first test

bloxplot_stats.py

@@ -0,0 +1,113 @@
+import sys
+import os
+import yaml
+import matplotlib.pyplot as plt
+import numpy as np
+scores_big =[]
+name = []
+colors = []
+def s_a(n):
+    return sum(n)/len(n)
+
+def mediana(n):
+    while len(n) >2:
+        n.remove(min(n))
+        n.remove(max(n))
+    if len(n) == 2:
+        return s_a(n)
+    else:
+        return n[0]
+
+def plot(ax, path, color):
+    scores =[]
+
+    for filename in sorted(os.listdir(path)):
+        file_path = os.path.join(path, filename)
+        # Check if it is a file and not a subdirectory
+        if os.path.isfile(file_path) and file_path.endswith('.yaml'):
+            with open(file_path, 'r', encoding='utf-8') as file:
+                data = yaml.load(file, Loader = yaml.Loader)
+                #scores.append(data['score'])
+                scores.append(data['score']/data['total_time'])
+
+
+    ax.plot(range(1, len(scores)+1),scores, '.-', label=f"{path.split('/')[-1]}'s scores", color = color)
+    ax.plot((1, len(scores)),(s_a(scores), s_a(scores)), '--', label=f"{path.split('/')[-1]}'s mean ({round(s_a(scores), 3)})", color = color)
+    ax.plot((1, len(scores)),(mediana(scores), mediana(scores)), ':', label=f"{path.split('/')[-1]}'s mediana ({round(mediana(scores), 3)})", color = color)
+
+
+def boxplot(ax, path, color):
+    scores =[]
+
+    for filename in sorted(os.listdir(path)):
+        file_path = os.path.join(path, filename)
+        # Check if it is a file and not a subdirectory
+        if os.path.isfile(file_path) and file_path.endswith('.yaml'):
+            with open(file_path, 'r', encoding='utf-8') as file:
+                data = yaml.load(file, Loader = yaml.Loader)
+                #scores.append(data['score'])
+                scores.append(data['score']/data['total_time'])
+
+    scores_big.append(scores)
+    name.append(path.split('/')[-1])
+    colors.append(color)
+
+
+if __name__ == '__main__':
+
+    global_path = "/home/gestures/Easy_sim/dummy_simulation/stats/"
+    # 1. Name (Dima)
+    # 2. Name-Name (Dima-Elisey)
+
+    DATA = {} # Name of creator - {} - Name of tester
+
+    for dirname in sorted(os.listdir(global_path)):
+        dirpath = os.path.join(global_path, dirname)
+        if os.path.isdir(file_path):
+            data = []
+            if not dirname.contains('-'):
+                name = dirname
+                if not name is DATA:
+                    DATA[name] = {}
+                DATA[name][name] = data
+            else:
+                names = dirname.split('-')
+                name1 = names[0]
+                name2 = names[1]
+                if not name1 is DATA:
+                    DATA[name1] = {}
+                DATA[name1][name2] = data
+            for filename in sorted(os.listdir(dirpath)):
+                file_path = os.path.join(dirpath, filename)
+                if file_path.endswith('.yaml'):
+                    with open(file_path, 'r', encoding='utf-8') as file:
+                    datafile = yaml.load(file, Loader = yaml.Loader)
+                    # TODO change score to new formula
+                    data.append(datafile['score'])
+
+
+
+
+
+
+
+
+    fig, ax = plt.subplots()
+
+    boxplot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Dima", "limegreen")
+    boxplot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Elisey", "red")
+    boxplot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/BOBA", "magenta")
+    boxplot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Nika", "pink")
+    boxplot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Sasha", "orange")
+    plot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Christine", "blue")
+
+    scores_BIG = ax.boxplot(scores_big, patch_artist=True, tick_labels=name)
+    # Применяем цвета к каждому ящику
+    for patch, color in zip(scores_BIG['boxes'], colors):
+        patch.set_facecolor(color)
+    ax.set(xlabel='№', ylabel='score')
+    ax.grid()
+    ax.legend()
+    ax.set_title("Scores of students in dummy simulation")
+    plt.show()
+#path.split('/')[-1]

