def execute(self):
rdata = []
r = []
for name in self.case_files:
fid = open(name, 'r')
fid.readline()
radius = fid.readline().split()[4]
radius = float(radius.strip('r='))
r.append(radius)
fid.readline()
rdata.append(np.loadtxt(fid))
isort = np.argsort(r)
r = np.asarray(r)[isort]
r = (r - r[0]) / self.blade_length
rdata = np.asarray(rdata)[isort]
if len(self.case_filter) == 0:
self.case_filter = range(rdata.shape[1])
for i in self.case_filter:
c = np.zeros((rdata.shape[0], 9))
c[:, 0] = r
c[:, 1:] = rdata[:, i, :] * 1.e6
v = LoadVectorArray()
try:
v.case_id = cases[i]
except:
v.case_id = 'case%03d' % i
v._fromarray(c)
self.load_cases.cases.append(v)
def execute(self):
rdata = []
r = []
for name in self.case_files:
fid = open(name, 'r')
fid.readline()
radius = fid.readline().split()[4]
radius = float(radius.strip('r='))
r.append(radius)
fid.readline()
rdata.append(np.loadtxt(fid))
isort = np.argsort(r)
r = np.asarray(r)[isort]
r = (r - r[0]) / self.blade_length
rdata = np.asarray(rdata)[isort]
if len(self.case_filter) == 0:
self.case_filter = range(rdata.shape[1])
for i in self.case_filter:
c = np.zeros((rdata.shape[0], 9))
c[:, 0] = r
c[:, 1:] = rdata[:, i, :] * 1.e6
v = LoadVectorArray()
try:
v.case_id = cases[i]
except:
v.case_id = 'case%03d' % i
v._fromarray(c)
self.load_cases.cases.append(v)
def execute(self):
for name in self.case_files:
fid = open(name, 'r')
case_id = fid.readline().split()[1]
data = np.loadtxt(fid)
lc = LoadVectorArray()
lc._fromarray(data)
self.load_cases.cases.append(lc.copy())
def execute(self):
for name in self.case_files:
fid = open(name, 'r')
case_id = fid.readline().split()[1]
data = np.loadtxt(fid)
lc = LoadVectorArray()
lc._fromarray(data)
self.load_cases.cases.append(lc.copy())
