autolens.Visibilities

class autolens.Visibilities(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, hdu) Create Visibilities (see AbstractVisibilities.__new__) by loading the(real, imag) values from a .fits file.
full(fill_value, shape_slim) Create Visibilities (see AbstractVisibilities.__new__) where all (real, imag) values are filled with an input fill value, analogous to the method numpy ndarray.full.
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_slim(visibilities) Create Visibilities (see AbstractVisibilities.__new__) by inputting (real, imag) values as a 1D complex NumPy array or 2D NumPy float array or list, for example:
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.
ones(shape_slim) Create Visibilities (see AbstractVisibilities.__new__) where all (real, imag) values are filled with ones, analogous to the method np.ones().
output_to_fits(file_path[, overwrite]) Output the visibilities 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.
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.
zeros(shape_slim) Create Visibilities (see AbstractVisibilities.__new__) where all (real, imag) values are filled with zeros, analogous to the method np.zeros().

Attributes

T The transposed array.
amplitudes A property that is only computed once per instance and then replaces itself with an ordinary attribute.
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.
dtype Data-type of the array’s elements.
extent The extent of the visibilities if they are treated as a 2D grid in the complex plane.
flags Information about the memory layout of the array.
flat A 1-D iterator over the array.
imag The imaginary part of the array.
in_array Returns the 1D complex NumPy array of values with shape [total_visibilities] as a NumPy float array of shape [total_visibilities, 2].
in_grid Returns the 1D complex NumPy array of values as an irregular grid.
itemsize Length of one array element in bytes.
nbytes Total bytes consumed by the elements of the array.
ndim Number of array dimensions.
phases A property that is only computed once per instance and then replaces itself with an ordinary attribute.
real The real part of the array.
scaled_maxima The maximum values of the visibilities if they are treated as a 2D grid in the complex plane.
scaled_minima The minimum values of the visibilities if they are treated as a 2D grid in the complex plane.
shape Tuple of array dimensions.
shape_slim
size Number of elements in the array.
slim
strides Tuple of bytes to step in each dimension when traversing an array.
classmethod manual_slim(visibilities)

Create Visibilities (see AbstractVisibilities.__new__) by inputting (real, imag) values as a 1D complex NumPy array or 2D NumPy float array or list, for example:

visibilities=np.array([1.0+1.0j, 2.0+2.0j, 3.0+3.0j, 4.0+4.0j]) visibilities=np.array([[1.0+1.0], [2.0+2.0], [3.0+3.0], [4.0+4.0]]) visibilities=[[1.0, 1.0], [2.0, 2.0], [3.0, 3.0], [4.0, 4.0]]

Parameters:visibilities – The (real, imag) visibilities values.
classmethod full(fill_value, shape_slim)

Create Visibilities (see AbstractVisibilities.__new__) where all (real, imag) values are filled with an input fill value, analogous to the method numpy ndarray.full.

From 1D input the method cannot determine the 2D shape of the array and its mask, thus the shape_native must be input into this method. The mask is setup as a unmasked Mask2D of shape_native.

Parameters:
  • fill_value – The value all real and imaginary array elements are filled with.
  • shape_slim – The 1D shape of output visibilities.
classmethod ones(shape_slim)

Create Visibilities (see AbstractVisibilities.__new__) where all (real, imag) values are filled with ones, analogous to the method np.ones().

From 1D input the method cannot determine the 2D shape of the array and its mask, thus the shape_native must be input into this method. The mask is setup as a unmasked Mask2D of shape_native.

Parameters:shape_slim – The 1D shape of output visibilities.
classmethod zeros(shape_slim)

Create Visibilities (see AbstractVisibilities.__new__) where all (real, imag) values are filled with zeros, analogous to the method np.zeros().

From 1D input the method cannot determine the 2D shape of the array and its mask, thus the shape_native must be input into this method. The mask is setup as a unmasked Mask2D of shape_native.

Parameters:shape_slim – The 1D shape of output visibilities.
classmethod from_fits(file_path, hdu)

Create Visibilities (see AbstractVisibilities.__new__) by loading the(real, imag) values from a .fits file.

The .fits file stores these values as a real set of values of shape [total_visibilities, 2] which are converted to a 1d complex NumPy array.

Parameters:
  • file_path (str) – The path the file is loaded from, including the filename and the .fits extension, e.g. ‘/path/to/filename.fits’
  • hdu – The Header-Data Unit of the .fits file the visibilitiy data is loaded from.