first_test.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+# Данные: (первый человек, второй человек, время1, время2)
+data = [
+    ("Елисей", "Ника",  "01:53.68", "00:46.85"),
+    ("Ника",   "Вова",  "00:57.28", "01:05.67"),
+    ("Вова",   "Елисей","00:38.35", "00:34.74"),
+    ("Дима",   "Саша",  "00:57.45", "00:52.90"),
+    ("Саша",   "Дима",  "00:25.69", "00:55.85"),
+]
+
+def time_to_seconds(t):
+    # поддерживает формат mm:ss.xx
+    mm, rest = t.split(":")
+    ss = float(rest)
+    return int(mm) * 60 + ss
+
+def seconds_to_time(sec):
+    mm = int(sec // 60)
+    ss = sec % 60
+    return f"{mm:02d}:{ss:05.2f}"
+
+# Подготовка данных
+labels = [f"{a} → {b}" for a, b, _, _ in data]
+t1 = np.array([time_to_seconds(x[2]) for x in data])
+t2 = np.array([time_to_seconds(x[3]) for x in data])
+
+y = np.arange(len(data))
+
+# Визуальный стиль
+plt.style.use("seaborn-v0_8-whitegrid")
+fig, ax = plt.subplots(figsize=(11, 6))
+
+color1 = "#4C78A8"
+color2 = "#F58518"
+
+bars1 = ax.barh(y, t1, color=color1, edgecolor="none", label="Первое время")
+bars2 = ax.barh(y, t2, left=t1, color=color2, edgecolor="none", label="Второе время")
+
+# Подписи на сегментах
+for i, (b1, b2, a1, a2) in enumerate(zip(bars1, bars2, t1, t2)):
+    ax.text(
+        b1.get_x() + b1.get_width() / 2,
+        b1.get_y() + b1.get_height() / 2,
+        seconds_to_time(a1),
+        ha="center", va="center", color="white", fontsize=10, fontweight="bold"
+    )
+    ax.text(
+        b2.get_x() + b2.get_width() / 2,
+        b2.get_y() + b2.get_height() / 2,
+        seconds_to_time(a2),
+        ha="center", va="center", color="white", fontsize=10, fontweight="bold"
+    )
+
+# Подписи осей и оформление
+ax.set_yticks(y)
+ax.set_yticklabels(labels, fontsize=11)
+ax.invert_yaxis()
+ax.set_xlabel("Время, сек.")
+ax.set_title("Сравнение суммарного времени выполнения задания", fontsize=15, pad=12)
+ax.legend(loc="lower right")
+
+# Сетка и рамки
+ax.spines["top"].set_visible(False)
+ax.spines["right"].set_visible(False)
+ax.grid(axis="x", linestyle="--", alpha=0.4)
+
+plt.tight_layout()
+
+fig.savefig("first_test.png")
+
+plt.show()

