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Merge 3bc5bca into 106878d
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@vindelico
vindelico committed May 6, 2024
2 parents 106878d + 3bc5bca commit 8681b9e
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Showing 3 changed files with 71 additions and 62 deletions.
1 change: 1 addition & 0 deletions CHANGES.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@ Contributors to this version: Trevor James Smith (:user:`Zeitsperre`), Marco Bra

New features and enhancements
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
* No-legend option in ``hatchmap``; use ``edgecolor`` and ``edgecolors`` as aliases (:pull:`195`)
* Use list or ndarray as levels for colorbar in gridmap and small bug fixes (:pull:`176`).
* Added style sheet ``transparent.mplstyle`` (:issue:`183`, :pull:`185`)
* Fix NaN issues, extreme values in sizes legend and added edgecolors in ``fg.matplotlib.scattermap`` (:pull:`184`).
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4 changes: 2 additions & 2 deletions docs/notebooks/figanos_multiplots.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -180,7 +180,7 @@
"im = fg.hatchmap({'sup_305k': sup_305k, 'inf_300k': inf_300k},\n",
" plot_kw={\n",
" 'sup_305k': {\n",
" 'hatches': '*',\n",
" 'hatches': ['////'], # hatches must be passed as a list\n",
" 'col': 'time',\n",
" \"x\": \"lon\",\n",
" \"y\": \"lat\"\n",
Expand All @@ -196,7 +196,7 @@
" frame = True,\n",
" legend_kw = {'title': 'Ensemble change'})\n",
"\n",
"im.fig.suptitle(\"Multiple hatchmaps\", y=1.08)\n"
"im.fig.suptitle(\"Multiple hatchmaps\", y=1.08)"
]
},
{
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128 changes: 68 additions & 60 deletions figanos/matplotlib/plot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1526,17 +1526,15 @@ def scattermap(
if "row" not in plot_kw and "col" not in plot_kw:
use_attrs.setdefault("title", "description")

plot_kw_pop = copy.deepcopy(plot_kw) # copy plot_kw to modify and pop info in it

# extract plot_kw from dict if needed
if isinstance(data, dict) and plot_kw and list(data.keys())[0] in plot_kw.keys():
plot_kw_pop = plot_kw_pop[list(data.keys())[0]]
plot_kw = plot_kw[list(data.keys())[0]]

# figanos does not use xr.plot.scatter default markersize
if "markersize" in plot_kw.keys():
if not sizes:
sizes = plot_kw["markersize"]
plot_kw_pop.pop("markersize")
plot_kw.pop("markersize")

# if data is dict, extract
if isinstance(data, dict):
Expand Down Expand Up @@ -1576,13 +1574,13 @@ def scattermap(
elif ax is not None and ("col" in plot_kw or "row" in plot_kw):
raise ValueError("Cannot use 'ax' and 'col'/'row' at the same time.")
elif ax is None:
plot_kw_pop = {"subplot_kws": {"projection": projection}} | plot_kw_pop
plot_kw = {"subplot_kws": {"projection": projection}} | plot_kw
cfig_kw = fig_kw.copy()
if "figsize" in fig_kw: # add figsize to plot_kw for facetgrid
plot_kw_pop.setdefault("figsize", fig_kw["figsize"])
plot_kw.setdefault("figsize", fig_kw["figsize"])
cfig_kw.pop("figsize")
if len(cfig_kw) >= 1:
plot_kw_pop = {"subplot_kws": {"projection": projection}} | plot_kw_pop
plot_kw = {"subplot_kws": {"projection": projection}} | plot_kw
warnings.warn(
"Only figsize and figure.add_subplot() arguments can be passed to fig_kw when using facetgrid."
)
Expand All @@ -1602,9 +1600,9 @@ def scattermap(
cbar_label = get_attributes(use_attrs["cbar_label"], data)

if "add_colorbar" not in plot_kw or plot_kw["add_colorbar"] is not False:
plot_kw_pop.setdefault("cbar_kwargs", {})
plot_kw_pop["cbar_kwargs"].setdefault("label", wrap_text(cbar_label))
plot_kw_pop["cbar_kwargs"].setdefault("pad", 0.015)
plot_kw.setdefault("cbar_kwargs", {})
plot_kw["cbar_kwargs"].setdefault("label", wrap_text(cbar_label))
plot_kw["cbar_kwargs"].setdefault("pad", 0.015)

# colormap
if isinstance(cmap, str):
Expand Down Expand Up @@ -1656,61 +1654,68 @@ def scattermap(
target_range=size_range,
data_range=None,
)
plot_kw_pop.setdefault("add_legend", False)
plot_kw.setdefault("add_legend", False)
if ax:
plot_kw_pop.setdefault("s", pt_sizes)
plot_kw.setdefault("s", pt_sizes)
else:
plot_kw_pop.setdefault("s", pt_sizes[0])
plot_kw.setdefault("s", pt_sizes[0])

# norm
plot_kw_pop.setdefault("vmin", np.nanmin(plot_data.values[mask]))
plot_kw_pop.setdefault("vmax", np.nanmax(plot_data.values[mask]))
plot_kw.setdefault("vmin", np.nanmin(plot_data.values[mask]))
plot_kw.setdefault("vmax", np.nanmax(plot_data.values[mask]))

norm = custom_cmap_norm(
cmap,
vmin=plot_kw_pop["vmin"],
vmax=plot_kw_pop["vmax"],
vmin=plot_kw["vmin"],
vmax=plot_kw["vmax"],
levels=levels,
divergent=divergent,
)

# matplotlib.pyplot.scatter treats "edgecolor" and "edgecolors" as aliases so we accept "edgecolor" and convert it
if "edgecolor" in plot_kw and "edgecolors" not in plot_kw:
plot_kw["edgecolors"] = plot_kw["edgecolor"]
plot_kw.pop("edgecolor")

# set defaults and create copy without vmin, vmax (conflicts with norm)
plot_kw_pop = {
plot_kw = {
"cmap": cmap,
"norm": norm,
"transform": transform,
"zorder": 8,
"marker": "o",
} | plot_kw_pop
"edgecolors": "none",
} | plot_kw

# chek if edgecolors in plot_kw and match len of plot_data
if "edgecolors" in plot_kw:
if matplotlib.colors.is_color_like(plot_kw["edgecolors"]):
plot_kw_pop["edgecolors"] = np.repeat(
plot_kw["edgecolors"] = np.repeat(
plot_kw["edgecolors"], len(plot_data.where(mask).values)
)
elif len(plot_kw["edgecolors"]) != len(plot_data.values):
plot_kw_pop["edgecolors"] = np.repeat(
plot_kw["edgecolors"] = np.repeat(
plot_kw["edgecolors"][0], len(plot_data.where(mask).values)
)
warnings.warn(
"Length of edgecolors does not match length of data. Only first edgecolor is used for plotting."
)
else:
if isinstance(plot_kw["edgecolors"], list):
plot_kw_pop["edgecolors"] = np.array(plot_kw["edgecolors"])
plot_kw_pop["edgecolors"] = plot_kw_pop["edgecolors"][mask]
plot_kw["edgecolors"] = np.array(plot_kw["edgecolors"])
plot_kw["edgecolors"] = plot_kw["edgecolors"][mask]
else:
plot_kw_pop.setdefault("edgecolor", "none")
plot_kw.setdefault("edgecolors", "none")

for key in ["vmin", "vmax"]:
plot_kw_pop.pop(key)
plot_kw.pop(key)
# plot
plot_kw_pop = {"x": "lon", "y": "lat", "hue": plot_data.name} | plot_kw_pop
plot_kw = {"x": "lon", "y": "lat", "hue": plot_data.name} | plot_kw
if ax:
plot_kw_pop.setdefault("ax", ax)
v = plot_data.where(mask).to_dataset()
im = v.plot.scatter(**plot_kw_pop)
plot_kw.setdefault("ax", ax)

plot_data_masked = plot_data.where(mask).to_dataset()
im = plot_data_masked.plot.scatter(**plot_kw)

# add features
if ax:
Expand Down Expand Up @@ -1773,7 +1778,7 @@ def scattermap(
np.resize(sdata.values[mask], (sdata.values[mask].size, 1)),
np.resize(pt_sizes[mask], (pt_sizes[mask].size, 1)),
max_entries=6,
marker=plot_kw_pop["marker"],
marker=plot_kw["marker"],
)
# legend spacing
if size_range[1] > 200:
Expand Down Expand Up @@ -2077,7 +2082,7 @@ def hatchmap(
features: list[str] | dict[str, dict[str, Any]] | None = None,
geometries_kw: dict[str, Any] | None = None,
levels: int | None = None,
legend_kw: dict[str, Any] | None = None,
legend_kw: dict[str, Any] | bool = True,
show_time: bool | str | int | tuple[float, float] = False,
frame: bool = False,
) -> matplotlib.axes.Axes:
Expand Down Expand Up @@ -2108,8 +2113,8 @@ def hatchmap(
cartopy.feature: ['coastline', 'borders', 'lakes', 'land', 'ocean', 'rivers', 'states'].
geometries_kw : dict, optional
Arguments passed to cartopy ax.add_geometry() which adds given geometries (GeoDataFrame geometry) to axis.
legend_kw : dict, optional
Arguments to pass to `ax.legend()`.
legend_kw : dict or boolean, optional
Arguments to pass to `ax.legend()`. No legend is added if legend_kw == False.
show_time : bool, tuple, string or int.
If True, show time (as date) at the bottom right of the figure.
Can be a tuple of axis coordinates (0 to 1, as a fraction of the axis length) representing the location
Expand Down Expand Up @@ -2169,24 +2174,23 @@ def hatchmap(

dattrs = None
plot_data = {}
dc = plot_kw.copy()

