Initial import of Microtracking project

plot_codigonuevo.py

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+import pandas as pd
+import numpy as np
+
+# --- Tablita que pasaste ---
+data = [
+    ("10:30",115.09,52.37),
+    ("10:45",118.65,55.47),
+    ("11:00",122.79,58.46),
+    ("11:15",127.65,61.3),
+    ("11:30",133.43,63.95),
+    ("11:45",140.31,66.33),
+    ("12:00",148.5,68.35),
+    ("12:15",158.07,69.92),
+    ("12:30",168.86,70.91),
+    ("12:45",180.37,71.23),
+    ("13:00",191.86,70.86),
+    ("13:15",202.57,69.82),
+    ("13:30",212.03,68.21),
+    ("13:45",220.12,66.16),
+    ("14:00",226.91,63.76),
+    ("14:15",232.61,61.09),
+    ("14:30",237.41,58.24),
+    ("14:45",241.5,55.24),
+    ("15:00",245.02,52.13),
+]
+df = pd.DataFrame(data, columns=["Hora","Az","Alt"])
+
+# --- Parámetros del tracker ---
+TILT = 23.2          # inclinación en grados
+AZ_REAL = 182.0      # orientación real del módulo (ej. 2° al SE)
+AZ_OFFSET = 26720.0
+AZ_SCALE = 605.3
+ZENITH_MAX_STEPS = 51500.0
+ZENITH_SCALE = 820.0
+
+# --- Funciones auxiliares ---
+def deg2rad(d): return d*np.pi/180
+def rad2deg(r): return r*180/np.pi
+
+def sun_to_panel_angles(az, alt, tilt, az_real):
+    # Vector solar global (ENU)
+    sx = np.cos(deg2rad(alt)) * np.sin(deg2rad(az))
+    sy = np.cos(deg2rad(alt)) * np.cos(deg2rad(az))
+    sz = np.sin(deg2rad(alt))
+
+    # Rotación Z(-AZ_REAL)
+    pr = deg2rad(az_real)
+    x1 =  np.cos(pr)*sx + np.sin(pr)*sy
+    y1 = -np.sin(pr)*sx + np.cos(pr)*sy
+    z1 =  sz
+
+    # Rotación X(-TILT)
+    tr = deg2rad(tilt)
+    x2 = x1
+    y2 =  np.cos(tr)*y1 + np.sin(tr)*z1
+    z2 = -np.sin(tr)*y1 + np.cos(tr)*z1
+
+    phi_local = (rad2deg(np.arctan2(x2, y2)) + 360) % 360
+    alt_local = rad2deg(np.arctan2(z2, np.sqrt(x2**2 + y2**2)))
+    return phi_local, alt_local
+
+# --- Calcular pasos ---
+X_fit, Y_fit = [], []
+for _, row in df.iterrows():
+    phi, altp = sun_to_panel_angles(row["Az"], row["Alt"], TILT, AZ_REAL)
+    zenp = 90 - altp
+    y_steps = -(AZ_OFFSET + phi*AZ_SCALE)
+    x_steps = -(ZENITH_MAX_STEPS - zenp*ZENITH_SCALE)
+    X_fit.append(x_steps)
+    Y_fit.append(y_steps)
+
+df["X_fit"] = np.round(X_fit).astype(int)
+df["Y_fit"] = np.round(Y_fit).astype(int)
+
+print(df)