Б12-514 , Косицына Таисия

solutions/sem02/lesson07/task1.py

@@ -13,8 +13,110 @@ def visualize_diagrams(
     ordinates: np.ndarray,
     diagram_type: Any,
 ) -> None:
-    # ваш код
-    pass
+    if abscissa.shape != ordinates.shape:
+        raise ShapeMismatchError
+
+    if not (diagram_type == "hist" or diagram_type == "violin" or diagram_type == "box"):
+        raise ValueError
+
+    space = 0.2
+
+    figure = plt.figure(figsize=(8, 8))
+    grid = plt.GridSpec(4, 4, wspace=space, hspace=space)
+
+    axis_scatter = figure.add_subplot(grid[:-1, 1:])
+    axis_vert = figure.add_subplot(
+        grid[:-1, 0],
+        sharey=axis_scatter,
+    )
+
+    axis_hor = figure.add_subplot(
+        grid[-1, 1:],
+        sharex=axis_scatter,
+    )
+
+    axis_scatter.scatter(abscissa, ordinates, color="deeppink", alpha=0.3)
+
+    if diagram_type == "hist":
+        axis_hor.hist(
+            abscissa,
+            bins=50,
+            color="lightpink",
+            density=True,
+            alpha=0.5,
+            edgecolor="palevioletred",
+            linewidth=1,
+        )
+
+        axis_vert.hist(
+            ordinates,
+            bins=50,
+            color="lightpink",
+            orientation="horizontal",
+            density=True,
+            alpha=0.5,
+            edgecolor="palevioletred",
+            linewidth=1,
+        )
+
+        axis_hor.invert_yaxis()
+        axis_vert.invert_xaxis()
+
+    if diagram_type == "violin":
+        violin_hor = axis_hor.violinplot(
+            abscissa,
+            vert=False,
+            showmedians=True,
+        )
+
+        for body in violin_hor["bodies"]:
+            body.set_facecolor("violet")
+            body.set_edgecolor("darkmagenta")
+            body.set_linewidth(2)
+
+        for part in violin_hor:
+            if part == "bodies":
+                continue
+
+            violin_hor[part].set_edgecolor("darkmagenta")
+
+        violin_vert = axis_vert.violinplot(
+            ordinates,
+            vert=True,
+            showmedians=True,
+        )
+
+        for body in violin_vert["bodies"]:
+            body.set_facecolor("violet")
+            body.set_edgecolor("darkmagenta")
+            body.set_linewidth(2)
+
+        for part in violin_vert:
+            if part == "bodies":
+                continue
+
+            violin_vert[part].set_edgecolor("darkmagenta")
+
+    if diagram_type == "box":
+        axis_hor.boxplot(
+            ordinates,
+            vert=False,
+            patch_artist=True,
+            boxprops=dict(facecolor="lightcoral"),
+            medianprops=dict(color="firebrick"),
+        )
+        axis_vert.set_xticks([])
+        axis_vert.set_xlabel("y values")
+
+        axis_vert.boxplot(
+            abscissa,
+            vert=True,
+            patch_artist=True,
+            boxprops=dict(facecolor="lightcoral"),
+            medianprops=dict(color="firebrick"),
+        )
+        axis_hor.set_yticks([])
+        axis_hor.set_xlabel("x values")
 
 
 if __name__ == "__main__":
@@ -25,4 +127,7 @@ def visualize_diagrams(
     abscissa, ordinates = np.random.multivariate_normal(mean, cov, size=1000).T
 
     visualize_diagrams(abscissa, ordinates, "hist")
+    visualize_diagrams(abscissa, ordinates, "violin")
+    visualize_diagrams(abscissa, ordinates, "box")
+
     plt.show()

