diff --git a/source/python/mods/disaggregation.py b/source/python/mods/disaggregation.py
index 13d1cab529dc1116cf2dd9e450851c5c04bd9f28..337aa44b95f6fd890fbdbc3bec1b5025f4b654d8 100644
--- a/source/python/mods/disaggregation.py
+++ b/source/python/mods/disaggregation.py
@@ -209,27 +209,27 @@ def IA3(g):
import numpy as np
# time step
- dt=1.0
+ dt = 1.0
############### Non-negative Geometric Mean Based Algorithm ###############
# for the left boundary the following boundary condition is valid:
# the value at t=0 of the interpolation algorithm coincides with the
# first data value according to the persistence hypothesis
- f=[g[0]]
+ f = [g[0]]
# compute two first sub-grid intervals without monotonicity check
# go through the data series and extend each interval by two sub-grid
# points and interpolate the corresponding data values
# except for the last interval due to boundary conditions
- for i in range(0,2):
+ for i in range(0, 2):
# as a requirement:
# if there is a zero data value such that g[i]=0, then the whole
# interval in f has to be zero to such that f[i+1]=f[i+2]=f[i+3]=0
# according to Eq. (6)
- if g[i]==0.:
- f.extend([0.,0.,0.])
+ if g[i] == 0.:
+ f.extend([0., 0., 0.])
# otherwise the sub-grid values are calculated and added to the list
else:
@@ -244,11 +244,11 @@ def IA3(g):
# the function value at the first sub-grid point (fi1) is determined
# according to the equal area condition with Eq. (19)
- fi1=3./2.*g[i]-5./12.*fip1-1./12.*fi
+ fi1 = 3./2.*g[i]-5./12.*fip1-1./12.*fi
# the function value at the second sub-grid point (fi2) is determined
# according Eq. (18)
- fi2=fi1+1./3.*(fip1-fi)
+ fi2 = fi1+1./3.*(fip1-fi)
# add next interval of interpolated (sub-)grid values
f.append(fi1)
@@ -259,18 +259,18 @@ def IA3(g):
# go through the data series and extend each interval by two sub-grid
# points and interpolate the corresponding data values
# except for the last interval due to boundary conditions
- for i in range(2,len(g)-1):
+ for i in range(2, len(g)-1):
# as a requirement:
# if there is a zero data value such that g[i]=0, then the whole
# interval in f has to be zero to such that f[i+1]=f[i+2]=f[i+3]=0
# according to Eq. (6)
- if g[i]==0.:
+ if g[i] == 0.:
# apply monotonicity filter for interval before
# check if there is "M" or "W" shape
- if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5])==-1 \
- and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4])==-1 \
- and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3])==-1:
+ if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5]) == -1 \
+ and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4]) == -1 \
+ and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3]) == -1:
# the monotonicity filter corrects the value at (fim1) by
# substituting (fim1) with (fmon), see Eq. (27), (28) and (29)
@@ -282,11 +282,11 @@ def IA3(g):
# recomputation of the sub-grid interval values while the
# interval boundaries (fi) and (fip2) remains unchanged
# see Eq. (18) and (19)
- f[-4]=fmon
- f[-6]=3./2.*g[i-2]-5./12.*fmon-1./12.*f[-7]
- f[-5]=f[-6]+(fmon-f[-7])/3.
- f[-3]=3./2.*g[i-1]-5./12.*f[-1]-1./12.*fmon
- f[-2]=f[-3]+(f[-1]-fmon)/3.
+ f[-4] = fmon
+ f[-6] = 3./2.*g[i-2]-5./12.*fmon-1./12.*f[-7]
+ f[-5] = f[-6]+(fmon-f[-7])/3.
+ f[-3] = 3./2.*g[i-1]-5./12.*f[-1]-1./12.*fmon
+ f[-2] = f[-3]+(f[-1]-fmon)/3.
f.extend([0.,0.,0.])
@@ -299,21 +299,21 @@ def IA3(g):
# the value at the end of the interval (fip1) is prescribed by the
# geometric mean, restricted such that non-negativity is guaranteed
# according to Eq. (25)
- fip1=min( 3.*g[i] , 3.*g[i+1] , np.sqrt(g[i+1]*g[i]) )
+ fip1 = min( 3.*g[i] , 3.*g[i+1] , np.sqrt(g[i+1]*g[i]) )
# the function value at the first sub-grid point (fi1) is determined
# according to the equal area condition with Eq. (19)
- fi1=3./2.*g[i]-5./12.*fip1-1./12.*fi
+ fi1 = 3./2.*g[i]-5./12.*fip1-1./12.*fi
# the function value at the second sub-grid point (fi2) is determined
# according Eq. (18)
- fi2=fi1+1./3.*(fip1-fi)
+ fi2 = fi1+1./3.*(fip1-fi)
# apply monotonicity filter for interval before
# check if there is "M" or "W" shape
- if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5])==-1 \
- and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4])==-1 \
- and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3])==-1:
+ if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5]) == -1 \
+ and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4]) == -1 \
+ and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3]) == -1:
# the monotonicity filter corrects the value at (fim1) by
# substituting (fim1) with fmon, see Eq. (27), (28) and (29)
@@ -325,11 +325,11 @@ def IA3(g):
# recomputation of the sub-grid interval values while the
# interval boundaries (fi) and (fip2) remains unchanged
# see Eq. (18) and (19)
- f[-4]=fmon
- f[-6]=3./2.*g[i-2]-5./12.*fmon-1./12.*f[-7]
- f[-5]=f[-6]+(fmon-f[-7])/3.
