Evaluate_basis_derivatives now returns values which are in agreement with FIAT at least on the reference element for all supported elements of orders up to 3 and derivatives of the same order. I think this was the last issue to be addressed before a release.
Kristian On 1 February 2010 23:09, <nore...@launchpad.net> wrote:
------------------------------------------------------------ revno: 1371 committer: Kristian B. Ølgaard <k.b.oelga...@gmail.com> branch nick: ffc timestamp: Mon 2010-02-01 23:06:13 +0100 message: Fix bug in unit tests for evaluate_basis_derivatives. modified: test/unit/evaluate_basis/test_against_fiat.py -- lp:ffc https://code.launchpad.net/~ffc-core/ffc/main Your team FFC Core Team is subscribed to branch lp:ffc. To unsubscribe from this branch go to https://code.launchpad.net/~ffc-core/ffc/main/+edit-subscription. === modified file 'test/unit/evaluate_basis/test_against_fiat.py' --- test/unit/evaluate_basis/test_against_fiat.py 2010-02-01 18:15:34 +0000 +++ test/unit/evaluate_basis/test_against_fiat.py 2010-02-01 22:06:13 +0000 @@ -9,7 +9,7 @@ from ufl import FiniteElement, MixedElement from ffc.fiatinterface import create_element, reference_cell from ffc.mixedelement import MixedElement as FFCMixedElement -from ffc.log import info +from ffc.log import info, error import numpy import sys, os, commands, numpy, shutil from test_common import xcomb, compile_element, print_results, compile_gcc_code,\ @@ -159,6 +159,7 @@ element, points, geo_dim, ref_coords, deriv_order = get_data(ufl_element) values = element.tabulate(deriv_order, points) return_values = {} + value_shape = element.value_shape() # Rearrange values to match what we get from evaluate_basis*() for n in range(deriv_order + 1): @@ -175,19 +176,18 @@ if n != 0: p += element.space_dimension() row = [[] for i in range(element.space_dimension())] - for deriv in combinations: - deriv_vals = values[deriv] - shape = numpy.shape(deriv_vals) - if len(shape) == 2: - for i in range(shape[0]): + for i in range(element.space_dimension()): + if value_shape == (): + for deriv in combinations: + deriv_vals = values[deriv] row[i].append(deriv_vals[i][p]) - elif len(shape) == 3: -# deriv_vals = numpy.transpose(deriv_vals, (1,0,2)) - for c in range(shape[1]): - for i in range(shape[0]): + elif len(value_shape) == 1: + for c in range(element.value_shape()[0]): + for deriv in combinations: + deriv_vals = values[deriv] row[i].append(deriv_vals[i][c][p]) else: - print deriv_vals + print values error("Did not expect tensor elements") new_row = [] for r in row:
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