Changeset 789 in ETALON

Timestamp:

Aug 2, 2018, 7:53:23 PM (6 years ago)

Author:

moutardier

Message:

big modification of print_datas.py

File:

• BPM/print_datas.py (modified) (3 diffs)

BPM/print_datas.py

@@ -2 +2 @@
 import matplotlib.pyplot as plt
 from scipy import stats
+import math
+from io import BytesIO
 
 
 global_index_figure = 0
 
-def float_list(l): # convert a list of char in a list of float 
+def float_list(l, avoid = []): # convert a list of char in a list of float, and it avoid all data in the list of index that must be avoid
     L = []
-    for i in l:
-        L.append(float(i))
+    for i in range(len(l)):
+        if i in avoid:
+            L.append(l[i])
+        else:
+            L.append(float(l[i]))
     return(L)
 
@@ -15 +20 @@
     Lx = []
     for i in L:
-        Lx.append(i*x +b)
+        Lx.append(i*x +b)   
     return(Lx)
 
-def read_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(fichier): # program to read data from a file of data with position of motor and them Va, Vb, Vc and Vd
-    fichier = open(fichier, "r")
-    Data = fichier.read()
-    Data_list = [[[] for i in range(9)] for j in range(3)]
-    value = ""
-    index = -1
-    for i in Data:
-        if (i == " ") :
-            if index == -1: 
-                bpm_index = int(value)
-                index +=1
-            else:
-                Data_list[bpm_index][index].append(value)
-                index += 1
-            value = ""
-        elif (i == "\n") :
-            if value != "":
-                Data_list[bpm_index][index].append(value)
-                value = ""
-            index = -1
-        else:
-            value += i
-    fichier.close()
-    for bpm in Data_list:
-        for i in range(len(bpm)):
-            bpm[i] = float_list(bpm[i])
-    return(Data_list)
+
+#print(read_first_line("data/test.txt"))
+
+"""    #other way to read data (without data of type different than float)
+def read_data(fichier): # program to read data from a file of data with position of motor and them Va, Vb, Vc and Vd
+    list_data_name = read_first_line(fichier) #create a list of the name of the data in the file
+    data = np.genfromtxt(fichier, delimiter=",", dtype="|U5", autostrip=True)# np.genfromtxt('data/test.txt', delimiter=' ', skip_header = 1) ### can't be use with other thiks than number
+    return(list_data_name,data)
 """
 
-        bpm[0] = product_list(Data_list[0],10**-6)
-
-    for i in range(1,5):
-        Data_list[i] = product_list(Data_list[i],1000)
+def read_line(line): # allow to read one line of the files
+    data_name = ""
+    list_data = []
+    for data_car in line:
+        if (data_car == " ") or (data_car == "\n"):
+            if data_name != "":
+                list_data.append(data_name)
+            data_name = ""
+        else:
+            data_name += data_car
+    return(list_data)
+
+def read_data(fichier): # program to read data from a file of data 
+    data = open(fichier, 'r')
+    data_list = []
+    for line in data:
+        #print(line)
+        data_list.append(read_line(line))
+    data.close()
+    return(data_list[0],data_list[1:])
+
+def number_of_data_name(list_data_name, data_name): # give the number of a data in list_data_name with the name data_name
+    name_number = float('nan')
+    for number in range(len(list_data_name)):
+        if data_name == list_data_name[number]:
+            name_number = number
+    return(name_number)
+
+def convert_data(list_data_name, data): # convert data from string to int 
+    data_avoid = number_of_data_name(list_data_name, "bpm_name") # all other data are string of float and must be convert in float
+    float_data = []
+    for sub_data in data:
+        float_data.append(float_list(sub_data, avoid = [data_avoid]))
+    return(float_data)
+
+def min_max(list_data_name, data, data_name):
+    number_data_name = number_of_data_name(list_data_name, data_name)
+    mini = data[0][number_data_name]
+    maxi = data[0][number_data_name]
+    for i in data:
+        if mini > i[number_data_name]:
+            mini = i[number_data_name]
+        if maxi < i[number_data_name]:
+            maxi = i[number_data_name]
+    return(mini,maxi)
+    
+#(list_data_name,data) = read_data("data/test.txt")
+#print(list_data_name)
+#print()
+#print(convert_data(list_data_name,data ))
+
+def all_value_of_data(list_data_name, data, data_name, data_name2 = None): #return a list that contain all different value that take data_name in data, data_name2 is to avoid 2 read of data for taken twice the same thing (used in moy_rms_data)
+    data_number = number_of_data_name(list_data_name, data_name)
+    #print(data_number)
+    all_data_name = []
+    if data_name2 is None:
+        for data_list in data:
+            #print(data_number)
+            #print(data_name)
+            #print(type(data_number))
+            if not(data_list[data_number] in all_data_name):
+                all_data_name.append(data_list[data_number])
+        return(all_data_name)
+    else:
+        data_number2 = number_of_data_name(list_data_name, data_name2)
+        all_data_name2 = []
+        for data_list in data:
+            if not(data_list[data_number] in all_data_name):
+                all_data_name.append(data_list[data_number])
+            if not(data_list[data_number2] in all_data_name2):
+                all_data_name2.append(data_list[data_number2])
+        return(all_data_name,all_data_name2)
+    
+#(list_data_name,data) = read_data("data/test.txt")    
+#print(all_value_of_data(list_data_name, data, "bpm_name", data_name2 = None))
+
+def cut_data(list_data_name, data, data_name, inf = None, equal = None, sup = None): # return list of data with were there is a contrain on the data name "data_name"
+    data_number = number_of_data_name(list_data_name, data_name)
+    list_of_keep_data = []
+    if data_number ==  float('nan'):
+        print("ERREUR in the name of cut data ")
+    elif not (inf is None):
+        if not (equal is None):
+            for value in range(len(data)):
+                if data[value][data_number] < inf or data[value][data_number] == equal:
+                    list_of_keep_data.append(value)
+        else:
+            for value in range(len(data)):
+                if data[value][data_number] < inf:
+                    list_of_keep_data.append(value)
+    elif not (sup is None):
+        if not (equal is None):
+            for value in range(len(data)):
+                if data[value][data_number] > sup or data[value][data_number] == equal:
+                    list_of_keep_data.append(value)
+        else:
+            for value in range(len(data)):
+                if data[value][data_number] > sup:
+                    list_of_keep_data.append(value)
+    elif not (equal is None):
+        for value in range(len(data)):
+            if data[value][data_number] == equal:
+                list_of_keep_data.append(value)
+    else:
+        return(data)
+    return([data[value] for value in list_of_keep_data])
+
+
+#def select_data(list_data_name, data, data_name1, data_name2, data_name3, data_name4)
+
+#def print_graph(list_data_name
+
+    
+#(list_data_name,data) = read_data("data/test.txt")
+#print(data)
+#print(cut_data(list_data_name, data, "bpm_name",equal = "bpm_E"))
+
+def moy_rms(list_data_name, data,data_name):
+    number_data_name = number_of_data_name(list_data_name, data_name)
+    moy = 0
+    rms = 0
+    data_len = float(len(data))
+    for data_list in data:
+        moy += data_list[number_data_name]/data_len
+    for data_list in data:
+        rms += (data_list[number_data_name] - moy)*(data_list[number_data_name] - moy)/data_len
