def __init__(self, **kwargs):
super(ScatterViewerState, self).__init__()
self.limits_cache = {}
self.x_lim_helper = StateAttributeLimitsHelper(
self,
attribute='x_att',
lower='x_min',
upper='x_max',
log='x_log',
margin=0.04,
limits_cache=self.limits_cache)
self.y_lim_helper = StateAttributeLimitsHelper(
self,
attribute='y_att',
lower='y_min',
upper='y_max',
log='y_log',
margin=0.04,
limits_cache=self.limits_cache)
self.add_callback('layers', self._layers_changed)
self.x_att_helper = ComponentIDComboHelper(self,
'x_att',
pixel_coord=True,
world_coord=True)
self.y_att_helper = ComponentIDComboHelper(self,
'y_att',
pixel_coord=True,
world_coord=True)
self.plot_mode_helper = ComboHelper(self, 'plot_mode')
self.plot_mode_helper.choices = [
proj for proj in get_projection_names()
if proj not in ['3d', 'scatter_density']
]
self.plot_mode_helper.selection = 'rectilinear'
self.angle_unit_helper = ComboHelper(self, 'angle_unit')
self.angle_unit_helper.choices = ['radians', 'degrees']
self.angle_unit_helper.selection = 'radians'
self.update_from_dict(kwargs)
self.add_callback('x_log', self._reset_x_limits)
self.add_callback('y_log', self._reset_y_limits)
if self.using_polar:
self.full_circle()
def get_mpl_transform(mpl_proj):
r"""This returns an instantiated transform function given a transform
function name and arguments.
Parameters
----------
mpl_proj : string or tuple
the matplotlib projection type. Can take the form of string or tuple.
Examples
--------
>>> get_mpl_transform("PlateCarree")
>>> get_mpl_transform(('RotatedPole', (), {'pole_latitude':37.5,
... 'pole_longitude':177.5}))
"""
# first check to see if the tranform dict is empty, if it is fill it with
# the cartopy functions
if not valid_transforms:
for mpl_transform in transform_list:
valid_transforms[mpl_transform] = cartopy_importer(mpl_transform)
# check to see if mpl_proj is a string or tuple, and construct args and
# kwargs to pass to cartopy function based on that.
key = None
if isinstance(mpl_proj, str):
key = mpl_proj
args = ()
kwargs = {}
instantiated_func = valid_transforms[key](*args, **kwargs)
elif isinstance(mpl_proj, tuple):
if len(mpl_proj) == 2:
key, args = mpl_proj
kwargs = {}
elif len(mpl_proj) == 3:
key, args, kwargs = mpl_proj
instantiated_func = valid_transforms[key](*args, **kwargs)
elif hasattr(mpl_proj, "globe"):
# cartopy transforms have a globe method associated with them
key = mpl_proj
instantiated_func = mpl_proj
elif hasattr(mpl_proj, "set_transform"):
# mpl axes objects have a set_transform method, so we'll check if that
# exists on something passed in.
key = mpl_proj
instantiated_func = mpl_proj
elif hasattr(mpl_proj, "name"):
# last we'll check if the transform is in the list of registered
# projections in matplotlib.
from matplotlib.projections import get_projection_names
registered_projections = get_projection_names()
if mpl_proj.name in registered_projections:
key = mpl_proj
instantiated_func = mpl_proj
else:
key = None
# build in a check that if none of the above options are satisfied by what
# the user passes that None is returned for the instantiated function
if key is None:
instantiated_func = None
return instantiated_func
from matplotlib.image import FigureImage
import matplotlib.colorbar as cbar
from matplotlib.axes import Axes, SubplotBase, subplot_class_factory
from matplotlib.blocking_input import BlockingMouseInput, BlockingKeyMouseInput
from matplotlib.legend import Legend
from matplotlib.patches import Rectangle
from matplotlib.projections import (get_projection_names,
process_projection_requirements)
from matplotlib.text import Text, _process_text_args
from matplotlib.transforms import (Affine2D, Bbox, BboxTransformTo,
TransformedBbox)
docstring.interpd.update(projection_names = get_projection_names())
class AxesStack(Stack):
"""
Specialization of the Stack to handle all tracking of Axes in a Figure.
This stack stores ``key, (ind, axes)`` pairs, where:
* **key** should be a hash of the args and kwargs
used in generating the Axes.
* **ind** is a serial number for tracking the order
in which axes were added.
The AxesStack is a callable, where ``ax_stack()`` returns
the current axes. Alternatively the :meth:`current_key_axes` will
return the current key and associated axes.
