def test_addConstantBands(self):
newimg = tools.addConstantBands(0, "a", "b", "c")(self.l8SR)
vals = tools.get_value(newimg, self.p_l8SR_no_cloud, 30)
self.assertEqual(vals["B1"], 517)
self.assertEqual(vals["a"], 0)
self.assertEqual(vals["b"], 0)
self.assertEqual(vals["c"], 0)
newimg2 = tools.addConstantBands(a=0, b=1, c=2)(self.l8SR)
vals2 = tools.get_value(newimg2, self.p_l8SR_no_cloud, 30)
self.assertEqual(vals2["B1"], 517)
self.assertEqual(vals2["a"], 0)
self.assertEqual(vals2["b"], 1)
self.assertEqual(vals2["c"], 2)
newimg3 = tools.addConstantBands(0, "a", "b", "c", d=1, e=2)(self.l8SR)
vals3 = tools.get_value(newimg3, self.p_l8SR_no_cloud, 30)
self.assertEqual(vals3["B1"], 517)
self.assertEqual(vals3["a"], 0)
self.assertEqual(vals3["b"], 0)
self.assertEqual(vals3["c"], 0)
self.assertEqual(vals3["d"], 1)
self.assertEqual(vals3["e"], 2)
def test_expressions(self):
from geetools import expressions
generator = expressions.ExpGen()
exp_max = generator.max("b('B1')", "b('B2')")
exp_min = generator.min("b('B1')", "b('B2')")
img_max = self.l8SR.expression(exp_max).select([0], ["max"])
img_min = self.l8SR.expression(exp_min).select([0], ["min"])
vals_max = tools.get_value(img_max, self.p_l8SR_no_cloud, 30, 'client')
vals_min = tools.get_value(img_min, self.p_l8SR_no_cloud, 30, 'client')
self.assertEqual(vals_max["max"], 580)
self.assertEqual(vals_min["min"], 517)
def test_bap2016_0(self):
pmulti = scores.MultiYear(2016, self.temporada)
objbap = bap.Bap(year=2016,
colgroup=self.coleccion,
season=self.temporada,
scores=(self.pindice, self.pmascpor, self.psat,
self.pout, self.pop, self.pdoy, pmulti),
masks=(self.nubes,),
filters=(self.filtro,),
)
# objbap.debug = True
sitio = self.sitio
unpix = objbap.bestpixel(sitio, indices=("ndvi",))
img = unpix.image
col = unpix.col
self.assertIsInstance(img, ee.Image)
self.assertIsInstance(col, ee.ImageCollection)
idict = img.getInfo()
cdict = col.getInfo()
self.assertIsInstance(idict, dict)
self.assertIsInstance(cdict, dict)
value = tools.get_value(img, self.centroid, 30, 'client')
print(value)
self.assertIsInstance(value, dict)
# self.assertEqual(value["BLUE"], 0.008500000461935997)
# self.assertEqual(value["col_id"], 12.0)
# self.assertEqual(value["ndvi"], 0.872759222984314)
def test_bap2016_0(self):
pmulti = scores.MultiYear(2016, self.temporada)
objbap = bap.Bap(year=2016,
# colgroup=self.coleccion,
season=self.temporada,
scores=(self.pindice, self.pmascpor, self.psat,
self.pout, self.pop, self.pdoy, pmulti),
masks=(self.nubes,),
filters=(self.filtro,),
)
# objbap.debug = True
sitio = self.sitio
unpix = objbap.bestpixel(sitio, indices=("ndvi",))
img = unpix.image
col = unpix.col
self.assertIsInstance(img, ee.Image)
self.assertIsInstance(col, ee.ImageCollection)
idict = img.getInfo()
cdict = col.getInfo()
self.assertIsInstance(idict, dict)
self.assertIsInstance(cdict, dict)
value = tools.get_value(img, self.centroid, 30, 'client')
print(value)
self.assertIsInstance(value, dict)
visual = img.visualize(bands=['NIR','SWIR','RED'], min=0, max=0.5)
url = visual.getThumbUrl({'region':tools.getRegion(img)})
print('Result:', url)
def test_parametrize(self):
newimg = tools.parametrize((0, 10000), (0, 1), ["B1", "B2"])(self.l8SR)
vals = tools.get_value(newimg, self.p_l8SR_no_cloud, 30)
self.assertEqual(vals["B1"], 517.0 / 10000)
self.assertEqual(vals["B2"], 580.0 / 10000)
self.assertEqual(vals["B3"], 824)
def test_sumBands(self):
newimg = tools.sumBands("added_bands", ("B1", "B2", "B3"))(self.l8SR)
vals = tools.get_value(newimg, self.p_l8SR_no_cloud, 30)
suma = int(vals["B1"]) + int(vals["B2"]) + int(vals["B3"])
self.assertEqual(vals["added_bands"], suma)
def test_mask2(self):
masked_img = self.l8SR.updateMask(self.l8SR.select(["cfmask"]).eq(0))
mask2zero = tools.mask2zero(masked_img)
val_no_change = tools.get_value(mask2zero, self.p_l8SR_no_cloud,
