From 06ff6c2004340ae570e10cb83f114bd3469ceff4 Mon Sep 17 00:00:00 2001
From: Paolo Veglio <paolo.veglio@ssec.wisc.edu>
Date: Wed, 15 Feb 2023 14:52:58 +0000
Subject: [PATCH] all tests implemented. need a second pass to make sure
everything is good
---
mvcm/spectral_tests.py | 59 ++++++++++++++++--------------------
tests/test_spectral_tests.py | 51 +++++++++++++++++++++++++++++++
2 files changed, 77 insertions(+), 33 deletions(-)
diff --git a/mvcm/spectral_tests.py b/mvcm/spectral_tests.py
index fcf8db2..dec93a9 100644
--- a/mvcm/spectral_tests.py
+++ b/mvcm/spectral_tests.py
@@ -462,7 +462,6 @@ class CloudTests(object):
return cmin, np.abs(1-kwargs['test_bit'])*kwargs['qa_bit']
# this test needs some TLC
- # NEED TO FIGURE OUT WHY CMIN BECOMES A TUPLE AT SOME POINT
@run_if_test_exists_for_scene('Visible_Reflectance_Test')
def visible_reflectance_test(self,
band: str,
@@ -470,6 +469,8 @@ class CloudTests(object):
**kwargs) -> np.ndarray:
threshold = kwargs['thresholds']
+ logger.warning('The pytest now seems to be working now but it use to fail for this function' +
+ 'If it fails again go check the test before turning this function inside out')
if (threshold['perform'] is True and self.pixels_in_scene is True):
print(f'Testing "{self.scene_name}"\n')
@@ -478,81 +479,73 @@ class CloudTests(object):
kwargs['confidence'][self.scene_idx] = conf.conf_test_new(rad, thr)
cmin = np.fmin(cmin, kwargs['confidence'])
- print(cmin.shape)
return cmin, kwargs['test_bit']
- @run_if_test_exists_for_scene
+ @run_if_test_exists_for_scene('GEMI_Test')
def gemi_test(self,
band: str,
cmin: np.ndarray,
- test_name: str = 'GEMI_Test') -> np.ndarray:
+ **kwargs) -> np.ndarray:
- confidence = np.ones(self.data.M01.shape)
- test_bit = np.zeros(self.data[band].shape)
- threshold = self.thresholds[self.scene_name][test_name]
+ threshold = kwargs['thresholds']
if (threshold['perform'] is True and self.pixels_in_scene is True):
thr = preproc.gemi_thresholds(self.data, threshold, self.scene_name,
self.scene_idx)
rad = self.data[band].values[self.scene_idx]
- confidence[self.scene_idx] = conf.conf_test_new(rad, thr)
+ kwargs['confidence'][self.scene_idx] = conf.conf_test_new(rad, thr)
- cmin = np.fmin(cmin, confidence)
+ cmin = np.fmin(cmin, kwargs['confidence'])
- return cmin, test_bit
+ return cmin, kwargs['test_bit']
- @run_if_test_exists_for_scene
+ @run_if_test_exists_for_scene('1.38um_High_Cloud_Test')
def test_1_38um_high_clouds(self,
band: str,
cmin: np.ndarray,
- test_name: str = '1.38um_High_Cloud_Test') -> np.ndarray:
+ **kwargs) -> np.ndarray:
- confidence = np.ones(self.data.M01.shape)
- qa_bit = np.zeros(self.data[band].shape)
- test_bit = np.zeros(self.data[band].shape)
- threshold = self.thresholds[self.scene_name][test_name]
+ threshold = kwargs['thresholds']
if (threshold['perform'] is True and self.pixels_in_scene is True):
- qa_bit[self.scene_idx] = 1
+ kwargs['qa_bit'][self.scene_idx] = 1
if self.scene_name in ['Ocean_Day', 'Polar_Day_Ocean']:
thr = preproc.thresholds_1_38um_test(self.data, self.thresholds, self.scene_name,
self.scene_idx)
else:
- return cmin, test_bit
- thr = threshold['thr']
+ # return cmin, kwargs['test_bit']
+ thr = np.full((len(self.scene_idx[0]), 4), threshold['thr'][:4]).T
print(f'Testing "{self.scene_name}"\n')
rad = self.data[band].values[self.scene_idx]
idx = np.nonzero((rad <= thr[1, :]) &
(self.data[self.scene_name].values[self.scene_idx] == 1))
- tmp_bit = test_bit[self.scene_idx]
+ tmp_bit = kwargs['test_bit'][self.scene_idx]
tmp_bit[idx] = 1
- test_bit[self.scene_idx] = tmp_bit
- confidence[self.scene_idx] = conf.conf_test_new(rad, thr)
+ kwargs['test_bit'][self.scene_idx] = tmp_bit
+ kwargs['confidence'][self.scene_idx] = conf.conf_test_new(rad, thr)
- cmin = np.fmin(cmin, confidence)
+ cmin = np.fmin(cmin, kwargs['confidence'])
- return cmin, np.abs(1-test_bit)*qa_bit
+ return cmin, np.abs(1-kwargs['test_bit'])*kwargs['qa_bit']
- @run_if_test_exists_for_scene
+ @run_if_test_exists_for_scene('4-12um_BTD_Thin_Cirrus_Test')
def thin_cirrus_4_12um_BTD_test(self,
band: str,
cmin: np.ndarray,
- test_name: str = '4-12um_BTD_Thin_Cirrus_Test') -> np.ndarray:
+ **kwargs) -> np.ndarray:
- confidence = np.ones(self.data.M01.shape)
- test_bit = np.zeros(self.data[band].shape)
- threshold = self.thresholds[self.scene_name][test_name]
+ threshold = kwargs['thresholds']
if (threshold['perform'] is True and self.pixels_in_scene is True):
thr = preproc.polar_night_thresholds(self.data, self.thresholds, self.scene_name,
- test_name, self.scene_idx)
+ '4-12um_BTD_Thin_Cirrus_Test', self.scene_idx)
rad = self.data[band].values[self.scene_idx]
- confidence[self.scene_idx] = conf.conf_test_new(rad, thr)
+ kwargs['confidence'][self.scene_idx] = conf.conf_test_new(rad, thr)
- cmin = np.fmin(cmin, confidence)
+ cmin = np.fmin(cmin, kwargs['confidence'])
- return cmin, test_bit
+ return cmin, kwargs['test_bit']
def single_threshold_test(self, test_name, band, cmin):
diff --git a/tests/test_spectral_tests.py b/tests/test_spectral_tests.py
index 44cfeff..b2c18f4 100644
--- a/tests/test_spectral_tests.py
+++ b/tests/test_spectral_tests.py
@@ -189,3 +189,54 @@ def test_16_21um_reflectance_test(data, thresholds, ref_confidence):
assert np.allclose(cmin, ref_confidence.refl_16_21um_confidence.values)
+
+def test_visible_reflectance_test(data, thresholds, ref_confidence):
+ cmin = np.ones(data.latitude.shape)
+ for scene_name in ['Land_Day', 'Land_Day_Coast', 'Land_Day_Desert',
+ 'Land_Day_Desert_Coast', 'Polar_Day_Land', 'Polar_Day_Coast',
+ 'Polar_Day_Desert', 'Polar_Day_Desert_Coast']:
+ SceneType = tst.CloudTests(data=data,
+ scene_name=scene_name,
+ thresholds=thresholds)
+
+ cmin, bit = SceneType.visible_reflectance_test('M128', cmin)
+
+ assert np.allclose(cmin, ref_confidence.vis_reflectance_confidence.values)
+
+
+def test_GEMI_test(data, thresholds, ref_confidence):
+ cmin = np.ones(data.latitude.shape)
+ for scene_name in ['Land_Day_Desert', 'Polar_Day_Desert']:
+ SceneType = tst.CloudTests(data=data,
+ scene_name=scene_name,
+ thresholds=thresholds)
+
+ cmin, bit = SceneType.gemi_test('GEMI', cmin)
+
+ assert np.allclose(cmin, ref_confidence.gemi_confidence.values)
+
+
+def test_1_38um_high_clouds_test(data, thresholds, ref_confidence):
+ cmin = np.ones(data.latitude.shape)
+ for scene_name in ['Land_Day', 'Land_Day_Coast', 'Land_Day_Desert', 'Land_Day_Desert_Coast',
+ 'Polar_Day_Land', 'Polar_Day_Coast', 'Polar_Day_Desert',
+ 'Polar_Day_Desert_Coast', 'Day_Snow', 'Ocean_Day', 'Polar_Day_Ocean']:
+ SceneType = tst.CloudTests(data=data,
+ scene_name=scene_name,
+ thresholds=thresholds)
+
+ cmin, bit = SceneType.test_1_38um_high_clouds('M09', cmin)
+
+ assert np.allclose(cmin, ref_confidence.hi_clouds_confidence.values)
+
+
+def test_4_12um_thin_cirrus_btd(data, thresholds, ref_confidence):
+ cmin = np.ones(data.latitude.shape)
+ for scene_name in ['Land_Night', 'Polar_Night_Land', 'Polar_Night_Snow', 'Night_Snow']:
+ SceneType = tst.CloudTests(data=data,
+ scene_name=scene_name,
+ thresholds=thresholds)
+
+ cmin, bit = SceneType.thin_cirrus_4_12um_BTD_test('M13-M16', cmin)
+
+ assert np.allclose(cmin, ref_confidence.thin_cirrus_confidence.values)
--
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