
def test_03_configuration_isolation_and_validation(self):
|
||||
with self.browser(A) as ca, self.browser(B) as cb:
|
||||
self.until(ca, "CONFIG:")
|
||||
self.until(cb, "CONFIG:")
|
||||
before_b = self.client.get(self.api(B, "/calib")).json()
|
||||
with self.esp(A) as a:
|
||||
a.send_text(SAMPLE)
|
||||
before = json.loads(self.until(ca, "DATA:"))["isc_ma"]
|
||||
self.assertAlmostEqual(before, 5469365 / 8388607 * 2048 / 20 / 0.075, delta=0.01)
|
||||
response = self.client.post(self.api(A, "/pcb"), json={"version": "V2"})
|
||||
self.assertEqual(response.status_code, 200)
|
||||
self.assertEqual(response.json()["r_shunt"], 0.130)
|
||||
history = json.loads(self.until(ca, "HISTORY:"))
|
||||
# The first HISTORY is the initial replay; consume until recalculated history.
|
||||
if not history or history[-1]["isc_ma"] == before:
|
||||
history = json.loads(self.until(ca, "HISTORY:"))
|
||||
self.assertAlmostEqual(history[-1]["isc_ma"] / before, 0.075 / 0.130, delta=0.001)
|
||||
self.assertAlmostEqual(history[-1]["isc_ma"], 5469365 / 8388607 * 2048 / 20 / 0.130, delta=0.01)
|
||||
pcb_b = self.client.get(self.api(B, "/pcb")).json()
|
||||
self.assertEqual((pcb_b["version"], pcb_b["r_shunt"]), ("V1", 0.075))
|
||||
self.assertEqual(self.client.post(self.api(A, "/calib"), json={"mV_per_WM2": 0.3, "az_dev": 18}).status_code, 200)
|
||||
self.assertEqual(self.client.get(self.api(B, "/calib")).json(), before_b)
|
||||
self.assertEqual(self.client.get(self.api(A, "/pcb")).json()["version"], "V2")
|
||||
self.assertEqual(self.client.post(self.api(A, "/pcb"), json={"version": "V9"}).status_code, 400)
|
||||
for value in (0, -1, "nan", "inf"):
|
||||
self.assertEqual(self.client.post(self.api(A, "/calib"), json={"mV_per_WM2": value}).status_code, 400)
|
||||
|
||||
def test_04_reconnect_old_socket_cannot_disconnect_new(self):
|
||||
with self.esp(A) as old, self.browser(A) as browser:
|
||||
self.until(browser, "CONFIG:")
|
||||
with self.esp(A) as new:
|
||||
old.close()
|
||||
new.send_text("VER:new-session")
|
||||
self.assertEqual(self.until(browser, "FW:"), "new-session")
|
||||
self.assertTrue(self.client.get(self.api(A, "/status")).json()["esp32_connected"])
|
||||
browser.send_text("CMD:10")
|
||||
self.assertEqual(self.receive_text(new), "CMD:10")
|
||||
|
||||
def test_05_ota_is_manual_and_scoped_to_confirmed_image(self):
|
||||
with self.esp(A) as a, self.esp(B) as b:
|
||||
# A simulated ESP32 is simply a WebSocket inbox; no hardware is touched.
|
||||
response = self.client.post("/ota/upload", files={"file": ("test.bin", b"test-firmware-1")}, data={"version": "test-2"})
|
||||
self.assertEqual(response.status_code, 200)
|
||||
manifest = response.json()["manifest"]
|
||||
self.assertEqual(self.client.post(self.api(A, "/ota/push"), json={"sha256": "wrong"}).status_code, 409)
|
||||
sent = self.client.post(self.api(B, "/ota/push"), json={"sha256": manifest["sha256"]})
|
||||
self.assertEqual(sent.status_code, 200)
|
||||
self.assertEqual(sent.json()["device_id"], B)
|
||||
ota_command = self.receive_text(b)
|
||||
self.assertTrue(ota_command.startswith("OTA:"))
|
||||
# A receives only its explicitly requested status command, not B's OTA.
|
||||
with self.browser(A) as browser:
|
||||
self.until(browser, "CONFIG:")
|
||||
browser.send_text("CMD:10")
|
||||
self.assertEqual(self.receive_text(a), "CMD:10")
|
||||
self.assertFalse(self.client.get(self.api(A, "/status")).json()["ota"]["auto"])
|
||||
self.assertFalse(self.client.get(self.api(B, "/status")).json()["ota"]["auto"])
|
||||
self.assertEqual(self.client.get("/ota/firmware").content, b"test-firmware-1")
|
||||
|
||||
def test_06_log_paths_and_disconnected_command(self):
|
||||
self.assertEqual(self.client.get(self.api(A, "/logs/log_1990-01-01.txt")).status_code, 404)
|
||||
self.assertEqual(self.client.get(self.api(A, "/logs/missing.txt")).status_code, 400)
|
||||
self.assertEqual(self.client.get(self.api(A, "/logs/..%2F..%2Fstate%2Fdevices.sqlite3")).status_code, 404)
|
||||
with self.browser(A) as browser:
|
||||
self.until(browser, "CONFIG:")
|
||||
# Drain initial replay before checking the explicit command failure.
|
||||
self.until(browser, "OTA_STATE:")
|
||||
browser.send_text("CMD:10")
|
||||
self.assertIn("ERROR", self.until(browser, "LOG:", containing="ERROR"))
|
||||
|
||||
def test_07_new_process_persists_settings_but_not_connections(self):
|
||||
script = (
|
||||
"import json\nfrom fastapi.testclient import TestClient\nfrom app.main import app\n"
|
||||
"with TestClient(app) as client:\n"
|
||||
f" base='/api/devices/{A}'\n"
|
||||
" print('__RESULT__'+json.dumps({'pcb':client.get(base+'/pcb').json(),"
|
||||
"'calib':client.get(base+'/calib').json(),'status':client.get(base+'/status').json()}))"
|
||||
)
|
||||
result = subprocess.run([sys.executable, "-c", script], cwd=ROOT,
|
||||
env=os.environ.copy(), capture_output=True, text=True, timeout=15)
|
||||
self.assertEqual(result.returncode, 0, result.stderr)
|
||||
payload = json.loads(next(line[len("__RESULT__"):] for line in result.stdout.splitlines()
|
||||
if line.startswith("__RESULT__")))
|
||||
self.assertEqual(payload["pcb"]["version"], "V2")
|
||||
self.assertEqual(payload["calib"]["mV_per_WM2"], 0.3)
|
||||
self.assertEqual(payload["calib"]["az_dev"], 18)
|
||||
self.assertFalse(payload["status"]["esp32_connected"])
|
||||
self.assertEqual(payload["status"]["samples_in_buffer"], 0)
|
||||
for token in self.tokens.values():
|
||||
self.assertNotIn(token, result.stdout + result.stderr)
|
||||
listing = self.cli("list")
|
||||
for token in self.tokens.values():
|
||||
self.assertNotIn(token, listing.stdout + listing.stderr)
|
||||
|
||||
def test_08_upload_never_triggers_ota_even_when_device_opted_in(self):
|
||||
original = self.client.get("/ota/manifest").json()
|
||||
with self.esp(A) as a, self.browser(A) as browser:
|
||||
self.until(browser, "CONFIG:")
|
||||
a.send_text("VER:" + original["version"])
|
||||
self.until(browser, "FW:")
|
||||
self.assertEqual(self.client.post(self.api(A, "/ota/auto"), json={"enabled": True}).status_code, 200)
|
||||
response = self.client.post("/ota/upload", files={"file": ("test.bin", b"test-firmware-2")}, data={"version": "test-3"})
|
||||
self.assertEqual(response.status_code, 200)
|
||||
try:
|
||||
# Outwait the legacy 3-second auto-update delay to catch accidental push-on-upload.
|
||||
time.sleep(4)
|
||||
browser.send_text("CMD:10")
|
||||
self.assertEqual(self.receive_text(a), "CMD:10", "upload unexpectedly pushed firmware")
|
||||
self.assertEqual(self.client.post(self.api(A, "/ota/push"), json={"sha256": original["sha256"]}).status_code, 409)
|
||||
self.assertFalse(self.client.get(self.api(B, "/status")).json()["ota"]["auto"])
|
||||
old_url = urlsplit(original["url"])
|
||||
self.assertEqual(self.client.get(old_url.path).content, b"test-firmware-1",
|
||||
"an already confirmed image URL must remain immutable")
|
||||
finally:
|
||||
self.client.post(self.api(A, "/ota/auto"), json={"enabled": False})
|
||||
|
||||
def test_09_rotation_revocation_and_database_secrecy(self):
|
||||
previous = self.tokens[B]
|
||||
self.cli("rotate", "--device-id", B, "--grace-hours", "1")
|
||||
token_file = self.directory / "state" / "provision" / (B + ".v2.token")
|
||||
current = token_file.read_text(encoding="utf-8").strip()
|
||||
self.assertNotEqual(previous, current)
|
||||
with self.esp(B, previous):
|
||||
pass
|
||||
with self.esp(B, current):
|
||||
pass
|
||||
self.cli("retire-previous", "--device-id", B)
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
with self.esp(B, previous):
|
||||
self.fail("retired token accepted")
|
||||
with self.esp(B, current) as active:
|
||||
self.cli("revoke", "--device-id", B)
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
self.receive_text(active)
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
with self.esp(B, current):
|
||||
self.fail("revoked token accepted")
|
||||
self.tokens[B] = current
|
||||
for database in (self.directory / "state").glob("*.sqlite3*"):
|
||||
content = database.read_bytes()
|
||||
for token in (previous, current, self.tokens[A]):
|
||||
self.assertFalse(token.encode() in content, "plaintext token leaked into SQLite")
|
||||
with self.esp(A):
|
||||
pass # Revoking B must leave A's credential valid.
|
||||
|
||||
def test_10_explicit_idempotent_primary_migration(self):
|
||||
c = "esp32-001122aabbee"
|
||||
self.cli("add", "--device-id", c, "--alias", "Migration target")
|
||||
legacy = self.directory / "firmware" / "pcb_state.json"
|
||||
legacy.write_text(json.dumps({"version": "V2"}), encoding="utf-8")
|
||||
(legacy.parent / "ota_state.json").write_text(json.dumps({"auto": True}), encoding="utf-8")
|
||||
self.assertEqual(self.client.get(self.api(c, "/pcb")).json()["version"], "V1")
|
||||
self.cli("migrate-primary", "--device-id", c)
|
||||
self.assertEqual(self.client.get(self.api(c, "/pcb")).json()["version"], "V2")
|
||||
self.assertEqual(self.client.get(self.api(B, "/pcb")).json()["version"], "V1")
|
||||
self.assertFalse(self.client.get(self.api(c, "/status")).json()["ota"]["auto"])
|
||||
# A repeated migration must not overwrite a later explicit setting.
|
||||
self.client.post(self.api(c, "/pcb"), json={"version": "V1"})
|
||||
self.cli("migrate-primary", "--device-id", c)
|
||||
self.assertEqual(self.client.get(self.api(c, "/pcb")).json()["version"], "V1")
|
||||
self.assertEqual(json.loads(legacy.read_text(encoding="utf-8"))["version"], "V2")
|
||||
|
||||
def test_11_oversized_session_isolated_and_corrupt_database_fails_closed(self):
|
||||
with self.esp(A) as a:
|
||||
a.send_text("x" * 16385)
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
self.receive_text(a)
|
||||
self.assertEqual(self.client.get(self.api(B, "/status")).status_code, 200)
|
||||
broken = self.directory / "broken-state"
|
||||
broken.mkdir()
|
||||
(broken / "devices.sqlite3").write_bytes(b"not a sqlite database")
|
||||
env = dict(os.environ, STATE_DIR=str(broken))
|
||||
result = subprocess.run([sys.executable, "-c", "from app.main import app"],
|
||||
cwd=ROOT, env=env, capture_output=True, text=True, timeout=15)
|
||||
self.assertNotEqual(result.returncode, 0, "corrupt registry must not fall back to anonymous access")
|
||||
|
||||
def test_12_ended_sessions_and_failed_accept_are_inert(self):
|
||||
from app.hub import HubManager
|
||||
|
||||
class Socket:
|
||||
def __init__(self, fail=False):
|
||||
self.fail = fail
|
||||
self.closed = False
|
||||
|
||||
async def accept(self):
|
||||
if self.fail:
|
||||
raise RuntimeError("simulated accept failure")
|
||||
|
||||
async def close(self, *args, **kwargs):
|
||||
self.closed = True
|
||||
|
||||
async def send_text(self, message):
|
||||
pass
|
||||
|
||||
async def check():
|
||||
manager = HubManager(A)
|
||||
original = Socket()
|
||||
connection = await manager.connect_esp32(original)
|
||||
await manager.handle_esp32_message("POS:1:2", connection)
|
||||
with self.assertRaises(RuntimeError):
|
||||
await manager.connect_esp32(Socket(fail=True))
|
||||
self.assertIs(manager.esp32_socket, original)
|
||||
self.assertEqual(manager.connection_id, connection)
|
||||
manager.disconnect_esp32(connection)
|
||||
await manager.handle_esp32_message("POS:999:999", connection)
|
||||
self.assertEqual((manager.last_pos_x, manager.last_pos_y), (1, 2))
|
||||
self.assertIsNone(manager.connection_id)
|
||||
connection = await manager.connect_esp32(Socket())
|
||||
await manager.force_close()
|
||||
await manager.handle_esp32_message("POS:888:888", connection)
|
||||
self.assertEqual((manager.last_pos_x, manager.last_pos_y), (1, 2))
|
||||
self.assertFalse(manager.esp32_connected)
|
||||
asyncio.run(check())
|
||||
|
||||
def test_13_failed_commit_rolls_back_before_next_write(self):
|
||||
from app.device_store import DeviceStore
|
||||
store = DeviceStore(str(self.directory / "rollback.sqlite3"))
|
||||
store.add_device(A, "rollback fixture")
|
||||
before = store.get_settings(A)
|
||||
connection = store._conn
|
||||
|
||||
class FailedCommit:
|
||||
attempted = False
|
||||
|
||||
def __getattr__(self, name):
|
||||
return getattr(connection, name)
|
||||
|
||||
def commit(self):
|
||||
self.attempted = True
|
||||
raise sqlite3.OperationalError("simulated full disk")
|
||||
|
||||
def __enter__(self):
|
||||
return self
|
||||
|
||||
def __exit__(self, kind, error, traceback):
|
||||
if kind is not None:
|
||||
connection.rollback()
|
||||
return False
|
||||
try:
|
||||
self.commit()
|
||||
except Exception:
|
||||
connection.rollback()
|
||||
raise
|
||||
|
||||
try:
|
||||
failure = FailedCommit()
|
||||
store._conn = failure
|
||||
with self.assertRaises(Exception):
|
||||
store.save_settings(A, az_dev=77)
|
||||
self.assertTrue(failure.attempted, "fixture did not reach the failing commit")
|
||||
store._conn = connection
|
||||
self.assertFalse(connection.in_transaction, "failed write left a pending transaction")
|
||||
self.assertEqual(store.get_settings(A), before)
|
||||
store.save_settings(A, pyrano=0.4)
|
||||
self.assertEqual(store.get_settings(A)["az_dev"], before["az_dev"])
|
||||
finally:
|
||||
store._conn = connection
|
||||
connection.rollback()
|
||||
store.close()
|
||||
|
||||
def test_14_unknown_id_cannot_allocate_rate_limit_state(self):
|
||||
from app.main import fleet
|
||||
from app.config import is_valid_device_id
|
||||
self.assertFalse(is_valid_device_id(A + "\n"))
|
||||
before = len(fleet._buckets)
|
||||
self.assertFalse(fleet.check_rate("not-a-device"))
|
||||
self.assertFalse(fleet.check_rate("esp32-ffffffffffff"))
|
||||
self.assertEqual(len(fleet._buckets), before)
|
||||
|
||||
def test_15_source_remains_compatible_with_python_311_image(self):
|
||||
for source in (ROOT / "app").glob("*.py"):
|
||||
with self.subTest(source=source.name):
|
||||
ast.parse(source.read_text(encoding="utf-8"), filename=str(source), feature_version=(3, 11))
|
||||
|
||||
def test_16_retiring_previous_token_closes_that_active_session_only(self):
|
||||
previous = self.tokens[A]
|
||||
with self.esp(A, previous) as active:
|
||||
self.cli("rotate", "--device-id", A, "--grace-hours", "1")
|
||||
current = (self.directory / "state" / "provision" / (A + ".v2.token")).read_text(encoding="utf-8").strip()
