Mercurial > ift6266
view utils/seriestables/test_series.py @ 613:5e481b224117
fix the reading of PNIST dataset following Dumi compression of the data.
author | Frederic Bastien <nouiz@nouiz.org> |
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date | Thu, 06 Jan 2011 13:57:05 -0500 |
parents | bfe20d63f88c |
children |
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import tempfile import numpy import numpy.random from jobman import DD import tables from series import * import series ################################################# # Utils def compare_floats(f1,f2): if f1-f2 < 1e-3: return True return False def compare_lists(it1, it2, floats=False): if len(it1) != len(it2): return False for el1, el2 in zip(it1, it2): if floats: if not compare_floats(el1,el2): return False elif el1 != el2: return False return True ################################################# # Basic Series class tests def test_Series_types(): pass ################################################# # ErrorSeries tests def test_ErrorSeries_common_case(h5f=None): if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") validation_error = series.ErrorSeries(error_name="validation_error", table_name="validation_error", hdf5_file=h5f, index_names=('epoch','minibatch'), title="Validation error indexed by epoch and minibatch") # (1,1), (1,2) etc. are (epoch, minibatch) index validation_error.append((1,1), 32.0) validation_error.append((1,2), 30.0) validation_error.append((2,1), 28.0) validation_error.append((2,2), 26.0) h5f.close() h5f = tables.openFile(h5f_path, "r") table = h5f.getNode('/', 'validation_error') assert compare_lists(table.cols.epoch[:], [1,1,2,2]) assert compare_lists(table.cols.minibatch[:], [1,2,1,2]) assert compare_lists(table.cols.validation_error[:], [32.0, 30.0, 28.0, 26.0]) def test_ErrorSeries_no_index(h5f=None): if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") validation_error = series.ErrorSeries(error_name="validation_error", table_name="validation_error", hdf5_file=h5f, # empty tuple index_names=tuple(), title="Validation error with no index") # (1,1), (1,2) etc. are (epoch, minibatch) index validation_error.append(tuple(), 32.0) validation_error.append(tuple(), 30.0) validation_error.append(tuple(), 28.0) validation_error.append(tuple(), 26.0) h5f.close() h5f = tables.openFile(h5f_path, "r") table = h5f.getNode('/', 'validation_error') assert compare_lists(table.cols.validation_error[:], [32.0, 30.0, 28.0, 26.0]) assert not ("epoch" in dir(table.cols)) def test_ErrorSeries_notimestamp(h5f=None): if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") validation_error = series.ErrorSeries(error_name="validation_error", table_name="validation_error", hdf5_file=h5f, index_names=('epoch','minibatch'), title="Validation error indexed by epoch and minibatch", store_timestamp=False) # (1,1), (1,2) etc. are (epoch, minibatch) index validation_error.append((1,1), 32.0) h5f.close() h5f = tables.openFile(h5f_path, "r") table = h5f.getNode('/', 'validation_error') assert compare_lists(table.cols.epoch[:], [1]) assert not ("timestamp" in dir(table.cols)) assert "cpuclock" in dir(table.cols) def test_ErrorSeries_nocpuclock(h5f=None): if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") validation_error = series.ErrorSeries(error_name="validation_error", table_name="validation_error", hdf5_file=h5f, index_names=('epoch','minibatch'), title="Validation error indexed by epoch and minibatch", store_cpuclock=False) # (1,1), (1,2) etc. are (epoch, minibatch) index validation_error.append((1,1), 32.0) h5f.close() h5f = tables.openFile(h5f_path, "r") table = h5f.getNode('/', 'validation_error') assert compare_lists(table.cols.epoch[:], [1]) assert not ("cpuclock" in dir(table.cols)) assert "timestamp" in dir(table.cols) def test_AccumulatorSeriesWrapper_common_case(h5f=None): if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") validation_error = ErrorSeries(error_name="accumulated_validation_error", table_name="accumulated_validation_error", hdf5_file=h5f, index_names=('epoch','minibatch'), title="Validation error, summed every 3 minibatches, indexed by epoch and minibatch") accumulator = AccumulatorSeriesWrapper(base_series=validation_error, reduce_every=3, reduce_function=numpy.sum) # (1,1), (1,2) etc. are (epoch, minibatch) index accumulator.append((1,1), 32.0) accumulator.append((1,2), 30.0) accumulator.append((2,1), 28.0) accumulator.append((2,2), 