I have been trying to plot live data (data that keeps on updating) using FuncAnimation from the MatplotLib module. When I run the program, the graph doesn't display. The program doesn't give any errors, but displays the following message when I run the program: "Figure size 576x396 with 0 Axes"
Here's my code to plot the live data:
import matplotlib.pyplot as plt
import pandas as pd
from matplotlib.animation import FuncAnimation
%matplotlib inline
plt.style.use('seaborn')
def animate(i):
df = pd.read_csv('data2.csv')
x = df['x_value']
y1 = df['total1']
y2 = df['total2']
plt.cla()
plt.plot(x, y1, label='Line1')
plt.plot(x, y2, label = 'Line2')
plt.legend(loc='upper left')
plt.tight_layout()
ani = FuncAnimation(plt.gcf(), animate, interval=1000)
plt.tight_layout()
plt.show()
Here's the csv file I created for the program:
import random
import csv
import time
import pandas as pd
x_value = 0
total1 = 10000
total2 = 10000
fieldnames = ['x_value','total1','total2']
with open('data2.csv', 'w') as csv_file:
csv_writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
csv_writer.writeheader()
while True:
with open('data2.csv','a') as csv_file:
csv_writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
info = {
'x_value': x_value,
'total1' : total1,
'total2' : total2
}
csv_writer.writerow(info)
print(x_value, total1, total2)
x_value += 1
total1 = total1 + random.randint(-6,8)
total2 = total2 + random.randint(9,11)
time.sleep(1)
Any recommendations will be greatly appreciated.
The message, <Figure size 576x396 with 0 Axes> , is showing the location where the graph is saved. Removing plt.show() shows the plot.
Related
I'm very early in making a simple graph to plot the temperature and humidity of a given space however, the graph plots both lines but they don't intersect instead they do something like in the image below:
here's the code:
import matplotlib.pyplot as plt
from itertools import count
from matplotlib.animation import FuncAnimation
import serial
import matplotlib as mpl
import numpy as np
x = []
line1 = []
line2 = []
serialPort = serial.Serial(port = "COM3", baudrate=115200,
bytesize=8, timeout=1, stopbits=serial.STOPBITS_ONE)
serialString = ""
index = count()
def animate(i):
if serialPort.in_waiting > 0:
serialString = serialPort.readline()
string = serialString.decode('Ascii')
line1.append(string.split(' ')[0])
line2.append(string.split(' ')[1])
x.append(next(index))
print(len(line1))
if len(line1) >= 1000:
line1.pop(0)
line2.pop(0)
x.pop(0)
plt.cla()
plt.plot(x, line1, label='Temperature')
plt.plot(x, line2, label='Humidity')
ani = FuncAnimation(plt.gcf(), animate, interval=400)
plt.tight_layout()
plt.show()
I'm using a Raspberry Pi to plot live data from serial, but eventually run out of memory. I'm not sure if/how I can close the figure, but still have a live data display.
Would it be possible to create and close a new figure with every animate?
My code at the moment:
import serial
import matplotlib
# Force matplotlib to not use any Xwindows backend.
matplotlib.use('TkAgg') #comment out for debugging
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
import gc
# Create figure for plotting
fig = plt.figure()
xs = []
ysAC = []
ysDC = []
ser = serial.Serial('/dev/ttyUSB0', 115200, timeout=1)
ser.flush()
# This function is called periodically from FuncAnimation
def animate(i, xs, ysAC, ysDC):
values = getValues()
wAC = values[1]
wDC = values[2]
# Add x and y to lists
xs.append(i)
ysAC.append(wAC)
ysDC.append(wDC)
# Limit x and y lists to 10 items
xs = ['T-9','T-8','T-7','T-6','T-5','T-4','T-3','T-2','T-1','Now']
ysDC = ysDC[-10:]
ysAC = ysAC[-10:]
# Draw x and y lists
axRT1.clear()
if len(ysDC) == 10:
lineAC, = axRT1.plot(xs, ysAC, 'b:', label='Mains', linewidth = 4)
lineDC, = axRT1.plot(xs, ysDC, 'g--', label='Solar', linewidth = 4)
gc.collect()
#fig.clf()
#plt.close()
def getValues():
if ser.in_waiting > 0:
line = ser.readline().decode('utf-8').rstrip()
return list(line.split(","))
# Set up plot to call animate() function periodically
ani = animation.FuncAnimation(fig, animate, fargs=(xs, ysAC, ysDC), interval=1000, blit=False)
plt.get_current_fig_manager().full_screen_toggle()
plt.ioff()
plt.show()
plt.draw()
The crude way of clearing the plots marked below fixed it for me:
