update tests
This commit is contained in:
Emily Soth
parent
5ca1ec3da3
commit
a5cd7186bf
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@ -240,7 +240,7 @@ MODEL_SPEC = {
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"type": "freestyle_string",
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"about": gettext("Unique name for the habitat. No spaces allowed.")},
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"path": {
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"type": "raster_or_vector",
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"type": {"raster", "vector"},
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"fields": {},
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"geometries": {"POLYGON", "MULTIPOLYGON"},
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"bands": {1: {"type": "number", "units": u.none}},
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@ -314,8 +314,13 @@ def build_datastack_archive(args, model_name, datastack_path):
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if 'columns' in args_spec[key]:
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for col_name, col_definition in (
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args_spec[key]['columns'].items()):
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if col_definition['type'] in [
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'raster', 'vector', 'raster_or_vector']:
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# Type attribute may be a string (one type) or set
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# (multiple types allowed), so always convert to a set for
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# easier comparison.
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col_types = col_definition['type']
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if isinstance(col_types, str):
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col_types = set([col_types])
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if col_types.intersection(spatial_types):
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spatial_columns.append(col_name)
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LOGGER.debug(f'Detected spatial columns: {spatial_columns}')
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@ -70,7 +70,7 @@ MODEL_SPEC = {
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"names must match the habitat and stressor names in "
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"the Criteria Scores Table.")},
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"path": {
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"type": "raster_or_vector",
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"type": {"raster", "vector"},
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"bands": {1: {
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"type": "number",
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"units": u.none,
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@ -52,7 +52,7 @@ predictor_table_columns = {
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"characters or less).")
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},
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"path": {
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"type": "raster_or_vector",
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"type": {"raster", "vector"},
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"about": gettext("A spatial file to use as a predictor."),
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"bands": {1: {"type": "number", "units": u.none}},
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"fields": {},
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@ -648,7 +648,7 @@ def get_validated_dataframe(csv_path, columns=None, rows=None, index_col=None,
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for col in matching_cols:
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try:
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# frozenset needed to make the set hashable. A frozenset and set with the same members are equal.
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if col_spec['type'] in {'csv', 'directory', 'file', 'raster', 'vector', 'raster_or_vector'}:
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if col_spec['type'] in {'csv', 'directory', 'file', 'raster', 'vector', frozenset({'raster', 'vector'})}:
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df[col] = df[col].apply(
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lambda p: p if pandas.isna(p) else utils.expand_path(str(p).strip(), csv_path))
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df[col] = df[col].astype(pandas.StringDtype())
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@ -669,12 +669,15 @@ def get_validated_dataframe(csv_path, columns=None, rows=None, index_col=None,
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f'Value(s) in the "{col}" column could not be interpreted '
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f'as {col_spec["type"]}s. Original error: {err}')
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if col_spec['type'] in {'csv', 'directory', 'file', 'raster', 'vector', 'raster_or_vector'}:
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col_type = col_spec['type']
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if isinstance(col_type, set):
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col_type = frozenset(col_type)
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if col_type in {'csv', 'directory', 'file', 'raster', 'vector', frozenset({'raster', 'vector'})}:
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# recursively validate the files within the column
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def check_value(value):
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if pandas.isna(value):
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return
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err_msg = _VALIDATION_FUNCS[col_spec['type']](value, **col_spec)
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err_msg = _VALIDATION_FUNCS[col_type](value, **col_spec)
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if err_msg:
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raise ValueError(
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f'Error in {axis} "{col}", value "{value}": {err_msg}')
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@ -838,6 +841,8 @@ def timeout(func, *args, timeout=5, **kwargs):
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message_queue = queue.Queue()
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def wrapper_func():
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print(func)
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print(args, kwargs)
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message_queue.put(func(*args, **kwargs))
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thread = threading.Thread(target=wrapper_func)
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@ -903,7 +908,7 @@ _VALIDATION_FUNCS = {
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'option_string': check_option_string,
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'raster': functools.partial(timeout, check_raster),
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'vector': functools.partial(timeout, check_vector),
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'raster_or_vector': functools.partial(timeout, check_raster_or_vector),
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frozenset({'raster', 'vector'}): functools.partial(timeout, check_raster_or_vector),
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'other': None, # Up to the user to define their validate()
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}
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@ -1041,7 +1046,10 @@ def validate(args, spec, spatial_overlap_opts=None):
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LOGGER.debug(f'Provided key {key} does not exist in MODEL_SPEC')
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continue
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type_validation_func = _VALIDATION_FUNCS[parameter_spec['type']]
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param_type = parameter_spec['type']
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if isinstance(param_type, set):
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param_type = frozenset(param_type)
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type_validation_func = _VALIDATION_FUNCS[param_type]
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if type_validation_func is None:
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# Validation for 'other' type must be performed by the user.
