diff --git a/.travis.yml b/.travis.yml index 94539674f1..02e1b80ec8 100644 --- a/.travis.yml +++ b/.travis.yml @@ -20,6 +20,7 @@ install: python=$TRAVIS_PYTHON_VERSION numpy pandas pip pytables pytest urbansim - source activate test-environment +- pip install openmatrix - pip install pytest-cov coveralls pep8 - pip install . script: diff --git a/activitysim/omx/LICENSE.TXT b/activitysim/omx/LICENSE.TXT deleted file mode 100644 index d645695673..0000000000 --- a/activitysim/omx/LICENSE.TXT +++ /dev/null @@ -1,202 +0,0 @@ - - Apache License - Version 2.0, January 2004 - http://www.apache.org/licenses/ - - TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION - - 1. 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User must pass in either - an existing numpy matrix, or a shape and an atom type.""" - - # If object was passed in, make sure its shape is correct - if (self.shape() is not None and - obj is not None and - obj.shape != self.shape()): - raise ShapeError( - '%s has shape %s but this file requires shape %s' % - (name, obj.shape, self.shape())) - - # Create the HDF5 array - if tables.__version__.startswith('3'): - matrix = self.create_carray( - self.root.data, name, atom, shape, title, filters, - chunkshape, byteorder, createparents, obj) - - # Store shape if we don't have one yet - if self._shape is None: - storeshape = np.array(matrix.shape, dtype='int32') - self.root._v_attrs['SHAPE'] = storeshape - self._shape = matrix.shape - - # attributes - if attrs: - for key in attrs: - matrix.attrs[key] = attrs[key] - - return matrix - - def shape(self): - """Return the one and only shape of all matrices in this File""" - - # If we already have the shape, just return it - if self._shape: - return self._shape - - # If shape is already set in root node attributes, grab it - if 'SHAPE' in self.root._v_attrs: - # Shape is stored as a numpy.array: - arrayshape = self.root._v_attrs['SHAPE'] - # which must be converted to a tuple: - realshape = tuple(arrayshape) - self._shape = realshape - return self._shape - - # Inspect the first CArray object to determine its shape - if len(self) > 0: - self._shape = self.iter_nodes( - self.root.data, 'CArray').next().shape - - # Store it if we can - if self._iswritable(): - storeshape = np.array(self._shape, dtype='int32') - self.root._v_attrs['SHAPE'] = storeshape - - return self._shape - - else: - return None - - def list_matrices(self): - """Return list of Matrix names in this File""" - return [ - node.name for node in self.list_nodes(self.root.data, 'CArray')] - - def list_all_attributes(self): - """ - Return combined list of all attributes used for - any Matrix in this File - - """ - all_tags = set() - for m in self.iter_nodes(self.root.data, 'CArray'): - all_tags.update(m.attrs._v_attrnamesuser) - return sorted(all_tags) - - # MAPPINGS ----------------------------------------------- - def list_mappings(self): - try: - return [m.name for m in self.list_nodes(self.root.lookup)] - except: - return [] - - def delete_mapping(self, title): - try: - self.remove_node(self.root.lookup, title) - except: - raise LookupError('No such mapping: ' + title) - - def mapping(self, title): - """Return dict containing key:value pairs for specified mapping. Keys - represent the map item and value represents the array offset.""" - try: - # fetch entries - entries = [] - entries.extend(self.get_node(self.root.lookup, title)[:]) - - # build reverse key-lookup - keymap = {} - for i in range(len(entries)): - keymap[entries[i]] = i - - return keymap - - except: - raise LookupError('No such mapping: ' + title) - - def create_mapping(self, title, entries, overwrite=False): - """Create an equivalency index, which maps a raw data dimension to - another integer value. Once created, mappings can be referenced by - offset or by key.""" - - # Enforce shape-checking - if self.shape(): - if not len(entries) in self._shape: - raise ShapeError('Mapping must match one data dimension') - - # Handle case where mapping already exists: - if title in self.list_mappings(): - if overwrite: - self.delete_mapping(title) - else: - raise LookupError(title + ' mapping already exists.') - - # Create lookup group under root if it doesn't already exist. - if 'lookup' not in self.root: - self.create_group(self.root, 'lookup') - - # Write the mapping! - mymap = self.create_array( - self.root.lookup, title, atom=tables.UInt16Atom(), - shape=(len(entries),)) - mymap[:] = entries - - return mymap - - def __getitem__(self, key): - """Return a matrix by name, or a list of matrices by attributes""" - return self.get_node(self.root.data, key) - - def get_matrices_by_attr(self, key, value): - """ - Returns a list of matrices that have an attribute matching - a certain value. - - Parameters - ---------- - key : str - Attribute name to match. - value : object - Attribute value to match. - - Returns - ------- - matrices : list - - """ - return [ - m for m in self - if key in m.attrs and m.attrs[key] == value] - - def __len__(self): - return len(self.list_nodes(self.root.data, 'CArray')) - - def __setitem__(self, key, dataset): - # checks to see if it is already a tables instance, and if so, - # copies it - if isinstance(dataset, tables.CArray): - return dataset.copy(self.root.data, key) - else: - # We need to determine atom and shape from the object that's - # been passed in. - # This assumes 'dataset' is a numpy object. - atom = tables.Atom.from_dtype(dataset.dtype) - shape = dataset.shape - - return self.create_matrix(key, atom, shape, obj=dataset) - - def __delitem__(self, key): - self.remove_node(self.root.data, key) - - def __iter__(self): - """Iterate over the keys in this container""" - return self.iter_nodes(self.root.data, 'CArray') - - def __contains__(self, item): - return item in self.root.data - - -def open_omxfile( - filename, mode='r', title='', root_uep='/', - filters=tables.Filters( - complevel=1, shuffle=True, fletcher32=False, complib='zlib'), - shape=None, **kwargs): - """Open or create a new OMX file. New files will be created with default - zlib compression enabled.""" - - f = OMXFile(filename, mode, title, root_uep, filters, **kwargs) - - # add omx structure if file is writable - if mode != 'r': - # version number - if 'OMX_VERSION' not in f.root._v_attrs: - f.root._v_attrs['OMX_VERSION'] = OMX_VERSION - - # shape - if shape: - storeshape = np.array(shape, dtype='int32') - f.root._v_attrs['SHAPE'] = storeshape - - # /data and /lookup folders - if 'data' not in f.root: - f.create_group(f.root, "data") - if 'lookup' not in f.root: - f.create_group(f.root, "lookup") - - return f diff --git a/activitysim/omx/tests/__init__.py b/activitysim/omx/tests/__init__.py deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/activitysim/omx/tests/test_omxfile.py b/activitysim/omx/tests/test_omxfile.py deleted file mode 100644 index 7f8b6ac23a..0000000000 --- a/activitysim/omx/tests/test_omxfile.py +++ /dev/null @@ -1,153 +0,0 @@ -# Licensed under the Apache License, v2.0 -# See activitysim/omx/LICENSE.txt -# Modified from the original OMX library available at -# https://github.com/osPlanning/omx/tree/dev/api/python/omx - -import os -import tempfile - -import numpy as np -import numpy.testing as npt -import pytest -import tables - -from .. import open_omxfile, ShapeError - - -@pytest.fixture -def tmpomx(request): - with tempfile.NamedTemporaryFile() as f: - fname = f.name - - def cleanup(): - if os.path.exists(fname): - os.remove(fname) - request.addfinalizer(cleanup) - - return fname - - -@pytest.fixture -def ones5x5(): - return np.ones((5, 5)) - - -@pytest.fixture -def basic_omx(request, tmpomx, ones5x5): - f = open_omxfile(tmpomx, mode='w') - f['m1'] = ones5x5 - - def fin(): - f.close() - request.addfinalizer(fin) - - return f - - -def test_open_readonly_hdf5_file(tmpomx): - f = tables.open_file(tmpomx, 'w') - f.close() - assert os.path.exists(tmpomx) - f = open_omxfile(tmpomx, 'r') - f.close() - - -def test_set_get_del(tmpomx, ones5x5): - with open_omxfile(tmpomx, 'w') as f: - f['m1'] = ones5x5 - npt.assert_array_equal(f['m1'], ones5x5) - assert f.shape() == (5, 5) - del f['m1'] - assert 'm1' not in f - - -def test_create_matrix(tmpomx, ones5x5): - with open_omxfile(tmpomx, 'w') as f: - f.create_matrix('m1', obj=ones5x5) - npt.assert_array_equal(f['m1'], ones5x5) - assert f.shape() == (5, 5) - - # test check for shape matching - with pytest.raises(ShapeError): - f.create_matrix('m2', obj=np.ones((8, 8))) - - -def test_add_matrix_to_readonly_file(tmpomx, ones5x5): - with open_omxfile(tmpomx, 'w') as f: - f['m2'] = ones5x5 - - with open_omxfile(tmpomx, 'r') as f: - with pytest.raises(tables.FileModeError): - f['m1'] = ones5x5 - - -def test_add_matrix_with_same_name(tmpomx, ones5x5): - with open_omxfile(tmpomx, 'w') as f: - f['m1'] = ones5x5 - - # now add m1 again: - with pytest.raises(tables.NodeError): - f['m1'] = ones5x5 - - -def test_len_list_iter(tmpomx, ones5x5): - names = ['m{}'.format(x) for x in range(5)] - with open_omxfile(tmpomx, 'w') as f: - for m in names: - f[m] = ones5x5 - - for mat in f: - npt.assert_array_equal(mat, ones5x5) - - assert len(f) == len(names) - assert f.list_matrices() == names - - -def test_shape(tmpomx): - with open_omxfile(tmpomx, mode='w', shape=(5, 5)) as f: - assert f.shape() == (5, 5) - - with pytest.raises(ShapeError): - f['test'] = np.ones(10) - - -def test_contains(basic_omx): - assert 'm1' in basic_omx - - -def test_list_all_attrs(basic_omx, ones5x5): - basic_omx['m2'] = ones5x5 - - assert basic_omx.list_all_attributes() == [] - - basic_omx['m1'].attrs['a1'] = 'a1' - basic_omx['m1'].attrs['a2'] = 'a2' - basic_omx['m2'].attrs['a2'] = 'a2' - basic_omx['m2'].attrs['a3'] = 'a3' - - assert basic_omx.list_all_attributes() == ['a1', 'a2', 'a3'] - - -def test_matrices_by_attr(basic_omx, ones5x5): - bo = basic_omx - bo['m2'] = ones5x5 - bo['m3'] = ones5x5 - - for m in bo: - m.attrs['a1'] = 'a1' - m.attrs['a2'] = 'a2' - bo['m3'].attrs['a2'] = 'a22' - bo['m3'].attrs['a3'] = 'a3' - - gmba = bo.get_matrices_by_attr - - assert gmba('zz', 'zz') == [] - assert gmba('a1', 'a1') == [bo['m1'], bo['m2'], bo['m3']] - assert gmba('a2', 'a2') == [bo['m1'], bo['m2']] - assert gmba('a2', 'a22') == [bo['m3']] - assert gmba('a3', 'a3') == [bo['m3']] - - -def test_set_with_carray(basic_omx): - basic_omx['m2'] = basic_omx['m1'] - npt.assert_array_equal(basic_omx['m2'], basic_omx['m1']) diff --git a/setup.py b/setup.py index d88ecdb149..53aeb9c4fd 100644 --- a/setup.py +++ b/setup.py @@ -19,6 +19,7 @@ packages=find_packages(exclude=['*.tests']), install_requires=[ 'numpy>=1.8.0', + 'openmatrix>=0.2.2', 'pandas>=0.13.1', 'tables>=3.1.0', 'urbansim>=1.3'