本文整理汇总了Python中molusce.algorithms.dataprovider.Raster类的典型用法代码示例。如果您正苦于以下问题:Python Raster类的具体用法?Python Raster怎么用?Python Raster使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了Raster类的20个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: TestMCE
class TestMCE(unittest.TestCase):
def setUp(self):
self.factor = Raster('../../examples/multifact.tif')
#~ [1,1,3]
#~ [3,2,1]
#~ [0,3,1]
self.state = Raster('../../examples/sites.tif')
self.state.resetMask(maskVals= [0])
#~ [1,2,1],
#~ [1,2,1],
#~ [0,1,2]
self.areaAnalyst = AreaAnalyst(self.state, second=None)
def test_MCE(self):
data = [
[1.0, 4.0, 6.0, 7.0],
[1.0/4, 1.0, 3.0, 4.0],
[1.0/6, 1.0/3, 1.0, 2.0],
[1.0/7, 1.0/4, 1.0/2, 1]
]
# Multiband
factor = Raster('../../examples/two_band.tif')
mce = MCE([self.factor, factor, self.factor], data, 1, 2, self.areaAnalyst)
w = mce.getWeights()
answer = [0.61682294, 0.22382863, 0.09723423, 0.06211421]
assert_almost_equal(w, answer)
# One-band
mce = MCE([self.factor, self.factor, self.factor, self.factor], data, 1, 2, self.areaAnalyst)
w = mce.getWeights()
answer = [0.61682294, 0.22382863, 0.09723423, 0.06211421]
assert_almost_equal(w, answer)
mask = [
[False, False, False],
[False, False, False],
[False, False, True]
]
p = mce.getPrediction(self.state).getBand(1)
self.assertEquals(p.dtype, np.uint8)
answer = [ # The locations where the big numbers are stored must be masked (see mask and self.state)
[1, 3, 1],
[1, 3, 1],
[100, 1, 100]
]
answer = np.ma.array(data = answer, mask = mask)
assert_almost_equal(p, answer)
c = mce.getConfidence().getBand(1)
self.assertEquals(c.dtype, np.uint8)
answer = [ # The locations where the big numbers are stored must be masked (see mask and self.state)
[sum((w*100).astype(int))/3, 0, sum((w*100).astype(int))],
[sum((w*100).astype(int)), 0, sum((w*100).astype(int))/3],
[10000, sum((w*100).astype(int)), 10000]
]
answer = np.ma.array(data = answer, mask = mask)
assert_almost_equal(c, answer)
开发者ID:nextgis,项目名称:molusce,代码行数:60,代码来源:test_mce.py
示例2: sim
def sim(self):
"""
Make 1 iteracion of simulation.
"""
# TODO: eleminate AreaAnalyst.getChangeMap() from the process
transition = self.crosstable.getCrosstable()
prediction = self.getPrediction()
state = self.getState()
new_state = state.getBand(1).copy() # New states (the result of simulation) will be stored there.
analyst = AreaAnalyst(state, prediction)
classes = analyst.classes
changes = analyst.getChangeMap().getBand(1)
# Make transition between classes according to
# number of moved pixel in crosstable
self.rangeChanged.emit(self.tr("Simulation process %p%"), len(classes) ** 2 - len(classes))
for initClass in classes:
for finalClass in classes:
if initClass == finalClass:
continue
# TODO: Calculate number of pixels to be moved via TransitoionMatrix and state raster
n = transition.getTransition(
initClass, finalClass
) # Number of pixels to be moved (constant count now).