import time
import serial
import datetime as dt
import matplotlib
# Force matplotlib to not use any Xwindows backend.
matplotlib.use('TkAgg') #comment out for debugging
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
import matplotlib.animation as animation
from decimal import Decimal
import pandas as pd
import numpy as np
import os.path as path
import re
import gc
import os
count = 0
# Create figure for plotting
fig = plt.figure()
fig.patch.set_facecolor('whitesmoke')
hFont = {'fontname':'sans-serif', 'weight':'bold', 'size':'12'}
xs = ['T-9','T-8','T-7','T-6','T-5','T-4','T-3','T-2','T-1','Now']
ysTemp = []
ysAC = []
ysDC = []
axRT1 = fig.add_subplot(2, 2, 1)
axRT2 = axRT1.twinx() # instantiate a second axes that shares the same x-axis
#Draw x and y lists
axRT1.clear()
axRT2.clear()
axRT1.set_ylim([0, 4])
axRT2.set_ylim([10, 70])
axRT1.set_ylabel('Power Consumption kW', **hFont)
axRT2.set_ylabel('Temperature C', **hFont)
axRT1.set_xlabel('Seconds', **hFont)
axRT1.set_title('Power Consumption and Temperature - Real Time', **hFont)
lineTemp, = axRT2.plot([], [], 'r', label='Temp', linewidth = 4)
lineAC, = axRT1.plot([], [], 'b:', label='Mains', linewidth = 4)
lineDC, = axRT1.plot([], [], 'g--', label='Solar', linewidth = 4)
fig.legend([lineAC, lineDC,lineTemp], ['Mains', 'Solar', 'Temp'], fontsize=20)
ser = serial.Serial('/dev/ttyUSB0', 115200, timeout=1)
ser.flush()
# This function is called periodically from FuncAnimation
def animate(i, xs, ysTemp, ysAC, ysDC):
values = getValues()
if values != 0:
temp_c = Decimal(re.search(r'\d+',values[3]).group())
if temp_c < 0: temp_c = 0
wAC = round(Decimal(re.search(r'\d+', values[1]).group())/1000, 2)
if wAC < 0.35: wAC = 0
aDC = float(re.search(r'\d+', values[2]).group()) #remove characters
vDC = float(re.search(r'\d+', values[4][:5]).group()) #remove characters
wDC = aDC * vDC
wDC = round(abs(Decimal(wDC))/1000, 2)
# Add x and y to lists
ysTemp.append(temp_c)
ysAC.append(wAC)
ysDC.append(wDC)
# Limit x and y lists to 10 items
ysTemp = ysTemp[-10:]
ysDC = ysDC[-10:]
ysAC = ysAC[-10:]
if len(ysTemp) == 10:
axRT2.lines = [] #This crude way of clearing the plots worked
axRT1.lines =[] #This crude way of clearing the plots worked
lineTemp, = axRT2.plot(xs, ysTemp, 'r', label='Temp', linewidth = 4)
lineAC, = axRT1.plot(xs, ysAC, 'b:', label='Mains', linewidth = 4)
lineDC, = axRT1.plot(xs, ysDC, 'g--', label='Solar', linewidth = 4)
def getValues():
measureList = 0
if ser.in_waiting > 0:
line = ser.readline().decode('utf-8').rstrip()
print(line)
if line.count(',') == 4:
measureList = list(line.split(","))
return measureList
# Set up plot to call animate() function periodically
ani = animation.FuncAnimation(fig, animate, fargs=(xs, ysTemp, ysAC, ysDC), interval=1000, blit=False)
plt.get_current_fig_manager().full_screen_toggle()
plt.ioff()
plt.show()
plt.draw()
I'm new to Python and I'm trying to combine two scripts together. The first script reads a value from a sensor and writes it to a .csv file.
