Source code for ffc.uflacs.analysis.crsarray

# -*- coding: utf-8 -*-
# Copyright (C) 2011-2017 Martin Sandve Alnæs
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"""Compressed row storage 'matrix' (actually just a non-rectangular 2d array)."""

import numpy

[docs]def sufficient_int(maxval):
return numpy.int16 if maxval < 2**15 else numpy.int32
[docs]class CRSArray(object): """An array of variable length dense arrays. Stored efficiently with simple compressed row storage. This CRS array variant doesn't have a sparsity pattern, as each row is simply a dense vector. Values are stored in one flat array 'data[]', and 'row_offsets[i]' contains the index to the first element on row i for 0<=i<=num_rows. There is no column index. """ def __init__(self, row_capacity, element_capacity, dtype): itype = sufficient_int(element_capacity) self.row_offsets = numpy.zeros(row_capacity + 1, dtype=itype) self.data = numpy.zeros(element_capacity, dtype=dtype) self.num_rows = 0
[docs] def push_row(self, elements): a = self.row_offsets[self.num_rows] b = a + len(elements) self.data[a:b] = elements self.num_rows += 1
self.row_offsets[self.num_rows] = b @property def num_elements(self): return self.row_offsets[self.num_rows] def __getitem__(self, row): if row < 0 or row >= self.num_rows: raise IndexError("Row number out of range!") a = self.row_offsets[row] b = self.row_offsets[row + 1] return self.data[a:b] def __len__(self): return self.num_rows def __str__(self): return "[%s]" % ('\n'.join(str(row) for row in self),)
[docs] @classmethod def from_rows(cls, rows, num_rows, num_elements, dtype): "Construct a CRSArray from a list of row element lists." crs = CRSArray(num_rows, num_elements, dtype) for row in rows: crs.push_row(row)
return crs