<reponame>MichaelMedford/fringez
#!/usr/bin/env python
"""utils.py"""
import numpy as np
import glob
import os
import shutil
from astropy.io import fits
import shutil


def flatten_images(images):
    """Flattens images for use in 1D analysis"""

    # If parallelFlag and non-root rank is passing in None
    if images is None:
        return None, None

    image_shape = images[0].shape
    images_flattened = []
    for i, image in enumerate(images):
        if i % 10 == 0:
            print('Flattening image %i/%i' % (i, len(images)))
        images_flattened.append(image.flatten())
    images_flattened = np.array(images_flattened)

    return images_flattened, image_shape


def create_fits(image_name,
                data,
                header=None):
    """Creates a fits image with an optional header

    Uses the astropy.io.fits pacakge to create a fits image.
    WARNING : THIS WILL OVERWRITE ANY FILE ALREADY NAMED 'image_name'.
    """
    # Creates the Header Data Unit
    hdu = fits.PrimaryHDU(data)

    # Adds the 'header' if None is not selected
    if header is not None:
        hdu.header = header

    # Remove the image if it currently exists
    if os.path.exists(image_name):
        os.remove(image_name)

    # Write the fits image to disk
    hdu.writeto(image_name)


def update_fits(image_name,
                data=None,
                header=None):
    """Safely replaces a fits image with new data and/or header

    Uses the astropy.io.fits pacakge. astropy.io.fits.writeto contains a
    clobber parameter which should allow replacement of one fits file by
    another of the same name with new data(s) and/or header(s). However if the
    rewrite is interupted then the original file is lost as well. This method
    eliminates this risk by guaranteeing that there is always a time where the
    original data is still safely on disk.

    Args:
        image_name : str
            Name of the image.
        data : numpy.ndarray
            2-dimensional array of 'float' or 'int'.
        header : astropy.io.fits.header.Header
            Header of the fits image.

    Returns:
        None

    """

    if data is None and header is None:
        with fits.open(image_name) as f:
            data = f[0].data
            header = f[0].header

    # Write the fits image to a temporary file
    image_tmp = image_name.replace("fits", "fits.tmp")
    fits.writeto(image_tmp,
                 data,
                 header,
                 overwrite=True)

    # Remove the original image
    if os.path.exists(image_name):
        os.remove(image_name)

    # Rename the temporary image name to the original image name
    shutil.move(image_tmp, image_name)


def generate_random_ds9_list(n_random=6):
    """ Generates a random list of images to be viewed in ds9
    Viewed with: ds9 -zscale $(<ds9.list) """

    fname_arr = glob.glob('ztf*sciimg.clean.fits')
    fname_arr.sort()

    n_images = min(n_random, len(fname_arr))

    idx_arr = np.random.choice(np.arange(len(fname_arr)), n_images,
                               replace=False)
    with open('ds9.list', 'w') as f:
        for idx in idx_arr:
            f.write('%s\n' % fname_arr[idx])
            f.write('%s\n' % fname_arr[idx].replace('.clean', ''))

#!/usr/bin/env python
"""utils.py"""
import numpy as np
import glob
import os
import shutil
from astropy.io import fits
import shutil


def flatten_images(images):
    """Flattens images for use in 1D analysis"""

    # If parallelFlag and non-root rank is passing in None
    if images is None:
        return None, None

    image_shape = images[0].shape
    images_flattened = []
    for i, image in enumerate(images):
        if i % 10 == 0:
            print('Flattening image %i/%i' % (i, len(images)))
        images_flattened.append(image.flatten())
    images_flattened = np.array(images_flattened)

    return images_flattened, image_shape


def create_fits(image_name,
                data,
                header=None):
    """Creates a fits image with an optional header

    Uses the astropy.io.fits pacakge to create a fits image.
    WARNING : THIS WILL OVERWRITE ANY FILE ALREADY NAMED 'image_name'.
    """
    # Creates the Header Data Unit
    hdu = fits.PrimaryHDU(data)

    # Adds the 'header' if None is not selected
    if header is not None:
        hdu.header = header

    # Remove the image if it currently exists
    if os.path.exists(image_name):
        os.remove(image_name)

    # Write the fits image to disk
    hdu.writeto(image_name)


def update_fits(image_name,
                data=None,
                header=None):
    """Safely replaces a fits image with new data and/or header

    Uses the astropy.io.fits pacakge. astropy.io.fits.writeto contains a
    clobber parameter which should allow replacement of one fits file by
    another of the same name with new data(s) and/or header(s). However if the
    rewrite is interupted then the original file is lost as well. This method
    eliminates this risk by guaranteeing that there is always a time where the
    original data is still safely on disk.

    Args:
        image_name : str
            Name of the image.
        data : numpy.ndarray
            2-dimensional array of 'float' or 'int'.
        header : astropy.io.fits.header.Header
            Header of the fits image.

    Returns:
        None

    """

    if data is None and header is None:
        with fits.open(image_name) as f:
            data = f[0].data
            header = f[0].header

    # Write the fits image to a temporary file
    image_tmp = image_name.replace("fits", "fits.tmp")
    fits.writeto(image_tmp,
                 data,
                 header,
                 overwrite=True)

    # Remove the original image
    if os.path.exists(image_name):
        os.remove(image_name)

    # Rename the temporary image name to the original image name
    shutil.move(image_tmp, image_name)


def generate_random_ds9_list(n_random=6):
    """ Generates a random list of images to be viewed in ds9
    Viewed with: ds9 -zscale $(<ds9.list) """

    fname_arr = glob.glob('ztf*sciimg.clean.fits')
    fname_arr.sort()

    n_images = min(n_random, len(fname_arr))

    idx_arr = np.random.choice(np.arange(len(fname_arr)), n_images,
                               replace=False)
    with open('ds9.list', 'w') as f:
        for idx in idx_arr:
            f.write('%s\n' % fname_arr[idx])
            f.write('%s\n' % fname_arr[idx].replace('.clean', ''))
#!/usr/bin/env python utils.py Flattens images for use in 1D analysis # If parallelFlag and non-root rank is passing in None Creates a fits image with an optional header      Uses the astropy.io.fits pacakge to create a fits image.     WARNING : THIS WILL OVERWRITE ANY FILE ALREADY NAMED 'image_name'. # Creates the Header Data Unit # Adds the 'header' if None is not selected # Remove the image if it currently exists # Write the fits image to disk Safely replaces a fits image with new data and/or header      Uses the astropy.io.fits pacakge. astropy.io.fits.writeto contains a     clobber parameter which should allow replacement of one fits file by     another of the same name with new data(s) and/or header(s). However if the     rewrite is interupted then the original file is lost as well. This method     eliminates this risk by guaranteeing that there is always a time where the     original data is still safely on disk.      Args:         image_name : str             Name of the image.         data : numpy.ndarray             2-dimensional array of 'float' or 'int'.         header : astropy.io.fits.header.Header             Header of the fits image.      Returns:         None # Write the fits image to a temporary file # Remove the original image # Rename the temporary image name to the original image name Generates a random list of images to be viewed in ds9     Viewed with: ds9 -zscale $(<ds9.list)