blimpy/file_wrapper.py
def read_blob(self,blob_dim,n_blob=0):
        """Read blob from a selection.
        """

        n_blobs = self.calc_n_blobs(blob_dim)
        if n_blob > n_blobs or n_blob < 0:
            raise ValueError('Please provide correct n_blob value. Given %i, but max values is %i'%(n_blob,n_blobs))

        #This prevents issues when the last blob is smaller than the others in time
        if blob_dim[self.time_axis]*(n_blob+1) > self.selection_shape[self.time_axis]:
            updated_blob_dim = (self.selection_shape[self.time_axis] - blob_dim[self.time_axis]*n_blob, 1, blob_dim[self.freq_axis])
        else:
            updated_blob_dim = [int(i) for i in blob_dim]

        blob_start = self._find_blob_start(blob_dim, n_blob)
        blob_end = blob_start + np.array(updated_blob_dim)

        blob = self.h5["data"][int(blob_start[self.time_axis]):int(blob_end[self.time_axis]),
                               :,
                               int(blob_start[self.freq_axis]):int(blob_end[self.freq_axis])
                               ]

#         if self.header[b'foff'] < 0:
#             blob = blob[:,:,::-1]

        return blob
def read_blob(self,blob_dim,n_blob=0):
        """Read blob from a selection.
        """

        n_blobs = self.calc_n_blobs(blob_dim)
        if n_blob > n_blobs or n_blob < 0:
            raise ValueError('Please provide correct n_blob value. Given %i, but max values is %i'%(n_blob,n_blobs))

        #This prevents issues when the last blob is smaller than the others in time
        if blob_dim[self.time_axis]*(n_blob+1) > self.selection_shape[self.time_axis]:
            updated_blob_dim = (self.selection_shape[self.time_axis] - blob_dim[self.time_axis]*n_blob, 1, blob_dim[self.freq_axis])
        else:
            updated_blob_dim = [int(i) for i in blob_dim]

        blob_start = self._find_blob_start(blob_dim, n_blob)
        blob_end = blob_start + np.array(updated_blob_dim)

        blob = self.h5["data"][int(blob_start[self.time_axis]):int(blob_end[self.time_axis]),
                               :,
                               int(blob_start[self.freq_axis]):int(blob_end[self.freq_axis])
                               ]

#         if self.header[b'foff'] < 0:
#             blob = blob[:,:,::-1]

        return blob
def read_blob ( self , blob_dim , n_blob = 0 ) : n_blobs = self . calc_n_blobs ( blob_dim ) if n_blob > n_blobs or n_blob < 0 : raise ValueError ( 'Please provide correct n_blob value. Given %i, but max values is %i' % ( n_blob , n_blobs ) ) #This prevents issues when the last blob is smaller than the others in time if blob_dim [ self . time_axis ] * ( n_blob + 1 ) > self . selection_shape [ self . time_axis ] : updated_blob_dim = ( self . selection_shape [ self . time_axis ] - blob_dim [ self . time_axis ] * n_blob , 1 , blob_dim [ self . freq_axis ] ) else : updated_blob_dim = [ int ( i ) for i in blob_dim ] blob_start = self . _find_blob_start ( blob_dim , n_blob ) blob_end = blob_start + np . array ( updated_blob_dim ) blob = self . h5 [ "data" ] [ int ( blob_start [ self . time_axis ] ) : int ( blob_end [ self . time_axis ] ) , : , int ( blob_start [ self . freq_axis ] ) : int ( blob_end [ self . freq_axis ] ) ] #         if self.header[b'foff'] < 0: #             blob = blob[:,:,::-1] return blob
Read blob from a selection.
Read blob from a selection .