def __init__(self, *args, **kwargs):
"""info is for information that is shared for a whole
tree, from vfile all the way down to fields
"""
super(Dataset, self).__init__(*args, **kwargs)
self.children = Bucket(ordered=True)
self.active_child = None
def __init__(self, *args, **kwargs):
super(Grid, self).__init__(*args, **kwargs)
self._fields = Bucket(ordered=True)
class Grid(tree.Node):
"""Computational grid container
Grids contain fields and coordinates. Datasets recurse to grids
using ``__getitem__`` and get_field in order to find fields. Grids
can also calculate fields by defining ``_get_*`` methods.
Attributes can be overridden globally to affect all data reads of
a given grid type. Subclasses of Grid document their own special
attributes. For example, one can change the default vector layout
with:
``viscid.grid.Grid.force_vector_layout = LAYOUT_INTERLACED``
Attributes:
force_vecter_layout (``field.LAYOUT_*``): force all vectors to
be of a certain layout when they're created
(default: LAYOUT_DEFAULT)
longterm_field_caches (bool): If True, then when a field is
cached, it must be explicitly removed from memory with
"clear_cache" or using the 'with' statemnt. If False,
"shell copies" of fields are made so that memory is freed
when the returned instance is garbage collected.
Default: False
"""
topology_info = None
geometry_info = None
_src_crds = None
_crds = None
fields = None
# so... not all grids have times? if we try to access time on a grid
# that doesnt have one, there is probably a bug somewhere
# time = None
# these attributes are intended to control how fields are read
# they can be customized by setting the class value, and inherited
# by grids that get created in the future
force_vector_layout = field.LAYOUT_DEFAULT
longterm_field_caches = False
def __init__(self, *args, **kwargs):
super(Grid, self).__init__(*args, **kwargs)
self._fields = Bucket(ordered=True)
@staticmethod
def null_transform(something):
return something
@property
def field_names(self):
return self._fields.get_primary_handles()
@property
def crds(self):
if self._src_crds is None:
for fld in self._fields.values():
fld_crds = fld.crds
if fld_crds is not None:
self._src_crds = fld_crds
if self._crds is None:
self._crds = self._src_crds.apply_reflections()
return self._crds
@crds.setter
def crds(self, val):
self._crds = None
self._src_crds = val
@property
def xl_nc(self):
return self.crds.xl_nc
@property
def xh_nc(self):
return self.crds.xh_nc
@property
def xl_cc(self):
return self.crds.xl_cc
@property
def xh_cc(self):
return self.crds.xh_cc
# def set_time(self, time):
# self.time = time
def set_crds(self, crds_object):
self.crds = crds_object
def add_field(self, *fields):
""" Note: in XDMF reader, the grid will NOT have crds when adding
fields, so any grid crd transforms won't be set
"""
for f in fields:
self[f.name] = f
def remove_all_items(self):
for fld in self._fields:
self.tear_down_child(fld)
self._fields = Bucket(ordered=True)
def clear_cache(self):
"""clear the cache on all child fields"""
for fld in self._fields:
fld.clear_cache()
