Fixed bugs

src/DataInput.py

@@ -0,0 +1,41 @@
+from tkinter import *
+
+
+class DataInput(Frame):
+
+    def __init__(self, master=None, cnf={}, **kw):
+        Frame.__init__(self, master, cnf, **kw)
+        self.entries = []
+        self.generate_entry()
+
+    def generate_entry(self):
+        entry_value = StringVar()
+        last_value = ""
+        def add_data_callback(var, indx, mode):
+            nonlocal last_value
+            if entry_value.get() == "":
+                entry_value.set(0)
+                return
+            try:
+                float(entry_value.get().replace(",", "."))
+            except ValueError:
+                entry_value.set(last_value)
+                return
+            if "," in entry_value.get():
+                entry_value.set(entry_value.get().replace(",", "."))
+                last_value = entry_value.get()
+                return
+            last_value = entry_value.get()
+            if self.entries[-1].get() != "":
+                self.generate_entry()
+            # For some reason, if we remove that, it doesn't seem to work anymore. Strange...
+        entry_value.trace_add("write", add_data_callback)
+        entry = Entry(self, width=50, font=("Arrial", 18), bg='#FFFFFF', fg='#4682B4',
+                      textvariable=entry_value)
+        entry.pack(expand=YES)
+        self.entries.append(entry)
+
+    def get_data(self):
+        print([entry for entry in self.entries])
+        [print(entry.get()) for entry in self.entries]
+        return [float(entry.get()) for entry in self.entries if entry.get() != ""]

src/Frame.py

@@ -1,9 +1,10 @@
-from tkinter import *
+from tkinter import Frame, Label, Button, YES
 from time import sleep
 from src.DataInput import DataInput
+from src.utils import present_xhi2_data
 
 
-class ClassFrame(Frame):
+class Frame(Frame):
 
     def __init__(self, containeur, color):
         super().__init__(containeur, bg=color)
@@ -50,6 +51,9 @@ def add_Button(self, content, police, size, background, forground, cmd):
 
     def add_Entry(self, entry):
         self.add_element(entry, expand=YES)
+
+    def on_load(self, callback):
+        self.bind("<Map>", callback)
     """
     def add_Bind(self, cmmd):
         self.Bind = bind(self, command=cmd)
@@ -60,21 +64,27 @@ def add_Bind(self, cmmd):
 """
     @classmethod
     def build_home(cls, window, callback):
-        frame = ClassFrame(window, "#4682B4")
+        frame = Frame(window, "#4682B4")
         frame.add_text("Bienvenue sur le test du \u03C7\u00B2", "Arial", 35, '#4682B4', '#FFFFFF')
-        frame.add_Button("Continuer", "Arrial", 20, '#FFFFFF', '#4682B4', callback)
+        frame.add_Button("Continuer", "Arial", 20, '#FFFFFF', '#4682B4', callback)
         frame.pack(expand=YES)
         return frame
 
     @classmethod
     def build_data_selection(cls, window, callback):
 
-        frame = ClassFrame(window, "#4682B4")
+        frame = Frame(window, "#4682B4")
         frame.add_text(
             "Sélectionnez votre échantillons de mesures",
             "Arial", 18, '#4682B4', '#FFFFFF')
-        #frame.add_Entry(())
-        frame.add_Button("Calculer", "Arrial", 20, '#FFFFFF', '#4682B4', callback)
+        frame.add_Button("Calculer", "Arial", 20, '#FFFFFF', '#4682B4', callback)
         data_input = DataInput(frame)
         frame.add_element(data_input)
         return frame, data_input
+
+    @classmethod
+    def build_table(cls, window, data_provider):
+        frame = Frame(window, "#4682B4")
+        frame.add_text("Tableau de \u03C7\u00B2", "Arial", 20, '#4682B4', '#FFFFFF')
+        frame.on_load(lambda e: present_xhi2_data(data_provider()))
+        return frame

src/main.py

@@ -2,12 +2,16 @@
 import statistics
 import matplotlib.pyplot as plt
 import numpy as np
-from DataArray import DataArray
-from ClassData import ClassData
-from src.ClassFrame import ClassFrame
-import src.ClassTable
+from src.DataArray import DataArray
+from src.ClassData import ClassData
+from src.Frame import Frame
+from src.utils import present_xhi2_data
+
+from tkinter import Tk, mainloop, Entry, YES
+
+data = []
+
 
