I am new to Python and Spyder. I am using Python 3.7 (Anaconda 3). I cannot get my graph after labelling x & y axis using plt.show() & also plt.draw() does not work either.
import os
import numpy as np
import matplotlib.pyplot as plt
time=[1,2,4]
data_list_Ch4=[1,3,5]
plt.plot(time, data_list_Ch4)
plt.xlabel("Time")
plt.ylabel("Channel")
plt.show()
screen shot of Spyder ide
I installed Matplotlib via Anaconda from here: https://anaconda.org/conda-forge/matplotlib
I used the very first command in Anaconda prompt.
But when I tried to plot from python (Spyder) as the following, I get the message:
ModuleNotFoundError: No module named 'matplotlib.plot'
import numpy as np
import matplotlib.plot as plt
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
plt.plot(x,y)
I have installed numpy, pandas and such using the same method and they work well.
How can I fix this?
Thank you so much.
matplotlib.pyplot is a state-based interface to matplotlib. pyplot is mainly intended for interactive plots and simple cases of programmatic plot generation. Therefore, whenever trying to work with graphs and what is commonly known and informally often referred as matplotlib you should import matplotlib.pyplot as plt:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
plt.plot(x,y)
Maybe I am being extremely slow today, but I swear this has worked for me before and was showing a plot, now it returns a list with a single Lines object:
%matplotlib inline
import matplotlib.pyplot as plt
values = [0.1, 0.2, 0.3, 0.4, 0.5]
f = plt.figure()
ax = f.add_subplot(111)
ax.plot(values)
And I get <matplotlib.lines.Line2D at 0x7f04a33d6cc0> instead of a plot...
However, if I use this %matplotlib nbagg and do the same it works. I then stop the interaction and I get my desired result. What is going on here?
My versions:
python 3.6.5
matplotlib 2.2.2
jupyter 4.4.0
ipython 6.4.0
ipywidgets 7.2.1
Thanks
Python 3.5, windows 10 Pro.
I'm trying to continuously plot an 8x8 array of pixels (for the sake of the question I'll just use random data, but in the real thing I'm reading from a serial port).
I can do it using a while loop, but I need to switch over to matplotlib.animation.FuncAnimation and I can't get it to work. I've tried looking at the help files and tried to follow examples from matplotlib.org here, but I've not been able to follow it.
Can someone help me figure out how to continuously plot an 8x8 array of pixels using FuncAnimation and pcolormesh? Here is what I've got so far:
import scipy as sp
import matplotlib.pyplot as plt
from matplotlib import animation
plt.close('all')
y = sp.rand(64).reshape([8,8])
def do_something():
y = sp.rand(64).reshape([8,8])
fig_plot.set_data(y)
return fig_plot,
fig1 = plt.figure(1,facecolor = 'w')
plt.clf()
fig_plot = plt.pcolormesh(y)
fig_ani = animation.FuncAnimation(fig1,do_something)
plt.show()
If you want to see the while loop code, just so you know exactly what I'm trying to reproduce, see below.
import scipy as sp
import matplotlib.pyplot as plt
plt.figure(1)
plt.clf()
while True:
y = sp.rand(64).reshape([8,8])
plt.pcolormesh(y)
plt.show()
plt.pause(.000001)
I was able to find a solution using imshow instead of pcolormesh. In case anyone else is struggling with the same issues I had, I've posted the working code below.
import scipy as sp
import matplotlib.pyplot as plt
import matplotlib.animation as animation
Hz = sp.rand(64).reshape([8,8]) # initalize with random data
fig = plt.figure(1,facecolor='w')
ax = plt.axes()
im = ax.imshow(Hz)
im.set_data(sp.zeros(Hz.shape))
def update_data(n):
Hz = sp.rand(64).reshape([8,8]) # More random data
im.set_data(Hz)
return
ani = animation.FuncAnimation(fig, update_data, interval = 10, blit = False, repeat = False)
fig.show()
I am trying to put animations in an iPython notebook and am not finding a solution. I saw one post that discussed using interactive widgets, but there are a couple problems that I have with this: First, every example I see with widgets uses a slider or some other input, whereas I just want the animation to run automatically when the cell is run. Second, all the documentation seems out of date on Jupyter's site--whenever I download and run their notebooks I get these messages about certain modules being deprecated and then later in the file something fails to run, presumably because they're trying to import and access files that no longer exist.
I've seen a few other pages on the topic but they often require downloading binaries or other modules, but I'm partly using this to teach some students Math and I've gotten them to download Anaconda--I was hoping to not further confuse the issue by making them also download and install more complicated things all while spending time not talking about the Math.
So in short, is there a way that I can create animations in an iPython notebook that only require the use of simple import commands that will run out-of-the-box so to speak with the software that comes from Anaconda?
[Edit: I should also note that I've used Tkinter to make animations, and I could make one in matplotlib I'm sure. So if there were a way to get the animations you produce with those to render in an iPython notebook, that would certainly be a working solution for me.]
[Further edit: I suppose I could also say what I am hoping to animate at the moment, although I really want to be pretty flexible about the range of things I could animate if I decide to. Right now I'm trying to make a digital clock that displays each digit in Sumerian base-60 numerals to illustrate a different counting and base system. So it should initially display | then after a second || and so on until ten gets represented as < and so on until eventually the clock ticks over to a minute where it now displays |:| to represent one minute, one second.]
