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Copy pathproject.py
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executable file
·2680 lines (2313 loc) · 97.7 KB
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"""Project module of the psyplot Package
This module contains the :class:`Project` class that serves as the main
part of the psyplot API. One instance of the :class:`Project` class serves as
coordinator of multiple plots and can be distributed into subprojects that
keep reference to the main project without holding all array instances
Furthermore this module contains an easy pyplot-like API to the current
subproject."""
import os
import os.path as osp
import yaml
import sys
import six
from copy import deepcopy as _deepcopy
import logging
import inspect
import pickle
from importlib import import_module
from itertools import chain, repeat, cycle, count, islice
from collections import defaultdict
from functools import wraps, partial
import xarray
import pandas as pd
import matplotlib as mpl
import matplotlib.figure as mfig
import numpy as np
import psyplot
from psyplot import rcParams, get_versions
import psyplot.utils as utils
from psyplot.config.rcsetup import get_configdir
from psyplot.warning import warn, critical
from psyplot.docstring import docstrings, dedent, safe_modulo
import psyplot.data as psyd
from psyplot.data import (
ArrayList, open_dataset, open_mfdataset, _MissingModule,
to_netcdf, Signal, CFDecoder, safe_list, InteractiveList)
from psyplot.plotter import unique_everseen, Plotter
from psyplot.compat.pycompat import (OrderedDict, range, getcwd,
get_default_value as _get_default_value)
try:
from cdo import Cdo as _CdoBase, CDO_PY_VERSION as cdo_version
with_cdo = True
cdo_version = tuple(map(int, cdo_version.split('.')[:2]))
except ImportError as e:
Cdo = _MissingModule(e)
with_cdo = False
cdo_version = None
try: # try import show_colormaps for convenience
from psy_simple.colors import show_colormaps, get_cmap
except ImportError:
pass
if rcParams['project.import_seaborn'] is not False:
try:
import seaborn as _sns
except ImportError as e:
if rcParams['project.import_seaborn']:
raise
_sns = _MissingModule(e)
_open_projects = [] # list of open projects
_current_project = None # current main project
_current_subproject = None # current subproject
# the informations on the psyplot and plugin versions
_versions = get_versions(requirements=False)
_concat_dim_default = _get_default_value(xarray.open_mfdataset, 'concat_dim')
def _update_versions():
"""Update :attr:`_versions` with the registered plotter methods"""
for pm_name in plot._plot_methods:
pm = getattr(plot, pm_name)
plugin = pm._plugin
if (plugin is not None and plugin not in _versions and
pm.module in sys.modules):
_versions.update(get_versions(key=lambda s: s == plugin))
@docstrings.get_sectionsf('multiple_subplots')
@docstrings.dedent
def multiple_subplots(rows=1, cols=1, maxplots=None, n=1, delete=True,
for_maps=False, *args, **kwargs):
"""
Function to create subplots.
This function creates so many subplots on so many figures until the
specified number `n` is reached.
Parameters
----------
rows: int
The number of subplots per rows
cols: int
The number of subplots per column
maxplots: int
The number of subplots per figure (if None, it will be row*cols)
n: int
number of subplots to create
delete: bool
If True, the additional subplots per figure are deleted
for_maps: bool
If True this is a simple shortcut for setting
``subplot_kw=dict(projection=cartopy.crs.PlateCarree())`` and is
useful if you want to use the :attr:`~ProjectPlotter.mapplot`,
:attr:`~ProjectPlotter.mapvector` or
:attr:`~ProjectPlotter.mapcombined` plotting methods
``*args`` and ``**kwargs``
anything that is passed to the :func:`matplotlib.pyplot.subplots`
function
Returns
-------
list
list of maplotlib.axes.SubplotBase instances"""
import matplotlib.pyplot as plt
axes = np.array([])
maxplots = maxplots or rows * cols
