Commit 26862f93 authored by Jait Dixit's avatar Jait Dixit
Browse files

Merge branch 'master' into add_axes_to_rg_fft

parents c4d65780 d06ba788
Pipeline #3221 skipped
......@@ -255,12 +255,11 @@ def _infer_key_type(key):
return (None, None)
found_boolean = False
# Check which case we got:
if isinstance(key, tuple) or isinstance(key, slice) or np.isscalar(key):
if isinstance(key, slice) or np.isscalar(key):
found = 'slicetuple'
elif isinstance(key, tuple) or isinstance(key, list):
# Check if there is something different in the array than
# scalars and slices
if isinstance(key, slice) or np.isscalar(key):
key = [key]
scalarQ = np.array(map(np.isscalar, key))
sliceQ = np.array(map(lambda z: isinstance(z, slice), key))
if np.all(scalarQ + sliceQ):
......@@ -273,8 +272,6 @@ def _infer_key_type(key):
elif isinstance(key, distributed_data_object):
found = 'd2o'
found_boolean = (key.dtype == np.bool_)
elif isinstance(key, list):
found = 'indexinglist'
raise ValueError(about._errors.cstring("ERROR: Unknown keytype!"))
return (found, found_boolean)
# -*- coding: utf-8 -*-
import numpy as np
from keepers import about
from itertools import product
def get_slice_list(shape, axes):
Helper function which generates slice list(s) to traverse over all
combinations of axes, other than the selected axes.
shape: tuple
Shape of the data array to traverse over.
axes: tuple
Axes which should not be iterated over.
The next list of indices and/or slice objects for each dimension.
If shape is empty.
If axes(axis) does not match shape.
if not shape:
raise ValueError(about._errors.cstring("ERROR: shape cannot be None."))
if not all(axis < len(shape) for axis in axes):
raise ValueError(
about._errors.cstring("ERROR: axes(axis) does not match shape.")
axes_select = [0 if x in axes else 1 for x, y in enumerate(shape)]
axes_iterables = [range(y) for x, y in enumerate(shape) if x not in axes]
for index in product(*axes_iterables):
it_iter = iter(index)
slice_list = [
if axis else slice(None, None) for axis in axes_select
yield slice_list
def hermitianize_gaussian(x):
......@@ -108,8 +156,8 @@ def convert_nested_list_to_object_array(x):
dimension_counter = 0
current_extract = x
for i in xrange(len(possible_shape)):
if isinstance(current_extract, list) == False and\
isinstance(current_extract, tuple) == False:
if not isinstance(current_extract, list) and \
not isinstance(current_extract, tuple):
current_extract = current_extract[0]
dimension_counter += 1
......@@ -153,8 +201,10 @@ def field_map(ishape, function, *args):
result = np.empty_like(args[0])
for i in xrange(
ii = np.unravel_index(i, result.shape)
result[ii] = function(*map(
lambda z: get_clipped(z, ii), args)
result[ii] = function(
lambda z: get_clipped(z, ii), args
# result[ii] = function(*map(lambda z: z[ii], args))
return result
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