fullplot_stats.py

@@ -0,0 +1,221 @@
+import sys
+import os
+import yaml
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def total_boxplot(DATA, creator = 'any', tester = 'any', simulation = "dummy_simulation", savepath = "./"):
+
+    fig, ax = plt.subplots()
+
+    data_to_plot = []
+    labels = []
+    title = f'Boxplot of scores in {simulation},'
+    xlabel = ""
+
+    colors_list = plt.colormaps['tab10'].colors
+
+    if creator == tester == 'any':
+        print(f"Warning: setting both creator and tester as 'any' plots only self testing!")
+        title += f" self testing"
+        xlabel = "self tester"
+        for creator_name, data in DATA.items():
+            if creator_name in data:
+                data_to_plot.append(data[creator_name])
+                labels.append(creator_name)
+
+    elif creator == 'any':
+        title += f" tester: {tester}"
+        xlabel = "creator"
+        for creator_name, data in DATA.items():
+            if tester in data:
+                data_to_plot.append(data[tester])
+                #labels.append(f"{creator_name}-{tester}")
+                labels.append(creator_name)
+
+    elif tester == 'any':
+        title += f" creator: {creator}"
+        xlabel = "tester"
+        if creator in DATA:
+            for tester_name, data in DATA[creator].items():
+                data_to_plot.append(data)
+                #labels.append(f"{creator}-{tester}")
+                labels.append(tester_name)
+
+
+    if len(data_to_plot) == 0:
+        print("No appropriate data!")
+        return
+
+
+    #print(len(data_to_plot), len(labels))
+    median_styling = {'color': 'black', 'linewidth': 2}
+    elements = ax.boxplot(data_to_plot, patch_artist=True, tick_labels=labels, medianprops=median_styling)
+    for i, patch in enumerate(elements['boxes']):
+        patch.set_facecolor(colors_list[(i)%10])
+
+    ax.grid()
+    #ax.legend()
+    ax.set(xlabel=xlabel, ylabel='Score')
+    ax.set_title(title)
+
+    ax.figure.savefig(f'{savepath}/{creator}_{tester}_{simulation}.png', bbox_inches='tight')
+
+
+def heat_map(DATA, criteria = np.median, savepath = "./"):
+
+    names_to_nums = {name: num for num, name in enumerate(list(DATA.keys()))}
+    values = np.zeros( (len(names_to_nums)+1, len(names_to_nums)+1) )
+
+    testers = {}
+    for creator, Data in DATA.items():
+        total_creator = []
+        for tester, data in Data.items():
+            if not tester in testers:
+                testers[tester] = []
+            if creator in names_to_nums and tester in names_to_nums:
+                creator_idx = names_to_nums[creator]
+                tester_idx = names_to_nums[tester]
+                values[creator_idx, tester_idx] = criteria(data)
+                total_creator += data
+                testers[tester] +=data
+            values[creator_idx, len(names_to_nums)] = criteria(total_creator)
+
+    for tester, data in testers.items():
+        tester_idx = names_to_nums[tester]
+        values[len(names_to_nums), tester_idx] = criteria(data)
+
+    fig, ax = plt.subplots()
+    im = ax.imshow(values, cmap='coolwarm')
+
+    for i in range(values.shape[0]):
+        for j in range(values.shape[1]):
+            text = ax.text(j, i, round(values[i, j],1), ha="center", va="center", color="k")
+
+    ax.set_xticks(range(len(DATA.keys())+1), labels=list(DATA.keys())+['mean'] )
+    ax.set_yticks(range(len(DATA.keys())+1), labels=list(DATA.keys())+['mean'] )
+
+    ax.set(xlabel='tester', ylabel='creator')
+    ax.set_title(f"Cross-validation heatmap ({criteria.__name__})")
+
+    ax.figure.savefig(f"{savepath}/cross_validation_{criteria.__name__}.png")
+
+
+
+def convert_score(data):
+
+    score = data['score']
+    Nsof = len(data['exted_sofs'])
+    Ncol = len(data['collisions'])
+    Ksof = data['k_params']['_k_sof']
+    Khp = data['k_params']['_k_hp']
+    Kch = data['k_params']['_k_charge']
+    Khp_max = 100
+    Kch_max = 100
+
+    Kch_r = (score - Ksof*Nsof-Khp*(Khp_max-Ncol)/Khp_max) * Kch_max/Kch
+
+    score_new = Ksof*Nsof*(Kch*Kch_r/Khp_max+Khp*(Khp_max-Ncol)/Khp_max)
+    #print(type(score_new))
+
+    return score_new
+
+# DATA[name] = {name: [scores]}
+def no_interface_plot(DATA, savepath = "./"):
+    n = 0
+    names_with = []#DATA.keys()
+    names_without = []
+    for creator, Data in DATA.items():
+        for tester, data in Data.items():
+            if tester == creator:
+                if 'NoInt' in creator:
+                    pass
+                else:
+
+                    wInt = creator+'NoInt'
+                    if wInt in DATA:
+                        names_with.append(creator)
+                        names_without.append(wInt)
+    #print(len(names_with), names_with)
+    #print(len(names_without), names_without)
+    '''
+    for tester, data in Data.items():
+        if tester == creator:
+            del DATA[]
+    '''
+    creator_means = {
+        'With interface': [np.median(DATA[name][name]) for name in names_with],
+        'Without interface': [np.median(DATA[name][name]) for name in names_without]}
+
+    x = np.arange(len(names_with))  # the label locations
+    width = 0.25  # the width of the bars
+    multiplier = 0
+
+    fig, ax = plt.subplots(layout='constrained')
+
+    for attribute, measurement in creator_means.items():
+        offset = width * multiplier
+        rects = ax.bar(x + offset, np.round(measurement,2), width, label=attribute)
+        ax.bar_label(rects, padding=3)
+        multiplier += 1
+    ax.set_ylabel('Score')
+    ax.set_title('Change in scores with visual interface disabled')
+    ax.set_xticks(x + width, names_with)
+    ax.legend(loc='upper left', ncols=3)
+    ax.set_ylim(0, 100)
+    ax.grid(axis='y')
+
+    ax.figure.savefig(f"{savepath}/no_interface.png")
+
+
+
+if __name__ == '__main__':
+
+    global_path = "/home/gestures6/Easy_sim/dummy_simulation/stats/"
+    # 1. Name (Dima)
+    # 2. Name-Name (Dima-Elisey)
+
+    DATA = {} # Name of creator - {} - Name of tester
+
+    for dirname in sorted(os.listdir(global_path)):
+        dirpath = os.path.join(global_path, dirname)
+        if os.path.isdir(dirpath) and not dirname.startswith('!'):
+            data = []
+            if not '-' in dirname:
+                name = dirname
+                if not name in DATA:
+                    DATA[name] = {}
+                DATA[name][name] = data
+            else:
+                names = dirname.split('-')
+                name1 = names[0]
+                name2 = names[1]
+                if not name1 in DATA:
+                    DATA[name1] = {}
+                DATA[name1][name2] = data
+            for filename in sorted(os.listdir(dirpath)):
+                file_path = os.path.join(dirpath, filename)
+                if file_path.endswith('.yaml'):
+                    with open(file_path, 'r', encoding='utf-8') as file:
+                        datafile = yaml.load(file, Loader = yaml.Loader)
+                        data.append(convert_score(datafile)) # TODO change score to new formula
+                        #data.append(datafile['score'])
+
+
+    #for cr, data in DATA.items():
+        #print(f"{cr}: {data}")
+    savepath = global_path
+    total_boxplot(DATA, creator = 'any', tester = 'any', savepath = savepath)
+
+    no_interface_plot(DATA, savepath = savepath)
+
+    #for name in DATA.keys():
+        #total_boxplot(DATA, creator = name, tester = 'any', savepath = savepath)
+        #total_boxplot(DATA, creator = 'any', tester = name, savepath = savepath)
+
+    #heat_map(DATA, savepath = savepath)
+
+
+    plt.show()
+

