"""Methods to plot data defined on Landlab grids.
Plotting functions
++++++++++++++++++
.. autosummary::
~landlab.plot.imshow.imshowhs_grid
~landlab.plot.imshow.imshowhs_grid_at_node
"""
import warnings
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LightSource
from matplotlib.colors import to_rgba
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
from .event_handler import query_grid_on_button_press
[docs]
def imshowhs_grid(grid, values, **kwds):
"""Prepare a map view of data over all nodes in the grid using a hillshade
topography map in the background.
Data are plotted as cells shaded with the value at the node at its center.
Outer edges of perimeter cells are extrapolated. Closed elements are
colored uniformly (with the color being controlled by the *color_for_closed*
keyword); other open boundary nodes get their actual values.
*values* can be a field name, a regular array, or a masked array. If a
masked array is provided, masked entries are treated as if they were
*landlab* :py:attr:`~.NodeStatus.CLOSED` nodes. If closed nodes are also set to
be transparent (i.e. ``color_for_closed=None``), this can allow for the
construction of overlying layers in a figure (e.g., only defining values in a
river network, and then overlaying it on another landscape).
Use matplotlib functions like ``xlim``, ``ylim`` to modify your plot after calling
:func:`imshowhs_grid`, as desired.
Node coordinates are printed when a mouse button is pressed on a cell in
the plot.
.. note::
For now, this function only works with :class:`~.RasterModelGrid`.
Parameters
----------
grid : ModelGrid
Grid containing the field to plot, or describing the geometry of the
provided array.
values : array_like, masked_array, or str
Node values, or a field name as a string from which to draw the data.
plot_name : str, optional
String to put as the plot title.
var_name : str, optional
Variable name, to use as a colorbar label.
var_name_two : str, optional
Variable name of second layer, to use as a colorbar label.
var_units : str, optional
Units for the variable being plotted, for the colorbar.
grid_units : tuple of str, optional
Units for *y*, and *x* dimensions. If ``None``, component will look to the
grid property :py:attr:`~.ModelGrid.axis_units` for this information. If no units are
specified there, no entry is made.
symmetric_cbar : bool
Make the colormap symmetric about 0.
cmap : str
Name of a colormap
limits : tuple of float
Minimum and maximum of the colorbar.
vmin, vmax: floats
Alternatives to limits.
norm : matplotlib.colors.Normalize
The normalizing object which scales data, typically into the interval
[0, 1]. Ignore in most cases.
ticks_km : bool, optional
Display ticks in km instead of m
allow_colorbar : bool
If ``True``, include the colorbar.
shrink : float
Fraction by which to shrink the colorbar.
color_for_closed : str or None
Color to use for closed nodes (default ``None``). If ``None``,
(or masked) nodes will be transparent.
color_for_background : color str or other color declaration, or None
Color to use for closed elements (default ``None``). If ``None``, the
background will be transparent, and appear white.
output : None, string, or bool
If ``None`` (or ``False``), the image is sent to the imaging buffer to await
an explicit call to ``show()`` or ``savefig()`` from outside this function.
If a ``str``, the string should be the path to a save location, and the
filename (with file extension). The function will then call
``plt.savefig([string])`` itself. If ``True``, the function will call
``plt.show()`` itself once plotting is complete.
fontweight_xlabel : str, optional
Weight of *x* label. The default is 'bold'.
fontweight_ylabel : str, optional
Weight of *y* label. The default is 'bold'.
plot_type : {"DEM", "Hillshade", "Drape1", "Drape2"}, optional
The type of plot that will be plotted.