# convert data to dict (if not one)
if not isinstance(data, dict):
if isinstance(data, xr.DataArray):
plot_data = {data.name: data}
if list(data.keys())[0] not in plot_kw.keys():
plot_kw = {list(plot_data.keys())[0]: dc}
if data.name not in plot_kw.keys():
plot_kw = {data.name: plot_kw}
elif isinstance(data, xr.Dataset):
dattrs = data
plot_data = {var: data[var] for var in data.data_vars}
for v in plot_data.keys():
if v not in plot_kw.keys():
plot_kw[v] = dc
plot_kw[v] = plot_kw
else:
for k, v in data.items():
if k not in plot_kw.keys():
plot_kw[k] = dc
plot_kw[k] = plot_kw
if isinstance(v, xr.Dataset):
dattrs = k
plot_data[k] = v[list(v.data_vars)[0]]
Expand All @@ -2208,28 +2212,25 @@ def hatchmap(
if transform and (
"xlim" in list(plot_kw.values())[0] and "ylim" in list(plot_kw.values())[0]
):
extend = [
extent = [
list(plot_kw.values())[0]["xlim"][0],
list(plot_kw.values())[0]["xlim"][1],
list(plot_kw.values())[0]["ylim"][0],
list(plot_kw.values())[0]["ylim"][1],
]
{v.pop("xlim") for v in plot_kw.values()}
{v.pop("ylim") for v in plot_kw.values()}
[v.pop(lim) for lim in ["xlim", "ylim"] for v in plot_kw.values() if lim in v]

elif transform and (
"xlim" in list(plot_kw.values())[0] or "ylim" in list(plot_kw.values())[0]
):
extend = None
extent = None
warnings.warn(
"Requires both xlim and ylim with 'transform'. Xlim or ylim was dropped"
)
if "xlim" in list(plot_kw.values())[0].keys():
{v.pop("xlim") for v in plot_kw.values()}
if "ylim" in list(plot_kw.values())[0].keys():
{v.pop("ylim") for v in plot_kw.values()}
[v.pop(lim) for lim in ["xlim", "ylim"] for v in plot_kw.values() if lim in v]

else:
extend = None
extent = None

# setup fig, ax
if ax is None and (
Expand All @@ -2243,11 +2244,11 @@ def hatchmap(
):
raise ValueError("Cannot use 'ax' and 'col'/'row' at the same time.")
elif ax is None:
{
[
v.setdefault("subplot_kws", {}).setdefault("projection", projection)
for v in plot_kw.values()
}
cfig_kw = fig_kw.copy()
]
cfig_kw = copy.deepcopy(fig_kw)
if "figsize" in fig_kw: # add figsize to plot_kw for facetgrid
plot_kw[0].setdefault("figsize", fig_kw["figsize"])
cfig_kw.pop("figsize")
Expand Down Expand Up @@ -2295,9 +2296,9 @@ def hatchmap(
im = v.where(mask is not True).plot.contourf(**plot_kw[k])
artists, labels = im.legend_elements(str_format="{:2.1f}".format)

if ax:
if ax and legend_kw:
ax.legend(artists, labels, **legend_kw)
else:
elif legend_kw:
im.figlegend = im.fig.legend(**legend_kw)

elif len(plot_data) > 1 and "levels" in plot_kw[k]:
Expand All @@ -2311,6 +2312,13 @@ def hatchmap(
if "hatches" not in plot_kw[k].keys():
plot_kw[k]["hatches"] = dfh[n]
n += 1
elif isinstance(
plot_kw[k]["hatches"], str
): # make sure the hatches are in a list
warnings.warn(
"Hatches argument must be of type 'list'. Wrapping string argument as list."
)
plot_kw[k]["hatches"] = [plot_kw[k]["hatches"]]

plot_kw[k].setdefault("transform", transform)
if ax:
Expand Down Expand Up @@ -2344,31 +2352,31 @@ def hatchmap(
geometries_kw,
frame,
)
if extend:
fax.set_extent(extend)
if extent:
fax.set_extent(extent)

pat_leg.append(
matplotlib.patches.Patch(
hatch=plot_kw[k]["hatches"], fill=False, label=k
hatch=plot_kw[k]["hatches"][0], fill=False, label=k
)
)

if pat_leg:
if pat_leg and legend_kw:
legend_kw = {
"loc": "lower right",
"handleheight": 2,
"handlelength": 4,
} | legend_kw

if ax:
if ax and legend_kw:
ax.legend(handles=pat_leg, **legend_kw)
else:
elif legend_kw:
im.figlegend = im.fig.legend(handles=pat_leg, **legend_kw)

# add features
if ax:
if extend:
ax.set_extend(extend)
if extent:
ax.set_extent(extent)
if dattrs:
use_attrs.setdefault("title", "description")

Expand Down

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