Translate this matplotlib to kivy

[Christopher Logan]

Hi Folks, i'm looking into converting an existing application using Matplotlib v3.3.1+

i created a poc that contains the versions of plots i need on RasberryPi - the application as it is written works on Raspberry Pi already. can you help convert this into a Kivy App? I don't need the pan/zoom and matplotilb tools at the bottom - just the plots on the canvas above.

Here is the code that i have running on Rasberry Pi and that needs to be converted to Kivy:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

fig, ax = plt.subplots(6)
x = np.arange(0, 2*np.pi, 0.01)
print("len="+str(len(x))+" " +str(x))
dataLen = len(x)
line, = ax[0].plot(x, np.sin(x))
line1, = ax[1].plot(x, np.sin(x))
line2, = ax[2].plot(x, np.sin(x))
line3, = ax[3].plot(x, np.sin(x))
line4, = ax[4].plot(x, np.sin(x))
line5, = ax[5].plot(x, np.sin(x))
indx = 0

def createGap(data, currentIndx):
    gap = 15
    gapIndx=currentIndx+1
    for x in range(gap):

        if gapIndx+x < len(data):

            data[gapIndx+x] = np.nan

def animate(i):
    indx = i % dataLen
    newYData = line.get_ydata()
    print(str(i)+ " indx=" + str(indx) + " " + str(i/50) + " " +str(np.sin(x+i/50)))
    newYData[indx] = np.sin(x[indx] + i / 50)

    #line.set_ydata(np.sin(x + i / 50)) # update the data.

    createGap(newYData, indx)

    line.set_ydata(newYData)

    return line,

def animate1(i):
    line1.set_ydata(np.sin(x + i / 50)) # update the data.
    return line1,
def animate2(i):
    line2.set_ydata(np.sin(x + i / 50)) # update the data.
    return line2,
def animate3(i):
    line3.set_ydata(np.sin(x + i / 50)) # update the data.
    return line3,
def animate4(i):
    line4.set_ydata(np.sin(x + i / 50)) # update the data.
    return line4,
def animate5(i):
    line5.set_ydata(np.sin(x + i / 50)) # update the data.
    return line5,

ani = animation.FuncAnimation(fig, animate, interval=20, blit=True, save_count=50)
ani1 = animation.FuncAnimation( fig, animate1, interval=20, blit=True, save_count=50)
ani2 = animation.FuncAnimation( fig, animate2, interval=20, blit=True, save_count=50)
ani3 = animation.FuncAnimation( fig, animate3, interval=20, blit=True, save_count=50)
ani4 = animation.FuncAnimation( fig, animate4, interval=20, blit=True, save_count=50)
ani5 = animation.FuncAnimation( fig, animate5, interval=20, blit=True, save_count=50)

plt.show()

=====

Here is what I have so far but it just gets me to the static plot. does Kivy support the latest version of Matplotlib 3.5.1?

import numpy as np

import matplotlib.pyplot as plt

import matplotlib.animation as animation

from kivy.lang import Builder

from kivy.uix.floatlayout import FloatLayout

from kivy.app import App

from kivy.properties import ObjectProperty, StringProperty

from kivy.garden.matplotlib import FigureCanvasKivyAgg

fig, ax = plt.subplots(6)

x = np.arange(0, 2*np.pi, 0.01)

print("len="+str(len(x))+" " +str(x))

dataLen = len(x)

line, = ax[0].plot(x, np.sin(x))

line1, = ax[1].plot(x, np.sin(x))

line2, = ax[2].plot(x, np.sin(x))

line3, = ax[3].plot(x, np.sin(x))

line4, = ax[4].plot(x, np.sin(x))

line5, = ax[5].plot(x, np.sin(x))

indx = 0

def animate( i):

    indx = i % dataLen

    newYData = line.get_ydata()

    print(str(i)+ " indx=" + str(indx) + " " + str(i/50) + " "    +str(np.sin(x+i/50)))

    newYData[indx] = np.sin(x[indx] + i / 50)

    #line.set_ydata(np.sin(x + i / 50)) # update the data.

    self.createGap(newYData, indx)

    line.set_ydata(newYData)

    return line,

def animate1(i):

    line1.set_ydata(np.sin(x + i / 50)) # update the data.

    return line1,

def animate2(i):

    line2.set_ydata(np.sin(x + i / 50)) # update the data.

    return line2,

def animate3(i):

    line3.set_ydata(np.sin(x + i / 50)) # update the data.

    return line3,

def animate4(i):

    line4.set_ydata(np.sin(x + i / 50)) # update the data.

    return line4,

def animate5(i):

    line5.set_ydata(np.sin(x + i / 50)) # update the data.

    return line5,

ani = animation.FuncAnimation(fig, animate, interval=20, blit=True, save_count=50)

ani1 = animation.FuncAnimation(fig, animate1, interval=20, blit=True, save_count=50)

ani2 = animation.FuncAnimation(fig, animate2, interval=20, blit=True, save_count=50)

ani3 = animation.FuncAnimation(fig, animate3, interval=20, blit=True, save_count=50)

ani4 = animation.FuncAnimation( fig, animate4, interval=20, blit=True, save_count=50)

ani5 = animation.FuncAnimation(fig, animate5, interval=20, blit=True, save_count=50)

class vmc(FloatLayout):

    def __init__(self, info=None, **kwargs):

        super().__init__(**kwargs)

        label_wid = ObjectProperty()

        info = StringProperty()

        box = self.ids.box

        box.add_widget(FigureCanvasKivyAgg(plt.gcf()))

def createGap(self, data, currentIndx):

    gap = 15

    gapIndx=currentIndx+1

    for x in range(gap):

        if gapIndx+x < len(data):

            data[gapIndx+x] = np.nan

class vmcApp(App):

    def build(self):

        Builder.load_file('../ui/layouts/vmc.kv')

        return vmc()

# Main driver if this module is called like a script

# Currently just supports VCM

if __name__ == "__main__":

    vmcApp().run()

Thank you

-Christopher