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from past.builtins import basestring
import copy
import numpy as np
import pandas
import ulmo
import test_util
test_sets = [
{
'element': 'pdsi',
'by_state': False,
'values': [
{
'state': 'WY',
'state_code': 48,
'division': 8,
'year': 1998,
'month': 1,
'pdsi': 1.84,
}, {
'state': 'WY',
'state_code': 48,
'division': 8,
'year': 1998,
'month': 2,
'pdsi': 1.88,
}, {
'state': 'WY',
'state_code': 48,
'division': 8,
'year': 1998,
'month': 3,
'pdsi': 1.99,
}, {
'state': 'WY',
'state_code': 48,
'division': 8,
'year': 1998,
'month': 11,
'pdsi': 2.71,
}, {
'state': 'WY',
'state_code': 48,
'division': 8,
'year': 1998,
'month': 12,
'pdsi': 2.53,
}, {
'state': 'TX',
'state_code': 41,
'division': 10,
'year': 1895,
'month': 1,
'pdsi': -0.05,
}, {
'state': 'TX',
'state_code': 41,
'division': 10,
'year': 1895,
'month': 12,
'pdsi': 1.72,
},
]
}, {
'element': 'tmpc',
'by_state': True,
'values': [
{
'location': 'ME',
'location_code': 17,
'year': 1895,
'month': 1,
'tmpc': 12.20,
}, {
'location': 'ME',
'location_code': 17,
'year': 1895,
'month': 12,
'tmpc': 20.7,
}, {
'location': 'national',
'location_code': 110,
'year': 2013,
'month': 1,
'tmpc': 32.25,
}, {
'location': 'national',
'location_code': 110,
'year': 2013,
'month': 2,
'tmpc': 34.79,
},
]
}, {
'element': 'tmpc',
'by_state': True,
'location_names': 'full',
'values': [
{
'location': 'Maine',
'location_code': 17,
'year': 1895,
'month': 1,
'tmpc': 12.20,
},
]
}, {
'element': 'sp01',
'by_state': True,
'values': [
{
'location': 'AL',
'location_code': 1,
'year': 1895,
'month': 1,
'sp01': 1.23,
},
]
}, {
'element': ['sp01', 'tmpc', 'pdsi'],
'by_state': True,
'values': [
{
'location': 'AL',
'location_code': 1,
'year': 1895,
'month': 1,
'sp01': 1.23,
'tmpc': 43.1,
'pdsi': 0.78,
},
{
'location': None,
'location_code': 113,
'year': 1895,
'month': 1,
'sp01': None,
'tmpc': 15.5,
'pdsi': None,
},
]
},
]
def test_get_data_by_state():
state_tests = [s for s in test_sets if s['by_state']]
_run_test_sets(state_tests)
def test_get_data_by_climate_division():
division_tests = [s for s in test_sets if not s['by_state']]
_run_test_sets(division_tests)
def test_doesnt_have_locations_if_location_names_is_none():
element = 'pdsi'
use_file = _test_use_file(element, False)
data = ulmo.ncdc.cirs.get_data(
element, location_names=None, use_file=use_file, as_dataframe=True)
assert 'location' not in data.columns
def _run_test_sets(test_sets):
for test_set in test_sets:
test_args = copy.copy(test_set)
element = test_args.pop('element')
test_values = test_args.pop('values')
by_state = test_args['by_state']
use_file = _test_use_file(element, by_state)
data = ulmo.ncdc.cirs.get_data(
element, use_file=use_file, as_dataframe=True, **test_args)
if isinstance(element, basestring) or len(element) == 1:
not_nulls = data[element].notnull()
else:
not_nulls = pandas.notnull(data[element]).any(axis=1)
assert np.all(not_nulls)
for test_value in test_values:
_assert_inclusion(test_value, data)
def _assert_inclusion(value_dict, dataframe):
"tests that a value_dict is in a dataframe"
sub_df = dataframe.copy()
for k, v in value_dict.items():
if pandas.isnull(v):
sub_df = sub_df[pandas.isnull(sub_df[k])]
else:
sub_df = sub_df[sub_df[k] == v]
assert len(sub_df) == 1
def _test_use_file(elements, by_state):
if test_util.use_test_files():
if isinstance(elements, basestring):
div = "st" if by_state else "dv"
path = 'ncdc/cirs/climdiv-{elements}{div}-v1.0.0-20140304'.format(
elements=elements, div=div)
else:
path = 'ncdc/cirs/'
return test_util.get_test_file_path(path)
else:
return None
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