def test_Image_etf_values(lst, ndvi, dt, elev, tcorr, tmax, expected,
tol=0.0001):
output_img = model.Image(
default_image(lst=lst, ndvi=ndvi), dt_source=dt, elev_source=elev,
tcorr_source=tcorr, tmax_source=tmax).etf
output = utils.constant_image_value(ee.Image(output_img))
assert abs(output['etf'] - expected) <= tol
def test_Image_ndvi_properties():
"""Test if properties are set on the NDVI image"""
output = utils.getinfo(model.Image(default_image()).ndvi)
assert output['bands'][0]['id'] == 'ndvi'
assert output['properties']['system:index'] == SCENE_ID
assert output['properties']['system:time_start'] == SCENE_TIME
assert output['properties']['image_id'] == COLL_ID + SCENE_ID
def test_Image_time_values():
# The time image is currently being built from the etf image, so all the
# ancillary values must be set for the constant_image_value to work.
output = utils.constant_image_value(model.Image(
default_image(ndvi=0.5, lst=308), dt_source=10, elev_source=50,
tcorr_source=0.98, tmax_source=310).time)
assert output['time'] == SCENE_TIME
def test_Image_tcorr_ftr_source(tcorr_source,
tmax_source,
scene_id,
month,
expected,
tol=0.0001):
"""Test getting Tcorr value and index for a single date at a real point"""
scene_date = datetime.datetime.strptime(scene_id.split('_')[-1], '%Y%m%d') \
.strftime('%Y-%m-%d')
input_image = ee.Image.constant(1).set({
'system:index':
scene_id,
'system:time_start':
ee.Date(scene_date).millis()
})
m = ssebop.Image(input_image,
tcorr_source=tcorr_source,
tmax_source=tmax_source)
# Overwrite the month property with the test value
m._month = ee.Number(month)
# _tcorr returns a tuple of the tcorr and tcorr_index
tcorr, tcorr_index = m.tcorr
tcorr = utils.getinfo(tcorr)
tcorr_index = utils.getinfo(tcorr_index)
assert abs(tcorr - expected[0]) <= tol
assert tcorr_index == expected[1]
def default_image_obj(
lst=305,
ndvi=0.8,
# et_reference_source='IDAHO_EPSCOR/GRIDMET',
et_reference_source=9.5730,
et_reference_band='etr',
et_reference_factor=1,
et_reference_resample='nearest',
dt_source=18,
elev_source=67,
elr_flag=False,
tcorr_source=0.9744,
tmax_source=310.15,
dt_resample='nearest',
tmax_resample='nearest',
):
return ssebop.Image(**default_image_args(
lst=lst,
ndvi=ndvi,
et_reference_source=et_reference_source,
et_reference_band=et_reference_band,
et_reference_factor=et_reference_factor,
et_reference_resample=et_reference_resample,
dt_source=dt_source,
elev_source=elev_source,
elr_flag=elr_flag,
tcorr_source=tcorr_source,
tmax_source=tmax_source,
dt_resample=dt_resample,
tmax_resample=tmax_resample,
))
def test_Image_etf_clamp_nodata(lst, ndvi, dt, elev, tcorr, tmax, expected):
"""Test that ETf is set to nodata for ETf > 1.3"""
output_img = model.Image(
default_image(lst=lst, ndvi=ndvi), dt_source=dt, elev_source=elev,
tcorr_source=tcorr, tmax_source=tmax).etf
output = utils.constant_image_value(ee.Image(output_img))
assert output['etf'] is None and expected is None
def test_Image_lst_properties():
"""Test if properties are set on the LST image"""
output = utils.getinfo(ssebop.Image(default_image()).lst)
assert output['bands'][0]['id'] == 'lst'
assert output['properties']['system:index'] == SCENE_ID
assert output['properties']['system:time_start'] == SCENE_TIME
assert output['properties']['image_id'] == COLL_ID + SCENE_ID
def test_Image_mask_values():
output_img = ssebop.Image(default_image(ndvi=0.5, lst=308),
dt_source=10,
elev_source=50,
tcorr_source=0.98,
tmax_source=310).mask
output = utils.constant_image_value(output_img)