#!/usr/bin/python
import csv
import spidev
import time
#Define Variables
x_value = 0
pad_value = 0
delay = 0.1
pad_channel = 0
fieldnames = ["x_value", "pad_value"]
#Create SPI
spi = spidev.SpiDev()
spi.open(0, 0)
spi.max_speed_hz=1000000
def readadc(adcnum):
# read SPI data from the MCP3008, 8 channels in total
if adcnum > 7 or adcnum < 0:
return -1
r = spi.xfer2([1, 8 + adcnum << 4, 0])
data = ((r[1] & 3) << 8) + r[2]
return data
#Write headers
with open('data.csv', 'w') as csv_file:
csv_writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
csv_writer.writeheader()
#Write values
while True:
with open('data.csv', 'a') as csv_file:
csv_writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
info = {
"x_value": x_value,
"pad_value": pad_value
}
csv_writer.writerow(info)
#Update values
x_value += 1
pad_value = readadc(pad_channel)
print(x_value, pad_value)
time.sleep(delay)
The second script reads the .csv file and plots the data to a graph using matplotlib.
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
plt.style.use('fivethirtyeight')
def animate(i):
data = pd.read_csv('data.csv')
x = data['x_value'].tail(600)
y = data['pad_value'].tail(600)
plt.cla()
plt.plot(x, y)
ani = FuncAnimation(plt.gcf(), animate, interval=100)
plt.tight_layout()
plt.show()
I can run both scripts separately and they work, but I want to combine them into a single script.
I've tried to merge them, but when it gets to plt.show() it shows the graph but doesn't continue. I tried plt.show(block=False), which continues, but doesn't show the graph.
#!/usr/bin/python
import csv
import spidev
import time
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
#Define Variables
x_value = 0
pad_value = 0
delay = 0.1
pad_channel = 0
fieldnames = ["x_value", "pad_value"]
#Create SPI
spi = spidev.SpiDev()
spi.open(0, 0)
spi.max_speed_hz=1000000
def readadc(adcnum):
# read SPI data from the MCP3008, 8 channels in total
if adcnum > 7 or adcnum < 0:
return -1
r = spi.xfer2([1, 8 + adcnum << 4, 0])
data = ((r[1] & 3) << 8) + r[2]
return data
#Animate graph
def animate(i):
data = pd.read_csv('data.csv')
x = data['x_value']
y = data['pad_value']
plt.cla()
plt.plot(x, y)
plt.style.use('fivethirtyeight')
plt.tight_layout()
plt.show(block=False)
#Write headers to CSV file
with open('data.csv', 'w') as csv_file:
csv_writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
csv_writer.writeheader()
#Append values to CSV file
while True:
with open('data.csv', 'a') as csv_file:
csv_writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
info = {
"x_value": x_value,
"pad_value": pad_value
}
csv_writer.writerow(info)
#Update values
x_value += 1
pad_value = readadc(pad_channel)
print(x_value, pad_value)
time.sleep(delay)
plt.style.use('fivethirtyeight')
ani = FuncAnimation(plt.gcf(), animate, interval=100)
plt.tight_layout()
plt.show(block=False)
Is there a simple way to combine these two?
