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pc4nanobio.py
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pc4nanobio.py
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# coding: utf-8
# In[2]:
# %load bin/pc4nanobio.py
# %load pc4nanobio.py
import ipywidgets as widgets
from ipywidgets import Layout, Button, Box, HBox, VBox, BoundedFloatText
#from ipywidgets import interact, interactive
from subprocess import Popen, PIPE, STDOUT
from hublib.cmd import runCommand
from hublib.ui import RunCommand
import xml.etree.ElementTree as ET
import matplotlib.pyplot as plt
import matplotlib.colors as mplc
import scipy.io
import sys, os, glob, random, math, pathlib
import numpy as np
from collections import deque
join_our_list = "(Join/ask questions at https://groups.google.com/forum/#!forum/physicell-users)\n"
get_ipython().run_line_magic('matplotlib', 'inline')
#===== Units =====
micron_units = widgets.HTMLMath(value=r"$\mu M$")
diffusion_coef_units = widgets.HTMLMath(value=r"$\frac{\mu M^2}{min}$")
survival_lifetime_units = widgets.HTMLMath(value=r"$min$")
min_units = widgets.HTMLMath(value=r"$min$")
min_inv_units = widgets.HTMLMath(value=r"$\frac{1}{min}$")
mmHg_units = widgets.HTMLMath(value=r"$mmHg$")
constWidth = '180px'
constWidth2 = '150px'
constWidth3 = '200px'
tab_height = '400px'
tab_height = '500px'
tab_layout = widgets.Layout( width='800px', # border='2px solid black',
height=tab_height, overflow_y='scroll',)
np_tab_layout = widgets.Layout( width='800px', # border='2px solid black',
height='350px', overflow_y='scroll',)
#tab_layout.height = '500px'
# my_domain = [0,0,-10, 2000,2000,10, 20,20,20] # [x,y,zmin, x,y,zmax, x,y,zdelta]
label_domain = widgets.Label('Domain ($\mu M$):')
xmin = widgets.FloatText(
description='$X_{min}$',
# disabled=False,
layout = Layout(width = constWidth),
)
ymin = widgets.FloatText(
description='$Y_{min}$',
layout = Layout(width = constWidth),
)
zmin = widgets.FloatText(
description='$Z_{min}$',
layout = Layout(width = constWidth),
)
xmax = widgets.FloatText(
description='$X_{max}$',
layout = Layout(width = constWidth),
)
ymax = widgets.FloatText(
description='$Y_{max}$',
layout = Layout(width = constWidth),
)
zmax = widgets.FloatText(
description='$Z_{max}$',
layout = Layout(width = constWidth),
)
tmax = widgets.BoundedFloatText(
min = 0.,
max = 100000000,
description='$Time_{max}$',
layout = Layout(width = constWidth),
)
xdelta = widgets.BoundedFloatText(
min = 1.,
description='$X_{delta}$',
layout = Layout(width = constWidth),
)
ydelta = widgets.BoundedFloatText(
min = 1.,
description='$Y_{delta}$',
layout = Layout(width = constWidth),
)
zdelta = widgets.BoundedFloatText(
min = 1.,
description='$Z_{delta}$',
layout = Layout(width = constWidth),
)
tdelta = widgets.BoundedFloatText(
min = 0.01,
description='$Time_{delta}$',
layout = Layout(width = constWidth),
)
toggle2D = widgets.Checkbox(
description='2-D',
layout = Layout(width = constWidth),
)
def toggle2D_cb(b):
if (toggle2D.value):