+    return(moy,np.sqrt(rms))
+
+
+def moy_rms_data(list_data_name, data, x_data_name, y_data_name):
+    x_number_data_name = number_of_data_name(list_data_name, x_data_name)
+    moy_list = []
+    rms_list = []
+    X = []
+    if "bpm_name" in list_data_name:
+        bpm_number = number_of_data_name(list_data_name, "bpm_name")
+        all_bpm_name, all_x_data_name = all_value_of_data(list_data_name, data, data_name = "bpm_name", data_name2 = x_data_name)
+        for bpm_name in all_bpm_name:
+            cut_dat = cut_data(list_data_name, data, "bpm_name", equal = bpm_name)
+            for name in all_x_data_name:
+                moy,rms = moy_rms(list_data_name, cut_data(list_data_name, cut_dat, x_data_name, equal = name), y_data_name)
+                moy_list.append(moy)
+                rms_list.append(rms)
+                X.append(name)
+    else:
+        all_data_name = all_value_of_data(list_data_name, data, data_name = x_data_name)
+        for name in all_data_name:
+            moy,rms = moy_rms(list_data_name, cut_data(list_data_name, cut_data, x_data_name, equal = name), y_data_name)
+            moy_list.append(moy)
+            rms_list.append(rms)
+            X.append(name)
+    return(X,moy_list,rms_list)
+
+
+def linear_fonction_on_data(list_data_name, data, data_name, begin_mm = None, end_mm = None): # convert the data name data_name (use to length convertion) 
+    number_data_name = number_of_data_name(list_data_name, data_name)
+    begin_step,end_step = min_max(list_data_name, data, data_name)
+    if begin_mm is None:
+        begin_mm = begin_step
+    if end_mm is None:
+        end_mm = end_step
+    if end_step == begin_step:
+        return(data)
+    a = float((end_mm - begin_mm))/(end_step - begin_step)
+    b = begin_mm - a*begin_step
+    #print(a,b)
+    for index in range(len(data)):
+        data[index][number_data_name] = a*data[index][number_data_name] + b
+    return(data)
+
+
+def plot_legend_fr(data_name): # return the legende in french for a graph according to the data read
+    if data_name == "bpm_name" :
+        return("Nom du BPM")
+    elif data_name == "bpm_number" :
+        return("Numero du BPM")
+    elif data_name == "x_motor_step" :
+        return("Coordonnee x d'apres le moteur (en million de pas)")
+    elif data_name == "x_motor_mm" :
+        return("Coordonnee x d'apres le moteur (en mm)")
+    elif data_name == "y_motor_step" :
+        return("Coordonnee y d'apres le moteur (en en million pas)")
+    elif data_name == "y_motor_mm" :
+        return("Coordonnee y d'apres le moteur (en mm)")
+    elif data_name == "Va" :
+        return("Tension sur l'electrode a (en mV)")
+    elif data_name == "Vb" :
+        return("Tension sur l'electrode b (en mV)")
+    elif data_name == "Vc" :
+        return("Tension sur l'electrode c (en mV)")
+    elif data_name == "Vd" :
+        return("Tension sur l'electrode d (en mV)")
+    elif data_name == "Sum": 
+        return("Somme des tensions sur les electrodes (en mV)")
+    elif data_name == "x_libera_mm" :
+        return("Coordonnee x d'apres le Libera (en mm)")
+    elif data_name == "y_libera_mm" :
+        return("Coordonnee x d'apres le Libera (en mm)")
+    else:
+        print("unknow ask data_name named " + data_name)
+        return("Inconnue")
+
+
+
+def print_graph_fr(list_data_name, data, x_data_name, y_data_name, index_figure, color = "r",title = None, legende = None, lin_reg = None, rms = None, centrage = None): # program to print graph of y_data_name vs x_data_name in french
+    fig1 = plt.figure(index_figure)
+    if not(centrage is None):
+        mini,maxi =  min_max(list_data_name, data, x_data_name)
+        data = linear_fonction_on_data(list_data_name, data, x_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+        mini,maxi =  min_max(list_data_name, data, y_data_name)
+        data = linear_fonction_on_data(list_data_name, data, y_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+    if rms is None:
+        x_data_number = number_of_data_name(list_data_name, x_data_name)
+        X = [i[x_data_number] for i in data]
+        y_data_number = number_of_data_name(list_data_name, y_data_name)
+        Y = [i[y_data_number] for i in data]
+        rms = [0 for i in data]
+    else:
+        X,Y,rms = moy_rms_data(list_data_name, data, x_data_name, y_data_name)
+    if (x_data_name == "x_motor_step") or (x_data_name == "y_motor_step"):
+        X = [i/1000000. for i in X]
+    if y_data_name == "x_motor_step" or y_data_name == "y_motor_step":
+        Y = [i[y_data_number]/1000000. for i in data]
+    if legende is None:
+        plt.plot(X,Y, color+".")
+        plt.errorbar(X,Y,yerr = rms, ecolor = color)
+    else:
+        plt.plot(X,Y, color+".", label = legende)
+        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)
+        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)))
+        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)
+    x_label = plot_legend_fr(x_data_name)
+    y_label = plot_legend_fr(y_data_name)
+    plt.xlabel(x_label, fontsize=20)
+    plt.ylabel(y_label, fontsize=20)
+    if title is None:
+        plt.title(y_label + " en fonction de " + x_label, fontsize=20)
+    else:
+        plt.title(title, fontsize=20)