# Find n appropriate places for transition initClass -> finalClass
class_code = analyst.encode(initClass, finalClass)
places = changes == class_code # Array of places where transitions initClass -> finalClass are occured
placesCount = np.sum(places)
if placesCount < n:
self.logMessage.emit(
self.tr("There are more transitions in the transition matrix, then the model have found")
)
n = placesCount
confidence = self.getConfidence().getBand(1)
confidence = (
confidence * places
) # The higher is number in cell, the higer is probability of transition in the cell
indices = []
for i in range(n):
index = np.unravel_index(
confidence.argmax(), confidence.shape
) # Select the cell with biggest probability
indices.append(index)
confidence[index] = -1 # Mark the cell to prevent second selection
# Now "indices" contains indices of the appropriate places,
# make transition initClass -> finalClass
for index in indices:
new_state[index] = finalClass
self.updateProgress.emit()
result = Raster()
result.create([new_state], state.getGeodata())
self.state = result
self.updatePrediction(result)
self.processFinished.emit()
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:60,代码来源:sim.py
示例3: setUp
def setUp(self):
self.r1 = Raster('examples/multifact.tif')
self.r2 = Raster('examples/sites.tif')
self.r3 = Raster('examples/two_band.tif')
# r1
data1 = np.array(
[
[1,1,3],
[3,2,1],
[0,3,1]
])
# r2
data2 = np.array(
[
[1,2,1],
[1,2,1],
[0,1,2]
])
mask = [
[False, False, False],
[False, False, False],
[False, False, False]
]
self.data1 = ma.array(data=data1, mask=mask)
self.data2 = ma.array(data=data2, mask=mask)
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:26,代码来源:test_dataprovider.py
示例4: TestSimulator
class TestSimulator(unittest.TestCase):
def setUp(self):
# Raster1:
# ~ [1, 1, 3,],
# ~ [3, 2, 1,],
# ~ [0, 3, 1,]
self.raster1 = Raster("../../examples/multifact.tif")
self.raster1.resetMask([0])
self.X = np.array([[1, 2, 3], [3, 2, 1], [0, 1, 1]])
self.X = np.ma.array(self.X, mask=(self.X == 0))
self.raster2 = Raster()
self.raster2.create([self.X], self.raster1.getGeodata())
self.aa = AreaAnalyst(self.raster1, self.raster2)
self.crosstab = CrossTableManager(self.raster1, self.raster2)
# Simple model
self.model = Model(state=self.raster1)
def test_compute_table(self):
# print self.crosstab.getCrosstable().getCrosstable()
# CrossTab:
# [[ 3. 1. 0.]
# [ 0. 1. 0.]
# [ 1. 0. 2.]]
prediction = self.model.getPrediction(self.raster1)
# print prediction.getBand(1)
# prediction = [[1.0 1.0 6.0]
# [6.0 5.0 1.0]
# [-- 6.0 1.0]]
# confidence = self.model.getConfidence()
# print confidence.getBand(1)
# confidence = [[1.0 0.5 0.33]
# [0.5 0.33 0.25]
# [-- 0.25 0.2]]
result = np.array([[2.0, 1.0, 3.0], [1.0, 2.0, 1.0], [0, 3.0, 1.0]])
result = np.ma.array(result, mask=(result == 0))
simulator = Simulator(
state=self.raster1, factors=None, model=self.model, crosstable=self.crosstab
) # The model does't use factors
simulator.setIterationCount(1)
simulator.simN()
state = simulator.getState().getBand(1)
assert_array_equal(result, state)
result = np.array([[2.0, 1.0, 1.0], [2.0, 2.0, 1.0], [0, 3.0, 1.0]])
result = np.ma.array(result, mask=(result == 0))
simulator = Simulator(self.raster1, None, self.model, self.crosstab)
simulator.setIterationCount(2)
simulator.simN()
state = simulator.getState().getBand(1)
assert_array_equal(result, state)
开发者ID:nextgis,项目名称:molusce,代码行数:58,代码来源:test_sim.py
示例5: _predict
def _predict(self, state, calcTransitions=False):
"""
Predict the changes.
"""
try:
self.rangeChanged.emit(self.tr("Initialize model %p%"), 1)
rows, cols = self.geodata["ySize"], self.geodata["xSize"]
if not self.changeMap.geoDataMatch(state):
raise WoeManagerError("Geometries of the state and changeMap rasters are different!")
