Simulation of Biol 3415/Chem 3515 Experiment 3, part A

Biol 3515-Chem 3515 Exp 3, Part A

Gist title

code_dict_exp3.py

code_dict = {'0GXY02': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.0780933743000794e-05,
  'bpti_conc': 3.385861355932284e-05,
  'kcat': 12.479059780623182,
  'km': 8.563436439963315e-05},
 'DD0371': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.943933934989462e-05,
  'bpti_conc': 3.517617542672528e-05,
  'kcat': 9.174417463278722,
  'km': 4.777372487256253e-05},
 'X5FX87': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.95266826439055e-05,
  'bpti_conc': 3.138461537261679e-05,
  'kcat': 11.789268600290177,
  'km': 5.58468122174051e-05},
 'FG188G': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.285031188273903e-05,
  'bpti_conc': 3.1851612073108055e-05,
  'kcat': 13.047612493354922,
  'km': 7.177787853319616e-05},
 '34P10Q': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.722682984532362e-05,
  'bpti_conc': 3.332900420043714e-05,
  'kcat': 8.145189509187809,
  'km': 6.57837365279514e-05},
 'Y4N6KZ': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.8906484201970237e-05,
  'bpti_conc': 3.2455623824540886e-05,
  'kcat': 13.614464085817126,
  'km': 5.4379228053721865e-05},
 'W5XM03': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.9115719982294164e-05,
  'bpti_conc': 3.0087175891276203e-05,
  'kcat': 10.075765236194103,
  'km': 3.320531258425417e-05},
 '9V51PV': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.2972895706886008e-05,
  'bpti_conc': 3.301735248311078e-05,
  'kcat': 14.253426350877806,
  'km': 8.949671739010028e-05},
 '942913': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.0249547380195524e-05,
  'bpti_conc': 3.2738298103130895e-05,
  'kcat': 11.135081432311162,
  'km': 7.07376899404837e-05},
 'N898UN': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.8674877368836247e-05,
  'bpti_conc': 3.062565836535658e-05,
  'kcat': 10.097357504977413,
  'km': 6.59893141525897e-05},
 'H4CGP6': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.4074717025273083e-05,
  'bpti_conc': 3.17443257141572e-05,
  'kcat': 10.86527728039156,
  'km': 4.0295083099196564e-05},
 '13KE9N': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.0654600749048573e-05,
  'bpti_conc': 3.103388919416864e-05,
  'kcat': 14.476740111724716,
  'km': 4.664199652900124e-05},
 '31PQ53': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.264345369791618e-05,
  'bpti_conc': 3.0372329090212688e-05,
  'kcat': 6.560328970813622,
  'km': 3.930321207228756e-05},
 'KK644G': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.9346499463477278e-05,
  'bpti_conc': 3.387315205215228e-05,
  'kcat': 8.322469408595582,
  'km': 4.5568979770163385e-05},
 '2TNA45': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.9246819164209123e-05,
  'bpti_conc': 3.578113635439317e-05,
  'kcat': 5.953190657380047,
  'km': 3.994947194229087e-05},
 'N6AADQ': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.8630368266346355e-05,
  'bpti_conc': 3.19547849326813e-05,
  'kcat': 8.425285215458262,
  'km': 8.304450919324063e-05},
 'SV22HX': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.7310317193021016e-05,
  'bpti_conc': 3.368622203870609e-05,
  'kcat': 11.54988636685996,
  'km': 5.4691251633663635e-05},
 'VS8S0J': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.1921188687159537e-05,
  'bpti_conc': 3.230870033910233e-05,
  'kcat': 11.169575003686369,
  'km': 6.197424343338799e-05},
 '4U2RCD': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.876088862624062e-05,
  'bpti_conc': 3.0681927928368936e-05,
  'kcat': 11.746442846771568,
  'km': 5.739471754772193e-05},
 'ZCRTWU': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.9224581361271966e-05,
  'bpti_conc': 3.162737039250661e-05,
  'kcat': 5.076806311887225,
  'km': 3.228842227365505e-05},
 '7182Y1': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.47216027558941e-05,
  'bpti_conc': 3.0170396309572576e-05,
  'kcat': 8.241979108276192,
  'km': 6.0074402918688364e-05},
 'W8Y4P3': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.7782485501855382e-05,
  'bpti_conc': 3.33401281619942e-05,
  'kcat': 10.195874314801054,
  'km': 3.488329626913995e-05},
 'J9PWB4': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.475736161044849e-05,
  'bpti_conc': 3.404517806270831e-05,
  'kcat': 6.754889828781962,
  'km': 8.773579280310646e-05},
 '43479S': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.6621708935755493e-05,
  'bpti_conc': 3.45845158476193e-05,
  'kcat': 13.144983394351692,
  'km': 5.9336652102587744e-05},
 'MYX1AX': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.6766972738830726e-05,
  'bpti_conc': 3.454616610975151e-05,