kwargs.setdefault('figsize', [
min(8.*cols, 16), min(6.5*rows, 12)])
if for_maps:
import cartopy.crs as ccrs
subplot_kw = kwargs.setdefault('subplot_kw', {})
subplot_kw['projection'] = ccrs.PlateCarree()
for i in range(0, n, maxplots):
fig, ax = plt.subplots(rows, cols, *args, **kwargs)
try:
axes = np.append(axes, ax.ravel()[:maxplots])
if delete:
for iax in range(maxplots, rows * cols):
fig.delaxes(ax.ravel()[iax])
except AttributeError: # got a single subplot
axes = np.append(axes, [ax])
if i + maxplots > n and delete:
for ax2 in axes[n:]:
fig.delaxes(ax2)
axes = axes[:n]
return axes
def _is_slice(val):
return isinstance(val, slice)
def _only_main(func):
"""Call the given `func` only from the main project"""
@wraps(func)
def wrapper(self, *args, **kwargs):
if not self.is_main:
return getattr(self.main, func.__name__)(*args, **kwargs)
return func(self, *args, **kwargs)
return wrapper
def _first_main(func):
"""Call the given `func` with the same arguments but after the function
of the main project"""
@wraps(func)
def wrapper(self, *args, **kwargs):
if not self.is_main:
getattr(self.main, func.__name__)(*args, **kwargs)
return func(self, *args, **kwargs)
return wrapper
class Project(ArrayList):
"""A manager of multiple interactive data projects"""
_main = None
_registered_plotters = {} #: registered plotter identifiers
#: signal to be emiitted when the current main and/or subproject changes
oncpchange = Signal(name='oncpchange', cls_signal=True)
# block the signals of this class
block_signals = utils._TempBool()
@property
def main(self):
""":class:`Project`. The main project of this subproject"""
return self._main if self._main is not None else self
@main.setter
def main(self, value):
self._main = value
@property
@dedent
def plot(self):
"""
Plotting instance of this :class:`Project`. See the
:class:`ProjectPlotter` class for method documentations"""
return self._plot
@property
def _fmtos(self):
"""An iterator over formatoption objects
Contains only the formatoption whose keys are in all plotters in this
list"""
plotters = self.plotters
if len(plotters) == 0:
return {}
p0 = plotters[0]
if len(plotters) == 1:
return p0._fmtos
return (getattr(p0, key) for key in set(p0).intersection(
*map(set, plotters[1:])))
@property
def is_csp(self):
"""Boolean that is True if the project is the current subproject"""
return self is _current_subproject
@property
def is_cmp(self):
"""Boolean that is True if the project is the current main project"""
return self is _current_project
@property
def figs(self):
"""A mapping from figures to data objects with the plotter in this
figure"""
ret = utils.DefaultOrderedDict(lambda: self[1:0])
for arr in self:
if arr.psy.plotter is not None:
ret[arr.psy.plotter.ax.get_figure()].append(arr)
return OrderedDict(ret)
@property
def axes(self):
"""A mapping from axes to data objects with the plotter in this axes
"""
ret = utils.DefaultOrderedDict(lambda: self[1:0])
for arr in self:
if arr.psy.plotter is not None:
ret[arr.psy.plotter.ax].append(arr)
return OrderedDict(ret)
@property
def is_main(self):
""":class:`bool`. True if this :class:`Project` is a main project"""
return self._main is None
@property
def logger(self):
""":class:`logging.Logger` of this instance"""
if not self.is_main:
return self.main.logger
try:
return self._logger
except AttributeError:
name = '%s.%s.%s' % (self.__module__, self.__class__.__name__,
self.num)
self._logger = logging.getLogger(name)
self.logger.debug('Initializing...')
return self._logger
@logger.setter
def logger(self, value):
self._logger = value
def with_plotter(self):
ret = super(Project, self).with_plotter
ret.main = self.main
return ret
with_plotter = property(with_plotter, doc=ArrayList.with_plotter.__doc__)
@property
def arr_names(self):
"""Names of the arrays (!not of the variables!) in this list
This attribute can be set with an iterable of unique names to change
the array names of the data objects in this list."""