#zmin.disabled = zmax.disabled = zdelta.disabled = True
zmin.disabled = True
zmax.disabled = True
zdelta.disabled = True
else:
zmin.disabled = False
zmax.disabled = False
zdelta.disabled = False
toggle2D.observe(toggle2D_cb)
x_row = widgets.HBox([xmin,xmax,xdelta])
y_row = widgets.HBox([ymin,ymax,ydelta])
z_row = widgets.HBox([zmin,zmax,zdelta])
# box_layout = Layout(display='flex',
# flex_flow='column',
# align_items='stretch',
# border='1px solid black',
# width='90%')
#z_row = Box(children=items, layout=box_layout)
#z_row = Box([toggle2D,zmin,zmax,zdelta], layout=box_layout)
#domain_range = Box([x_row,y_row,z_row], layout=box_layout)
tumor_radius = widgets.BoundedFloatText(
min=1,
max=99999, # TODO - wth
step=1,
description='Tumor Radius', style={'description_width': 'initial'},
layout = Layout(width = constWidth),
)
omp_threads = widgets.BoundedIntText(
min=1,
step=1,
description='# threads',
layout = Layout(width = constWidth),
)
toggle_prng = widgets.Checkbox(
description='Seed PRNG', style={'description_width': 'initial'}, # e.g. 'initial' '120px'
layout = Layout(width = constWidth),
)
prng_seed = widgets.BoundedIntText(
min = 1,
description='Seed',
disabled=True,
layout = Layout(width = constWidth),
)
def toggle_prng_cb(b):
if (toggle_prng.value):
prng_seed.disabled = False
else:
prng_seed.disabled = True
toggle_prng.observe(toggle_prng_cb)
#prng_row = widgets.HBox([toggle_prng, prng_seed])
#----- Output ------
# TODO: this changes when running on nanoHUB (= $RESULTSDIR)
output_dir_str = os.getenv('RESULTSDIR') + "/pc4nanobio/"
# output_dir_str = 'output' # match the "value" of the widget below
# NOTE: not used anymore
output_dir = widgets.Text(
# value='output',
description='Output Dir',
)
def config_output_dir_cb(w):
global output_dir_str
output_dir_str = w.value
print(output_dir_str)
output_dir.on_submit(config_output_dir_cb)
toggle_svg = widgets.Checkbox(
description='SVG',
layout = Layout(width = constWidth),
)
svg_t0 = widgets.BoundedFloatText (
min=0,
description='$T_0$',
layout = Layout(width = constWidth),
)
svg_interval = widgets.BoundedIntText(
min=1,
max=99999999, # TODO: set max on all Bounded widgets to avoid unwanted default
description='interval',
layout = Layout(width = constWidth),
)
def toggle_svg_cb(b):
if (toggle_svg.value):
svg_t0.disabled = False #False
svg_interval.disabled = False
else:
svg_t0.disabled = True
svg_interval.disabled = True
toggle_svg.observe(toggle_svg_cb)
toggle_mcds = widgets.Checkbox(
# value=False,
description='Full',
layout = Layout(width = constWidth),
)
mcds_t0 = widgets.FloatText(
description='$T_0$',
disabled=True,
layout = Layout(width = constWidth),
)
mcds_interval = widgets.BoundedIntText(
min=0,
max=99999999,
description='interval',
disabled=True,
layout = Layout(width = constWidth),
)
def toggle_mcds_cb(b):
if (toggle_mcds.value):
mcds_t0.disabled = False #False
mcds_interval.disabled = False
else:
mcds_t0.disabled = True
mcds_interval.disabled = True
toggle_mcds.observe(toggle_mcds_cb)
#----------------------------
# NOTE/TODO: any time the elm names change in the XML, need to change here!!!
def read_config_file_cb(b):
config_file = os.getenv('HOME') + '/' + read_config_file.value
fill_gui_params(config_file)
def default_config_file_cb(b):
fill_gui_params('data/nanobio_settings.xml') # NOTE: hard-coded for now
def fill_gui_params(config_file):
# global pc4nanobio_config_xml
tree = ET.parse(config_file)
root = tree.getroot()
xmin.value = float(root.find(".//x_min").text)
xmin.value = float(root.find(".//x_min").text)
xmax.value = float(root.find(".//x_max").text)
xdelta.value = float(root.find(".//dx").text)
ymin.value = float(root.find(".//y_min").text)
ymax.value = float(root.find(".//y_max").text)
ydelta.value = float(root.find(".//dy").text)
zmin.value = float(root.find(".//z_min").text)
zmax.value = float(root.find(".//z_max").text)
zdelta.value = float(root.find(".//dz").text)
tmax.value = float(root.find(".//max_time").text)
tumor_radius.value = float(root.find(".//radius").text)
omp_threads.value = int(root.find(".//omp_num_threads").text)
# output_dir.value = (root.find(".//folder").text)
toggle_svg.value = bool(root.find(".//SVG").find(".//enable").text)
svg_interval.value = int(root.find(".//SVG").find(".//interval").text)
toggle_mcds.value = bool(root.find(".//full_data").find(".//enable").text)
mcds_interval.value = int(root.find(".//full_data").find(".//interval").text)
cdp = root.find(".//cell_definition")
# e2 = e1.find('.//')
cell0_max_birth_rate.children[0].value = float(cdp.find(".//max_birth_rate").text)
cell0_o2_prolif_sat.children[0].value = float(cdp.find(".//o2_proliferation_saturation").text)
cell0_o2_prolif_thresh.children[0].value = float(cdp.find(".//o2_proliferation_threshold").text)
cell0_o2_ref.children[0].value = float(cdp.find(".//o2_reference").text)
cell0_glucose_prolif_ref.children[0].value = float(root.find(".//glucose_proliferation_reference").text)
cell0_glucose_prolif_sat.children[0].value = float(root.find(".//glucose_proliferation_saturation").text)
cell0_glucose_prolif_thresh.children[0].value = float(root.find(".//glucose_proliferation_threshold").text)
cell0_max_necrosis_rate.children[0].value = float(root.find(".//max_necrosis_rate").text)
cell0_o2_necrosis_thresh.children[0].value = float(root.find(".//o2_necrosis_threshold").text)
cell0_o2_necrosis_max.children[0].value = float(root.find(".//o2_necrosis_max").text)
cell0_apoptosis_rate.children[0].value = float(cdp.find(".//apoptosis_rate").text)
cell0_metab_aero.children[0].value = float(cdp.find(".//relative_aerobic_effects").text)
cell0_metab_glyco.children[0].value = float(cdp.find(".//relative_glycolytic_effects").text)
cell0_toggle_motile.value = bool(cdp.find(".//is_motile").text)
cell0_motile_bias.value = float(cdp.find(".//bias").text)
return
default_config_button = Button(
description='Use defaults', style={'description_width': 'initial'},
button_style='info', # 'success', 'info', 'warning', 'danger' or ''
tooltip='Populate the GUI with default parameters',
)
default_config_button.on_click(default_config_file_cb)
read_config_button = Button(
description='Read config (in ~)', style={'description_width': 'initial'},
button_style='info', # 'success', 'info', 'warning', 'danger' or ''
tooltip='Populate the GUI with info in your configuration file (in your home directory)',
)
read_config_file = widgets.Text(
value='my_nanobio_settings.xml',
description='',
)
read_config_button.on_click(read_config_file_cb)
#----------------------------
def write_config_file_cb(b):
# print('writing config')
# TODO: verify template .xml file exists!
# read/parse existing template that we'll then overwrite
tree = ET.parse('data/nanobio_settings.xml')
root = tree.getroot()
# TODO: verify valid type (numeric) and range?
root.find(".//x_min").text = str(xmin.value)
root.find(".//x_max").text = str(xmax.value)
root.find(".//dx").text = str(xdelta.value)
root.find(".//y_min").text = str(ymin.value)
root.find(".//y_max").text = str(ymax.value)
root.find(".//dy").text = str(ydelta.value)
root.find(".//z_min").text = str(zmin.value)
root.find(".//z_max").text = str(zmax.value)
root.find(".//dz").text = str(zdelta.value)
root.find(".//max_time").text = str(tmax.value)
root.find(".//radius").text = str(tumor_radius.value)
root.find(".//omp_num_threads").text = str(omp_threads.value)
# root.find(".//folder").text = str(output_dir.value)
# user_details = ET.SubElement(root, "user_details")
# ET.SubElement(user_details, "PhysiCell_settings", name="version").text = "devel-version"
# ET.SubElement(user_details, "domain")
# ET.SubElement(user_details, "xmin").text = "-100"
# tree = ET.ElementTree(root)
# tree.write(write_config_file.value)
# tree.write("test.xml")
# TODO: verify can write to this filename and don't allow overwrite of default
# Q: where does this file get written/saved?
tree.write(write_config_file.value)
write_config_button = Button(
description='Write config file',
button_style='success', # 'success', 'info', 'warning', 'danger' or ''
tooltip='Generate XML',
)
write_config_button.on_click(write_config_file_cb)
write_config_file = widgets.Text(
value='my_nanobio_settings.xml',
description='',
)
#----------------------------
run_output = widgets.Output(layout=widgets.Layout(width='900px', height='100px', border='solid'))
#run_output
# This is NOT used for the RunCommand
run_command_str = widgets.Text(
value='pc-nb nanobio_settings.xml',
description='',
)
# This is used now for the RunCommand
def run_sim_func(s):
s.run("bin/pc-nb data/nanobio_settings.xml") # TODO: choose: nanoHUB vs local
# s.run("/Users/heiland/dev/run-nanobio/pc-nb nanobio_settings.xml")
# This is NOT used now
def run_cb(b):
global my_proc
print('running: ', run_command_str.value)
with run_output:
# print(type(run_button))
# print(dir(run_button))
# args = ['/Users/heiland/git/PhysiCell-nanobio-com-fork/trunk/src/PhysiCell-nanobio','nanobio_settings.xml']
# args = ['/Users/heiland/dev/run-nanobio/pc-nb','nanobio_settings.xml']
#my_proc = Popen(args, stdout=PIPE, stderr=STDOUT)
#runCommand('/Users/heiland/git/PhysiCell-nanobio-com-fork/trunk/src/PhysiCell-nanobio nanobio_settings.xml')
sys.path.insert(0, os.path.abspath('..'))
# runCommand('/Users/heiland/dev/run-nanobio/pc-nb nanobio_settings.xml')
runCommand('pc-nb nanobio_settings.xml')
# NOTE: using the following approach will block us from other processes, e.g. visualizing results or executing a cmd in another cell
# This should be safe because we're not piping stdin to the process.
# It gets tricky if we are, because the process can be waiting for input while we're waiting for output.
# while True:
# # Wait for some output, read it and print it.
# with run_output:
# my_output = my_proc.stdout.read1(1024).decode('utf-8')
# print(my_output, end='')
# # Has the subprocess finished yet?
# if my_proc.poll() is not None:
# break
if my_proc.returncode != 0:
print("Exited with error code:", my_proc.returncode)
run_button = RunCommand(start_func=run_sim_func) # optionally: , done_func=read_data
# run_button = Button(
# description='Run',
# disabled=False,
# button_style='success', # 'success', 'info', 'warning', 'danger' or ''
# tooltip='Run simulation',
# )
# run_button.on_click(run_cb)
# def kill_cb(b):
# global my_proc
# print('kill sim...')
# my_proc.terminate()
# kill_button = Button(
# description='Kill',
# disabled=False,
# button_style='danger', # 'success', 'info', 'warning', 'danger' or ''
# tooltip='Kill simulation',
# )
# kill_button.on_click(kill_cb)
read_config_row = widgets.HBox([default_config_button, read_config_button, read_config_file])
#svg_output_row = widgets.HBox([toggle_svg, svg_t0, svg_interval])
#mat_output_row = widgets.HBox([toggle_mcds, mcds_t0, mcds_interval])
svg_mat_output_row = widgets.HBox([toggle_svg,svg_interval, toggle_mcds,mcds_interval])
write_config_row = widgets.HBox([write_config_button, write_config_file])
#run_sim_row = widgets.HBox([run_button, run_command_str, kill_button])
