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[Kristian Oelgaard <k.b.oelgaard@xxxxxxxxx>]

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,  <noreply@xxxxxxxxxxxxx> wrote:
> ------------------------------------------------------------
> revno: 1371
> committer: Kristian B. Ølgaard <k.b.oelgaard@xxxxxxxxx>
> 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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