Changeset 793 in ETALON

Timestamp:

Aug 7, 2018, 11:20:09 AM (6 years ago)

Author:

delerue

Message:

Minor bugs corrected

File:

• BPM/print_datas.py (modified) (5 diffs)

BPM/print_datas.py

@@ -265 +265 @@
         plt.errorbar(X,Y,yerr = rms, ecolor = color)
     if not(lin_reg is None):
-        lr1 = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
+        slope, intercept, r_value, p_value, std_err = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
         if legende is None:
-            plt.plot(X,[lr1.slope*i + lr1.intercept for i in X], color+"--", label =  " regression lineaire, \nerreur = "+str(round(lr1.stderr,3))+",\ncoefficient de correlation = "+str(round(lr1.rvalue,3)) + "\npente de la regression lineaire = " + str(round(lr1.slope,3)))
+            plt.plot(X,[slope*i + intercept for i in X], color+"--", label =  " regression lineaire, \nerreur = "+str(round(std_err,3))+",\ncoefficient de correlation = "+str(round(r_value,3)) + "\npente de la regression lineaire = " + str(round(slope,3)))
         else:
-            plt.plot(X,[lr1.slope*i + lr1.intercept for i in X], color+"--", label = legende + " : regression lineaire, \nerreur = "+str(round(lr1.stderr,3))+",\ncoefficient de correlation  = "+str(round(lr1.rvalue,3))+ "\npente de la regression lineaire = " + str(round(lr1.slope,3)))
-            plt.legend(fontsize=15)
+            plt.plot(X,[slope*i + intercept for i in X], color+"--", label = legende + " : regression lineaire, \nerreur = "+str(round(std_err,3))+",\ncoefficient de correlation  = "+str(round(r_value,3))+ "\npente de la regression lineaire = " + str(round(slope,3)))            
+    plt.legend(fontsize=15)
     x_label = plot_legend_fr(x_data_name)
     y_label = plot_legend_fr(y_data_name)
@@ -356 +356 @@
         plt.errorbar(X,Y,yerr = rms, ecolor = color)
     if not(lin_reg is None):
-        lr1 = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
+        slope, intercept, r_value, p_value, std_err = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
         if legende is None:
-            plt.plot(X,[lr1.slope*i + lr1.intercept for i in X], color+"--", label =  "linear regression, \nerror = "+str(round(lr1.stderr,3))+",\ncorrelation coefficient = "+str(round(lr1.rvalue,3)) + "\nslope = " + str(round(lr1.slope,3)))
+            plt.plot(X,[slope*i + intercept for i in X], color+"--", label =  "linear regression, \nerror = "+str(round(std_err,3))+",\ncorrelation coefficient = "+str(round(r_value,3)) + "\nslope = " + str(round(slope,3)))
         else:
-            plt.plot(X,[lr1.slope*i + lr1.intercept for i in X], color+"--", label = legende + " : lineare regression, \nerror = "+str(round(lr1.stderr,3))+",\ncorrelation coefficient = "+str(round(lr1.rvalue,3))+ "\nslope = " + str(round(lr1.slope,3)))
+            plt.plot(X,[slope*i + intercept for i in X], color+"--", label = legende + " : lineare regression, \nerror = "+str(round(std_err,3))+",\ncorrelation coefficient = "+str(round(r_value,3))+ "\nslope = " + str(round(slope,3)))
             plt.legend(fontsize=15)
     x_label = plot_legend(x_data_name)
@@ -394 +394 @@
     if y_data_name == "x_motor_step" or y_data_name == "y_motor_step":
         Y = [i[y_data_number]/1000000. for i in data]
-    lr1 = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
+    slope, intercept, r_value, p_value, std_err  = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
     for index in range(len(Y)):
-        Y[index] = abs(Y[index] - (lr1.slope*X[index] + lr1.intercept))
+        Y[index] = abs(Y[index] - (slope*X[index] + intercept))
     if legende is None:
         plt.plot(X,Y, color+".")
@@ -441 +441 @@
     if y_data_name == "x_motor_step" or y_data_name == "y_motor_step":
         Y = [i[y_data_number]/1000000. for i in data]
-    lr1 = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
+    slope, intercept, r_value, p_value, std_err = stats.linregress(X,Y) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
     moyenne = 0
     len_Y = len(Y)
     for index in range(len_Y):
-        Y[index] = abs(Y[index] - (lr1.slope*X[index] + lr1.intercept))
+        Y[index] = abs(Y[index] - (slope*X[index] + intercept))
         moyenne += Y[index]/len_Y
     if legende is None:
@@ -570 +570 @@
 
 #graph_fr("/Users/delerue/Downloads/BPM_data/bpm_name_bpm_number_x_motor_step_x_motor_mm_y_motor_step_y_motor_mm_Va_Vb_Vc_Vd_Sum_x_libera_mm_y_libera_mm_test_decrochage_BPM0-E_BPM1-impr_BPM2-C_High_Stat_20180803_2.txt", "y_motor_step", "y_libera_mm",lin_reg = "true", residu = "yes", rms = "yes")#, centrage = "yes", y_minimal = -20., y_maximal = -10.)
-graph_fr("/Users/delerue/Downloads/BPM_data/bpm_name_bpm_number_x_motor_step_x_motor_mm_y_motor_step_y_motor_mm_Va_Vb_Vc_Vd_Sum_x_libera_mm_y_libera_mm_test_decrochage_BPM0-E_BPM1-impr_BPM2-C_High_Stat_20180803_2.txt", "y_motor_step", "y_libera_mm",lin_reg = None, residu = None, rms = "yes" )#, centrage = "yes", y_minimal = -20., y_maximal = -10.)
+graph_fr("/Users/delerue/Downloads/BPM_data/bpm_name_bpm_number_x_motor_step_x_motor_mm_y_motor_step_y_motor_mm_Va_Vb_Vc_Vd_Sum_x_libera_mm_y_libera_mm_test_decrochage_BPM0-E_BPM1-impr_BPM2-C_High_Stat_20180803_2.txt", "y_motor_step", "y_libera_mm",lin_reg = "yes", residu = "yes", rms = "yes" )#, centrage = "yes", y_minimal = -20., y_maximal = -10.)
 
 #graph_fr("data/bpm_name_bpm_number_x_motor_step_x_motor_mm_y_motor_step_y_motor_mm_Va_Vb_Vc_Vd_Sum_x_libera_mm_y_libera_mm_BPM0-E_BPM1-impr_BPM2-C_3pts-horizontal_100pts-vertical_20180802_0.txt", "y_motor_mm", "Va", residu = "yes", centrage = "yes", one_bpm = "BPM_E")#, rms = "yes")