def nr_times(self, *args, **kwargs): # pylint: disable=W0613,R0201
return 1
def iter_times(self, *args, **kwargs): # pylint: disable=W0613
# FIXME: it is unclear to me what to do here, since a dataset
# may have > 1 grid... and if so only the first will be returned...
# i guess there is some ambiguity if there is no temporal dataset...
with self as me:
yield me
def get_times(self, *args, **kwargs):
return list(self.iter_times(*args, **kwargs))
def get_time(self, *args, **kwargs):
return self.get_times(*args, **kwargs)[0]
def to_dataframe(self, fld_names=None, selection=Ellipsis,
time_sel=slice(None), time_col='time',
datetime_col='datetime'):
"""Consolidate grid's field data into pandas dataframe
Args:
fld_names (sequence, None): grab specific fields by name,
or None to grab all fields
selection (selection): for selecting only parts of fields
Returns:
pandas.DataFrame
"""
assert time_sel == slice(None)
import pandas
frame = pandas.DataFrame()
if fld_names is None:
fld_names = self.field_names
fld_list = list(self.iter_fields(fld_names=fld_names))
if fld_list:
fld0 = fld_list[0][selection]
# add coordinates as series
mesh = np.meshgrid(*fld0.get_crds(), indexing='ij')
for ax_name, ax_arr in zip(fld0.crds.axes, mesh):
frame[ax_name] = ax_arr.reshape(-1)
# add time as series
frame.insert(0, time_col, fld0.time)
try:
frame.insert(1, datetime_col, fld0.time_as_datetime64())
except viscid.NoBasetimeError:
pass
# add fields
for fld_name, fld in zip(fld_names, fld_list):
frame[fld_name] = fld[selection].data.reshape(-1)
return frame
def iter_fields(self, fld_names=None, **kwargs): # pylint: disable=W0613
""" iterate over fields in a grid, if fld_names is given, it should
be a list of field names to iterate over
"""
# Note: using 'with' here is better than making a shell copy
if fld_names is None:
fld_names = self.field_names
for name in fld_names:
with self._fields[name] as f:
yield f
def iter_field_items(self, fld_names=None, **kwargs): # pylint: disable=W0613
""" iterate over fields in a grid, if fld_names is given, it should
be a list of field names to iterate over
"""
# Note: using 'with' here is better than making a shell copy
if fld_names is None:
fld_names = self.field_names
for name in fld_names:
with self._fields[name] as f:
yield (name, f)
def field_dict(self, fld_names=None, **kwargs):
""" fields as dict of {name: field} """
return OrderedDict(list(self.iter_field_items(fld_names=fld_names)))
def print_tree(self, depth=-1, prefix=""): # pylint: disable=W0613
self._fields.print_tree(prefix=prefix + tree_prefix)
##################################
## Utility methods to get at crds
# these are the same as something like self._src_crds['xnc']
# or self._src_crds.get_crd()
def get_crd_nc(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_nc(axis, shaped=shaped)
def get_crd_cc(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_cc(axis, shaped=shaped)
def get_crd_ec(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_ec(axis, shaped=shaped)
def get_crd_fc(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_fc(axis, shaped=shaped)
## these return all crd dimensions
# these are the same as something like self._src_crds.get_crds()
def get_crds_nc(self, axes=None, shaped=False):
""" returns all node centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_nc(axes=axes, shaped=shaped)
def get_crds_cc(self, axes=None, shaped=False):
""" returns all cell centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_cc(axes=axes, shaped=shaped)
def get_crds_fc(self, axes=None, shaped=False):
""" returns all face centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_fc(axes=axes, shaped=shaped)
def get_crds_ec(self, axes=None, shaped=False):
""" returns all edge centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_ec(axes=axes, shaped=shaped)
##
def get_field(self, fldname, time=None, force_longterm_caches=False,
slc=Ellipsis): # pylint: disable=unused-argument
ret = None
try_final_slice = True
try:
if force_longterm_caches or self.longterm_field_caches:
ret = self._fields[fldname]
else:
ret = self._fields[fldname].shell_copy(force=False)
except KeyError:
func = "_get_" + fldname
if hasattr(self, func):
ret = getattr(self, func)()
elif len(fldname.split('=')) == 2:
result_name, eqn = (s.strip() for s in fldname.split('='))
ret = evaluate(self, result_name, eqn, slc=slc)
try_final_slice = False
else:
raise KeyError("field not found: {0}".format(fldname))
process_func = "_process_" + fldname
if hasattr(self, process_func):
ret = getattr(self, process_func)(ret)
if hasattr(self, "_processALL"):
ret = getattr(self, "_processALL")(ret)
if slc != Ellipsis and try_final_slice:
ret = ret.slice_and_keep(slc)
return ret
def get_grid(self, time=None): # pylint: disable=unused-argument
return self
def __contains__(self, item):
return item in self._fields
def __len__(self):
return len(self._fields)
def __getitem__(self, item):
""" returns a field by name, or if no field is found, a coordinate by
name some crd identifier, see Coordinate.get_item for details
"""
try:
return self.get_field(item)
except KeyError:
if self._src_crds is not None and item in self._src_crds:
return self._src_crds[item]
else:
raise KeyError(item)
def __setitem__(self, fldname, fld):
if isinstance(fld, field.VectorField):
fld.layout = self.force_vector_layout
self.prepare_child(fld)
self._fields[fldname] = fld
def __delitem__(self, fldname):
self.tear_down_child(self._fields[fldname])
self._fields.__delitem__(fldname)
def __str__(self):
return "<Grid name={0}>".format(self.name)
def __enter__(self):
return self
def __exit__(self, exc_type, value, traceback):
self.clear_cache()
return None
def remove_all_items(self):
for fld in self._fields:
self.tear_down_child(fld)
self._fields = Bucket(ordered=True)
def remove_all_items(self):
for child in self.children:
self.tear_down_child(child)
child.remove_all_items()
self.children = Bucket(ordered=True)
class Dataset(tree.Node):
"""Datasets contain grids or other datasets
Note:
Datasets should probably be created using a vfile's
`_make_dataset` to make sure the info dict is propogated
appropriately
It is the programmer's responsibility to ensure objects added to a AOEUIDH
dataset have __getitem__ and get_fields methods, this is not
enforced
"""
children = None # Bucket or (time, grid)
active_child = None
topology_info = None
geometry_info = None
crds = None
def __init__(self, *args, **kwargs):
"""info is for information that is shared for a whole
tree, from vfile all the way down to fields
"""
super(Dataset, self).__init__(**kwargs)
if self.children is None:
self.children = Bucket(ordered=True)
self.active_child = None
for arg in args:
self.add(arg)
def add(self, child, set_active=True):
self.prepare_child(child)
self.children[child.name] = child
if set_active:
self.active_child = child
def add_deferred(self, key, callback, callback_args=None,
callback_kwargs=None, set_active=True):
child = DeferredChild(callback, callback_args=callback_args,
callback_kwargs=callback_kwargs,
parent=self, name=key)
self.add(child, set_active=set_active)
def _clear_cache(self):
for child in self.children:
child.clear_cache()
def clear_cache(self):
"""Clear all childrens' caches"""
self._clear_cache()
def remove_all_items(self):
for child in self.children:
self.tear_down_child(child)
child.remove_all_items()
self.children = Bucket(ordered=True)
def activate(self, child_handle):
""" it may not look like it, but this will recursively look
in my active child for the handle because it uses getitem """
self.active_child = self.children[child_handle]
def activate_time(self, time):
""" this is basically 'activate' except it specifically picks out
temporal datasets, and does all children, not just the active child """
for child in self.children:
try:
child.activate_time(time)
except AttributeError:
pass
def nr_times(self, sel=slice(None), val_endpoint=True, interior=False,
tdunit='s', tol=100):
for child in self.children:
try:
return child.nr_times(sel=sel, val_endpoint=val_endpoint,
interior=interior, tdunit=tdunit, tol=tol)
except AttributeError:
pass
raise RuntimeError("I find no temporal datasets")
def iter_times(self, sel=slice(None), val_endpoint=True, interior=False,
tdunit='s', tol=100, resolved=True):
for child in self.iter_resolved_children():
try:
return child.iter_times(sel=sel, val_endpoint=val_endpoint,
interior=interior, tdunit=tdunit, tol=tol,
resolved=resolved)
except AttributeError:
pass
raise RuntimeError("I find no temporal datasets")
def tslc_range(self, sel=slice(None), tdunit='s'):
"""Find endpoints for a time slice selection
Note:
If the selection is slice-by-location, the values are not
adjusted to the nearest frame. For this functionality,
you will want to use :py:func:`get_times` and pull out the
first and last values.