-from tkinter import *
 def ecart_centre_red(a, mean, ecart_type):
     b = (a - mean) / ecart_type
     return b
@@ -19,18 +23,6 @@ def population(a, b, data):
             pop += 1
     return pop
 
-def theorical_frequency(a, b, integration_table):
-    # int(a < 0) = -1 si a > 0, 1 si a < 0
-    # Les calculs sont bizarres, mais ils doivent marcher ^^
-    print(a)
-    print(b)
-    a = abs(int(100 * a))
-    b = abs(int(100 * b))
-    print((str(a // 100) + "." + str(a // 10 - a // 100 * 10), str(a - a // 10 * 10)))
-    print((str(b // 100) + "." + str(b // 10 - b // 100 * 10), str(b - b // 10 * 10)))
-    return \
-        int(a < 0) * float(integration_table[str(a // 100) + "." + str(a // 10 - a // 100 * 10), str(a - a // 10 * 10)]) + \
-        int(b > 0) * float(integration_table[str(b // 100) + "." + str(b // 10 - b // 100 * 10), str(b - b // 10 * 10)])
 
 def home_buttom_continue():
     frame_home.destroy()
@@ -42,63 +34,29 @@ def return_entry(en):
     return content
 
 
+def get_data():
+    return data
+
+
 def data_buttom_calculate():
-    content_entry = entry_frameselct.get()
-    content_entry = str(content_entry).split(",")
-    sample = sorted([int(i) for i in content_entry])
-    sample_mean = statistics.mean(sample)
-    def Calculate_e_type_sb():
-        e_type_sb = statistics.stdev(sample, sample_mean)
-        return e_type_sb
-
-    values = sorted([ecart_centre_red(i, sample_mean, Calculate_e_type_sb()) for i in sample])
-
-    width = values[-1] - values[0]
-    class_count = int(math.sqrt(len(sample))) + 1
-    class_width = width / class_count
-    # Je pense que ça sert à rien, si on peut avoir plus précis, autant avoir plus précis
-    # class_width = round(class_width, 4) + 0.0001
-
-    # La même ici je pense
-    min_value = values[0]  # round(values[0], 4) - 0.0001
-
-    # Format d'une class : [(borne_sup, borne_inf), population, fréquence_expérimentale, fréquence_théorique, x²]
-    class_data = []
-    for i in range(class_count):
-        data = ClassData()
-        data.infimum = min_value + class_width * i
-        data.supremum = min_value + (1 + i) * class_width
-        class_data.append(data)
-    # On ajoute 1 pour faire comme si l'intervalle était fermé. On aurait pu ajouter 2, 3, 4, 0.0000001,
-    # mais autant ajouter 1, c'est pratique ^^
-    # class_data[-1].supremum = values[-1] + 1
-    # J'ai pas compris ici, mais ça fesait un dernier intervalle incoherent
-
-    for i, data in enumerate(class_data):
-        data.population = population(min_value + class_width * i, min_value + (1 + i) * class_width, values)
-    for data in class_data:
-        data.experimental_frequency = data.population / len(values)
-
-    integration_table = DataArray.load_array("Integrate_gauss")
-    for data in class_data:
-        data.theorical_frequency = theorical_frequency(data.infimum, data.supremum, integration_table)
-
-    xhi2 = class_count * sum(
-        [(data.experimental_frequency * data.theorical_frequency) ** 2 / data.theorical_frequency for data in
-         class_data])
-
-    result = ("Valeurs centrées réduites : {}\nEtendue des valeurs : {}\nLongueur des classes : {}\nDonnées des classes : {}\nxhi² : {}".format(str(values), str(width), str(class_width), str(class_data), str(xhi2)))
+
+    #xhi2 = present_xhi2_data(data_input.get_data())
+    #print(xhi2)
+
+    #result = ("Valeurs centrées réduites : {}\nEtendue des valeurs : {}\nLongueur des classes : {}\nDonnées des classes : {}\nxhi² : {}".format(str(values), str(width), str(class_width), str(class_data), str(xhi2)))
     #print(result)
 
-    bins_class = []  # On definis les diffférents intervalles
-    for data in class_data:
-        bins_class.append(data.infimum)
-    bins_class.append(values[-1])
+    #bins_class = []  # On definis les diffférents intervalles
+    #for data in class_data:
+    #    bins_class.append(data.infimum)
+    #bins_class.append(values[-1])
+    global data
+    data = data_input.get_data()
     frame_dataselection.destroy()
-    frame_table_presentaion.pack()
-    list_calculate = (sample, sample_mean, Calculate_e_type_sb(), values, width, class_width, class_data, xhi2, bins_class)
-    print(list_calculate)
-    return list_calculate
+    frame_table_presentation.pack()
+    #list_calculate = (sample, sample_mean, Calculate_e_type_sb(), values, width, class_width, class_data, xhi2, bins_class)
+    #print(list_calculate)
+    #return list_calculate
 
