New Matplotlib demo based on Template that allows changing Matplotlib Style and PySimpleGUI Theme to see what matches
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PySimpleGUI
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import PySimpleGUI as sg
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import numpy as np
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from matplotlib.backends.backend_tkagg import FigureCanvasAgg
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import matplotlib.figure
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import matplotlib.pyplot as plt
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import io
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from matplotlib import cm
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from mpl_toolkits.mplot3d.axes3d import get_test_data
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from matplotlib.ticker import NullFormatter # useful for `logit` scale
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"""
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Demo - Matplotlib Non-interactive Embedded with Theme and Style selection
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This demo is based on the Matplotlib "TEMPLATE" demo that is a general purpose, display-only
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demo as only the image of the plot is shown. None of the buttons and interactive parts
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of the MAtplotlib interface are included.
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This demo adds the ability to change the Window's "Theme" and the Matplotlib's "Style".
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It gives you a way to quickly see how well a theme is going to match a particular Matplotlib Style.
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Copyright 2020 PySimpleGUI.org
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"""
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def create_axis_grid():
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from mpl_toolkits.axes_grid1.axes_rgb import RGBAxes
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plt.close('all')
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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 create_figure():
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# ------------------------------- START OF YOUR MATPLOTLIB CODE -------------------------------
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fig = matplotlib.figure.Figure(figsize=(5, 4), dpi=100)
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t = np.arange(0, 3, .01)
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fig.add_subplot(111).plot(t, 2 * np.sin(2 * np.pi * t))
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return fig
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def create_subplot_3d():
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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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fig.colorbar(surf, shrink=0.5, aspect=5)
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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 create_pyplot_scales():
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plt.close('all')
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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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# ----------------------------- The draw figure helpful function -----------------------------
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def draw_figure(element, figure):
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"""
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Draws the previously created "figure" in the supplied Image Element
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:param element: an Image Element
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:param figure: a Matplotlib figure
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:return: The figure canvas
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"""
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plt.close('all') # erases previously drawn plots
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canv = FigureCanvasAgg(figure)
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buf = io.BytesIO()
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canv.print_figure(buf, format='png')
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if buf is None:
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return None
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buf.seek(0)
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element.update(data=buf.read())
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return canv
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dictionary_of_figures = {'Axis Grid': create_axis_grid,
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'Subplot 3D': create_subplot_3d,
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'Scales': create_pyplot_scales,
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'Basic Figure': create_figure}
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# ----------------------------- The GUI Section -----------------------------
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def create_window():
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"""
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Defines the window's layout and creates the window object.
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This function is used so that the window's theme can be changed and the window "re-started".
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:return: The Window object
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:rtype: sg.Window
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"""
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left_col = [[sg.T('Figures to Draw')],
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[sg.Listbox(list(dictionary_of_figures), default_values=[list(dictionary_of_figures)[0]], size=(15, 5), key='-LB-')],
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[sg.T('Matplotlib Styles')],
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[sg.Combo(plt.style.available, size=(15, 10), key='-STYLE-')],
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[sg.T('PySimpleGUI Themes')],
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[sg.Combo(sg.theme_list(), default_value=sg.theme(), size=(15, 10), key='-THEME-')]]
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layout = [[sg.T('Matplotlib Example', font='Any 20')],
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[sg.Col(left_col), sg.Image(key='-IMAGE-')],
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[sg.B('Draw'), sg.B('Exit')]]
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window = sg.Window('Matplotlib Embedded Template', layout, finalize=True)
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return window
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def main():
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window = create_window()
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while True:
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event, values = window.read()
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print(event, values)
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if event == 'Exit' or event == sg.WIN_CLOSED:
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break
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if event == 'Draw':
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if values['-THEME-'] != sg.theme(): # if new theme chosen, create a new window
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window.close()
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sg.theme(values['-THEME-'])
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window = create_window()
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if values['-LB-']: # make sure something selected to draw
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func = dictionary_of_figures[values['-LB-'][0]]
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if values['-STYLE-']:
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plt.style.use(values['-STYLE-'])
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draw_figure(window['-IMAGE-'], func())
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window.close()
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if __name__ == "__main__":
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main()
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