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import numpy as np
import matplotlib.pyplot as plt
class PlotOverview:
"""
Class for plotting list of views at different points in instrument
"""
def __init__(self, event_plotter_list, view_list):
"""
Stores list of event plotters and views, able to create figure
parameters:
event_plotter_list : list of EventPlotter objects
EventPlotter objects for each investigated point in instrument
view_list : list of View objects
View specifications which will all be used for each point
"""
self.event_plotter_list = event_plotter_list
self.n_points = len(event_plotter_list)
self.views = view_list
self.n_plots = len(view_list)
def plot_all(self, figsize=None, same_scale=True):
"""
Plots all views for all guide points
The same_scale features is enabled per default, but even then
individual Views can opt out of being drawn on the same scale.
Parameters:
figsize : tuple of length 2
size of figure, default scales according to number of plots
same_scale : bool
Allow the use of the same scale feature (default)
"""
if same_scale:
self.set_same_scale()
if figsize is None:
# Scale size after number of plots
figsize = (1 + self.n_plots*3, self.n_points*3)
fig, axs = plt.subplots(self.n_points, self.n_plots,
figsize=figsize, squeeze=False)
for plotter, ax_row in zip(self.event_plotter_list, axs):
major_label_set = False
for view, ax in zip(self.views, ax_row):
plotter.plot(view=view, fig=fig, ax=ax)
if not major_label_set:
ylabel = ax.get_ylabel()
row_name = plotter.name.replace("_", "\\ ")
new_label = r"$\bf{" + row_name + "}$" + "\n" + ylabel
ax.set_ylabel(new_label)
major_label_set = True
fig.tight_layout()
def set_same_scale(self):
"""
Uses minimum and maximum of each dataset to find global min/max
"""
for view in self.views:
if not view.same_scale:
# View controls same scale or not
continue
axis1_mins = []
axis1_maxs = []
axis2_mins = []
axis2_maxs = []
for plotter in self.event_plotter_list:
lim_min, lim_max = plotter.get_view_limits_axis1(view)
axis1_mins.append(lim_min)
axis1_maxs.append(lim_max)
lim_min, lim_max = plotter.get_view_limits_axis2(view)
axis2_mins.append(lim_min)
axis2_maxs.append(lim_max)
view.set_axis1_limits(np.nanmin(axis1_mins), np.nanmax(axis1_maxs))
if view.axis2 is not None:
view.set_axis2_limits(np.nanmin(axis2_mins), np.nanmax(axis2_maxs))
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