def set_axis_integer(ax_: plt.Axes, axis='x'):
if axis == 'x':
axis = ax_.get_xaxis()
elif axis == 'y':
axis = ax_.get_yaxis()
else:
raise ValueError
axis.set_major_locator(MultipleLocator(1))
def _remove_ticklabels(axis: plt.Axes):
axis.get_yaxis().set_ticklabels([])
axis.get_xaxis().set_ticklabels([])
def _remove_ticklabels(axis: plt.Axes):
axis.get_yaxis().set_ticklabels([])
axis.get_xaxis().set_ticklabels([])
def hexplot_TEST(
node_data,
decimals: int = 0,
var_lim: Iterable = None,
c: object = None,
lc: str = 'k',
#edge_data: Dict=None, edge_c='r', # EDGE DATA NOT IMPLEMENTED YET
ax: plt.Axes = None,
scale_factor: float = 0.015):
"""
Plot a map of the hexagonal lattice of the megaphragma compound eye. Each ommatidium will be labelled and coloured
according to the strings and (r, g, b, a) values passed with node_data. This will also take a 1-col dataframe indexed by om
TODO: fix dataframe input options, type of cmap as an arg, use plt.scatter instead of all the networkx functions?
:param node_data: Dict, {om: {'label': str,
{'outline': matplotlib line spec, e.g. '-',
{'colour': (rgba)}}
:param edge_data:
:param ax: plt.Axes, if None, will plot to current Axis
:param scale_factor: float, controls the spacing between nodes
:c: Default node colour (if node_data: colours is None)
:param e_colour: Default edge colour (if edge_data is used)
:return:
"""
if c == None: # default color
c = (0.2, 0.2, 0.2, 1)
if not isinstance(node_data, Dict):
node_data = __from_series(node_data,
c=c,
var_lim=var_lim,
decimals=decimals)
if ax == None:
ax = plt.gca()
om_list = sorted([str(om) for om in node_data.keys()])
pos = [om_to_hex(o) for o in om_list] # 2D figure coords of each om
node_colours = [] #dict.fromkeys(om_list)
node_outline = [] #dict.fromkeys(om_list)
node_labels = [] #dict.fromkeys(om_list)
#name_to_ind =
for om, xy in zip(om_list, pos):
if node_data[om].get('label', None) == None:
label = om
elif isinstance(node_data.get('label'), (int, float)):
label = str(round(node_data.get('label'), decimals))
else:
label = node_data.get('label')
if (node_data[om].get('colour') == None):
fill_c = c
else:
fill_c = node_data[om].get('colour')
x, y = (xy[0] * 0.01, xy[1] * 0.01)
#y = xy[1] * 0.01
ax.scatter(xy[0], xy[1], marker='H', color=fill_c, s=100)
ax.annotate(label, xy, fontsize=8, color='w', ha='center', va='center')
#ax.set_xlim((-30, 4))
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
#plt.axis('off')
ax.set_aspect('equal')
return ax
def set_axes_properties(ax: plt.Axes, **kwargs) -> None:
"""
Ease the configuration of a :class:`matplotlib.axes.Axes` object.
Parameters
----------
ax : matplotlib.axes.Axes
The axes.
Keyword arguments
-----------------
fontsize : int
Font size to use for the plot titles, and axes ticks and labels.
Defaults to 12.
title_center : str
The center title. Defaults to an empty string.
title_left : str
The left title. Defaults to an empty string.
title_right : str
The right title. Defaults to an empty string.
x_label : str
The x-axis label. Defaults to an empty string.
x_labelcolor : str
Color of the x-axis label. Defaults to 'black'.
x_lim : Sequence[int]
Data limits for the x-axis. Defaults to `None`, i.e., the data limits
will be left unchanged.
invert_xaxis : bool
`True` to make to invert the x-axis, `False` otherwise.
Defaults to `False`.
x_scale : str
The x-axis scale. Defaults to 'linear'.
x_ticks : sequence[float]
Sequence of x-axis ticks location. Defaults to `None`.
x_ticklabels : sequence[str]
Sequence of x-axis ticks labels. Defaults to `None`.
x_ticklabels_color : str
Color for the x-axis ticks labels. Defaults to 'black'.
x_ticklabels_rotation : float
Rotation angle of the x-axis ticks labels. Defaults to 0.
xaxis_minor_ticks_visible : bool
`True` to show all ticks, either labelled or unlabelled,
`False` to show only the labelled ticks. Defaults to `False`.
xaxis_visible : bool
`False` to make the x-axis invisible. Defaults to `True`.
y_label : str
The y-axis label. Defaults to an empty string.
y_labelcolor : str
Color of the y-axis label. Defaults to 'black'.
y_lim : Sequence[int]
Data limits for the y-axis. Defaults to `None`, i.e., the data limits
will be left unchanged.
invert_yaxis : bool
`True` to make to invert the y-axis, `False` otherwise.