  'kcat': 12.914367456489144,
  'km': 4.940114234055595e-05},
 'S0E0YV': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.7032357040088922e-05,
  'bpti_conc': 3.340431664908145e-05,
  'kcat': 10.957824559421038,
  'km': 3.289894725028064e-05},
 'DFKPU9': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.723282359923739e-05,
  'bpti_conc': 3.364544537727849e-05,
  'kcat': 7.466998500516203,
  'km': 6.51627417368447e-05},
 '9RFXYW': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.5000509553011084e-05,
  'bpti_conc': 3.416324621738166e-05,
  'kcat': 6.705684564747556,
  'km': 5.8051980187978164e-05},
 '88PTV8': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.4524217499362522e-05,
  'bpti_conc': 3.526260165210863e-05,
  'kcat': 5.011219927285401,
  'km': 8.251030817940819e-05},
 'H0X54M': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.4139816960349272e-05,
  'bpti_conc': 3.104640020546267e-05,
  'kcat': 6.589695629876994,
  'km': 6.600131868852241e-05},
 'KD1K2N': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.7172667254962533e-05,
  'bpti_conc': 3.4168766856849033e-05,
  'kcat': 10.800375363792174,
  'km': 4.161401188579533e-05},
 '23W0N6': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.922648717519026e-05,
  'bpti_conc': 3.244865757821224e-05,
  'kcat': 10.434092819204855,
  'km': 8.777019172064786e-05},
 'GQ5P11': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.7288023178577137e-05,
  'bpti_conc': 3.372014139433057e-05,
  'kcat': 8.027464722293182,
  'km': 8.77400879268201e-05},
 '597J70': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.912745303888913e-05,
  'bpti_conc': 3.56382749381675e-05,
  'kcat': 10.458568211196791,
  'km': 4.246737812426825e-05},
 '77YE98': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.6706669601780035e-05,
  'bpti_conc': 3.245311391523635e-05,
  'kcat': 7.330432197837356,
  'km': 8.891603561232728e-05},
 '994A4U': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.8895005256200494e-05,
  'bpti_conc': 3.259486743957249e-05,
  'kcat': 5.174640178640072,
  'km': 5.320770050272746e-05},
 '22NZ8S': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.1267935215025052e-05,
  'bpti_conc': 3.247345993620789e-05,
  'kcat': 9.340617525524213,
  'km': 8.084998120581375e-05},
 '33VZHV': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.588140524849908e-05,
  'bpti_conc': 3.069265913614357e-05,
  'kcat': 11.929996897914258,
  'km': 4.824483178683697e-05},
 'YD34E7': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.1705054520364497e-05,
  'bpti_conc': 3.0709011784212644e-05,
  'kcat': 10.27610221982453,
  'km': 3.781178868193927e-05},
 'B4EV54': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.0354460994888705e-05,
  'bpti_conc': 3.116014032604333e-05,
  'kcat': 7.021725135847429,
  'km': 5.7035565773548506e-05},
 'QXQEA0': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.3323423105185772e-05,
  'bpti_conc': 3.1520993936694644e-05,
  'kcat': 6.929654495543255,
  'km': 3.181108783085965e-05},
 'RCE9Z2': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.01296550430366e-05,
  'bpti_conc': 3.348731237039411e-05,
  'kcat': 13.410636428482128,
  'km': 6.436577355205234e-05},
 'W382SW': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.774481028180708e-05,
  'bpti_conc': 3.5226383654173546e-05,
  'kcat': 12.769638907644534,
  'km': 7.359061292718445e-05},
 'Y1UUUA': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.0828543359469805e-05,
  'bpti_conc': 3.0181583232375123e-05,
  'kcat': 6.72929920464161,
  'km': 8.86483930276227e-05},
 '240125': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.7918021956761915e-05,
  'bpti_conc': 3.501677251343129e-05,
  'kcat': 5.844744273832838,
  'km': 4.588117735847368e-05},
 '0P20E8': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.9706742739803737e-05,
  'bpti_conc': 3.5919910588591474e-05,
  'kcat': 11.3167024699186,
  'km': 8.655867671649303e-05},
 'CTZKSB': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.6678519754892104e-05,
  'bpti_conc': 3.063378110243431e-05,
  'kcat': 14.698116904941546,
  'km': 7.633417818129455e-05},
 'K60820': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.7891470882886813e-05,
  'bpti_conc': 3.408969521270859e-05,
  'kcat': 5.1724040679813585,
  'km': 8.540103081102389e-05},
 'WE21H5': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 1.8244941876266545e-05,
  'bpti_conc': 3.552211078184191e-05,
  'kcat': 9.019636410141747,
  'km': 8.204223957035615e-05},
 'N180MF': {'pip_sigma': 0.03,
  'abs_sigma': 0.001,
  'e_conc': 2.3419204687993863e-05,
  'bpti_conc': 3.1431254231335e-05,
  'kcat': 7.10770397148994,
  'km': 5.528682797277228e-05}}

