Metadata-Version: 2.1
Name: figurestream
Version: 1.2.6
Summary: A Matplotlib.Figure fork with real-time plot streaming features.
Download-URL: https://github.com/UN-GCPDS/matplotlib-figurestream
Author: Yeison Cardona
Author-email: yencardonaal@unal.edu.co
Maintainer: Yeison Cardona
Maintainer-email: yencardonaal@unal.edu.co
License: BSD-2-Clause
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Software Development :: Embedded Systems
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: System :: Hardware :: Hardware Drivers
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# Matplotlib-FigureStream

A backend for serve Matplotlib animations as web streams.

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[![Documentation Status](https://readthedocs.org/projects/figurestream/badge/?version=latest)](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.