plot_stats.py

@@ -0,0 +1,54 @@
+import sys
+import os
+import yaml
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def s_a(n):
+    return sum(n)/len(n)
+
+def mediana(n):
+    while len(n) >2:
+        n.remove(min(n))
+        n.remove(max(n))
+    if len(n) == 2:
+        return s_a(n)
+    else:
+        return n[0]
+
+
+def plot(ax, path, color):
+    scores =[]
+
+    for filename in sorted(os.listdir(path)):
+        file_path = os.path.join(path, filename)
+        # Check if it is a file and not a subdirectory
+        if os.path.isfile(file_path) and file_path.endswith('.yaml'):
+            with open(file_path, 'r', encoding='utf-8') as file:
+                data = yaml.load(file, Loader = yaml.Loader)
+                scores.append(data['score'])
+                #scores.append(data['score']/data['total_time'])
+
+
+    ax.plot(range(1, len(scores)+1),scores, '.-', label=f"{path.split('/')[-1]}'s scores", color = color)
+    ax.plot((1, len(scores)),(s_a(scores), s_a(scores)), '--', label=f"{path.split('/')[-1]}'s mean ({round(s_a(scores), 3)})", color = color)
+    ax.plot((1, len(scores)),(mediana(scores), mediana(scores)), ':', label=f"{path.split('/')[-1]}'s mediana ({round(mediana(scores), 3)})", color = color)
+
+
+
+if __name__ == '__main__':
+    fig, ax = plt.subplots()
+
+    plot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Dima", "limegreen")
+    plot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Elisey", "red")
+    plot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/BOBA", "magenta")
+    plot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Nika", "pink")
+    plot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Sasha", "orange")
+    plot(ax, "/home/gestures/Easy_sim/dummy_simulation/stats/Christine", "blue")
+
+    ax.set(xlabel='№', ylabel='score')
+    ax.grid()
+    ax.legend()
+    ax.set_title("Scores of students in dummy simulation")
+    plt.show()