588 lines
13 KiB
C++
588 lines
13 KiB
C++
// SPDX-License-Identifier: Apache-2.0
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//
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// Copyright 2011-2017 Ryan Curtin (http://www.ratml.org/)
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// Copyright 2017 National ICT Australia (NICTA)
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// ------------------------------------------------------------------------
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#include <armadillo>
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#include "catch.hpp"
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#include "utils.hpp"
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using namespace arma;
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TEST_CASE("fn_var_empty_sparse_test", "[var]")
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{
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SpMat<double> m(100, 100);
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SpRow<double> result = var(m);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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result = var(m, 0, 0);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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result = var(m, 1, 0);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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result = var(m, 1);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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SpCol<double> colres = var(m, 1, 1);
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REQUIRE( colres.n_cols == 1 );
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REQUIRE( colres.n_rows == 100 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) colres[i] == Approx(0.0).margin(0.001) );
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}
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colres = var(m, 0, 1);
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REQUIRE( colres.n_cols == 1 );
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REQUIRE( colres.n_rows == 100 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) colres[i] == Approx(0.0).margin(0.001) );
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}
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}
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TEST_CASE("fn_var_empty_cx_sparse_test", "[var]")
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{
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SpMat<std::complex<double> > m(100, 100);
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SpRow<double> result = var(m);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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result = var(m, 0, 0);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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result = var(m, 1, 0);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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result = var(m, 1);
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REQUIRE( result.n_cols == 100 );
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REQUIRE( result.n_rows == 1 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) result[i] == Approx(0.0).margin(0.001) );
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}
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SpCol<double> colres = var(m, 1, 1);
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REQUIRE( colres.n_cols == 1 );
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REQUIRE( colres.n_rows == 100 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) colres[i] == Approx(0.0).margin(0.001) );
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}
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colres = var(m, 0, 1);
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REQUIRE( colres.n_cols == 1 );
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REQUIRE( colres.n_rows == 100 );
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for (uword i = 0; i < 100; ++i)
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{
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REQUIRE( (double) colres[i] == Approx(0.0).margin(0.001) );
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}
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}
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TEST_CASE("fn_var_sparse_test", "[var]")
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{
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// Create a random matrix and do variance testing on it, with varying levels
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// of nonzero (eventually this becomes a fully dense matrix).
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for (int i = 0; i < 10; ++i)
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{
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SpMat<double> x;
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x.sprandu(50, 75, ((double) (i + 1)) / 10);
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mat d(x);
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SpRow<double> rr = var(x);
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rowvec drr = var(d);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x, 1, 0);
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drr = var(d, 1, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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SpCol<double> cr = var(x, 0, 1);
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vec dcr = var(d, 0, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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cr = var(x, 1, 1);
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dcr = var(d, 1, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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// Now on a subview.
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rr = var(x.submat(11, 11, 30, 45), 0, 0);
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drr = var(d.submat(11, 11, 30, 45), 0, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 35 );
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for (uword j = 0; j < 35; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x.submat(11, 11, 30, 45), 1, 0);
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drr = var(d.submat(11, 11, 30, 45), 1, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 35 );
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for (uword j = 0; j < 35; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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cr = var(x.submat(11, 11, 30, 45), 0, 1);
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dcr = var(d.submat(11, 11, 30, 45), 0, 1);
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REQUIRE( cr.n_rows == 20 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 20; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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cr = var(x.submat(11, 11, 30, 45), 1, 1);
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dcr = var(d.submat(11, 11, 30, 45), 1, 1);
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REQUIRE( cr.n_rows == 20 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 20; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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// Now on an SpOp (spop_scalar_times)
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rr = var(3.0 * x, 0, 0);
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drr = var(3.0 * d, 0, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(3.0 * x, 1, 0);
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drr = var(3.0 * d, 1, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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cr = var(4.5 * x, 0, 1);
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dcr = var(4.5 * d, 0, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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cr = var(4.5 * x, 1, 1);
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dcr = var(4.5 * d, 1, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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// Now on an SpGlue!
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SpMat<double> y;
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y.sprandu(50, 75, 0.3);
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mat e(y);
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rr = var(x + y);
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drr = var(d + e);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x + y, 1);
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drr = var(d + e, 1);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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cr = var(x + y, 0, 1);
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dcr = var(d + e, 0, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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cr = var(x + y, 1, 1);
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dcr = var(d + e, 1, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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}
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}
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TEST_CASE("fn_var_sparse_cx_test", "[var]")
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{
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// Create a random matrix and do variance testing on it, with varying levels
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// of nonzero (eventually this becomes a fully dense matrix).
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for (int i = 0; i < 10; ++i)
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{
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SpMat<std::complex<double> > x;
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x.sprandu(50, 75, ((double) (i + 1)) / 10);
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cx_mat d(x);
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SpRow<double> rr = var(x);
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rowvec drr = var(d);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x, 1, 0);
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drr = var(d, 1, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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SpCol<double> cr = var(x, 0, 1);
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vec dcr = var(d, 0, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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cr = var(x, 1, 1);
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dcr = var(d, 1, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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// Now on a subview.