return list(arr.psy.arr_name for arr in self)
@arr_names.setter
def arr_names(self, value):
value = list(islice(value, len(self)))
if not len(set(value)) == len(self):
raise ValueError(
"Got %i unique array names for %i data objects!" % (
len(set(value)), len(self)))
elif not self.is_main and set(value) & (
set(self.main.arr_names) - set(self.arr_names)):
raise ValueError(
"Cannot rename arrays because there are duplicates with the "
"main project: %s" % (
set(value) & (
set(self.main.arr_names) - set(self.arr_names)), ))
for arr, n in zip(self, value):
arr.psy.arr_name = n
if self.main is gcp(True):
for arr in self:
arr.psy.onupdate.emit()
@property
def plotters(self):
"""A list of all the plotters in this instance"""
return [arr.psy.plotter for arr in self.with_plotter]
@property
def datasets(self):
"""A mapping from dataset numbers to datasets in this list"""
return {key: val['ds'] for key, val in six.iteritems(
self._get_ds_descriptions(self.array_info(ds_description=['ds'])))}
@property
def dsnames_map(self):
"""A dictionary from the dataset numbers in this list to their
filenames"""
return {key: val['fname'] for key, val in six.iteritems(
self._get_ds_descriptions(self.array_info(
ds_description=['num', 'fname']), ds_description={'fname'}))}
@property
def dsnames(self):
"""The set of dataset names in this instance"""
return {t[0] for t in self._get_dsnames(self.array_info()) if t[0]}
@docstrings.get_sectionsf('Project')
@docstrings.dedent
def __init__(self, *args, **kwargs):
"""
Parameters
----------
%(ArrayList.parameters)s
main: Project
The main project this subproject belongs to (or None if this
project is the main project)
num: int
The number of the project
"""
self.main = kwargs.pop('main', None)
self._plot = ProjectPlotter(self)
self.num = kwargs.pop('num', 1)
self._ds_counter = count()
with self.block_signals:
super(Project, self).__init__(*args, **kwargs)
@classmethod
@docstrings.get_sectionsf('Project._register_plotter')
@dedent
def _register_plotter(cls, identifier, module, plotter_name,
plotter_cls=None):
"""
Register a plotter in the :class:`Project` class to easy access it
Parameters
----------
identifier: str
Name of the attribute that is used to filter for the instances
belonging to this plotter
module: str
The module from where to import the `plotter_name`
plotter_name: str
The name of the plotter class in `module`
plotter_cls: type
The imported class of `plotter_name`. If None, it will be imported
when it is needed
"""
if plotter_cls is not None: # plotter has already been imported
def get_x(self):
return self(plotter_cls)
else:
def get_x(self):
return self(getattr(import_module(module), plotter_name))
setattr(cls, identifier, property(get_x, doc=(
"List of data arrays that are plotted by :class:`%s.%s`"
" plotters") % (module, plotter_name)))
cls._registered_plotters[identifier] = (module, plotter_name)
def disable(self):
"""Disables the plotters in this list"""
for arr in self:
if arr.psy.plotter:
arr.psy.plotter.disabled = True
def enable(self):
for arr in self:
if arr.psy.plotter:
arr.psy.plotter.disabled = False
def __call__(self, *args, **kwargs):
ret = super(Project, self).__call__(*args, **kwargs)
ret.main = self.main
return ret
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.close(True, True, True)
@staticmethod
@docstrings.get_sectionsf('Project._load_preset',
sections=["Parameters", "Notes"])
def _load_preset(preset: str):
"""Load a preset from disk
Parameters
----------
preset: str or dict
The filename or identifier of a preset. If the given `preset` is
the path to an existing yaml file, it will be loaded. Otherwise we
look up the `preset` in the psyplot configuration directory (see
:func:`~psyplot.config.rcsetup.get_configdir`).
If a dictionary is provided, we assume that this is the preset
Returns
-------
dict
The loaded preset
Notes
-----
An identifier is the filename without extension. If you want to list
the available presets, run ``psyplot -lp`` from the command-line"""
if isinstance(preset, dict):
config = preset
else:
path = Project._resolve_preset_path(preset)
with open(path) as f:
config = yaml.load(f, yaml.Loader)
return config
@staticmethod
def _resolve_preset_path(preset, if_exists=True):
if osp.exists(preset):
return preset
else:
confdir = get_configdir()
presets_dir = osp.join(confdir, 'presets')
if osp.exists(osp.join(presets_dir, preset)):
return osp.join(presets_dir, preset)
elif osp.exists(osp.join(presets_dir, preset + '.yml')):
return osp.exists(osp.join(presets_dir, preset + '.yml'))
else:
if if_exists:
raise ValueError(
f"Could not find a preset with name {preset}")
else:
if not preset.endswith('.yml'):
return osp.join(presets_dir, preset + '.yml')
return preset
@docstrings.dedent
def load_preset(self, preset: str, **kwargs):
"""Load a preset from disk and apply it to the open project.
