.

analisis/plots/20250421_fluorescencorrelation/FluoCorrForCompensation.py

@@ -54,8 +54,8 @@ taurf = 1/freqrf
 meds = [20889, 20890, 20891, 20892, 20893, 20894, 20895, 20896, 20897, 20898, 20899, 20900, 20901, 20903, 20904 , 20905 , 20906, 20907, 20908, 20909, 20910, 20911]
 Vdouble =  [0, 10, 20, 40, 50, 50, 55, 55, 55, 60, 65, 70, 75, 80, 85, 90,100, 110, 130, 150, 170, 190]
 
-
-
+meds = [20871, 20872, 20873, 20874, 20875]
+Vdouble = [-10, -30, -50, -70, -90, -120]
 y_mean_values = []
 y_max_of_norm_values = []
 y_max = []
@@ -67,7 +67,7 @@ amp_fitted = []
 amp_fitted_err = []
 offset_fitted = []
 
-meds = [meds[-1]]
+# meds = [meds[-1]]
 for i, med in enumerate(meds):
     #print(i)
 
@@ -76,7 +76,7 @@ for i, med in enumerate(meds):
     
     x_data = dropnan(np.array(data['datasets']['x_data']))
     y_data = dropnan(np.array(data['datasets']['y_data']))
-    y_data_2 = dropnan(np.array(data['datasets']['y_data_2']))
+    #y_data_2 = dropnan(np.array(data['datasets']['y_data_2']))
     
     """
     Grafico temporal replicado 3 veces a la frecuencia dada
@@ -111,7 +111,8 @@ for i, med in enumerate(meds):
 
 plt.figure(2), plt.clf()
 plt.errorbar(Vdouble_fitted, np.abs(amp_fitted),fmt = '.', yerr=amp_fitted_err)
-
+plt.xlabel("V double")
+plt.ylabel("Amplitud del fit")