* 'DEM': Display a digital elevation map underlain by a shaded relief,
based on the same DEM ('topographic__elevation')
* 'Hillshade': Display the shaded relief, of the provided DEM
('topographic__elevation')
* 'Drape1': Display any kind of provided layer on top of a shaded
relief provided in the 'topographic__elevation' field
* 'Drape2': Display two layers on top of a shaded relief provided in
the 'topographic__elevation' field
The default is "DEM".
drape1 : array_like, masked_array
Node values to plot on top of a hillshade map. The default is ``None``.
drape2 : array_like, masked_array
Node values to plot on top of drape1 and a hillshade map. The default is ``None``.
cmap2 : str
Name of a colormap for drape 2. The default is ``None``.
vertical_exa : float, optional
Vertical exaggeration of hillshade map. The default is ``None``.
azdeg : float, optional
Azimuth of the light source. The default is 315.
altdeg : float, optional
Elevation of the light source. The default is 65.
thres_drape1 : float, optional
Threshold below which drape1 is made transparent. The default is ``None``.
alpha : float (0-1), optional
Transparency of DEM/Drape1 . The default is ``None``.
thres_drape2 : float, optional
Threshold below which drape2 is made transparent. The default is ``None``.
alpha2 : float (0-1), optional
Transparency of Drape2 . The default is ``None``.
add_double_colorbar : bool, optional
Add a double colorbar when two drapes are plotted. The default is ``False``.
plt_contour : bool, optional
Add contour lines to elevation plot. The default is ``False``.
contour_nb : int, optional
Number of contour lines. The default is 50.
default_fontsize : float, optional
Default font size for plot labels. The default is 10.
cbar_height : percentage, optional
Height of colorbar as a percentage of the figure. The default is *5%*.
cbar_width : percentage, optional
Width of colorbar in percentage of figure. The default is *30%*.
cbar_or : str, optional
Orientation of colorbar. The default is "horizontal".
cbar_loc : str, optional
Location of colorbar. The default is "lower right".
bbox_to_anchor : vector, optional
Bounding box to anchor. The default is ``(0, 0, 1, 1)``.
cbar_ticks_position : str, optional
location of colorbar ticks (below or on top of the colorbar). The default
is "top".
cbar_ticks_position2 : str, optional
location of colorbar ticks for colorbar of Drape2 (below or on top of the
colorbar). The default is "bottom".
colorbar_label_y : float, optional
location of colorbar label with respect to the colorbar in y direction.
The default is -40.
colorbar_label_x : float , optional
location of colorbar label with respect to the colorbar in x direction.
The default is 0.5.
cbar_tick_size : float, optional
Colorbar tick size. The default is 10.
cbar_label_color : str, optional
Colorbar tick color. The default is 'black'.
cbar_label_fontweight : str, optional
Colorbar font weight. The default is 'bold'.
add_label_bbox : bool, optional
Add a bbox surrounding the colorbar label. The default is ``False``.
y_label_offSet_var_1 : float, optional
Offset of ylabel on colorbar of first variable in plot with two
overlaying plots. The default is 3.0.
y_label_offSet_var_2 : float, optional
Offset of ylabel on colorbar of first variable in plot with two
overlaying plots. The default is -1.25.
Returns
-------
ax
Axis of the plot if *output* keyword is ``True``.
"""
if "values_at" in kwds:
warnings.warn(
f"the 'values_at' keyword is deprecated, use `at={kwds['values_at']!r}` instead",
DeprecationWarning,
stacklevel=2,
)
values_at = kwds.pop("values_at", "node")
values_at = kwds.pop("at", values_at)
if isinstance(values, str):
values = grid.field_values(values_at, values)
if values_at == "node":
ax = imshowhs_grid_at_node(grid, values, **kwds)
elif values_at in {"link", "patch", "corner", "face", "cell"}:
raise NotImplementedError(
"For now, only values at nodes can be displayed using the in the "
"imshowhs functions"
)
else:
raise TypeError(f"{values_at}: value location not understood")
return ax
[docs]
def imshowhs_grid_at_node(grid, values, **kwds):
"""Prepare a map view of data over all nodes in the grid using a hillshade
topography map in the background.
Data are plotted as cells shaded with the value at the node at its center.
Outer edges of perimeter cells are extrapolated. Closed elements are
colored uniformly (with the color being controlled by the *color_for_closed*
keyword); other open boundary nodes get their actual values.
