def _lerp(a, b, t, out=None):
""" Linearly interpolate from a to b by a factor of t """
diff_b_a = subtract(b, a)
# asanyarray is a stop-gap until gh-13105
lerp_interpolation = asanyarray(add(a, diff_b_a * t, out=out))
subtract(b, diff_b_a * (1 - t), out=lerp_interpolation, where=t >= 0.5)
if lerp_interpolation.ndim == 0 and out is None:
lerp_interpolation = lerp_interpolation[()] # unpack 0d arrays
return lerp_interpolation
def CalcLSWI (self, NIR, SWIR, Blue, fill):
Blue [Blue >= 0.27] = fill
Swir_lower=numpy.where(Blue == fill, fill , add(NIR, SWIR))
Swir_upper=numpy.where(Blue == fill, fill , subtract(NIR, SWIR))
Swir_lower=numpy.where(Swir_lower ==0 , fill, Swir_lower)
LSWI=numpy.where(Swir_lower==fill, fill ,Swir_upper/Swir_lower)
return LSWI
def CalcNDVI ( self , NIR , Red, fill):
Ndvi_lower = numpy.where (NIR == fill, fill , add (NIR , Red))
Ndvi_upper = numpy.where (NIR == fill, fill ,subtract (NIR , Red))
#Mask = Numpy.Greater (Ndvi_lower, 0)
Ndvi_lower = numpy.where (Ndvi_lower == 0 , fill , Ndvi_lower)
NDVI = numpy.where (Ndvi_lower == fill , fill , Ndvi_upper/Ndvi_lower)
return NDVI
def CalcEVI ( self , NIR , Red , Blue, fill ):
#for cloud-cover blue >= 0.27
Blue [Blue >= 0.27] = fill
Evi_upper = numpy.where (Blue == fill , fill , 2.5 * subtract (NIR , Red))
Evi_lower = numpy.where (Blue == fill , fill , (NIR + (6 * Red) - (7.5 * Blue) + 1))
Evi_lower = numpy.where (Evi_lower == 0 , fill , Evi_lower)
EVI = numpy.where(Evi_lower == fill , fill , Evi_upper/Evi_lower)
#EVI [EVI <= 0] = fill
EVI [EVI >= 1] = fill
#EVI = 2.5 * (NIR - Red) / (NIR + 6 * Red - 7.5 * Blue + 1) * mask
return EVI
def CalcMLSWI ( self , NIR , SWIR, fill):
mlswi_lower = numpy.where (NIR == fill, fill , add (NIR , SWIR))
mlswi_upper = numpy.where (NIR == fill, fill ,subtract (NIR , SWIR))
#Mask = Numpy.Greater (Ndvi_lower, 0)
mlswi_lower = numpy.where (mlswi_lower == 0 , fill , mlswi_lower)
lower = (1-mlswi_lower)
lower = numpy.where (lower == 0 , fill , lower)
mlswi = numpy.where (mlswi_lower == fill , fill , (1-mlswi_upper)/lower)
#mlswi1= numpy.where (((mlswi>= 0.75) & (mlswi <= 1.0)), 1, 0)
#MLSWI = numpy.where (NIR == fill , fill , mlswi1 )
return mlswi
def _ptp(a, axis=None, out=None, keepdims=False):
return um.subtract(
umr_maximum(a, axis, None, out, keepdims),
umr_minimum(a, axis, None, None, keepdims),
out,
)
def myfunc(x):
return clf.predict([Data[0][x], Data[1][x], subtract(Data[0][x], Data[1][x])])
def myfunc(x):
'''
並列に計算したい関数
'''
return clf.predict([Data[0][x], Data[1][x], subtract(Data[0][x], Data[1][x])])
def _ptp(a, axis=None, out=None, keepdims=False):
return um.subtract(
umr_maximum(a, axis, None, out, keepdims),
umr_minimum(a, axis, None, None, keepdims),
out
)
def CalcDVEL(self, EVI, LSWI, fill):
DVEL=numpy.where(LSWI == fill, fill , subtract(EVI,LSWI))
return DVEL
def CalcNDVI(self, NIR, Red):
ndvi_lower = add(NIR, Red)
ndvi_upper = subtract(NIR, Red)
NDVI = numpy.where(ndvi_lower == 0, 0.0, ndvi_upper/ndvi_lower)
return NDVI