This method loads a preset and updates the corresponding plots
Parameters
----------
%(Project._load_preset.parameters)s
``**kwargs``
Any other parameter that shall be passed to the
:meth:`~psyplot.data.ArrayList.update` method
Notes
-----
%(Project._load_preset.notes)s
"""
config = self._load_preset(preset)
plotmethods = self.plot._plot_methods
pm_config, defaults = utils.sort_kwargs(config, plotmethods)
with self.no_auto_update:
for pm in plotmethods:
method = getattr(self.plot, pm)
if method.is_imported:
sp = getattr(self, pm)
if sp:
valid = method.plotter_cls._get_formatoptions()
fmts = {key: val for key, val in defaults.items()
if key in valid}
fmts.update(pm_config.get(pm, {}))
sp.update(fmt=fmts, **kwargs)
self.start_update()
def save_preset(self, fname=None, include_defaults=False, update=False):
"""Save the formatoptions of this project as a preset
This method takes the formatoptions in the plotters of this project and
saves it as a preset file"""
def include(fmto, plotters):
key = fmto.key
for plotter in plotters:
if fmto.diff(plotter[key]):
return False
return True if include_defaults else fmto.changed
if update:
with open(f) as f:
preset = yaml.load(f, yaml.Loader)
else:
preset = {}
plotters = self.plotters
for fmto in self._fmtos:
if include(fmto, plotters):
preset[fmto.key] = fmto.value
for pm in self.plot._plot_methods:
method = getattr(self.plot, pm)
if method.is_imported:
sp = getattr(self, pm)
plotters = sp.plotters
for fmto in sp._fmtos:
if fmto.key not in preset and include(fmto, plotters):
preset.setdefault(pm, {})
preset[pm][fmto.key] = fmto.value
if fname is not None:
fname = self._resolve_preset_path(fname, False)
os.makedirs(osp.dirname(fname))
with open(fname, 'w') as f:
yaml.dump(preset, f)
else:
return preset
@_first_main
def extend(self, *args, **kwargs):
len0 = len(self)
ret = super(Project, self).extend(*args, **kwargs)
if self._main is None:
for arr in self:
if arr.psy.plotter is not None:
arr.psy.plotter._project = self
if len(self) > len0 and (self.is_csp or self.is_cmp):
self.oncpchange.emit(self)
return ret
extend.__doc__ = ArrayList.extend.__doc__
@_first_main
def append(self, *args, **kwargs):
len0 = len(self)
ret = super(Project, self).append(*args, **kwargs)
if self._main is None:
for arr in self:
if arr.psy.plotter is not None:
arr.psy.plotter._project = self
if len(self) > len0 and (self.is_csp or self.is_cmp):
self.oncpchange.emit(self)
return ret
append.__doc__ = ArrayList.append.__doc__
__call__.__doc__ = ArrayList.__call__.__doc__
@docstrings.get_sectionsf('Project.close')
@dedent
def close(self, figs=True, data=False, ds=False, remove_only=False):
"""
Close this project instance
Parameters
----------
figs: bool
Close the figures
data: bool
delete the arrays from the (main) project
ds: bool
If True, close the dataset as well
remove_only: bool
If True and `figs` is True, the figures are not closed but the
plotters are removed"""
import matplotlib.pyplot as plt
close_ds = ds
for arr in self[:]:
if figs and arr.psy.plotter is not None:
if remove_only:
for fmto in arr.psy.plotter._fmtos:
try:
fmto.remove()
except Exception:
pass
else:
plt.close(arr.psy.plotter.ax.get_figure().number)
arr.psy.plotter = None
if data:
self.remove(arr)
if not self.is_main:
try:
self.main.remove(arr)
except ValueError: # arr not in list
pass
if close_ds:
if isinstance(arr, InteractiveList):
for ds in [val['ds'] for val in six.itervalues(
arr._get_ds_descriptions(
arr.array_info(ds_description=['ds'],
standardize_dims=False)))]:
ds.close()
else:
arr.psy.base.close()
if self.is_main and self is gcp(True) and data:
scp(None)
elif self.is_main and self.is_cmp:
self.oncpchange.emit(self)
elif self.main.is_cmp:
self.oncpchange.emit(self.main)
docstrings.keep_params('multiple_subplots.parameters', 'delete')
docstrings.delete_params('ArrayList.from_dataset.parameters', 'base')
docstrings.delete_kwargs('ArrayList.from_dataset.other_parameters',
kwargs='kwargs')
docstrings.keep_params('xarray.open_mfdataset.parameters', 'concat_dim')
@_only_main
@docstrings.get_sectionsf('Project._add_data',
sections=['Parameters', 'Other Parameters',
'Returns'])
@docstrings.dedent
def _add_data(self, plotter_cls, filename_or_obj, fmt={}, make_plot=True,
draw=False, mf_mode=False, ax=None, engine=None, delete=True,
share=False, clear=False, enable_post=None,
concat_dim=_concat_dim_default, load=False,
*args, **kwargs):
"""
Extract data from a dataset and visualize it with the given plotter
Parameters
----------
plotter_cls: type
The subclass of :class:`psyplot.plotter.Plotter` to use for
visualization
filename_or_obj: filename, :class:`xarray.Dataset` or data store
The object (or file name) to open. If not a dataset, the
:func:`psyplot.data.open_dataset` will be used to open a dataset
fmt: dict
Formatoptions that shall be when initializing the plot (you can
however also specify them as extra keyword arguments)
make_plot: bool
If True, the data is plotted at the end. Otherwise you have to
call the :meth:`psyplot.plotter.Plotter.initialize_plot` method or
the :meth:`psyplot.plotter.Plotter.reinit` method by yourself
%(InteractiveBase.start_update.parameters.draw)s
mf_mode: bool
If True, the :func:`psyplot.open_mfdataset` method is used.