*values* can be a field name, a regular array, or a masked array. If a
masked array is provided, masked entries are treated as if they were
*landlab* :py:attr:`~.NodeStatus.CLOSED` nodes. If closed nodes are also set to
be transparent (i.e. ``color_for_closed=None``), this can allow for the
construction of overlying layers in a figure (e.g., only defining values in a
river network, and then overlaying it on another landscape).
Use matplotlib functions like ``xlim``, ``ylim`` to modify your plot after calling
:func:`imshowhs_grid`, as desired.
Node coordinates are printed when a mouse button is pressed on a cell in
the plot.
.. note::
For now, this function only works with :class:`~.RasterModelGrid`.
Parameters
----------
grid : ModelGrid
Grid containing the field to plot, or describing the geometry of the
provided array.
values : array_like, masked_array, or str
Node values, or a field name as a string from which to draw the data.
plot_name : str, optional
String to put as the plot title.
var_name : str, optional
Variable name, to use as a colorbar label.
var_name_two : str, optional
Variable name of second layer, to use as a colorbar label.
var_units : str, optional
Units for the variable being plotted, for the colorbar.
grid_units : tuple of str, optional
Units for *y*, and *x* dimensions. If ``None``, component will look to the
grid property :py:attr:`~.ModelGrid.axis_units` for this information. If no units are
specified there, no entry is made.
symmetric_cbar : bool
Make the colormap symmetric about 0.
cmap : str
Name of a colormap
limits : tuple of float
Minimum and maximum of the colorbar.
vmin, vmax: floats
Alternatives to limits.
norm : matplotlib.colors.Normalize
The normalizing object which scales data, typically into the interval
[0, 1]. Ignore in most cases.
ticks_km : bool, optional
Display ticks in km instead of m
allow_colorbar : bool
If ``True``, include the colorbar.
shrink : float
Fraction by which to shrink the colorbar.
color_for_closed : str or None
Color to use for closed nodes (default ``None``). If ``None``,
(or masked) nodes will be transparent.
color_for_background : color str or other color declaration, or None
Color to use for closed elements (default ``None``). If ``None``, the
background will be transparent, and appear white.
output : None, string, or bool
If ``None`` (or ``False``), the image is sent to the imaging buffer to await
an explicit call to ``show()`` or ``savefig()`` from outside this function.
If a ``str``, the string should be the path to a save location, and the
filename (with file extension). The function will then call
``plt.savefig([string])`` itself. If ``True``, the function will call
``plt.show()`` itself once plotting is complete.
fontweight_xlabel : str, optional
Weight of *x* label. The default is 'bold'.
fontweight_ylabel : str, optional
Weight of *y* label. The default is 'bold'.
plot_type : {"DEM", "Hillshade", "Drape1", "Drape2"}, optional
The type of plot that will be plotted.
* 'DEM' (the default): Display a digital elevation map underlain by a
shaded relief, based on the same DEM ('topographic__elevation')
* 'Hillshade': Display the shaded relief, of the provided DEM
('topographic__elevation')
* 'Drape1': Display any kind of provided layer on top of a shaded
relief provided in the 'topographic__elevation' field
* 'Drape2': Display two layers on top of a shaded relief provided in
the 'topographic__elevation' field
The default is "DEM".
drape1 : array_like, masked_array
Node values to plot on top of a hillshade map. The default is ``None``.
drape2 : array_like, masked_array
Node values to plot on top of drape1 and a hillshade map. The default is ``None``.
cmap2 : str
Name of a colormap for drape 2. The default is ``None``.
vertical_exa : float, optional
Vertical exaggeration of hillshade map. The default is ``None``.
azdeg : float, optional
Azimuth of the light source. The default is 315.
altdeg : float, optional
Elevation of the light source. The default is 65.
thres_drape1 : float, optional
Threshold below which drape1 is made transparent. The default is ``None``.
alpha : float (0-1), optional
Transparency of DEM/Drape1 . The default is ``None``.
thres_drape2 : float, optional
Threshold below which drape2 is made transparent. The default is ``None``.
alpha2 : float (0-1), optional
Transparency of Drape2 . The default is ``None``.
add_double_colorbar : bool, optional
Add a double colorbar when two drapes are plotted. The default is ``False``.
plt_contour : bool, optional
Add contour lines to elevation plot. The default is ``False``.
contour_nb : int, optional
Number of contour lines. The default is 50.
default_fontsize : float, optional
Default font size for plot labels. The default is 10.
cbar_height : percentage, optional
Height of colorbar as a percentage of the figure. The default is *5%*.
cbar_width : percentage, optional
Width of colorbar in percentage of figure. The default is *30%*.
cbar_or : str, optional
Orientation of colorbar. The default is "horizontal".
cbar_loc : str, optional
Location of colorbar. The default is "lower right".
bbox_to_anchor : vector, optional
Bounding box to anchor. The default is ``(0, 0, 1, 1)``.
cbar_ticks_position : str, optional
Location of colorbar ticks (below or on top of the colorbar). The default
is "top".
cbar_ticks_position2 : str, optional
Location of colorbar ticks for colorbar of *Drape2* (below or on top of the
colorbar). The default is "bottom".
colorbar_label_y : float, optional
Location of colorbar label with respect to the colorbar in *y* direction.
The default is -40.
colorbar_label_x : float , optional
Location of colorbar label with respect to the colorbar in x direction.
The default is 0.5.
cbar_tick_size : float, optional
Colorbar tick size. The default is 10.
cbar_label_color : str, optional
Colorbar tick color. The default is 'black'.
cbar_label_fontweight : str, optional
Colorbar font weight. The default is 'bold'.
add_label_bbox : bool, optional
Add a bbox surrounding the colorbar label. The default is ``False``.
y_label_offSet_var_1 : float, optional
Offset of *ylabel* on colorbar of first variable in plot with two overlaying
plots. The default is 3.0.
y_label_offSet_var_2 : float, optional
Offset of *ylabel* on colorbar of first variable in plot with two overlaying
plots. The default is -1.25.
Returns
-------
ax
Axis of the plot if *output* keyword is ``True``.
"""
if isinstance(values, str):
values_at_node = grid.at_node[values]
else:
values_at_node = values.reshape((-1,))
if values_at_node.size != grid.number_of_nodes:
raise ValueError("number of values does not match number of nodes")
values_at_node = np.ma.masked_where(
grid.status_at_node == grid.BC_NODE_IS_CLOSED, values_at_node
)
ax = _imshowhs_grid_values(grid, values_at_node, **kwds)
if isinstance(values, str):
plt.title(values)
plt.gcf().canvas.mpl_connect(
"button_press_event", lambda event: query_grid_on_button_press(event, grid)
)
# plt.show()
return ax
def _imshowhs_grid_values(
grid,
values,
plot_name=None,
var_name=None,
var_name_two=None,
var_units=None,
fontweight_xlabel="bold",
fontweight_ylabel="bold",
grid_units=(None, None),
symmetric_cbar=False,
cmap="pink",
limits=None,
allow_colorbar=True,
vmin=None,
vmax=None,
norm=None,
ticks_km=False,
shrink=1.0,
color_for_closed=None,
color_for_background=None,
output=None,
plot_type="DEM",
drape1=None,
drape2=None,
cmap2=None,
vertical_exa=None,
azdeg=315,
altdeg=65,
thres_drape1=None,
alpha=None,
thres_drape2=None,