# run_sim_row = widgets.HBox([run_button, run_command_str])
# run_sim_row = widgets.HBox([run_button.w]) # need ".w" for the custom RunCommand widget
label_blankline = widgets.Label('')
tumor_radius2 = HBox([tumor_radius,micron_units])
# toggle_2D_seed_row = widgets.HBox([toggle_prng, prng_seed]) # toggle2D
config_tab = widgets.VBox([read_config_row, label_domain,x_row,y_row,z_row,
label_blankline, tmax, omp_threads,
tumor_radius2,svg_mat_output_row], layout=tab_layout) # output_dir, toggle_2D_seed_row
#----------------------------------------------
#current_idx = 0
#for idx in range(len(sys.argv)):
use_defaults = True
show_nucleus = 0
current_idx = 0
axes_min = 0.0
axes_max = 2000
#axes_max = 1000
scale_radius = 1.0
# TODO: these change when running on nanoHUB
#svg_dir_str = output_dir_str
#mcds_dir_str = output_dir_str
field_index = 4
def plot_substrate(FileId):
global current_idx, axes_max, gFileId, field_index
# global svg_dir_str
# dir = svg_dir.value
# print('debug> plot_substrate: idx=',FileId)
gFileId = FileId
fname = "output%08d_microenvironment0.mat" % FileId
# fullname = svg_dir_str + "/" + fname
fullname = output_dir_str + fname
if not pathlib.Path(fullname).is_file():
return
info_dict = {}
scipy.io.loadmat(fullname, info_dict)
M = info_dict['multiscale_microenvironment']
# global_field_index = int(mcds_field.value)
# print('plot_substrate: field_index =',field_index)
# print('plot_substrate: field_index=',field_index)
f = M[field_index,:] # 4=tumor cells field, 5=blood vessel density, 6=growth substrate
#plt.clf()
#my_plot = plt.imshow(f.reshape(400,400), cmap='jet', extent=[0,20, 0,20])
fig = plt.figure(figsize=(7.2,6)) # this strange figsize results in a ~square contour plot
# fig.set_tight_layout(True)
# ax = plt.axes([0, 0.05, 0.9, 0.9 ]) #left, bottom, width, height
# ax = plt.axes([0, 0.0, 1, 1 ])
# cmap = plt.cm.viridis # Blues, YlOrBr, ...
# im = ax.imshow(f.reshape(100,100), interpolation='nearest', cmap=cmap, extent=[0,20, 0,20])
# ax.grid(False)
grid2D = M[0,:].reshape(100,100)
xvec = grid2D[0,:]
#xvec.size
#xvec.shape
num_contours = 30
my_plot = plt.contourf(xvec,xvec,M[field_index,:].reshape(100,100), num_contours, cmap=field_cmap.value) #'viridis'
plt.colorbar(my_plot)
axes_min = 0
axes_max = 2000
plt.xlim(axes_min,axes_max)
plt.ylim(axes_min,axes_max)
# plt.title(fname)
# ax.set_title(fname)
# plt.axis('equal')
#plt.show()
get_ipython().run_line_magic('matplotlib', 'inline')
def plot_svg(SVG):
global current_idx, axes_max
# global svg_dir_str
# dir = svg_dir.value
# print('plot_svg: SVG=',SVG)
fname = "snapshot%08d.svg" % SVG
fullname = output_dir_str + fname
if not pathlib.Path(fullname).is_file():
# print("File does not exist: ",fname)
return
xlist = deque()
ylist = deque()
rlist = deque()
rgb_list = deque()
# print('\n---- ' + fullname + ':')
tree = ET.parse(fullname)
root = tree.getroot()
# print('--- root.tag ---')
# print(root.tag)
# print('--- root.attrib ---')
# print(root.attrib)
# print('--- child.tag, child.attrib ---')
numChildren = 0
for child in root:
# print(child.tag, child.attrib)
# print("keys=",child.attrib.keys())
if use_defaults and ('width' in child.attrib.keys()):
axes_max = float(child.attrib['width'])
# print("debug> found width --> axes_max =", axes_max)
if child.text and "Current time" in child.text:
svals = child.text.split()
#title_str = "(" + str(current_idx) + ") Current time: " + svals[2] + "d, " + svals[4] + "h, " + svals[7] + "m"
title_str = "Current time: " + svals[2] + "d, " + svals[4] + "h, " + svals[7] + "m"
# print("width ",child.attrib['width'])
# print('attrib=',child.attrib)
# if (child.attrib['id'] == 'tissue'):
if ('id' in child.attrib.keys()):
