autolens.Mask1D#

class Mask1D[source]#

Bases: Mask

A 1D mask, representing 1D data on a uniform line of pixels with equal spacing.

When applied to 1D data it extracts or masks the unmasked image pixels corresponding to mask entries that are False or 0).

The mask also defines the geometry of the 1D data structure it is paired to, for example how every pixel coordinate on the 1D line of data converts to physical units via the pixel_scales and origin parameters and a sub-grid which is used for performing calculations via super-sampling.

Parameters:

mask (Union[ndarray, List]) – The ndarray of shape [total_pixels] containing the bool’s representing the mask, where False signifies an entry is unmasked and used in calculations.
pixel_scales (Union[Tuple[float], Tuple[float, float], float]) – The scaled units to pixel units conversion factor of each pixel.
origin (Tuple[float]) – The x origin of the mask’s coordinate system in scaled units.

Methods

`all`
`all_false`	Setup a 1D mask where all pixels are unmasked.
`astype`	rtype: `AbstractNDArray`
`copy`
`flip_hdu_for_ds9`
`from_fits`	Loads the 1D mask from a .fits file.
`from_primary_hdu`	Returns an `Mask1D` by from a PrimaryHDU object which has been loaded via astropy.fits
`instance_flatten`	Flatten an instance of an autoarray class into a tuple of its attributes (i.e.
`instance_unflatten`	Unflatten a tuple of attributes (i.e.
`invert`
`mask_new_sub_size_from`	Returns the mask on the same scaled coordinate system but with a sub-grid of an inputsub_size.
`max`
`min`
`output_to_fits`	Write the 1D mask to a .fits file.
`reshape`	rtype: `AbstractNDArray`
`sqrt`	rtype: `AbstractNDArray`
`sum`
`with_new_array`	Copy this object but give it a new array.

Attributes

`array`
`derive_grid`	rtype: `DeriveGrid1D`
`derive_mask`	rtype: `DeriveMask1D`
`dimensions`	rtype: `int`
`dtype`
`geometry`	Return the 1D geometry of the mask, representing its uniform rectangular grid of (x) coordinates defined by its `shape_native`.
`hdu_for_output`	The mask as a HDU object, which can be output to a .fits file.
`imag`	rtype: `AbstractNDArray`
`is_all_false`	Returns False if all pixels in a mask are False, else returns True.
`is_all_true`	Returns True if all pixels in a mask are True, else returns False.
`mask`
`native`	Returns the data structure in its native format which contains all unmaksed values to the native dimensions.
`ndim`
`pixel_scale`	For a mask with dimensions two or above check that are pixel scales are the same, and if so return this single value as a float.
`pixel_scale_header`	Returns the pixel scale of the mask as a header dictionary, which can be written to a .fits file.
`pixel_scales`
`pixels_in_mask`	The total number of unmasked pixels (values are False) in the mask.
`real`	rtype: `AbstractNDArray`
`shape`
`shape_native`	rtype: `Tuple`[`int`]
`shape_slim`	The 1D shape of the mask, which is equivalent to the total number of unmasked pixels in the mask.
`size`
`sub_fraction`	The fraction of the area of a pixel every sub-pixel contains.
`sub_length`	The total number of sub-pixels in a give pixel,
`sub_pixels_in_mask`	The total number of unmasked sub-pixels (values are False) in the mask.
`sub_shape_native`	rtype: `Tuple`[`int`]
`sub_shape_slim`	The 1D shape of the mask's sub-grid, which is equivalent to the total number of unmasked pixels in the mask.

property native: Structure#

Returns the data structure in its native format which contains all unmaksed values to the native dimensions.

Return type:: Structure

property geometry: Geometry1D#

Return the 1D geometry of the mask, representing its uniform rectangular grid of (x) coordinates defined by its shape_native.

Return type:: Geometry1D

classmethod all_false(shape_slim, pixel_scales, sub_size=1, origin=(0.0,), invert=False)[source]#

Setup a 1D mask where all pixels are unmasked.

Parameters:

shape_slim – The (y,x) shape of the mask in units of pixels.
pixel_scales (Union[Tuple[float], Tuple[float, float], float]) – The scaled units to pixel units conversion factor of each pixel.

Return type:

Mask1D

classmethod from_fits(file_path, pixel_scales, sub_size=1, hdu=0, origin=(0.0,))[source]#

Loads the 1D mask from a .fits file.

Parameters:

file_path (Union[Path, str]) – The full path of the fits file.
hdu (int) – The HDU number in the fits file containing the image image.
pixel_scales (Union[Tuple[float], Tuple[float, float], float]) – The scaled units to pixel units conversion factor of each pixel.

Return type:

Mask1D

classmethod from_primary_hdu(primary_hdu, sub_size=1, origin=(0.0, 0.0))[source]#

Returns an Mask1D by from a PrimaryHDU object which has been loaded via astropy.fits

This assumes that the header of the PrimaryHDU contains an entry named PIXSCALE which gives the pixel-scale of the array.

For a full description of Mask1D objects, including a description of the slim and native attribute used by the API, see the Mask1D class API documentation.

Parameters:

primary_hdu (PrimaryHDU) – The PrimaryHDU object which has already been loaded from a .fits file via astropy.fits and contains the array data and the pixel-scale in the header with an entry named PIXSCALE.
sub_size (int) – The size (sub_size x sub_size) of each unmasked pixels sub-array.
origin (Tuple[float, float]) – The (y,x) scaled units origin of the coordinate system.

Examples

from astropy.io import fits
import autoarray as aa

# Make Mask1D with sub_size 1.

primary_hdu = fits.open("path/to/file.fits")

array_1d = aa.Mask1D.from_primary_hdu(
    primary_hdu=primary_hdu,
    sub_size=1
)

import autoarray as aa

# Make Mask1D with sub_size 2.
# (It is uncommon that a sub-gridded array would be loaded from
# a .fits, but the API support its).

 primary_hdu = fits.open("path/to/file.fits")

array_1d = aa.Mask1D.from_primary_hdu(
    primary_hdu=primary_hdu,
    sub_size=2
)

Return type:: Mask1D

property shape_slim: Tuple[int]#

The 1D shape of the mask, which is equivalent to the total number of unmasked pixels in the mask.

Return type:: Tuple[int]

property hdu_for_output: PrimaryHDU#

The mask as a HDU object, which can be output to a .fits file.

The header of the HDU is used to store the pixel_scale of the array, which is used by the Array1D.from_hdu.

This method is used in other projects (E.g. PyAutoGalaxy, PyAutoLens) to conveniently output the array to .fits files.

Return type:: The HDU containing the data and its header which can then be written to .fits.

output_to_fits(file_path, overwrite=False)[source]#

Write the 1D mask to a .fits file.

Parameters:

file_path (Union[Path, str]) – The full path of the file that is output, including the file name and .fits extension.
overwrite (bool) – If True and a file already exists with the input file_path the .fits file is overwritten. If False, an error is raised.

Return type:

None

Examples

mask = Mask1D(mask=np.full(shape=(5,), fill_value=False)) mask.output_to_fits(file_path=’/path/to/file/filename.fits’, overwrite=True)