|
||||
# The old credential is still valid during the grace period.
|
||||
self.assertTrue(self.client.get(self.api(A, "/status")).json()["esp32_connected"])
|
||||
self.cli("retire-previous", "--device-id", A)
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
self.receive_text(active)
|
||||
with self.assertRaises(WebSocketDisconnect):
|
||||
with self.esp(A, previous):
|
||||
self.fail("retired credential accepted")
|
||||
self.tokens[A] = current
|
||||
with self.esp(A, current):
|
||||
pass
|
||||
|
||||
def test_17_log_quota_is_visible_without_stopping_telemetry(self):
|
||||
from app.hub import HubManager
|
||||
from app.config import LOGS_DIR, get_local_now
|
||||
device = "esp32-001122aabbee"
|
||||
path = Path(LOGS_DIR) / device / f"log_{get_local_now():%Y-%m-%d}.txt"
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
path.write_bytes(b"sentinel\n")
|
||||
manager = HubManager(device)
|
||||
with patch("app.hub.LOG_DAILY_MAX_BYTES", 9):
|
||||
asyncio.run(manager.handle_esp32_message(SAMPLE))
|
||||
self.assertEqual(path.read_bytes(), b"sentinel\n")
|
||||
self.assertEqual(len(manager.samples), 1)
|
||||
self.assertTrue(manager.status_payload()["log_degraded"])
|
||||
self.assertEqual(manager.status_payload()["log_error_count"], 1)
|
||||
|
||||
def test_18_rate_retention_and_slow_subscriber_are_bounded(self):
|
||||
from app.device_store import DeviceStore
|
||||
from app.fleet import FleetManager
|
||||
from app.hub import HubManager
|
||||
from app.config import LOGS_DIR
|
||||
store = DeviceStore(str(self.directory / "limits.sqlite3"))
|
||||
try:
|
||||
store.add_device(A)
|
||||
fleet = FleetManager(store, rate=0, burst=2)
|
||||
self.assertTrue(fleet.check_rate(A))
|
||||
self.assertTrue(fleet.check_rate(A))
|
||||
self.assertFalse(fleet.check_rate(A))
|
||||
self.assertFalse(fleet.check_rate("esp32-ffffffffffff"))
|
||||
self.assertEqual(len(fleet._buckets), 1)
|
||||
old = Path(LOGS_DIR) / A / "log_2000-01-01.txt"
|
||||
legacy = Path(LOGS_DIR) / "log_2000-01-01.txt"
|
||||
for path in (old, legacy):
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
path.write_text("fixture", encoding="utf-8")
|
||||
os.utime(path, (1, 1))
|
||||
self.assertEqual(fleet.prune_logs(30), 1)
|
||||
self.assertFalse(old.exists())
|
||||
self.assertTrue(legacy.exists())
|
||||
finally:
|
||||
store.close()
|
||||
|
||||
class Subscriber:
|
||||
def __init__(self, slow=False):
|
||||
self.slow, self.closed, self.received = slow, False, []
|
||||
|
||||
async def send_text(self, message):
|
||||
if self.slow:
|
||||
await asyncio.sleep(10)
|
||||
self.received.append(message)
|
||||
|
||||
async def close(self, **kwargs):
|
||||
self.closed = True
|
||||
|
||||
async def check():
|
||||
manager = HubManager()
|
||||
slow, fast = Subscriber(True), Subscriber()
|
||||
manager.client_sockets.extend([slow, fast])
|
||||
with patch("app.hub.BROADCAST_TIMEOUT", 0.01):
|
||||
await manager._broadcast("test")
|
||||
self.assertEqual(fast.received, ["test"])
|
||||
self.assertTrue(slow.closed)
|
||||
self.assertEqual(manager.client_sockets, [fast])
|
||||
asyncio.run(check())
|
||||
|
||||
def test_19_cross_origin_http_writes_are_rejected_before_mutation(self):
|
||||
before = self.client.get(self.api(A, "/calib")).json()
|
||||
rejected = self.client.post(self.api(A, "/calib"), json={"mV_per_WM2": 99},
|
||||
headers={"Origin": "https://evil.invalid"})
|
||||
self.assertEqual(rejected.status_code, 403)
|
||||
self.assertEqual(self.client.get(self.api(A, "/calib")).json(), before)
|
||||
manifest = self.client.get("/ota/manifest").json()
|
||||
upload = self.client.post("/ota/upload", files={"file": ("bad.bin", b"not-approved")},
|
||||
headers={"Origin": "null"})
|
||||
self.assertEqual(upload.status_code, 403)
|
||||
self.assertEqual(self.client.get("/ota/manifest").json(), manifest)
|
||||
accepted = self.client.post(self.api(A, "/calib"),
|
||||
json={"mV_per_WM2": before["mV_per_WM2"]},
|
||||
headers={"Origin": ORIGIN})
|
||||
self.assertEqual(accepted.status_code, 200)
|
||||
|
||||
def test_20_auto_ota_pending_task_cancels_when_disabled_or_already_installed(self):
|
||||
from app.hub import HubManager
|
||||
|
||||
class Socket:
|
||||
async def accept(self):
|
||||
pass
|
||||
|
||||
async def send_text(self, text):
|
||||
raise AssertionError("Cancelled OTA must not send any command")
|
||||
|
||||
async def check():
|
||||
manager = HubManager(A)
|
||||
cid = await manager.connect_esp32(Socket())
|
||||
manager.ota_manifest = {"version": "target", "sha256": "a" * 64, "url": "https://test.invalid/image"}
|
||||
manager.esp32_firmware_version = "old"
|
||||
manager._version_session_id = cid
|
||||
manager.ota_auto_enabled = True
|
||||
manager._maybe_auto_update()
|
||||
pending = manager._auto_task
|
||||
self.assertIsNotNone(pending)
|
||||
await manager.set_ota_auto(False)
|
||||
await asyncio.gather(pending, return_exceptions=True)
|
||||
self.assertTrue(pending.cancelled())
|
||||
self.assertIsNone(manager._auto_task)
|
||||
manager.ota_auto_enabled = True
|
||||
manager._maybe_auto_update()
|
||||
pending = manager._auto_task
|
||||
manager.esp32_firmware_version = "target"
|
||||
manager._maybe_auto_update()
|
||||
await asyncio.gather(pending, return_exceptions=True)
|
||||
self.assertTrue(pending.cancelled())
|
||||
self.assertIsNone(manager._auto_task)
|
||||
manager.disconnect_esp32(cid)
|
||||
asyncio.run(check())
|
||||
|
||||
def test_21_docker_healthcheck_targets_a_live_endpoint(self):
|
||||
dockerfile = (ROOT / "Dockerfile").read_text(encoding="utf-8")
|
||||
path = re.search(r"http://127\.0\.0\.1:8000([^'\" ]+)", dockerfile).group(1)
|
||||
response = self.client.get(path)
|
||||
self.assertEqual(response.status_code, 200)
|
||||
self.assertTrue(response.json()["ok"])
|
||||
|
||||
def test_22_tracker_settings_reach_selected_device(self):
|
||||
with self.esp(A) as device, self.browser(A) as browser:
|
||||
self.until(browser, "CONFIG:")
|
||||
for command in (
|
||||
"SET_PARAM:minErrMax=193", "SET_PARAM:lpfBeta=0.70",
|
||||
"SET_PARAM:smallThreshold=4500", "SET_PARAM:peakProximity=0.30",
|
||||
"SET_PARAM:cicleMax=2",
|
||||
"SET_PARAM:axisXFactor=3", "SET_PARAM:axisYFactor=1",
|
||||
):
|
||||
with self.subTest(command=command):
|
||||
browser.send_text(command)
|
||||
browser.send_text("CMD:10")
|
||||
# The status sentinel also bounds a rejected setting without waiting for it.
|
||||
self.assertEqual(self.receive_text(device), command)
|
||||
self.assertEqual(self.receive_text(device), "CMD:10")
|
||||
|
||||
def test_23_command_validation_covers_dashboard_settings_and_keeps_guards(self):
|
||||
from app.main import COMMAND_MAX_LEN, _valid_command
|
||||
|
||||
html = (ROOT / "static" / "index.html").read_text(encoding="utf-8")
|
||||
parameters = set(re.findall(r"sendParam\('([^']+)'\s*,\s*'[^']+'\)", html))
|
||||
self.assertTrue(parameters, "dashboard parameter controls were not found")
|
||||
for name in parameters | {"errMin", "coarseStep", "fineStep", "angleThreshold"}:
|
||||
with self.subTest(parameter=name):
|
||||
self.assertTrue(_valid_command(f"SET_PARAM:{name}=1"))
|
||||
for value in ("1", "3", "8"):
|
||||
self.assertTrue(_valid_command("SET_PARAM:axisXFactor=" + value))
|
||||
for value in ("0", "9", "-1", "1.5", "nan", "inf"):
|
||||
self.assertFalse(_valid_command("SET_PARAM:axisXFactor=" + value))
|
||||
for value in ("1", "4", "64"):
|
||||
self.assertTrue(_valid_command("SET_PARAM:cicleMax=" + value))
|
||||
for value in ("0", "-1", "1.5", "65", "999999999999"):
|
||||
self.assertFalse(_valid_command("SET_PARAM:cicleMax=" + value))
|
||||
html_controls = ("axisXFactor", "axisYFactor", "axisRequested", "device_id", "x_budget")
|
||||
for text in html_controls:
|
||||
self.assertIn(text, html)
|
||||
|
||||
prefix = "SET_PARAM:minErrMax="
|
||||
at_limit = prefix + "0" * (COMMAND_MAX_LEN - len(prefix))
|
||||
self.assertTrue(_valid_command(at_limit))
|
||||
for command in (
|
||||
at_limit + "0", "SET_PARAM:unknown=1", "SET_PARAM:minerrmax=193",
|
||||
"SET_PARAM:minErrMax=", "SET_PARAM:minErrMax=abc",
|
||||
"SET_PARAM:lpfBeta=nan", "SET_PARAM:lpfBeta=inf",
|
||||
"SET_PARAM:lpfBeta=1.2.3", "SET_PARAM:lpfBeta=0,70",
|
||||
"SET_PARAM:lpfBeta=0.70\nCMD:4", "SET_PARAM:lpfBeta=0.70\x00",
|
||||
"SET_PARAM:lpfBeta=1e309",
|
||||
"OTA:https://evil.invalid/payload.bin",
|
||||
):
|
||||
with self.subTest(command=command):
|
||||
self.assertFalse(_valid_command(command))
|
||||
|
||||
def test_24_axis_confirmation_is_device_scoped_and_reports_effective_budgets(self):
|
||||
from app.hub import HubManager
|
||||
async def check():
|
||||
sent_by_device = {}
|
||||
managers = {}
|
||||
for device in (A, B):
|
||||
manager = HubManager(device_id=device)
|
||||
managers[device] = manager
|
||||
sent = sent_by_device[device] = []
|
||||
async def capture(message, sent=sent):
|
||||
sent.append(message)
|
||||
manager._broadcast = capture
|
||||
await manager._process_line("LOG:[2026-11-04 12:00:00] AXISCFG:3:1:4")
|
||||
ack = json.loads(sent[0][len("AXISCFG:"):])
|
||||
self.assertEqual(ack, {"x": 3, "y": 1, "base": 4, "device_id": device,
|
||||
"x_budget": 12, "y_budget": 4})
|
||||
for invalid in (
|
||||
"junk AXISCFG:3:1:4", "AXISCFG:3:1:4 junk",
|
||||
"LOG:[bad timestamp] AXISCFG:3:1:4", "LOG:[2026-11-04 12:00:00] prefix AXISCFG:3:1:4",
|
||||
"AXISCFG:8:1:9", "AXISCFG:3:1:2147483647", "AXISCFG:3:-1:4",
|
||||
):
|
||||
before = len(sent_by_device[A])
|
||||
await managers[A]._process_line(invalid)
|
||||
self.assertFalse(any(m.startswith("AXISCFG:") for m in sent_by_device[A][before:]))
|
||||
asyncio.run(check())
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main(verbosity=2)
|
||||
@@ -0,0 +1,102 @@
|
||||
# Throwaway smoke test: validate the conversion math + log parsers in server.py
|
||||
# without needing FastAPI installed (FastAPI is stubbed before the import).
|
||||
import sys, types
|
||||
|
||||
def _install_stub():
|
||||
fa = types.ModuleType("fastapi")
|
||||
class FastAPI:
|
||||
def __init__(self, *a, **k): pass
|
||||
def add_middleware(self, *a, **k): pass
|
||||
def get(self, *a, **k): return (lambda f: f)
|
||||
def post(self, *a, **k): return (lambda f: f)
|
||||
def websocket(self, *a, **k): return (lambda f: f)
|
||||
def mount(self, *a, **k): pass
|
||||
class WebSocket: pass
|
||||
class WebSocketDisconnect(Exception): pass
|
||||
class HTTPException(Exception):
|
||||
def __init__(self, status_code=None, detail=None):
|
||||
self.status_code, self.detail = status_code, detail
|
||||
super().__init__(detail)
|
||||
fa.FastAPI, fa.WebSocket, fa.WebSocketDisconnect, fa.HTTPException = \
|
||||
FastAPI, WebSocket, WebSocketDisconnect, HTTPException
|
||||
resp = types.ModuleType("fastapi.responses")
|
||||
class HTMLResponse: pass
|
||||
class FileResponse: pass
|
||||
resp.HTMLResponse, resp.FileResponse = HTMLResponse, FileResponse
|
||||
mid = types.ModuleType("fastapi.middleware")
|
||||
cors = types.ModuleType("fastapi.middleware.cors")
|
||||
class CORSMiddleware: pass
|
||||
cors.CORSMiddleware, mid.cors = CORSMiddleware, cors
|
||||
sf = types.ModuleType("fastapi.staticfiles")
|
||||
class StaticFiles:
|
||||
def __init__(self, *a, **k): pass
|
||||
sf.StaticFiles = StaticFiles
|
||||
sys.modules.update({"fastapi": fa, "fastapi.responses": resp,
|
||||
"fastapi.middleware": mid, "fastapi.middleware.cors": cors,
|
||||
"fastapi.staticfiles": sf})
|
||||
|
||||
_install_stub()
|
||||
import server # noqa: E401 (imported after stubbing fastapi)
|
||||
|
||||
# A real periodic sample captured on 21/09/2025 (21092025.txt, line 4)
|
||||
line = "[2025-09-21 10:41:00] X:53037,Y:0,C:219838,V:4699627,P:7601002,S:19,er:1500"
|
||||
|
||||
# --- regex must match BOTH the bare and the legacy 'LOG-to prefix ---
|
||||
m = server.RE_SAMPLE.match(line)
|
||||
assert m, "RE_SAMPLE failed to match a standard sample line"
|
||||
m2 = server.RE_SAMPLE.match("LOG:" + line)
|
||||
assert m2, "RE_SAMPLE failed to match a LOG:-prefixed sample line"
|
||||
pm = server.RE_PARAM.match("LOG:[2025-09-21 10:42:09] Az_deviation=5.00")
|
||||
assert pm and abs(float(pm.group("val")) - 5.0) < 1e-9, "RE_PARAM failed"
|
||||
|
||||
h = server.hub
|
||||
h.azdev = 5.0
|
||||
|
||||
# --- independent reference using the article / parse_log.py formulas ---
|
||||
ADC_MAX = 8388607.0; VREF_MV = 2048.0; VREF_V = 2.048
|
||||
GAIN_SHUNT = 20.0; R_SHUNT = 0.075; FF = 0.82; VOC_DIV = 2.0
|
||||
p, v, c, x, y = (int(m.group(k)) for k in ("p", "v", "c", "x", "y"))
|
||||
azdev = 5.0
|
||||
voc_raw = v / ADC_MAX * VREF_V * VOC_DIV
|
||||
isc_raw = (c / ADC_MAX * (VREF_MV / GAIN_SHUNT)) / 1000.0 / R_SHUNT
|
||||
gpoa_20 = round(p / ADC_MAX * (VREF_MV / 2.0), 1)
|
||||
voc_exp = round(voc_raw, 3)
|
||||
isc_exp = round(isc_raw * 1000, 2)
|
||||
pcpv_exp = round(voc_raw * isc_raw * FF * 1000, 2)
|
||||
x_base = x - azdev / 90.0 * y
|
||||
el_exp = round(90.0 - (x_base - 53000) / 53000 * 80.0, 2)
|
||||
az_exp = round(180.0 + (y - 53000) / 53000 * 80.0, 2)
|
||||
|
||||
h.pyrano = 2.0
|
||||
pt20 = h.on_sample(m.groupdict())
|
||||
for got, exp, tag in [(pt20["gpoa"], gpoa_20, "G_POA"),
|
||||
(pt20["voc"], voc_exp, "Voc"),
|
||||
(pt20["isc_ma"], isc_exp, "Isc"),
|
||||
(pt20["pcpv_mw"], pcpv_exp, "P_CPV"),
|
||||
(pt20["az"], az_exp, "az"),
|
||||
(pt20["el"], el_exp, "el")]:
|
||||
assert got == exp or abs(got - exp) < 1e-9, (tag, got, exp)
|
||||
print("OLD 2.0 mV/Wm2 : G_POA=%6.1f W/m2 Voc=%5.3f V Isc=%7.2f mA P_CPV=%6.2f mW az=%6.2f el=%6.2f"
|
||||
% (pt20["gpoa"], pt20["voc"], pt20["isc_ma"], pt20["pcpv_mw"], pt20["az"], pt20["el"]))
|
||||
|
||||
h.pyrano = 0.2
|
||||
pt02 = h.on_sample(m.groupdict())
|
||||
print("NEW 0.2 mV/Wm2 : G_POA=%6.1f W/m2 (ratio vs 2.0 = %.3fx)"
|
||||
% (pt02["gpoa"], pt02["gpoa"] / pt20["gpoa"]))
|
||||
assert abs(pt02["gpoa"] / pt20["gpoa"] - 10.0) < 0.05, "0.2 must be 10x the 2.0 irradiance"