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@ -1182,6 +1190,8 @@ def invest_validator(validate_func):
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# need to validate it.
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if args_value not in ('', None):
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input_type = args_key_spec['type']
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if isinstance(input_type, set):
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input_type = frozenset(input_type)
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validator_func = _VALIDATION_FUNCS[input_type]
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error_msg = validator_func(args_value, **args_key_spec)
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@ -14,7 +14,11 @@ MODEL_SPEC = {
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'type': 'csv',
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'columns': {
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'ID': {'type': 'integer'},
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'path': {'type': {'raster', 'vector'}},
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'path': {
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'type': {'raster', 'vector'},
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'geometries': {'POINT', 'POLYGON'},
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'bands': {1: {'type': 'number'}}
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}
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}
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}
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}
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@ -1260,7 +1260,7 @@ class HRAModelTests(unittest.TestCase):
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array, 255, (10, -10), (ORIGIN[0] - 50, ORIGIN[1] - 50),
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SRS_WKT, full_path)
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archive_path = '/Users/emily/Documents/hrad_dat.tar.gz'#os.path.join(self.workspace_dir, 'datstack.tar.gz')
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archive_path = os.path.join(self.workspace_dir, 'datstack.tar.gz')
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datastack.build_datastack_archive(
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args, 'natcap.invest.hra', archive_path)
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@ -19,7 +19,6 @@ valid_nested_types = {
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'raster',
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'ratio',
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'vector',
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'raster_or_vector'
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},
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'raster': {'integer', 'number', 'ratio', 'percent'},
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'vector': {
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@ -38,8 +37,7 @@ valid_nested_types = {
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'percent',
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'raster',
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'ratio',
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'vector',
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'raster_or_vector'},
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'vector'},
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'directory': {'csv', 'directory', 'file', 'raster', 'vector'}
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}
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@ -128,7 +126,7 @@ class ValidateModelSpecs(unittest.TestCase):
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self.assertIsInstance(spec['units'], pint.Unit)
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attrs.remove('units')
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elif t in {'raster', 'raster_or_vector'}:
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elif t == 'raster':
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# raster type should have a bands property that maps each band
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# index to a nested type dictionary describing the band's data
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self.assertIn('bands', spec)
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@ -141,7 +139,7 @@ class ValidateModelSpecs(unittest.TestCase):
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parent_type=t)
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attrs.remove('bands')
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elif t in {'vector', 'raster_or_vector'}:
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elif t == 'vector':
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# vector type should have:
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# - a fields property that maps each field header to a nested
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# type dictionary describing the data in that field
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@ -251,191 +249,195 @@ class ValidateModelSpecs(unittest.TestCase):
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for attr in ['name', 'about']:
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self.assertIn(attr, arg)
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# arg['type'] can be either a string or a set of strings
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types = arg['type'] if isinstance(
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arg['type'], set) else [arg['type']]
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attrs = set(arg.keys())
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self.assertIn(arg['type'], valid_nested_types[parent_type])
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for t in types:
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self.assertIn(t, valid_nested_types[parent_type])
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if arg['type'] == 'option_string':
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# option_string type should have an options property that
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# describes the valid options
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self.assertIn('options', arg)
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# May be a list or dict because some option sets are self
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# explanatory and others need a description
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self.assertIsInstance(arg['options'], dict)
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for key, val in arg['options'].items():
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self.assertTrue(
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isinstance(key, str) or
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isinstance(key, int))
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self.assertIsInstance(val, dict)
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# top-level option_string args are shown as dropdowns
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# so each option needs a display name
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# an additional description is optional
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if parent_type is None:
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if t == 'option_string':
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# option_string type should have an options property that
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# describes the valid options
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self.assertIn('options', arg)
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# May be a list or dict because some option sets are self
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# explanatory and others need a description
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self.assertIsInstance(arg['options'], dict)
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for key, val in arg['options'].items():
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self.assertTrue(
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set(val.keys()) == {'display_name'} or
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set(val.keys()) == {
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'display_name', 'description'})
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# option_strings within a CSV or vector don't get a
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# display name. the user has to enter the key.
