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Correct some type check which was platform dependant. #5

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Correct some type check which was platform dependant. #5

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8 changes: 4 additions & 4 deletions sequencer/sequencer_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@ def __init__(self, grid, objects_list, estimator_list, scale_list=None):
assert ((grid.shape[0] == objects_list.shape[1]) and (grid.shape[1] == objects_list.shape[2])), "the grid and the objects must have the same dimensions"

if scale_list != None:
assert numpy.fromiter([(isinstance(scale_value, int) or type(scale_value) == numpy.int64) for scale_value in numpy.array(scale_list).flatten()], dtype=bool).all(), "scale values must all be integers"
assert numpy.fromiter([(isinstance(scale_value, int) or type(scale_value) == numpy.int64 or type(scale_value) == numpy.int32) for scale_value in numpy.array(scale_list).flatten()], dtype=bool).all(), "scale values must all be integers"
assert numpy.fromiter([estimator_value in ['EMD', 'energy', 'KL', 'L2'] for estimator_value in estimator_list], dtype=bool).all(), "estimators must be EMD, energy, KL or L2"
if scale_list != None:
assert len(scale_list) == len(estimator_list), "the length of scale_list must equal to the length of estimator_list"
Expand Down Expand Up @@ -176,8 +176,8 @@ def execute(self, outpath, to_print_progress=True, to_calculate_distance_matrice
assert (self.grid.shape[0] == self.objects_list.shape[1]), "the grid and the objects must have the same dimensions"
if len(self.grid.shape) == 2:
assert ((self.grid.shape[0] == self.objects_list.shape[1]) and (self.grid.shape[1] == self.objects_list.shape[2])), "the grid and the objects must have the same dimensions"

assert numpy.fromiter([(isinstance(scale_value, int) or type(scale_value) == numpy.int64) for scale_value in numpy.array(self.scale_list).flatten()], dtype=bool).all(), "scale values must all be integers"
print(type(x) for x in numpy.array(self.scale_list).flatten())
assert numpy.fromiter([(isinstance(scale_value, int) or type(scale_value) == numpy.int64 or type(scale_value) == numpy.int32) for scale_value in numpy.array(self.scale_list).flatten()], dtype=bool).all(), "scale values must all be integers"
assert numpy.fromiter([estimator_value in ['EMD', 'energy', 'KL', 'L2'] for estimator_value in self.estimator_list], dtype=bool).all(), "estimators must be EMD, energy, KL or L2"
if len(self.grid.shape) == 2:
assert ('EMD' not in self.estimator_list), "EMD cannot be applied to two-dimensional objects"
Expand Down Expand Up @@ -1080,7 +1080,7 @@ def _return_distance_matrix_dictionary_for_estimators_and_scales(self):
assert (self.grid.shape[0] == self.objects_list.shape[1]), "the grid and the objects must have the same dimensions"
if len(self.grid.shape) == 2:
assert ((self.grid.shape[0] == self.objects_list.shape[1]) and (self.grid.shape[1] == self.objects_list.shape[2])), "the grid and the objects must have the same dimensions"
assert numpy.fromiter([(isinstance(scale_value, int) or type(scale_value) == numpy.int64) for scale_value in numpy.array(self.scale_list).flatten()], dtype=bool).all(), "scale values must all be integers"
assert numpy.fromiter([(isinstance(scale_value, int) or type(scale_value) == numpy.int64 or type(scale_value) == numpy.int32) for scale_value in numpy.array(self.scale_list).flatten()], dtype=bool).all(), "scale values must all be integers"
assert numpy.fromiter([estimator_value in ['EMD', 'energy', 'KL', 'L2'] for estimator_value in self.estimator_list], dtype=bool).all(), "estimators must be EMD, energy, KL or L2"

distance_matrix_dictionary = {}
Expand Down