alpha2=None,
add_double_colorbar=False,
plt_contour=False,
contour_nb=50,
default_fontsize=10,
cbar_height="5%",
cbar_width="30%",
cbar_or="horizontal",
cbar_loc="lower right",
bbox_to_anchor=(0, 0, 1, 1),
cbar_ticks_position="top",
cbar_ticks_position2="bottom",
colorbar_label_y=-40,
colorbar_label_x=0.5,
cbar_tick_size=10,
cbar_label_color="black",
cbar_tick_color="black",
cbar_label_fontweight="bold",
add_label_bbox=False,
y_label_offSet_var_1=3,
y_label_offSet_var_2=-1.25,
):
from ..grid.raster import RasterModelGrid
if not isinstance(grid, RasterModelGrid):
raise NotImplementedError(
"For now, only RasterModelGrids are supported in the imshowhs functions"
)
plot_type_options = ["DEM", "Hillshade", "Drape1", "Drape2"]
if plot_type not in plot_type_options:
raise ValueError(
f"plot_type should be one of the following: {', '.join(plot_type_options)}"
)
if plot_type == "Drape1" and drape1 is None:
raise ValueError(
"if plot_type is Drape1, 'drape1' input argument cannot be None. "
"Provide at least one array with the size of the number of grid "
"nodes as drape1='field_to_be_plotted'"
)
if plot_type == "Drape2" and (drape1 is None or drape2 is None):
raise ValueError(
"if plot_type is Drape2, 'drape1' and 'drape2' input arguments cannot be None. "
"Provide an array for both with the size of the number of grid nodes as "
"drape1='field1_to_be_plotted' and drape2='field2_to_be_plotted'"
)
# Poperties of bounding box of colorbar label, if used:
if add_label_bbox:
bbox_prop = {
"boxstyle": "round",
"pad": 0.1,
"facecolor": "white",
"alpha": 0.7,
"edgecolor": "white",
}
else:
bbox_prop = None
if isinstance(cmap, str):
cmap = plt.colormaps[cmap]
if color_for_closed is not None:
cmap.set_bad(color=color_for_closed)
else:
cmap.set_bad(alpha=0.0)
values.shape = grid.shape
if isinstance(grid, RasterModelGrid):
# somethingToPlot is a flag indicating if any pixels should be plotted.
somethingToPlot = True
if values.ndim != 2:
raise ValueError("values must have ndim == 2")
y = (
np.arange(values.shape[0] + 1) * grid.dy
- grid.dy * 0.5
+ grid.xy_of_lower_left[1]
)
x = (
np.arange(values.shape[1] + 1) * grid.dx
- grid.dx * 0.5
+ grid.xy_of_lower_left[0]
)
ls = LightSource(azdeg=azdeg, altdeg=altdeg)
if cmap is None:
cmap = plt.colormaps["terrain"]
dx = x[1] - x[0]
dy = y[1] - y[0]
if vertical_exa is not None:
ve = vertical_exa
else:
ve = 3
extent = np.array([x[0], x[-1], y[-1], y[0]])
if ticks_km:
extent /= 1e3
ax1 = plt.gca()
if alpha is None:
alpha = 1
if alpha2 is None:
alpha2 = 1
blend_modes = ["hsv", "overlay", "soft"]
if plot_type == "DEM":
kwds = {"cmap": cmap}
(kwds["vmin"], kwds["vmax"]) = (values.min(), values.max())
if (limits is None) and ((vmin is None) and (vmax is None)):
if symmetric_cbar:
(var_min, var_max) = (values.min(), values.max())
limit = max(abs(var_min), abs(var_max))
(kwds["vmin"], kwds["vmax"]) = (-limit, limit)
elif limits is not None:
(kwds["vmin"], kwds["vmax"]) = (limits[0], limits[1])
else:
if vmin is not None:
kwds["vmin"] = vmin
if vmax is not None:
kwds["vmax"] = vmax
val = values.data
rgb = ls.shade(
val,
cmap=cmap,
blend_mode=blend_modes[0],