"""
for child in self.children:
try:
return child.tslc_range(sel=sel, tdunit=tdunit)
except AttributeError:
pass
raise RuntimeError("I find no temporal datasets")
def get_times(self, sel=slice(None), val_endpoint=True, interior=False,
tdunit='s', tol=100):
return list(self.iter_times(sel=sel, val_endpoint=val_endpoint,
interior=interior, tdunit=tdunit, tol=tol,
resolved=False))
def get_time(self, sel=slice(None), val_endpoint=True, interior=False,
tdunit='s', tol=100):
try:
return next(self.iter_times(sel=sel, val_endpoint=val_endpoint,
interior=interior, tdunit=tdunit, tol=tol))
except StopIteration:
raise RuntimeError("Dataset has no time slices")
def to_dataframe(self, fld_names=None, selection=Ellipsis,
time_sel=slice(None), time_col='time',
datetime_col='datetime'):
"""Consolidate grid's field data into pandas dataframe
Args:
fld_names (sequence, None): grab specific fields by name,
or None to grab all fields
selection (selection): optional spatial selection
time (selection): optional time selection
Returns:
pandas.DataFrame
"""
# deferred import so that viscid does not depend on pandas
import pandas
frames = [child.to_dataframe(fld_names=fld_names, selection=selection,
time_sel=time_sel, time_col=time_col,
datetime_col=datetime_col)
for child in self.children]
frame = pandas.concat(frames, ignore_index=True, sort=False)
# make sure crds are all at the beginning, since concat can reorder them
col0 = list(frames[0].columns)
frame = frame[col0 + list(set(frame.columns) - set(col0))]
return frame
def iter_fields(self, time=None, fld_names=None):
""" generator for fields in the active dataset,
this will recurse down to a grid """
child = self.active_child
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.iter_fields(time=time, fld_names=fld_names)
def iter_field_items(self, time=None, fld_names=None):
""" generator for (name, field) in the active dataset,
this will recurse down to a grid """
child = self.active_child
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.iter_field_items(time=time, fld_names=fld_names)
def field_dict(self, time=None, fld_names=None, **kwargs):
""" fields as dict of {name: field} """
child = self.active_child
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.field_dict(time=time, fld_names=fld_names)
def print_tree(self, depth=-1, prefix=""):
if prefix == "":
print(self)
prefix += tree_prefix
for child in self.children:
suffix = ""
if child is self.active_child:
suffix = " <-- active"
print("{0}{1}{2}".format(prefix, child, suffix))
if depth != 0:
child.print_tree(depth=depth - 1, prefix=prefix + tree_prefix)
# def get_non_dataset(self):
# """ recurse down datasets until active_grid is not a subclass
# of Dataset """
# if isinstance(self.activate_grid, Dataset):
# return self.active_grid.get_non_dataset()
# else:
# return self.active_grid
def get_field(self, fldname, time=None, slc=Ellipsis):
""" recurse down active children to get a field """
child = self.active_child
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.get_field(fldname, time=time, slc=slc)
def get_grid(self, time=None):
""" recurse down active children to get a field """
child = self.active_child.resolve()
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.get_grid(time=time)
def get_child(self, item):
""" get a child from this Dataset, """
return self.children[item].resolve()
def __getitem__(self, item):
""" if a child exists with handle, return it, else ask
the active child if it knows what you want """
if item in self.children:
return self.get_child(item)
elif self.active_child is not None:
return self.active_child[item]
else:
raise KeyError()
def __delitem__(self, item):
# FIXME, is it possable to de-resolve item to a DeferredChild?
child = self.get_child(item)
child.clear_cache()
self.children.remove_item(child)
def __len__(self):
return self.children.__len__()
def __setitem__(self, name, child):
# um... is this kosher??
child.name = name
self.add(child)
def __contains__(self, item):