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else:
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self.assertEqual(set(val.keys()), {'description'})
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isinstance(key, str) or
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isinstance(key, int))
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self.assertIsInstance(val, dict)
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# top-level option_string args are shown as dropdowns
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# so each option needs a display name
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# an additional description is optional
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if parent_type is None:
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self.assertTrue(
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set(val.keys()) == {'display_name'} or
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set(val.keys()) == {
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'display_name', 'description'})
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# option_strings within a CSV or vector don't get a
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# display name. the user has to enter the key.
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else:
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self.assertEqual(set(val.keys()), {'description'})
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if 'display_name' in val:
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self.assertIsInstance(val['display_name'], str)
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if 'description' in val:
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self.assertIsInstance(val['description'], str)
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if 'display_name' in val:
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self.assertIsInstance(val['display_name'], str)
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if 'description' in val:
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self.assertIsInstance(val['description'], str)
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attrs.remove('options')
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attrs.remove('options')
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elif arg['type'] == 'freestyle_string':
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# freestyle_string may optionally have a regexp attribute
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# this is a regular expression that the string must match
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if 'regexp' in arg:
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self.assertIsInstance(arg['regexp'], str)
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re.compile(arg['regexp']) # should be regex compilable
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attrs.remove('regexp')
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elif t == 'freestyle_string':
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# freestyle_string may optionally have a regexp attribute
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# this is a regular expression that the string must match
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if 'regexp' in arg:
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self.assertIsInstance(arg['regexp'], str)
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re.compile(arg['regexp']) # should be regex compilable
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attrs.remove('regexp')
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elif arg['type'] == 'number':
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# number type should have a units property
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self.assertIn('units', arg)
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# Undefined units should use the custom u.none unit
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self.assertIsInstance(arg['units'], pint.Unit)
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attrs.remove('units')
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elif t == 'number':
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# number type should have a units property
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self.assertIn('units', arg)
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# Undefined units should use the custom u.none unit
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self.assertIsInstance(arg['units'], pint.Unit)
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attrs.remove('units')
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# number type may optionally have an 'expression' attribute
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# this is a string expression to be evaluated with the
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# intent of determining that the value is within a range.
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# The expression must contain the string ``value``, which
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# will represent the user-provided value (after it has been
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# cast to a float). Example: "(value >= 0) & (value <= 1)"
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if 'expression' in arg:
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self.assertIsInstance(arg['expression'], str)
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attrs.remove('expression')
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# number type may optionally have an 'expression' attribute
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# this is a string expression to be evaluated with the
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# intent of determining that the value is within a range.
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# The expression must contain the string ``value``, which
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# will represent the user-provided value (after it has been
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# cast to a float). Example: "(value >= 0) & (value <= 1)"
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if 'expression' in arg:
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self.assertIsInstance(arg['expression'], str)
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attrs.remove('expression')
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elif arg['type'] in {'raster', 'raster_or_vector'}:
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# raster type should have a bands property that maps each band
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# index to a nested type dictionary describing the band's data
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self.assertIn('bands', arg)
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self.assertIsInstance(arg['bands'], dict)
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for band in arg['bands']:
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self.assertIsInstance(band, int)
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self.validate_args(
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arg['bands'][band],
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f'{name}.bands.{band}',
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parent_type=arg['type'])
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attrs.remove('bands')
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# may optionally have a 'projected' attribute that says
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# whether the raster must be linearly projected
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if 'projected' in arg:
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self.assertIsInstance(arg['projected'], bool)
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attrs.remove('projected')
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# if 'projected' is True, may also have a 'projection_units'
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# attribute saying the expected linear projection unit
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if 'projection_units' in arg:
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# doesn't make sense to have projection units unless
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# projected is True
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self.assertTrue(arg['projected'])
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self.assertIsInstance(
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arg['projection_units'], pint.Unit)
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attrs.remove('projection_units')
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elif arg['type'] in {'vector', 'raster_or_vector'}:
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# vector type should have:
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# - a fields property that maps each field header to a nested
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# type dictionary describing the data in that field
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# - a geometries property: the set of valid geometry types
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self.assertIn('fields', arg)
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self.assertIsInstance(arg['fields'], dict)
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for field in arg['fields']:
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self.assertIsInstance(field, str)
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self.validate_args(
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arg['fields'][field],
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f'{name}.fields.{field}',
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parent_type=arg['type'])
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self.assertIn('geometries', arg)
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self.assertIsInstance(arg['geometries'], set)
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attrs.remove('fields')
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attrs.remove('geometries')
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# may optionally have a 'projected' attribute that says
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# whether the vector must be linearly projected
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if 'projected' in arg:
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self.assertIsInstance(arg['projected'], bool)
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attrs.remove('projected')
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# if 'projected' is True, may also have a 'projection_units'
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# attribute saying the expected linear projection unit
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if 'projection_units' in arg:
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# doesn't make sense to have projection units unless
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# projected is True
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self.assertTrue(arg['projected'])
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self.assertIsInstance(
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arg['projection_units'], pint.Unit)
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attrs.remove('projection_units')
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elif arg['type'] == 'csv':
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# csv type should have a rows property, columns property, or
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# neither. rows or columns properties map each expected header
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# name/pattern to a nested type dictionary describing the data
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# in that row/column. may have neither if the table structure
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# is too complex to describe this way.