Defaults to `False`.
y_scale : str
The y-axis scale. Defaults to 'linear'.
y_ticks : sequence[float]
Sequence of y-axis ticks location. Defaults to `None`.
y_ticklabels : sequence[str]
Sequence of y-axis ticks labels. Defaults to `None`.
y_ticklabels_color : str
Color for the y-axis ticks labels. Defaults to 'black'.
y_ticklabels_rotation : float
Rotation angle of the y-axis ticks labels. Defaults to 0.
yaxis_minor_ticks_visible : bool
`True` to show all ticks, either labelled or unlabelled,
`False` to show only the labelled ticks. Defaults to :obj:`False`.
yaxis_visible : bool
:obj:`False` to make the y-axis invisible. Defaults to :obj:`True`.
z_label : str
The z-axis label. Defaults to an empty string.
z_labelcolor : str
Color of the z-axis label. Defaults to 'black'.
z_lim : Sequence[int]
Data limits for the z-axis. Defaults to :obj:`None`, i.e., the data limits
will be left unchanged.
invert_zaxis : bool
:obj:`True` to make to invert the z-axis, :obj:`False` otherwise.
Defaults to :obj:`False`.
z_scale : str
The z-axis scale. Defaults to 'linear'.
z_ticks : sequence[float]
Sequence of z-axis ticks location. Defaults to :obj:`None`.
z_ticklabels : sequence[str]
Sequence of z-axis ticks labels. Defaults to :obj:`None`.
z_ticklabels_color : str
Rotation angle of the z-axis ticks labels. Defaults to 0.
z_ticklabels_rotation : float
Color for the z-axis ticks labels. Defaults to 'black'.
zaxis_minor_ticks_visible : bool
:obj:`True` to show all ticks, either labelled or unlabelled,
:obj:`False` to show only the labelled ticks. Defaults to :obj:`False`.
zaxis_visible : bool
:obj:`False` to make the z-axis invisible. Defaults to :obj:`True`.
legend_on : bool
:obj:`True` to show the legend, :obj:`False` otherwise. Defaults to :obj:`False`.
legend_loc : str
String specifying the location where the legend should be placed.
Defaults to 'best'; please see :func:`matplotlib.pyplot.legend` for all
the available options.
legend_bbox_to_anchor : Sequence[float]
4-items tuple defining the box used to place the legend. This is used in
conjuction with `legend_loc` to allow arbitrary placement of the legend.
legend_framealpha : float
Legend transparency. It should be between 0 and 1; defaults to 0.5.
legend_ncol : int
Number of columns into which the legend labels should be arranged.
Defaults to 1.
text : str
Text to be added to the figure as anchored text. Defaults to :obj:`None`,
meaning that no text box is shown.
text_loc : str
String specifying the location where the text box should be placed.
Defaults to 'upper right'; please see :class:`matplotlib.offsetbox.AnchoredText`
for all the available options.
grid_on : bool
:obj:`True` to show the plot grid, :obj:`False` otherwise.
Defaults to :obj:`False`.
grid_properties : dict
Keyword arguments specifying various settings of the plot grid.