# print('-------- found tissue!!')
tissue_parent = child
break
# print('------ search tissue')
cells_parent = None
for child in tissue_parent:
# print('attrib=',child.attrib)
if (child.attrib['id'] == 'cells'):
# print('-------- found cells, setting cells_parent')
cells_parent = child
break
numChildren += 1
num_cells = 0
# print('------ search cells')
for child in cells_parent:
# print(child.tag, child.attrib)
# print('attrib=',child.attrib)
for circle in child: # two circles in each child: outer + nucleus
# circle.attrib={'cx': '1085.59','cy': '1225.24','fill': 'rgb(159,159,96)','r': '6.67717','stroke': 'rgb(159,159,96)','stroke-width': '0.5'}
# print(' --- cx,cy=',circle.attrib['cx'],circle.attrib['cy'])
xval = float(circle.attrib['cx'])
s = circle.attrib['fill']
# print("s=",s)
# print("type(s)=",type(s))
if (s[0:3] == "rgb"): # if an rgb string, e.g. "rgb(175,175,80)"
rgb = list(map(int, s[4:-1].split(",")))
rgb[:]=[x/255. for x in rgb]
else: # otherwise, must be a color name
rgb_tuple = mplc.to_rgb(mplc.cnames[s]) # a tuple
rgb = [x for x in rgb_tuple]
# test for bogus x,y locations (rwh TODO: use max of domain?)
too_large_val = 10000.
if (math.fabs(xval) > too_large_val):
print("bogus xval=",xval)
break
yval = float(circle.attrib['cy'])
if (math.fabs(yval) > too_large_val):
print("bogus xval=",xval)
break
rval = float(circle.attrib['r'])
# if (rgb[0] > rgb[1]):
# print(num_cells,rgb, rval)
xlist.append(xval)
ylist.append(yval)
rlist.append(rval)
rgb_list.append(rgb)
# For .svg files with cells that *have* a nucleus, there will be a 2nd
if (show_nucleus == 0):
break
num_cells += 1
# if num_cells > 3: # for debugging
# print(fname,': num_cells= ',num_cells," --- debug exit.")
# sys.exit(1)
# break
#print(fname,': num_cells= ',num_cells)
xvals = np.array(xlist)
yvals = np.array(ylist)
rvals = np.array(rlist)
rgbs = np.array(rgb_list)
#print("xvals[0:5]=",xvals[0:5])
#print("rvals[0:5]=",rvals[0:5])
# print("rvals.min, max=",rvals.min(),rvals.max())
#rwh - is this where I change size of render window?? (YES - yipeee!)
# plt.figure(figsize=(6, 6))
# plt.cla()
title_str += " (" + str(num_cells) + " agents)"
# plt.title(title_str)
# plt.xlim(axes_min,axes_max)
# plt.ylim(axes_min,axes_max)
# plt.scatter(xvals,yvals, s=rvals*scale_radius, c=rgbs)
fig = plt.figure(figsize=(6,6))
ax = plt.axes([0, 0.05, 0.9, 0.9 ]) #left, bottom, width, height
# im = ax.imshow(f.reshape(100,100), interpolation='nearest', cmap=cmap, extent=[0,20, 0,20])
# ax.xlim(axes_min,axes_max)
# ax.ylim(axes_min,axes_max)
ax.scatter(xvals,yvals, s=rvals*scale_radius, c=rgbs)
plt.xlim(axes_min,axes_max)
plt.ylim(axes_min,axes_max)
# ax.grid(False)
ax.set_title(title_str)
#plt.xlim(0,2000) # TODO - get these values from width,height in .svg at top
#plt.ylim(0,2000)
# plt.pause(time_delay)
# plt.axis('equal') # doing this will cause the axes to scale dynamically, probably unwanted
# keep last plot displayed
#plt.ioff()
# plt.show()
#def svg_dir_cb(w):
# global svg_dir_str
# svg_dir_str = w.value
# print(svg_dir_str)
#svg_dir = widgets.Text(
# value=svg_dir_str,
# description='Directory',
#)
#svg_dir.on_submit(svg_dir_cb)
#rwh - is this where I change size of render window?? (apparently not)
# TODO: dynamically change max value
svg_plot = widgets.interactive(plot_svg, SVG=(0, 500), continuous_update=False)
# output = svg_plot.children[-1]
# output.layout.height = '300px'
# output = svg_plot.children[1]
svg_plot_size = '500px'