|
||||
|
||||
# az_dev change must re-derive elevation when the Y axis is non-zero.
|
||||
# (The 10:41 sample has Y:0, so it cannot exercise the az_dev coupling;
|
||||
# use a SunPos-style sample with a non-zero Y instead.)
|
||||
d = {"ts": "2025-09-21 10:43:00", "x": "62299", "y": "9444",
|
||||
"c": "200000", "v": "4600000", "p": "7600000", "er": "1500"}
|
||||
h.azdev = 5.0
|
||||
h.on_sample(d)
|
||||
el_at_5 = h.samples[-1]["el"]
|
||||
h.azdev = 0.0
|
||||
h._recompute_position()
|
||||
el_at_0 = h.samples[-1]["el"]
|
||||
assert el_at_5 != el_at_0, "az_dev change should alter the elevation estimate when y!=0"
|
||||
print("az_dev recompute: el(azdev=5)=%.2f el(azdev=0)=%.2f (differ as expected)" % (el_at_5, el_at_0))
|
||||
|
||||
print("OK: unit conversion, geometry and log parsers are all consistent.")
|
||||
@@ -0,0 +1,184 @@
|
||||
# Reproducible regression test for the "TEL:" telemetry parser in app/hub.py.
|
||||
#
|
||||
# History: the firmware 1.1.1 build (F6) added two diagnostic fields between
|
||||
# LPF and X in the telemetry line:
|
||||
# ... LPF=<lpf>, prox=<0..1>, CmaxN=<counts>, X=<x>, Y=<y>
|
||||
# The original RE_TEL expected X immediately after LPF, so the new line stopped
|
||||
# parsing (the "TEL ya no se parsea" regression). This test locks the contract:
|
||||
#
|
||||
# * parses the NEW line (with prox/CmaxN) -- incl. the real 2026-10-30 line
|
||||
# * still parses the OLD line (without prox/CmaxN) -> backward compatible
|
||||
# * handles signed (negative) X/Y coordinates
|
||||
# * captures prox/cmaxn into on_tel() points (None on old-format lines)
|
||||
# * negates X/Y in on_tel() so telemetry overlays the sample trajectory
|
||||
# * does NOT cross-match (sample / FineTune / SunPos lines -> no TEL)
|
||||
# * feeds the tel_samples buffer and the TEL_HISTORY replay on connect
|
||||
# * dispatches handle_esp32_message -> "TEL:" (new fw) / "DATA:" (old fw)
|
||||
#
|
||||
# It mirrors _smoke_test.py: fastapi is stubbed before the import so this runs
|
||||
# on a machine where fastapi is NOT installed.
|
||||
import sys, types, json, asyncio, tempfile, shutil
|
||||
|
||||
def _install_stub():
|
||||
try:
|
||||
import fastapi # noqa: F401 (real one present -> nothing to do)
|
||||
return
|
||||
except Exception:
|
||||
pass
|
||||
fa = types.ModuleType("fastapi")
|
||||
class WebSocket: pass
|
||||
fa.WebSocket = WebSocket
|
||||
sys.modules["fastapi"] = fa
|
||||
|
||||
_install_stub()
|
||||
import app.hub as hubmod # noqa: E402 (imported after stubbing)
|
||||
from app.hub import HubManager, RE_TEL, RE_SAMPLE # noqa: E402
|
||||
|
||||
# Redirect log writes to a temp dir so the test never touches data_logs/.
|
||||
_tmp = tempfile.mkdtemp(prefix="teltest_")
|
||||
hubmod.LOGS_DIR = _tmp
|
||||
hub = HubManager()
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self):
|
||||
self.sent = []
|
||||
async def accept(self): pass
|
||||
async def send_text(self, msg):
|
||||
self.sent.append(msg)
|
||||
|
||||
# --- Fixtures -----------------------------------------------------------------
|
||||
# Real line captured from the field device (2026-10-30 10:34:03), new firmware.
|
||||
TEL_REAL = ("LOG:[2026-10-30 10:34:03] TEL: t=246s, steps=29825(+1000), "
|
||||
"avgC=5469365, avgV=5160269, avgP=679686, LPF=4338597, "
|
||||
"prox=0.00, CmaxN=53643680, X=-9827, Y=-65788")
|
||||
# Same layout, signed coordinates and a non-trivial proximity value.
|
||||
TEL_NEG = ("LOG:[2026-10-02 09:34:05] TEL: t=125s, steps=5100(-20), "
|
||||
"avgC=-100, avgV=18000, avgP=1400, LPF=-50, "
|
||||
"prox=0.85, CmaxN=123456, X=-54810, Y=-48890")
|
||||
# OLD firmware (pre-F6): no prox/CmaxN. Must keep parsing.
|
||||
TEL_OLD = ("LOG:[2026-10-02 09:34:03] TEL: t=123s, steps=5000(+100), "
|
||||
"avgC=9900, avgV=18380, avgP=1490, LPF=9900, X=54810, Y=48890")
|
||||
# Legacy periodic sample (RE_SAMPLE) and a plain event line.
|
||||
OLD_SMP = "LOG:[2026-10-02 09:34:07] X:54810,Y:48890,C:9898,V:18263,P:1450,S:17,er:1500"
|
||||
FINE = "LOG:[2026-10-02 09:34:09] FineTune: inicio"
|
||||
|
||||
def test_parsers():
|
||||
# NEW format (real line) -- every field present.
|
||||
m = RE_TEL.match(TEL_REAL)
|
||||
assert m, "RE_TEL failed to match the real new-format TEL line"
|
||||
g = m.groupdict()
|
||||
assert g["ts"] == "2026-10-30 10:34:03"
|
||||
assert g["t"] == "246" and g["steps"] == "29825" and g["stepsDelta"] == "+1000"
|
||||
assert g["avgC"] == "5469365" and g["avgV"] == "5160269" and g["avgP"] == "679686"
|
||||
assert g["lpf"] == "4338597"
|
||||
assert g["prox"] == "0.00" and g["cmaxN"] == "53643680"
|
||||
assert g["x"] == "-9827" and g["y"] == "-65788"
|
||||
|
||||
# Signed coords + non-trivial prox.
|
||||
mn = RE_TEL.match(TEL_NEG)
|
||||
assert mn, "RE_TEL failed to match a TEL line with signed X/Y"
|
||||
assert mn.group("x") == "-54810" and mn.group("y") == "-48890"
|
||||
assert mn.group("avgC") == "-100" and mn.group("stepsDelta") == "-20"
|
||||
assert mn.group("prox") == "0.85" and mn.group("cmaxN") == "123456"
|
||||
|
||||
# OLD format (backward compatibility): prox/cmaxN optional -> None.
|
||||
mo = RE_TEL.match(TEL_OLD)
|
||||
assert mo, "RE_TEL failed to match the old (pre-F6) TEL line"
|
||||
assert mo.group("x") == "54810" and mo.group("y") == "48890"
|
||||
assert mo.group("prox") is None and mo.group("cmaxN") is None
|
||||
|
||||
# Bare line without the leading LOG: prefix must also match.
|
||||
assert RE_TEL.match(TEL_OLD[4:]), "RE_TEL must match a bare (no LOG:) line"
|
||||
|
||||
# No cross-matching with sample / event lines.
|
||||
assert RE_TEL.match(OLD_SMP) is None, "legacy sample line must NOT match RE_TEL"
|
||||
assert RE_TEL.match(FINE) is None, "event line must NOT match RE_TEL"
|
||||
assert RE_SAMPLE.match(OLD_SMP), "legacy sample line must still match RE_SAMPLE"
|
||||
|
||||
def test_on_tel():
|
||||
hub.tel_samples.clear()
|
||||
# New format: negation of X/Y + prox/cmaxn captured.
|
||||
pt = hub.on_tel(RE_TEL.match(TEL_REAL).groupdict())
|
||||
assert pt["x"] == 9827 and pt["y"] == 65788, "on_tel must negate X/Y"
|
||||
assert pt["t"] == 246 and pt["steps"] == 29825 and pt["steps_delta"] == 1000
|
||||
assert pt["lpf"] == 4338597
|
||||
assert pt["prox"] == 0.0 and pt["cmaxn"] == 53643680
|
||||
for k in ("gpoa", "voc", "isc_ma", "pcpv_mw", "az", "el"):
|
||||
assert k in pt, "on_tel point missing field %s" % k
|
||||
|
||||
# Old format: prox/cmaxn absent -> None, no crash.
|
||||
pt_old = hub.on_tel(RE_TEL.match(TEL_OLD).groupdict())
|
||||
assert pt_old["x"] == -54810 and pt_old["y"] == -48890
|
||||
assert pt_old["prox"] is None and pt_old["cmaxn"] is None
|
||||
assert len(hub.tel_samples) == 2
|
||||
|
||||
def test_buffer_and_history():
|
||||
hub.tel_samples.clear()
|
||||
for line in (TEL_REAL, TEL_NEG, TEL_OLD):
|
||||
hub.on_tel(RE_TEL.match(line).groupdict())
|
||||
assert len(hub.tel_samples) == 3, "buffer must hold all three TEL points"
|
||||
|
||||
# TEL_HISTORY replay must deliver the buffered points to a new client.
|
||||
async def _run():
|
||||
client = FakeClient()
|
||||
await hub.connect_client(client)
|
||||
hist = [x for x in client.sent if x.startswith("TEL_HISTORY:")]
|
||||
assert len(hist) == 1, "connect_client must send exactly one TEL_HISTORY"
|
||||
payload = json.loads(hist[0][len("TEL_HISTORY:"):])
|
||||
assert isinstance(payload, list) and len(payload) == 3
|
||||
# The real line's negated coords must be in the replayed history.
|
||||
assert any(p.get("x") == 9827 and p.get("y") == 65788 for p in payload), \
|
||||
"TEL_HISTORY must include the negated real-line coords"
|
||||
# Old-format point carried prox=None through the round trip.
|
||||
assert any(p.get("prox") is None for p in payload), \
|
||||
"old-format point must keep prox=None in history"
|
||||
hub.disconnect_client(client)
|
||||
asyncio.run(_run())
|
||||
|
||||
def test_dispatch():
|
||||
async def _run():
|
||||
client = FakeClient()
|
||||
hub.client_sockets.append(client)
|
||||
await hub.handle_esp32_message(TEL_REAL)
|
||||
tel_msgs = [x for x in client.sent if x.startswith("TEL:")]
|
||||
assert len(tel_msgs) == 1, "expected one TEL: broadcast, got %d" % len(tel_msgs)
|
||||
assert json.loads(tel_msgs[0][4:])["x"] == 9827
|
||||
assert json.loads(tel_msgs[0][4:])["cmaxn"] == 53643680
|
||||
client.sent.clear()
|
||||
await hub.handle_esp32_message(OLD_SMP)
|
||||
assert any(x.startswith("DATA:") for x in client.sent), "old line must emit DATA:"
|
||||
assert not any(x.startswith("TEL:") for x in client.sent), "old line must NOT emit TEL:"
|
||||
client.sent.clear()
|
||||
await hub.handle_esp32_message(FINE)
|
||||
assert not any(x.startswith(("DATA:", "TEL:")) for x in client.sent), "event line must only log"
|
||||
hub.disconnect_client(client)
|
||||
asyncio.run(_run())
|
||||
|
||||
def test_position_mapping():
|
||||
previous = hub.azdev
|
||||
try:
|
||||
hub.azdev = 18.0
|
||||
# Firmware mapping: X is azimuth; Y is elevation plus X coupling.
|
||||
x, y = 39750, 87450
|
||||
az, el = hub._pos_deg(x, y)
|
||||
assert abs(az - 160.0) < 1e-9
|
||||
assert abs(el - 50.0) < 1e-9
|
||||
sample = RE_SAMPLE.match(OLD_SMP).groupdict()
|
||||
sample.update(x=str(x), y=str(y))
|
||||
tel = RE_TEL.match(TEL_REAL).groupdict()
|
||||
tel.update(x=str(-x), y=str(-y))
|
||||
for point in (hub.on_sample(sample), hub.on_tel(tel)):
|
||||
assert point['az'] == 160.0 and point['el'] == 50.0
|
||||
finally:
|
||||
hub.azdev = previous
|
||||
|
||||
def _run():
|
||||
test_parsers()
|
||||
test_on_tel()
|
||||
test_buffer_and_history()
|
||||
test_dispatch()
|
||||
test_position_mapping()
|
||||
print("OK: RE_TEL (new+old format), on_tel conversion, buffer, TEL_HISTORY and dispatch are all consistent.")
|
||||
|
||||
_run()
|
||||
shutil.rmtree(_tmp, ignore_errors=True)
|
||||
@@ -0,0 +1,95 @@
|
||||
import os
|
||||
import re
|
||||
from datetime import datetime, timezone, timedelta
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
# Aguascalientes está en UTC-6 todo el año (sin horario de verano).
|
||||
# Usamos un offset fijo para evitar que tzdata desactualizado aplique DST en octubre.
|
||||
LOCAL_TZ = timezone(timedelta(hours=-6))
|
||||
|
||||
def get_local_now() -> datetime:
|
||||
"""Devuelve la fecha/hora actual fijada en UTC-6."""