+    plt.gca().xaxis.set_tick_params(labelsize = 15)
+    plt.gca().yaxis.set_tick_params(labelsize = 15)
+
+    
+
+#(list_data_name,data) = read_data("data/test.txt")
+#data = convert_data(list_data_name, data)
+#print_graph_fr(list_data_name, data, "x_motor_mm", "x_motor_step", 1, color = "r", legende = "BPM_C", lin_reg = "true")
+
+#print_graph_fr(list_data_name, data, "x_motor_mm", "x_motor_step", 1, color = "b", legende = "BPM_C", lin_reg = "true")
+
+
+
+
+
+def plot_legend(data_name): # return the legende in english for a graph according to the data read
+    if data_name == "bpm_name" :
+        return("BPM name")
+    elif data_name == "bpm_number" :
+        return("BPM number")
+    elif data_name == "x_motor_step" :
+        return("x coordinate acording to motor (in step)")
+    elif data_name == "x_motor_mm" :
+        return("x coordinate acording to motor (in mm)")
+    elif data_name == "y_motor_step" :
+        return("y coordinate acording to motor (in step)")
+    elif data_name == "y_motor_mm" :
+        return("y coordinate acording to motor (in mm)")
+    elif data_name == "Va" :
+        return("Tension on electrode a (in mV)")
+    elif data_name == "Vb" :
+        return("Tension on electrode b (in mV)")
+    elif data_name == "Vc" :
+        return("Tension on electrode c (in mV)")
+    elif data_name == "Vd" :
+        return("Tension on electrode d (in mV)")
+    elif data_name == "Sum": 
+        return("Sum of tensions on electrodes (in mV)")
+    elif data_name == "x_libera_mm" :
+        return("x coordinate acording d'apres le Libera (in mm)")
+    elif data_name == "y_libera_mm" :
+        return("Coordonnee x d'apres le Libera (en mm)")
+    elif data_name == "x_libera_um" :
+        return("x coordinate acording d'apres le Libera (in um)")
+    elif data_name == "y_libera_um" :
+        return("Coordonnee x d'apres le Libera (en um)")
+    else:
+        print("unknow ask data_name named " + data_name)
+        return("Inconnue")
+
+    
+def print_graph(list_data_name, data, x_data_name, y_data_name, index_figure, color = "r",title = None, legende = None, lin_reg = None, rms = None, centrage = None):  # program to print graph of y_data_name vs x_data_name in english
+    if not(centrage is None):
+        mini,maxi =  min_max(list_data_name, data, x_data_name)
+        data = linear_fonction_on_data(list_data_name, data, x_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+        mini,maxi =  min_max(list_data_name, data, y_data_name)
+        data = linear_fonction_on_data(list_data_name, data, y_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+    fig1 = plt.figure(index_figure)
+    if rms is None:
+        x_data_number = number_of_data_name(list_data_name, x_data_name)
+        X = [i[x_data_number] for i in data]
+        y_data_number = number_of_data_name(list_data_name, y_data_name)
+        Y = [i[y_data_number] for i in data]
+        rms = [0 for i in data]
+    else:
+        X,Y,rms = moy_rms_data(list_data_name, data, x_data_name, y_data_name)
+    if (x_data_name == "x_motor_step") or (x_data_name == "y_motor_step"):
+        X = [i/1000000. for i in X]
+    if y_data_name == "x_motor_step" or y_data_name == "y_motor_step":
+        Y = [i[y_data_number]/1000000. for i in data]
+    if legende is None:
+        plt.plot(X,Y, color+".")
+        plt.errorbar(X,Y,yerr = rms, ecolor = color)
+    else:
+        plt.plot(X,Y, color+".", label = legende)
+        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)
+        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)))
+        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.legend(fontsize=15)
+    x_label = plot_legend(x_data_name)
+    y_label = plot_legend(y_data_name)
+    plt.xlabel(x_label, fontsize=20)
+    plt.ylabel(y_label, fontsize=20)
+    if title is None:
+        plt.title(y_label + " in fonction of " + x_label, fontsize=20)
+    else:
+        plt.title(title, fontsize=20)
+    plt.gca().xaxis.set_tick_params(labelsize = 15)
+    plt.gca().yaxis.set_tick_params(labelsize = 15)
+
+
+    
+def print_residu(list_data_name, data, x_data_name, y_data_name, index_figure, color = "r", legende = None , title = None, rms = None, centrage = None):  # program to print graph of residu of y_data_name vs x_data_name in english
+    if not(centrage is None):
+        mini,maxi =  min_max(list_data_name, data, x_data_name)
+        data = linear_fonction_on_data(list_data_name, data, x_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+        mini,maxi =  min_max(list_data_name, data, y_data_name)
+        data = linear_fonction_on_data(list_data_name, data, y_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+    fig1 = plt.figure(index_figure)
+    if rms is None:
+        x_data_number = number_of_data_name(list_data_name, x_data_name)
+        X = [i[x_data_number] for i in data]
+        y_data_number = number_of_data_name(list_data_name, y_data_name)
+        Y = [i[y_data_number] for i in data]
+        rms = [0 for i in data]
+    else:
+        X,Y,rms = moy_rms_data(list_data_name, data, x_data_name, y_data_name)
+    if (x_data_name == "x_motor_step") or (x_data_name == "y_motor_step"):
+        X = [i/1000000. for i in X]
+    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)
