autolens.Mask1D

class autolens.Mask1D(shape, dtype=float, buffer=None, offset=0, strides=None, order=None)
__init__(*args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

Methods

all([axis, out, keepdims]) Returns True if all elements evaluate to True.
any([axis, out, keepdims]) Returns True if any of the elements of a evaluate to True.
argmax([axis, out]) Return indices of the maximum values along the given axis.
argmin([axis, out]) Return indices of the minimum values along the given axis of a.
argpartition(kth[, axis, kind, order]) Returns the indices that would partition this array.
argsort([axis, kind, order]) Returns the indices that would sort this array.
astype(dtype[, order, casting, subok, copy]) Copy of the array, cast to a specified type.
byteswap([inplace]) Swap the bytes of the array elements
choose(choices[, out, mode]) Use an index array to construct a new array from a set of choices.
clip([min, max, out]) Return an array whose values are limited to [min, max].
compress(condition[, axis, out]) Return selected slices of this array along given axis.
conj() Complex-conjugate all elements.
conjugate() Return the complex conjugate, element-wise.
copy([order]) Return a copy of the array.
cumprod([axis, dtype, out]) Return the cumulative product of the elements along the given axis.
cumsum([axis, dtype, out]) Return the cumulative sum of the elements along the given axis.
diagonal([offset, axis1, axis2]) Return specified diagonals.
dot(b[, out]) Dot product of two arrays.
dump(file) Dump a pickle of the array to the specified file.
dumps() Returns the pickle of the array as a string.
fill(value) Fill the array with a scalar value.
flatten([order]) Return a copy of the array collapsed into one dimension.
from_fits(file_path, pixel_scales, …) Loads the 1D mask from a .fits file.
getfield(dtype[, offset]) Returns a field of the given array as a certain type.
item(*args) Copy an element of an array to a standard Python scalar and return it.
itemset(*args) Insert scalar into an array (scalar is cast to array’s dtype, if possible)
manual(mask, numpy.ndarray], pixel_scales, …)
mask_new_sub_size_from(mask[, sub_size]) Returns the mask on the same scaled coordinate system but with a sub-grid of an inputsub_size.
max([axis, out, keepdims, initial, where]) Return the maximum along a given axis.
mean([axis, dtype, out, keepdims]) Returns the average of the array elements along given axis.
min([axis, out, keepdims, initial, where]) Return the minimum along a given axis.
newbyteorder([new_order]) Return the array with the same data viewed with a different byte order.
nonzero() Return the indices of the elements that are non-zero.
output_to_fits(file_path, overwrite) Write the 1D mask to a .fits file.
partition(kth[, axis, kind, order]) Rearranges the elements in the array in such a way that the value of the element in kth position is in the position it would be in a sorted array.
prod([axis, dtype, out, keepdims, initial, …]) Return the product of the array elements over the given axis
ptp([axis, out, keepdims]) Peak to peak (maximum - minimum) value along a given axis.
put(indices, values[, mode]) Set a.flat[n] = values[n] for all n in indices.
ravel([order]) Return a flattened array.
repeat(repeats[, axis]) Repeat elements of an array.
reshape(shape[, order]) Returns an array containing the same data with a new shape.
resize(new_shape[, refcheck]) Change shape and size of array in-place.
round([decimals, out]) Return a with each element rounded to the given number of decimals.
searchsorted(v[, side, sorter]) Find indices where elements of v should be inserted in a to maintain order.
setfield(val, dtype[, offset]) Put a value into a specified place in a field defined by a data-type.
setflags([write, align, uic]) Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY), respectively.
sort([axis, kind, order]) Sort an array in-place.
squeeze([axis]) Remove single-dimensional entries from the shape of a.
std([axis, dtype, out, ddof, keepdims]) Returns the standard deviation of the array elements along given axis.
sum([axis, dtype, out, keepdims, initial, where]) Return the sum of the array elements over the given axis.
swapaxes(axis1, axis2) Return a view of the array with axis1 and axis2 interchanged.
take(indices[, axis, out, mode]) Return an array formed from the elements of a at the given indices.
tobytes([order]) Construct Python bytes containing the raw data bytes in the array.
tofile(fid[, sep, format]) Write array to a file as text or binary (default).
tolist() Return the array as an a.ndim-levels deep nested list of Python scalars.
tostring([order]) A compatibility alias for tobytes, with exactly the same behavior.
trace([offset, axis1, axis2, dtype, out]) Return the sum along diagonals of the array.
transpose(*axes) Returns a view of the array with axes transposed.
unmasked(shape_slim, pixel_scales, …) Setup a 1D mask where all pixels are unmasked.
var([axis, dtype, out, ddof, keepdims]) Returns the variance of the array elements, along given axis.
view([dtype][, type]) New view of array with the same data.

Attributes

T The transposed array.
base Base object if memory is from some other object.
ctypes An object to simplify the interaction of the array with the ctypes module.
data Python buffer object pointing to the start of the array’s data.
dimensions
dtype Data-type of the array’s elements.
extent
flags Information about the memory layout of the array.
flat A 1-D iterator over the array.
imag The imaginary part of the array.
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.
itemsize Length of one array element in bytes.
mask_sub_1 Returns the mask on the same scaled coordinate system but with a sub-grid of sub_size.
nbytes Total bytes consumed by the elements of the array.
ndim Number of array dimensions.
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_scales
pixels_in_mask The total number of unmasked pixels (values are False) in the mask.
real The real part of the array.
scaled_maxima
scaled_minima
shape Tuple of array dimensions.
shape_native
shape_slim The 1D shape of the mask, which is equivalent to the total number of unmasked pixels in the mask.
shape_slim_scaled
size Number of elements in the array.
strides Tuple of bytes to step in each dimension when traversing an array.
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.
to_mask_2d Map the Mask1D to a Mask2D of shape [total_mask_1d_pixel, 1].
unmasked_grid_sub_1 The scaled-grid of (y,x) coordinates of every pixel.
unmasked_mask
classmethod unmasked(shape_slim, pixel_scales: Union[float, Tuple[float]], sub_size: int = 1, origin: Tuple[float] = (0.0,), invert: bool = False) → autoarray.mask.mask_1d.Mask1D

Setup a 1D mask where all pixels are unmasked.

Parameters:
  • shape – The (y,x) shape of the mask in units of pixels.
  • pixel_scales – The scaled units to pixel units conversion factor of each pixel.
classmethod from_fits(file_path: str, pixel_scales: Union[float, Tuple[float]], sub_size: int = 1, hdu: int = 0, origin: Tuple[float] = (0.0,)) → autoarray.mask.mask_1d.Mask1D

Loads the 1D mask from a .fits file.

Parameters:
  • file_path – The full path of the fits file.
  • hdu – The HDU number in the fits file containing the image image.
  • pixel_scales – The scaled units to pixel units conversion factor of each pixel.
output_to_fits(file_path: str, overwrite: bool = False)

Write the 1D mask to a .fits file.

Parameters:
  • file_path – The full path of the file that is output, including the file name and .fits extension.
  • overwrite – If True and a file already exists with the input file_path the .fits file is overwritten. If False, an error is raised.
Returns:

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)

pixels_in_mask

The total number of unmasked pixels (values are False) in the mask.

is_all_false

Returns False if all pixels in a mask are False, else returns True.

shape_slim

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