utils

Module contents

poornn.utils.take_slice(arr, sls, axis)

take slices along specific axis.

Parameters:
  • arr (ndarray) – target array.
  • sls (slice) – the target sector.
  • axis (int) – the target axis.
Returns:

result array.
Return type:

ndarray
poornn.utils.scan2csc(kernel_shape, img_in_shape, strides, boundary)

Scan target shape with filter, and transform it into csc_matrix.

Parameters:
  • kernel_shape (tuple) – shape of kernel.
  • img_in_shape (tuple) – shape of image dimension.
  • strides (tuple) – strides for image dimensions.
  • boundary ('P'|'O') – boundary condition.
Returns:

indptr for csc maitrx, indices of csc matrix, output image shape.
Return type:

(1darray, 1darray, tuple)
poornn.utils.typed_random(dtype, shape)

generate a random numbers with specific data type.

Parameters:
  • dtype (str) – data type.
  • shape (tuple) – shape of desired array.
Returns:

random array in ‘F’ order.
Return type:

ndarray
poornn.utils.typed_randn(dtype, shape)

generate a normal distributed random numbers with specific data type.

Parameters:
  • dtype (str) – data type.
  • shape (tuple) – shape of desired array.
Returns:

random array in ‘F’ order.
Return type:

ndarray
poornn.utils.typed_uniform(dtype, shape, low=-1.0, high=1.0)

generate a uniformly distributed random numbers with specific data type.

Parameters:
  • dtype (str) – data type.
  • shape (tuple) – shape of desired array.
Returns:

random array in ‘F’ order.
Return type:

ndarray
poornn.utils.tuple_prod(tp)

product over a tuple of numbers.

Parameters:tp (tuple) – the target tuple to product over.
Returns:product of tuple.
Return type:number
poornn.utils.masked_concatenate(vl, mask)

concatenate multiple arrays with mask True.

Parameters:
  • vl (list<ndarray>) – arrays.
  • mask (list<bool>) – masks for arrays.
Returns:

result array.
Return type:

ndarray
poornn.utils.dtype2token(dtype)

Parse data type to token.

Parameters:dtype ('float32'|'float64'|'complex64'|'complex128') – data type.
Returns:‘s’|’d’|’c’|’z’
Return type:str
poornn.utils.dtype_c2r(complex_dtype)

Get corresponding real data type from complex data type.

Parameters:dtype ('complex64'|'complex128') – data type.
Returns:(‘float32’|’float64’)
Return type:str
poornn.utils.dtype_r2c(real_dtype)

Get corresponding complex data type from real data type :param dtype: data type. :type dtype: ‘float32’|’float64’

Returns:(‘complex64’|’complex128’)
Return type:str
poornn.utils.complex_backward(dz, dzc)

Complex propagation rule.

Parameters:
  • dz (ndarray) – \(\partial J/\partial z\)
  • dzc (ndarray) – \(\partial J/\partial z^*\)
Returns:

backward function that take xy and dy as input.
Return type:

func
poornn.utils.fsign(x)

sign function that work properly for complex numbers \(x/|x|\),

Parameters:x (ndarray) – input array.
Returns:sign of x.
Return type:ndarray

Note

if x is 0, return 0.