+    for index in range(len(Y)):
+        Y[index] = abs(Y[index] - (lr1.slope*X[index] + lr1.intercept))
+    if legende is None:
+        plt.plot(X,Y, color+".")
+    else:
+        plt.plot(X,Y, color+".", label = legende)
+    plt.legend(fontsize=15)
+    x_label = plot_legend(x_data_name)
+    y_label = plot_legend(y_data_name)
+    plt.xlabel(x_label, fontsize=20)
+    plt.ylabel(y_label, fontsize=20)
+    if title is None:
+        plt.title("Residu of " + y_label + " in fonction of " + x_label, fontsize=20)
+    else:
+        plt.title("Residu of " + y_label + " in fonction of " + x_label + "\n" +title, fontsize=20)
+    plt.gca().xaxis.set_tick_params(labelsize = 15)
+    plt.gca().yaxis.set_tick_params(labelsize = 15)
+
+
+
+#(list_data_name,data) = read_data("data/test.txt")
+#data = convert_data(list_data_name, data)
+#print_residu(list_data_name, data, "x_motor_mm", "x_motor_step", 1, color = "r", legende = "BPM_C")
+
+
+
+
+def print_residu_fr(list_data_name, data, x_data_name, y_data_name, index_figure, color = "r", legende = None, title = None, rms = None, centrage = None):  # program to print graph of residu of y_data_name vs x_data_name in french
+    if not(centrage is None):
+        mini,maxi =  min_max(list_data_name, data, x_data_name)
+        data = linear_fonction_on_data(list_data_name, data, x_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+        #mini,maxi =  min_max(list_data_name, data, y_data_name)
+        #data = linear_fonction_on_data(list_data_name, data, y_data_name, begin_mm = (mini - maxi)/2., end_mm = (maxi - mini)/2.)
+    fig1 = plt.figure(index_figure)
+    if rms is None:
+        x_data_number = number_of_data_name(list_data_name, x_data_name)
+        X = [i[x_data_number] for i in data]
+        y_data_number = number_of_data_name(list_data_name, y_data_name)
+        Y = [i[y_data_number] for i in data]
+        rms = [0 for i in data]
+    else:
+        X,Y,rms = moy_rms_data(list_data_name, data, x_data_name, y_data_name)
+    if (x_data_name == "x_motor_step") or (x_data_name == "y_motor_step"):
+        X = [i/1000000. for i in X]
+    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)
+    moyenne = 0
+    len_Y = len(Y)
+    for index in range(len_Y):
+        Y[index] = abs(Y[index] - (lr1.slope*X[index] + lr1.intercept))
+        moyenne += Y[index]/len_Y
+    if legende is None:
+        plt.plot(X,Y, color+".")
+    else:
+        plt.plot(X,Y, color+".", label = legende + " residu moyen = " + str(round(moyenne,4)))
+    plt.legend(fontsize=15)
+    x_label = plot_legend_fr(x_data_name)
+    y_label = plot_legend_fr(y_data_name)
+    plt.xlabel(x_label, fontsize=20)
+    plt.ylabel(y_label, fontsize=20)
+    if title is None:
+        plt.title("Residu de " + y_label + " en fonction de " + x_label, fontsize=20)
+    else:
+        plt.title("Residu de " + y_label + " en fonction de " + x_label + "\n" +title, fontsize=20)
+    plt.gca().xaxis.set_tick_params(labelsize = 15)
+    plt.gca().yaxis.set_tick_params(labelsize = 15)
+
+
 """
-
-
-def read_data_position_Va_Vb_Vc_Vd(fichier): # program to read data from a file of data with position of motor and them Va, Vb, Vc and Vd
-    fichier = open(fichier, "r")
-    Data = fichier.read()
-    Data_list = [[],[],[],[],[]]
-    value = ""
-    index = 0
-    for i in Data:
-        if (i == " ") :
-            if index == 0: 
-                Data_list[0].append(value)
-                index +=1
-            elif index == 1:
-                Data_list[1].append(value)
-                #print(value)
-                index += 1
-            elif index == 2:
-                Data_list[2].append(value)
-                index += 1
-            elif index == 3:
-                Data_list[3].append(value)
-                index += 1
-            else:
-                Data_list[4].append(value)
-                index = 0
-            value = ""
-        elif (i == "\n") :
-            value = ""
-        else:
-            value += i
-    fichier.close()
-    for i in range(5):
-        Data_list[i] = float_list(Data_list[i])
-    Data_list[0] = product_list(Data_list[0],10**-6)
-    for i in range(1,5):
-        Data_list[i] = product_list(Data_list[i],1000)
-    return(Data_list)
-
-
-
-
-
-def print_graph_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(data,lin_reg = None): # program to print graph of X_libera vs X_motor with a list data = [[[x_motor_position][y_motor_position][Va][Vb][Vc][Vd][sum][x_libera_position][y_libera_position]][same for BPM1][same for BPM2]],also do a linear regretion and print the equation
+(list_data_name,data) = read_data("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_100pts-horizontal_3pts-vertical_20180801_0.txt")
+data = convert_data(list_data_name, data)
+print_graph(list_data_name, data, "x_motor_step", "x_libera_mm",0, color = "r", legende = "BPM_C", lin_reg = "true")
+print_residu_fr(list_data_name, data, "x_motor_mm", "x_motor_step", 1, color = "r", legende = "BPM_C")
+"""
+
+
+
+
+
+
+
+
+"""
+
+(list_data_name,data) = read_data("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_100pts-horizontal_3pts-vertical_20180801_0.txt")
+data = convert_data(list_data_name, data)
+a,data = moy_rms_data(list_data_name, data, "x_motor_step", "x_libera_mm")
+#print(data)
+#print_graph(list_data_name, data, "x_motor_step", "x_libera_mm",0, color = "r", legende = "BPM_C", lin_reg = "true")
+#print_residu_fr(list_data_name, data, "x_motor_mm", "x_motor_step", 1, color = "r", legende = "BPM_C")
+"""
+
+def oposit_name(list_data_name, data_name):
+    if data_name[0] == "x":
+        if "y_motor_step" in list_data_name:
+            return("y_motor_step")
+    if data_name[0] == "y":
+        if "x_motor_step" in list_data_name:
+            return("x_motor_step")
+    else:
+        print("ERROR MULTIPLE LINE")
+        return("")
+
+
+
+def graph_fr(fichier, x_data_name, y_data_name, lin_reg = None, residu = None, rms = None, x_begin_mm = None, x_end_mm = None, y_begin_mm = None, y_end_mm = None, x_minimal = None, x_maximal = None, y_minimal = None,  y_maximal = None, centrage = None):
+    (list_data_name,data) = read_data(fichier)
+    data = convert_data(list_data_name, data)
     global global_index_figure # to creat different figure
-    fig1 = plt.figure(global_index_figure)
-    global_index_figure += 1
-    plt.clf()
-    color = ["r","g","b"]
-    legende = ["BPM soleil","BPM impr","BPM ref"]
-    for bpm_number in range(len(data)):
-        plt.plot(data[bpm_number][0],data[bpm_number][7], color[bpm_number]+".", label = legende[bpm_number])
-        if lin_reg == "yes":
-            lr1 = stats.linregress(data[bpm_number][0],data[bpm_number][7]) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
-            plt.plot(data[bpm_number][0],[lr1.slope*i + lr1.intercept for i in data[bpm_number][0]], color[bpm_number]+"--", label = legende[bpm_number] + " regression line, \nerror = "+str(round(lr1.stderr,3))+",\ncorrelation coefficient = "+str(round(lr1.rvalue,3)))
-    plt.legend()
-    plt.xlabel("length in million motor step") #, fontsize=20)
-    plt.ylabel("tension in mV")
-    plt.gca().yaxis.set_tick_params(labelsize = 8)
-    #plt.show(block = False)
-        
-
-
-
-def print_graph_position_Va_Vb_Vc_Vd(L): # program to print graph of X_libera vs X_motor with a list L = [[position][Va][Vb][Vc][Vd]], also do a linear regretion and print the equation
-    global global_index_figure # to creat different figure
-    fig1 = plt.figure(global_index_figure)
-    global_index_figure += 1
-    plt.clf()
-    
-    lr1 = stats.linregress(L[0],L[1]) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
-    plt.plot(L[0],L[1], "r", label = "BMP_ref")
-    plt.plot(L[0],[lr1.slope*i + lr1.intercept for i in L[0]], "r--", label = "BMP_ref regression line, \nerror = "+str(round(lr1.stderr,3))+",\ncorrelation coefficient = "+str(round(lr1.rvalue,3)))
-
-    lr2 = stats.linregress(L[0],L[2])
-    plt.plot(L[0],L[2], "b", label = "BMP_impr")
-    plt.plot(L[0],[lr2.slope*i + lr2.intercept for i in L[0]], "b--", label = "BMP_impr regression line, \nerror = "+str(round(lr2.stderr,3))+",\ncorrelation coefficient = "+str(round(lr2.rvalue,3)))
-
-    lr3 = stats.linregress(L[0],L[3])
-    plt.plot(L[0],L[3], "g", label = "BMP_ref")
-    plt.plot(L[0],[lr3.slope*i + lr3.intercept for i in L[0]], "g--", label = "BMP_ref regression line, \nerror = "+str(round(lr3.stderr,3))+",\ncorrelation coefficient = "+str(round(lr3.rvalue,3)))
-
-    lr4 = stats.linregress(L[0],L[4])
-    plt.plot(L[0],L[4], "m", label = "BMP_impr")
-    plt.plot(L[0],[lr4.slope*i + lr4.intercept for i in L[0]], "m--", label = "BMP_impr regression line, \nerror = "+str(round(lr4.stderr,2))+",\ncorrelation coefficient = "+str(round(lr4.rvalue,3)))
-    
-    plt.legend()
-    plt.xlabel("length in million motor step") #, fontsize=20)
-    plt.ylabel("tension in mV")
-    plt.gca().yaxis.set_tick_params(labelsize = 8)
-    #plt.show(block = False)
-
-    #    plt.show()
-
-def residu_position_Va_Vb_Vc_Vd(L): # program to do graph of residu of data give in a list with [[position][Va][Vb][Vc][Vd]]
-    global global_index_figure
-    fig1 = plt.figure(global_index_figure)
-    global_index_figure += 1
-    plt.clf()
-    plt.title("Residu")
-    lr1 = stats.linregress(L[0],L[1]) # return tuple (pente (.slope),ordonnee a l'origine (.intercept), coef de correlation (.rvalue), p-value (.pvalue ?), erreur standard de l'estimation (.stderr))
-    for i in range(len(L[1])):
-        L[1][i] = L[1][i] -  lr1.slope*L[0][i] - lr1.intercept
-    plt.plot(L[0],L[1], "r", label = "BMP_ref")
-
-    lr2 = stats.linregress(L[0],L[2])
-    for i in range(len(L[2])):
-        L[2][i] = L[2][i] -  lr2.slope*L[0][i] - lr2.intercept
-    plt.plot(L[0],L[2], "b", label = "BMP_impr")
-
-    lr3 = stats.linregress(L[0],L[3])
-    for i in range(len(L[3])):
-        L[3][i] = L[3][i] -  lr3.slope*L[0][i] - lr3.intercept
-    plt.plot(L[0],L[3], "g", label = "BMP_ref")
-
-    lr4 = stats.linregress(L[0],L[4])
-    for i in range(len(L[4])):
-        L[4][i] = L[4][i] -  lr4.slope*L[0][i] - lr4.intercept
-    plt.plot(L[0],L[4], "m", label = "BMP_impr")
-    plt.legend()
-    plt.xlabel("length in million motor step")
-    plt.ylabel("tension in mV")
-    #plt.show(block = False)
-
-#    plt.show()
+    linear_fonction_on_data(list_data_name, data, x_data_name, begin_mm = x_begin_mm, end_mm = x_end_mm)
+    linear_fonction_on_data(list_data_name, data, y_data_name, begin_mm = y_begin_mm, end_mm = y_end_mm)