- f[-3]=3./2.*g[i-1]-5./12.*f[-1]-1./12.*fmon
- f[-2]=f[-3]+(f[-1]-fmon)/3.
+ f[-4] = fmon
+ f[-6] = 3./2.*g[i-2]-5./12.*fmon-1./12.*f[-7]
+ f[-5] = f[-6]+(fmon-f[-7])/3.
+ f[-3] = 3./2.*g[i-1]-5./12.*f[-1]-1./12.*fmon
+ f[-2] = f[-3]+(f[-1]-fmon)/3.
# add next interval of interpolated (sub-)grid values
f.append(fi1)
@@ -342,12 +342,12 @@ def IA3(g):
# if there is a zero data value such that g[i]=0, then the whole
# interval in f has to be zero to such that f[i+1]=f[i+2]=f[i+3]=0
# according to Eq. (6)
- if g[-1]==0.:
+ if g[-1] == 0.:
# apply monotonicity filter for interval before
# check if there is "M" or "W" shape
- if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5])==-1 \
- and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4])==-1 \
- and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3])==-1:
+ if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5]) == -1 \
+ and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4]) == -1 \
+ and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3]) == -1:
# the monotonicity filter corrects the value at (fim1) by
# substituting (fim1) with (fmon), see Eq. (27), (28) and (29)
@@ -359,11 +359,11 @@ def IA3(g):
# recomputation of the sub-grid interval values while the
# interval boundaries (fi) and (fip2) remains unchanged
# see Eq. (18) and (19)
- f[-4]=fmon
- f[-6]=3./2.*g[-3]-5./12.*fmon-1./12.*f[-7]
- f[-5]=f[-6]+(fmon-f[-7])/3.
- f[-3]=3./2.*g[-2]-5./12.*f[-1]-1./12.*fmon
- f[-2]=f[-3]+(f[-1]-fmon)/3.
+ f[-4] = fmon
+ f[-6] = 3./2.*g[-3]-5./12.*fmon-1./12.*f[-7]
+ f[-5] = f[-6]+(fmon-f[-7])/3.
+ f[-3] = 3./2.*g[-2]-5./12.*f[-1]-1./12.*fmon
+ f[-2] = f[-3]+(f[-1]-fmon)/3.
f.extend([0.,0.,0.])
@@ -384,9 +384,9 @@ def IA3(g):
# apply monotonicity filter for interval before
# check if there is "M" or "W" shape
- if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5])==-1 \
- and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4])==-1 \
- and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3])==-1:
+ if np.sign(f[-5]-f[-6]) * np.sign(f[-4]-f[-5]) == -1 \
+ and np.sign(f[-4]-f[-5]) * np.sign(f[-3]-f[-4]) == -1 \
+ and np.sign(f[-3]-f[-4]) * np.sign(f[-2]-f[-3]) == -1:
# the monotonicity filter corrects the value at (fim1) by
# substituting (fim1) with (fmon), see Eq. (27), (28) and (29)
@@ -398,11 +398,11 @@ def IA3(g):
# recomputation of the sub-grid interval values while the
# interval boundaries (fi) and (fip2) remains unchanged
# see Eq. (18) and (19)
- f[-4]=fmon
- f[-6]=3./2.*g[-3]-5./12.*fmon-1./12.*f[-7]
- f[-5]=f[-6]+(fmon-f[-7])/3.
- f[-3]=3./2.*g[-2]-5./12.*f[-1]-1./12.*fmon
- f[-2]=f[-3]+(f[-1]-fmon)/3.
+ f[-4] = fmon
+ f[-6] = 3./2.*g[-3]-5./12.*fmon-1./12.*f[-7]
+ f[-5] = f[-6]+(fmon-f[-7])/3.
+ f[-3] = 3./2.*g[-2]-5./12.*f[-1]-1./12.*fmon
+ f[-2] = f[-3]+(f[-1]-fmon)/3.
# add next interval of interpolated (sub-)grid values
f.append(fi1)