|
||||
return datetime.now(LOCAL_TZ)
|
||||
|
||||
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
||||
|
||||
# Directorios configurables por env (permite tests con rutas temporales sin
|
||||
# tocar datos reales).
|
||||
LOGS_DIR = os.environ.get("LOGS_DIR") or os.path.join(BASE_DIR, "data_logs")
|
||||
STATIC_DIR = os.environ.get("STATIC_DIR") or os.path.join(BASE_DIR, "static")
|
||||
FIRMWARE_DIR = os.environ.get("FIRMWARE_DIR") or os.path.join(BASE_DIR, "firmware")
|
||||
|
||||
# Estado multitarjeta (identidades, tokens hasheados, ajustes) en SQLite.
|
||||
STATE_DIR = os.environ.get("STATE_DIR") or os.path.join(BASE_DIR, "state")
|
||||
DATABASE_PATH = os.path.join(STATE_DIR, "devices.sqlite3")
|
||||
PROVISION_DIR = os.path.join(STATE_DIR, "provision")
|
||||
|
||||
FIRMWARE_BIN = os.path.join(FIRMWARE_DIR, "firmware.bin")
|
||||
OTA_MANIFEST_FILE = os.path.join(FIRMWARE_DIR, "manifest.json")
|
||||
OTA_STATE_FILE = os.path.join(FIRMWARE_DIR, "ota_state.json")
|
||||
|
||||
OTA_SLOT_MAX = 0x640000
|
||||
OTA_PUBLIC_URL = os.environ.get("OTA_PUBLIC_URL", "https://micro.ferrasdh.uk").rstrip("/")
|
||||
PCB_STATE_FILE = os.path.join(FIRMWARE_DIR, "pcb_state.json")
|
||||
|
||||
# Constantes hardware / calibración
|
||||
ADC_MAX = 8388607.0
|
||||
VREF_MV = 2048.0
|
||||
VREF_V = 2.048
|
||||
GAIN_SHUNT = 20.0
|
||||
R_SHUNT = 0.075 # legacy / valor por defecto; el hub usa PCB_VERSIONS[pcb_version]
|
||||
PCB_VERSIONS = {"V1": 0.075, "V2": 0.130} # r_shunt en ohms por versión de PCB
|
||||
DEFAULT_PCB_VERSION = "V1"
|
||||
FF = 0.82
|
||||
VOC_DIVIDER = 2.0
|
||||
|
||||
PYRANO_MV_PER_WM2 = 0.2
|
||||
AZ_DEV_DEFAULT = 5.0
|
||||
STEPS_80 = 53000.0
|
||||
DEG_SPAN = 80.0
|
||||
|
||||
MAX_SAMPLES = max(1, int(os.environ.get("MAX_SAMPLES", "15000")))
|
||||
HISTORY_LIMIT = MAX_SAMPLES
|
||||
|
||||
# ----------------------- Límites y seguridad -----------------------
|
||||
|
||||
# Máximo de tarjetas registradas (buffers solo se reservan para IDs conocidos).
|
||||
MAX_DEVICES = int(os.environ.get("MAX_DEVICES", "16"))
|
||||
|
||||
# Canal de ingesta ESP32: límite por mensaje (bytes) y tasa por tarjeta.
|
||||
WS_MESSAGE_MAX = int(os.environ.get("WS_MESSAGE_MAX", str(16 * 1024)))
|
||||
WS_RATE_PER_SEC = float(os.environ.get("WS_RATE_PER_SEC", "100"))
|
||||
WS_RATE_BURST = int(os.environ.get("WS_RATE_BURST", "200"))
|
||||
|
||||
# Timeout de envío a un suscriptor de navegador lento (solo corta a ese cliente).
|
||||
BROADCAST_TIMEOUT = float(os.environ.get("BROADCAST_TIMEOUT", "5"))
|
||||
|
||||
# Retención de logs diarios por tarjeta (días). No toca archivos legacy en la
|
||||
# raíz de LOGS_DIR.
|
||||
LOG_RETENTION_DAYS = int(os.environ.get("LOG_RETENTION_DAYS", "30"))
|
||||
LOG_DAILY_MAX_BYTES = max(1, int(os.environ.get("LOG_DAILY_MAX_BYTES", str(50 * 1024 * 1024))))
|
||||
|
||||
# Sondeo periódico de credenciales (la revocación desde CLI, proceso separado,
|
||||
# cierra la sesión activa en este intervalo).
|
||||
CREDENTIAL_POLL_SECONDS = float(os.environ.get("CREDENTIAL_POLL_SECONDS", "5"))
|
||||
|
||||
# Caducidad del token anterior tras rotar (horas).
|
||||
TOKEN_GRACE_HOURS = int(os.environ.get("TOKEN_GRACE_HOURS", "24"))
|
||||
|
||||
# Aliases legacy: solo se habilitan con una tarjeta primaria explícita.
|
||||
PRIMARY_DEVICE_ID = os.environ.get("PRIMARY_DEVICE_ID", "").strip() or None
|
||||
|
||||
# Orígenes permitidos para el WebSocket de navegador (reemplaza CORS "*").
|
||||
# El canal ESP32 no usa Origin: se autentica por token.
|
||||
_DEFAULT_ORIGINS = "https://micro.ferrasdh.uk,http://localhost:4000,http://127.0.0.1:4000"
|
||||
ALLOWED_ORIGINS = {
|
||||
o.strip().rstrip("/")
|
||||
for o in os.environ.get("ALLOWED_ORIGINS", _DEFAULT_ORIGINS).split(",")
|
||||
if o.strip()
|
||||
}
|
||||
|
||||
# Identidad: PCB_ID configurado o MAC eFuse (12 hex minúsculos con prefijo estable).
|
||||
DEVICE_ID_RE = re.compile(r"^esp32-[0-9a-f]{12}$")
|
||||
|
||||
def is_valid_device_id(value) -> bool:
|
||||
return isinstance(value, str) and bool(DEVICE_ID_RE.fullmatch(value))
|
||||
@@ -0,0 +1,433 @@
|
||||
"""Almacenamiento de identidades, tokens (solo hashes SHA-256) y ajustes por
|
||||
tarjeta. SQLite de biblioteca estándar, sin ORM.
|
||||
|
||||
Reglas:
|
||||
- Nunca se guardan tokens en claro: solo SHA-256 del token aleatorio.
|
||||
- Máximo un token actual + un token anterior con caducidad explícita.
|
||||
- Los cambios de ajustes se escriben en transacción antes de confirmarse.
|
||||
"""
|
||||
import hashlib
|
||||
import hmac
|
||||
import json
|
||||
import math
|
||||
import os
|
||||
import secrets
|
||||
import sqlite3
|
||||
import threading
|
||||
from contextlib import contextmanager
|
||||
from datetime import datetime, timedelta, timezone
|
||||
|
||||
from app.config import (
|
||||
DATABASE_PATH, MAX_DEVICES, PCB_VERSIONS, DEFAULT_PCB_VERSION,
|
||||
PYRANO_MV_PER_WM2, AZ_DEV_DEFAULT, TOKEN_GRACE_HOURS, is_valid_device_id,
|
||||
)
|
||||
|
||||
_TS_FMT = "%Y-%m-%d %H:%M:%S"
|
||||
|
||||
|
||||
class StoreError(Exception):
|
||||
"""Error de estado/validación del almacén (sin detalle de rutas)."""
|
||||
|
||||
|
||||
def _now() -> datetime:
|
||||
return datetime.now(timezone.utc)
|
||||
|
||||
|
||||
def _iso(dt: datetime) -> str:
|
||||
return dt.strftime(_TS_FMT)
|
||||
|
||||
|
||||
def _parse_ts(s: str) -> datetime:
|
||||
return datetime.strptime(s, _TS_FMT).replace(tzinfo=timezone.utc)
|
||||
|
||||
|
||||
def _hash_token(token: str) -> str:
|
||||
return hashlib.sha256(token.encode("utf-8")).hexdigest()
|
||||
|
||||
|
||||
def _gen_token() -> str:
|
||||
"""Token aleatorio criptográfico de 256 bits (64 hex)."""
|
||||
return secrets.token_hex(32)
|
||||
|
||||
|
||||
class DeviceStore:
|
||||
def __init__(self, path: str = DATABASE_PATH):
|
||||
self.path = path
|
||||
self._lock = threading.RLock()
|
||||
self.last_write_error = None
|
||||
parent = os.path.dirname(os.path.abspath(path))
|
||||
if parent:
|
||||
os.makedirs(parent, mode=0o700, exist_ok=True)
|
||||
self._conn = sqlite3.connect(path, check_same_thread=False, timeout=10)
|
||||
self._conn.row_factory = sqlite3.Row
|
||||
self._conn.execute("PRAGMA journal_mode=WAL")
|
||||
self._conn.execute("PRAGMA foreign_keys=ON")
|
||||
self._init_schema()
|
||||
|
||||
@contextmanager
|
||||
def _transaction(self):
|
||||
with self._lock:
|
||||
try:
|
||||
self._conn.execute("BEGIN IMMEDIATE")
|
||||
yield
|
||||
self._conn.commit()
|
||||
self.last_write_error = None
|
||||
except BaseException as error:
|
||||
self.last_write_error = type(error).__name__
|
||||
self._conn.rollback()
|
||||
raise
|
||||
|
||||
def _init_schema(self):
|
||||
with self._lock:
|
||||
self._conn.executescript(
|
||||
"""
|
||||
CREATE TABLE IF NOT EXISTS devices (
|
||||
device_id TEXT PRIMARY KEY,
|
||||
alias TEXT NOT NULL DEFAULT '',
|
||||
enabled INTEGER NOT NULL DEFAULT 1,
|
||||
created_at TEXT NOT NULL,
|
||||
updated_at TEXT NOT NULL
|
||||
);
|
||||
CREATE TABLE IF NOT EXISTS tokens (
|
||||
device_id TEXT PRIMARY KEY REFERENCES devices(device_id),
|
||||
current_hash TEXT,
|
||||
current_version INTEGER NOT NULL DEFAULT 1,
|
||||
previous_hash TEXT,
|
||||
previous_expires_at TEXT,
|
||||
rotated_at TEXT
|
||||
);
|
||||
CREATE TABLE IF NOT EXISTS device_settings (
|
||||
device_id TEXT PRIMARY KEY REFERENCES devices(device_id),
|
||||
pcb_version TEXT NOT NULL,
|
||||
pyrano REAL NOT NULL,
|
||||
az_dev REAL NOT NULL,
|
||||
ota_auto INTEGER NOT NULL DEFAULT 0,
|
||||
config_revision INTEGER NOT NULL DEFAULT 0,
|
||||
updated_at TEXT NOT NULL
|
||||
);
|
||||
CREATE TABLE IF NOT EXISTS migration_state (
|
||||
key TEXT PRIMARY KEY,
|
||||
value TEXT NOT NULL,
|
||||
updated_at TEXT NOT NULL
|
||||
);
|
||||
"""
|
||||
)
|
||||
self._conn.commit()
|
||||
|
||||
def close(self):
|
||||
with self._lock:
|
||||
try:
|
||||
self._conn.close()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# ----------------------------- devices -----------------------------
|
||||
|
||||
def list_devices(self):
|
||||
with self._lock:
|
||||
rows = self._conn.execute(
|
||||
"""SELECT d.device_id, d.alias, d.enabled, d.created_at,
|
||||
t.current_version, t.previous_expires_at
|
||||
FROM devices d
|
||||
LEFT JOIN tokens t ON t.device_id = d.device_id
|
||||
ORDER BY d.created_at, d.device_id"""
|
||||
).fetchall()
|
||||
out = []
|
||||
for r in rows:
|
||||
out.append({
|
||||
"device_id": r["device_id"],
|
||||
"alias": r["alias"],
|
||||
"enabled": bool(r["enabled"]),
|
||||
"created_at": r["created_at"],
|
||||
"token_version": r["current_version"],
|
||||
"previous_expires_at": r["previous_expires_at"],
|
||||
})
|
||||
return out
|
||||
|
||||
def get_device(self, device_id: str):
|
||||
with self._lock:
|
||||
row = self._conn.execute(
|
||||
"SELECT device_id, alias, enabled, created_at FROM devices WHERE device_id = ?",
|
||||
(device_id,),
|
||||
).fetchone()
|
||||
if row is None:
|
||||
return None
|
||||
return {"device_id": row["device_id"], "alias": row["alias"], "enabled": bool(row["enabled"])}
|
||||
|
||||
def add_device(self, device_id: str, alias: str = "") -> str:
|
||||
"""Alta de tarjeta. Devuelve el token EXACTAMENTE UNA VEZ (el llamador
|
||||
lo entrega por el canal local seguro). No en claro en la BD."""
|
||||
if not is_valid_device_id(device_id):
|
||||
raise StoreError("device_id inválido")
|
||||
alias = (alias or "").strip()[:64]
|
||||
token = _gen_token()
|
||||
with self._transaction():
|
||||
exists = self._conn.execute(
|
||||
"SELECT 1 FROM devices WHERE device_id = ?", (device_id,)
|
||||
).fetchone()
|
||||
if exists:
|
||||
raise StoreError("device_id ya registrado")
|
||||
count = self._conn.execute("SELECT COUNT(*) FROM devices").fetchone()[0]
|
||||
if count >= MAX_DEVICES:
|
||||
raise StoreError("máximo de tarjetas alcanzado")
|
||||
now = _iso(_now())
|
||||
self._conn.execute(
|
||||
"INSERT INTO devices (device_id, alias, enabled, created_at, updated_at) "
|
||||
"VALUES (?, ?, 1, ?, ?)", (device_id, alias, now, now)
|
||||
)
|
||||
self._conn.execute(
|
||||
"INSERT INTO tokens (device_id, current_hash, current_version) VALUES (?, ?, 1)",
|
||||
(device_id, _hash_token(token)),
|
||||
)
|
||||
self._conn.execute(
|
||||
"INSERT INTO device_settings (device_id, pcb_version, pyrano, az_dev, ota_auto, config_revision, updated_at) "
|
||||
"VALUES (?, ?, ?, ?, 0, 0, ?)",
|
||||
(device_id, DEFAULT_PCB_VERSION, PYRANO_MV_PER_WM2, AZ_DEV_DEFAULT, now),
|
||||
)
|
||||
return token
|
||||
|
||||
def set_alias(self, device_id: str, alias: str):
|
||||
alias = (alias or "").strip()[:64]
|
||||
with self._transaction():
|
||||
cur = self._conn.execute(
|
||||
"UPDATE devices SET alias = ?, updated_at = ? WHERE device_id = ?",
|
||||
(alias, _iso(_now()), device_id),
|
||||
)
|
||||
if cur.rowcount == 0:
|
||||
raise StoreError("device_id no registrado")
|
||||
|
||||
def set_enabled(self, device_id: str, enabled: bool):
|
||||
with self._transaction():
|
||||
cur = self._conn.execute(
|
||||
"UPDATE devices SET enabled = ?, updated_at = ? WHERE device_id = ?",
|
||||
(1 if enabled else 0, _iso(_now()), device_id),
|
||||
)
|
||||
if cur.rowcount == 0:
|
||||
raise StoreError("device_id no registrado")
|
||||
|
||||
# ----------------------------- tokens ------------------------------
|
||||
|
||||
def _get_token_row(self, device_id: str):
|
||||
return self._conn.execute(
|
||||
"SELECT * FROM tokens WHERE device_id = ?", (device_id,)
|
||||
).fetchone()
|
||||
|
||||
def verify_token(self, device_id: str, token: str) -> bool:
|
||||
"""Verificación constante en tiempo. Token válido solo para su ID."""
|
||||
if not is_valid_device_id(device_id) or not token:
|
||||
return False
|
||||
return self.credential_active(device_id, _hash_token(token))
|
||||
|
||||
def credential_active(self, device_id: str, digest: str) -> bool:
|
||||
"""Validate the credential used by this session, not just any card key."""
|
||||
dev = self.get_device(device_id)
|
||||
if dev is None or not dev["enabled"]:
|
||||
return False
|
||||
with self._lock:
|
||||
row = self._get_token_row(device_id)
|
||||
if row is None:
|
||||
return False
|
||||
if row["current_hash"] and hmac.compare_digest(digest, row["current_hash"]):
|
||||
return True
|
||||
if row["previous_hash"] and row["previous_expires_at"]:
|
||||
return (_parse_ts(row["previous_expires_at"]) > _now()
|
||||
and hmac.compare_digest(digest, row["previous_hash"]))
|
||||
return False
|
||||
|
||||
def rotate_token(self, device_id: str, grace_hours: int = None) -> str:
|
||||
"""Crea el token reemplazo. El anterior queda como 'previous' con
|
||||
caducidad explícita. Devuelve el nuevo token UNA sola vez."""
