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())