vert_exag=ve,
dx=dx,
dy=dy,
fraction=0.4,
)
if color_for_closed is not None:
rgb[:, :, :][values.mask] = to_rgba(color_for_closed)
ima = ax1.imshow(rgb, extent=extent, **kwds)
elif plot_type == "Hillshade":
cmap_gray = plt.colormaps["gray"]
if color_for_closed is not None:
cmap_gray.set_bad(color=color_for_closed)
else:
cmap_gray.set_bad(alpha=0.0)
hs_values = ls.hillshade(values.data, vert_exag=ve, dx=dx, dy=dy)
if color_for_closed is not None:
hs_values = np.ma.masked_where(values.mask, hs_values)
ima = plt.imshow(
hs_values,
cmap=cmap_gray,
extent=extent,
)
allow_colorbar = False
elif plot_type == "Drape1" or plot_type == "Drape2":
# Process values from first drape
if isinstance(drape1, str):
values_at_node_drape1 = grid.at_node[drape1]
else:
values_at_node_drape1 = drape1.reshape((-1,))
if values_at_node_drape1.size != grid.number_of_nodes:
raise ValueError("number of values does not match number of nodes")
values_at_node_drape1 = np.ma.masked_where(
grid.status_at_node == grid.BC_NODE_IS_CLOSED, values_at_node_drape1
)
# Add mask if thres_drape1 is given
if thres_drape1 is not None:
# check if any value exceeds threshold
if not np.any(values_at_node_drape1 > thres_drape1):
somethingToPlot = False
values_at_node_drape1 = np.ma.masked_where(
values_at_node_drape1 < thres_drape1, values_at_node_drape1
)
if isinstance(grid, RasterModelGrid):
shape = grid.shape
else:
shape = (-1,)
val1 = values_at_node_drape1.reshape(shape)
kwds = {"cmap": cmap}
(kwds["vmin"], kwds["vmax"]) = (val1.min(), val1.max())
if (limits is None) and ((vmin is None) and (vmax is None)):
if symmetric_cbar:
(var_min, var_max) = (val1.min(), val1.max())
limit = max(abs(var_min), abs(var_max))
(kwds["vmin"], kwds["vmax"]) = (-limit, limit)
elif limits is not None:
(kwds["vmin"], kwds["vmax"]) = (limits[0], limits[1])
else:
if vmin is not None:
kwds["vmin"] = vmin
if vmax is not None:
kwds["vmax"] = vmax
cmap_gray = plt.colormaps["gray"]
if color_for_closed is not None:
cmap_gray.set_bad(color=color_for_closed)
else:
cmap_gray.set_bad(alpha=0.0)
hs_values = ls.hillshade(values.data, vert_exag=ve, dx=dx, dy=dy)
if color_for_closed is not None:
hs_values = np.ma.masked_where(values.mask, hs_values)
ima = plt.imshow(
hs_values,
cmap=cmap_gray,
extent=extent,
)
ima = ax1.imshow(val1, extent=extent, alpha=alpha, **kwds)
if plt_contour:
plt.contour(
x[0:-1] * 1e-3,
y[0:-1] * 1e-3,
val1,
contour_nb,
colors="black",
linewidths=0.2,
)
if somethingToPlot:
# To cartezian coordinates (not if other layers has to be plotted on top!)
if plot_type != "Drape2":
ax1.invert_yaxis()
plt.xticks(fontsize=default_fontsize)
plt.yticks(fontsize=default_fontsize)
# if Drape2, default behavior is to add colorbar of first layer if
# add_double_colorbar == False
if allow_colorbar and (
plot_type == "DEM"
or plot_type == "Drape1"
or (plot_type == "Drape2" and not add_double_colorbar)
):
cb_or = cbar_or
cb_ticks_position = cbar_ticks_position
axins1 = inset_axes(
ax1,
width=cbar_width, # width = 50% of parent_bbox width
height=cbar_height, # height : 5%
loc=cbar_loc,
bbox_transform=ax1.transAxes,
borderpad=0,