|
||||
grace = TOKEN_GRACE_HOURS if grace_hours is None else int(grace_hours)
|
||||
if grace <= 0:
|
||||
raise StoreError("grace_hours debe ser positivo")
|
||||
token = _gen_token()
|
||||
now = _now()
|
||||
with self._transaction():
|
||||
row = self._get_token_row(device_id)
|
||||
if row is None:
|
||||
raise StoreError("device_id no registrado")
|
||||
self._conn.execute(
|
||||
"""UPDATE tokens SET
|
||||
current_hash = ?, current_version = current_version + 1,
|
||||
previous_hash = current_hash,
|
||||
previous_expires_at = ?, rotated_at = ?
|
||||
WHERE device_id = ?""",
|
||||
(_hash_token(token), _iso(now + timedelta(hours=grace)), _iso(now), device_id),
|
||||
)
|
||||
return token
|
||||
|
||||
def get_token_version(self, device_id: str):
|
||||
with self._lock:
|
||||
row = self._get_token_row(device_id)
|
||||
if row is None:
|
||||
return None
|
||||
return row["current_version"]
|
||||
|
||||
def retire_previous(self, device_id: str):
|
||||
"""Revoca el token anterior (tras verificar la nueva conexión)."""
|
||||
with self._transaction():
|
||||
cur = self._conn.execute(
|
||||
"UPDATE tokens SET previous_hash = NULL, previous_expires_at = NULL WHERE device_id = ?",
|
||||
(device_id,),
|
||||
)
|
||||
if cur.rowcount == 0:
|
||||
raise StoreError("device_id no registrado")
|
||||
|
||||
def revoke_tokens(self, device_id: str):
|
||||
"""Revocación urgente: elimina la validez de ambos tokens."""
|
||||
with self._transaction():
|
||||
cur = self._conn.execute(
|
||||
"UPDATE tokens SET current_hash = NULL, previous_hash = NULL, "
|
||||
"previous_expires_at = NULL WHERE device_id = ?",
|
||||
(device_id,),
|
||||
)
|
||||
if cur.rowcount == 0:
|
||||
raise StoreError("device_id no registrado")
|
||||
|
||||
# ---------------------------- settings -----------------------------
|
||||
|
||||
def get_settings(self, device_id: str):
|
||||
with self._lock:
|
||||
row = self._conn.execute(
|
||||
"SELECT pcb_version, pyrano, az_dev, ota_auto, config_revision "
|
||||
"FROM device_settings WHERE device_id = ?", (device_id,)
|
||||
).fetchone()
|
||||
if row is None:
|
||||
return None
|
||||
return {
|
||||
"pcb_version": row["pcb_version"],
|
||||
"pyrano": row["pyrano"],
|
||||
"az_dev": row["az_dev"],
|
||||
"ota_auto": bool(row["ota_auto"]),
|
||||
"config_revision": row["config_revision"],
|
||||
}
|
||||
|
||||
def save_settings(self, device_id: str, pcb_version: str = None,
|
||||
pyrano: float = None, az_dev: float = None,
|
||||
ota_auto: bool = None):
|
||||
"""Persiste en transacción. Lanza StoreError si el valor es inválido;
|
||||
el llamador debe conservar el estado previo en ese caso."""
|
||||
if pcb_version is not None and (not isinstance(pcb_version, str) or pcb_version not in PCB_VERSIONS):
|
||||
raise StoreError("pcb_version inválida")
|
||||
if pyrano is not None:
|
||||
p = float(pyrano)
|
||||
if not math.isfinite(p) or p <= 0:
|
||||
raise StoreError("pyrano debe ser finita y positiva")
|
||||
if az_dev is not None:
|
||||
a = float(az_dev)
|
||||
if not math.isfinite(a):
|
||||
raise StoreError("az_dev debe ser finita")
|
||||
with self._transaction():
|
||||
dev = self._conn.execute(
|
||||
"SELECT 1 FROM devices WHERE device_id = ?", (device_id,)
|
||||
).fetchone()
|
||||
if dev is None:
|
||||
raise StoreError("device_id no registrado")
|
||||
existing = self._conn.execute(
|
||||
"SELECT pcb_version, pyrano, az_dev, ota_auto FROM device_settings "
|
||||
"WHERE device_id = ?", (device_id,)
|
||||
).fetchone()
|
||||
now = _iso(_now())
|
||||
if existing is None:
|
||||
self._conn.execute(
|
||||
"INSERT INTO device_settings (device_id, pcb_version, pyrano, az_dev, ota_auto, config_revision, updated_at) "
|
||||
"VALUES (?, ?, ?, ?, ?, 0, ?)",
|
||||
(device_id,
|
||||
pcb_version if pcb_version is not None else DEFAULT_PCB_VERSION,
|
||||
float(pyrano) if pyrano is not None else PYRANO_MV_PER_WM2,
|
||||
float(az_dev) if az_dev is not None else AZ_DEV_DEFAULT,
|
||||
1 if ota_auto else 0, now),
|
||||
)
|
||||
else:
|
||||
self._conn.execute(
|
||||
"""UPDATE device_settings SET
|
||||
pcb_version = COALESCE(?, pcb_version),
|
||||
pyrano = COALESCE(?, pyrano),
|
||||
az_dev = COALESCE(?, az_dev),
|
||||
ota_auto = COALESCE(?, ota_auto),
|
||||
config_revision = config_revision + 1,
|
||||
updated_at = ?
|
||||
WHERE device_id = ?""",
|
||||
(pcb_version,
|
||||
float(pyrano) if pyrano is not None else None,
|
||||
float(az_dev) if az_dev is not None else None,
|
||||
(1 if ota_auto else 0) if ota_auto is not None else None,
|
||||
now, device_id),
|
||||
)
|
||||
return self.get_settings(device_id)
|
||||
|
||||
# ---------------------------- migration ----------------------------
|
||||
|
||||
def get_migration(self, key: str):
|
||||
with self._lock:
|
||||
row = self._conn.execute(
|
||||
"SELECT value FROM migration_state WHERE key = ?", (key,)
|
||||
).fetchone()
|
||||
if row is None:
|
||||
return None
|
||||
try:
|
||||
return json.loads(row["value"])
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
def set_migration(self, key: str, value):
|
||||
with self._transaction():
|
||||
self._conn.execute(
|
||||
"INSERT INTO migration_state (key, value, updated_at) VALUES (?, ?, ?) "
|
||||
"ON CONFLICT(key) DO UPDATE SET value = excluded.value, updated_at = excluded.updated_at",
|
||||
(key, json.dumps(value, ensure_ascii=False), _iso(_now())),
|
||||
)
|
||||
|
||||
def migrate_legacy(self, primary_id: str, pcb_version: str,
|
||||
pyrano: float, az_dev: float):
|
||||
"""Importación idempotente del estado legacy a UNA identidad primaria
|
||||
explícita. Devuelve (importado: bool, token_nuevo: str|None).
|
||||
Si la primaria no existe se crea (con su token de provisionamiento)."""
|
||||
marker_key = "legacy_migrated"
|
||||
if not is_valid_device_id(primary_id):
|
||||
raise StoreError("device_id inválido")
|
||||
if pcb_version not in PCB_VERSIONS:
|
||||
raise StoreError("pcb_version inválida")
|
||||
if not math.isfinite(pyrano) or pyrano <= 0 or not math.isfinite(az_dev):
|
||||
raise StoreError("calibración inválida")
|
||||
token = None
|
||||
with self._transaction():
|
||||
if self.get_migration(marker_key) is not None:
|
||||
return False, None
|
||||
exists = self._conn.execute(
|
||||
"SELECT 1 FROM devices WHERE device_id = ?", (primary_id,)
|
||||
).fetchone()
|
||||
now = _iso(_now())
|
||||
if exists:
|
||||
self._conn.execute(
|
||||
"UPDATE device_settings SET pcb_version = ?, pyrano = ?, az_dev = ?, "
|
||||
"config_revision = config_revision + 1, updated_at = ? WHERE device_id = ?",
|
||||
(pcb_version, float(pyrano), float(az_dev), now, primary_id),
|
||||
)
|
||||
else:
|
||||
count = self._conn.execute("SELECT COUNT(*) FROM devices").fetchone()[0]
|
||||
if count >= MAX_DEVICES:
|
||||
raise StoreError("máximo de tarjetas alcanzado")
|
||||
token = _gen_token()
|
||||
self._conn.execute(
|
||||
"INSERT INTO devices (device_id, alias, enabled, created_at, updated_at) "
|
||||
"VALUES (?, 'Primario', 1, ?, ?)", (primary_id, now, now)
|
||||
)
|
||||
self._conn.execute(
|
||||
"INSERT INTO tokens (device_id, current_hash, current_version) VALUES (?, ?, 1)",
|
||||
(primary_id, _hash_token(token)),
|
||||
)
|
||||
self._conn.execute(
|
||||
"INSERT INTO device_settings (device_id, pcb_version, pyrano, az_dev, ota_auto, config_revision, updated_at) "
|
||||
"VALUES (?, ?, ?, ?, 0, 0, ?)",
|
||||
(primary_id, pcb_version, float(pyrano), float(az_dev), now),
|
||||
)
|
||||
self._conn.execute(
|
||||
"INSERT INTO migration_state (key, value, updated_at) VALUES (?, ?, ?) "
|
||||
"ON CONFLICT(key) DO UPDATE SET value = excluded.value, updated_at = excluded.updated_at",
|
||||
(marker_key, json.dumps({
|
||||
"primary_id": primary_id, "pcb_version": pcb_version,
|
||||
"pyrano": float(pyrano), "az_dev": float(az_dev),
|
||||
}, ensure_ascii=False), now),
|
||||
)
|
||||
return True, token
|
||||
@@ -0,0 +1,249 @@
|
||||
"""CLI de provisionamiento local de tarjetas (proceso separado del hub).
|
||||
|
||||
Uso:
|
||||
python -m app.devices add --device-id esp32-001122aabbcc --alias "Cuarto sur"
|
||||
python -m app.devices list
|
||||
python -m app.devices rename --device-id ... --alias ...
|
||||
python -m app.devices enable --device-id ...
|
||||
python -m app.devices disable --device-id ...
|
||||
python -m app.devices rotate --device-id ... [--grace-hours N]
|
||||
python -m app.devices revoke --device-id ...
|
||||
python -m app.devices retire-previous --device-id ...
|
||||
python -m app.devices migrate-primary --device-id ...
|
||||
|
||||
El token generado se entrega UNA sola vez, solo a un archivo local protegido
|
||||
(0600) bajo STATE_DIR/provision/. Nunca se imprime en stdout ni se guarda en
|
||||
claro (la BD guarda solo SHA-256).
|
||||
"""
|
||||
import argparse
|
||||
import json
|
||||
import os
|
||||
import shutil
|
||||
import stat
|
||||
import sys
|
||||
import time
|
||||
|
||||
from app.config import (
|
||||
DATABASE_PATH, PROVISION_DIR, FIRMWARE_DIR, PCB_STATE_FILE,
|
||||
DEFAULT_PCB_VERSION, PYRANO_MV_PER_WM2, AZ_DEV_DEFAULT, is_valid_device_id,
|
||||
)
|
||||
from app.device_store import DeviceStore, StoreError
|
||||
|
||||
|
||||
def _store() -> DeviceStore:
|
||||
return DeviceStore(DATABASE_PATH)
|
||||
|
||||
|
||||
def _require_device_id(args) -> str:
|
||||
device_id = getattr(args, "device_id", None)
|
||||
if not device_id or not is_valid_device_id(device_id):
|
||||
print("ERROR: --device-id inválido (formato esperado: esp32-<12 hex minúsculos>)")
|
||||
sys.exit(2)
|
||||
return device_id
|
||||
|
||||
|
||||
def _write_token_file(device_id: str, token: str, label: str):
|
||||
"""Canal local seguro: archivo nuevo (nunca sobreescribe) con permisos
|
||||
0600. Solo imprime la ruta, NUNCA el token."""
|
||||
os.makedirs(PROVISION_DIR, exist_ok=True)
|
||||
path = os.path.join(PROVISION_DIR, f"{device_id}.{label}.token")
|
||||
if os.path.exists(path):
|
||||
print(f"ERROR: ya existe {path}; se usa un canal nuevo por operación (no se sobreescribe).")
|
||||
sys.exit(1)
|
||||
try:
|
||||
fd = os.open(path, os.O_WRONLY | os.O_CREAT | os.O_EXCL, 0o600)
|
||||
except FileExistsError:
|
||||
print(f"ERROR: ya existe {path}.")
|
||||
sys.exit(1)
|
||||
with os.fdopen(fd, "w", encoding="utf-8") as f:
|
||||
f.write(token + "\n")
|
||||
try:
|
||||
os.chmod(path, stat.S_IRUSR | stat.S_IWUSR)
|
||||
except Exception:
|
||||
pass
|
||||
print(f"Token guardado (una sola vez) en: {path}")
|
||||
print("ADVERTENCIA: verifica los permisos del archivo (0600 / ACL en Windows).")
|
||||
print("El token NO se puede recuperar: cópialo a tu ESP32 ahora y borra este archivo tras installarlo.")
|
||||
|
||||
|
||||
def cmd_add(args):
|
||||
device_id = _require_device_id(args)
|
||||
store = _store()
|
||||
try:
|
||||
token = store.add_device(device_id, args.alias)
|
||||
except StoreError as e:
|
||||
print(f"ERROR: {e}")
|
||||
sys.exit(1)
|
||||
_write_token_file(device_id, token, "v1")
|
||||
print(f"Alta completada: {device_id} (alias: {args.alias!r})")
|
||||
|
||||
|
||||
def cmd_list(args):
|
||||
store = _store()
|
||||
rows = store.list_devices()
|
||||
if not rows:
|
||||
print("Sin tarjetas registradas.")
|
||||
return
|
||||
print(f"{'DEVICE_ID':<22} {'ENABLED':<8} {'TOKEN_V':<8} {'ALIAS'}")
|
||||
for r in rows:
|
||||
print(f"{r['device_id']:<22} {'si' if r['enabled'] else 'no':<8} "
|
||||
f"{r['token_version']:<8} {r['alias']}")
|
||||
|
||||
|
||||
def cmd_rename(args):
|
||||
device_id = _require_device_id(args)
|
||||
store = _store()
|
||||
try:
|
||||
store.set_alias(device_id, args.alias)
|
||||
except StoreError as e:
|
||||
print(f"ERROR: {e}")
|
||||
sys.exit(1)
|
||||
print(f"Alias actualizado: {device_id} -> {args.alias!r}")
|
||||
|
||||
|
||||
def cmd_enable(args):
|
||||
_set_enabled(args, True)
|
||||
|
||||
|
||||
def cmd_disable(args):
|
||||
_set_enabled(args, False)
|
||||
|
||||
|
||||
def _set_enabled(args, enabled: bool):
|
||||
device_id = _require_device_id(args)
|
||||
store = _store()
|
||||
try:
|
||||
store.set_enabled(device_id, enabled)
|
||||
except StoreError as e:
|
||||
print(f"ERROR: {e}")
|
||||
sys.exit(1)
|
||||
print(f"{'Habilitada' if enabled else 'Deshabilitada'}: {device_id} "
|
||||
"(la sesión activa se cierra en el próximo sondeo del hub)")
|
||||
|
||||
|
||||
def cmd_rotate(args):
|
||||
device_id = _require_device_id(args)
|
||||
store = _store()
|
||||
try:
|
||||
token = store.rotate_token(device_id, args.grace_hours)
|
||||
v = store.get_token_version(device_id) or 2
|
||||
except StoreError as e:
|
||||
print(f"ERROR: {e}")
|
||||
sys.exit(1)
|
||||
_write_token_file(device_id, token, f"v{v}")
|
||||
print("Rotación completada: el token anterior sigue válido hasta su caducidad "
|
||||
"(o hasta 'retire-previous' / 'revoke').")
