2019-04-13 14:41:32 +05:30
|
|
|
# -*- coding: UTF-8 no BOM -*-
|
|
|
|
import h5py
|
|
|
|
import re
|
2019-04-17 23:27:16 +05:30
|
|
|
import numpy as np
|
2019-04-13 14:41:32 +05:30
|
|
|
|
|
|
|
# ------------------------------------------------------------------
|
|
|
|
class DADF5():
|
|
|
|
"""Read and write to DADF5 files"""
|
|
|
|
|
|
|
|
# ------------------------------------------------------------------
|
|
|
|
def __init__(self,
|
|
|
|
filename,
|
|
|
|
mode = 'r',
|
|
|
|
):
|
|
|
|
|
|
|
|
if mode not in ['a','r']:
|
|
|
|
print('Invalid file access mode')
|
|
|
|
with h5py.File(filename,mode):
|
|
|
|
pass
|
|
|
|
|
|
|
|
with h5py.File(filename,'r') as f:
|
|
|
|
|
2019-05-03 10:16:22 +05:30
|
|
|
if f.attrs['DADF5-major'] != 0 or f.attrs['DADF5-minor'] != 2:
|
2019-04-17 23:27:16 +05:30
|
|
|
raise TypeError('Unsupported DADF5 version {} '.format(f.attrs['DADF5-version']))
|
2019-04-13 14:41:32 +05:30
|
|
|
|
2019-05-03 10:16:22 +05:30
|
|
|
self.structured = 'grid' in f['geometry'].attrs.keys()
|
2019-04-13 14:41:32 +05:30
|
|
|
|
|
|
|
if self.structured:
|
2019-05-03 10:16:22 +05:30
|
|
|
self.grid = f['geometry'].attrs['grid']
|
|
|
|
self.size = f['geometry'].attrs['size']
|
2019-04-13 14:41:32 +05:30
|
|
|
|
|
|
|
r=re.compile('inc[0-9]+')
|
2019-04-17 23:27:16 +05:30
|
|
|
self.increments = [{'inc': int(u[3:]),
|
|
|
|
'time': round(f[u].attrs['time/s'],12),
|
2019-04-13 14:41:32 +05:30
|
|
|
} for u in f.keys() if r.match(u)]
|
2019-04-17 23:27:16 +05:30
|
|
|
|
2019-04-18 15:28:17 +05:30
|
|
|
self.constituents = np.unique(f['mapping/cellResults/constituent']['Name']).tolist() # ToDo: I am not to happy with the name
|
|
|
|
self.constituents = [c.decode() for c in self.constituents]
|
2019-04-17 23:27:16 +05:30
|
|
|
|
2019-04-18 15:28:17 +05:30
|
|
|
self.materialpoints = np.unique(f['mapping/cellResults/materialpoint']['Name']).tolist() # ToDo: I am not to happy with the name
|
|
|
|
self.materialpoints = [m.decode() for m in self.materialpoints]
|
|
|
|
|
|
|
|
self.Nconstituents = [i for i in range(np.shape(f['mapping/cellResults/constituent'])[1])]
|
|
|
|
self.Nmaterialpoints = np.shape(f['mapping/cellResults/constituent'])[0]
|
|
|
|
|
|
|
|
self.c_output_types = []
|
|
|
|
for c in self.constituents:
|
|
|
|
for o in f['inc{:05}/constituent/{}'.format(self.increments[0]['inc'],c)].keys():
|
|
|
|
self.c_output_types.append(o)
|
|
|
|
self.c_output_types = list(set(self.c_output_types)) # make unique
|
2019-05-16 03:02:23 +05:30
|
|
|
|
|
|
|
self.m_output_types = []
|
|
|
|
for m in self.materialpoints:
|
|
|
|
for o in f['inc{:05}/materialpoint/{}'.format(self.increments[0]['inc'],m)].keys():
|
|
|
|
self.m_output_types.append(o)
|
|
|
|
self.m_output_types = list(set(self.m_output_types)) # make unique
|
2019-04-18 15:28:17 +05:30
|
|
|
|
|
|
|
self.active= {'increments': self.increments,
|
|
|
|
'constituents': self.constituents,
|
|
|
|
'materialpoints': self.materialpoints,
|
|
|
|
'constituent': self.Nconstituents,
|
2019-05-16 03:02:23 +05:30
|
|
|
'c_output_types': self.c_output_types,
|
|
|
|
'm_output_types': self.m_output_types}
|
2019-04-13 14:41:32 +05:30
|
|
|
|
|
|
|
self.filename = filename
|
|
|
|
self.mode = mode
|
2019-05-16 03:02:23 +05:30
|
|
|
|
|
|
|
|
2019-04-18 15:28:17 +05:30
|
|
|
def list_data(self):
|
|
|
|
"""Shows information on all datasets in the file"""
|
|
|
|
with h5py.File(self.filename,'r') as f:
|
|
|
|
group_inc = 'inc{:05}'.format(self.active['increments'][0]['inc'])
|
|
|
