Matplotlib demos! Single, animated, multiple
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MikeTheWatchGuy
parent
82e326a6c1
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@ -41,18 +41,66 @@ def draw_figure(canvas, figure, loc=(0, 0)):
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return photo
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#------------------------------- PASTE YOUR MATPLOTLIB CODE HERE -------------------------------
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import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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from matplotlib.ticker import NullFormatter # useful for `logit` scale
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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# make up some data in the interval ]0, 1[
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y = np.random.normal(loc=0.5, scale=0.4, size=1000)
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y = y[(y > 0) & (y < 1)]
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y.sort()
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x = np.arange(len(y))
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matplotlib.rcParams['axes.unicode_minus'] = False
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fig, ax = plt.subplots()
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ax.plot(10*np.random.randn(100), 10*np.random.randn(100), 'o')
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ax.set_title('Using hyphen instead of Unicode minus')
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# plot with various axes scales
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plt.figure(1)
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# linear
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plt.subplot(221)
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plt.plot(x, y)
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plt.yscale('linear')
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plt.title('linear')
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plt.grid(True)
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# log
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plt.subplot(222)
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plt.plot(x, y)
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plt.yscale('log')
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plt.title('log')
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plt.grid(True)
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# symmetric log
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plt.subplot(223)
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plt.plot(x, y - y.mean())
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plt.yscale('symlog', linthreshy=0.01)
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plt.title('symlog')
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plt.grid(True)
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# logit
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plt.subplot(224)
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plt.plot(x, y)
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plt.yscale('logit')
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plt.title('logit')
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plt.grid(True)
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# Format the minor tick labels of the y-axis into empty strings with
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# `NullFormatter`, to avoid cumbering the axis with too many labels.
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plt.gca().yaxis.set_minor_formatter(NullFormatter())
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# Adjust the subplot layout, because the logit one may take more space
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# than usual, due to y-tick labels like "1 - 10^{-3}"
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plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=0.25,
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wspace=0.35)
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#------------------------------- END OF YOUR MATPLOTLIB CODE -------------------------------
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# ****** Comment out this line if not using Pyplot ******
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fig = plt.gcf() # if using Pyplot then get the figure from the plot
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# -------------------------------- GUI Starts Here -------------------------------#
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# fig = your figure you want to display. Assumption is that 'fig' holds the #
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@ -1,12 +1,10 @@
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from tkinter import *
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from random import randint
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import PySimpleGUI as g
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from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, FigureCanvasAgg
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from matplotlib.figure import Figure
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import matplotlib.backends.tkagg as tkagg
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import tkinter as Tk
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import tkinter as tk
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VIEW_SIZE = 50 # number of data points visible on 1 screen
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def main():
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fig = Figure()
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@ -17,9 +15,11 @@ def main():
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ax.grid()
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canvas_elem = g.Canvas(size=(640, 480)) # get the canvas we'll be drawing on
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slider_elem = g.Slider(range=(0,10000), size=(60,10), orientation='h')
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# define the form layout
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layout = [[g.Text('Animated Matplotlib', size=(40,1), justification='center', font='Helvetica 20')],
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[canvas_elem],
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[slider_elem],
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[g.ReadFormButton('Exit', size=(10,2), pad=((280, 0), 3), font='Helvetica 14')]]
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# create the form and show it without the plot
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@ -36,14 +36,15 @@ def main():
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if button is 'Exit' or values is None:
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exit(69)
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slider_elem.Update(i)
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ax.cla()
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ax.grid()
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ax.plot(range(VIEW_SIZE), dpts[i:i+VIEW_SIZE], color='purple')
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DATA_POINTS_PER_SCREEN = 40
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ax.plot(range(DATA_POINTS_PER_SCREEN), dpts[i:i+DATA_POINTS_PER_SCREEN], color='purple')
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graph.draw()
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figure_x, figure_y, figure_w, figure_h = fig.bbox.bounds
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figure_w, figure_h = int(figure_w), int(figure_h)
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photo = Tk.PhotoImage(master=canvas, width=figure_w, height=figure_h)
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photo = tk.PhotoImage(master=canvas, width=figure_w, height=figure_h)
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canvas.create_image(640/2, 480/2, image=photo)
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@ -58,4 +59,3 @@ def main():
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if __name__ == '__main__':
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main()
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@ -0,0 +1,266 @@
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import PySimpleGUI as g
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import matplotlib
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matplotlib.use('TkAgg')
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from matplotlib.backends.backend_tkagg import FigureCanvasAgg
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import matplotlib.backends.tkagg as tkagg
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import tkinter as Tk
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"""
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Demonstrates one way of embedding Matplotlib figures into a PySimpleGUI window.