You can interactively change data on the canvas by setting the plot to interactive mode like this:
import matplotlib.pyplot as plt
import numpy as np
import time
phase = 0
delay = 0.1
t = 0
x = np.linspace(t, t+2, 200)
data = 0.5*np.sin(x)+.5
#Setting interactive mode on plt
plt.ion()
#create new figure
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_ylim((-1.1, 1.1))
line1, = ax.plot(x, data, 'b-')
while True:
#I generate some random data, you will use your data (from the csv)
x = np.linspace(t, t+2, 200)
data = np.sin(x)
line1.set_ydata(data)
line1.set_xdata(x)
#Set the xlim to contain new data
ax.set_xlim((x[0], x[-1]))
#This shows newly set xdata and ydata on the plot
fig.canvas.draw()
#You need to use plt.pause otherwise the plot won't show up
plt.pause(0.001)
time.sleep(delay)
#Just another variable I used to generate new data
t += 1
See this link for the whole tutorial.
I have been trying to create a live plot by matplotlib.
My trial code is this.
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
import time
from PySide import QtCore
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
N=100
def animate(j):
graph_data = open('example.txt','r').read()
lines = graph_data.split('\n')
xs=[]
ys=[]
for line in lines:
if len(line) > 1:
x,y = line.split(',')
xs.append(float(x))
ys.append(float(y))
ax.clear()
ax.plot(xs, ys)
def initFile():
fid = open('example.txt','w')
fid.write('')
fid.close()
for i in range(0,N):
fid = open('example.txt', 'a')
fid.write(str(i) + ',' + str(0) + '\n')
fid.close()
def updateFile():
global wThread
wThread = writeThread()
wThread.start()
class writeThread(QtCore.QThread):
def __init__(self, parent=None):
QtCore.QThread.__init__(self, parent)
self.exiting = False
def run(self):
i=0
while 1:
fid = open('example.txt', 'a')
fid.write(str(N+i) + ',' + str(np.sin(2*np.pi*0.05*i)) + '\n')
time.sleep(0.1)
i=i+1
fid.close()
initFile()
updateFile()
ani = animation.FuncAnimation(fig, animate, interval = 200)
plt.show()
It works well. But, the plot points are accumulated. I want to keep up the number of points in my plot as N.
How could I do that?
Simply restrict the size of your array/list to the last N points:
def animate(j):
(...)
ax.clear()
ax.plot(xs[-N:], ys[-N:])
I create code to read a csv file.
the error message is
File "C:/Users/amori/Desktop/programas de python/Nova
pasta/alg1.py", line 17, in get_data
csvFileReader = csv.reader(csvfile)
NameError: name 'csvfile' is not defined
Can someone help me with this code? what I am doing wrong?
import csv
import numpy as np
from sklearn.svm import SVR
import matplotlib.pyplot as plt
dates = []
prices = []
def get_data(filename):
with open(filename, 'r') as csvfile_:
csvFileReader = csv.reader(csvfile)
next(csvFileReader)
for row in csvFileReader:
dates.append(int(row[0].split('-')[0]))
prices.append(float(row[1]))
return
def predict_prices(dates, proces, x):
dates = np.reshape(dates,(len(dates),1))
svr_len = SVR(kernal = 'liner', c = 1e3)
svr_poly = SVR(kernal = 'poly', c = 1e3, degree = 2)
svr_rbf = SVR(kernal = 'rbf', c = 1e3, gamma = 0.1)
svr_lin.fit(dates, prices)
svr_ply.fit(dates, prices)
svr_rbf.fit(dates, prices)
plt.scatter(dates, prices, color='black', label='data')
plt.plot(dates, svr_rbf.predict(dates), color='red', label='RBF model')
plt.plot(dates, svr_lin.predict(dates), color='green', label='linear model')
plt.plot(dates, svr_poly.predict(dates), color='blue', label='Polynomial model')
plt.xlavell('date')
plt.title('price')
plt.title('support vector regression')
plt.legend()
plt.show()
return svr_rbf.predict(x)[0], svr_lin.predict(x)[0], svr_poly.predict(x)[0]
get_data('aapl.csv')
predicted_price = predict_pice[dates, prices, 29]
print(predicted_price)
you have an underscore that's not wanted:
with open(filename, 'r') as csvfile_:
should be
with open(filename, 'r') as csvfile: