def test_from_scene_et_actual_daily_et_fraction_max(tol=0.0001):
output_coll = interpolate.from_scene_et_actual(
scene_coll(['et', 'time', 'mask'], et=100),
start_date='2017-07-01',
end_date='2017-08-01',
variables=['et', 'et_reference', 'et_fraction'],
interp_args={
'interp_method': 'linear',
'interp_days': 32,
'interp_source': 'IDAHO_EPSCOR/GRIDMET',
'interp_band': 'etr',
'interp_resample': 'nearest',
'et_fraction_min': 0.0,
'et_fraction_max': 1.4,
},
model_args={
'et_reference_source': 'IDAHO_EPSCOR/GRIDMET',
'et_reference_band': 'etr',
'et_reference_resample': 'nearest',
'et_reference_factor': 1.0,
},
t_interval='daily')
TEST_POINT = (-121.5265, 38.7399)
output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
assert abs(output['et_fraction']['2017-07-10'] - 1.4) <= tol
def test_from_scene_et_actual_monthly_et_reference_resample(tol=0.0001):
output_coll = interpolate.from_scene_et_actual(
scene_coll(['et', 'time', 'mask']),
start_date='2017-07-01',
end_date='2017-08-01',
variables=['et', 'et_reference', 'et_fraction', 'count'],
interp_args={
'interp_method': 'linear',
'interp_days': 32,
'interp_source': 'IDAHO_EPSCOR/GRIDMET',
'interp_band': 'etr',
'interp_resample': 'bilinear'
},
model_args={
'et_reference_source': 'IDAHO_EPSCOR/GRIDMET',
'et_reference_band': 'etr',
'et_reference_factor': 0.5,
'et_reference_resample': 'bilinear'
},
t_interval='monthly')
TEST_POINT = (-121.5265, 38.7399)
output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
assert abs(output['et']['2017-07-01'] - 142.895752) <= tol
assert abs(output['et_reference']['2017-07-01'] - 303.622559 * 0.5) <= tol
assert abs(output['et_fraction']['2017-07-01'] -
0.47063612937927246 / 0.5) <= tol
assert output['count']['2017-07-01'] == 3
def test_from_scene_et_fraction_custom_values(tol=0.0001):
output_coll = interpolate.from_scene_et_fraction(
scene_coll(['et_fraction', 'ndvi', 'time', 'mask']),
start_date='2017-07-01',
end_date='2017-08-01',
variables=['et', 'et_reference', 'et_fraction', 'ndvi', 'count'],
interp_args={
'interp_method': 'linear',
'interp_days': 32
},
model_args={
'et_reference_source': 'IDAHO_EPSCOR/GRIDMET',
'et_reference_band': 'etr',
'et_reference_factor': 1.0,
'et_reference_resample': 'nearest'
},
t_interval='custom')
TEST_POINT = (-121.5265, 38.7399)
output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
assert abs(output['ndvi']['2017-07-01'] - 0.6) <= tol
assert abs(output['et_fraction']['2017-07-01'] - 0.4) <= tol
assert abs(output['et_reference']['2017-07-01'] - 303.622559) <= tol
assert abs(output['et']['2017-07-01'] - (303.622559 * 0.4)) <= tol
assert output['count']['2017-07-01'] == 3
def test_from_scene_et_actual_daily_values(tol=0.0001):
output_coll = interpolate.from_scene_et_actual(
scene_coll(['et', 'time', 'mask']),
start_date='2017-07-01',
end_date='2017-08-01',
variables=['et', 'et_reference', 'et_fraction'],
interp_args={
'interp_method': 'linear',
'interp_days': 32,
'interp_source': 'IDAHO_EPSCOR/GRIDMET',
'interp_band': 'etr',
'interp_resample': 'nearest'
},
model_args={
'et_reference_source': 'IDAHO_EPSCOR/GRIDMET',
'et_reference_band': 'etr',
'et_reference_factor': 1.0,
'et_reference_resample': 'nearest'
},
t_interval='daily')
TEST_POINT = (-121.5265, 38.7399)
output = utils.point_coll_value(output_coll, TEST_POINT, scale=10)
assert abs(output['et_fraction']['2017-07-10'] - 0.4530041813850403) <= tol
assert abs(output['et_reference']['2017-07-10'] - 10.50879955291748) <= tol
assert abs(output['et']['2017-07-10'] - 4.7605299949646) <= tol
assert abs(output['et']['2017-07-01'] - 3.643141031265259) <= tol
assert abs(output['et']['2017-07-31'] - 4.9681010246276855) <= tol
assert '2017-08-01' not in output['et'].keys()
def test_point_coll_value(tol=0.001):
expected = 2364.351
output = utils.point_coll_value(
ee.ImageCollection([ee.Image('USGS/NED')]), [-106.03249, 37.17777])
assert abs(output['elevation']['2012-04-04'] - expected) <= tol