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Basic steps are:
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* Create a Canvas Element
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* Layout form
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* Display form (NON BLOCKING)
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* Draw plots onto convas
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* Display form (BLOCKING)
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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def PyplotSimple():
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import numpy as np
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import matplotlib.pyplot as plt
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# evenly sampled time at 200ms intervals
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t = np.arange(0., 5., 0.2)
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# red dashes, blue squares and green triangles
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plt.plot(t, t, 'r--', t, t ** 2, 'bs', t, t ** 3, 'g^')
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fig = plt.gcf() # get the figure to show
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return fig
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def PyplotFormatstr():
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def f(t):
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return np.exp(-t) * np.cos(2*np.pi*t)
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t1 = np.arange(0.0, 5.0, 0.1)
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t2 = np.arange(0.0, 5.0, 0.02)
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plt.figure(1)
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plt.subplot(211)
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plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')
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plt.subplot(212)
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plt.plot(t2, np.cos(2*np.pi*t2), 'r--')
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fig = plt.gcf() # get the figure to show
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return fig
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def UnicodeMinus():
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import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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matplotlib.rcParams['axes.unicode_minus'] = False
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fig, ax = plt.subplots()
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ax.plot(10 * np.random.randn(100), 10 * np.random.randn(100), 'o')
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ax.set_title('Using hyphen instead of Unicode minus')
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return fig
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def Subplot3d():
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from mpl_toolkits.mplot3d.axes3d import Axes3D
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from matplotlib import cm
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# from matplotlib.ticker import LinearLocator, FixedLocator, FormatStrFormatter
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import matplotlib.pyplot as plt
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import numpy as np
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fig = plt.figure()
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ax = fig.add_subplot(1, 2, 1, projection='3d')
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X = np.arange(-5, 5, 0.25)
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Y = np.arange(-5, 5, 0.25)
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X, Y = np.meshgrid(X, Y)
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R = np.sqrt(X ** 2 + Y ** 2)
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Z = np.sin(R)
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surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet,
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linewidth=0, antialiased=False)
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ax.set_zlim3d(-1.01, 1.01)
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# ax.w_zaxis.set_major_locator(LinearLocator(10))
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# ax.w_zaxis.set_major_formatter(FormatStrFormatter('%.03f'))
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fig.colorbar(surf, shrink=0.5, aspect=5)
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from mpl_toolkits.mplot3d.axes3d import get_test_data
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ax = fig.add_subplot(1, 2, 2, projection='3d')
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X, Y, Z = get_test_data(0.05)
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ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
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return fig
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def PyplotScales():
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.ticker import NullFormatter # useful for `logit` scale
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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# make up some data in the interval ]0, 1[
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y = np.random.normal(loc=0.5, scale=0.4, size=1000)
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y = y[(y > 0) & (y < 1)]
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y.sort()
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x = np.arange(len(y))
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# plot with various axes scales
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plt.figure(1)
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# linear
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plt.subplot(221)
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plt.plot(x, y)
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plt.yscale('linear')
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plt.title('linear')
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plt.grid(True)
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# log
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plt.subplot(222)
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plt.plot(x, y)
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plt.yscale('log')
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plt.title('log')
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plt.grid(True)
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# symmetric log
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plt.subplot(223)
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plt.plot(x, y - y.mean())
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plt.yscale('symlog', linthreshy=0.01)
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plt.title('symlog')
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plt.grid(True)
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# logit
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plt.subplot(224)
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plt.plot(x, y)
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plt.yscale('logit')
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plt.title('logit')
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plt.grid(True)
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# Format the minor tick labels of the y-axis into empty strings with
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# `NullFormatter`, to avoid cumbering the axis with too many labels.
