def test_ndvi():
collection = col.map(lambda img: img.addBands(indices.ndvi(img, 'B8','B4')))
image = ee.Image(collection.first())
values = getValue(image, p, 10, side='client')
NIR = float(values['B8'])
RED = float(values['B4'])
index = (NIR-RED)/(NIR+RED)
index_from_i = getValue(image, p, 10, 'client')['ndvi']
assert index == index_from_i
def test_nbr2():
collection = col.map(lambda img: img.addBands(indices.nbr2(img, 'B11', 'B12')))
image = ee.Image(collection.first())
values = getValue(image, p, 10, side='client')
SWIR1 = float(values['B11'])
SWIR2 = float(values['B12'])
index = (SWIR1-SWIR2)/(SWIR1+SWIR2)
index_from_i = getValue(image, p, 10, 'client')['nbr2']
assert index == index_from_i
def test_evi():
collection = col.map(lambda img: img.addBands(indices.evi(img, 'B8', 'B4', 'B2')))
image = ee.Image(collection.first())
values = getValue(image, p, 10, side='client')
NIR = float(values['B8'])
RED = float(values['B4'])
BLUE = float(values['B2'])
index = (2.5)*((NIR-RED)/(NIR+(6*RED)-((7.5)*BLUE)+1))
index_from_i = getValue(image, p, 10, 'client')['evi']
assert index == index_from_i
def test_expressions():
from geetools import expressions
generator = expressions.Expression()
exp_max = generator.max("b('B1')", "b('B2')")
exp_min = generator.min("b('B1')", "b('B2')")
img_max = l8SR.expression(exp_max).select([0], ["max"])
img_min = l8SR.expression(exp_min).select([0], ["min"])
vals_max = getValue(img_max, p_l8SR_no_cloud, 30, 'client')
vals_min = getValue(img_min, p_l8SR_no_cloud, 30, 'client')
assert vals_max["max"] == 580
assert vals_min["min"] == 517
def test_snow():
masked = cloud_mask.applyHollstein(image, ['snow'])
vals = getValue(masked, p_snow, 30)
assert vals.get("B1").getInfo() == None
def test_cirrus():
masked = cloud_mask.applyHollstein(image, ['cirrus'])
vals = getValue(masked, p_cirrus, 30)
assert vals.get("B1").getInfo() == None
def test_cirrus():
masked = cloud_mask.sentinel2(['cirrus'])(image)
vals = getValue(masked, p_cirrus, 30)
assert vals.get("B1").getInfo() == None
def test_snow():
masked = cloud_mask.landsat457SRPixelQA(['snow'])(image)
vals = getValue(masked, p_snow, 30)
assert vals.get("B1").getInfo() == None
def test_shadows():
masked = cloud_mask.landsat457ToaBQA(['shadow'])(image)
vals = getValue(masked, p_shadow, 30)
assert vals.get("B1").getInfo() == None
def test_clouds():
masked = cloud_mask.landsat457ToaBQA(['cloud'])(image)
vals = getValue(masked, p_cloud, 30)
assert vals.get("B1").getInfo() == None