Otherwise we use the :func:`psyplot.open_dataset` method which can
open only one single dataset
ax: None, tuple (x, y[, z]) or (list of) matplotlib.axes.Axes
Specifies the subplots on which to plot the new data objects.
- If None, a new figure will be created for each created plotter
- If tuple (x, y[, z]), `x` specifies the number of rows, `y` the
number of columns and the optional third parameter `z` the
maximal number of subplots per figure.
- If :class:`matplotlib.axes.Axes` (or list of those, e.g. created
by the :func:`matplotlib.pyplot.subplots` function), the data
will be plotted on these subplots
%(open_dataset.parameters.engine)s
%(multiple_subplots.parameters.delete)s
share: bool, fmt key or list of fmt keys
Determines whether the first created plotter shares it's
formatoptions with the others. If True, all formatoptions are
shared. Strings or list of strings specify the keys to share.
clear: bool
If True, axes are cleared before making the plot. This is only
necessary if the `ax` keyword consists of subplots with projection
that differs from the one that is needed
enable_post: bool
If True, the :attr:`~psyplot.plotter.Plotter.post` formatoption is
enabled and post processing scripts are allowed. If ``None``, this
parameter is set to True if there is a value given for the `post`
formatoption in `fmt` or `kwargs`
%(xarray.open_mfdataset.parameters.concat_dim)s
This parameter only does have an effect if `mf_mode` is True.
load: bool
If True, load the complete dataset into memory before plotting.
This might be useful if the data of other variables in the dataset
has to be accessed multiple times, e.g. for unstructured grids.
%(ArrayList.from_dataset.parameters.no_base)s
Other Parameters
----------------
%(ArrayList.from_dataset.other_parameters.no_args_kwargs)s
``**kwargs``
Any other dimension or formatoption that shall be passed to `dims`
or `fmt` respectively.