|
||||
|
||||
|
||||
def cmd_revoke(args):
|
||||
device_id = _require_device_id(args)
|
||||
store = _store()
|
||||
try:
|
||||
store.revoke_tokens(device_id)
|
||||
except StoreError as e:
|
||||
print(f"ERROR: {e}")
|
||||
sys.exit(1)
|
||||
print(f"Revocación urgente: {device_id}. La sesión activa se cierra en el "
|
||||
"próximo sondeo del hub y ambos tokens quedan inválidos.")
|
||||
|
||||
|
||||
def cmd_retire_previous(args):
|
||||
device_id = _require_device_id(args)
|
||||
store = _store()
|
||||
try:
|
||||
store.retire_previous(device_id)
|
||||
except StoreError as e:
|
||||
print(f"ERROR: {e}")
|
||||
sys.exit(1)
|
||||
print(f"Token anterior revocado: {device_id} (solo el token actual queda válido).")
|
||||
|
||||
|
||||
def cmd_migrate_primary(args):
|
||||
device_id = _require_device_id(args)
|
||||
store = _store()
|
||||
pcb = DEFAULT_PCB_VERSION
|
||||
if os.path.exists(PCB_STATE_FILE):
|
||||
try:
|
||||
with open(PCB_STATE_FILE, "r", encoding="utf-8") as f:
|
||||
v = json.load(f).get("version")
|
||||
if v not in ("V1", "V2"):
|
||||
raise ValueError("PCB legacy inválida")
|
||||
pcb = v
|
||||
except Exception:
|
||||
print("ERROR: PCB legacy inválida; migración cancelada sin cambiar ajustes.")
|
||||
sys.exit(1)
|
||||
# Respaldo ANTES de la importación (idempotente por timestamp).
|
||||
try:
|
||||
bak = f"{PCB_STATE_FILE}.bak-{time.strftime('%Y%m%d-%H%M%S')}"
|
||||
shutil.copy2(PCB_STATE_FILE, bak)
|
||||
print(f"Respaldo legacy: {bak}")
|
||||
except Exception as e:
|
||||
print(f"ERROR: no se pudo respaldar el PCB legacy ({type(e).__name__}); migración cancelada.")
|
||||
sys.exit(1)
|
||||
# La calibración legacy vive en memoria del proceso antiguo; aquí se
|
||||
# importan los defaults y el operador aplica explícitamente si difieren.
|
||||
try:
|
||||
imported, token = store.migrate_legacy(device_id, pcb, PYRANO_MV_PER_WM2, AZ_DEV_DEFAULT)
|
||||
except StoreError as e:
|
||||
print(f"ERROR: {e}")
|
||||
sys.exit(1)
|
||||
if not imported:
|
||||
print("Migración ya realizada (idempotente): no se repite. "
|
||||
"La primaria ya tiene su estado importado.")
|
||||
return
|
||||
print(f"Migración legacy -> {device_id} completada (PCB={pcb}, calibración=defaults).")
|
||||
if token is not None:
|
||||
_write_token_file(device_id, token, "v1")
|
||||
print("La primaria no existía: se creó con su token de provisionamiento.")
|
||||
else:
|
||||
print("La primaria ya estaba dada de alta: se aplicó solo su estado.")
|
||||
|
||||
|
||||
def main(argv=None):
|
||||
p = argparse.ArgumentParser(prog="app.devices", description="Provisionamiento local de tarjetas")
|
||||
sub = p.add_subparsers(dest="cmd", required=True)
|
||||
|
||||
sp = sub.add_parser("add", help="Alta de tarjeta (genera token, se entrega una vez)")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.add_argument("--alias", default="")
|
||||
sp.set_defaults(fn=cmd_add)
|
||||
|
||||
sp = sub.add_parser("list", help="Lista tarjetas (sin secretos)")
|
||||
sp.set_defaults(fn=cmd_list)
|
||||
|
||||
sp = sub.add_parser("rename", help="Renombra alias")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.add_argument("--alias", required=True)
|
||||
sp.set_defaults(fn=cmd_rename)
|
||||
|
||||
sp = sub.add_parser("enable", help="Habilita tarjeta")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.set_defaults(fn=cmd_enable)
|
||||
|
||||
sp = sub.add_parser("disable", help="Deshabilita tarjeta")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.set_defaults(fn=cmd_disable)
|
||||
|
||||
sp = sub.add_parser("rotate", help="Rota token (el anterior caduca en grace-hours)")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.add_argument("--grace-hours", type=int, default=None)
|
||||
sp.set_defaults(fn=cmd_rotate)
|
||||
|
||||
sp = sub.add_parser("revoke", help="Revocación urgente de ambos tokens")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.set_defaults(fn=cmd_revoke)
|
||||
|
||||
sp = sub.add_parser("retire-previous", help="Revoca solo el token anterior")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.set_defaults(fn=cmd_retire_previous)
|
||||
|
||||
sp = sub.add_parser("migrate-primary", help="Importa estado legacy a una primaria explícita")
|
||||
sp.add_argument("--device-id", required=True)
|
||||
sp.set_defaults(fn=cmd_migrate_primary)
|
||||
|
||||
args = p.parse_args(argv)
|
||||
args.fn(args)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,205 @@
|
||||
"""Coordinación de varias tarjetas: registro de sesiones por identidad,
|
||||
autenticación, límites por tarjeta y retención de logs.
|
||||
|
||||
El estado por tarjeta (buffers, sockets, calibración) vive en HubManager;
|
||||
aquí solo se coordina. Nunca se reservan buffers para identidades
|
||||
desconocidas: solo se instancian tarjetas registradas.
|
||||
"""
|
||||
import logging
|
||||
import hashlib
|
||||
import os
|
||||
import time
|
||||
from typing import Dict, Optional
|
||||
|
||||
from app.config import (
|
||||
LOGS_DIR, MAX_DEVICES, WS_RATE_PER_SEC, WS_RATE_BURST,
|
||||
is_valid_device_id,
|
||||
)
|
||||
from app.hub import HubManager
|
||||
|
||||
log = logging.getLogger("tracker_hub.fleet")
|
||||
|
||||
|
||||
class _TokenBucket:
|
||||
__slots__ = ("rate", "burst", "tokens", "ts")
|
||||
|
||||
def __init__(self, rate: float, burst: int):
|
||||
self.rate = rate
|
||||
self.burst = float(burst)
|
||||
self.tokens = float(burst)
|
||||
self.ts = time.monotonic()
|
||||
|
||||
def allow(self) -> bool:
|
||||
now = time.monotonic()
|
||||
self.tokens = min(self.burst, self.tokens + (now - self.ts) * self.rate)
|
||||
self.ts = now
|
||||
if self.tokens >= 1.0:
|
||||
self.tokens -= 1.0
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
class FleetManager:
|
||||
def __init__(self, store, rate: float = WS_RATE_PER_SEC, burst: int = WS_RATE_BURST):
|
||||
self.store = store
|
||||
self._rate = rate
|
||||
self._burst = burst
|
||||
self._hubs: Dict[str, HubManager] = {}
|
||||
self._buckets: Dict[str, _TokenBucket] = {}
|
||||
self._credentials = {}
|
||||
|
||||
@property
|
||||
def hubs(self) -> Dict[str, HubManager]:
|
||||
return self._hubs
|
||||
|
||||
# ---------------------------- identidad ----------------------------
|
||||
|
||||
def is_registered(self, device_id: str) -> bool:
|
||||
if not is_valid_device_id(device_id):
|
||||
return False
|
||||
return self.store.get_device(device_id) is not None
|
||||
|
||||
def get(self, device_id: str) -> Optional[HubManager]:
|
||||
"""Devuelve el hub de una tarjeta REGISTRADA (instanciando bajo
|
||||
demanda; buffers vacíos hasta recibir telemetría). Nunca crea estado
|
||||
para IDs desconocidos."""
|
||||
if not self.is_registered(device_id):
|
||||
return None
|
||||
h = self._hubs.get(device_id)
|
||||
if h is None:
|
||||
h = HubManager(device_id=device_id, store=self.store)
|
||||
self._hubs[device_id] = h
|
||||
else:
|
||||
h._load_settings()
|
||||
return h
|
||||
|
||||
def bind_session(self, device_id, connection_id, token):
|
||||
self._credentials[device_id] = (connection_id, hashlib.sha256(token.encode()).hexdigest())
|
||||
self._hubs[device_id].authorize_session = lambda: self.session_valid(device_id, connection_id)
|
||||
|
||||
def forget_session(self, device_id, connection_id):
|
||||
if self._credentials.get(device_id, (None,))[0] == connection_id:
|
||||
self._credentials.pop(device_id, None)
|
||||
|
||||
def session_valid(self, device_id, connection_id):
|
||||
record = self._credentials.get(device_id)
|
||||
if record is None or record[0] != connection_id:
|
||||
return False
|
||||
try:
|
||||
return self.store.credential_active(device_id, record[1])
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
def get_or_create(self, device_id: str) -> Optional[HubManager]:
|
||||
return self.get(device_id)
|
||||
|
||||
def authenticate(self, device_id: str, token: str) -> bool:
|
||||
"""Verifica ID + token (solo para ese ID y canal). Rechazo genérico:
|
||||
no se revela si la identidad existe."""
|
||||
if not is_valid_device_id(device_id) or not token:
|
||||
return False
|
||||
try:
|
||||
return self.store.verify_token(device_id, token)
|
||||
except Exception as e:
|
||||
log.error("auth_check_failed", extra={"event": "auth_check_failed",
|
||||
"device_id": device_id,
|
||||
"error_type": type(e).__name__})
|
||||
return False
|
||||
|
||||
# ----------------------------- límites -----------------------------
|
||||
|
||||
def check_rate(self, device_id: str) -> bool:
|
||||
if not self.is_registered(device_id):
|
||||
return False
|
||||
b = self._buckets.get(device_id)
|
||||
if b is None:
|
||||
b = self._buckets[device_id] = _TokenBucket(self._rate, self._burst)
|
||||
return b.allow()
|
||||
|
||||
# --------------------- revocación (polling) ------------------------
|
||||
|
||||
async def poll_credentials(self):
|
||||
"""Sondea credenciales de las tarjetas conectadas. La revocación o
|
||||
deshabilitación desde la CLI (proceso separado) cierra la sesión
|
||||
activa en este intervalo."""
|
||||
closed = []
|
||||
for device_id, h in list(self._hubs.items()):
|
||||
if not h.esp32_connected:
|
||||
continue
|
||||
try:
|
||||
connection_id = h.connection_id
|
||||
active = self.session_valid(device_id, connection_id)
|
||||
except Exception as e:
|
||||
log.error("credential_poll_failed", extra={"event": "credential_poll_failed",
|
||||
"device_id": device_id,
|
||||
"error_type": type(e).__name__})
|
||||
active = False
|
||||
if not active:
|
||||
log.warning("credential_revoked_close", extra={"event": "credential_revoked_close",
|
||||
"device_id": device_id})
|
||||
try:
|
||||
await h.force_close(connection_id)
|
||||
except Exception:
|
||||
pass
|
||||
closed.append(device_id)
|
||||
self.forget_session(device_id, connection_id)
|
||||
return closed
|
||||
|
||||
# --------------------------- retención logs -------------------------
|
||||
|
||||
def prune_logs(self, retention_days: int) -> int:
|
||||
"""Borra logs diarios por tarjeta mayores a retention_days. NUNCA
|
||||
toca los archivos legacy en la raíz de LOGS_DIR."""
|
||||
if retention_days <= 0:
|
||||
return 0
|
||||
cutoff = time.time() - retention_days * 86400
|
||||
removed = 0
|
||||
try:
|
||||
entries = os.listdir(LOGS_DIR)
|
||||
except Exception:
|
||||
return 0
|
||||
for name in entries:
|
||||
p = os.path.join(LOGS_DIR, name)
|
||||
if not os.path.isdir(p) or os.path.islink(p):
|
||||
continue
|
||||
if not is_valid_device_id(name):
|
||||
continue
|
||||
try:
|
||||
for fn in os.listdir(p):
|
||||
fp = os.path.join(p, fn)
|
||||
if (fn.startswith("log_") and fn.endswith(".txt")
|
||||
and os.path.isfile(fp) and os.path.getmtime(fp) < cutoff):
|
||||
try:
|
||||
os.remove(fp)
|
||||
removed += 1
|
||||
except Exception:
|
||||
pass
|
||||
except Exception:
|
||||
pass
|
||||
return removed
|
||||
|
||||
# ------------------------------ listado -----------------------------
|
||||
|
||||
def list_devices(self):
|
||||
out = []
|
||||
for row in self.store.list_devices():
|
||||
h = self._hubs.get(row["device_id"])
|
||||
pcb = h.pcb_version if h is not None else None
|
||||
if pcb is None:
|
||||
try:
|
||||
s = self.store.get_settings(row["device_id"])
|
||||
pcb = s["pcb_version"] if s else None
|
||||
except Exception:
|
||||
pcb = None
|
||||
out.append({
|
||||
"device_id": row["device_id"],
|
||||
"alias": row["alias"],
|
||||
"enabled": row["enabled"],
|
||||
"esp32_connected": bool(h.esp32_connected) if h is not None else False,
|
||||
"last_seen": h.last_seen.isoformat() if (h and h.last_seen) else None,
|
||||
"last_telemetry_at": h.last_telemetry_at.isoformat() if (h and h.last_telemetry_at) else None,
|
||||
"firmware": h.esp32_firmware_version if h is not None else None,
|
||||
"pcb_version": pcb,
|
||||
"created_at": row["created_at"],
|
||||
})
|
||||
return out
|
||||
@@ -0,0 +1,630 @@
|
||||
import os
|
||||
import re
|
||||
import json
|
||||
import math
|
||||
import uuid
|
||||
import asyncio
|
||||
import logging
|
||||
from collections import deque
|
||||
from datetime import datetime
|
||||
from typing import List, Optional
|
||||
from fastapi import WebSocket
|
||||
|
||||
from app.config import (
|
||||
LOGS_DIR, FIRMWARE_DIR, FIRMWARE_BIN, OTA_MANIFEST_FILE, OTA_STATE_FILE,
|
||||
OTA_PUBLIC_URL, ADC_MAX, VREF_MV, VREF_V, GAIN_SHUNT, FF, VOC_DIVIDER,
|
||||
PCB_VERSIONS, DEFAULT_PCB_VERSION, PCB_STATE_FILE,
|
||||
PYRANO_MV_PER_WM2, AZ_DEV_DEFAULT, STEPS_80, DEG_SPAN, MAX_SAMPLES,
|
||||
HISTORY_LIMIT, LOCAL_TZ, BROADCAST_TIMEOUT, LOG_DAILY_MAX_BYTES, get_local_now
|
||||
)
|
||||
|
||||
log = logging.getLogger("tracker_hub.hub")
|
||||
|
||||
RE_SAMPLE = re.compile(
|
||||
r"^(?:LOG:)?\[(?P<ts>[0-9\-/ :]+)\]\s*X:(?P<x>-?\d+),Y:(?P<y>-?\d+),"
|
||||
r"C:(?P<c>-?\d+),V:(?P<v>-?\d+),P:(?P<p>-?\d+),S:\d+,er:(?P<er>-?\d+)\s*$"
|
||||
)
|
||||
# Telemetría periódica (promedios cada 2 s) emitida por el firmware nuevo:
|
||||
# LOG:[YYYY-MM-DD HH:MM:SS] TEL: t=<uptime>s, steps=<tot>(+<delta>),
|
||||
# avgC=<c>, avgV=<v>, avgP=<p>, LPF=<lpf>, X=<x>, Y=<y>
|
||||
# Desde el firmware 1.1.1 (F6) se agregan dos campos de diagnóstico ENTRE LPF
|
||||
# y X: prox=<0..1> y CmaxN=<counts>. Son OPCIONALES en el parser para no
|
||||
# romper el formato previo (builds sin F6 no los emiten). X/Y llegan "crudos"
|
||||
# (getPosX/getPosY); el resto del hub usa posición invertida, así que on_tel()
|
||||
# los invierte para que las series se superpongan. Con firmware viejo no hay
|
||||
# líneas TEL: y el parser simplemente no dispara.
|
||||
RE_TEL = re.compile(
|
||||
r"^(?:LOG:)?\[(?P<ts>[0-9\-/ :]+)\]\s*TEL:\s*"
|
||||
r"t=(?P<t>\d+)s,\s*"
|
||||
r"steps=(?P<steps>\d+)\((?P<stepsDelta>[+\-]?\d+)\),\s*"
|
||||
r"avgC=(?P<avgC>-?\d+),\s*"
|
||||
r"avgV=(?P<avgV>-?\d+),\s*"
|
||||
r"avgP=(?P<avgP>-?\d+),\s*"
|
||||
r"LPF=(?P<lpf>-?\d+)"
|
||||
r"(?:,\s*prox=(?P<prox>-?\d+(?:\.\d+)?))?"
