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Diffstat (limited to 'silx/opencl/test/test_sparse.py')
| -rw-r--r-- | silx/opencl/test/test_sparse.py | 192 |
1 files changed, 192 insertions, 0 deletions
diff --git a/silx/opencl/test/test_sparse.py b/silx/opencl/test/test_sparse.py new file mode 100644 index 0000000..56f1ba4 --- /dev/null +++ b/silx/opencl/test/test_sparse.py @@ -0,0 +1,192 @@ +#!/usr/bin/env python +# coding: utf-8 +# /*########################################################################## +# +# Copyright (c) 2018-2019 European Synchrotron Radiation Facility +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in +# all copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +# +# ###########################################################################*/ +"""Test of the sparse module""" + +import numpy as np +import unittest +import logging +from itertools import product +from ..common import ocl +if ocl: + import pyopencl.array as parray + from silx.opencl.sparse import CSR +try: + import scipy.sparse as sp +except ImportError: + sp = None +logger = logging.getLogger(__name__) + + + +def generate_sparse_random_data( + shape=(1000,), + data_min=0, data_max=100, + density=0.1, + use_only_integers=True, + dtype="f"): + """ + Generate random sparse data where. + + Parameters + ------------ + shape: tuple + Output data shape. + data_min: int or float + Minimum value of data + data_max: int or float + Maximum value of data + density: float + Density of non-zero elements in the output data. + Low value of density mean low number of non-zero elements. + use_only_integers: bool + If set to True, the output data items will be primarily integers, + possibly casted to float if dtype is a floating-point type. + This can be used for ease of debugging. + dtype: str or numpy.dtype + Output data type + """ + mask = np.random.binomial(1, density, size=shape) + if use_only_integers: + d = np.random.randint(data_min, high=data_max, size=shape) + else: + d = data_min + (data_max - data_min) * np.random.rand(*shape) + return (d * mask).astype(dtype) + + + +@unittest.skipUnless(ocl and sp, "PyOpenCl/scipy is missing") +class TestCSR(unittest.TestCase): + """Test CSR format""" + + def setUp(self): + self.array = generate_sparse_random_data(shape=(512, 511)) + # Compute reference sparsification + a_s = sp.csr_matrix(self.array) + self.ref_data = a_s.data + self.ref_indices = a_s.indices + self.ref_indptr = a_s.indptr + self.ref_nnz = a_s.nnz + # Test possible configurations + input_on_device = [False, True] + output_on_device = [False, True] + self._test_configs = list(product(input_on_device, output_on_device)) + + + def test_sparsification(self): + for input_on_device, output_on_device in self._test_configs: + self._test_sparsification(input_on_device, output_on_device) + + + def _test_sparsification(self, input_on_device, output_on_device): + current_config = "input on device: %s, output on device: %s" % ( + str(input_on_device), str(output_on_device) + ) + # Sparsify on device + csr = CSR(self.array.shape) + if input_on_device: + # The array has to be flattened + arr = parray.to_device(csr.queue, self.array.ravel()) + else: + arr = self.array + if output_on_device: + d_data = parray.zeros_like(csr.data) + d_indices = parray.zeros_like(csr.indices) + d_indptr = parray.zeros_like(csr.indptr) + output = (d_data, d_indices, d_indptr) + else: + output = None + data, indices, indptr = csr.sparsify(arr, output=output) + if output_on_device: + data = data.get() + indices = indices.get() + indptr = indptr.get() + # Compare + nnz = self.ref_nnz + self.assertTrue( + np.allclose(data[:nnz], self.ref_data), + "something wrong with sparsified data (%s)" + % current_config + ) + self.assertTrue( + np.allclose(indices[:nnz], self.ref_indices), + "something wrong with sparsified indices (%s)" + % current_config + ) + self.assertTrue( + np.allclose(indptr, self.ref_indptr), + "something wrong with sparsified indices pointers (indptr) (%s)" + % current_config + ) + + + def test_desparsification(self): + for input_on_device, output_on_device in self._test_configs: + self._test_desparsification(input_on_device, output_on_device) + + + def _test_desparsification(self, input_on_device, output_on_device): + current_config = "input on device: %s, output on device: %s" % ( + str(input_on_device), str(output_on_device) + ) + # De-sparsify on device + csr = CSR(self.array.shape, max_nnz=self.ref_nnz) + if input_on_device: + data = parray.to_device(csr.queue, self.ref_data) + indices = parray.to_device(csr.queue, self.ref_indices) + indptr = parray.to_device(csr.queue, self.ref_indptr) + else: + data = self.ref_data + indices = self.ref_indices + indptr = self.ref_indptr + if output_on_device: + d_arr = parray.zeros_like(csr.array) + output = d_arr + else: + output = None + arr = csr.densify(data, indices, indptr, output=output) + if output_on_device: + arr = arr.get() + # Compare + self.assertTrue( + np.allclose(arr.reshape(self.array.shape), self.array), + "something wrong with densified data (%s)" + % current_config + ) + + + +def suite(): + suite = unittest.TestSuite() + suite.addTest( + unittest.defaultTestLoader.loadTestsFromTestCase(TestCSR) + ) + return suite + + +if __name__ == '__main__': + unittest.main(defaultTest="suite") + + |