# FIXME, is it possable to de-resolve item to a DeferredChild?
if item in self.children:
return True
# FIXME: this might cause a bug somewhere someday
if item in self.active_child:
return True
return False
def __enter__(self):
return self
def __exit__(self, exc_type, value, traceback):
self.clear_cache()
return None
def __iter__(self):
return self.iter_resolved_children()
class Dataset(tree.Node):
"""Datasets contain grids or other datasets
Note:
Datasets should probably be created using a vfile's
`_make_dataset` to make sure the info dict is propogated
appropriately
It is the programmer's responsibility to ensure objects added to a AOEUIDH
dataset have __getitem__ and get_fields methods, this is not
enforced
"""
children = None # Bucket or (time, grid)
active_child = None
topology_info = None
geometry_info = None
crds = None
def __init__(self, *args, **kwargs):
"""info is for information that is shared for a whole
tree, from vfile all the way down to fields
"""
super(Dataset, self).__init__(*args, **kwargs)
self.children = Bucket(ordered=True)
self.active_child = None
def add(self, child, set_active=True):
self.prepare_child(child)
self.children[child.name] = child
if set_active:
self.active_child = child
def _clear_cache(self):
for child in self.children:
child.clear_cache()
def clear_cache(self):
"""Clear all childrens' caches"""
self._clear_cache()
def remove_all_items(self):
for child in self.children:
self.tear_down_child(child)
child.remove_all_items()
self.children = Bucket(ordered=True)
def activate(self, child_handle):
""" it may not look like it, but this will recursively look
in my active child for the handle because it uses getitem """
self.active_child = self.children[child_handle]
def activate_time(self, time):
""" this is basically 'activate' except it specifically picks out
temporal datasets, and does all children, not just the active child """
for child in self.children:
try:
child.activate_time(time)
except AttributeError:
pass
def nr_times(self, slice_str=":"):
for child in self.children:
try:
return child.nr_times(slice_str)
except AttributeError:
pass
raise RuntimeError("I find no temporal datasets")
def iter_times(self, slice_str=":"):
for child in self.children:
try:
return child.iter_times(slice_str)
except AttributeError:
pass
raise RuntimeError("I find no temporal datasets")
def get_times(self, slice_str=":"):
return list(self.iter_times(slice_str=slice_str))
def get_time(self, slice_str=":"):
try:
return next(self.iter_times(slice_str))
except StopIteration:
raise RuntimeError("Dataset has no time slices")
def iter_fields(self, time=None, named=None):
""" generator for fields in the active dataset,
this will recurse down to a grid """
child = self.active_child
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.iter_fields(time=time, named=named)
def print_tree(self, depth=-1, prefix=""):
if prefix == "":
print(self)
prefix += tree_prefix
for child in self.children:
suffix = ""
if child is self.active_child:
suffix = " <-- active"
print("{0}{1}{2}".format(prefix, child, suffix))
if depth != 0:
child.print_tree(depth=depth - 1, prefix=prefix + tree_prefix)
# def get_non_dataset(self):
# """ recurse down datasets until active_grid is not a subclass
# of Dataset """
# if isinstance(self.activate_grid, Dataset):
# return self.active_grid.get_non_dataset()
# else:
# return self.active_grid
def get_field(self, fldname, time=None, slc=None):
""" recurse down active children to get a field """
child = self.active_child
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.get_field(fldname, time=time, slc=slc)
def get_grid(self, time=None):
""" recurse down active children to get a field """
child = self.active_child
if child is None:
logger.error("Could not get appropriate child...")
return None
else:
return child.get_grid(time=time)
def get_child(self, item):
""" get a child from this Dataset, """
return self.children[item]
def __getitem__(self, item):
""" if a child exists with handle, return it, else ask
the active child if it knows what you want """
if item in self.children:
return self.get_child(item)
elif self.active_child is not None:
return self.active_child[item]
else:
raise KeyError()
def __delitem__(self, item):
child = self.get_child(item)
child.clear_cache()
self.children.remove_item(child)
def __len__(self):
return self.children.__len__()
def __setitem__(self, name, child):
# um... is this kosher??
child.name = name
self.add(child)
def __contains__(self, item):
if item in self.children:
return True
# FIXME: this might cause a bug somewhere someday
if item in self.active_child:
return True
return False
def __enter__(self):
return self
def __exit__(self, exc_type, value, traceback):
self.clear_cache()
return None
def __iter__(self):
return self.children.__iter__()
def __init__(self, *args, **kwargs):
super(Grid, self).__init__(*args, **kwargs)
self._fields = Bucket(ordered=True)
class Grid(tree.Node):
"""Computational grid container
Grids contain fields and coordinates. Datasets recurse to grids
using ``__getitem__`` and get_field in order to find fields. Grids
can also calculate fields by defining ``_get_*`` methods.
