Package hedge :: Module tools

Module tools

Miscellaneous helper facilities.

License: This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see U{http://www.gnu.org/licenses/}.

Classes

[hide private]

Rotation

Reflection

SubsettableCrossProduct
A cross product that can operate on an arbitrary subsets of its two operands and return an arbitrary subset of its result.

EOCRecorder

Closable

BlockMatrix
A block matrix is the sum of different smaller matrices positioned within one big matrix.

IndexListRegistry

Future
An abstract interface definition for futures.

ImmediateFuture
A non-future that immediately has a value available.

NestedFuture
A future that combines two sub-futures into one.

Functions

[hide private]

cyl_bessel_j(...)
cyl_bessel_j( (object)arg1, (object)arg2, (object)arg3) -> float :

cyl_neumann(...)
cyl_neumann( (object)arg1, (object)arg2, (object)arg3) -> float :

is_zero(x)

source code

relative_error(norm_diff, norm_true)

source code

has_data_in_numpy_arrays(a, allow_objarray_levels)

source code

numpy_linear_comb(lin_comb)

source code

mul_add(afac, a, bfac, b, add_timer=None)

source code

cyl_bessel_j_prime(nu, z)

source code

_affine_map___getinitargs__(self)

source code

plot_1d(f, a, b, steps=100, driver=None)

source code

is_obj_array(val)

source code

to_obj_array(ary)

source code

is_field_equal(a, b)

source code

make_obj_array(res_list)

source code

setify_field(f)

source code

hashable_field(f)

source code

field_equal(a, b)

source code

join_fields(*args)

source code

log_shape(array)
Returns the "logical shape" of the array.

source code

with_object_array_or_scalar(f, field)

source code

ptwise_mul(a, b)

source code

ptwise_dot(logdims1, logdims2, a1, a2)

source code

levi_civita(tuple)
Compute an entry of the Levi-Civita tensor for the indices tuple. source code

count_subset(subset)

source code

full_to_subset_indices(subset, base=0)
Takes a sequence of bools and turns it into an array of indices to be used to extract the subset from the full set.

source code

full_to_all_subset_indices(subsets, base=0)
Takes a sequence of bools and generates it into an array of indices to be used to extract the subset from the full set.

source code

partial_to_all_subset_indices(subsets, base=0)
Takes a sequence of bools and generates it into an array of indices to be used to insert the subset into the full set.

source code

normalize(v)

source code

sign(x)

source code

find_matching_vertices_along_axis(axis, points_a, points_b, numbers_a, numbers_b)

source code

orthonormalize(vectors, discard_threshold=None)
Carry out a modified [1] Gram-Schmidt orthonormalization on vectors.

source code

permutation_matrix(to_indices=None, from_indices=None, h=None, w=None, dtype=None, flavor=None)
Return a permutation matrix.

source code

leftsolve(A, B)

source code

unit_vector(n, i, dtype=None)
Return the i-th unit vector of size n, with the given dtype.

source code

estimate_order_of_convergence(abscissae, errors)
Assuming that abscissae and errors are connected by a law of the form

source code

mem_checkpoint(name=None)
Invoke the garbage collector and wait for a keypress.

source code

apply_index_map(imap, vector)

source code

apply_inverse_index_map(imap, vector)

source code

cuthill_mckee(graph)
Return a Cuthill-McKee ordering for the given graph.

source code

reverse_lookup_table(lut)

source code

time_count_flop(func, timer, counter, flop_counter, flops, increment=1)

source code

diff_rst_flops(discr)

source code

diff_rescale_one_flops(discr)

source code

mass_flops(discr)

source code

lift_flops(fg)

source code

gather_flops(discr)

source code

count_dofs(vec)

source code

make_lax_friedrichs_flux(wave_speed, state, flux_func, bdry_tags_and_states, strong)

source code

wait_for_keypress(discr)
MPI-aware keypress wait

source code

get_rank(discr)
Rank query that works with and without MPI active.

source code

typedump(value, max_seq=5, special_handlers={}) source code

Variables

[hide private]

cross = SubsettableCrossProduct()

Function Details

[hide private]

cyl_bessel_j(...)


cyl_bessel_j( (object)arg1, (object)arg2, (object)arg3) -> float :

    C++ signature :
        double cyl_bessel_j(int,double,boost::math::policies::policy<boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>)

cyl_neumann(...)


cyl_neumann( (object)arg1, (object)arg2, (object)arg3) -> float :

    C++ signature :
        double cyl_neumann(int,double,boost::math::policies::policy<boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>)

log_shape(array)

source code

Returns the "logical shape" of the array.

The "logical shape" is the shape that's left when the node-depending dimension has been eliminated.

levi_civita(tuple)

source code

Compute an entry of the Levi-Civita tensor for the indices tuple.

Only three-tuples are supported for now.

full_to_subset_indices(subset, base=0)

source code

Takes a sequence of bools and turns it into an array of indices to be used to extract the subset from the full set.

Example:

>>> full_to_subset_indices([False, True, True])
array([1 2])

full_to_all_subset_indices(subsets, base=0)

source code

Takes a sequence of bools and generates it into an array of indices to be used to extract the subset from the full set.

Example:

>>> list(full_to_all_subset_indices([[False, True, True], [True,False,True]]))
[array([1 2]), array([3 5]

partial_to_all_subset_indices(subsets, base=0)

source code

Takes a sequence of bools and generates it into an array of indices to be used to insert the subset into the full set.

Example:

>>> list(partial_to_all_subset_indices([[False, True, True], [True,False,True]]))
[array([0 1]), array([2 3]

orthonormalize(vectors, discard_threshold=None)

source code

Carry out a modified [1] Gram-Schmidt orthonormalization on vectors.

If, during orthonormalization, the 2-norm of a vector drops below discard_threshold, then this vector is silently discarded. If discard_threshold is None, then no vector will ever be dropped, and a zero 2-norm encountered during orthonormalization will throw a RuntimeError.

[1] http://en.wikipedia.org/wiki/Gram%E2%80%93Schmidt_process

permutation_matrix(to_indices=None, from_indices=None, h=None, w=None, dtype=None, flavor=None)

source code

Return a permutation matrix.

If to_indices is specified, the resulting permutation matrix P satisfies the condition

P * e[i] = e[to_indices[i]] for i=1,...,len(to_indices)

where e[i] is the i-th unit vector. The height of P is determined either implicitly by the maximum of to_indices or explicitly by the parameter h.

If from_indices is specified, the resulting permutation matrix P satisfies the condition

P * e[from_indices[i]] = e[i] for i=1,...,len(from_indices)

where e[i] is the i-th unit vector. The width of P is determined either implicitly by the maximum of from_indices of explicitly by the parameter w.

If both to_indices and from_indices is specified, a ValueError exception is raised.

estimate_order_of_convergence(abscissae, errors)

source code

Assuming that abscissae and errors are connected by a law of the form

error = constant * abscissa ^ (-order),

this function finds, in a least-squares sense, the best approximation of constant and order for the given data set. It returns a tuple (constant, order). Both inputs must be PyLinear vectors.

cuthill_mckee(graph)

source code

Return a Cuthill-McKee ordering for the given graph.

See (for example) Y. Saad, Iterative Methods for Sparse Linear System, 2nd edition, p. 76.

`graph' is given as an adjacency mapping, i.e. each node is mapped to a list of its neighbors.