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Adapted the plot to not have the y axis' legend hidden by the matlpotlib icons, added a better looking legend to the plot, made the comparison results work, added cummulative doses' curves for ExposureComparissonResult and ExposureModelResult, modified the viral load to be displayed as scientific writing on the UI

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Germain Personne 2022-05-12 16:26:45 +02:00
parent 9147b73a90
commit 18cce44afa
1 changed files with 25 additions and 16 deletions
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41
cara/apps/expert.py
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@ -9,8 +9,9 @@ import matplotlib.figure
import numpy as np
import mplcursors
from matplotlib import pyplot as plt
from numpy import object_
from cara import data, models, state
import matplotlib.lines as mlines
import matplotlib.patches as patches
def collapsible(widgets_to_collapse: typing.List, title: str, start_collapsed=False):
collapsed = widgets.Accordion([widgets.VBox(widgets_to_collapse)])
@ -107,11 +108,10 @@ def ipympl_canvas(figure):
class ExposureModelResult(View):
def __init__(self):
self.figure = matplotlib.figure.Figure(figsize=(9, 5))
self.figure = matplotlib.figure.Figure(figsize=(9, 6))
ipympl_canvas(self.figure)
self.html_output = widgets.HTML()
self.ax = self.figure.add_subplot(1, 1, 1)
self.figure.subplots_adjust(left=8, right=9)
self.ax2 = self.ax.twinx()
self.concentration_line = None
self.concentration_area = None
@ -124,6 +124,15 @@ class ExposureModelResult(View):
self.figure.canvas,
])
def initialize_axes(self) -> matplotlib.figure.Axes:
ax = self.figure.add_subplot(1, 1, 1)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.set_xlabel('Time (hours)')
ax.set_ylabel('Concentration ($virions/m^{3}$)')
ax.set_title('Concentration of virions')
return ax
def update(self, model: models.ExposureModel):
self.update_plot(model)
self.update_textual_result(model)
@ -150,7 +159,7 @@ class ExposureModelResult(View):
ax.set_xlabel('Time (hours)')
ax.set_ylabel('Mean concentration ($virions/m^{3}$)')
ax.set_title('Concentration of virions and Cumulative dose')
ax.set_title('Concentration of virions \nand Cumulative dose')
#cursor = SnaptoCursor(self.ax, ts, concentration)
@ -191,15 +200,14 @@ class ExposureModelResult(View):
cumulative_top = max([1e-5, max(cumulative_doses)])
self.ax2.set_ylim(bottom=0., top=cumulative_top)
self.ax.set_xlim(left = min(model.concentration_model.infected.presence.present_times[0]), right = max(model.concentration_model.infected.presence.present_times[1]))
self.ax.set_xlim(left = min(min(model.concentration_model.infected.presence.present_times[0]), min(model.exposed.presence.present_times[0])), right = max(max(model.concentration_model.infected.presence.present_times[1]), max(model.exposed.presence.present_times[1])))
figure_legends = [mlines.Line2D([], [], color='#3530fe', markersize=15, label='Mean concentration'),
mlines.Line2D([], [], color='#0000c8', markersize=15, ls="dotted", label='Cumulative dose'),
patches.Patch(edgecolor="#96cbff", facecolor='#96cbff', label='Presence of exposed person(s)')]
self.figure.legend(handles=figure_legends)
legend = self.ax.legend(bbox_to_anchor=(1.15, 1), frameon=False)
self.ax2.legend(bbox_to_anchor=(1.15, 0.89), frameon=False)
#sself.marker=plt.connect('motion_notify_event', mouse_move)
self.figure.canvas.draw()
self.figure.tight_layout()
return legend
def update_textual_result(self, model: models.ExposureModel):
lines = []
@ -215,7 +223,7 @@ class ExposureModelResult(View):
R0 = np.round(np.array(model.reproduction_number()).mean(), 1)
lines.append(f'Reproduction number (R0): {R0}')
self.html_output.value = '<br>\n'.join(lines)
self.html_output.value = '<br>\n'.join(lines)
class ExposureComparissonResult(View):
@ -223,7 +231,7 @@ class ExposureComparissonResult(View):
self.figure = matplotlib.figure.Figure(figsize=(9, 6))
ipympl_canvas(self.figure)
self.html_output = widgets.HTML()
self.ax = self.figure.add_subplot(2, 1, 2)
self.ax = self.figure.add_subplot(1, 1, 1)
self.ax2 = self.ax.twinx()
self.concentration_line = None
self.cumulative_line = None
@ -672,16 +680,17 @@ class ModelWidgets(View):
def on_expiration_change(change):
expiration = models.Expiration.types[change['new']]
node.dcs_update_from(expiration)
expiration_choice.observe(on_expiration_change, names=['value'])
return widgets.HBox([widgets.Label("Expiration"), expiration_choice], layout=widgets.Layout(justify_content='space-between'))
def _build_viral_load(self, node):
viral_load_in_sputum = widgets.IntText(value=node.viral_load_in_sputum, PlaceHolder='1e9')
viral_load_in_sputum = widgets.Text(continuous_update=False, value=("{:.2e}".format(node.viral_load_in_sputum)))
def viral_load_change(change):
node.viral_load_in_sputum = change['new']
viral_load_in_sputum.value = "{:.2e}".format(float(change['new']))
node.viral_load_in_sputum = float(viral_load_in_sputum.value)
viral_load_in_sputum.observe(viral_load_change, names=['value'])