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has_rows = 'rows' in arg
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has_cols = 'columns' in arg
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# should not have both
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self.assertFalse(has_rows and has_cols)
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if has_cols or has_rows:
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direction = 'rows' if has_rows else 'columns'
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headers = arg[direction]
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self.assertIsInstance(headers, dict)
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for header in headers:
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self.assertIsInstance(header, str)
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elif t == 'raster':
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# raster type should have a bands property that maps each band
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# index to a nested type dictionary describing the band's data
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self.assertIn('bands', arg)
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self.assertIsInstance(arg['bands'], dict)
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for band in arg['bands']:
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self.assertIsInstance(band, int)
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self.validate_args(
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headers[header],
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f'{name}.{direction}.{header}',
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parent_type=arg['type'])
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arg['bands'][band],
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f'{name}.bands.{band}',
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parent_type=t)
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attrs.remove('bands')
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if 'index_col' in arg:
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self.assertIn(arg['index_col'], arg['columns'])
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attrs.discard('index_col')
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# may optionally have a 'projected' attribute that says
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# whether the raster must be linearly projected
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if 'projected' in arg:
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self.assertIsInstance(arg['projected'], bool)
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attrs.remove('projected')
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# if 'projected' is True, may also have a 'projection_units'
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# attribute saying the expected linear projection unit
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if 'projection_units' in arg:
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# doesn't make sense to have projection units unless
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# projected is True
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self.assertTrue(arg['projected'])
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self.assertIsInstance(
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arg['projection_units'], pint.Unit)
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attrs.remove('projection_units')
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attrs.discard('rows')
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attrs.discard('columns')
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elif t == 'vector':
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# vector type should have:
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# - a fields property that maps each field header to a nested
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# type dictionary describing the data in that field
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# - a geometries property: the set of valid geometry types
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self.assertIn('fields', arg)
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self.assertIsInstance(arg['fields'], dict)
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for field in arg['fields']:
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self.assertIsInstance(field, str)
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self.validate_args(
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arg['fields'][field],
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f'{name}.fields.{field}',
