proxtoolbox.utils.OrbitalTomog package

Submodules

proxtoolbox.utils.OrbitalTomog.array_tools module

proxtoolbox.utils.OrbitalTomog.array_tools.shift_array(arr: numpy.ndarray, dy: int, dx: int)

Use numpy.roll to shift an array in the first and second dimensions :param arr: numpy array :param dy: shift in first dimension :param dx: shift in second dimension :return: array like arr

proxtoolbox.utils.OrbitalTomog.array_tools.roll_to_pos(arr: numpy.ndarray, y: int = 0, x: int = 0, pos: tuple = None, move_maximum: bool = False, by_abs_val: bool = True) → numpy.ndarray

Shift the center of mass of an array to the given position by cyclic permutation

Parameters:

• arr – 2d array, works best for well-centered feature with limited support
• y – position parameter
• x – position parameter for second dimension
• pos – tuple with the new position, overriding y,x values. should be used for higher-dimensional arrays
• move_maximum – if true, look only at max-value
• by_abs_val – take abs value for the determination of max-val or center-of-mass

Returns:

array like original

proxtoolbox.utils.OrbitalTomog.array_tools.shifted_fft(arr, axes=None)

Combined fftshift and fft routine, based on scipy.fftpack

Args:

arr: numpy array axes: identical to argument for scipy.fftpack.fft

Returns:

transformed array

proxtoolbox.utils.OrbitalTomog.array_tools.shifted_ifft(arr, axes=None)

Combined fftshift and fft routine, based on scipy.fftpack

Args:

arr: numpy array axes: identical to argument for scipy.fftpack.fft

Returns:

transformed array

proxtoolbox.utils.OrbitalTomog.array_tools.tile_array(a: numpy.ndarray, shape, normalize: bool = False)

Upsample an array by nearest-neighbour interpolation, i.e. [1,2] -> [1,1,2,2] :param a: numpy array, ndim = [2,3] :param shape: tile size, single integer for rectangular tiles, tuple for individual axes otherwise :return: resampled array

proxtoolbox.utils.OrbitalTomog.binning module

proxtoolbox.utils.OrbitalTomog.binning.bin_array(arr: numpy.ndarray, new_shape: any, pad_zeros: bool = True) → numpy.ndarray

Reduce the size of an array by binning

Parameters:

• arr – original
• new_shape – tuple which must be an integer divisor of the original shape, or integer to bin by that factor
• pad_zeros – pad array with zeros to enable binning by the given factor

Returns:

new array

proxtoolbox.utils.OrbitalTomog.interpolation module

proxtoolbox.utils.OrbitalTomog.interpolation.fourier_interpolate(arr: numpy.ndarray, factor: any = 2.0, **kwargs) → numpy.ndarray

Interpolation by padding in the Fourier domain. Keyword arguments get passed to sub-functionalities. Options are for example: - center_data: whether to move the center of mass to the center of the array before interpolation, this is generally a good idea

NOTE: testing by simple 2x interpolation and subsequent 2x2 binning shows that errors are introduced in the procedure

Parameters:

• arr – numpy array, 2 or 3-dimensional
• factor – tuple or float to indicate by which factor to interpolate, default to factor 2

Returns:

interpolated array, cast to identical dtype as arr

proxtoolbox.utils.OrbitalTomog.padding module

proxtoolbox.utils.OrbitalTomog.padding.pad_to_square(arr: numpy.core.multiarray.array, new_shape: tuple = None, **kwargs) → numpy.core.multiarray.array

Given a numpy array of unequal dimensions, pad with zeros until it all dimensions have equal length

Parameters:

• arr – numpy array
• new_shape – desired shape
• kwargs – are passed on to np.pad

Returns: