acryo.backend package

Module contents

class acryo.backend.AnyArray[source]

Bases: Generic[acryo.backend._api._T]

Type representing a ndarray of numpy or cupy (or any other array that has similar API).

astype(dtype: type[_T1]) → acryo.backend._api.AnyArray[acryo.backend._api._T1][source]

conj() → acryo.backend._api.AnyArray[acryo.backend._api._T][source]

dot(other: acryo.backend._api.AnyArray[acryo.backend._api._T]) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]

property dtype: numpy.dtype[acryo.backend._api._T]

property imag: acryo.backend._api.AnyArray[numpy.float32]

mean(axis: None = None) → _T
mean(axis: int | tuple[int, ...]) → AnyArray[_T]: Helper for @overload to raise when called.

property ndim: int

property real: acryo.backend._api.AnyArray[numpy.float32]

property shape: tuple[int, ...]

class acryo.backend.Backend(name: str | None = None)[source]

Bases: object

affine_transform(img, matrix, output_shape: tuple[int, ...] | None = None, output=None, order: int = 3, mode: str = 'constant', cval: float = 0.0, prefilter: bool = True) → acryo.backend._api.AnyArray[numpy.float32][source]: Affine transform.

arange(*args, dtype: type[_T], **kwargs) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]
arange(*args, dtype: None = 'None', **kwargs) → acryo.backend._api.AnyArray: Return evenly spaced values within a given interval.

argmax(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: None = None) → numpy.int64[source]
argmax(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: int | tuple[int, ...]) → acryo.backend._api.AnyArray[numpy.int64]

argmin(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: None = None) → numpy.int64[source]
argmin(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: int | tuple[int, ...]) → acryo.backend._api.AnyArray[numpy.int64]

array(x, dtype: type[_T] | numpy.dtype[acryo.backend._api._T]) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]
array(x: Union[acryo.backend._api.AnyArray[acryo.backend._api._T], numpy.ndarray[Any, numpy.dtype[acryo.backend._api._T]]], dtype: None = None) → acryo.backend._api.AnyArray[acryo.backend._api._T]: Convert to numpy array.

asarray(x, dtype: type[_T] | numpy.dtype[acryo.backend._api._T]) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]
asarray(x: Union[acryo.backend._api.AnyArray[acryo.backend._api._T], numpy.ndarray[Any, numpy.dtype[acryo.backend._api._T]]], dtype: None = None) → acryo.backend._api.AnyArray[acryo.backend._api._T]: Convert to numpy array.

asnumpy(x: Union[acryo.backend._api.AnyArray[acryo.backend._api._T], numpy.ndarray[Any, numpy.dtype[acryo.backend._api._T]]]) → numpy.ndarray[Any, numpy.dtype[acryo.backend._api._T]][source]: Convert to numpy array.

cumsum(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: int | None = None) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]

exp(x: acryo.backend._api.AnyArray[acryo.backend._api._T]) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Return the exponential of an array.

fftfreq(n: int, d: float = 1.0) → acryo.backend._api.AnyArray[numpy.float64][source]: Return the Discrete Fourier Transform sample frequencies.

fftn(x: Union[acryo.backend._api.AnyArray[numpy.float32], acryo.backend._api.AnyArray[numpy.complex64]], s: tuple[int, int, int] | None = None, axes: int | tuple[int, ...] | None = None) → acryo.backend._api.AnyArray[numpy.complex64][source]: N-dimensional FFT.

fftshift(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axes=None) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Shift zero-frequency component to center.

fix(x: acryo.backend._api.AnyArray[acryo.backend._api._T]) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Round to nearest integer towards zero.

full(shape: int | tuple[int, ...], fill_value: Any, dtype: type[_T] | numpy.dtype[acryo.backend._api._T] | None = None) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Return a new array of given shape and type, filled with fill_value.

ifftn(x: Union[acryo.backend._api.AnyArray[numpy.float32], acryo.backend._api.AnyArray[numpy.complex64]], s: tuple[int, int, int] | None = None, axes: int | tuple[int, ...] | None = None) → acryo.backend._api.AnyArray[numpy.complex64][source]: N-dimensional inverse FFT.

ifftshift(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axes=None) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Inverse shift zero-frequency component to center.

indices(shape: tuple[int], dtype: type[_T] = np.int32) → tuple[acryo.backend._api.AnyArray[_T]][source]
indices(shape: tuple[int, int], dtype: type[_T] = np.int32) → tuple[acryo.backend._api.AnyArray[_T], acryo.backend._api.AnyArray[_T]]
indices(shape: tuple[int, int, int], dtype: type[_T] = np.int32) → tuple[acryo.backend._api.AnyArray[_T], acryo.backend._api.AnyArray[_T], acryo.backend._api.AnyArray[_T]]
indices(shape: tuple[int, ...], dtype: type[_T] = np.int32) → tuple[acryo.backend._api.AnyArray[_T], ...]: Return an array representing the indices of a grid.

irfftn(x: acryo.backend._api.AnyArray[numpy.complex64], s: tuple[int, int, int] | None = None, axes: int | tuple[int, ...] | None = None) → acryo.backend._api.AnyArray[numpy.float32][source]: N-dimensional inverse FFT of real part.

lowpass_filter(img, cutoff, order: int = 2) → acryo.backend._api.AnyArray[numpy.float32][source]: Lowpass filter in real space.