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rr = var(x.submat(11, 11, 30, 45), 0, 0);
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drr = var(d.submat(11, 11, 30, 45), 0, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 35 );
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for (uword j = 0; j < 35; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x.submat(11, 11, 30, 45), 1, 0);
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drr = var(d.submat(11, 11, 30, 45), 1, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 35 );
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for (uword j = 0; j < 35; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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cr = var(x.submat(11, 11, 30, 45), 0, 1);
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dcr = var(d.submat(11, 11, 30, 45), 0, 1);
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REQUIRE( cr.n_rows == 20 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 20; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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cr = var(x.submat(11, 11, 30, 45), 1, 1);
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dcr = var(d.submat(11, 11, 30, 45), 1, 1);
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REQUIRE( cr.n_rows == 20 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 20; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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// Now on an SpOp (spop_scalar_times)
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rr = var(3.0 * x, 0, 0);
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drr = var(3.0 * d, 0, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(3.0 * x, 1, 0);
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drr = var(3.0 * d, 1, 0);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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cr = var(4.5 * x, 0, 1);
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dcr = var(4.5 * d, 0, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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cr = var(4.5 * x, 1, 1);
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dcr = var(4.5 * d, 1, 1);
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REQUIRE( cr.n_rows == 50 );
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REQUIRE( cr.n_cols == 1 );
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for (uword j = 0; j < 50; ++j)
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{
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REQUIRE( dcr[j] == Approx((double) cr[j]) );
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}
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// Now on an SpGlue!
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SpMat<std::complex<double> > y;
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y.sprandu(50, 75, 0.3);
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cx_mat e(y);
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rr = var(x + y);
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drr = var(d + e);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
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{
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REQUIRE( drr[j] == Approx((double) rr[j]) );
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}
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rr = var(x + y, 1);
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drr = var(d + e, 1);
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REQUIRE( rr.n_rows == 1 );
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REQUIRE( rr.n_cols == 75 );
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for (uword j = 0; j < 75; ++j)
|
|
{
|
|
REQUIRE( drr[j] == Approx((double) rr[j]) );
|
|
}
|
|
|
|
cr = var(x + y, 0, 1);
|
|
dcr = var(d + e, 0, 1);
|
|
|
|
REQUIRE( cr.n_rows == 50 );
|
|
REQUIRE( cr.n_cols == 1 );
|
|
for (uword j = 0; j < 50; ++j)
|
|
{
|
|
REQUIRE( dcr[j] == Approx((double) cr[j]) );
|
|
}
|
|
|
|
cr = var(x + y, 1, 1);
|
|
dcr = var(d + e, 1, 1);
|
|
|
|
REQUIRE( cr.n_rows == 50 );
|
|
REQUIRE( cr.n_cols == 1 );
|
|
for (uword j = 0; j < 50; ++j)
|
|
{
|
|
REQUIRE( dcr[j] == Approx((double) cr[j]) );
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
|
|
TEST_CASE("fn_var_sparse_alias_test", "[var]")
|
|
{
|
|
sp_mat s;
|
|
s.sprandu(70, 70, 0.3);
|
|
mat d(s);
|
|
|
|
s = var(s);
|
|
d = var(d);
|
|
|
|
REQUIRE( d.n_rows == s.n_rows );
|
|
REQUIRE( d.n_cols == s.n_cols );
|
|
for (uword i = 0; i < d.n_elem; ++i)
|
|
{
|
|
REQUIRE(d[i] == Approx((double) s[i]) );
|
|
}
|
|
|
|
s.sprandu(70, 70, 0.3);
|
|
d = s;
|
|
|
|
s = var(s, 1);
|
|
d = var(d, 1);
|
|
for (uword i = 0; i < d.n_elem; ++i)
|
|
{
|
|
REQUIRE( d[i] == Approx((double) s[i]) );
|
|
}
|
|
}
|
|
|
|
|
|
|
|
TEMPLATE_TEST_CASE("fn_var_fp_reference", "[var]", TEST_FLOAT_TYPES)
|
|
{
|
|
typedef TestType eT;
|
|
|
|
Col<eT> X(10, fill::randn);
|
|
vec X_ref = conv_to<vec>::from(X);
|
|
|
|
const eT var_val = var(X);
|
|
const double var_ref = var(X_ref);
|
|
|
|
const eT margin = is_blas_real<eT>::value ? eT(0.001) : eT(0.02);
|
|
|
|
REQUIRE( var_val == Approx(eT(var_ref)).margin(margin) );
|
|
}
|
|
|
|
|
|
|
|
//TEMPLATE_TEST_CASE("fn_var_sp_fp_reference", "[var]", TEST_FLOAT_TYPES)
|
|
// {
|
|
// typedef TestType eT;
|
|
//
|
|
// SpCol<eT> X;
|
|
// X.sprandu(100, 1, 0.3);
|
|
// sp_vec X_ref = conv_to<sp_mat>::from(X);
|
|
//
|
|
// const eT var_val = var(X);
|
|
// const double var_ref = var(X_ref);
|
|
//
|
|
// const eT margin = is_blas_real<eT>::value ? eT(0.001) : eT(0.02);
|
|
//
|
|
// REQUIRE( var_val == Approx(eT(var_ref)).margin(margin) );
|
|
// }
|