svg_plot.layout.width = svg_plot_size
svg_plot.layout.height = svg_plot_size
# video-style widget - perhaps for future use
# svg_play = widgets.Play(
# interval=1,
# value=50,
# min=0,
# max=100,
# step=1,
# description="Press play",
# disabled=False,
# )
# def svg_slider_change(change):
# print('svg_slider_change: type(change)=',type(change),change.new)
# plot_svg(change.new)
#svg_play
# svg_slider = widgets.IntSlider()
# svg_slider.observe(svg_slider_change, names='value')
# widgets.jslink((svg_play, 'value'), (svg_slider,'value')) # (svg_slider, 'value'), (plot_svg, 'value'))
# svg_slider = widgets.IntSlider()
# widgets.jslink((play, 'value'), (slider, 'value'))
# widgets.HBox([svg_play, svg_slider])
# Using the following generates a new mpl plot; it doesn't use the existing plot!
#svg_anim = widgets.HBox([svg_play, svg_slider])
#svg_tab = widgets.VBox([svg_dir, svg_plot, svg_anim], layout=tab_layout)
svg_tab = widgets.HBox([svg_plot], layout=tab_layout) # svg_dir
#svg_tab = widgets.VBox([svg_dir, svg_anim], layout=tab_layout)
#---------------------
#============ Cells tab ===================
cell_name = widgets.Text(
value='untreated cancer',
description='Cell line name', style={'description_width': 'initial'},
)
#-------
label_cycle = widgets.Label('Cycle:') # no worky: ,style={'font_weight': 'bold'})
# NOTE: by adopting the
cell0_max_birth_rate = HBox([BoundedFloatText (
min=0,
#value = 0.0079,
description='Max birth rate', style={'description_width': 'initial'},
layout = Layout(width = constWidth3),
), min_inv_units], layout=Layout(width='300px'))
width_cell_params_units = '230px'
cell0_o2_prolif_sat = HBox([BoundedFloatText (
min=0,
description='$O_2$: Prolif sat',
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_o2_prolif_thresh = HBox([BoundedFloatText (
min=0,
description='Prolif thresh',
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_o2_ref = HBox([BoundedFloatText (
min=0,
description='Ref',
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_glucose_prolif_sat = HBox([BoundedFloatText (
min=0,
description='$Glc$: Prolif sat',
layout = Layout(width = constWidth),style={'description_width': 'initial'},
), ], layout=Layout(width=width_cell_params_units))
cell0_glucose_prolif_thresh = HBox([BoundedFloatText (
min=0,
description='Prolif thresh',
layout = Layout(width = constWidth),
), ], layout=Layout(width=width_cell_params_units))
cell0_glucose_prolif_ref = HBox([BoundedFloatText (
min=0,
description='Ref',
layout = Layout(width = constWidth),
), ], layout=Layout(width=width_cell_params_units))
#-------
label_necrosis = widgets.Label('Necrosis:')
cell0_max_necrosis_rate = HBox([BoundedFloatText (
min=0,
description='Max rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_o2_necrosis_thresh = HBox([BoundedFloatText (
min=0,
description='$O_2$: Thresh',
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_o2_necrosis_max = HBox([BoundedFloatText (
min=0,
description='Max',
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
#-------
label_apoptosis = widgets.Label('Apoptosis:')
cell0_apoptosis_rate = HBox([BoundedFloatText (
min=0,
description='Rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
#-------
# TODO: enforce sum=1
label_metabolism = widgets.Label('Metabolism (must sum to 1):')
# TODO: assert these next 2 values sum to 1.0
cell0_metab_aero = HBox([BoundedFloatText (
min=0,max=1,step=0.1,
description='Aerobic', #style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), ], layout=Layout(width=width_cell_params_units))
cell0_metab_glyco = HBox([BoundedFloatText (
min=0,max=1,step=0.1,
description='Glycolytic', #style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), ], layout=Layout(width=width_cell_params_units))
#-------
label_motility = widgets.Label('Motility:')
cell0_toggle_motile = widgets.Checkbox(
description='Motile',
layout = Layout(width = constWidth),
)
cell0_motile_bias = BoundedFloatText (
min=0,max=1,step=0.1,
# disabled = True,
description='Bias', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
)
def cell0_toggle_motile_cb(b):
if (cell0_toggle_motile.value):
cell0_motile_bias.disabled = False
else:
cell0_motile_bias.disabled = True
cell0_toggle_motile.observe(cell0_toggle_motile_cb)
#-------
label_mechanics = widgets.Label('Mechanics:')
cell0_max_rel_adhesion_dist = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Max adhesion distance', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), ], layout=Layout(width=width_cell_params_units))
cell0_adhesion_strength = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Adhesion strength', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), ], layout=Layout(width=width_cell_params_units))
cell0_repulsion_strength = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Repulsion strength', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), ], layout=Layout(width=width_cell_params_units))
#-------
