drawplot.py

#!/usr/bin/env python
# encoding: utf-8

import os
import numpy as np
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d
from matplotlib import cm
import time


class DrawPlot:
    def __init__(self, path2save):
        self.picture_number = 0

        if not os.path.exists(path2save):
            os.makedirs(path2save)
        self.path = path2save

    def draw_hist(self, data_list, data_name):
        self.picture_number += 1
        y = np.array(data_list, dtype=float)
        y = y.ravel()

        # Create a new figure
        plt.figure(self.picture_number, figsize=(8, 4))
        plt.hist(y, bins=50, range=None, normed=False)

        # Add text description
        text = ("Min:" + str(y.min()) + "\nMax:" +
                str(y.max()) + "\nMean:" + str(y.mean()))
        plt.figtext(0.2, 0.7, text)

        plt.title(data_name + " Histogram Plot")    # title of figure
        plt.xlabel('value')                         # Label of x-axis
        plt.ylabel('count')                         # Label of y-axis
        plt.grid(True)                              # Turn the grid on
        plt.savefig(self.path + data_name + '_hist.pdf')
        plt.close()

    def draw_runchart(self, data_list, data_name):
        self.picture_number += 1
        # 2D Matrix, duts * sensors
        data_array = np.array(data_list, dtype=int)
        # caculate stdev of data, output 1D Matrix, rows + columns
        std_data = np.std(data_array, axis=0)

        x = np.arange(len(std_data))
        y = std_data

        plt.figure(self.picture_number, figsize=(8, 4))
        plt.plot(x, y, 'ro')
        plt.title(data_name + " StdDev Plot")
        plt.xlabel("sensor")
        plt.ylabel("value")
        plt.grid(True)
        plt.savefig(self.path + data_name + '_stdDev.pdf')
        plt.close()

    def draw_3Dplot(self, data_list, data_name):
        self.picture_number += 1
        # 3D Matrix, duts * rows * columns
        data_array = np.array(data_list, dtype=int)
        # caculate stdev of duts, output 2D Matrix, rows * columns
        std_data = np.std(data_array, axis=0)

        x_arange, y_arange = std_data.shape
        x, y = np.mgrid[:x_arange, :y_arange]

        plt.figure(self.picture_number, figsize=(8, 4))
        plt.title(data_name + " StdDev Surface")
        # 111 means 1 row 1 column and the No.1 subplot
        ax = plt.subplot(111, projection='3d')
        ax.plot_surface(x, y, std_data, rstride=1, cstride=1, cmap=cm.coolwarm)
        ax.set_xlabel("sensor_x")
        ax.set_ylabel("sensor_y")
        ax.set_zlabel(data_name + " StdDev")
        plt.savefig(self.path + data_name + '_stdDev_3D.pdf')
        plt.close()


if __name__ == "__main__":
    start_time = time.time()

    draw_plot = DrawPlot("./")
    draw_plot.draw_hist(np.random.rand(100), "random 100")
    draw_plot.draw_runchart(np.random.rand(2, 100), "random 100")
    draw_plot.draw_3Dplot(np.random.rand(3, 3, 100), "random 100")

    elasped_time = time.time() - start_time
    print("Succeed. Elapsed Time: {0}".format(elasped_time))