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parent_type=t)
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elif arg['type'] == 'directory':
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||||
# directory type should have a contents property that maps each
|
||||
# expected path name/pattern within the directory to a nested
|
||||
# type dictionary describing the data at that filepath
|
||||
self.assertIn('contents', arg)
|
||||
self.assertIsInstance(arg['contents'], dict)
|
||||
for path in arg['contents']:
|
||||
self.assertIsInstance(path, str)
|
||||
self.validate_args(
|
||||
arg['contents'][path],
|
||||
f'{name}.contents.{path}',
|
||||
parent_type=arg['type'])
|
||||
attrs.remove('contents')
|
||||
self.assertIn('geometries', arg)
|
||||
self.assertIsInstance(arg['geometries'], set)
|
||||
|
||||
# may optionally have a 'permissions' attribute, which is a
|
||||
# string of the unix-style directory permissions e.g. 'rwx'
|
||||
if 'permissions' in arg:
|
||||
self.validate_permissions_value(arg['permissions'])
|
||||
attrs.remove('permissions')
|
||||
# may optionally have an 'must_exist' attribute, which says
|
||||
# whether the directory must already exist
|
||||
# this defaults to True
|
||||
if 'must_exist' in arg:
|
||||
self.assertIsInstance(arg['must_exist'], bool)
|
||||
attrs.remove('must_exist')
|
||||
attrs.remove('fields')
|
||||
attrs.remove('geometries')
|
||||
|
||||
elif arg['type'] == 'file':
|
||||
# file type may optionally have a 'permissions' attribute
|
||||
# this is a string listing the permissions e.g. 'rwx'
|
||||
if 'permissions' in arg:
|
||||
self.validate_permissions_value(arg['permissions'])
|
||||
# may optionally have a 'projected' attribute that says
|
||||
# whether the vector must be linearly projected
|
||||
if 'projected' in arg:
|
||||
self.assertIsInstance(arg['projected'], bool)
|
||||
attrs.remove('projected')
|
||||
# if 'projected' is True, may also have a 'projection_units'
|
||||
# attribute saying the expected linear projection unit
|
||||
if 'projection_units' in arg:
|
||||
# doesn't make sense to have projection units unless
|
||||
# projected is True
|
||||
self.assertTrue(arg['projected'])
|
||||
self.assertIsInstance(
|
||||
arg['projection_units'], pint.Unit)
|
||||
attrs.remove('projection_units')
|
||||
|
||||
elif t == 'csv':
|
||||
# csv type should have a rows property, columns property, or
|
||||
# neither. rows or columns properties map each expected header
|
||||
# name/pattern to a nested type dictionary describing the data
|
||||
# in that row/column. may have neither if the table structure
|
||||
# is too complex to describe this way.
|
||||
has_rows = 'rows' in arg
|
||||
has_cols = 'columns' in arg
|
||||
# should not have both
|
||||
self.assertFalse(has_rows and has_cols)
|
||||
|
||||
if has_cols or has_rows:
|
||||
direction = 'rows' if has_rows else 'columns'
|
||||
headers = arg[direction]
|
||||
self.assertIsInstance(headers, dict)
|
||||
|
||||
for header in headers:
|
||||
self.assertIsInstance(header, str)
|
||||
self.validate_args(
|
||||
headers[header],
|
||||
f'{name}.{direction}.{header}',
|
||||
parent_type=t)
|
||||
|
||||
if 'index_col' in arg:
|
||||
self.assertIn(arg['index_col'], arg['columns'])
|
||||
attrs.discard('index_col')
|
||||
|
||||
attrs.discard('rows')
|
||||
attrs.discard('columns')
|
||||
|
||||
elif t == 'directory':
|
||||
# directory type should have a contents property that maps each
|
||||
# expected path name/pattern within the directory to a nested
|
||||
# type dictionary describing the data at that filepath
|
||||
self.assertIn('contents', arg)
|
||||
self.assertIsInstance(arg['contents'], dict)
|
||||
for path in arg['contents']:
|
||||
self.assertIsInstance(path, str)
|
||||
self.validate_args(
|
||||
arg['contents'][path],
|
||||
f'{name}.contents.{path}',
|
||||
parent_type=t)
|
||||
attrs.remove('contents')
|
||||
|
||||
# may optionally have a 'permissions' attribute, which is a
|
||||
# string of the unix-style directory permissions e.g. 'rwx'
|
||||
if 'permissions' in arg:
|
||||
self.validate_permissions_value(arg['permissions'])
|
||||
attrs.remove('permissions')
|
||||
# may optionally have an 'must_exist' attribute, which says
|
||||
# whether the directory must already exist
|
||||
# this defaults to True
|
||||
if 'must_exist' in arg:
|
||||
self.assertIsInstance(arg['must_exist'], bool)
|
||||
attrs.remove('must_exist')
|
||||
|
||||
elif t == 'file':
|
||||
# file type may optionally have a 'permissions' attribute
|
||||
# this is a string listing the permissions e.g. 'rwx'
|
||||
if 'permissions' in arg:
|
||||
self.validate_permissions_value(arg['permissions'])
|
||||
|
||||
# iterate over the remaining attributes
|
||||
# type-specific ones have been removed by this point
|
||||
|
|
|
|||
Loading…
Reference in New Issue