def put_file_order(fname):
arr = []
aux = []
n = 1
f0 = open(fname).read().split('\n')
i = 0
while i < len(f0):
if0 = f0[i].split()
if len(if0) != n:
if n != 1:
flaux = phc.flatten(aux)
for j in range(n):
arr.extend(flaux[j::n])
n = len(if0)
aux = []
if len(if0) == 1:
arr.extend(if0)
else:
aux.append(if0)
i += 1
return arr
def put_file_order(fname):
arr = []
aux = []
n = 1
f0 = open(fname).read().split('\n')
i = 0
while i < len(f0):
if0 = f0[i].split()
if len(if0) != n:
if n != 1:
flaux = phc.flatten(aux)
for j in range(n):
arr.extend(flaux[j::n])
n = len(if0)
aux = []
if len(if0) == 1:
arr.extend(if0)
else:
aux.append(if0)
i += 1
return arr
def griddataBAtlas(minfo, models, params, listpar, dims, isig):
import pyhdust.phc as phc
from scipy.interpolate import griddata
idx = range(len(minfo))
lim_vals = len(params)*[ [], ]
for i in [i for i in range(len(params)) if i != isig]:
lim_vals[i] = [
phc.find_nearest(listpar[i], params[i], bigger=False),
phc.find_nearest(listpar[i], params[i], bigger=True)]
tmp = np.where((minfo[:, i] == lim_vals[i][0]) |
(minfo[:, i] == lim_vals[i][1]))
idx = np.intersect1d(idx, tmp)
#
out_interp = griddata(minfo[idx], models[idx], params)[0]
#
if (np.sum(out_interp) == 0 or np.sum(np.isnan(out_interp)) > 0):
print("# Houve um problema na grade. Tentando arrumar...")
print(params)
idx = np.arange(len(minfo))
for i in [i for i in range(len(params)) if i != dims["sig0"]]:
imin = lim_vals[i][0]
if lim_vals[i][0] != np.min(listpar[i]):
imin = phc.find_nearest(listpar[i], lim_vals[i][0],
bigger=False)
imax = lim_vals[i][1]
if lim_vals[i][1] != np.max(listpar[i]):
imax = phc.find_nearest(listpar[i], lim_vals[i][1],
bigger=True)
lim_vals[i] = [imin, imax]
tmp = np.where((minfo[:, i] >= lim_vals[i][0]) &
(minfo[:, i] <= lim_vals[i][1]))
idx = np.intersect1d(idx, phc.flatten(tmp))
out_interp = griddata(minfo[idx], models[idx], params)[0]
#
if (np.sum(out_interp) == 0 or np.sum(np.isnan(out_interp)) > 0):
print("# Houve um problema na grade e eu nao conseguir arrumar...")
#
return out_interp