def make_block_iterator(data, first=False):
if not data.vardata: # only x-values
sweepvars = ()
head = data.ivardata.keys()[0]
dim = data.ivardata[head]
header = [
head,
]
fmts = (data[head].outputformat, )
columns = (hfarray(dim), )
blockname = data.blockname
comments = data.comments
yield (sweepvars, header, fmts, columns, blockname, comments)
raise StopIteration
d = data.vardata.values()[0]
if ismatrix(d):
dimsnames = [x.name for x in d.dims[:-2]]
else:
dimsnames = [x.name for x in d.dims]
dimsdata = [hfarray(data.ivardata[iname]) for iname in dimsnames]
dimsidx = [range(x.shape[0]) for x in dimsdata]
if first:
if data.comments:
comments = data.comments.copy()
comments.property.clear()
else:
comments = Comments()
else:
comments = Comments()
for enum, idx in enumerate(itertools.product(*dimsidx[1:])):
sweepvars = []
for iname, dim, i in zip(dimsnames[1:], dimsdata[1:], idx):
fmt = getattr(dim, "outputformat", "%.16e")
sweepvars.append((iname, fmt, dim[i]))
if dimsnames:
header = [dimsnames[0]] + data.vardata.keys()
columns = dimsdata[:1] + [
col[(slice(None), ) + idx] for col in data.vardata.values()
]
fmts = [getattr(x, "outputformat", "%.16e") for x in columns]
else:
header = []
columns = []
fmts = []
for k, v in data.vardata.items():
if v.dims == tuple():
comments.property[k] = v
if enum:
comments = Comments()
yield (sweepvars, header, fmts, columns, data.blockname, comments)
def make_block_iterator(data, first=False):
if not data.vardata: # only x-values
sweepvars = ()
head = data.ivardata.keys()[0]
dim = data.ivardata[head]
header = [head, ]
fmts = (data[head].outputformat,)
columns = (hfarray(dim),)
blockname = data.blockname
comments = data.comments
yield (sweepvars, header, fmts, columns,
blockname, comments)
raise StopIteration
d = data.vardata.values()[0]
if ismatrix(d):
dimsnames = [x.name for x in d.dims[:-2]]
else:
dimsnames = [x.name for x in d.dims]
dimsdata = [hfarray(data.ivardata[iname]) for iname in dimsnames]
dimsidx = [range(x.shape[0]) for x in dimsdata]
if first:
if data.comments:
comments = data.comments.copy()
comments.property.clear()
else:
comments = Comments()
else:
comments = Comments()
for enum, idx in enumerate(itertools.product(*dimsidx[1:])):
sweepvars = []
for iname, dim, i in zip(dimsnames[1:], dimsdata[1:], idx):
fmt = getattr(dim, "outputformat", "%.16e")
sweepvars.append((iname, fmt, dim[i]))
if dimsnames:
header = [dimsnames[0]] + data.vardata.keys()
columns = dimsdata[:1] + [col[(slice(None), ) + idx]
for col in data.vardata.values()]
fmts = [getattr(x, "outputformat", "%.16e") for x in columns]
else:
header = []
columns = []
fmts = []
for k, v in data.vardata.items():
if v.dims == tuple():
comments.property[k] = v
if enum:
comments = Comments()
yield (sweepvars, header, fmts, columns,
data.blockname, comments)
def db_iterator(indb, fmt_block_generator):
datablock = {}
used_ivars = set()
for vname in indb.vardata.keys():
if ismatrix(indb.vardata[vname]):
dimsnames = get_dims_names(*indb[vname].dims)[:-2]
names = get_dims_names(*indb[vname].dims)[-2:]
used_ivars = used_ivars.union(names)
else:
dimsnames = get_dims_names(*indb[vname].dims)
q = datablock.setdefault(dimsnames, DataBlock())
if q.comments is None:
q.comments = indb.comments
q[vname] = indb[vname]
q[vname].outputformat = indb[vname].outputformat
#
#Collect dangling ivars
#
for names in datablock.keys():
used_ivars = used_ivars.union(names)
for vname in set(indb.ivardata).difference(used_ivars):
q = datablock.setdefault((vname,), DataBlock())
if q.comments is None:
q.comments = Comments()
q[vname] = indb.ivardata[vname]
first = True
#Handle block with scalar data first
dbs = []
if tuple() in datablock:
dbs.append(datablock.pop(tuple()))
for v in datablock.values():
dbs.append(v)
for db in dbs:
for block_content in make_block_iterator(db, first):
if first:
first = False
else:
yield []
for rad in fmt_block_generator(*block_content):
yield rad
def make_col_from_matrix(header, columns, fmt_matrix, fortranorder=False):
fullheader = []
fullcolumns = []
for colname, col in zip(header, columns):
if ismatrix(col):
for i in range(col.dims[-2].data.shape[0]):
for j in range(col.dims[-1].data.shape[0]):
if fortranorder:
I, J = j, i
else:
I, J = i, j
fullheader.append(fmt_matrix % (colname, I + 1, J + 1))
fullcolumns.append(col[..., I, J])
else:
fullheader.append(colname)
fullcolumns.append(col)
return fullheader, fullcolumns
def db_iterator(indb, fmt_block_generator):
datablock = {}
used_ivars = set()
for vname in indb.vardata.keys():
if ismatrix(indb.vardata[vname]):
dimsnames = get_dims_names(*indb[vname].dims)[:-2]
names = get_dims_names(*indb[vname].dims)[-2:]
used_ivars = used_ivars.union(names)
else:
dimsnames = get_dims_names(*indb[vname].dims)
q = datablock.setdefault(dimsnames, DataBlock())
if q.comments is None:
q.comments = indb.comments
q[vname] = indb[vname]
q[vname].outputformat = indb[vname].outputformat
#
#Collect dangling ivars
#
for names in datablock.keys():
used_ivars = used_ivars.union(names)
for vname in set(indb.ivardata).difference(used_ivars):
q = datablock.setdefault((vname, ), DataBlock())
if q.comments is None:
q.comments = Comments()
q[vname] = indb.ivardata[vname]
first = True
#Handle block with scalar data first
dbs = []
if tuple() in datablock:
dbs.append(datablock.pop(tuple()))
for v in datablock.values():
dbs.append(v)
for db in dbs:
for block_content in make_block_iterator(db, first):
if first:
first = False
else:
yield []
for rad in fmt_block_generator(*block_content):
yield rad
def make_col_from_matrix(header, columns, fmt_matrix, fortranorder=False):
fullheader = []
fullcolumns = []
for colname, col in zip(header, columns):
if ismatrix(col):
for i in range(col.dims[-2].data.shape[0]):
for j in range(col.dims[-1].data.shape[0]):
if fortranorder:
I, J = j, i
else:
I, J = i, j
fullheader.append(fmt_matrix % (colname, I + 1, J + 1))
fullcolumns.append(col[..., I, J])
else:
fullheader.append(colname)
fullcolumns.append(col)
return fullheader, fullcolumns
