Fast Imaging Solar Spectrograph

FISSPy

FISSPy Package

An open-source Python library for GST/FISS data analysis.

FISS Coloar Map

You can call the FISS colormap for each color filters

In [3]:
import numpy as np
import matplotlib.pyplot as plt
import fisspy

%matplotlib notebook
In [11]:
a = np.arange(255)
fig, ax = plt.subplots(2,1, figsize=(6,3))

im_cm_ha = ax[0].imshow(a*np.ones((20, 255)), cmap=fisspy.cm.ha, origin='lower')
ax[0].set_title(r'H$\alpha$')
im_cm_ca = ax[1].imshow(a*np.ones((20, 255)), cmap=fisspy.cm.ca, origin='lower')
ax[1].set_title('Ca II')
fig.tight_layout()

Make image files to video

There are lots of way to make video or movie files in Python, such as matplotlib or ffmpeg etc...

In this pacakge, we use the matplotlib animation method which is generally used in python.

img2video

fisspy.makevideo.img2video(imglist, fps, output='video.mp4', show=False, **kwargs)

Make a video file from the set of images.

Default output directory is the same as the images, but you can change the output directory from the 'output' parameter.

Parameters:

  • imglist (list) - list of image files.
  • fps (int) - frame per seconds
  • output (str) - output data file name. Default output directory is same as the file directory of image direcotry.
  • show (bool, optional) - Show the animation. Defalut is False.
  • **kwargs - Keyword arguments of ~matplotlib.animation.FunctionAnimation.save function (writer, dpi, codec, bitrate, extra_args, metadata, extra_anim, progress_callback)

Returns:

  • None

Example

>>> from fisspy import makevideo
    >>> from glob import glob
    >>> imglist = glob('/data/img/*.png')
    >>> makevideo.img2video(imglist, 10, 'video.mp4')