Returns
-------
Project
The subproject that contains the new (visualized) data array"""
if not isinstance(filename_or_obj, xarray.Dataset):
if mf_mode:
filename_or_obj = open_mfdataset(filename_or_obj,
engine=engine,
concat_dim=concat_dim)
else:
filename_or_obj = open_dataset(filename_or_obj,
engine=engine)
if load:
old = filename_or_obj
filename_or_obj = filename_or_obj.load()
old.close()
fmt = dict(fmt)
possible_fmts = list(plotter_cls._get_formatoptions())
additional_fmt, kwargs = utils.sort_kwargs(
kwargs, possible_fmts)
fmt.update(additional_fmt)
if enable_post is None:
enable_post = bool(fmt.get('post'))
# create the subproject
sub_project = self.from_dataset(filename_or_obj, **kwargs)
sub_project.main = self
sub_project.no_auto_update = not (
not sub_project.no_auto_update or not self.no_auto_update)
# create the subplots
proj = plotter_cls._get_sample_projection()
if isinstance(ax, tuple):
axes = iter(multiple_subplots(
*ax, n=len(sub_project), subplot_kw={'projection': proj}))
elif ax is None or isinstance(ax, (mpl.axes.SubplotBase,
mpl.axes.Axes)):
axes = repeat(ax)
else:
axes = iter(ax)
clear = clear or (isinstance(ax, tuple) and proj is not None)
for arr in sub_project:
plotter_cls(arr, make_plot=(not bool(share) and make_plot),
draw=False, ax=next(axes), clear=clear,
project=self, enable_post=enable_post, **fmt)
if share:
if share is True:
share = possible_fmts
elif isinstance(share, six.string_types):
share = [share]
else:
share = list(share)
sub_project[0].psy.plotter.share(
[arr.psy.plotter for arr in sub_project[1:]], keys=share,
draw=False)
if make_plot:
for arr in sub_project:
arr.psy.plotter.reinit(draw=False, clear=clear)
if draw is None:
draw = rcParams['auto_draw']
if draw:
sub_project.draw()
if rcParams['auto_show']:
self.show()
self.extend(sub_project, new_name=True)
if self is gcp(True):
scp(sub_project)
return sub_project
def __getitem__(self, key):
"""Overwrites lists __getitem__ by returning subproject if `key` is a
slice"""
if isinstance(key, slice): # return a new project
ret = self.__class__(
super(Project, self).__getitem__(key))
ret.main = self.main
else: # return the item
ret = super(Project, self).__getitem__(key)
return ret
if six.PY2: # for compatibility to python 2.7
def __getslice__(self, *args):
return self[slice(*args)]
def __add__(self, other):
# overwritte to return a subproject
ret = self.__class__(super(Project, self).__add__(other))
ret.main = self.main
return ret
@staticmethod
def show():
"""Shows all open figures"""
import matplotlib.pyplot as plt
plt.show(block=False)
docstrings.keep_params('join_dicts.parameters', 'delimiter')
docstrings.keep_params('join_dicts.parameters', 'keep_all')
@docstrings.get_sectionsf('Project.joined_attrs')
@docstrings.with_indent(8)
def joined_attrs(self, delimiter=', ', enhanced=True, plot_data=False,
keep_all=True):
"""Join the attributes of the arrays in this project
Parameters
----------
%(join_dicts.parameters.delimiter)s
enhanced: bool
If True, the :meth:`psyplot.plotter.Plotter.get_enhanced_attrs`
method is used, otherwise the :attr:`xarray.DataArray.attrs`
attribute is used.
plot_data: bool
It True, use the :attr:`psyplot.plotter.Plotter.plot_data`
attribute of the plotters rather than the raw data in this project
%(join_dicts.parameters.keep_all)s
Returns
-------
dict
A mapping from the attribute to the joined attributes which are
either strings or (if there is only one attribute value), the
data type of the corresponding value"""
if enhanced:
all_attrs = [
plotter.get_enhanced_attrs(
getattr(plotter, 'plot_data' if plot_data else 'data'))
for plotter in self.plotters]
else:
if plot_data:
all_attrs = [plotter.plot_data.attrs
for plotter in self.plotters]
else:
all_attrs = [arr.attrs for arr in self]
return utils.join_dicts(all_attrs, delimiter=delimiter,
keep_all=keep_all)
@docstrings.get_sectionsf('Project.format_string')
@docstrings.with_indent(8)
def format_string(self, s, use_time=False, format_args=None, *args,
**kwargs):
"""Format a string with the attributes in this project
Parameters
----------
s: str
The string that is subject to be formatted
use_time: bool
If True, formatting strings for the
:meth:`datetime.datetime.strftime` are expected to be found in
`output` (e.g. ``'%%m'``, ``'%%Y'``, etc.). If so, other formatting
strings must be escaped by double ``'%%'`` (e.g. ``'%%%i'``
instead of (``'%%i'``))
format_args: tuple
A tuple of arguments that shall be inserted in `s` via
``s %% format_args``. (There will be no error, when this fails!)
%(Project.joined_attrs.parameters)s
Returns
-------
str
The formatted string `s`
"""
attrs = self.joined_attrs(*args, **kwargs)
if use_time:
tnames = self._get_tnames()
tname = next(iter(tnames)) if len(tnames) == 1 else None
time = attrs[tname]
try: # assume a valid datetime.datetime instance
s = pd.to_datetime(time).strftime(s)
except ValueError:
pass
if format_args is not None:
try:
s = safe_modulo(s, format_args, print_warning=False)
except TypeError:
pass
return safe_modulo(s, attrs)
docstrings.keep_params('Project.format_string.parameters', 'use_time')
@docstrings.with_indent(8)
def export(self, output, tight=False, concat=True, close_pdf=None,
use_time=False, **kwargs):
"""Exports the figures of the project to one or more image files
Parameters
----------
output: str, iterable or matplotlib.backends.backend_pdf.PdfPages
if string or list of strings, those define the names of the output
files. Otherwise you may provide an instance of
:class:`matplotlib.backends.backend_pdf.PdfPages` to save the
figures in it.