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plt.gca().yaxis.set_minor_formatter(NullFormatter())
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# Adjust the subplot layout, because the logit one may take more space
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# than usual, due to y-tick labels like "1 - 10^{-3}"
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plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=0.25,
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wspace=0.35)
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return plt.gcf()
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def AxesGrid():
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import numpy as np
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1.axes_rgb import RGBAxes
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def get_demo_image():
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# prepare image
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delta = 0.5
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extent = (-3, 4, -4, 3)
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x = np.arange(-3.0, 4.001, delta)
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y = np.arange(-4.0, 3.001, delta)
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X, Y = np.meshgrid(x, y)
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Z1 = np.exp(-X ** 2 - Y ** 2)
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Z2 = np.exp(-(X - 1) ** 2 - (Y - 1) ** 2)
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Z = (Z1 - Z2) * 2
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return Z, extent
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def get_rgb():
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Z, extent = get_demo_image()
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Z[Z < 0] = 0.
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Z = Z / Z.max()
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R = Z[:13, :13]
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G = Z[2:, 2:]
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B = Z[:13, 2:]
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return R, G, B
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fig = plt.figure(1)
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ax = RGBAxes(fig, [0.1, 0.1, 0.8, 0.8])
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r, g, b = get_rgb()
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kwargs = dict(origin="lower", interpolation="nearest")
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ax.imshow_rgb(r, g, b, **kwargs)
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ax.RGB.set_xlim(0., 9.5)
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ax.RGB.set_ylim(0.9, 10.6)
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plt.draw()
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return plt.gcf()
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def draw_figure(canvas, figure, loc=(0, 0)):
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""" Draw a matplotlib figure onto a Tk canvas
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loc: location of top-left corner of figure on canvas in pixels.
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Inspired by matplotlib source: lib/matplotlib/backends/backend_tkagg.py
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"""
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figure_canvas_agg = FigureCanvasAgg(figure)
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figure_canvas_agg.draw()
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figure_x, figure_y, figure_w, figure_h = figure.bbox.bounds
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figure_w, figure_h = int(figure_w), int(figure_h)
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photo = Tk.PhotoImage(master=canvas, width=figure_w, height=figure_h)
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# Position: convert from top-left anchor to center anchor
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canvas.create_image(loc[0] + figure_w/2, loc[1] + figure_h/2, image=photo)
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# Unfortunately, there's no accessor for the pointer to the native renderer
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tkagg.blit(photo, figure_canvas_agg.get_renderer()._renderer, colormode=2)
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# Return a handle which contains a reference to the photo object
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# which must be kept live or else the picture disappears
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return photo
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#------------------------------- PASTE YOUR MATPLOTLIB CODE HERE -------------------------------
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# -------------------------------- GUI Starts Here -------------------------------#
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# fig = your figure you want to display. Assumption is that 'fig' holds the #
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# information to display. #
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# --------------------------------------------------------------------------------#
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fig_dict = {'Pyplot Simple':PyplotSimple, 'Pyplot Formatstr':PyplotFormatstr,'PyPlot Three':Subplot3d,
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'Unicode Minus': UnicodeMinus, 'Pyplot Scales' : PyplotScales, 'Axes Grid' : AxesGrid}
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figure_w, figure_h = 640,480
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canvas_elem = g.Canvas(size=(figure_w, figure_h)) # get the canvas we'll be drawing on
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# define the form layout
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listbox_values = [key for key in fig_dict.keys()]
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col_listbox = [[g.Listbox(values=listbox_values,size=(20,8), key='func')],
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[g.ReadFormButton('Plot', pad=((50,0), 3))]]
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layout = [[g.Text('Matplotlib Plot Test', font=('current 18'))],
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[g.Column(col_listbox), canvas_elem],
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[g.Exit(pad=((50,0), 3), size=(4,2))]]
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# create the form and show it without the plot
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form = g.FlexForm('Demo Application - Embedding Matplotlib In PySimpleGUI')
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form.Layout(layout)
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form.Show(non_blocking=True)
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form.NonBlocking = False
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# add the plot to the window
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func = fig_dict['Pyplot Simple']
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while True:
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fig = func()
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fig_photo = draw_figure(canvas_elem.TKCanvas, fig)
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# show it all again and get buttons
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button, values = form.Read()
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if button is None or button is 'Exit':
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break
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choice = values['func'][0]
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try:
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func = fig_dict[choice]
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except:
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func = fig_dict['Pyplot Simple']
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