lowpass_filter_ft(img, cutoff, order: int = 2) → acryo.backend._api.AnyArray[numpy.complex64][source]: Lowpass filter in Fourier space.

map_coordinates(x: acryo.backend._api.AnyArray[acryo.backend._api._T], coords: acryo.backend._api.AnyArray[acryo.backend._api._T], order: int = 3, mode: str = 'constant', cval: float = - 1.0, prefilter: bool = True) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]

max(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: None = None) → acryo.backend._api._T[source]
max(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: int | tuple[int, ...]) → acryo.backend._api.AnyArray[acryo.backend._api._T]: Return the maximum of an array or maximum along an axis.

maycopy(x: acryo.backend._api.AnyArray[acryo.backend._api._T]) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]

mean(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: None = None) → acryo.backend._api._T[source]
mean(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: int | tuple[int, ...]) → acryo.backend._api.AnyArray[acryo.backend._api._T]: Return the mean of array elements over a given axis.

meshgrid(x0: acryo.backend._api.AnyArray[acryo.backend._api._T], copy: bool = True, sparse: bool = False, indexing: Literal['xy', 'ij'] = 'xy') → tuple[acryo.backend._api.AnyArray[_T]][source]
meshgrid(x0: acryo.backend._api.AnyArray[acryo.backend._api._T], x1: acryo.backend._api.AnyArray[acryo.backend._api._T], copy: bool = True, sparse: bool = False, indexing: Literal['xy', 'ij'] = 'xy') → tuple[acryo.backend._api.AnyArray[_T], acryo.backend._api.AnyArray[_T]]
meshgrid(x0: acryo.backend._api.AnyArray[acryo.backend._api._T], x1: acryo.backend._api.AnyArray[acryo.backend._api._T], x2: acryo.backend._api.AnyArray[acryo.backend._api._T], copy: bool = True, sparse: bool = False, indexing: Literal['xy', 'ij'] = 'xy') → tuple[acryo.backend._api.AnyArray[_T], acryo.backend._api.AnyArray[_T], acryo.backend._api.AnyArray[_T]]: Return coordinate matrices from coordinate vectors.

min(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: None = None) → acryo.backend._api._T[source]
min(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: int | tuple[int, ...]) → acryo.backend._api.AnyArray[acryo.backend._api._T]: Return the minimum of an array or minimum along an axis.

missing_wedge_mask(rotator: scipy.spatial.transform._rotation.Rotation, tilt_range: tuple[float, float], shape: tuple[int, int, int])[source]

property name: str

pad(x: acryo.backend._api.AnyArray[acryo.backend._api._T], pad_width: Union[int, Sequence[int], Sequence[tuple[int, int]]], mode: str = 'constant', constant_values: float = 0.0) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Pad an array.

percentile(x: acryo.backend._api.AnyArray[acryo.backend._api._T], q: float, axis: None = None) → acryo.backend._api._T[source]
percentile(x: acryo.backend._api.AnyArray[acryo.backend._api._T], q: float, axis: int | tuple[int, ...]) → acryo.backend._api.AnyArray[acryo.backend._api._T]: Compute the q-th percentile of the data along the specified axis.

rfftn(x: acryo.backend._api.AnyArray[numpy.float32], s: tuple[int, int, int] | None = None, axes: int | tuple[int, ...] | None = None) → acryo.backend._api.AnyArray[numpy.complex64][source]: N-dimensional FFT of real part.

rotated_crop(subimg, mtx: numpy.ndarray[Any, numpy.dtype[numpy.float32]], shape: tuple[int, int, int], order: int, cval: Union[float, Callable[[acryo.backend._api.AnyArray[numpy.float32]], Any]]) → acryo.backend._api.AnyArray[numpy.float32][source]

spline_filter(input, order: int = 3, output: type[~_T] = <class 'numpy.float64'>, mode: str = 'mirror') → acryo.backend._api.AnyArray[acryo.backend._api._T][source]

sqrt(x: acryo.backend._api.AnyArray[acryo.backend._api._T]) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Return the non-negative square-root of an array.

stack(arrays: Sequence[acryo.backend._api.AnyArray[acryo.backend._api._T]], axis: int = 0) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Stack arrays in sequence along a new axis.

sum(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: None = None) → acryo.backend._api._T[source]
sum(x: acryo.backend._api.AnyArray[acryo.backend._api._T], axis: int | tuple[int, ...]) → acryo.backend._api.AnyArray[acryo.backend._api._T]: Return the sum of array elements over a given axis.

tensordot(a: acryo.backend._api.AnyArray[acryo.backend._api._T], b: acryo.backend._api.AnyArray[acryo.backend._api._T], axes: int | tuple[int, ...] = 2) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Return tensor dot product of two arrays.

unravel_index(indices, shape: tuple[int, ...]) → acryo.backend._api.AnyArray[numpy.int64][source]: Converts a flat index into a tuple of coordinate arrays.

zeros(shape: int | tuple[int, ...], dtype: type[_T] | numpy.dtype[acryo.backend._api._T] | None = None) → acryo.backend._api.AnyArray[acryo.backend._api._T][source]: Return a new array of given shape and type, filled with zeros.

acryo.backend.set_backend(name: str)[source]: Set the default backend.

acryo.backend.using_backend(name: str)[source]: Context manager to temporarily change the default backend.