Image¶

class sofia_redux.scan.source_models.maps.image.Image(data=None, blanking_value=None, dtype=<class 'float'>, shape=None, unit=None)[source]¶

Bases: FitsData

Creates an Image instance.

This class is an extension of the FitsData class and is used to provide additional handling for FITS image HDUs.

Parameters:

datanumpy.ndarray, optional: Data to initialize the flagged array with. If supplied, sets the shape of the array. Note that the data type will be set to that defined by the dtype parameter.
blanking_valueint or float, optional: The blanking value defines invalid values in the data array. This is the equivalent of defining a NaN value.
dtypetype, optional: The data type of the data array.
shapetuple (int), optional: The shape of the data array. This will only be relevant if data is not defined.
unitstr or units.Unit or units.Quantity, optional: The data unit.

Methods Summary

`auto_crop`()	Auto crop the image data.
`copy`([with_contents])	Return a copy of the image.
`crop`(ranges)	Crop the image to the required dimensions.
`destroy`()	Destroy the image data.
`edit_header`(header)	Edit a FITS header using information in the current map.
`get_asymmetry`(grid, center_index, angle, ...)	Return the Asymmetry.
`get_asymmetry_2d`(grid, center_index, angle, ...)	Return the 2-D asymmetry.
`get_data_asymmetry`(data, valid, grid, ...)	Return the asymmetry for the given data.
`get_id`()	Return the image ID.
`get_image`([dtype, blanking_value])	Return an image copy, optionally changing type and blanking value.
`get_valid_data`([default])	Return a copy of the image data, optionally replacing invalid points.
`new_image`()	Return a new image.
`parse_header`(header)	Parse a FITS header and apply to the image.
`read_hdu`(image_hdu)	Read and apply an HDU.
`read_hdul`(hdul, hdu_index)	Read a specific HDU image from an HDU list, and return an image.
`renew`()	Renew the image by clearing all data.
`set_data`(data[, change_type])	Set the image data array.
`set_id`(image_id)	Set the image ID.
`transpose`()	Transpose the data array.

Methods Documentation

auto_crop()[source]¶

Auto crop the image data.

The data is cropped to the extent of valid data point indices.

Returns:

None

copy(with_contents=True)[source]¶

Return a copy of the image.

Parameters:

with_contentsbool, optional: If True, paste the contents of this image onto the new one.

Returns:

Image

crop(ranges)[source]¶

Crop the image to the required dimensions.

Parameters:

rangesnumpy.ndarray (int,): The ranges to set crop the data to. Should be of shape (n_dimensions, 2) where ranges[0, 0] would give the minimum crop limit for the first dimension and ranges[0, 1] would give the maximum crop limit for the first dimension. In this case, the ‘first’ dimension is in numpy format. i.e., (y, x) for a 2-D array. Also note that the upper crop limit is inclusive so a range of (0, 3) includes indices [0, 1, 2, 3].

Returns:

None

destroy()[source]¶

Destroy the image data.

Returns:

None

edit_header(header)[source]¶

Edit a FITS header using information in the current map.

Parameters:

headerastropy.io.fits.header.Header

Returns:

None

get_asymmetry(grid, center_index, angle, radial_range)[source]¶

Return the Asymmetry.

The asymmetry and rms are calculated via:

asymmetry = sum(d * c) / sum(|d|)
rms = sum(|c|) / sum(|d|)

where:

c = cos(arctan2(dy, dx) - angle)
dx = x - x_0
dy = y - y_0

The sum occurs over all points within the provided radial_range about the center_index. The coordinates (x, y) are the projected coordinates of the image map indices onto the grid, and (x_0, y_0) is the center_index projected onto the same grid. The data values d are the image data values.

Parameters:

gridGrid2D: The grid used to convert image pixel locations to the coordinate system in which to calculate the asymmetry.
center_indexCoordinate2D: The center index on the image (x_pix, y_pix) from which to calculate the asymmetry.
angleunits.Quantity: The rotation of the image with respect to the asymmetry,
radial_rangeRange: The range (in grid units) about center_index on which to base the asymmetry calculation.

Returns:

asymmetry, asymmetry_rmsfloat, float: The asymmetry and asymmetry RMS.

get_asymmetry_2d(grid, center_index, angle, radial_range)[source]¶

Return the 2-D asymmetry.

Calculates the asymmetry in both the x and y directions. The y asymmetry values are calculated by applying an addition rotation of 90 degrees to supplied angle during the asymmetry derivation.

Parameters:

gridGrid2D: The grid used to convert image pixel locations to the coordinate system in which to calculate the asymmetry.
center_indexCoordinate2D: The center index on the image (x_pix, y_pix) from which to calculate the asymmetry.
angleunits.Quantity: The rotation of the image with respect to the asymmetry,
radial_rangeRange: The range (in grid units) about center_index on which to base the asymmetry calculation.

Returns:

asymmetryAsymmetry2D

static get_data_asymmetry(data, valid, grid, center_index, angle, radial_range)[source]¶

Return the asymmetry for the given data.

Parameters:

datanumpy.ndarray (float): The 2-D data for which to calculate the asymmetry of shape (ny, nx)
validnumpy.ndarray (bool): A mask for the data of shape (ny, nx) where False excludes any given element from inclusion in the calculation.
gridGrid2D: The grid used to convert image pixel locations to the coordinate system in which to calculate the asymmetry.
center_indexCoordinate2D: The center index on the image (x_pix, y_pix) from which to calculate the asymmetry.
angleunits.Quantity: The rotation of the image with respect to the asymmetry,
radial_rangeRange: The range (in grid units) about center_index on which to base the asymmetry calculation.

Returns:

asymmetry, asymmetry_rmsfloat, float: The asymmetry and asymmetry RMS.

get_id()[source]¶

Return the image ID.

Returns:

image_idstr

get_image(dtype=None, blanking_value=None)[source]¶

Return an image copy, optionally changing type and blanking value.

Parameters:

dtypetype, optional: The image data type.
blanking_valueint or float, optional: The new image blanking value.

Returns:

imageImage

get_valid_data(default=None)[source]¶

Return a copy of the image data, optionally replacing invalid points.

Parameters:

defaultint or float, optional: The value to replace blanked values with.

Returns:

numpy.ndarray or None

new_image()[source]¶

Return a new image.

Returns:

imageImage

parse_header(header)[source]¶

Parse a FITS header and apply to the image.

Parameters:

headerastropy.io.fits.header.Header: The FITS header to parse.

Returns:

None

read_hdu(image_hdu)[source]¶

Read and apply an HDU.

Parameters:

image_hduastropy.io.fits.hdu.image.ImageHDU: The image HDU to read and apply.

Returns:

None

classmethod read_hdul(hdul, hdu_index)[source]¶

Read a specific HDU image from an HDU list, and return an image.

Parameters:

hdulastropy.io.fits.hdu.hdulist.HDUList: The HDU list to read.
hdu_indexint: The index of the HDU in the provided hdul to read.

Returns:

imageImage

renew()[source]¶

Renew the image by clearing all data.

Returns:

None

set_data(data, change_type=False)[source]¶

Set the image data array.

Parameters:

datanumpy.ndarray or FlaggedArray: A 2-dimensional image array.
change_typebool, optional: If True, change the data type to that of the data.

Returns:

None

set_id(image_id)[source]¶

Set the image ID.

Parameters:

image_idstr

Returns:

None

transpose()[source]¶

Transpose the data array.

Returns:

None

Navigation

Image¶