If string (or iterable of strings), attribute names in the
xarray.DataArray.attrs attribute as well as index dimensions
are replaced by the respective value (see examples below).
Furthermore a single format string without key (e.g. %%i, %%s, %%d,
etc.) is replaced by a counter.
tight: bool
If True, it is tried to figure out the tight bbox of the figure
(same as bbox_inches='tight')
concat: bool
if True and the output format is `pdf`, all figures are
concatenated into one single pdf
close_pdf: bool or None
If True and the figures are concatenated into one single pdf,
the resulting pdf instance is closed. If False it remains open.
If None and `output` is a string, it is the same as
``close_pdf=True``, if None and `output` is neither a string nor an
iterable, it is the same as ``close_pdf=False``
%(Project.format_string.parameters.use_time)s
``**kwargs``
Any valid keyword for the :func:`matplotlib.pyplot.savefig`
function
Returns
-------
matplotlib.backends.backend_pdf.PdfPages or None
a PdfPages instance if output is a string and close_pdf is False,
otherwise None
Examples
--------
Simply save all figures into one single pdf::
>>> p = psy.gcp()
>>> p.export('my_plots.pdf')
Save all figures into separate pngs with increasing numbers (e.g.
``'my_plots_1.png'``)::
>>> p.export('my_plots_%%i.png')
Save all figures into separate pngs with the name of the variables
shown in each figure (e.g. ``'my_plots_t2m.png'``)::
>>> p.export('my_plots_%%(name)s.png')
Save all figures into separate pngs with the name of the variables
shown in each figure and with increasing numbers (e.g.
``'my_plots_1_t2m.png'``)::
>>> p.export('my_plots_%%i_%%(name)s.png')
Specify the names for each figure directly via a list::
>>> p.export(['my_plots1.pdf', 'my_plots2.pdf'])
"""
from matplotlib.backends.backend_pdf import PdfPages
if tight:
kwargs['bbox_inches'] = 'tight'
not_enough_files_warnings = (
"Not enough output files specified! %i figures are open "
"but only %i filenames have been given! This will cause "
"that some figures may be overwritten after being "
"exported! Use a pdf instead if you want to save all "
"figures or include a '%%i' string in the filename to "
"avoid duplicates.")
if isinstance(output, six.string_types): # a single string
out_fmt = kwargs.pop('format', os.path.splitext(output))[1][1:]
if out_fmt.lower() == 'pdf' and concat:
output = self.format_string(output, use_time, delimiter='-')
pdf = PdfPages(output)
for fig in self.figs:
pdf.savefig(fig, **kwargs)
if close_pdf is None or close_pdf:
pdf.close()
return
else:
return pdf
else:
output = [output] * len(self.figs)
if utils.is_iterable(output): # a list of strings
output = [sp.format_string(out, use_time, i, delimiter='-')
for i, (out, sp) in enumerate(
zip(output, self.figs.values()), 1)]
if len(set(output)) != len(output):
warn(not_enough_files_warnings % (
len(output), len(self.figs)))
output = iter(output)
for fig, out in zip(self.figs, output):
fig.savefig(out, **kwargs)
else: # an instances of matplotlib.backends.backend_pdf.PdfPages
for fig in self.figs:
output.savefig(fig, **kwargs)
if close_pdf:
output.close()
docstrings.keep_params('Plotter.share.parameters', 'keys')
docstrings.delete_params('Plotter.share.parameters', 'keys', 'plotters')
@docstrings.dedent
def share(self, base=None, keys=None, by=None, **kwargs):
"""
Share the formatoptions of one plotter with all the others
This method shares specified formatoptions from `base` with all the
plotters in this instance.
Parameters
----------
base: None, Plotter, xarray.DataArray, InteractiveList, or list of them
The source of the plotter that shares its formatoptions with the
others. It can be None (then the first instance in this project
is used), a :class:`~psyplot.plotter.Plotter` or any data object
with a *psy* attribute. If `by` is not None, then it is expected