prediction = np.zeros((rows, cols), dtype=np.uint8)
confidence = np.zeros((rows, cols), dtype=np.uint8)
mask = np.zeros((rows, cols), dtype=np.byte)
stateBand = state.getBand(1)
self.updateProgress.emit()
self.rangeChanged.emit(self.tr("Prediction %p%"), rows)
for r in xrange(rows):
for c in xrange(cols):
oldMax, currMax = -1000, -1000 # Small numbers
indexMax = -1 # Index of Max weight
initCat = stateBand[r, c] # Init category (state before transition)
try:
codes = self.analyst.codes(initCat) # Possible final states
for code in codes:
try: # If not all possible transitions are presented in the changeMap
map = self.woe[code] # Get WoE map of transition 'code'
except KeyError:
continue
w = map[r, c] # The weight in the (r,c)-pixel
if w > currMax:
indexMax, oldMax, currMax = code, currMax, w
prediction[r, c] = indexMax
confidence[r, c] = int(100 * (sigmoid(currMax) - sigmoid(oldMax)))
except ValueError:
mask[r, c] = 1
self.updateProgress.emit()
predicted_band = np.ma.array(data=prediction, mask=mask, dtype=np.uint8)
self.prediction = Raster()
self.prediction.create([predicted_band], self.geodata)
confidence_band = np.ma.array(data=confidence, mask=mask, dtype=np.uint8)
self.confidence = Raster()
self.confidence.create([confidence_band], self.geodata)
except MemoryError:
self.errorReport.emit(self.tr("The system out of memory during WOE prediction"))
raise
except:
self.errorReport.emit(self.tr("An unknown error occurs during WoE prediction"))
raise
finally:
self.processFinished.emit()
开发者ID:nextgis,项目名称:molusce,代码行数:55,代码来源:manager.py
示例6: test_cat2vect
def test_cat2vect(self):
smp = Sampler(self.state, self.factors, self.output, ns=0)
assert_array_equal(smp.cat2vect(0), [1, 0])
assert_array_equal(smp.cat2vect(1), [0, 1])
assert_array_equal(smp.cat2vect(2), [0, 0])
inputRast = Raster('../../examples/sites.tif')
inputRast.resetMask([0])
smp = Sampler(inputRast, self.factors, self.output, ns=0)
assert_array_equal(smp.cat2vect(1), [1])
assert_array_equal(smp.cat2vect(2), [0])
开发者ID:nextgis,项目名称:molusce,代码行数:11,代码来源:test_sampler.py
示例7: train
def train(self):
"""
Train the model
"""
self.transitionPotentials = {}
try:
iterCount = len(self.codes) * len(self.factors)
self.rangeChanged.emit(self.tr("Training WoE... %p%"), iterCount)
changeMap = self.changeMap.getBand(1)
for code in self.codes:
sites = binaryzation(changeMap, [code])
# Reclass factors (continuous factor -> ordinal factor)
wMap = np.ma.zeros(changeMap.shape) # The map of summary weight of the all factors
self.weights[code] = {} # Dictionary for storing wheights of every raster's band
for k in xrange(len(self.factors)):
fact = self.factors[k]
self.weights[code][k] = {} # Weights of the factor
factorW = self.weights[code][k]
if self.bins: # Get bins of the factor
bin = self.bins[k]
if (bin != None) and fact.getBandsCount() != len(bin):
raise WoeManagerError("Count of bins list for multiband factor is't equal to band count!")
else:
bin = None
for i in range(1, fact.getBandsCount() + 1):
band = fact.getBand(i)
if bin and bin[i - 1]: #
band = reclass(band, bin[i - 1])
band, sites = masks_identity(band, sites, dtype=np.uint8) # Combine masks of the rasters
woeRes = woe(
band, sites, self.unit_cell
) # WoE for the 'code' (initState->finalState) transition and current 'factor'.
weights = woeRes["map"]
wMap = wMap + weights
factorW[i] = woeRes["weights"]
self.updateProgress.emit()
# Reclassification finished => set WoE coefficients
self.woe[code] = wMap # WoE for all factors and the transition code.