|
for c in self.active['constituents']:
|
|
|
|
print('\n'+c)
|
|
|
|
group_constituent = group_inc+'/constituent/'+c
|
|
|
|
for t in self.active['c_output_types']:
|
|
|
|
print(' {}'.format(t))
|
|
|
|
group_output_types = group_constituent+'/'+t
|
|
|
|
try:
|
|
|
|
for x in f[group_output_types].keys():
|
|
|
|
print(' {} ({})'.format(x,f[group_output_types+'/'+x].attrs['Description'].decode()))
|
|
|
|
except:
|
|
|
|
pass
|
2019-05-16 03:02:23 +05:30
|
|
|
for m in self.active['materialpoints']:
|
|
|
|
group_materialpoint = group_inc+'/materialpoint/'+m
|
|
|
|
for t in self.active['m_output_types']:
|
|
|
|
print(' {}'.format(t))
|
|
|
|
group_output_types = group_materialpoint+'/'+t
|
|
|
|
try:
|
|
|
|
for x in f[group_output_types].keys():
|
|
|
|
print(' {} ({})'.format(x,f[group_output_types+'/'+x].attrs['Description'].decode()))
|
|
|
|
except:
|
|
|
|
pass
|
2019-04-18 15:28:17 +05:30
|
|
|
|
2019-04-17 23:27:16 +05:30
|
|
|
|
|
|
|
def get_dataset_location(self,label):
|
2019-04-18 15:28:17 +05:30
|
|
|
"""Returns the location of all active datasets with given label"""
|
2019-04-17 23:27:16 +05:30
|
|
|
path = []
|
|
|
|
with h5py.File(self.filename,'r') as f:
|
|
|
|
for i in self.active['increments']:
|
|
|
|
group_inc = 'inc{:05}'.format(i['inc'])
|
|
|
|
for c in self.active['constituents']:
|
|
|
|
group_constituent = group_inc+'/constituent/'+c
|
2019-04-18 15:28:17 +05:30
|
|
|
for t in self.active['c_output_types']:
|
2019-04-17 23:27:16 +05:30
|
|
|
try:
|
|
|
|
f[group_constituent+'/'+t+'/'+label]
|
|
|
|
path.append(group_constituent+'/'+t+'/'+label)
|
|
|
|
except:
|
|
|
|
pass
|
2019-05-16 03:57:06 +05:30
|
|
|
for m in self.active['materialpoints']:
|
|
|
|
group_materialpoint = group_inc+'/materialpoint/'+m
|
|
|
|
for t in self.active['m_output_types']:
|
|
|
|
try:
|
|
|
|
f[group_materialpoint+'/'+t+'/'+label]
|
|
|
|
path.append(group_materialpoint+'/'+t+'/'+label)
|
|
|
|
except:
|
|
|
|
pass
|
2019-04-17 23:27:16 +05:30
|
|
|
return path
|
|
|
|
|
|
|
|
|
|
|
|
def read_dataset(self,path,c):
|
2019-04-18 15:28:17 +05:30
|
|
|
"""
|
|
|
|
Dataset for all points/cells
|
|
|
|
|
|
|
|
If more than one path is given, the dataset is composed of the individual contributions
|
|
|
|
"""
|
2019-04-17 23:27:16 +05:30
|
|
|
with h5py.File(self.filename,'r') as f:
|
2019-04-18 15:28:17 +05:30
|
|
|
shape = (self.Nmaterialpoints,) + np.shape(f[path[0]])[1:]
|
2019-05-16 13:01:13 +05:30
|
|
|
if len(shape) == 1: shape = shape +(1,)
|
2019-04-17 23:27:16 +05:30
|
|
|
dataset = np.full(shape,np.nan)
|
2019-04-18 15:28:17 +05:30
|
|
|
for pa in path:
|
|
|
|
label = pa.split('/')[2]
|
2019-05-16 03:57:06 +05:30
|
|
|
try:
|
|
|
|
p = np.where(f['mapping/cellResults/constituent'][:,c]['Name'] == str.encode(label))[0]
|
|
|
|
u = (f['mapping/cellResults/constituent'][p,c]['Position'])
|
2019-05-16 13:01:13 +05:30
|
|
|
a = np.array(f[pa])
|
|
|
|
if len(a.shape) == 1:
|
|
|
|
a=a.reshape([a.shape[0],1])
|
|
|
|
dataset
|
2019-05-16 03:57:06 +05:30
|
|
|
except:
|
|
|
|
pass
|
|
|
|
try:
|
|
|
|
p = np.where(f['mapping/cellResults/materialpoint']['Name'] == str.encode(label))[0]
|
|
|
|
u = (f['mapping/cellResults/materialpoint'][p.tolist()]['Position'])
|
2019-05-16 13:01:13 +05:30
|
|
|
a = np.array(f[pa])
|
|
|
|
if len(a.shape) == 1:
|
|
|
|
a=a.reshape([a.shape[0],1])
|
|
|
|
dataset[p,:] = a[u,:]
|
2019-05-16 03:57:06 +05:30
|
|
|
except:
|
|
|
|
pass
|
|
|
|
|
2019-04-17 23:27:16 +05:30
|
|
|
return dataset
|
|
|
|
|
|
|
|
|