"""
fontsize = kwargs.get("fontsize", 12)
# title
title_center = kwargs.get("title_center", "")
title_left = kwargs.get("title_left", "")
title_right = kwargs.get("title_right", "")
# x-axis
x_label = kwargs.get("x_label", "")
x_labelcolor = kwargs.get("x_labelcolor", "black")
x_lim = kwargs.get("x_lim", None)
invert_xaxis = kwargs.get("invert_xaxis", False)
x_scale = kwargs.get("x_scale", "linear")
x_ticks = kwargs.get("x_ticks", None)
x_ticklabels = kwargs.get("x_ticklabels", None)
x_ticklabels_color = kwargs.get("x_ticklabels_color", "black")
x_ticklabels_rotation = kwargs.get("x_ticklabels_rotation", 0)
x_tickformat = kwargs.get("x_tickformat", None)
xaxis_minor_ticks_visible = kwargs.get("xaxis_minor_ticks_visible", False)
xaxis_visible = kwargs.get("xaxis_visible", True)
# y-axis
y_label = kwargs.get("y_label", "")
y_labelcolor = kwargs.get("y_labelcolor", "black")
y_lim = kwargs.get("y_lim", None)
invert_yaxis = kwargs.get("invert_yaxis", False)
y_scale = kwargs.get("y_scale", "linear")
y_ticks = kwargs.get("y_ticks", None)
y_ticklabels = kwargs.get("y_ticklabels", None)
y_ticklabels_color = kwargs.get("y_ticklabels_color", "black")
y_ticklabels_rotation = kwargs.get("y_ticklabels_rotation", 0)
y_tickformat = kwargs.get("y_tickformat", None)
yaxis_minor_ticks_visible = kwargs.get("yaxis_minor_ticks_visible", False)
yaxis_visible = kwargs.get("yaxis_visible", True)
# legend
legend_on = kwargs.get("legend_on", False)
legend_loc = kwargs.get("legend_loc", "best")
legend_bbox_to_anchor = kwargs.get("legend_bbox_to_anchor", None)
legend_framealpha = kwargs.get("legend_framealpha", 0.5)
legend_ncol = kwargs.get("legend_ncol", 1)
legend_fontsize = kwargs.get("legend_fontsize", fontsize)
# textbox
text = kwargs.get("text", None)
text_loc = kwargs.get("text_loc", "")
# grid
grid_on = kwargs.get("grid_on", False)
grid_properties = kwargs.get("grid_properties", None)
rcParams["font.size"] = fontsize
# rcParams['text.usetex'] = True
# plot titles
if ax.get_title(loc="center") == "":
ax.set_title(title_center, loc="center", fontsize=rcParams["font.size"] - 1)
if ax.get_title(loc="left") == "":
ax.set_title(title_left, loc="left", fontsize=rcParams["font.size"] - 1)
if ax.get_title(loc="right") == "":
ax.set_title(title_right, loc="right", fontsize=rcParams["font.size"] - 1)
# axes labels
if ax.get_xlabel() == "":
ax.set(xlabel=x_label)
if ax.get_ylabel() == "":
ax.set(ylabel=y_label)
# axes labelcolors
if ax.get_xlabel() != "" and x_labelcolor != "":
ax.xaxis.label.set_color(x_labelcolor)
if ax.get_ylabel() != "" and y_labelcolor != "":
ax.yaxis.label.set_color(y_labelcolor)
# axes limits
if x_lim is not None:
ax.set_xlim(x_lim)
if y_lim is not None:
ax.set_ylim(y_lim)
# invert the axes
if invert_xaxis:
ax.invert_xaxis()
if invert_yaxis:
ax.invert_yaxis()
# axes scale
if x_scale is not None:
ax.set_xscale(x_scale)
if y_scale is not None:
ax.set_yscale(y_scale)
# axes ticks
if x_ticks is not None:
ax.get_xaxis().set_ticks(x_ticks)
if y_ticks is not None:
ax.get_yaxis().set_ticks(y_ticks)
# axes tick labels
if x_ticklabels is not None:
ax.get_xaxis().set_ticklabels(x_ticklabels)
if y_ticklabels is not None:
ax.get_yaxis().set_ticklabels(y_ticklabels)
# axes tick labels color
if x_ticklabels_color != "":
ax.tick_params(axis="x", colors=x_ticklabels_color)
if y_ticklabels_color != "":
ax.tick_params(axis="y", colors=y_ticklabels_color)
# axes tick format
if x_tickformat is not None:
ax.xaxis.set_major_formatter(FormatStrFormatter(x_tickformat))
if y_tickformat is not None:
ax.yaxis.set_major_formatter(FormatStrFormatter(y_tickformat))
# axes tick labels rotation
plt.xticks(rotation=x_ticklabels_rotation)
plt.yticks(rotation=y_ticklabels_rotation)
# unlabelled axes ticks
if not xaxis_minor_ticks_visible:
ax.get_xaxis().set_tick_params(which="minor", size=0)
ax.get_xaxis().set_tick_params(which="minor", width=0)
if not yaxis_minor_ticks_visible:
ax.get_yaxis().set_tick_params(which="minor", size=0)
ax.get_yaxis().set_tick_params(which="minor", width=0)
# axes visibility
if not xaxis_visible:
ax.get_xaxis().set_visible(False)
if not yaxis_visible:
ax.get_yaxis().set_visible(False)
# legend
if legend_on:
if legend_bbox_to_anchor is None:
ax.legend(
loc=legend_loc,
framealpha=legend_framealpha,
ncol=legend_ncol,
fontsize=legend_fontsize,
)
else:
ax.legend(
loc=legend_loc,
framealpha=legend_framealpha,
ncol=legend_ncol,
fontsize=legend_fontsize,
bbox_to_anchor=legend_bbox_to_anchor,
)
# text box
if text is not None:
ax.add_artist(AnchoredText(text, loc=text_locations[text_loc]))
# plot grid
if grid_on:
gps = grid_properties if grid_properties is not None else {}
ax.grid(True, **gps)