|
||||
r"(?:,\s*CmaxN=(?P<cmaxN>-?\d+))?"
|
||||
r",\s*"
|
||||
r"X=(?P<x>-?\d+),\s*"
|
||||
r"Y=(?P<y>-?\d+)\s*$"
|
||||
)
|
||||
RE_AXIS_ACK = re.compile(r"AXISCFG:(?P<x>\d+):(?P<y>\d+):(?P<base>\d+)")
|
||||
RE_AXIS_ACK_LOG = re.compile(
|
||||
r"LOG:\[(?:\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}|sin hora)\] "
|
||||
r"AXISCFG:(?P<x>\d+):(?P<y>\d+):(?P<base>\d+)"
|
||||
)
|
||||
RE_PARAM = re.compile(
|
||||
r"^(?:LOG:)?\[(?P<ts>[0-9\-/ :]+)\]\s*(?P<name>Az_deviation|ErrMax|"
|
||||
r"MinErrMax|TiltAngle|delay)\s*=\s*(?P<val>[-\d.]+)\s*$"
|
||||
)
|
||||
_TS_FORMATS = ("%Y-%m-%d %H:%M:%S", "%Y-%m-%d %H:%M", "%d/%m/%Y %H:%M:%S", "%d/%m/%Y %H:%M")
|
||||
|
||||
def parse_ts(s: str) -> Optional[datetime]:
|
||||
s = s.strip()
|
||||
for fmt in _TS_FORMATS:
|
||||
try:
|
||||
return datetime.strptime(s, fmt).replace(tzinfo=LOCAL_TZ)
|
||||
except Exception:
|
||||
pass
|
||||
return None
|
||||
|
||||
|
||||
class HubManager:
|
||||
"""Estado de UNA tarjeta (parsers, buffers, calibración, sesión ESP32).
|
||||
|
||||
Constructible en modo standalone (`HubManager()`): efímero, sin SQLite ni
|
||||
I/O de estado global. Con `store` se persisten calibración/PCB/OTA-auto.
|
||||
"""
|
||||
|
||||
def __init__(self, device_id: Optional[str] = None, store=None):
|
||||
self.device_id = device_id
|
||||
self._store = store
|
||||
self.esp32_socket: Optional[WebSocket] = None
|
||||
self.esp32_connected = False
|
||||
self.client_sockets: List[WebSocket] = []
|
||||
self.last_pos_x = 0
|
||||
self.last_pos_y = 0
|
||||
self.last_seen: Optional[datetime] = None
|
||||
self.last_telemetry_at: Optional[datetime] = None
|
||||
self.connected_at: Optional[datetime] = None
|
||||
self.connection_id: Optional[str] = None
|
||||
self.pyrano = PYRANO_MV_PER_WM2
|
||||
self.azdev = AZ_DEV_DEFAULT
|
||||
self.samples: deque = deque(maxlen=MAX_SAMPLES)
|
||||
self.tel_samples: deque = deque(maxlen=MAX_SAMPLES)
|
||||
|
||||
self.esp32_firmware_version: Optional[str] = None
|
||||
self.ota_manifest: Optional[dict] = None
|
||||
self.ota_auto_enabled: bool = False
|
||||
self.ota_url: str = OTA_PUBLIC_URL + "/ota/firmware"
|
||||
|
||||
self.pcb_version: str = DEFAULT_PCB_VERSION
|
||||
self._send_lock = asyncio.Lock()
|
||||
self._auto_task: Optional[asyncio.Task] = None
|
||||
self.config_revision = -1
|
||||
self.log_error_count = 0
|
||||
self.log_error = None
|
||||
self._log_error_day = None
|
||||
self._version_session_id = None
|
||||
self.authorize_session = None
|
||||
|
||||
if store is not None and device_id is not None:
|
||||
self._load_settings()
|
||||
|
||||
# --------------------------- sesión ESP32 ---------------------------
|
||||
|
||||
async def connect_esp32(self, websocket: WebSocket, on_connect=None) -> str:
|
||||
"""Acepta una sesión autenticada. Si ya había otra del MISMO ID, la
|
||||
cierra explícitamente; los eventos tardíos de la antigua se ignoran
|
||||
por connection_id."""
|
||||
await websocket.accept()
|
||||
old = self.esp32_socket
|
||||
conn_id = uuid.uuid4().hex[:12]
|
||||
self.connection_id = conn_id
|
||||
self.esp32_socket = websocket
|
||||
self.esp32_connected = True
|
||||
self.connected_at = get_local_now()
|
||||
self.last_seen = self.connected_at
|
||||
self._version_session_id = None
|
||||
if on_connect is not None:
|
||||
on_connect(conn_id)
|
||||
if self._auto_task is not None:
|
||||
self._auto_task.cancel()
|
||||
self._auto_task = None
|
||||
log.info("esp32_connect", extra={"event": "esp32_connect", "device_id": self.device_id,
|
||||
"connection_id": conn_id})
|
||||
if old is not None and old is not websocket:
|
||||
try:
|
||||
await old.close(code=1000)
|
||||
except Exception:
|
||||
pass
|
||||
await self.broadcast_status()
|
||||
await self.broadcast_ota()
|
||||
return conn_id
|
||||
|
||||
def disconnect_esp32(self, conn_id: Optional[str] = None):
|
||||
"""Cierre de sesión. Un `finally` tardío de una sesión reemplazada NO
|
||||
desconecta a la nueva: se verifica connection_id."""
|
||||
if conn_id is not None and conn_id != self.connection_id:
|
||||
log.info("esp32_late_event_ignored", extra={"event": "esp32_late_event_ignored",
|
||||
"device_id": self.device_id})
|
||||
return
|
||||
if self._auto_task is not None:
|
||||
self._auto_task.cancel()
|
||||
self._auto_task = None
|
||||
was_connected = self.esp32_connected
|
||||
self.esp32_socket = None
|
||||
self.esp32_connected = False
|
||||
self.connection_id = None
|
||||
if was_connected:
|
||||
log.info("esp32_disconnect", extra={"event": "esp32_disconnect", "device_id": self.device_id,
|
||||
"connection_id": conn_id})
|
||||
|
||||
async def force_close(self, conn_id=None):
|
||||
"""Cierre forzado (revocación de credenciales): cierra el socket y
|
||||
marca desconectado; publica el cambio de estado."""
|
||||
if conn_id is not None and conn_id != self.connection_id:
|
||||
return
|
||||
if self._auto_task is not None:
|
||||
self._auto_task.cancel()
|
||||
self._auto_task = None
|
||||
sock, self.esp32_socket = self.esp32_socket, None
|
||||
self.esp32_connected = False
|
||||
self.connection_id = None
|
||||
if sock is not None:
|
||||
try:
|
||||
await sock.close(code=1008)
|
||||
except Exception:
|
||||
pass
|
||||
log.warning("esp32_forced_close", extra={"event": "esp32_forced_close", "device_id": self.device_id})
|
||||
await self.broadcast_status()
|
||||
await self.broadcast_ota()
|
||||
|
||||
async def handle_esp32_message(self, message: str, conn_id: Optional[str] = None):
|
||||
if conn_id is not None and (conn_id != self.connection_id or not self.esp32_connected):
|
||||
log.info("esp32_late_message_ignored", extra={"event": "esp32_late_message_ignored",
|
||||
"device_id": self.device_id})
|
||||
return
|
||||
self.last_seen = get_local_now()
|
||||
line = message.strip()
|
||||
self._append_log(line)
|
||||
if not line:
|
||||
return
|
||||
try:
|
||||
await self._process_line(line)
|
||||
except (ValueError, TypeError, OverflowError):
|
||||
log.warning("line_rejected", extra={"event": "line_rejected", "device_id": self.device_id})
|
||||
|
||||
async def _process_line(self, line):
|
||||
if line.startswith("POS:"):
|
||||
parts = line.split(":")
|
||||
if len(parts) >= 3:
|
||||
try:
|
||||
self.last_pos_x, self.last_pos_y = int(parts[1]), int(parts[2])
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
axis_ack = RE_AXIS_ACK.fullmatch(line) or RE_AXIS_ACK_LOG.fullmatch(line)
|
||||
if axis_ack:
|
||||
x_factor, y_factor, base = (int(axis_ack.group(k)) for k in ("x", "y", "base"))
|
||||
if (1 <= x_factor <= 8 and 1 <= y_factor <= 8 and 1 <= base <= 64
|
||||
and x_factor * base <= 64 and y_factor * base <= 64):
|
||||
await self._broadcast("AXISCFG:" + json.dumps({"x": x_factor, "y": y_factor, "base": base,
|
||||
"device_id": self.device_id,
|
||||
"x_budget": x_factor * base, "y_budget": y_factor * base}))
|
||||
|
||||
if line.startswith("VER:"):
|
||||
v = line[4:].strip()
|
||||
self._version_session_id = self.connection_id
|
||||
if v and v != self.esp32_firmware_version:
|
||||
self.esp32_firmware_version = v
|
||||
await self._broadcast("FW:" + v)
|
||||
await self.broadcast_ota()
|
||||
if v:
|
||||
self._maybe_auto_update()
|
||||
|
||||
m = RE_SAMPLE.match(line)
|
||||
if m:
|
||||
pt = self.on_sample(m.groupdict())
|
||||
self.last_telemetry_at = get_local_now()
|
||||
if pt:
|
||||
await self._broadcast("DATA:" + json.dumps(pt))
|
||||
|
||||
# Telemetría promediada (firmware nuevo). Con firmware viejo no hay
|
||||
# líneas TEL: y este bloque no se ejecuta (compatibilidad hacia atrás).
|
||||
mt = RE_TEL.match(line)
|
||||
if mt:
|
||||
tpt = self.on_tel(mt.groupdict())
|
||||
self.last_telemetry_at = get_local_now()
|
||||
if tpt:
|
||||
await self._broadcast("TEL:" + json.dumps(tpt))
|
||||
|
||||
pm = RE_PARAM.match(line)
|
||||
if pm:
|
||||
name, val = pm.group("name"), float(pm.group("val"))
|
||||
if name == "Az_deviation" and abs(val - self.azdev) > 1e-6:
|
||||
# Persistir ANTES de mutar el estado en memoria.
|
||||
if self._store is not None:
|
||||
try:
|
||||
self._store.save_settings(self.device_id, az_dev=val)
|
||||
except Exception as e:
|
||||
log.error("azdev_persist_failed", extra={"event": "azdev_persist_failed",
|
||||
"device_id": self.device_id,
|
||||
"error_type": type(e).__name__})
|
||||
else:
|
||||
self.azdev = val
|
||||
self._recompute_position()
|
||||
await self._broadcast("CONFIG:" + self._config_json())
|
||||
else:
|
||||
self.azdev = val
|
||||
self._recompute_position()
|
||||
await self._broadcast("CONFIG:" + self._config_json())
|
||||
|
||||
await self._broadcast("LOG:" + line + "\n")
|
||||
|
||||
# ------------------------- conversión de datos ------------------------
|
||||
|
||||
def _units(self, x, y, c, v, p):
|
||||
r_shunt = PCB_VERSIONS[self.pcb_version]
|
||||
gpoa = p / ADC_MAX * (VREF_MV / self.pyrano)
|
||||
voc = v / ADC_MAX * VREF_V * VOC_DIVIDER
|
||||
isc = (c / ADC_MAX * (VREF_MV / GAIN_SHUNT)) / 1000.0 / r_shunt
|
||||
pcpv = voc * isc * FF
|
||||
return gpoa, voc, isc, pcpv
|
||||
|
||||
def _pos_deg(self, x, y):
|
||||
x_base = y - self.azdev / 90.0 * x
|
||||
el = 90.0 - (x_base - STEPS_80) / STEPS_80 * DEG_SPAN
|
||||
az = 180.0 + (x - STEPS_80) / STEPS_80 * DEG_SPAN
|
||||
return az, el
|
||||
|
||||
def on_sample(self, d):
|
||||
ts = parse_ts(d["ts"])
|
||||
t = ts.timestamp() if ts else get_local_now().timestamp()
|
||||
x, y, c, v, p = int(d["x"]), int(d["y"]), int(d["c"]), int(d["v"]), int(d["p"])
|
||||
gpoa, voc, isc, pcpv = self._units(x, y, c, v, p)
|
||||
az, el = self._pos_deg(x, y)
|
||||
pt = {
|
||||
"ts": round(t, 3), "x": x, "y": y, "p_raw": p, "c_raw": c, "v_raw": v,
|
||||
"gpoa": round(gpoa, 1), "voc": round(voc, 3),
|
||||
"isc_ma": round(isc * 1000, 2), "pcpv_mw": round(pcpv * 1000, 2),
|
||||
"az": round(az, 2), "el": round(el, 2)
|
||||
}
|
||||
if self.device_id:
|
||||
pt["device_id"] = self.device_id
|
||||
self.samples.append(pt)
|
||||
return pt
|
||||
|
||||
def on_tel(self, d):
|
||||
ts = parse_ts(d["ts"])
|
||||
t_wall = ts.timestamp() if ts else get_local_now().timestamp()
|
||||
avg_c, avg_v, avg_p = int(d["avgC"]), int(d["avgV"]), int(d["avgP"])
|
||||
# X/Y crudos del firmware -> se invierten para alinear con el sistema
|
||||
# de coordenadas del hub (muestras y POS usan valores negados).
|
||||
x, y = -int(d["x"]), -int(d["y"])
|
||||
gpoa, voc, isc, pcpv = self._units(x, y, avg_c, avg_v, avg_p)
|
||||
az, el = self._pos_deg(x, y)
|
||||
pt = {
|
||||
"ts": round(t_wall, 3), "t": int(d["t"]),
|
||||
"steps": int(d["steps"]), "steps_delta": int(d["stepsDelta"]),
|
||||
"avg_c": avg_c, "avg_v": avg_v, "avg_p": avg_p,
|
||||
"lpf": int(d["lpf"]), "x": x, "y": y,
|
||||
# F6 (firmware >= 1.1.1): campos de diagnóstico opcionales.
|
||||
"prox": float(d["prox"]) if d.get("prox") is not None else None,
|
||||
"cmaxn": int(d["cmaxN"]) if d.get("cmaxN") is not None else None,
|
||||
"gpoa": round(gpoa, 1), "voc": round(voc, 3),
|
||||
"isc_ma": round(isc * 1000, 2), "pcpv_mw": round(pcpv * 1000, 2),
|
||||
"az": round(az, 2), "el": round(el, 2),
|
||||
}
|
||||
if self.device_id:
|
||||
pt["device_id"] = self.device_id
|
||||
self.tel_samples.append(pt)
|
||||
return pt
|
||||
|
||||
def _recompute_position(self):
|
||||
for pt in self.samples:
|
||||
az, el = self._pos_deg(pt["x"], pt["y"])
|
||||
pt["az"], pt["el"] = round(az, 2), round(el, 2)
|
||||
for pt in self.tel_samples:
|
||||
az, el = self._pos_deg(pt["x"], pt["y"])
|
||||
pt["az"], pt["el"] = round(az, 2), round(el, 2)
|
||||
|
||||
def _config_json(self):
|
||||
return json.dumps({
|
||||
"device_id": self.device_id,
|
||||
"pyrano": self.pyrano, "azdev": self.azdev, "adc_max": ADC_MAX,
|
||||
"vref_mv": VREF_MV, "vref_v": VREF_V, "gain_shunt": GAIN_SHUNT,
|
||||
"r_shunt": PCB_VERSIONS[self.pcb_version], "ff": FF, "voc_div": VOC_DIVIDER,
|
||||
"pcb_version": self.pcb_version,
|
||||
"steps80": STEPS_80, "deg_span": DEG_SPAN, "pos": [self.last_pos_x, self.last_pos_y]
|
||||
})
|
||||
|
||||
# ---------------------------- suscriptores ----------------------------
|
||||
|
||||
async def connect_client(self, websocket: WebSocket):
|
||||
await websocket.accept()
|
||||
self.client_sockets.append(websocket)
|
||||
try:
|
||||
# CONFIG va como instantánea inicial completa (marcador de
|
||||
# "listo") ANTES de cualquier historial, para que la UI no vea
|
||||
# datos con configuración vieja.
|
||||
await self._send_to(websocket, "STATUS:%s" % ("ONLINE" if self.esp32_connected else "OFFLINE"))
|
||||
await self._send_to(websocket, "CONFIG:" + self._config_json())
|
||||
await self._send_to(websocket, "HISTORY:" + json.dumps(list(self.samples)[-HISTORY_LIMIT:]))
|
||||
await self._send_to(websocket, "TEL_HISTORY:" + json.dumps(list(self.tel_samples)[-HISTORY_LIMIT:]))
|
||||
await self._send_to(websocket, "POS:%d:%d" % (self.last_pos_x, self.last_pos_y))
|
||||
if self.esp32_firmware_version:
|
||||
await self._send_to(websocket, "FW:" + self.esp32_firmware_version)
|
||||
await self._send_to(websocket, "OTA_STATE:" + json.dumps(self._ota_payload()))
|
||||
|
||||
today = f"log_{get_local_now():%Y-%m-%d}.txt"
|
||||
base = LOGS_DIR if self.device_id is None else os.path.join(LOGS_DIR, self.device_id)
|
||||
path = os.path.join(base, today)
|
||||
if os.path.exists(path):
|
||||
with open(path, "rb") as f:
|
||||
f.seek(max(0, os.path.getsize(path) - 655360))
|
||||
tail = "".join(f.read().decode("utf-8", errors="replace").splitlines(keepends=True)[-40:])
|
||||
if tail:
|
||||
await self._send_to(websocket, "LOG:" + tail)
|
||||
except Exception as e:
|
||||
log.error("connect_client_error", extra={"event": "connect_client_error",
|
||||
"device_id": self.device_id,
|
||||
"error_type": type(e).__name__})
|
||||
|
||||
def disconnect_client(self, websocket):
|
||||
if websocket in self.client_sockets:
|
||||
self.client_sockets.remove(websocket)
|
||||
|
||||
async def _send_to(self, client, msg: str):
|
||||
"""Envío acotado por timeout: un navegador lento solo se corta a él."""
|
||||
try:
|
||||
await asyncio.wait_for(client.send_text(msg), timeout=BROADCAST_TIMEOUT)
|
||||
except Exception:
|
||||
self.disconnect_client(client)
|
||||
try:
|
||||
await asyncio.wait_for(client.close(code=1001), timeout=BROADCAST_TIMEOUT)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
async def _broadcast(self, msg):
|
||||
await asyncio.gather(*(self._send_to(c, msg) for c in list(self.client_sockets)))
|
||||
|
||||
async def broadcast_status(self):
|
||||
await self._broadcast("STATUS:%s" % ("ONLINE" if self.esp32_connected else "OFFLINE"))
|
||||
|
||||
async def send_command_to_esp32(self, command: str, expected_connection=None) -> bool:
|
||||
"""Envía al socket ACTUAL de esta tarjeta; escrituras serializadas.
|
||||
Sin ACK del firmware solo existe estado 'enviado', no 'ejecutado'."""
|
||||
if not (self.esp32_socket and self.esp32_connected):
|
||||
return False
|
||||
async with self._send_lock:
|
||||
sock = self.esp32_socket
|
||||
connection_id = self.connection_id
|
||||
if (sock is None or not self.esp32_connected
|
||||
or (expected_connection is not None and expected_connection != connection_id)):
|
||||
return False
|
||||
if self._store is not None and (self.authorize_session is None or not self.authorize_session()):
|
||||
return False
|
||||
try:
|
||||
await asyncio.wait_for(sock.send_text(command), timeout=BROADCAST_TIMEOUT)
|
||||
log.info("command_sent", extra={"event": "command_sent", "device_id": self.device_id,
|
||||
"connection_id": self.connection_id})
|
||||
return True
|
||||
except Exception as e:
|
||||
log.error("command_failed", extra={"event": "command_failed", "device_id": self.device_id,
|
||||
"error_type": type(e).__name__})
|
||||
self.disconnect_esp32(connection_id)
|
||||
await self.broadcast_status()
|
||||
await self.broadcast_ota()
|
||||
return False
|
||||
|
||||
# --------------------- calibración / PCB (persiste 1ro) ---------------------
|
||||
|
||||
def apply_calibration(self, mV_per_WM2=None, az_dev=None) -> dict:
|
||||
"""Valida, persiste (si hay store) y luego muta. Si la persistencia
|
||||
falla, el estado previo se conserva y se propaga el error."""
|
||||
new_pyrano, new_az = self.pyrano, self.azdev
|
||||
changed_pyrano = changed_az = False
|
||||
if mV_per_WM2 is not None:
|
||||
v = float(mV_per_WM2)
|
||||
if not math.isfinite(v) or v <= 0:
|
||||
raise ValueError("mV_per_WM2 debe ser finita y positiva")
|
||||
new_pyrano, changed_pyrano = v, True
|
||||
if az_dev is not None:
|
||||
v = float(az_dev)
|
||||
if not math.isfinite(v):
|
||||
raise ValueError("az_dev debe ser finita")
|
||||
new_az, changed_az = v, True
|
||||
if not (changed_pyrano or changed_az):
|
||||
return {"mV_per_WM2": self.pyrano, "az_dev": self.azdev}
|
||||
if self._store is not None:
|
||||
self._store.save_settings(self.device_id, pyrano=new_pyrano, az_dev=new_az)
|
||||
if changed_pyrano:
|
||||
self.pyrano = new_pyrano
|
||||
for pt in self.samples:
|
||||
if pt.get("p_raw") is not None:
|
||||
pt["gpoa"] = round(pt["p_raw"] / ADC_MAX * (VREF_MV / self.pyrano), 1)
|
||||
for pt in self.tel_samples:
|
||||
if pt.get("avg_p") is not None:
|
||||
pt["gpoa"] = round(pt["avg_p"] / ADC_MAX * (VREF_MV / self.pyrano), 1)
|
||||
if changed_az:
|
||||
self.azdev = new_az
|
||||
self._recompute_position()
|
||||
log.info("calibration_updated", extra={"event": "calibration_updated", "device_id": self.device_id,
|
||||
"result": {"pyrano": self.pyrano, "az_dev": self.azdev}})
|
||||
return {"mV_per_WM2": self.pyrano, "az_dev": self.azdev}
|
||||
|
||||
def set_pcb_version(self, version) -> bool:
|
||||
if not isinstance(version, str) or version not in PCB_VERSIONS:
|
||||
return False
|
||||
if self._store is not None:
|
||||
self._store.save_settings(self.device_id, pcb_version=version)
|
||||
self.pcb_version = version
|
||||
r = PCB_VERSIONS[version]
|
||||
for pt in self.samples:
|
||||
c = pt.get("c_raw")
|
||||
if c is None:
|
||||
continue
|
||||
isc = (c / ADC_MAX * (VREF_MV / GAIN_SHUNT)) / 1000.0 / r
|
||||
pt["isc_ma"] = round(isc * 1000, 2)
|
||||
if pt.get("voc") is not None:
|
||||
pt["pcpv_mw"] = round(pt["voc"] * isc * FF * 1000, 2)
|
||||
for pt in self.tel_samples:
|
||||
c = pt.get("avg_c")
|
||||
if c is None:
|
||||
continue
|
||||
isc = (c / ADC_MAX * (VREF_MV / GAIN_SHUNT)) / 1000.0 / r
|
||||
pt["isc_ma"] = round(isc * 1000, 2)
|
||||
if pt.get("voc") is not None:
|
||||
pt["pcpv_mw"] = round(pt["voc"] * isc * FF * 1000, 2)
|
||||
log.info("pcb_updated", extra={"event": "pcb_updated", "device_id": self.device_id,
|
||||
"result": version})
|
||||
return True
|
||||
|
||||
async def rebroadcast_config(self):
|
||||
await self._broadcast("CONFIG:" + self._config_json())
|
||||
await self._broadcast("HISTORY:" + json.dumps(list(self.samples)[-HISTORY_LIMIT:]))
|
||||
await self._broadcast("TEL_HISTORY:" + json.dumps(list(self.tel_samples)[-HISTORY_LIMIT:]))
|
||||
|
||||
# ------------------------------- OTA --------------------------------
|
||||
|
||||
def _ota_payload(self) -> dict:
|
||||
return {
|
||||
"device_id": self.device_id,
|
||||
"device": self.esp32_firmware_version, "available": self.ota_manifest,
|
||||
"auto": self.ota_auto_enabled, "url": self.ota_url, "connected": self.esp32_connected,
|
||||
}
|
||||
|
||||
async def broadcast_ota(self):
|
||||
await self._broadcast("OTA_STATE:" + json.dumps(self._ota_payload()))
|
||||
|
||||
async def set_ota_auto(self, enabled: bool):
|
||||
"""OTA automática POR TARJETA (default False; no se hereda de un
|
||||
estado global)."""
|
||||
if self._store is not None:
|
||||
self._store.save_settings(self.device_id, ota_auto=bool(enabled))
|
||||
self.ota_auto_enabled = bool(enabled)
|
||||
if not self.ota_auto_enabled and self._auto_task is not None:
|
||||
self._auto_task.cancel()
|
||||
self._auto_task = None
|
||||
await self.broadcast_ota()
|
||||
|
||||
async def push_ota(self, sha256: Optional[str] = None, expected_connection=None) -> bool:
|
||||
"""Push manual de OTA a ESTA tarjeta. Si se indica sha256, debe
|
||||
coincidir con el manifiesto actual (previene carreras de archivo)."""
|
||||
if not (self.esp32_connected and self.esp32_socket and self.ota_manifest and os.path.exists(FIRMWARE_BIN)):
|
||||
return False
|
||||
if sha256:
|
||||
cur = str(self.ota_manifest.get("sha256") or "").lower()
|
||||
if not cur or not _const_eq(str(sha256).lower(), cur):
|
||||
return False
|
||||
manifest = self.ota_manifest.copy()
|
||||
ok = await self.send_command_to_esp32("OTA:" + manifest["url"], expected_connection)
|
||||
if ok:
|
||||
await self._broadcast(
|
||||
f"LOG:[hub] Empujando firmware '{manifest.get('version', '?')}' a la ESP32 (enviado, no ejecutado)...\n"
|
||||
)
|
||||
return ok
|
||||
|
||||
def _maybe_auto_update(self):
|
||||
"""Flujo auto POR tarjeta, ligado a identidad Y sesión; se cancela al
|
||||
desconectar. La subida de artefacto NUNCA invoca esto."""
|
||||
try:
|
||||
if self._auto_task is not None:
|
||||
self._auto_task.cancel()
|
||||
self._auto_task = None
|
||||
if not self.ota_auto_enabled or not self.ota_manifest or not os.path.exists(FIRMWARE_BIN):
|
||||
return
|
||||
if not self.esp32_firmware_version or self._version_session_id != self.connection_id:
|
||||
return
|
||||
if self.esp32_firmware_version == self.ota_manifest.get("version"):
|
||||
return
|
||||
cid = self.connection_id
|
||||
sha = self.ota_manifest.get("sha256")
|
||||
version = self.ota_manifest.get("version")
|
||||
|
||||
async def _do():
|
||||
await asyncio.sleep(3)
|
||||
if (self.ota_auto_enabled and self.esp32_connected and cid is not None
|
||||
and self.connection_id == cid and self.esp32_firmware_version != version):
|
||||
await self.push_ota(sha, cid)
|
||||
|
||||
self._auto_task = asyncio.create_task(_do())
|
||||
except Exception as e:
|
||||
log.error("auto_update_error", extra={"event": "auto_update_error",
|
||||
"device_id": self.device_id,
|
||||
"error_type": type(e).__name__})
|
||||
|
||||
# --------------------------- persistencia ---------------------------
|
||||
|
||||
def _load_settings(self):
|
||||
s = self._store.get_settings(self.device_id)
|
||||
if s is None:
|
||||
raise ValueError("Missing registered device settings")
|
||||
if s["config_revision"] == self.config_revision:
|
||||
return
|
||||
self.pcb_version = s["pcb_version"]
|
||||
self.pyrano, self.azdev = s["pyrano"], s["az_dev"]
|
||||
self.ota_auto_enabled = s["ota_auto"]
|
||||
self.config_revision = s["config_revision"]
|
||||
for points, keys in ((self.samples, ("c_raw", "v_raw", "p_raw")),
|
||||
(self.tel_samples, ("avg_c", "avg_v", "avg_p"))):
|
||||
for point in points:
|
||||
g, v, i, p = self._units(point["x"], point["y"], *(point[k] for k in keys))
|
||||
point.update(gpoa=round(g, 1), voc=round(v, 3), isc_ma=round(i * 1000, 2), pcpv_mw=round(p * 1000, 2))
|
||||
self._recompute_position()
|
||||
|
||||
def _append_log(self, line: str):
|
||||
if not line:
|
||||
return
|
||||
fn = f"log_{get_local_now():%Y-%m-%d}.txt"
|
||||
base = LOGS_DIR if self.device_id is None else os.path.join(LOGS_DIR, self.device_id)
|
||||
try:
|
||||
os.makedirs(base, exist_ok=True)
|
||||
path = os.path.join(base, fn)
|
||||
content = (line + "\n").encode("utf-8")
|
||||
if (os.path.getsize(path) if os.path.exists(path) else 0) + len(content) > LOG_DAILY_MAX_BYTES:
|
||||
raise OSError("daily log quota")
|
||||
with open(path, "ab") as f:
|
||||
f.write(content)
|
||||
self.log_error = None
|
||||
except Exception as e:
|
||||
# Modo degradado visible: la ingesta continua, el log lo registra.
|
||||
self.log_error_count += 1
|
||||
self.log_error = type(e).__name__
|
||||
if self._log_error_day == fn:
|
||||
return
|
||||
self._log_error_day = fn
|
||||
log.error("log_write_failed", extra={"event": "log_write_failed",
|
||||
"device_id": self.device_id,
|
||||
"error_type": type(e).__name__})
|
||||
|
||||
def status_payload(self, alias: Optional[str] = None) -> dict:
|
||||
return {
|
||||
"device_id": self.device_id,
|
||||
"alias": alias,
|
||||
"esp32_connected": self.esp32_connected,
|
||||
"connected_at": self.connected_at.isoformat() if self.connected_at else None,
|
||||
"last_seen": self.last_seen.isoformat() if self.last_seen else None,
|
||||
"last_telemetry_at": self.last_telemetry_at.isoformat() if self.last_telemetry_at else None,
|
||||
"connection_id": self.connection_id,
|
||||
"pos_x": self.last_pos_x, "pos_y": self.last_pos_y,
|
||||
"pyrano_mV_per_Wm2": self.pyrano, "az_dev_deg": self.azdev,
|
||||
"pcb_version": self.pcb_version,
|
||||
"active_clients": len(self.client_sockets),
|
||||
"samples_in_buffer": len(self.samples),
|
||||
"tel_samples_in_buffer": len(self.tel_samples),
|
||||
"firmware_device": self.esp32_firmware_version,
|
||||
"log_degraded": self.log_error is not None,
|
||||
"log_error_count": self.log_error_count,
|
||||
"ota": self._ota_payload(),
|
||||
}
|
||||
|
||||
|
||||
def _const_eq(a: str, b: str) -> bool:
|
||||
import hmac
|
||||
return hmac.compare_digest(a, b)
|
||||
|
||||
|
||||
# Nota: HubManager() sigue siendo constructible standalone (sin argumentos,
|
||||
# sin SQLite ni I/O de estado global) para pruebas efímeras. No hay
|
||||
# singleton global: cada proceso/instancia gestiona sus propias tarjetas.
|
||||
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