Attributes can be overridden globally to affect all data reads of
a given grid type. Subclasses of Grid document their own special
attributes. For example, one can change the default vector layout
with:
``viscid.grid.Grid.force_vector_layout = LAYOUT_INTERLACED``
Attributes:
force_vecter_layout (``field.LAYOUT_*``): force all vectors to
be of a certain layout when they're created
(default: LAYOUT_DEFAULT)
longterm_field_caches (bool): If True, then when a field is
cached, it must be explicitly removed from memory with
"clear_cache" or using the 'with' statemnt. If False,
"shell copies" of fields are made so that memory is freed
when the returned instance is garbage collected.
Default: False
"""
topology_info = None
geometry_info = None
_src_crds = None
_crds = None
fields = None
# so... not all grids have times? if we try to access time on a grid
# that doesnt have one, there is probably a bug somewhere
# time = None
# these attributes are intended to control how fields are read
# they can be customized by setting the class value, and inherited
# by grids that get created in the future
force_vector_layout = field.LAYOUT_DEFAULT
longterm_field_caches = False
def __init__(self, *args, **kwargs):
super(Grid, self).__init__(*args, **kwargs)
self._fields = Bucket(ordered=True)
@staticmethod
def null_transform(something):
return something
@property
def field_names(self):
return self._fields.get_primary_handles()
@property
def crds(self):
if self._src_crds is None:
for fld in self._fields.values():
fld_crds = fld.crds
if fld_crds is not None:
self._src_crds = fld_crds
if self._crds is None:
self._crds = self._src_crds.apply_reflections()
return self._crds
@crds.setter
def crds(self, val):
self._crds = None
self._src_crds = val
@property
def xl_nc(self):
return self.crds.xl_nc
@property
def xh_nc(self):
return self.crds.xh_nc
@property
def xl_cc(self):
return self.crds.xl_cc
@property
def xh_cc(self):
return self.crds.xh_cc
# def set_time(self, time):
# self.time = time
def set_crds(self, crds_object):
self.crds = crds_object
def add_field(self, *fields):
""" Note: in XDMF reader, the grid will NOT have crds when adding
fields, so any grid crd transforms won't be set
"""
for f in fields:
self[f.name] = f
def remove_all_items(self):
for fld in self._fields:
self.tear_down_child(fld)
self._fields = Bucket(ordered=True)
def clear_cache(self):
"""clear the cache on all child fields"""
for fld in self._fields:
fld.clear_cache()
def nr_times(self, *args, **kwargs): # pylint: disable=W0613,R0201
return 1
def iter_times(self, *args, **kwargs): # pylint: disable=W0613
# FIXME: it is unclear to me what to do here, since a dataset
# may have > 1 grid... and if so only the first will be returned...
# i guess there is some ambiguity if there is no temporal dataset...
with self as me:
yield me
def get_times(self, *args, **kwargs):
return list(self.iter_times(*args, **kwargs))
def get_time(self, *args, **kwargs):
return self.get_times(*args, **kwargs)[0]
def to_dataframe(self,
fld_names=None,
selection=Ellipsis,
time_sel=slice(None),
time_col='time',
datetime_col='datetime'):
"""Consolidate grid's field data into pandas dataframe
Args:
fld_names (sequence, None): grab specific fields by name,
or None to grab all fields
selection (selection): for selecting only parts of fields
Returns:
pandas.DataFrame
"""
assert time_sel == slice(None)
import pandas
frame = pandas.DataFrame()
if fld_names is None:
fld_names = self.field_names
fld_list = list(self.iter_fields(fld_names=fld_names))
if fld_list:
fld0 = fld_list[0][selection]
# add coordinates as series
mesh = np.meshgrid(*fld0.get_crds(), indexing='ij')
for ax_name, ax_arr in zip(fld0.crds.axes, mesh):
frame[ax_name] = ax_arr.reshape(-1)
# add time as series
frame.insert(0, time_col, fld0.time)
try:
frame.insert(1, datetime_col, fld0.time_as_datetime64())
except viscid.NoBasetimeError:
pass
# add fields
for fld_name, fld in zip(fld_names, fld_list):
frame[fld_name] = fld[selection].data.reshape(-1)
return frame
def iter_fields(self, fld_names=None, **kwargs): # pylint: disable=W0613
""" iterate over fields in a grid, if fld_names is given, it should
be a list of field names to iterate over
"""