label_hypoxia = widgets.Label('Hypoxia:')
cell0_o2_hypoxic_thresh = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='$O_2$: Thresh', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_o2_hypoxic_response = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Response', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_o2_hypoxic_sat = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Saturation', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
#-------
label_secretion = widgets.Label('Secretion:')
cell0_secretion_o2_uptake = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='$O_2$: Uptake rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_o2_secretion = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Secretion rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_o2_sat = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Saturation', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_glc_uptake = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='$Glc$: Uptake rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_glc_secretion = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Secretion rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_glc_sat = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Saturation', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_Hions_uptake = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='$H$+: Uptake rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_Hions_secretion = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Secretion rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_Hions_sat = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Saturation', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_ECM_uptake = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='$ECM$: Uptake rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_ECM_secretion = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Secretion rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_ECM_sat = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Saturation', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_NP1_uptake = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='$NP1$: Uptake rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_NP1_secretion = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Secretion rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_NP1_sat = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Saturation', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_NP2_uptake = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='$NP2$: Uptake rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_NP2_secretion = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Secretion rate', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), min_inv_units], layout=Layout(width=width_cell_params_units))
cell0_secretion_NP2_sat = HBox([BoundedFloatText (
min=0, step=0.1, #max=1,
description='Saturation', # style={'description_width': 'initial'},
layout = Layout(width = constWidth),
), mmHg_units], layout=Layout(width=width_cell_params_units))
#-----------------
# cells_max_birth_rate2 = HBox([max_birth_rate,min_inv_units], layout=Layout(width='300px'))
# cells_o2_prolif_sat2 = HBox([o2_prolif_sat,min_inv_units])
# cells_o2_prolif_thresh2 = HBox([o2_prolif_thresh, mmHg_units])
cells_row1 = HBox([cell_name])
cells_row2 = HBox([cell0_o2_prolif_sat, cell0_o2_prolif_thresh, cell0_o2_ref])
cells_row3 = HBox([cell0_glucose_prolif_sat, cell0_glucose_prolif_thresh, cell0_glucose_prolif_ref])
cell0_necrosis_row = HBox([cell0_o2_necrosis_thresh, cell0_o2_necrosis_max]) #, layout=Layout(width=pk_widgets_width))
cells_tab = VBox([cells_row1,
label_cycle, cell0_max_birth_rate, cells_row2, cells_row3,
label_necrosis, cell0_max_necrosis_rate, cell0_necrosis_row,
label_apoptosis, cell0_apoptosis_rate,
label_metabolism, HBox([cell0_metab_aero, cell0_metab_glyco]),
label_motility, HBox([cell0_toggle_motile, cell0_motile_bias]),
label_mechanics, HBox([cell0_max_rel_adhesion_dist,cell0_adhesion_strength,cell0_repulsion_strength]),
label_hypoxia, HBox([cell0_o2_hypoxic_thresh,cell0_o2_hypoxic_response,cell0_o2_hypoxic_sat]),
label_secretion, HBox([cell0_secretion_o2_uptake,cell0_secretion_o2_secretion,cell0_secretion_o2_sat]),
HBox([cell0_secretion_glc_uptake,cell0_secretion_glc_secretion,cell0_secretion_glc_sat]),
HBox([cell0_secretion_Hions_uptake,cell0_secretion_Hions_secretion,cell0_secretion_Hions_sat]),
HBox([cell0_secretion_ECM_uptake,cell0_secretion_ECM_secretion,cell0_secretion_ECM_sat]),
HBox([cell0_secretion_NP1_uptake,cell0_secretion_NP1_secretion,cell0_secretion_NP1_sat]),
HBox([cell0_secretion_NP2_uptake,cell0_secretion_NP1_secretion,cell0_secretion_NP2_sat]),
]) #, layout=tab_layout)
#=========
# PK
half_conc_desc = '$T_{0.5}$'
diffusion_coef_desc = 'Diffusion coef'
survival_desc = 'Survival lifetime'
binding_desc = 'ECM binding rate'