# Potentials are WoE map rescaled to 0--100 percents
band = (sigmoid(wMap) * 100).astype(np.uint8)
p = Raster()
p.create([band], self.geodata)
self.transitionPotentials[code] = p
gc.collect()
except MemoryError:
self.errorReport.emit("The system out of memory during WoE trainig")
raise
except:
self.errorReport.emit(self.tr("An unknown error occurs during WoE trainig"))
raise
finally:
self.processFinished.emit()
开发者ID:nextgis,项目名称:molusce,代码行数:54,代码来源:manager.py
示例8: test_save
def test_save(self):
try:
filename = 'temp.tiff'
self.r1.save(filename)
r2 = Raster(filename)
self.assertEqual(r2.get_dtype(), self.r1.get_dtype())
self.assertEqual(r2.getBandsCount(), self.r1.getBandsCount())
for i in range(r2.getBandsCount()):
assert_array_equal(r2.getBand(i+1), self.r1.getBand(i+1))
finally:
os.remove(filename)
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:11,代码来源:test_dataprovider.py
示例9: errorMap
def errorMap(self, answer):
'''
Create map of correct and incorrect prediction.
This function compares the known answer and the result of predicting procedure,
correct pixel is marked as 0.
'''
state = self.getState()
b = state.getBand(1)
a = answer.getBand(1)
diff = (a-b).astype(np.int16)
result = Raster()
result.create([diff], state.getGeodata())
return result
开发者ID:nextgis,项目名称:molusce,代码行数:13,代码来源:sim.py
示例10: setUp
def setUp(self):
self.factor = Raster('../../examples/multifact.tif')
#~ [1,1,3]
#~ [3,2,1]
#~ [0,3,1]
self.sites = Raster('../../examples/sites.tif')
#~ [1,2,1],
#~ [1,2,1],
#~ [0,1,2]
self.sites.resetMask(maskVals= [0])
self.mask = [
[False, False, False,],
[False, False, False,],
[True, False, False,]
]
fact = [
[1, 1, 3,],
[3, 2, 1,],
[0, 3, 1,]
]
site = [
[False, True, False,],
[False, True, False,],
[False, False, True,]
]
self.factraster = ma.array(data = fact, mask=self.mask, dtype=np.int)
self.sitesraster = ma.array(data = site, mask=self.mask, dtype=np.bool)
开发者ID:nextgis,项目名称:molusce,代码行数:29,代码来源:test_manager.py
示例11: setUp
def setUp(self):
self.factor = Raster('../../examples/multifact.tif')
#~ [1,1,3]
#~ [3,2,1]
#~ [0,3,1]
self.state = Raster('../../examples/sites.tif')
self.state.resetMask(maskVals= [0])
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:8,代码来源:test_mce.py
示例12: makeChangeMap
def makeChangeMap(self):
f, s = self.first, self.second
rows, cols = self.geodata['ySize'], self.geodata['xSize']
band = np.zeros([rows, cols])
self.rangeChanged.emit(self.tr("Creating change map %p%"), rows)
for i in xrange(rows):
for j in xrange(cols):
if not f.mask[i,j]:
r = f[i,j]
c = s[i,j]
band[i, j] = self.encode(r, c)
self.updateProgress.emit()
bands = [np.ma.array(data = band, mask = f.mask)]
raster = Raster()
raster.create(bands, self.geodata)
self.processFinished.emit(raster)
self.changeMap = raster
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:17,代码来源:manager.py
示例13: TestLRManager
class TestLRManager (unittest.TestCase):
def setUp(self):
self.output = Raster('../../examples/multifact.tif')
#~ [1,1,3]
#~ [3,2,1]
#~ [0,3,1]
self.output.resetMask([0])
self.state = self.output
self.factors = [Raster('../../examples/sites.tif'), Raster('../../examples/sites.tif')]
#~ [1,2,1],
