autocti.Mask1D#

class autocti.Mask1D(mask: Union[ndarray, List], pixel_scales: Union[Tuple[float], Tuple[float, float], float], sub_size: int = 1, origin: Tuple[float] = (0.0,), invert: bool = False)[source]#

Bases: Mask1D

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 – 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 – The scaled units to pixel units conversion factor of each pixel.
origin – 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`
`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.
`masked_eper_from_layout`
`masked_fpr_and_eper_from`
`masked_fpr_from_layout`
`max`
`min`
`output_to_fits`	Write the 1D mask to a .fits file.
`reshape`
`sqrt`
`sum`
`with_new_array`	Copy this object but give it a new array.

Attributes

`array`
`derive_grid`
`derive_mask`
`dimensions`
`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`
`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`
`shape`
`shape_native`
`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`
`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.