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from ipywidgets import widgets
import numpy as np
import colorsys
from bokeh import io as bkio
from bokeh import plotting as bkp
from bokeh import models as bkm
from import value
from bokeh.models import FixedTicker
from bokeh.models.mappers import LinearColorMapper
from bokeh.plotting import ColumnDataSource
from bokeh.models import HoverTool
def interact(*args, **kwargs):
widgets.interact(*args, **kwargs)
IntSlider = widgets.IntSlider
FloatSlider = widgets.FloatSlider
## Disable autoscrolling
from IPython.display import display, Javascript
disable_js = """
IPython.OutputArea.prototype._should_scroll = function(lines) {
return false;
## Load bokeh for jupyter
## Routines for adjusting figures
def tweak_fig(fig, grid=False, three_ticks_enable=False):
if three_ticks_enable:
if not grid:
fig.toolbar.logo = None
def tight_layout(fig):
fig.min_border_top = 35
fig.min_border_bottom = 35
fig.min_border_right = 35
fig.min_border_left = 35
def three_ticks(fig):
x_min, x_max = fig.x_range.start, fig.x_range.end
y_min, y_max = fig.y_range.start, fig.y_range.end
x_ticks = [x_min, 0, x_max]
y_ticks = [x_min, 0, x_max]
def disable_minor_ticks(fig):
fig.axis.major_label_text_font_size = value('8pt')
fig.axis.minor_tick_line_color = None
fig.axis.major_tick_in = 0
def disable_grid(fig):
fig.xgrid.grid_line_color = None
fig.ygrid.grid_line_color = None
## Figure 1
def curve(xs, ys, ys_dash, title='Child growth curve', y_range=[-0.5, 9], **kwargs):
"""Plots a continuous curve and a dashed one for Fig. 1."""
fig = bkp.figure(x_range=[-0.5, 25.5], y_range=y_range,
title=title, tools="",
plot_width=320, plot_height=250, **kwargs)
tweak_fig(fig, three_ticks_enable=False, grid=False)
fig.title.text_font_size = '12pt'
fig.title.align = 'center'
line_dash = fig.line(xs, ys_dash, line_width=2, line_dash='dashed')
line_ref = fig.line(xs, ys, line_width=2)
return fig,
def fig1(xs, g, P_sb, P_sc, I, R=8.4/2):
"""Compute y-values, and lay out Fig. 1 plots."""
kwargs = {}
ys_1a = [g(x, 8.4) for x in xs]
ys_1a_dashed = [g(x, R) for x in xs]
fig1a, data_1a = curve(xs, ys_1a, ys_1a_dashed, y_range=[-0.5, 15],
title='Child growth curve', **kwargs)
fig1a.xaxis.axis_label = "Age (month)"
fig1a.yaxis.axis_label = "Head radius R (cm)"
ys_1b = [P_sb(x, 8.4) for x in xs]
ys_1b_dashed = [P_sb(x, R) for x in xs]
fig1b, data_1b = curve(xs, ys_1b, ys_1b_dashed, y_range=[-0.05, 1.05],
title='Birth survival curve', **kwargs)
fig1b.xaxis.axis_label = "Birth Age T (month)"
fig1b.yaxis.axis_label = "P(survive birth)"
ys_1c = [P_sc(x, I(8.4)) for x in xs]
ys_1c_dashed = [P_sc(x, I(R)) for x in xs]
fig1c, data_1c = curve(xs, ys_1c, ys_1c_dashed, y_range=[-0.05, 1.05],
title='Childhood survival curve', **kwargs)
fig1c.xaxis.axis_label = "Time until maturity M (month)"
fig1c.yaxis.axis_label = "P(survive childhood)"
fig = bkp.gridplot([[fig1a, fig1b, fig1c]])
#fig.logo = None
# fig.toolbar.location = None
handle =, notebook_handle=True)
return handle, (data_1a, data_1b, data_1c)
def update_fig1(datas, g, P_sb, P_sc, r):
"""Refresh plots of Fig 1 for a new value of `r`."""