environment.yml

name: exp_3a_sim
channels:
  - conda-forge
  - defaults
  - conda-forge/label/broken
dependencies:
  - python=3.8.3
  - numpy=1.19.2
  - scipy = 1.5.2
  - matplotlib=3.3.2
  - ipython=7.19.0
  - ipywidgets=7.5.1
  - voila=0.2.6

exp3a_sim.ipynb

exp3a_sim.py

## Module for import into Jupyter for simulation of Experiment 3, part A
## in Biology 3515/Chem 3515 at the University of Utah, Spring 2021
## https://goldenberg.biology.utah.edu/courses/biol3515/
## David P. Goldenberg, January 2021
## [email protected]

import random as rand
import numpy as np
import matplotlib.pyplot as plt
import ipywidgets as widgets
from IPython.display import display, HTML

from time import sleep, time
import threading
from scipy.integrate import solve_ivp
import functools
from scipy.stats import linregress

from labcodes import codes
from code_dict_exp3 import code_dict


##----------Global Parameters--------------------##
 # delay time while filling the absorbance table
 # Use 0 for testing and 0.2 for production to make the simulation run about
 # 5-x the actual speed. 
t_sleep = 0.2 


abs_read = 0.0 # for kin run
zero_set = 0.0 # for kin run


# Total time and number of steps for abs reading to settle
t_tot = 2
steps = 25
# Title for graph
graph_title = 'Experiment 3, Part A'
display(HTML("<style>div.output_scroll { height: 400ex; }</style>"))

##----------------Classes----------------------##

class Tube():
    '''Tube class for putting stuff in'''
    def __init__(self,vol=0.0,vol_n=0,max_vol=1.0,conc={}):
        self.vol = vol # actual volume
        self.vol_n= vol_n # nominal volume, reflecting pipette settings, vs actual delivered volumes
        self.max_vol = max_vol # max volume of tube
        self.conc = conc # concentrations of compounds
        

class Cuvette():
    '''Cuvette class, like Tube but with additional 
    attributes for sample name and reactions start time, t0'''
    def __init__(self):
        self.vol = 0.0
        self.vol_n = 0.0
        self.conc = {}
        self.t0 =0.0

class VolTable(widgets.HTML):
    def __init__(self,tube_dict,head):
        super().__init__(
        value='',
        layout=widgets.Layout(width='250px'))
        self.tube_dict = tube_dict
        self.head = head
        