# Note: using 'with' here is better than making a shell copy
if fld_names is None:
fld_names = self.field_names
for name in fld_names:
with self._fields[name] as f:
yield f
def iter_field_items(self, fld_names=None, **kwargs): # pylint: disable=W0613
""" iterate over fields in a grid, if fld_names is given, it should
be a list of field names to iterate over
"""
# Note: using 'with' here is better than making a shell copy
if fld_names is None:
fld_names = self.field_names
for name in fld_names:
with self._fields[name] as f:
yield (name, f)
def field_dict(self, fld_names=None, **kwargs):
""" fields as dict of {name: field} """
return OrderedDict(list(self.iter_field_items(fld_names=fld_names)))
def print_tree(self, depth=-1, prefix=""): # pylint: disable=W0613
self._fields.print_tree(prefix=prefix + tree_prefix)
##################################
## Utility methods to get at crds
# these are the same as something like self._src_crds['xnc']
# or self._src_crds.get_crd()
def get_crd_nc(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_nc(axis, shaped=shaped)
def get_crd_cc(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_cc(axis, shaped=shaped)
def get_crd_ec(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_ec(axis, shaped=shaped)
def get_crd_fc(self, axis, shaped=False):
""" returns a flat ndarray of coordinates along a given axis
axis can be crd name as string, or index, as in x==2, y==1, z==2
"""
return self._src_crds.get_fc(axis, shaped=shaped)
## these return all crd dimensions
# these are the same as something like self._src_crds.get_crds()
def get_crds_nc(self, axes=None, shaped=False):
""" returns all node centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_nc(axes=axes, shaped=shaped)
def get_crds_cc(self, axes=None, shaped=False):
""" returns all cell centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_cc(axes=axes, shaped=shaped)
def get_crds_fc(self, axes=None, shaped=False):
""" returns all face centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_fc(axes=axes, shaped=shaped)
def get_crds_ec(self, axes=None, shaped=False):
""" returns all edge centered coords as a list of ndarrays, flat if
shaped==False, or shaped if shaped==True
"""
return self._src_crds.get_crds_ec(axes=axes, shaped=shaped)
##
def get_field(self,
fldname,
time=None,
force_longterm_caches=False,
slc=Ellipsis): # pylint: disable=unused-argument
ret = None
try_final_slice = True
try:
if force_longterm_caches or self.longterm_field_caches:
ret = self._fields[fldname]
else:
ret = self._fields[fldname].shell_copy(force=False)
except KeyError:
func = "_get_" + fldname
if hasattr(self, func):
ret = getattr(self, func)()
elif len(fldname.split('=')) == 2:
result_name, eqn = (s.strip() for s in fldname.split('='))
ret = evaluate(self, result_name, eqn, slc=slc)
try_final_slice = False
else:
raise KeyError("field not found: {0}".format(fldname))
process_func = "_process_" + fldname
if hasattr(self, process_func):
ret = getattr(self, process_func)(ret)
if hasattr(self, "_processALL"):
ret = getattr(self, "_processALL")(ret)
if slc != Ellipsis and try_final_slice:
ret = ret.slice_and_keep(slc)
return ret
def get_grid(self, time=None): # pylint: disable=unused-argument
return self
def __contains__(self, item):
return item in self._fields
def __len__(self):
return len(self._fields)
def __getitem__(self, item):
""" returns a field by name, or if no field is found, a coordinate by
name some crd identifier, see Coordinate.get_item for details
"""
try:
return self.get_field(item)
except KeyError:
if self._src_crds is not None and item in self._src_crds:
return self._src_crds[item]
else:
raise KeyError(item)
def __setitem__(self, fldname, fld):
if isinstance(fld, field.VectorField):
fld.layout = self.force_vector_layout
self.prepare_child(fld)
self._fields[fldname] = fld
def __delitem__(self, fldname):
self.tear_down_child(self._fields[fldname])
self._fields.__delitem__(fldname)
def __str__(self):
return "<Grid name={0}>".format(self.name)
def __enter__(self):
return self
def __exit__(self, exc_type, value, traceback):
self.clear_cache()
return None
def remove_all_items(self):
for fld in self._fields:
self.tear_down_child(fld)
self._fields = Bucket(ordered=True)