30)["B1"]
val_change = tools.get_value(mask2zero, self.p_l8SR_cloud, 30)["B1"]
self.assertEqual(val_no_change, 517)
self.assertEqual(val_change, 0)
mask2num = tools.mask2number(10)(masked_img)
val_no_change_num = tools.get_value(mask2num, self.p_l8SR_no_cloud,
30)["B1"]
val_change_num = tools.get_value(mask2num, self.p_l8SR_cloud, 30)["B1"]
self.assertEqual(val_no_change_num, 517)
self.assertEqual(val_change_num, 10)
def test_minmax(self):
min = 150
max = 2000
thres = scores.Threshold(self.band, (min, max))
newimg = thres.map()(self.img)
val1 = tools.get_value(img=newimg,
point=self.p1,
scale=30,
side='client')['score-thres']
val2 = tools.get_value(img=newimg,
point=self.p2,
scale=30,
side='client')['score-thres']
val3 = tools.get_value(img=newimg,
point=self.p3,
scale=30,
side='client')['score-thres']
self.assertEqual(val1, 1)
self.assertEqual(val2, 0)
self.assertEqual(val3, 0)
masked = newimg.select(['B5', 'B7',
'B4']).updateMask(newimg.select('score-thres'))
thumb = masked.getThumbUrl({
'min':
0,
'max':
5000,
'region':
self.region.getInfo()['coordinates']
})
original = newimg.select(['B5', 'B7', 'B4']).getThumbUrl({
'min':
0,
'max':
5000,
'region':
self.region.getInfo()['coordinates']
})
print('Original: {}'.format(original))
print('See image at: {}'.format(thumb))
def test_default(self):
# SCORE
score = scores.MaskPercent(self.band)
newimg = score.map(self.col, self.pol)(self.image)
maskpercent_prop = newimg.get(score.name).getInfo()
maskpercent_pix = tools.get_value(newimg, self.p,
side='client')[score.name]
self.assertEqual(maskpercent_prop, 0, 5625)
self.assertEqual(maskpercent_pix, 0, 5625)
def test_rename_bands(self):
i = tools.rename_bands({"B1": "BLUE", "B2": "GREEN"})(self.l8SR)
vals = tools.get_value(i, self.p_l8SR_no_cloud, 30)
bands = i.bandNames().getInfo()
self.assertEqual(bands, [
"BLUE", "GREEN", "B3", "B4", "B5", "B6", "B7", "cfmask",
"cfmask_conf"
])
self.assertEqual(vals["BLUE"], 517)
def test_threshold_satcol(self):
col = Collection.Landsat8USGS()
p = ee.Geometry.Point([-70.16521453857422, -43.02372558882024])
colEE = col.colEE.filterBounds(p).map(col.rename())
score = Threshold()
colEE_score = colEE.map(score.map(col))
p1 = ee.Geometry.Point([-69.38690186070744, -43.06088427532436])
p0 = ee.Geometry.Point([-69.21112061070744, -43.41704165930161])
image = ee.Image(colEE_score.first())
p1_val = tools.get_value(image, p1, 30, 'client')['score-thres']
p0_val = tools.get_value(image, p0, 30, 'client')['score-thres']
self.assertEqual(float(p1_val), 1)
self.assertEqual(float(p0_val), 0)
# output(image, 'from_satcol', {'bands':['score-thres'], 'min':0, 'max':1})
export(image.select([score.name]), 'test_scores', 'threshold_satcol',
30)
def test_break2band(self):
b2b = self.principe.break2band()
self.assertEqual(type(b2b), ee.Image)
if exist_geetools:
values = tools.get_value(b2b, self.center, scale=30, side='client')
pp.pprint(values)
self.output(b2b, 'test_break2band', {
'bands': ['change_0', 'change_1', 'change_2'],
'min': 0,
'max': 1
})
def test_with_zeros(self):
col = Collection.Sentinel2()
score = MaskPercent()
image = cloud_mask.sentinel2()(cloud_S2)
bounds = image.geometry().buffer(-50000)
computed = score.map(col, bounds)(image)
maskprop = computed.get(score.name).getInfo()
maskband = tools.get_value(computed,
image.geometry().centroid(), 10,
'client')[score.name]
print(maskband, maskprop)
self.assertEqual(maskband, maskprop)
scores = (doy, sat, op, out, ind, mascpor, dist)
# BAP OBJECT
bap = bap.Bap(year=2010, range=(0, 0),
season=a_season,
# colgroup=col_group, # if colgroup is None, it'll use season.SeasonPriority
masks=masks,
scores=scores,
filters=filters)
# SITE
site = ee.Geometry.Polygon([[-71,-42],
[-71,-43],
[-72,-43],
[-72,-42]])
# COMPOSITE
composite = bap.bestpixel(site=site,
indices=("ndvi",))