#~ [1,2,1],
#~ [0,1,2]
self.output1 = Raster('../../examples/data.tif')
self.state1 = self.output1
self.factors1 = [Raster('../../examples/fact16.tif')]
def test_LR(self):
data = [
[3.0, 1.0, 3.0],
[3.0, 1.0, 3.0],
[0, 3.0, 1.0]
]
result = np.ma.array(data = data, mask = (data==0))
lr = LR(ns=0) # 3-class problem
lr.setTrainingData(self.state, self.factors, self.output)
lr.train()
predict = lr.getPrediction(self.state, self.factors)
predict = predict.getBand(1)
assert_array_equal(predict, result)
lr = LR(ns=1) # Two-class problem (it's because of boundary effect)
lr.setTrainingData(self.state1, self.factors1, self.output1)
lr.train()
predict = lr.getPrediction(self.state1, self.factors1)
predict = predict.getBand(1)
data = [
[0.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 2.0, 0.0],
[0.0, 2.0, 2.0, 0.0],
[0.0, 0.0, 0.0, 0.0],
]
result = np.ma.array(data = data, mask = (data==0))
assert_array_equal(predict, result)
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:46,代码来源:test_lr.py
示例14: test_get_state
def test_get_state(self):
smp = Sampler(self.state, self.factors, self.output, ns=0)
assert_array_equal(smp.get_state(self.state, 1,1), [0, 0])
assert_array_equal(smp.get_state(self.state, 0,0), [0, 1])
smp = Sampler(self.state, self.factors, self.output, ns=1)
res = [ 0, 1, 0, 0, 0, 1,
0, 1, 0, 0, 0, 1,
1, 0, 0, 1, 0, 0,
]
assert_array_equal(smp.get_state(self.state, 1,1), res)
inputRast = Raster('../../examples/sites.tif')
inputRast.resetMask([0])
smp = Sampler(inputRast, self.factors, self.output, ns=0)
assert_array_equal(smp.get_state(self.state, 1,1), [0])
assert_array_equal(smp.get_state(self.state, 0,0), [1])
开发者ID:nextgis,项目名称:molusce,代码行数:17,代码来源:test_sampler.py
示例15: TestAreaAnalysisManager
class TestAreaAnalysisManager (unittest.TestCase):
def setUp(self):
self.r1 = Raster('../../examples/multifact.tif')
# r1 -> r1 transition
self.r1r1 = [
[5, 5, 15,],
[15, 10, 5, ],
[0, 15, 5, ]
]
self.r2 = Raster('../../examples/multifact.tif')
self.r2.resetMask([0])
self.r2r2 = [
[0, 0, 8,],
[8, 4, 0,],
[100, 8, 0,]
]
self.r3 = Raster('../../examples/multifact.tif')
self.r3.resetMask([2])
def test_AreaAnalyst(self):
aa = AreaAnalyst(self.r1, self.r1)
raster = aa.getChangeMap()
band = raster.getBand(1)
assert_array_equal(band, self.r1r1)
# Masked raster
aa = AreaAnalyst(self.r2, self.r2)
raster = aa.getChangeMap()
band = raster.getBand(1)
assert_array_equal(band, self.r2r2)
def test_encode(self):
aa = AreaAnalyst(self.r1, self.r1)
self.assertEqual(aa.classes, [0,1,2,3])
self.assertEqual(aa.encode(1,2), 6)
for initClass in range(4):
for finalClass in range(4):
k = aa.encode(initClass, finalClass)
self.assertEqual(aa.decode(k), (initClass, finalClass))
self.assertEqual(aa.finalCodes(0), [0,1,2,3])
self.assertEqual(aa.finalCodes(1), [4,5,6,7])
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:43,代码来源:test_manager.py
示例16: _predict
def _predict(self, state):
'''
Predict the changes.
'''
geodata = self.changeMap.getGeodata()
rows, cols = geodata['ySize'], geodata['xSize']
if not self.changeMap.geoDataMatch(state):
raise WoeManagerError('Geometries of the state and changeMap rasters are different!')