solutions/sem02/lesson07/task2.py

@@ -1 +1,41 @@
-# ваш код (используйте функции или классы для решения данной задачи)
+import matplotlib.pyplot as plt
+import numpy as np
+
+before = [0]*4
+after = [0]*4
+file_path = 'D:/GitHub/python_mipt_dafe_tasks/solutions/sem02/lesson07/data/medic_data.json'
+with open(file_path, 'r') as file:
+    content = file.read()
+
+before_part = content.split('"before"')[1].split('"after"')[0]
+after_part = content.split('"after"')[1]
+
+before[0] = before_part.count('"I"') - before_part.count('"IV"')
+before[1] = before_part.count('"II"')
+before[2] = before_part.count('"III"')
+before[3] = before_part.count('"IV"')
+
+after[0] = after_part.count('"I"') - after_part.count('"IV"')
+after[1] = after_part.count('"II"')
+after[2] = after_part.count('"III"')
+after[3] = after_part.count('"IV"')
+
+figure, axis = plt.subplots(figsize=(9, 9))
+
+stages = np.array(['I', 'II', 'III', 'IV'])
+axis.set_xticks(np.arange(stages.size), labels=stages, weight="bold")
+
+x = np.arange(4)
+width = 0.35
+
+axis.bar(x - width/2, before, width, color='goldenrod', edgecolor='brown')
+axis.bar(x + width/2, after, width, color='lightgreen', edgecolor='olive')
+
+axis.set_ylabel('amount of people')
+axis.set_title('Mitral desease stages')
+axis.legend(["before", "after"], title="Desease stages")
+
+figure.savefig("medic.png", bbox_inches="tight")
+plt.show()
+
+

solutions/sem02/lesson08/task1.py

@@ -8,27 +8,60 @@
 
 
 def create_modulation_animation(
-    modulation, 
-    fc, 
-    num_frames, 
-    plot_duration, 
-    time_step=0.001, 
-    animation_step=0.01,
-    save_path=""
+    modulation, fc, num_frames, plot_duration, time_step=0.001, animation_step=0.01, save_path=""
 ) -> FuncAnimation:
-    # ваш код
-    return FuncAnimation()
+    abscissa = np.arange(0, plot_duration, time_step)
+
+    def signal(abscissa, modulation, fc):
+        f = np.sin(2 * np.pi * fc * abscissa)
+
+        if modulation is None:
+            return f
+        else:
+            return modulation(abscissa) * f
+
+    figure, axis = plt.subplots(figsize=(16, 9))
+    axis.set_xlim(0, plot_duration)
+
+    line, *_ = axis.plot(
+        abscissa,
+        signal(abscissa, modulation, fc),
+        c="deeppink",
+    )
+
+    def update_frame(
+        frame_id: int,
+    ) -> tuple[plt.Line2D]:
+        new_x = abscissa + frame_id * animation_step
+        sign = signal(new_x, modulation, fc)
+        line.set_ydata(sign)
+
+        return (line,)
+
+    animation = FuncAnimation(
+        figure,
+        update_frame,
+        frames=num_frames,
+        interval=50,
+        blit=True,
+    )
+
+    if save_path:
+        animation.save("func.gif", writer="pillow", fps=24)
+
+    return animation
 
 
 if __name__ == "__main__":
+
     def modulation_function(t):
-        return np.cos(t * 6) 
+        return np.cos(t * 6)
 
-    num_frames = 100  
-    plot_duration = np.pi / 2 
-    time_step = 0.001  
-    animation_step = np.pi / 200 
-    fc = 50  
+    num_frames = 100
+    plot_duration = np.pi / 2
+    time_step = 0.001
+    animation_step = np.pi / 200
+    fc = 50
     save_path_with_modulation = "modulated_signal.gif"
 
     animation = create_modulation_animation(
@@ -38,6 +71,6 @@ def modulation_function(t):
         plot_duration=plot_duration,
         time_step=time_step,
         animation_step=animation_step,
-        save_path=save_path_with_modulation
+        save_path=save_path_with_modulation,
     )
-    HTML(animation.to_jshtml())
+    plt.show()