Astrospec

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This project is used to reconstruct image from raw video captured by the spectroheliograph

Highlights

• Clear API interface
• Algorithm with sub-pixel interpolation for wavelength correction
• Additional features such as color mapping
• Advanced algorithm to remove stray light (view comparison)

Installation

pip install astrospec

Getting Started

For end users

# single file input, generate 16-bit png files at the sub-folder named "output/img", no normalization, no color mapping
ascli -i "<SER file>" --raw

# single file input, generate png files at the sub-folder named "output/img"
ascli -i "<SER file>" [-c color_map_name] [-nb brightness(default=1)]

# process all .ser files in the folder, generate png files at the sub-folder named "output/img"
ascli -f "<folder>" [-c color_map_name] [-nb brightness(default=1)]

# color_map_name（optional）:
# - orange-enhanced (default)
# - enhanced
# - linear

For developers

example 1

import astrospec as ass
import matplotlib.pyplot as plt

img = ass.raw_file_to_image('input.ser')
plt.imshow(img[0])
plt.show()

example 2

import astrospec as ass
import matplotlib.pyplot as plt

img = ass.raw_file_to_image('input.ser', color_map_name='linear')
plt.imshow(img[0], cmap='gray')
plt.show()

API

• Reconstruct image from the ser file, return the reconstructed image in the original value space, np.array(float64)

def raw_file_to_raw_image(file, shifts = [0], verbose = 0, return_details = False):
    """
    raw_file_to_raw_image reconstruct image from raw video (ser file), return the reconstructed image, np.array(float64)

    :param file: input file path
    :param shifts: the wavelength offsets in pixels, e.g. [-0.5, 0, 0.5] returns 3 images in corresponding wavelengths
    :param verbose: 0~3，log information level
    :param return_details: whether to return data from intermediate steps
    :return: reconstructed image, np.array(float64)
    """ 

• Reconstruct image from the ser file, return the reconstructed image after color mapping, np.array(uint8)

def raw_file_to_image(file, shifts = [0], color_map_name = 'orange-enhanced', verbose = 0):
    """
    raw_file_to_image reconstruct image from raw video (ser file), return the reconstructed, normalized, color mapped image, np.array(uint8)

    :param file: input file path
    :param shifts: the wavelength offsets in pixels, e.g. [-0.5, 0, 0.5] returns 3 images in corresponding wavelengths
    :param color_map_name: color map, values: orange-enhanced (default), enhanced, linear
    :param verbose: 0~3，log information level
    :return: reconstructed, normalized, color mapped image, np.array(uint8)
    """ 

• Reconstruct image from the ser file, write reconstructed image to file(s)

def raw_file_to_file(file, output_file, shifts = [0], color_map_name = 'orange-enhanced', verbose = 0):
    """
    raw_file_to_file reconstruct image from raw video (ser file), write reconstructed, normalized, color mapped image to file(s)

    :param file: input file path
    :param output_file: output file path
    :param shifts: the wavelength offsets in pixels, e.g. [-0.5, 0, 0.5] returns 3 images in corresponding wavelengths
    :param color_map_name: color map, values: orange-enhanced (default), enhanced, linear
    :param verbose: 0~3，log information level
    :return: None
    """ 

Stray light remove

Reference

1. SolEx - The design of a DIY spectroheliograph by Valerie Desnoux, with very detailed introduction, which is worth reading carefully.
2. DIY迷你太阳光谱仪 by 阴天wnova酱 - The design of another DIY mini-spectroheliograph
3. Solex_ser_recon - An open-source reconstruct software made by Valerie Desnoux
4. SHG - Another open-source reconstruct software
5. 又能看光谱又能拍摄太阳的太阳光谱仪 by 摄日者天文
6. 太阳光谱扫描成像 by Harold Liang - My DIY and observation records

License

Astrospec has a MIT-style license, as found in the LICENSE file.