prediction = np.zeros((rows,cols))
confidence = np.zeros((rows,cols))
mask = np.zeros((rows,cols))
woe = self.getWoe()
stateBand = state.getBand(1)
for r in xrange(rows):
for c in xrange(cols):
oldMax, currMax = -1000, -1000 # Small numbers
indexMax = -1 # Index of Max weight
initClass = stateBand[r,c] # Init class (state before transition)
try:
codes = self.analyst.codes(initClass) # Possible final states
for code in codes:
try: # If not all possible transitions are presented in the changeMap
map = woe[code] # Get WoE map of transition 'code'
except KeyError:
continue
w = map[r,c] # The weight in the (r,c)-pixel
if w > currMax:
indexMax, oldMax, currMax = code, currMax, w
decode = self.analyst.decode(indexMax) # Get init & final classes (initState, finalState)
prediction[r,c] = decode[1] # final class
confidence[r,c] = sigmoid(currMax) - sigmoid(oldMax)
except ValueError:
mask[r,c] = 1
predicted_band = np.ma.array(data=prediction, mask=mask)
self.prediction = Raster()
self.prediction.create([predicted_band], geodata)
confidence_band = np.ma.array(data=confidence, mask=mask)
self.confidence = Raster()
self.confidence.create([confidence_band], geodata)
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:43,代码来源:manager.py
示例17: setUp
def setUp(self):
self.r1 = Raster('../../examples/multifact.tif')
# r1 -> r1 transition
self.r1r1 = [
[5, 5, 15,],
[15, 10, 5, ],
[0, 15, 5, ]
]
self.r2 = Raster('../../examples/multifact.tif')
self.r2.resetMask([0])
self.r2r2 = [
[0, 0, 8,],
[8, 4, 0,],
[100, 8, 0,]
]
self.r3 = Raster('../../examples/multifact.tif')
self.r3.resetMask([2])
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:19,代码来源:test_manager.py
示例18: _predict
def _predict(self, state):
'''
Predict the changes.
'''
geodata = state.getGeodata()
rows, cols = geodata['ySize'], geodata['xSize']
# Get locations where self.initStateNum is occurs
band = state.getBand(1)
initStateMask = binaryzation(band, [self.initStateNum])
mask = band.mask
# Calculate summary map of factors weights
# Confidence:
# confidence is summary map of factors, if current state = self.initState
# confidence is 0, if current state != self.initState
# Prediction:
# predicted value is a constant = self.finalStateNum, if current state = self.initState
# predicted value is current state, if current state != self.initState
confidence = np.zeros((rows,cols))
weights = self.getWeights()
weightNum = 0 # Number of processed weights
for f in self.factors:
if not f.geoDataMatch(state):
raise MCEError('Geometries of the state and factor rasters are different!')
f.normalize(mode = 'maxmin')
for i in xrange(f.getBandsCount()):
band = f.getBand(i+1)
confidence = confidence + band*weights[weightNum]
mask = np.ma.mask_or(mask, band.mask)
weightNum = weightNum + 1
confidence = confidence*initStateMask
prediction = np.copy(state.getBand(1))
prediction = np.logical_not(initStateMask) * prediction
prediction = prediction + initStateMask*self.finalStateNum
predicted_band = np.ma.array(data=prediction, mask=mask)
self.prediction = Raster()
self.prediction.create([predicted_band], geodata)
confidence_band = np.ma.array(data=confidence, mask=mask)
self.confidence = Raster()
self.confidence.create([confidence_band], geodata)
开发者ID:asiaairsurvey,项目名称:molusce,代码行数:42,代码来源:mce.py
示例19: setUp
def setUp(self):
# Raster1:
# ~ [1, 1, 3,],
# ~ [3, 2, 1,],
# ~ [0, 3, 1,]
self.raster1 = Raster("../../examples/multifact.tif")
self.raster1.resetMask([0])
self.X = np.array([[1, 2, 3], [3, 2, 1], [0, 1, 1]])
self.X = np.ma.array(self.X, mask=(self.X == 0))
self.raster2 = Raster()
self.raster2.create([self.X], self.raster1.getGeodata())
self.aa = AreaAnalyst(self.raster1, self.raster2)
self.crosstab = CrossTableManager(self.raster1, self.raster2)
# Simple model
self.model = Model(state=self.raster1)
开发者ID:nextgis,项目名称:molusce,代码行数:20,代码来源:test_sim.py
示例20: setUp
def setUp(self):
self.factor = Raster('../../examples/multifact.tif')
#~ [1,1,3]
#~ [3,2,1]
#~ [0,3,1]
self.state = Raster('../../examples/sites.tif')
self.state.resetMask(maskVals= [0])
#~ [1,2,1],
#~ [1,2,1],
#~ [0,1,2]
self.areaAnalyst = AreaAnalyst(self.state, second=None)
开发者ID:nextgis,项目名称:molusce,代码行数:12,代码来源:test_mce.py
注:本文中的molusce.algorithms.dataprovider.Raster类示例由纯净天空整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。 |
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