assert output['mask'] == 1
def test_Image_etf_elr_param(lst, ndvi, dt, elev, tcorr, tmax, elr, expected,
tol=0.0001):
"""Test that elr_flag works and changes ETf values"""
output_img = model.Image(
default_image(lst=lst, ndvi=ndvi), dt_source=dt, elev_source=elev,
tcorr_source=tcorr, tmax_source=tmax, elr_flag=elr).etf
output = utils.constant_image_value(ee.Image(output_img))
assert abs(output['etf'] - expected) <= tol
def test_Image_etf_tdiff_param(lst, ndvi, dt, elev, tcorr, tmax, tdiff,
expected):
"""Test that ETf is set to nodata for tdiff values outside threshold"""
output_img = model.Image(
default_image(lst=lst, ndvi=ndvi), dt_source=dt, elev_source=elev,
tcorr_source=tcorr, tmax_source=tmax, tdiff_threshold=tdiff).etf
output = utils.constant_image_value(ee.Image(output_img))
assert output['etf'] is None and expected is None
def test_Image_et_values(tol=0.0001):
output_img = ssebop.Image(default_image(ndvi=0.5, lst=308),
dt_source=10,
elev_source=50,
tcorr_source=0.98,
tmax_source=310,
etr_source=10).et
output = utils.constant_image_value(output_img)
assert abs(output['et'] - 5.8) <= tol
def test_Image_tcorr_image_values(lst=300,
ndvi=0.8,
tmax=306,
expected=0.9804,
tol=0.0001):
output = utils.constant_image_value(
ssebop.Image(default_image(lst=lst, ndvi=ndvi),
tmax_source=tmax).tcorr_image)
assert abs(output['tcorr'] - expected) <= tol
def test_Image_tcorr_stats_constant(expected=0.993548387, tol=0.00000001):
# The input image needs to be clipped otherwise it is unbounded
input_image = ee.Image(default_image(ndvi=0.8, lst=308)) \
.clip(ee.Geometry.Rectangle(-120, 39, -119, 40))
output = utils.getinfo(
model.Image(input_image, dt_source=10, elev_source=50,
tcorr_source=0.98, tmax_source=310).tcorr_stats)
assert abs(output['tcorr_p5'] - expected) <= tol
assert output['tcorr_count'] == 1
def test_Image_calculate_values(tol=0.0001):
"""Test if the calculate method returns ET, ETr, and ETf values"""
output_img = ssebop.Image(
default_image(ndvi=0.5, lst=308), dt_source=10, elev_source=50,
tcorr_source=0.98, tmax_source=310, etr_source=10)\
.calculate(['et', 'etr', 'etf'])
output = utils.constant_image_value(output_img)
assert abs(output['et'] - 5.8) <= tol
assert abs(output['etr'] - 10) <= tol
assert abs(output['etf'] - 0.58) <= tol
def test_Image_dt_clamping(doy, dt_min, dt_max):
m = model.Image(default_image(), dt_source='DAYMET_MEDIAN_V1',
dt_min=dt_min, dt_max=dt_max)
m._doy = doy
reducer = ee.Reducer.min().combine(ee.Reducer.max(), sharedInputs=True)
output = utils.getinfo(ee.Image(m._dt)\
.reduceRegion(reducer=reducer, scale=1000, tileScale=4, maxPixels=2E8,
geometry=ee.Geometry.Rectangle(-125, 25, -65, 50)))
assert output['dt_min'] >= dt_min
assert output['dt_max'] <= dt_max
def test_Image_tcorr_image_daily():
"""Tcorr should be masked for date outside range with IMAGE_DAILY"""
input_image = ee.Image.constant(1).set({
'system:time_start': ee.Date('1980-07-04').millis()})
m = model.Image(input_image, tcorr_source='IMAGE_DAILY',
tmax_source='TOPOWX_MEDIAN_V0')
tcorr_img, index_img = m._tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.point_image_value(index_img, SCENE_POINT)
assert tcorr['tcorr'] is None
assert index['index'] is None
def test_Image_tmax_fallback(tmax_source, xy, expected, tol=0.001):
"""Test getting Tmax median value when daily doesn't exist
To test this, move the test date into the future
"""
input_img = ee.Image.constant([300, 0.8]).rename(['lst', 'ndvi']) \
.set({'system:index': SCENE_ID,
'system:time_start': ee.Date(SCENE_DATE).update(2099).millis()})
output_img = ssebop.Image(input_img, tmax_source=tmax_source).tmax
output = utils.point_image_value(ee.Image(output_img), xy)
assert abs(output['tmax'] - expected) <= tol
def test_Image_dt_source_calculated(dt_source, date, xy, expected, tol=0.001):
"""Test getting calculated dT values for a single date at a real point"""
m = ssebop.Image(default_image(), dt_source=dt_source)
# Start/end date are needed to filter the source collection
m._start_date = ee.Date.parse('yyyy-MM-dd', date)
m._end_date = ee.Date.parse('yyyy-MM-dd', date).advance(1, 'day')
# DOY is needed in dT calculation
m._doy = ee.Date.parse('yyyy-MM-dd', date).getRelative('day', 'year')\
.int().add(1)
output = utils.point_image_value(ee.Image(m.dt), xy)
assert abs(output['dt'] - expected) <= tol
def test_Image_tcorr_image_annual(expected=[0.9786, 2], tol=0.0001):
"""Test getting annual Tcorr from composite when monthly/daily are missing"""
input_image = ee.Image.constant(1).set({
'system:time_start': ee.Date('1980-07-04').millis()})
m = model.Image(input_image, tcorr_source='IMAGE',
tmax_source='TOPOWX_MEDIAN_V0')
m._month = ee.Number(9999)
tcorr_img, index_img = m._tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.point_image_value(index_img, SCENE_POINT)
assert abs(tcorr['tcorr'] - expected[0]) <= tol
assert index['index'] == expected[1]
def default_image_obj(lst=305,
ndvi=0.8,
etr_source='IDAHO_EPSCOR/GRIDMET',
etr_band='etr',
etr_factor=0.85,
etr_resample='nearest'):
return ssebop.Image(**default_image_args(lst=lst,
ndvi=ndvi,
etr_source=etr_source,
etr_band=etr_band,
etr_factor=etr_factor,
etr_resample=etr_resample))
def test_Image_default_parameters():
m = model.Image(default_image())
assert m.etr_source == None
assert m.etr_band == None
assert m.etr_factor == 1.0
assert m._dt_source == 'DAYMET_MEDIAN_V1'
assert m._elev_source == 'SRTM'
assert m._tcorr_source == 'IMAGE'
assert m._tmax_source == 'TOPOWX_MEDIAN_V0'
assert m._elr_flag == False
assert m._tdiff_threshold == 15
assert m._dt_min == 6
assert m._dt_max == 25
def test_Image_tcorr_image_month(expected=[0.9723, 1], tol=0.0001):
"""Test getting monthly Tcorr from composite when daily is missing"""
# Setting start date to well before beginning of daily Tcorr images
# 1980-07-04 should have the same cycle_day value as previous tests
input_image = ee.Image.constant(1).set({
'system:time_start': ee.Date('1980-07-04').millis()})
m = model.Image(input_image, tcorr_source='IMAGE',
tmax_source='TOPOWX_MEDIAN_V0')
tcorr_img, index_img = m._tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.point_image_value(index_img, SCENE_POINT)
assert abs(tcorr['tcorr'] - expected[0]) <= tol
assert index['index'] == expected[1]
def test_Image_init_default_parameters():
m = ssebop.Image(default_image())
assert m.et_reference_source == None
assert m.et_reference_band == None
assert m.et_reference_factor == None
assert m.et_reference_resample == None
assert m._dt_source == 'DAYMET_MEDIAN_V0'
assert m._elev_source == 'SRTM'
assert m._tcorr_source == 'IMAGE'
assert m._tmax_source == 'DAYMET_MEDIAN_V2'
assert m._elr_flag == False
assert m._dt_min == 6
assert m._dt_max == 25
def test_Image_tcorr_image_default(expected=[0.978, 3], tol=0.0001):
"""Test getting default Tcorr from composite"""
input_image = ee.Image.constant(1).set(
{'system:time_start': ee.Date('1980-07-04').millis()})
m = ssebop.Image(input_image,
tcorr_source='IMAGE',
tmax_source='TOPOWX_MEDIAN_V0')
m._month = ee.Number(9999)
m._cycle_day = ee.Number(9999)
tcorr_img, index_img = m.tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.point_image_value(index_img, SCENE_POINT)
assert abs(tcorr['tcorr'] - expected[0]) <= tol
assert index['index'] == expected[1]
def test_Image_tcorr_image_source(tcorr_source, tmax_source, scene_id,
expected, tol=0.0001):
"""Test getting Tcorr value and index for a single date at a real point"""
scene_date = datetime.datetime.strptime(scene_id.split('_')[-1], '%Y%m%d') \
.strftime('%Y-%m-%d')
input_image = ee.Image.constant(1).set({
'system:time_start': ee.Date(scene_date).millis()})
tcorr_img, index_img = model.Image(
input_image, tcorr_source=tcorr_source, tmax_source=tmax_source)._tcorr
# Tcorr images are constant images and need to be queried at a point
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.point_image_value(index_img, SCENE_POINT)
assert abs(tcorr['tcorr'] - expected[0]) <= tol
assert index['index'] == expected[1]
def test_Image_tcorr_image_daily_last_date_ingested():
"""Test if last exported daily Tcorr image is used
Two extra daily images with system:time_starts of "1979-01-01" but different
"date_ingested" properties were added to the collection for this test.
The "first" and "second" images have values of 1 and 2 respectively.
"""
input_image = ee.Image.constant(1).set(
{'system:time_start': ee.Date('1979-01-01').millis()})
m = ssebop.Image(input_image,
tcorr_source='IMAGE_DAILY',
tmax_source='TOPOWX_MEDIAN_V0')
tcorr_img, index_img = m.tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
assert tcorr['tcorr'] == 2
def test_Image_tcorr_scene_daily():
"""Tcorr should be masked for date outside range with SCENE_DAILY"""
input_image = ee.Image.constant(1).set({
'system:index':
'LC08_042035_20150713',
'system:time_start':
ee.Date('1980-07-04').millis()
})
m = ssebop.Image(input_image,
tcorr_source='SCENE_DAILY',
tmax_source='DAYMET_MEDIAN_V2')
tcorr_img = m.tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.getinfo(tcorr_img.get('tcorr_index'))
assert tcorr['tcorr'] is None
assert index == 9
def test_Image_tcorr_scene_month(expected=[0.97006134520787, 1], tol=0.000001):
"""Test getting monthly Tcorr from composite when daily is missing"""
# Setting start date to well before beginning of daily Tcorr images
input_image = ee.Image.constant(1).set({
'system:index':
'LC08_042035_20150713',
'system:time_start':
ee.Date('1980-07-13').millis()
})
m = ssebop.Image(input_image,
tcorr_source='SCENE',
tmax_source='DAYMET_MEDIAN_V2')
tcorr_img = m.tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.getinfo(tcorr_img.get('tcorr_index'))
assert abs(tcorr['tcorr'] - expected[0]) <= tol
assert index == expected[1]
def test_Image_tcorr_scene_annual(expected=[0.9762536456651, 2], tol=0.000001):
"""Test getting annual Tcorr from composite when monthly/daily are missing"""
input_image = ee.Image.constant(1).set({
'system:index':
'LC08_042035_20150713',
'system:time_start':
ee.Date('1980-07-13').millis()
})
m = ssebop.Image(input_image,
tcorr_source='SCENE',
tmax_source='DAYMET_MEDIAN_V2')
m._month = ee.Number(9999)
tcorr_img = m.tcorr
tcorr = utils.point_image_value(tcorr_img, SCENE_POINT)
index = utils.getinfo(tcorr_img.get('tcorr_index'))
assert abs(tcorr['tcorr'] - expected[0]) <= tol
assert index == expected[1]
def test_Image_tcorr_image_nodata(lst, ndvi, tmax, expected):
output = utils.constant_image_value(
ssebop.Image(default_image(lst=lst, ndvi=ndvi),
tmax_source=tmax).tcorr_image)
assert output['tcorr'] is None and expected is None
