bluepine · November 10, 2018 01:42 · Nov 10, 2018
diff --git a/plot.py b/plot.py
@@ -0,0 +1,97 @@
+# pyline: disable=no-member
+""" plot3d using existing visuals : LinePlotVisual """
+
+import numpy as np
+import sys
+import seaborn as sns
+from vispy import app, visuals, scene
+import matplotlib.pyplot as plt
+
+
+def line_plot3d_matplotlib(x, y, z):
+    plt.ioff()
+#     fig = plt.figure()
+    ax = plt.gca(projection='3d')
+    ax.set_xlabel('$X$', fontsize=20)
+    ax.set_ylabel('$Y$', fontsize=20)
+    ax.set_zlabel('$Z$', fontsize=20)
+    ax.plot(x, y, z, 'gray')
+    ax.scatter(x, y, z, 'gray')
+    # ax.legend()
+    plt.show()
+
+
+def line_plot3d_vispy(x, y, z):
+    z = z.astype(float)
+    xm = np.mean(x)
+    ym = np.mean(y)
+    zm = np.mean(z)
+    x -= xm
+    y -= ym
+    z -= zm
+    x *= 1.0/max(x)
+    y *= 1.0/max(y)
+    z *= 1.0/max(z)
+    center = (0, 0, 0)
+    # build visuals
+    Plot3D = scene.visuals.create_visual_node(visuals.LinePlotVisual)
+
+    # build canvas
+    canvas = scene.SceneCanvas(keys='interactive', title='plot3d', show=True)
+
+    # Add a ViewBox to let the user zoom/rotate
+    view = canvas.central_widget.add_view()
+    view.camera = 'turntable'
+    view.camera.fov = 45
+    view.camera.distance = 2
+    view.camera.center = center
+    # plot
+    pos = np.c_[x, y, z]
+    Plot3D(pos, width=2.0, color='red',
+           edge_color='w', symbol='o', face_color=(0.2, 0.2, 1, 0.8),
+           parent=view.scene)
+    app.run()
+
+
+def hist(data_frame):
+    for column in data_frame:
+        if 'id' != column and data_frame[column].dtype == 'object':
+            sns.catplot(x=column, kind="count", palette="ch:.25",
+                        data=data_frame, log=True)
+
+    data_frame.hist(bins=15, color='steelblue', edgecolor='black',
+                    linewidth=1.0, xlabelsize=8, ylabelsize=8, grid=False, log=True)
+    plt.show()
+
+
+def corr_heatmap(data_frame):
+    """Correlation Matrix Heatmap"""
+    # f, ax = plt.subplots(figsize=(10, 6))
+    corr = data_frame.corr()
+    sns.heatmap(round(corr, 2), annot=True, cmap="coolwarm", fmt='.2f',
+                linewidths=.05)
+    plt.show()
+    # f.subplots_adjust(top=0.93)
+    # t = f.suptitle('Wine Attributes Correlation Heatmap', fontsize=14)
+
+
+def select_cols_by_bool_vec(bv, data_frame):
+    cols = bv.index[bv]
+    return data_frame[cols]
+
+
+def pairplot(data_frame, corr_threshold=0.5):
+    corr = data_frame.corr()
+    np.fill_diagonal(corr.values, 0)
+    corr_index = corr.max().abs() > corr_threshold
+    sns.pairplot(select_cols_by_bool_vec(corr_index, data_frame).dropna())
+
+
+if __name__ == '__main__':
+    # prepare data
+    N = 6000
+    x = np.sin(np.linspace(-2, 2, N)*np.pi)
+    y = np.cos(np.linspace(-2, 2, N)*np.pi)
+    z = np.linspace(-2, 2, N)
+    if sys.flags.interactive != 1:
+        line_plot3d_vispy(x, y, z)