bbox_to_anchor=bbox_to_anchor,
)
maxV = kwds["vmax"]
minV = kwds["vmin"]
cb_length = maxV - minV
if maxV <= 10:
cb = plt.colorbar(
ima,
ax=ax1,
cax=axins1,
orientation=cb_or,
ticks=[
np.round(minV + 0.2 * cb_length, 1),
np.round(minV + 0.8 * cb_length, 1),
],
)
elif maxV <= 100:
cb = plt.colorbar(
ima,
ax=ax1,
cax=axins1,
orientation=cb_or,
ticks=[
np.round(minV + 0.2 * cb_length, 0),
np.round(minV + 0.8 * cb_length, 0),
],
)
else:
cb = plt.colorbar(
ima,
ax=ax1,
cax=axins1,
orientation=cb_or,
ticks=[
np.round(0.1 * (minV + 0.2 * cb_length)) * 10,
np.round(0.1 * (minV + 0.8 * cb_length)) * 10,
],
)
axins1.xaxis.set_ticks_position(cb_ticks_position)
cb.ax.tick_params(
labelsize=cbar_tick_size,
color=cbar_tick_color,
labelcolor=cbar_tick_color,
)
# if colorbar_label:
# cb.set_label(colorbar_label, rotation=270)
# # ax1.xaxis.set_label_coords(0,2.5)
if plot_type == "Drape2":
# Process values from first drape
if isinstance(drape2, str):
values_at_node_drape2 = grid.at_node[drape2]
else:
values_at_node_drape2 = drape2.reshape((-1,))
if values_at_node_drape2.size != grid.number_of_nodes:
raise ValueError("number of values does not match number of nodes")
values_at_node_drape2 = np.ma.masked_where(
grid.status_at_node == grid.BC_NODE_IS_CLOSED, values_at_node_drape2
)
# Add mask if thres_drape1 is given
if thres_drape2 is not None:
values_at_node_drape2 = np.ma.masked_where(
values_at_node_drape2 < thres_drape2, values_at_node_drape2
)
if isinstance(grid, RasterModelGrid):
shape = grid.shape
else:
shape = (-1,)
val2 = values_at_node_drape2.reshape(shape)
if cmap2 is None:
cmap2 = plt.colormaps["terrain"]
kwds = {"cmap": cmap2}
(kwds["vmin"], kwds["vmax"]) = (val2.min(), val2.max())
if (limits is None) and ((vmin is None) and (vmax is None)):
if symmetric_cbar:
(var_min, var_max) = (val2.min(), val2.max())
limit = max(abs(var_min), abs(var_max))
(kwds["vmin"], kwds["vmax"]) = (-limit, limit)
elif limits is not None:
(kwds["vmin"], kwds["vmax"]) = (limits[0], limits[1])
else:
if vmin is not None:
kwds["vmin"] = vmin
if vmax is not None:
kwds["vmax"] = vmax
ima2 = ax1.imshow(val2, extent=extent, alpha=alpha2, **kwds)
ax1.invert_yaxis()
# Add colorbars
if add_double_colorbar:
axins1 = inset_axes(
ax1,
width=cbar_width, # width = 50% of parent_bbox width
height=cbar_height, # height : 5%
loc=cbar_loc,
bbox_to_anchor=(-0.005, 0.25, 1, 1),
bbox_transform=ax1.transAxes,
borderpad=0,
)
cb_or = cbar_or
cb_ticks_position = cbar_ticks_position
maxV = np.max(val1)
minV = np.min(val1)
cb_length = maxV - minV
if maxV <= 10:
cb = plt.colorbar(
ima,
ax=ax1,
cax=axins1,
orientation=cb_or,
ticks=[
np.round(minV + 0.2 * cb_length, 1),
np.round(minV + 0.8 * cb_length, 1),
],
)
elif maxV <= 100:
cb = plt.colorbar(
ima,
ax=ax1,
cax=axins1,
orientation=cb_or,
ticks=[
np.round(minV + 0.2 * cb_length, 0),
np.round(minV + 0.8 * cb_length, 0),
],
)
else:
cb = plt.colorbar(
ima,
ax=ax1,
cax=axins1,
orientation=cb_or,
ticks=[
np.round(0.1 * (minV + 0.2 * cb_length)) * 10,
np.round(0.1 * (minV + 0.8 * cb_length)) * 10,
],
)
cb.ax.tick_params(
labelsize=cbar_tick_size,
color=cbar_tick_color,
labelcolor=cbar_tick_color,