+    data = cut_data(list_data_name, data, x_data_name, inf = x_maximal, equal = x_maximal)
+    data = cut_data(list_data_name, data, x_data_name, sup = x_minimal, equal = x_minimal)
+    data = cut_data(list_data_name, data, y_data_name, inf = y_maximal, equal = y_maximal)
+    data = cut_data(list_data_name, data, y_data_name, sup = y_minimal, equal = y_minimal)
+    if data == []:
+        print("cut to high")
+        return(0)
+    color_list = ["r","g","b","k","m","c","y"]
+    if "bpm_name" in list_data_name:
+        all_bpm_name = all_value_of_data(list_data_name, data, "bpm_name")
+        while len(all_bpm_name) > len(color_list):
+            color_list += color_list
+        oposit_y_data_name = oposit_name(list_data_name, y_data_name)
+        oposit_y_data_number = number_of_data_name(list_data_name, oposit_y_data_name)
+        if oposit_y_data_number == "":
+            for bpm_number in range(len(all_bpm_name)):
+                print_graph_fr(list_data_name, cut_data(list_data_name, data, "bpm_name", equal =  all_bpm_name[bpm_number]), x_data_name, y_data_name, global_index_figure, color = color_list[bpm_number], legende = all_bpm_name[bpm_number], lin_reg = lin_reg, rms = rms, centrage = centrage)
+                if not(residu is None):
+                    print_residu_fr(list_data_name,  cut_data(list_data_name, data, "bpm_name", equal = all_bpm_name[bpm_number]), x_data_name, y_data_name, global_index_figure + 1, color_list[bpm_number], legende = all_bpm_name[bpm_number], rms = rms, centrage = centrage)
+            global_index_figure += 2
+        else:
+            all_oposit_y_value = all_value_of_data(list_data_name, data,oposit_y_data_name)
+            for index_value in range(len(all_oposit_y_value)):
+                data_cut =  cut_data(list_data_name, data, oposit_y_data_name, equal = all_oposit_y_value[index_value])
+                for bpm_number in range(len(all_bpm_name)):
+                    #print(cut_data(list_data_name, data_cut, "bpm_name", equal =  all_bpm_name[bpm_number]))
+                    print_graph_fr(list_data_name, cut_data(list_data_name, data_cut, "bpm_name", equal =  all_bpm_name[bpm_number]), x_data_name, y_data_name, global_index_figure + 2*index_value, color = color_list[bpm_number], legende = all_bpm_name[bpm_number], lin_reg = lin_reg, rms = rms, title = oposit_y_data_name + " = " + str(all_oposit_y_value[index_value]), centrage = centrage)
+                    if not(residu is None):
+                        print_residu_fr(list_data_name, cut_data(list_data_name, data_cut, "bpm_name", equal = all_bpm_name[bpm_number]), x_data_name, y_data_name, global_index_figure + 2*index_value + 1, color_list[bpm_number], legende = all_bpm_name[bpm_number], rms = rms, title = oposit_y_data_name + " = " + str(all_oposit_y_value[index_value]), centrage = centrage)
+            global_index_figure += 2*len(all_oposit_y_value)
+    else: # need to be done, same as befor with "bpm_number" to replace "bpm_name" 
+        print("ERROR TYPE OF DATA")
+
+# ettendre linge
+
+#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_100pts-horizontal_3pts-vertical_20180801_0.txt", "x_motor_step", "x_libera_mm",lin_reg = "true", residu = "yes", rms = "yes")
+
+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_100pts-horizontal_3pts-vertical_20180801_1.txt", "x_motor_step", "x_libera_mm",lin_reg = "true", residu = "yes", rms = "yes")#, x_begin_mm =103.78 , x_end_mm = 72.5)
+
+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_100pts-horizontal_3pts-vertical_20180801_1.txt", "x_motor_mm", "x_libera_mm",lin_reg = "true", residu = "yes", rms = "yes", centrage = "yes")#, x_begin_mm =103.78 , x_end_mm = 72.5, x_minimal = 77., x_maximal = 99, centrage = "yes")#, x_minimal = 77, x_maximal = 99
+
+#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", "x_motor_mm", "x_libera_mm",lin_reg = "true", residu = "yes", rms = "yes")
+
+
+
+
+#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", "y_libera_mm",lin_reg = "true", residu = "yes", rms = "yes",x_minimal = -10, x_maximal = -20)#need data complete
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+    
+#print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_1.txt",  miny = 0, maxy = 57)
+#print_residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_1.txt")
+
+#print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_2_convert-100000_94,36_100000_78,72.txt", begin_mm = 78.72, end_mm = 94.36)
+#print_residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_2_convert-100000_94,36_100000_78,72.txt")
+
+#print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/test.txt", begin_mm = 100)
+#print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/test.txt, begin_mm = 0, end_mm = 1")
+#print_residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/test.txt")
+
+
+#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_20180611_160153_0.txt",0.1,0.3)
+#print_residu_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_20180611_160153_0.txt",0.1,0.3)
+#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_20180611_163036_0.txt")
+#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_vertical_acquisition_20180612_0.txt")
+#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_vertical_acquisition_20180612_0.txt")
+#plt.show(block = False)
+plt.show()
+
     