handle, figdatas = datas
for figdata, f in zip(figdatas, [g, P_sb, P_sc]):
figdata['y'] = [f(x, r) for x in figdata['x']]
## Figure 2A
palette_20 = ['#d52b22', '#db2c23', '#e52e24', '#d62b22',
'#ce2a21', '#ce3021', '#df4b23', '#d15b21',
'#dc7423', '#e78d25', '#efa626', '#ddab23',
'#fdda28', '#f4f127', '#e8f825', '#e6f625',
'#e7f625', '#e1ec5d', '#f2fba0', '#f4f7db']
palette_20 = ([(3*i+198, int(i/19*(3*i+198)), 0) for i in range(20)]
+[(255, 255, int(255*i/4)) for i in range(4)])
palette_20 = ["#%02x%02x%02x" % rgb for rgb in palette_20]
def fig2a(D, x_max=30, y_max=10, palette=palette_20,
title='P(survive to adulthood)', show=True,
plot_width=500, plot_height=400, tools=''):
fig = bkp.figure(x_range=(0, x_max), y_range=(0, y_max),
plot_width=plot_width, plot_height=plot_height,
tools=tools, title=title)
fig.title.text_font_size = '12pt'
fig.title.align = 'center'
tweak_fig(fig, three_ticks_enable=False, grid=False)
cmap = LinearColorMapper(high=1.0, low=0.0, palette=palette)
Dmat = fig.image(image=[D], x=0, y=0, dw=x_max, dh=y_max, color_mapper=cmap)
fig.xaxis.axis_label = "Birth age (month)"
fig.yaxis.axis_label = "Brain size (radius, cm)"
# color_bar = bkm.ColorBar(color_mapper=cmap, label_standoff=12, location=(0,0),
# border_line_color=None, bar_line_color='black', major_tick_line_color='black')
# fig.add_layout(color_bar, 'right')
if show:
handle =, notebook_handle=True)
handle = None
return handle, fig,
def update_fig2a(fig_data, D, gamma, V):
"""Refresh plots of Fig 1 for a new value of `r`."""
print('recomputing fig2a...')
handle, fig, data = fig_data
data['image'] = [D]
fig.title.text = 'P(survive to adulthood) gamma={}, V={}'.format(gamma, V)
## Figure 2B
palette_2 = ['#dddddd', '#ffffff']
def line_color():
"""Return a random (bright) color"""
r, g, b = colorsys.hsv_to_rgb(np.random.random(), 0.65, 0.95)
return '#{0:02x}{1:02x}{2:02x}'.format(int(255*r), int(255*g), int(255*b))
def fig2b(traces, D, x_max=30, y_max=10):
return fig2b_aux(traces, D, x_max=30, y_max=10, axes=('T', 'R'),
line_width=3, radius=0.2)
def intelligence_radius_fig(traces):
return fig2b_aux(traces, None, x_max=11, y_max=10, axes=('I', 'R'),
line_width=1, radius=0.05, display_D=False,
display_start=False, display_end=True)
def fig2b_aux(traces, D, x_max=30, y_max=10, axes=('T', 'R'), line_width=3, radius=0.2,
display_D=True, display_start=True, display_end=False):
x_idx = ('R', 'T', 'I').index(axes[0])
y_idx = ('R', 'T', 'I').index(axes[1])
if display_D:
handle, fig, data = fig2a(D, x_max=x_max, y_max=y_max, palette=palette_2, show=False,
plot_width=900, plot_height=720, title='Population dynamics',
fig = bkp.figure(x_range=(0, x_max), y_range=(0, y_max),
plot_width=660, plot_height=600,
tools='pan,wheel_zoom,reset,save', title='Intelligence/Brain radius relationship')
tweak_fig(fig, three_ticks_enable=False, grid=False)
fig.xaxis.axis_label = ["Brain size (radius, cm)", "Birth age (month)", "Intelligence"][x_idx]
fig.yaxis.axis_label = ["Brain size (radius, cm)", "Birth age (month)", "Intelligence"][y_idx]
colors = []
for trace in traces:
color = line_color()
fig.line([RTI[x_idx] for RTI in trace], [RTI[y_idx] for RTI in trace],
line_width=line_width, line_join='bevel', color=color)
source = ColumnDataSource(
x=[trace[0][x_idx] for trace in traces],
y=[trace[0][y_idx] for trace in traces],
x_end=[trace[-1][x_idx] for trace in traces],
y_end=[trace[-1][y_idx] for trace in traces],
R_start=['{:.2f}'.format(trace[0][0]) for trace in traces],
T_start=['{:.2f}'.format(trace[0][1]) for trace in traces],
I_start=['{:.2f}'.format(trace[0][2]) for trace in traces],
R_end=['{:.2f}'.format(trace[-1][0]) for trace in traces],
T_end=['{:.2f}'.format(trace[-1][1]) for trace in traces],
I_end=['{:.2f}'.format(trace[-1][2]) for trace in traces],
if display_start:
# radius=radius, color=colors
g_r ='x', 'y', color='color', radius='radius', size='size', source=source)
if display_end:
g_r = fig.square('x_end', 'y_end', size='size', color='color', source=source)
g_hover = bkm.HoverTool(renderers=[g_r],
tooltips=[("R_start", "@R_start"),
("R_end", "@R_end"),
("T_start", "@T_start"),
("T_end", "@T_end"),
("I_start", "@I_start"),
("I_end", "@I_end"),