diff options
| -rw-r--r-- | Wrappers/Python/ccpi/common.py | 79 |
1 files changed, 63 insertions, 16 deletions
diff --git a/Wrappers/Python/ccpi/common.py b/Wrappers/Python/ccpi/common.py index 6450951..9d7780e 100644 --- a/Wrappers/Python/ccpi/common.py +++ b/Wrappers/Python/ccpi/common.py @@ -93,37 +93,77 @@ class DataSet(ABC): self.array = array[:] else: self.array = array - + def as_array(self, dimensions=None): + '''Returns the DataSet as Numpy Array + + Returns the pointer to the array if dimensions is not set. + If dimensions is set, it first creates a new DataSet with the subset + and then it returns the pointer to the array''' + if dimensions is not None: + return self.subset(dimensions).as_array() + return self.array + + def subset(self, dimensions=None): + '''Creates a DataSet containing a subset of self according to the + labels in dimensions''' if dimensions is None: return self.array else: # check that all the requested dimensions are in the array # this is done by checking the dimension_labels proceed = True + unknown_key = '' + # axis_order contains the order of the axis that the user wants + # in the output DataSet axis_order = [] if type(dimensions) == list: for dl in dimensions: if dl not in self.dimension_labels.values(): proceed = False + unknown_key = dl break else: axis_order.append(find_key(self.dimension_labels, dl)) - print (axis_order) - # transpose the array and slice away the unwanted data + if not proceed: + raise KeyError('Unknown key specified {0}'.format(dl)) + + # slice away the unwanted data from the array unwanted_dimensions = self.dimension_labels.copy() - for ax in axis_order: - unwanted_dimensions.pop(ax) - new_shape = [] - #for i in range(axis_order): - # new_shape.append(self.shape(axis_order[i])) - new_shape = [self.shape[ax] for ax in axis_order] - return numpy.reshape( - numpy.delete( self.array , unwanted_dimensions.keys() ) , - new_shape - ) - #return numpy.transpose(self.array, new_shape) - + left_dimensions = [] + for ax in sorted(axis_order): + this_dimension = unwanted_dimensions.pop(ax) + left_dimensions.append(this_dimension) + #print ("unwanted_dimensions {0}".format(unwanted_dimensions)) + #print ("left_dimensions {0}".format(left_dimensions)) + #new_shape = [self.shape[ax] for ax in axis_order] + #print ("new_shape {0}".format(new_shape)) + command = "self.array" + for i in range(self.number_of_dimensions): + if self.dimension_labels[i] in unwanted_dimensions.values(): + command = command + "[0]" + else: + command = command + "[:]" + #print ("command {0}".format(command)) + cleaned = eval(command) + # cleaned has collapsed dimensions in the same order of + # self.array, but we want it in the order stated in the + # "dimensions". + # create axes order for numpy.transpose + axes = [] + for key in dimensions: + #print ("key {0}".format( key)) + for i in range(len( left_dimensions )): + ld = left_dimensions[i] + #print ("ld {0}".format( ld)) + if ld == key: + axes.append(i) + #print ("axes {0}".format(axes)) + + cleaned = numpy.transpose(cleaned, axes).copy() + + return DataSet(cleaned , True, dimensions) + @@ -136,7 +176,14 @@ if __name__ == '__main__': a = numpy.asarray([i for i in range( size )]) a = numpy.reshape(a, shape) ds = DataSet(a, False, ['X', 'Y','Z' ,'W']) - b = ds.as_array(['Z' ,'W']) + print ("ds label {0}".format(ds.dimension_labels)) + subset = ['W' ,'X'] + b = ds.subset( subset ) + print ("b label {0} shape {1}".format(b.dimension_labels, + numpy.shape(b.as_array()))) + c = ds.as_array(['Z','W']) + + |