)
axins1.xaxis.set_ticks_position(cb_ticks_position)
axins1.set_xlabel(
var_name,
usetex=True,
fontsize=default_fontsize,
rotation=0,
color=cbar_label_color,
fontweight=cbar_label_fontweight,
bbox=bbox_prop,
)
axins1.xaxis.set_label_coords(0.5, y_label_offSet_var_1)
axins2 = inset_axes(
ax1,
width=cbar_width, # width = 50% of parent_bbox width
height=cbar_height, # height : 5%
loc=cbar_loc,
bbox_to_anchor=(-0.005, 0.15, 1, 1),
bbox_transform=ax1.transAxes,
borderpad=0,
)
cb_or = cbar_or
cb_ticks_position = cbar_ticks_position2
maxV = np.max(val2)
minV = np.min(val2)
cb_length = maxV - minV
if maxV <= 10:
cb = plt.colorbar(
ima2,
ax=ax1,
cax=axins2,
orientation=cb_or,
ticks=[
np.round(minV + 0.2 * cb_length, 1),
np.round(minV + 0.8 * cb_length, 1),
],
)
elif maxV <= 100:
cb = plt.colorbar(
ima2,
ax=ax1,
cax=axins2,
orientation=cb_or,
ticks=[
np.round(minV + 0.2 * cb_length, 0),
np.round(minV + 0.8 * cb_length, 0),
],
)
else:
cb = plt.colorbar(
ima2,
ax=ax1,
cax=axins2,
orientation=cb_or,
ticks=[
np.round(0.1 * (minV + 0.2 * cb_length)) * 10,
np.round(0.1 * (minV + 0.8 * cb_length)) * 10,
],
)
cb.ax.tick_params(
labelsize=cbar_tick_size,
color=cbar_tick_color,
labelcolor=cbar_tick_color,
)
axins2.xaxis.set_ticks_position(cb_ticks_position)
axins2.set_xlabel(
var_name_two,
usetex=True,
fontsize=default_fontsize,
rotation=0,
color=cbar_label_color,
fontweight=cbar_label_fontweight,
bbox=bbox_prop,
)
axins2.xaxis.set_label_coords(0.5, y_label_offSet_var_2)
# If nothing to plot
else:
ax1.invert_yaxis()
if grid_units[1] is None and grid_units[0] is None:
grid_units = grid.axis_units
if grid_units[1] == "-" and grid_units[0] == "-":
ax1.set_xlabel(
"Easting", fontweight=fontweight_xlabel, fontsize=default_fontsize
)
ax1.set_ylabel(
"Northing", fontweight=fontweight_ylabel, fontsize=default_fontsize
)
else:
ax1.set_xlabel(
"Easting, %s" % grid_units[1],
fontweight=fontweight_xlabel,
fontsize=default_fontsize,
)
ax1.set_ylabel(
"Northing, %s" % grid_units[1],
fontweight=fontweight_ylabel,
fontsize=default_fontsize,
)
else:
ax1.set_xlabel(
"Easting, %s" % grid_units[1],
fontweight=fontweight_xlabel,
fontsize=default_fontsize,
)
ax1.set_ylabel(
"Northing, %s" % grid_units[1],
fontweight=fontweight_ylabel,
fontsize=default_fontsize,
)
if plot_name is not None:
plt.title(f"{plot_name}")
if (
somethingToPlot
and (var_name is not None or var_units is not None)
and plot_type != "Drape2"
):
if var_name is not None:
assert type(var_name) is str
if var_units is not None:
assert type(var_units) is str
colorbar_label = var_name + " (" + var_units + ")"
else:
colorbar_label = var_name
else:
assert type(var_units) is str
colorbar_label = "(" + var_units + ")"
assert type(colorbar_label) is str
if allow_colorbar:
cb.set_label(
colorbar_label,
fontsize=default_fontsize,
labelpad=colorbar_label_y,
color=cbar_label_color,
x=colorbar_label_x,
fontweight=cbar_label_fontweight,
bbox=bbox_prop,
)
if color_for_background is not None:
plt.gca().set_facecolor(color_for_background)
if output is not None:
if isinstance(output, str):
plt.savefig(output)
plt.clf()
elif output:
plt.show()
return ax1