diff --git a/wetb/prepost/Simulations.py b/wetb/prepost/Simulations.py
index bdc0cdf314ceeb346e309d1a37d39832800bdfe5..d46e0b1c20b19f77d427236d4e07b75b1bfb0514 100755
--- a/wetb/prepost/Simulations.py
+++ b/wetb/prepost/Simulations.py
@@ -3316,7 +3316,7 @@ class WeibullParameters(object):
self.Vstep = 2.
self.shape_k = 2.
-def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12,Ntheta=181):
+def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12, Ntheta=181):
"""
The function computes load envelopes for given channels and a groups of
load cases starting from the envelopes computed for single simulations.
@@ -3361,12 +3361,12 @@ def compute_env_of_env(envelope, dlc_list, Nx=300, Nsectors=12,Ntheta=181):
cloud[(Nx+1)*i:(Nx+1)*(i+1),:] = envelope[dlc_list[i]]
# Compute total Hull of all the envelopes
hull = scipy.spatial.ConvexHull(cloud[:,:2])
- cc = np.append(cloud[hull.vertices,:2],\
- cloud[hull.vertices[0],:2].reshape(1,2),axis=0)
+ cc = np.append(cloud[hull.vertices,:2],
+ cloud[hull.vertices[0],:2].reshape(1,2),axis=0)
# Interpolate full envelope
- cc_x,cc_up,cc_low,cc_int= int_envelope(cc[:,0],cc[:,1],Nx=Nx)
+ cc_x,cc_up,cc_low,cc_int= int_envelope(cc[:,0], cc[:,1], Nx=Nx)
# Project full envelope on given direction
- cc_proj = proj_envelope(cc_x,cc_up,cc_low,cc_int,Nx,Nsectors,Ntheta)
+ cc_proj = proj_envelope(cc_x, cc_up, cc_low, cc_int, Nx, Nsectors, Ntheta)
env_proj = np.zeros([len(cc_proj),6])
env_proj[:,:2] = cc_proj
@@ -3403,26 +3403,29 @@ def int_envelope(ch1,ch2,Nx):
indmin = np.argmin(ch1)
if indmax > indmin:
lower = np.array([ch1[indmin:indmax+1],ch2[indmin:indmax+1]]).T
- upper = np.concatenate((np.array([ch1[indmax:],ch2[indmax:]]).T,\
- np.array([ch1[:indmin+1],ch2[:indmin+1]]).T),axis=0)
+ upper = np.concatenate((np.array([ch1[indmax:],ch2[indmax:]]).T,
+ np.array([ch1[:indmin+1],ch2[:indmin+1]]).T),
+ axis=0)
else:
upper = np.array([ch1[indmax:indmin+1],ch2[indmax:indmin+1]]).T
- lower = np.concatenate((np.array([ch1[indmin:],ch2[indmin:]]).T,\
- np.array([ch1[:indmax+1],ch2[:indmax+1]]).T),axis=0)
+ lower = np.concatenate((np.array([ch1[indmin:],ch2[indmin:]]).T,
+ np.array([ch1[:indmax+1],ch2[:indmax+1]]).T),
+ axis=0)
- int_1 = np.linspace(min(min(upper[:,0]),min(lower[:,0])),\
- max(max(upper[:,0]),max(upper[:,0])),Nx/2+1)
+ int_1 = np.linspace(min(upper[:,0].min(),min(lower[:,0])),\
+ max(upper[:,0].max(),max(upper[:,0])),Nx/2+1)
upper = np.flipud(upper)
int_2_up = np.interp(int_1,np.array(upper[:,0]),np.array(upper[:,1]))
int_2_low = np.interp(int_1,np.array(lower[:,0]),np.array(lower[:,1]))
- int_env = np.concatenate((np.array([int_1[:-1],int_2_up[:-1]]).T,\
- np.array([int_1[::-1],int_2_low[::-1]]).T),axis=0)
+ int_env = np.concatenate((np.array([int_1[:-1],int_2_up[:-1]]).T,
+ np.array([int_1[::-1],int_2_low[::-1]]).T),
+ axis=0)
return int_1, int_2_up, int_2_low, int_env
-def proj_envelope(env_x,env_up,env_low,env,Nx,Nsectors,Ntheta):
+def proj_envelope(env_x, env_up, env_low, env, Nx, Nsectors, Ntheta):
# Function to project envelope on given angles
# Angles of projection is defined by Nsectors
@@ -3448,45 +3451,45 @@ def proj_envelope(env_x,env_up,env_low,env,Nx,Nsectors,Ntheta):
for i in range(Nsectors):
if sectors[i]>=-np.pi and sectors[i+1]<-np.pi/2:
- indices = np.where(np.logical_and(theta_int >= sectors[i],\
- theta_int <= sectors[i+1]))
- maxR = max(R_int[indices])
+ indices = np.where(np.logical_and(theta_int >= sectors[i],
+ theta_int <= sectors[i+1]))
+ maxR = R_int[indices].max()
proj[i+1,0] = maxR*np.cos(sectors[i+1])
proj[i+1,1] = maxR*np.sin(sectors[i+1])
elif sectors[i]==-np.pi/2:
continue
elif sectors[i]>-np.pi/2 and sectors[i+1]<=0:
- indices = np.where(np.logical_and(theta_int >= sectors[i],\
- theta_int <= sectors[i+1]))
- maxR = max(R_int[indices])
+ indices = np.where(np.logical_and(theta_int >= sectors[i],
+ theta_int <= sectors[i+1]))
+ maxR = R_int[indices].max()
proj[i,0] = maxR*np.cos(sectors[i])
proj[i,1] = maxR*np.sin(sectors[i])
elif sectors[i]>=0 and sectors[i+1]<np.pi/2:
- indices = np.where(np.logical_and(theta_int >= sectors[i],\
- theta_int <= sectors[i+1]))
- maxR = max(R_int[indices])
+ indices = np.where(np.logical_and(theta_int >= sectors[i],
+ theta_int <= sectors[i+1]))
+ maxR = R_int[indices].max()
proj[i+1,0] = maxR*np.cos(sectors[i+1])
proj[i+1,1] = maxR*np.sin(sectors[i+1])
elif sectors[i]==np.pi/2:
continue
elif sectors[i]>np.pi/2 and sectors[i+1]<=np.pi:
- indices = np.where(np.logical_and(theta_int >= sectors[i],\
- theta_int <= sectors[i+1]))
- maxR = max(R_int[indices])
+ indices = np.where(np.logical_and(theta_int >= sectors[i],
+ theta_int <= sectors[i+1]))
+ maxR = R_int[indices].max()
proj[i,0] = maxR*np.cos(sectors[i])
proj[i,1] = maxR*np.sin(sectors[i])
ind = np.where(sectors==0)
- proj[ind,0] = max(env[:,0])
+ proj[ind,0] = env[:,0].max()
ind = np.where(sectors==np.pi/2)
- proj[ind,1] = max(env[:,1])
+ proj[ind,1] = env[:,1].max()
ind = np.where(sectors==-np.pi)
- proj[ind,0] = min(env[:,0])
+ proj[ind,0] = env[:,0].min()
ind = np.where(sectors==-np.pi/2)
- proj[ind,1] = min(env[:,1])
+ proj[ind,1] = env[:,1].min()
return proj