 """    
@@ -185 +597 @@
     plt.show()
 """
-
-
-
-
-
-
-
-def residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(data): # program to print graph of X_libera vs X_motor with a list data = [[[x_motor_position][y_motor_position][Va][Vb][Vc][Vd][sum][x_libera_position][y_libera_position]][same for BPM1][same for BPM2]],also do a linear regretion and print the equation
-    global global_index_figure # to creat different figure
-    fig1 = plt.figure(global_index_figure)
-    global_index_figure += 1
-    plt.clf()
-    color = ["r","g","b"]
-    legende = ["BPM soleil","BPM impr","BPM ref"]
-    for bpm_number in range(len(data)):
-        lr1 = stats.linregress(data[bpm_number][0],data[bpm_number][7]) # return tuple (pente,ordonnee a l'origine, coef de correlation, p-value, erreur standard de l'estimation)
-    #    residu = product_list(data[bpm_number][7], lr1.slope, b =  lr1.intercept)
-        residu = []
-        for i in range(len(data[bpm_number][0])):
-            residu.append(abs(data[bpm_number][7][i] - data[bpm_number][0][i]*lr1.slope - lr1.intercept))
-        plt.plot(data[bpm_number][0], residu, color[bpm_number]+".", label = legende[bpm_number])
-    plt.legend()
-    plt.title("Residu en fonction de la position")
-    plt.xlabel("length in million motor step")
-    plt.ylabel("tension in mV")
-    plt.gca().yaxis.set_tick_params(labelsize = 8)
-    #plt.show(block = False)
-
-    #    plt.s
-
-
-
-
-
-def min_max(data, cut_index, mini = None ,maxi = None): #program to cut a list data = [[position][Va][Vb][Vc][Vd]] with minimum value of position = mini and maximum value of position = maxi
-    if mini is None and maxi is None :
-        return(data)
-    elif mini is None :
-        for i in data[cut_index]:
-            if i < mini :
-                mini = i
-    elif maxi is None:
-        for i in data[cut_index]:
-            if maxi < i :
-                maxi = i
-    index_list = []
-    for i in range(len(data[cut_index])):
-        if  data[cut_index][i] >= mini and data[cut_index][i] <= maxi :
-            index_list.append(i)
-    return([[data[j][i] for i in index_list] for j in range(len(data))])
-
-            #return([[data[0][i] for i in index_list],[data[1][i] for i in index_list],[data[2][i] for i in index_list],[data[3][i] for i in index_list],[data[4][i] for i in index_list]])
-
-
-def convertion_step_mm(data,begin_mm,end_mm): # length convertion 
-#    print(data)
-    if begin_mm is None:
-        begin_mm = data[0]
-    if end_mm is None:
-        end_mm = data[len(data)-1]
-    begin_step = data[0]
-    end_step = data[len(data)-1]
-    a = float((end_mm - begin_mm))/(end_step - begin_step)
-    b = begin_mm - a*begin_step
-    print(a,b)
-    data = product_list(data, a, b)
-    return(data)
-    
-
-#L = [[i for i in range(51)] for j in range(5)]
-#print(convertion_step_mm(L[0],3.1,44520))
-
-    
-def print_data_position_Va_Vb_Vc_Vd(fichier, min = None, max = None):
-    L = min_max(read_data_position_Va_Vb_Vc_Vd(fichier), 0, mini = min, maxi = max)
-    print_graph_position_Va_Vb_Vc_Vd(L)
-    #print(L)
-
-def print_residu_position_Va_Vb_Vc_Vd(fichier, min_position = None, max_position = None):
-    L = min_max(read_data_position_Va_Vb_Vc_Vd(fichier), 0, mini = min_position, maxi = max_position)
-    residu_position_Va_Vb_Vc_Vd(L)
-    
-def print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(fichier, lin_reg = "yes", minx = None, maxx = None, miny = None, maxy = None, begin_mm = None, end_mm = None): 
-    data = read_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(fichier)
-    if (not minx is None) or (not maxx is None):
-        data =  [min_max(bpm, 0, mini = minx, maxi = maxx) for bpm in data]
-    if (not miny is None) or (not maxy is None):
-        data =  [min_max(bpm, 1, mini = miny, maxi = maxy) for bpm in data]
-    if (not begin_mm is None) or (not end_mm is None):
-        for bpm_index in range(len(data)):
-            data[bpm_index][0] = convertion_step_mm(data[bpm_index][0], (begin_mm - end_mm)/2, (-begin_mm +  end_mm)/2)
-    print_graph_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(data,lin_reg)
-    
-def print_residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(fichier, minx = None, maxx = None, miny = None, maxy = None): 
-    data = read_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(fichier)
-    if (not minx is None) or (not maxx is None):
-        data =  [min_max(bpm, 0, mini = minx, maxi = maxx) for bpm in data]
-    if (not miny is None) or (not maxy is None):
-        data =  [min_max(bpm, 1, mini = miny, maxi = maxy) for bpm in data]
-    residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y(data)
-
-#print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_1.txt",  miny = 0, maxy = 57)
-#print_residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_1.txt")
-
-print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_2_convert-100000_94,36_100000_78,72.txt", begin_mm = 78.72, end_mm = 94.36)
-#print_residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/BPM-number_x-motor_y-motor_Va_Vb_Vc_Vd_Sum_X_Y_BPM0-soleil_BPM1-impr_BPM2-ref_20180718_2_convert-100000_94,36_100000_78,72.txt")
-
-#print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/test.txt", begin_mm = 100)
-#print_data_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/test.txt, begin_mm = 0, end_mm = 1")
-#print_residu_xmotor_ymotor_Va_Vb_Vc_Vd_sum_x_y("data/test.txt")
-
-
-#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_20180611_160153_0.txt",0.1,0.3)
-#print_residu_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_20180611_160153_0.txt",0.1,0.3)
-#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_20180611_163036_0.txt")
-#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_vertical_acquisition_20180612_0.txt")
-#print_data_position_Va_Vb_Vc_Vd("data/position_vs_tension_ch1-3_bpm_ref_ch2-4_bpm_impr_vertical_acquisition_20180612_0.txt")
-#plt.show(block = False)
-plt.show()
-