26.0) accumulator.append((3,1), 24.0) accumulator.append((3,2), 22.0) h5f.close() h5f = tables.openFile(h5f_path, "r") table = h5f.getNode('/', 'accumulated_validation_error') assert compare_lists(table.cols.epoch[:], [2,3]) assert compare_lists(table.cols.minibatch[:], [1,2]) assert compare_lists(table.cols.accumulated_validation_error[:], [90.0,72.0], floats=True) def test_BasicStatisticsSeries_common_case(h5f=None): if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") stats_series = BasicStatisticsSeries(table_name="b_vector_statistics", hdf5_file=h5f, index_names=('epoch','minibatch'), title="Basic statistics for b vector indexed by epoch and minibatch") # (1,1), (1,2) etc. are (epoch, minibatch) index stats_series.append((1,1), [0.15, 0.20, 0.30]) stats_series.append((1,2), [-0.18, 0.30, 0.58]) stats_series.append((2,1), [0.18, -0.38, -0.68]) stats_series.append((2,2), [0.15, 0.02, 1.9]) h5f.close() h5f = tables.openFile(h5f_path, "r") table = h5f.getNode('/', 'b_vector_statistics') assert compare_lists(table.cols.epoch[:], [1,1,2,2]) assert compare_lists(table.cols.minibatch[:], [1,2,1,2]) assert compare_lists(table.cols.mean[:], [0.21666667, 0.23333333, -0.29333332, 0.69], floats=True) assert compare_lists(table.cols.min[:], [0.15000001, -0.18000001, -0.68000001, 0.02], floats=True) assert compare_lists(table.cols.max[:], [0.30, 0.58, 0.18, 1.9], floats=True) assert compare_lists(table.cols.std[:], [0.06236095, 0.31382939, 0.35640177, 0.85724366], floats=True) def test_SharedParamsStatisticsWrapper_commoncase(h5f=None): import numpy.random if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") stats = SharedParamsStatisticsWrapper(new_group_name="params", base_group="/", arrays_names=('b1','b2','b3'), hdf5_file=h5f, index_names=('epoch','minibatch')) b1 = DD({'value':numpy.random.rand(5)}) b2 = DD({'value':numpy.random.rand(5)}) b3 = DD({'value':numpy.random.rand(5)}) stats.append((1,1), [b1,b2,b3]) h5f.close() h5f = tables.openFile(h5f_path, "r") b1_table = h5f.getNode('/params', 'b1') b3_table = h5f.getNode('/params', 'b3') assert b1_table.cols.mean[0] - numpy.mean(b1.value) < 1e-3 assert b3_table.cols.mean[0] - numpy.mean(b3.value) < 1e-3 assert b1_table.cols.min[0] - numpy.min(b1.value) < 1e-3 assert b3_table.cols.min[0] - numpy.min(b3.value) < 1e-3 def test_SharedParamsStatisticsWrapper_notimestamp(h5f=None): import numpy.random if not h5f: h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") stats = SharedParamsStatisticsWrapper(new_group_name="params", base_group="/", arrays_names=('b1','b2','b3'), hdf5_file=h5f, index_names=('epoch','minibatch'), store_timestamp=False) b1 = DD({'value':numpy.random.rand(5)}) b2 = DD({'value':numpy.random.rand(5)}) b3 = DD({'value':numpy.random.rand(5)}) stats.append((1,1), [b1,b2,b3]) h5f.close() h5f = tables.openFile(h5f_path, "r") b1_table = h5f.getNode('/params', 'b1') b3_table = h5f.getNode('/params', 'b3') assert b1_table.cols.mean[0] - numpy.mean(b1.value) < 1e-3 assert b3_table.cols.mean[0] - numpy.mean(b3.value) < 1e-3 assert b1_table.cols.min[0] - numpy.min(b1.value) < 1e-3 assert b3_table.cols.min[0] - numpy.min(b3.value) < 1e-3 assert not ('timestamp' in dir(b1_table.cols)) def test_get_desc(): h5f_path = tempfile.NamedTemporaryFile().name h5f = tables.openFile(h5f_path, "w") desc = series._get_description_with_n_ints_n_floats(("col1","col2"), ("col3","col4")) mytable = h5f.createTable('/', 'mytable', desc) # just make sure the columns are there... otherwise this will throw an exception mytable.cols.col1 mytable.cols.col2 mytable.cols.col3 mytable.cols.col4 try: # this should fail... LocalDescription must be local to get_desc_etc test = LocalDescription assert False except: assert True assert True def test_index_to_tuple_floaterror(): try: series._index_to_tuple(5.1) assert False except TypeError: assert True def test_index_to_tuple_arrayok(): tpl = series._index_to_tuple([1,2,3]) assert type(tpl) == tuple and tpl[1] == 2 and tpl[2] == 3 def test_index_to_tuple_intbecomestuple(): tpl = series._index_to_tuple(32) assert type(tpl) == tuple and tpl == (32,) def test_index_to_tuple_longbecomestuple(): tpl = series._index_to_tuple(928374928374928L) assert type(tpl) == tuple and tpl == (928374928374928L,) if __name__ == '__main__': import tempfile test_get_desc() test_ErrorSeries_common_case() test_BasicStatisticsSeries_common_case() test_AccumulatorSeriesWrapper_common_case() test_SharedParamsStatisticsWrapper_commoncase()