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In a measurement chain, each instrument embedded in various measurement loops will record a CSV and I want to monitor the live plots in separate figures i.e figure 1 for instrument1 , figure 2 for instrument2...etc. I try to implement animations but nothing out. csv is continuously generating data.

I first generate data in a CSV then i try to plot 2 animations in parallel:I get the figure 2 animated but the first is frozen. any help appreciated.

import pandas as pd
from matplotlib import pyplot as plt
from matplotlib import animation

# making figures
def makeFigure():
    df = pd.read_csv('data.csv')
    data = pd.DataFrame(df)
    x = data['current']
    y1 = data['resistance']
    y2 = data['voltage']
    fig=plt.figure()
    ax=fig.add_subplot(1,1,1)
    # # Plot 1 set of data
    dataset =ax.plot(x,y1)
    return fig,ax,dataset

# Frame rendering function
def renderFrame(i, dataset):
    df = pd.read_csv('data.csv')
    data = pd.DataFrame(df)
    x = data['current']
    y1 = data['resistance']
    y2 = data['voltage']
    # Plot data
    plt.cla()
    dataset, =ax.plot(x,y2)
   
    return dataset

# Make the figures
figcomps1=makeFigure()
figcomps2=makeFigure()

# List of Animation objects for tracking
anim = []

# Animate the figures
for figcomps in [figcomps1,figcomps2]:
    fig,ax,dataset = figcomps
    anim.append(animation.FuncAnimation(fig,renderFrame,fargs=[dataset]))
# plt.gcf()
plt.show()
```
Trenton McKinney
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datac
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1 Answers1

1

these lines can plot 2 animations in parallel reading datapoints from a CSV file. it does the job although sometimes the figure gets blank.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import pandas as pd

df = pd.read_csv('data.csv')
data = pd.DataFrame(df)
x = data['current']
y1 = data['resistance']
y2 = data['voltage']
 

fig1, ax1 = plt.subplots(figsize=(4, 4))

def animatex(i):
    ax1.clear()
    ax1.plot(x[i:], y1[i:], color='r')
    ax1.autoscale(enable=True, axis='y')

anix = FuncAnimation(fig1, animatex, interval=1000)


fig2, ax2 = plt.subplots(figsize=(4, 4))

def animatev(i):
    ax2.clear()
    ax2.plot(x[i:], y2[i:], color='b')
    ax2.autoscale(enable=True, axis='y')
aniv = FuncAnimation(fig2, animatev, interval=1000)
plt.show()
datac
  • 39
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