 
 
@@ -110,64 +68,9 @@ def Calculate_e_type_sb():
 window.config(background='#4682B4')
 
 
-frame_home = ClassFrame(window, "#4682B4")
-frame_home.add_Subitle("Bienvenue sur le test du \u03C7\u00B2", "Arial", 35, '#4682B4', '#FFFFFF')
-frame_home.add_Buttom("Continuer", "Arrial", 20, '#FFFFFF', '#4682B4', home_buttom_continue)
-
-frame_home.pack(expand=YES)
-
-frame_dataselection = ClassFrame(window, "#4682B4")
-frame_dataselection.add_Title("Sélectionnez votre échantillons de mesures \n(chaque mesure doit être séparée par une virgule et entière)", "Arial", 18, '#4682B4', '#FFFFFF')
-entry_frameselct = Entry(frame_dataselection, width=50, font=("Arrial", 18), bg='#FFFFFF', fg='#4682B4')
-entry_frameselct.pack(expand=YES)
-
-entry_frameselct.bind('<Return>', return_entry(entry_frameselct))
-frame_dataselection.add_Buttom("Calculer", "Arrial", 20, '#FFFFFF', '#4682B4', data_buttom_calculate)
-
-frame_table_presentaion = ClassFrame(window, "#4682B4")
-frame_table_presentaion.add_Title("Tableau de \u03C7\u00B2", "Arrial", 20, '#4682B4', '#FFFFFF')
-
-def buttom_TableandGraph():
-    fig, ax = plt.subplots()  # On cree la fenetre pyplot
-    exp_freq_array = np.array(data_buttom_calculate()[3])  # On change une liste en une matrice
-
-
-    # 10,10,11,11,11,13,12,9,12,14
-    # Echantillon test1
-    x = []
-    y = []
-    # On cree une liste d'antécendant une une matrice d'immage pour pouvoir
-    # creer la courbe théorique
-    while len(x) <= 100:
-        x.append((sample[0] - sample_mean) + len(x) * (sample[-1] - sample[0]) / 100)
-    for i in range(len(x)):
-        y.append((1 / (np.sqrt(2 * np.pi) * e_type_sb)) * np.exp(-0.5 * ((x[i]) / e_type_sb) ** 2))
-
-    num_bins = class_count
-    # On construit l'histogramme reel
-    n, bins, patches = ax.hist(exp_freq_array, num_bins, density=True)
-    # 14,15,16,17,18,14,15,17,16,17,17,18,17,17,13,15,15,15,14,13,16,17,18,14,15,16,17,18,19,17,14,17,16,15,15,16
-    # echantillon test 2
-    # 0.385,0.387,0.388,0.383,0.391,0.380,0.382,0.384,0,.386,0.389,0.390,0.385,0.389,0.388,0.382,0.387,0.388,0.392,0.383,0.388,0.385
-    # 385,387,388,383,391,380,382,384,386,389,390,385,389,388,382,387,388,392,383,388,385
-    # On transforme les liste en matrice
-    x_array = np.array(x)
-    y_array = np.array(y)
-    # On met le teste de la bulle
-    textstr = "$\mu=%.2f${}\n$\sigma=%.2f${}\n\u03C7\u00B2={}".format(round(sample_mean, 3), round(e_type_sb, 3),
-                                                                      round(xhi2, 4))
-    # On creer la bulle
-    props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
-    # On assemble le texte et la bulle pour former la légende
-    ax.text(0.05, 0.95, textstr, transform=ax.transAxes, fontsize=14, verticalalignment='top', bbox=props)
-
-    # On creer la courbe théorique
-    plt.plot(x_array, y_array, '--')
-    # On met le titre
-    plt.title("Test du \u03C7\u00B2")
-    # On met une legende sur l'axe y
-    plt.ylabel('Frequence')
-    # plt.show()
+frame_home = Frame.build_home(window, home_buttom_continue)
+frame_dataselection, data_input = Frame.build_data_selection(window, data_buttom_calculate)
+frame_table_presentation = Frame.build_table(window, lambda: data)
 
 
 #total_rows = len(lst)

src/utils/__init__.py

@@ -0,0 +1 @@
+from src.utils.xhi2 import *