def _plt_xcoef(ax, x_ts, w, c=None, name=None, bold=0, **kwargs):
# Create coordinates (x, y)
coords = list(enumerate(x_ts))
# Line-starts from : 0 -> semi-last (-1)
starts = coords[:-1]
# Line-ends from : 1 -> final
ends = coords[1:]
# Colors
if not isinstance(c, str):
c = "Reds"
color_map = plt.cm.get_cmap(c)
color_norm = colors.Normalize()
# Line intervals
lines = [(start, end) for start, end in zip(starts, ends)]
lines_lc = LineCollection(
lines,
# linewidths= 1 + w * 2,
array=w,
# norm=color_norm,
cmap=color_map,
)
line = ax.add_collection(lines_lc)
ax.autoscale()
# plt.colorbar(line)
if name is not None:
pos_of_name = 0.5 # center between 0 - 1
# Custom Legend for LineCollection
handle = Line2D([0, 1], [0, 1], color=lines_lc.cmap(pos_of_name))
ax.legend([handle], [name],
loc='center left',
bbox_to_anchor=(1.0, 0.5))
def display(self,
ax,
step=1,
only_used=False,
only_unused=False,
only_contain_eddies=False,
display_criterion=False,
field=None,
bins=None,
cmap="Spectral_r",
**kwargs):
"""
Display contour
:param matplotlib.axes.Axes ax:
:param int step: display only contour every step
:param bool only_used: display only contour used in an eddy
:param bool only_unused: display only contour unused in an eddy
:param bool only_contain_eddies: display only contour which enclosed an eddiy
:param bool display_criterion:
display only unused contour with criterion color
0. - Accepted (green)
1. - Reject for shape error (red)
2. - Masked value in contour (blue)
3. - Under or over pixel limit bound (black)
4. - Amplitude criterion (yellow)
:param str field:
Must be 'shape_error', 'x', 'y' or 'radius'.
If define display_criterion is not use.
bins argument must be define
:param array bins: bins use to colorize contour
:param str cmap: Name of cmap to use for field display
:param dict kwargs: look at :py:method:`matplotlib.collections.LineCollection`
.. minigallery:: py_eddy_tracker.Contours.display
"""
from matplotlib.collections import LineCollection
overide_color = display_criterion or field is not None
if display_criterion:
paths = {0: list(), 1: list(), 2: list(), 3: list(), 4: list()}
elif field is not None:
paths = dict()
for i in range(len(bins)):
paths[i] = list()
paths[i + 1] = list()
for j, collection in enumerate(self.contours.collections[::step]):
if not overide_color:
paths = list()
for i in collection.get_paths():
if only_used and not i.used:
continue
elif only_unused and i.used:
continue
elif only_contain_eddies and not i.contain_eddies:
continue
if display_criterion:
paths[i.reject].append(i.vertices)
elif field is not None:
x, y, radius, shape_error = i.fit_circle()
if field == "shape_error":
i_ = digitize(shape_error, bins)
elif field == "radius":
i_ = digitize(radius, bins)
elif field == "x":
i_ = digitize(x, bins)
elif field == "y":
i_ = digitize(y, bins)
paths[i_].append(i.vertices)
else:
paths.append(i.vertices)
local_kwargs = kwargs.copy()
if "color" not in kwargs:
local_kwargs["color"] = collection.get_color()
local_kwargs.pop("label", None)
elif j != 0:
local_kwargs.pop("label", None)
if not overide_color:
ax.add_collection(LineCollection(paths, **local_kwargs))
if display_criterion:
colors = {0: "g", 1: "r", 2: "b", 3: "k", 4: "y"}
for k, v in paths.items():
local_kwargs = kwargs.copy()
local_kwargs.pop("label", None)
local_kwargs["colors"] = colors[k]
ax.add_collection(LineCollection(v, **local_kwargs))
elif field is not None:
nb_bins = len(bins) - 1
cmap = get_cmap(cmap, lut=nb_bins)
for k, v in paths.items():
local_kwargs = kwargs.copy()
local_kwargs.pop("label", None)
if k == 0:
local_kwargs["colors"] = cmap(0.0)
elif k > nb_bins:
local_kwargs["colors"] = cmap(1.0)
else:
local_kwargs["colors"] = cmap((k - 1.0) / nb_bins)
mappable = LineCollection(v, **local_kwargs)
ax.add_collection(mappable)
mappable.cmap = cmap
mappable.norm = Normalize(vmin=bins[0], vmax=bins[-1])
# TODO : need to create an object with all collections
return mappable
else:
if hasattr(self.contours, "_mins"):
ax.update_datalim([self.contours._mins, self.contours._maxs])
ax.autoscale_view()
