# Matplotlib-FigureStream
A backend for serve Matplotlib animations as web streams.







[](https://figurestream.readthedocs.io/en/latest/?badge=latest)
## Instalation
```python
pip install figurestream
```
## Bare minimum
By default, the stream serves on http://localhost:5000
```python
# FigureStream replace any Figure object
from figurestream import FigureStream
import numpy as np
from datetime import datetime
# FigureStream can be used like any Figure object
stream = FigureStream()
sub = stream.add_subplot(111)
x = np.linspace(0, 3, 1000)
# Update animation loop
while True:
sub.clear() # clear the canvas
# ------------------------------------------------------------------------
# Any plot operation
sub.set_title('FigureStream')
sub.set_xlabel('Time [s]')
sub.set_ylabel('Amplitude')
sub.plot(x, np.sin(2 * np.pi * 2 * (x + datetime.now().timestamp())))
sub.plot(x, np.sin(2 * np.pi * 0.5 * (x + datetime.now().timestamp())))
# ------------------------------------------------------------------------
stream.feed() # push the frame into the server
```
For fast updates is recommended to use `set_data`, `set_ydata` and `set_xdata` instead of clear and draw again in each loop, also `FigureStream` can be implemented from a custom class.
```python
# FigureStream replace any Figure object
from figurestream import FigureStream
import numpy as np
from datetime import datetime
class FastAnimation(FigureStream):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
axis = self.add_subplot(111)
self.x = np.linspace(0, 3, 1000)
# ------------------------------------------------------------------------
# Single time plot configuration
axis.set_title('FigureStream')
axis.set_xlabel('Time [s]')
axis.set_ylabel('Amplitude')
axis.set_ylim(-1.2, 1.2)
axis.set_xlim(0, 3)
# Lines objects
self.line1, *_ = axis.plot(self.x, np.zeros(self.x.size))
self.line2, *_ = axis.plot(self.x, np.zeros(self.x.size))
# ------------------------------------------------------------------------
self.anim()
def anim(self):
# Update animation loop
while True:
# ------------------------------------------------------------------------
# Update only the data values is faster than update all the plot
self.line1.set_ydata(np.sin(2 * np.pi * 2 * (self.x + datetime.now().timestamp())))
self.line2.set_ydata(np.sin(2 * np.pi * 0.5 * (self.x + datetime.now().timestamp())))
# ------------------------------------------------------------------------
self.feed() # push the frame into the server
if __name__ == '__main__':
FastAnimation()
```
## Set host, port and endpoint
If we want to serve the stream in a different place we can use the parameters `host`, `port` and `endpoint`, for example:
```python
FigureStream(host='0.0.0.0', port='5500', endpoint='figure.jpeg')
```
Now the stream will serve on http://localhost:5500/figure.jpeg and due the `0.0.0.0` host is accesible for any device on network.
By default `host` is `localhost`, `port` is `5000` and endopoint is empty.