[Note to future humans: If you're implementing some animation and are willing to publicly host it, please leave a link to it in the comments! I'm curious to see how people are making animations these days, and also a little curious to see what they're animating.]
Some options you have for animating plots in Jupyter/IPython, using matplotlib:
Using display in a loop Use IPython.display.display(fig) to display a figure in the output. Using a loop you would want to clear the output before a new figure is shown. Note that this technique gives in general not so smooth resluts. I would hence advice to use any of the below.
import matplotlib.pyplot as plt
import matplotlib.animation
import numpy as np
from IPython.display import display, clear_output
t = np.linspace(0,2*np.pi)
x = np.sin(t)
fig, ax = plt.subplots()
l, = ax.plot([0,2*np.pi],[-1,1])
animate = lambda i: l.set_data(t[:i], x[:i])
for i in range(len(x)):
animate(i)
clear_output(wait=True)
display(fig)
plt.show()
%matplotlib notebook Use IPython magic %matplotlib notebook to set the backend to the notebook backend. This will keep the figure alive instead of displaying a static png file and can hence also show animations.
Complete example:
%matplotlib notebook
import matplotlib.pyplot as plt
import matplotlib.animation
import numpy as np
t = np.linspace(0,2*np.pi)
x = np.sin(t)
fig, ax = plt.subplots()
l, = ax.plot([0,2*np.pi],[-1,1])
animate = lambda i: l.set_data(t[:i], x[:i])
ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
plt.show()
%matplotlib tk Use IPython magic %matplotlib tk to set the backend to the tk backend. This will open the figure in a new plotting window, which is interactive and can thus also show animations.
Complete example:
%matplotlib tk
import matplotlib.pyplot as plt
import matplotlib.animation
import numpy as np
t = np.linspace(0,2*np.pi)
x = np.sin(t)
fig, ax = plt.subplots()
l, = ax.plot([0,2*np.pi],[-1,1])
animate = lambda i: l.set_data(t[:i], x[:i])
ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
plt.show()
Convert animation to mp4 video (option mentionned by #Perfi already):
from IPython.display import HTML
HTML(ani.to_html5_video())
or use plt.rcParams["animation.html"] = "html5" at the beginning of the notebook.
This will require to have ffmpeg video codecs available to convert to HTML5 video. The video is then shown inline. This is therefore compatible with %matplotlib inline backend. Complete example:
%matplotlib inline
import matplotlib.pyplot as plt
plt.rcParams["animation.html"] = "html5"
import matplotlib.animation
import numpy as np
t = np.linspace(0,2*np.pi)
x = np.sin(t)
fig, ax = plt.subplots()
l, = ax.plot([0,2*np.pi],[-1,1])
animate = lambda i: l.set_data(t[:i], x[:i])
ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
ani
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.animation
import numpy as np
t = np.linspace(0,2*np.pi)
x = np.sin(t)
fig, ax = plt.subplots()
l, = ax.plot([0,2*np.pi],[-1,1])
animate = lambda i: l.set_data(t[:i], x[:i])
ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
from IPython.display import HTML
HTML(ani.to_html5_video())
Convert animation to JavaScript:
from IPython.display import HTML
HTML(ani.to_jshtml())
or use plt.rcParams["animation.html"] = "jshtml" at the beginning of the notebook.
This will display the animation as HTML with JavaScript. This highly compatible with most new browsers and also with the %matplotlib inline backend. It is available in matplotlib 2.1 or higher.
Complete example:
%matplotlib inline
import matplotlib.pyplot as plt
plt.rcParams["animation.html"] = "jshtml"
import matplotlib.animation
import numpy as np
t = np.linspace(0,2*np.pi)
x = np.sin(t)
fig, ax = plt.subplots()
l, = ax.plot([0,2*np.pi],[-1,1])
animate = lambda i: l.set_data(t[:i], x[:i])
ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
ani
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.animation
import numpy as np
t = np.linspace(0,2*np.pi)
x = np.sin(t)
fig, ax = plt.subplots()
l, = ax.plot([0,2*np.pi],[-1,1])
animate = lambda i: l.set_data(t[:i], x[:i])
ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
from IPython.display import HTML
HTML(ani.to_jshtml())
You may find this tutorial interesting.
If you can turn what you need into a matplotlib animation, and I'm fairly sure from your description that it's possible, you can then use
from matplotlib import rc, animation
rc('animation', html='html5')
and display your animation using
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=N, interval=20, blit=True)
anim
Might come in handy!
Jupyter widgets is a good way of displaying animations. The code below displays an animated gif.....
from ipywidgets import Image
from IPython import display
animatedGif = "animatedGifs/01-progress.gif" #path relative to your notebook
file = open(animatedGif , "rb")
image = file.read()
progress= Image(
value=image,
format='gif',
width=100,
height=100)
display.display(progress)
You can close this animation using:
progress.close()
N.B. I found a few nice animated gifs from http://www.downgraf.com/inspiration/25-beautiful-loading-bar-design-examples-gif-animated/.
I had a similar problem, and this question helped me get started. I put together a notebook that illustrates using FuncAnimation along with good explanations of why the notebook does some things the way it does. It also has links to instructions on FFmpeg. It also has links to the examples I used in developing and understanding of animations. You can view my contribution at:
Animation Illustration
For your question, you might find interactive sliders a better tool. I also created a notebook which demonstrates interactive widgets in Jupyter. It is available here; however, the interactive parts don't work there.
Both are available in a GitHub Repostory