# The result (composite) is a namedtuple, so
image = composite.image
# image is a ee.Image object, so you can do anything
# from here..
one_value = tools.get_value(image,
site.centroid(),
30, 'client')
pp.pprint(one_value)
def test_cloud_mask(self):
from geetools import cloud_mask
# LANDSAT 4 TOA
masked_l4toa = cloud_mask.fmask("fmask")(self.l4toa)
p_l4toa = ee.Geometry.Point([-72.2736, -44.6062])
vals_l4toa = tools.get_value(masked_l4toa, p_l4toa, 30)
self.assertEqual(vals_l4toa["B1"], None)
# LANDSAT 5 USGS
p_l5usgs = ee.Geometry.Point([-65.4991, -24.534])
masked_l5usgs = cloud_mask.fmask("cfmask")(self.l5SR)
vals_l5usgs = tools.get_value(masked_l5usgs, p_l5usgs, 30)
self.assertEqual(vals_l5usgs["B1"], None)
# LANDSAT 5 LEDAPS
p_l5led = ee.Geometry.Point([-70.3455, -43.8306])
masked_l5led = cloud_mask.ledaps(self.l5led)
vals_l5led = tools.get_value(masked_l5led, p_l5led, 30)
self.assertEqual(vals_l5led["B1"], None)
# LANDSAT 5 TOA
masked_l5toa = cloud_mask.fmask("fmask")(self.l5toa)
p_l5toa = ee.Geometry.Point([-70.9003, -39.7421])
vals_l5toa = tools.get_value(masked_l5toa, p_l5toa, 30)
self.assertEqual(vals_l5toa["B1"], None)
# LANDSAT 7 USGS
p_l7usgs = ee.Geometry.Point([-64.8533, -26.1052])
masked_l7usgs = cloud_mask.fmask("cfmask")(self.l7SR)
vals_l7usgs = tools.get_value(masked_l7usgs, p_l7usgs, 30)
self.assertEqual(vals_l7usgs["B1"], None)
# LANDSAT 7 LEDAPS
p_l7led = ee.Geometry.Point([-64.9141, -25.2264])
masked_l7led = cloud_mask.ledaps(self.l7led)
vals_l7led = tools.get_value(masked_l7led, p_l7led, 30)
self.assertEqual(vals_l7led["B1"], None)
# LANDSAT 7 TOA
masked_l7toa = cloud_mask.fmask("fmask")(self.l7toa)
p_l7toa = ee.Geometry.Point([-64.8495, -25.2354])
vals_l7toa = tools.get_value(masked_l7toa, p_l7toa, 30)
self.assertEqual(vals_l7toa["B1"], None)
# LANDSAT 8 USGS
p_l8usgs = ee.Geometry.Point([-65.5568, -24.3327])
masked_l8usgs = cloud_mask.fmask("cfmask")(self.l8SR)
vals_l8usgs = tools.get_value(masked_l8usgs, p_l8usgs, 30)
self.assertEqual(vals_l8usgs["B1"], None)
# LANDSAT 8 TOA
masked_l8toa = cloud_mask.fmask("fmask")(self.l8toa)
p_l8toa = ee.Geometry.Point([-71.7833, -43.6634])
vals_l8toa = tools.get_value(masked_l8toa, p_l8toa, 30)
self.assertEqual(vals_l8toa["B1"], None)
# LANDSAT SENTINEL 2
masked_s2 = cloud_mask.sentinel2(self.sentinel2)
p_s2 = ee.Geometry.Point([-72.2104, -42.7592])
vals_s2 = tools.get_value(masked_s2, p_s2, 10)
self.assertEqual(vals_s2["B1"], None)
# LANDSAT MODIS AQ
masked_ma = cloud_mask.modis(self.modis_aqua)
p_ma = ee.Geometry.Point([-69.071, -43.755])
vals_ma = tools.get_value(masked_ma, p_ma, 500)
self.assertEqual(vals_ma["sur_refl_b01"], None)
# LANDSAT MODIS TE
masked_te = cloud_mask.modis(self.modis_terra)
p_te = ee.Geometry.Point([-71.993, -43.692])
vals_te = tools.get_value(masked_te, p_te, 500)
self.assertEqual(vals_te["sur_refl_b01"], None)
def test_replace(self):
testband = ee.Image.constant(10).select([0], ["anyname"])
newimg = tools.replace(self.l8SR, "B1", testband)
vals = tools.get_value(newimg, self.p_l8SR_no_cloud, 30)
self.assertEqual(vals["B1"], 10)