        self.update()

    def update(self):
        '''function to update the table of tube or cuvette volumes'''
        html_str = '''
        <style>
        table, th, td {
          border: 1px solid black;
        }
        th, td {
          padding: 5px;
        }
        table, {border-collapse: collapse;}
        </style>
        <table>
        <tr>'''
        html_str += f'<th style="width:100px"> {self.head} </th>'       
        html_str += '''<th style="width:100px"> Volume (&mu;L)</th></tr>'''

        for tube in self.tube_dict:
            vol = self.tube_dict[tube].vol_n
            html_str += f'<tr><td>{tube}</td><td>{vol:.0f} </td></tr>\n'
        html_str += '</table>'
        self.value=html_str

class AbsTable(widgets.HTML):
    
    def __init__(self,cuv_dict,t_int,t_tot):
        super().__init__(
            value='',
            layout=widgets.Layout(width='600px'))
        self.cuv_dict = cuv_dict
        self.t_int = t_int
        self.t_tot = t_tot
        self.abs_data = []        
        self.n_meas = int(t_tot/t_int)+1
        self.n_cuv = len(self.cuv_dict)
        
        self.refresh()
        self.update()
        
    def refresh(self):
        self.abs_data=[['Time (min)']]
        for cuv in self.cuv_dict:
            self.abs_data[0].append('Cuvette ' + str(cuv))
        for i in range(self.n_meas):
            t = i*self.t_int
            self.abs_data.append([t]+[None]*self.n_cuv)
        self.update()

    def update(self):
        html_str = '''
        <style>
        table, th, td {
          border: 1px solid black;
        }
        th, td {
          padding: 5px;
        }
        table, {border-collapse: collapse;}
        </style>
        <table>
        <tr>
        <th style="width:100px"> Time (min) </th>'''
        for i in range(self.n_cuv):
            html_str += f'<th style="width:100px"> {self.abs_data[0][i+1]} </th>'
        html_str += '</tr>\n'
        for i in range(self.n_meas):
            html_str += f'<tr><td> {self.abs_data[i+1][0]}</td>'
            for j in range(self.n_cuv):
                if self.abs_data[i+1][j+1] != None:
                    html_str += f'<td>{self.abs_data[i+1][j+1]:0.3f}</td>'
                else:
                    html_str += '<td></td>'
        html_str += '</tr>\n'
        html_str += '</table>'
        self.value=html_str
        

class RegTable(widgets.HTML):
    def __init__(self,reg_results):
        super().__init__(
        value='',
        layout=widgets.Layout(width='500px'))
        self.reg_results = reg_results
        
        
        self.update()
        
    def update(self):
       
        '''function to update the table of results from linear regression'''
        n_cuv = len(self.reg_results)
        html_str = '''
        <style>
        table, th, td {
          border: 1px solid black;
        }
        th, td {
          padding: 5px;
        }
        table, {border-collapse: collapse;}
        </style>
        <table>
        <tr>'''
        html_str += '''<th style="width:100px"> Cuvette </th>'''
        html_str += '''<th style="width:100px"> Rate (min<sup>-1</sup>) </th>'''
        html_str += '''<th style="width:100px"> A<sub>0</sub> </th>'''
        html_str += '''<th style="width:100px"> R<sup>2</sup> </th></tr>'''

        for cuv in range(n_cuv):
            html_str += f'<tr><td> {cuv+1}</td>'
            slope = self.reg_results[cuv].slope
            html_str += f'<td>{slope:.4f}</td>'
            a0 = self.reg_results[cuv].intercept
            html_str += f'<td>{a0:.4f}</td>'
            rsq = self.reg_results[cuv].rvalue**2
            html_str += f'<td>{rsq:.3f}</td></tr>'
        html_str += '</table>'
        self.value=html_str



##----------Setup Dictionaries-----------------------##
# This has to come after Cuvette class is defined
conc_dict = {'trypsin':0.0,'tris':0.0, 'cacl':0.0,'substr':0.0,'prod':0.0}

cuv_dict = {}
for n in range(1,7):
    cuv_dict[n] = Cuvette()
    cuv_dict[n].conc = conc_dict.copy()

solns_dict={} # used to store stock solution concentrations
# trypsin concentration is set when code is read or changed
solns_dict['trypsin'] =0.0
solns_dict['cacl'] = 20.0*1e-3 # M
solns_dict['substr'] = 2.0*1e-3 # M
solns_dict['tris'] = 0.2 # M



#########---------Widgets and Their Functions --------------########
style = {'description_width': 'initial'}

##----------------Pipettes -----------------------##
# Used for multiple parts of experiment
# The deliver button is specific to each part
def on_pipette_ch(change):
    '''Function to changes volume parameters when pipette is changed.'''
    pip_vol.max = 1000.0
    if pipette.value == 1000.0:
        pip_vol.min = 200.0  
        pip_vol.max = 1000.0        
        pip_vol.step = 10.0
    elif pipette.value == 200.0:
        pip_vol.min = 20.0
        pip_vol.max = 200.0               
        pip_vol.step = 1.0
    elif pipette.value == 20.0:
        pip_vol.min = 1.0
        pip_vol.max = 20.0              
        pip_vol.step = 0.1
    pip_vol.value = pip_vol.max
    
pipette = widgets.Dropdown(
    # Choose pipette size
    options = [('P1000',1000.0),('P200',200.0),('P20',20.0)],
    description = 'Pipette:',
    style=style,
    layout=widgets.Layout(width='150px',margin='0px 0px 0px 50px')
    )
pipette.observe(on_pipette_ch,names=['value'])


pip_vol = widgets.BoundedFloatText(
    # Pipette volume setting
    value = 1000.0,
    min = 200.0,
    max = 1000.0,
    step = 10.0,
    description = 'Volume set (uL):',
    style = style,
    layout=widgets.Layout(width='200px',margin='0px 0px 0px 50px')
    )

def pip_deliver(soln_widget, soln_dict, tube_widget,tube_dict):
    
    tube_list = list(tube_dict)
    conc_list = list(tube_dict[tube_list[0]].conc)    
    pip_sigma = code_dict[lab_code.value]['pip_sigma']
    # get pipette err from normal distr
    err_pipette = pipette.value*rand.normalvariate(0,pip_sigma)
    
    # calculate delivered volume
    vol = pip_vol.value+err_pipette
    # save old volume and calculate new
    vol_old = tube_dict[tube_widget.value].vol
    vol_new = vol_old + vol

    tube_list = list(tube_dict)
    reag_list = list(tube_dict[tube_list[0]].conc)
    
    incr = {}
    for reag in reag_list:
        incr[reag]=0.0
    # calculate increment in solute amount (mg, moles,etc)
    for reag in reag_list:
        if reag == soln_widget.value:
            incr[reag] = vol*soln_dict[reag]
        
        if 'trypsin' == soln_widget.value:
            # special provision for trypsin solution conaining 20 mM CaCl2
            incr['cacl'] =vol*0.02
  
    # update concentrations
    for reag in reag_list:
        conc_old = tube_dict[tube_widget.value].conc[reag]       
        conc_new = (conc_old*vol_old + incr[reag])/vol_new      
        tube_dict[tube_widget.value].conc[reag] = conc_new
    
    #update volumes
    tube_dict[tube_widget.value].vol = vol_new
    tube_dict[tube_widget.value].vol_n += pip_vol.value
    

##----------------Lab Code Entry ------------------##

def on_code_ch(value):
    '''Respond to change in the code entered in the code box'''
    
    if lab_code.value != '' and lab_code.value not in codes:

        code_warn.value = '<span style="color:red;">Invalid code</span>'
    else:
        solns_dict['trypsin'] = code_dict[lab_code.value]['e_conc']/500.0
        code_warn.value =''

        deliver_butt.button_style = 'success'
        deliver_butt.description='Pipette!'
        run_butt.button_style = 'success'
        run_butt.description='Run!'
        
        
code_label = widgets.HTML(
    value = ''' <h3>Lab code: </h3>'''
    )

lab_code = widgets.Text(
    # text-entry widget to enter lab code
    value = '',
    placeholder='',
    #description = 'Lab code',
    layout=widgets.Layout(width='100px',margin='20px 0px 0px 15px')
    )
lab_code.observe(on_code_ch,names=['value'])   


code_warn = widgets.HTML(
    # warning when invalid lab code is entered
    value = '',
    layout=widgets.Layout(width='200px',margin='15px 50px 15px 0px')
    )
    
row_code = widgets.HBox([code_label,lab_code,code_warn])   


##----------------Set Up Cuvettes ----------------##

def deliver(change):
    if lab_code.value not in codes:
        deliver_butt.description='Enter valid lab code'
        deliver_butt.button_style = 'warning'
        return

    pip_deliver(solns_widget, solns_dict, cuv_widget, cuv_dict)
    c_trypsin = cuv_dict[cuv_widget.value].conc['trypsin']
    c_substr = cuv_dict[cuv_widget.value].conc['substr']
    if c_trypsin >0 and c_substr >0:
        cuv_dict[cuv_widget.value].t0 = time()
    vol_table.update()
    

def empty_cuv(change):
    cuv = cuv_dict[cuv_widget.value]
    for conc in cuv.conc:
        cuv.conc[conc]=0.0
    cuv.vol = 0.0
    cuv.vol_n = 0.0
    vol_table.update()

solns_widget = widgets.RadioButtons(
    # solutions for cuvettes for part A
    options =[('H20','H2O'), ('0.2 M Tris-Cl, pH 8','tris'), ('20 mM CaCl2','cacl'),
        ('Trypsin (1 ug/mL)','trypsin'), ('2 mM substrate','substr')],
    description='Solutions',
    layout=widgets.Layout(width='30%',margin='0px 0px 0px 0px')
    )

cuv_widget = widgets.RadioButtons(
    # Cuvettes for part A
    options=[1,2,3,4,5,6],
    description = 'Cuvettes:'
    )

empty_cuv_butt = widgets.Button(
    # button to empty cuvettes for part A
    description = 'Empty',
    button_style = 'danger',
    )   
empty_cuv_butt.on_click(empty_cuv)


vol_table = VolTable(cuv_dict,'Cuvette')

deliver_butt = widgets.Button(
    # Button to deliver volume for BSA dilution
    description = 'Pipette!',
    button_style = 'success',
    )
deliver_butt.on_click(deliver)   


cuvVb=widgets.VBox([cuv_widget,empty_cuv_butt],
                     layout=widgets.Layout(width='40%',margin='0px 0px 0px 00px'))

row_cuv = widgets.HBox([solns_widget,cuvVb,vol_table])

row_pip = widgets.HBox([deliver_butt,pipette,pip_vol],
    layout=widgets.Layout(margin='15px 0px 0px 0px'))

box_cuv = widgets.VBox([row_cuv,row_pip])

##---------------Kinetic Run --------------------=##
def mm_de(t,y,e_conc,km,kcat):
    s_conc = y[0]
    p_conc = y[1]
    dp_conc = e_conc*kcat*s_conc/(km+s_conc)
    ds_conc = -dp_conc
    return [ds_conc,dp_conc]
    
    
def kin_sim(cuv_dict,t_tot):
    # simulation is run for twice t_tot, to allow for starting delay
    # and continued absorbance readings after the run
    pts = int(1.5*t_tot*60)
    kin_sols =[]
    km=code_dict[lab_code.value]['km']
    kcat=code_dict[lab_code.value]['kcat']
    
    for cuv in cuv_dict:
        s_conc = cuv_dict[cuv].conc['substr']
        p_conc = 0.0
        e_conc =cuv_dict[cuv].conc['trypsin']
        
        if cuv_dict[cuv].conc['tris'] < 0.09:
             # activity is reduced if tris concentration isn't adequate
            kcat *= 0.5
        if cuv_dict[cuv].conc['cacl'] < 0.0009:
            # some of the enzyme is lost if CaCl2 concentration isn't adequate
            e_conc *= 0.5

        kin_sols.append(solve_ivp(mm_de,[0.0,float(pts)],[s_conc,p_conc],
                args=[e_conc,km,kcat],t_eval=np.linspace(0.0,float(pts),pts+1)))
        # return kcat to its original value
        kcat=code_dict[lab_code.value]['kcat'] 
    return kin_sols
        
        
def kin_run(abs_table,change):
    if lab_code.value not in codes:
        run_butt.description='Enter valid lab code'
        run_butt.button_style = 'warning'
        return

    run_butt.disabled = True
    abs_sigma = code_dict[lab_code.value]['abs_sigma']
    abs_table.refresh()
    
    ext_coef=1e4
    t_int = abs_table.t_int
    t_tot = abs_table.t_tot
    n_cuv = abs_table.n_cuv
    n_meas = abs_table.n_meas
    cuv_dict = abs_table.cuv_dict
    abs_data = abs_table.abs_data
    
    kin_sols = kin_sim(cuv_dict,t_tot)
        
    sleep(1)
    cuv_int =int(60*t_int/n_cuv)

    
    delay_t = [0]
    for cuv in cuv_dict:
        if cuv_dict[cuv].t0 > 0:
            delay_t.append(time()-cuv_dict[cuv].t0)
        else:
            delay_t.append(0)
            
    t=0
    tcuv=0
    meas = 1
    cuv = 1
    cuv_show(cuv)
    pts_total = int((t_tot+t_int)*60+cuv_int)
    for i in range(pts_total):
        sleep(t_sleep)

        abs_show(kin_sols[cuv-1].y[1][t]*ext_coef)
        if tcuv>=cuv_int:
            read_t = t + delay_t[cuv]
            err = rand.normalvariate(0,abs_sigma)
            absorb = (kin_sols[cuv-1].y[1][t]*ext_coef)+err
            abs_data[meas][cuv] = absorb
            abs_table.update()
                     
            if cuv < n_cuv:
                cuv+=1
            else:
                cuv=1
                meas +=1
            cuv_show(cuv)
            tcuv=0

        tcuv+=1
        t += 1
        
    make_plot(abs_table.abs_data)
    
    reset_butt.disabled = False
def make_plot(abs_data):
    global reg_table   
    prop_cycle = plt.rcParams['axes.prop_cycle']
    colors = prop_cycle.by_key()['color']
    colors.pop(2) # remove green
    #colors.pop(4) # remove brown
    #colors.pop(5) # remove grey
    
    plot_data = [[]]
    n_meas = abs_table.n_meas
    n_cuv = abs_table.n_cuv
    abs_data = abs_table.abs_data
    for j in range(n_meas):
        plot_data[0].append(abs_data[j+1][0])
    for i in range(n_cuv):
        plot_data.append([])
        for j in range(n_meas):
            plot_data[i+1].append(abs_data[j+1][i+1])
    plot_data = np.array(plot_data)
    
    
    reg_results = []
    for i in range(n_cuv):
        reg = linregress(plot_data[0],plot_data[i+1])
        reg_results.append(reg)
    reg_x = np.array([0.0,plot_data[0,-1]])
    fig = plt.figure(figsize=(7.5,5))
    ax= fig.add_subplot(1,1,1)
    for i in range(n_cuv):
        reg_yint = reg_results[i].intercept
        reg_slope = reg_results[i].slope
        reg_y = reg_x*reg_slope+reg_yint
        ax.plot(plot_data[0],plot_data[i+1],'o',color=colors[i])
        ax.plot(reg_x,reg_y,color=colors[i], label =f'Cuvette {i+1}')
        
    ax.set_title(graph_title,fontsize=18)
    ax.set_xlabel('Time (min)',fontsize=14)
    ax.set_ylabel('Absorbance at 405 nm',fontsize=14)
    data_min = plot_data.min()
    if data_min < 0.0:
        ax.set_ylim(data_min,)
    else:
        ax.set_ylim(0,)
    ax.set_xlim(0,)
    
    ax.legend()
    
    # Important note: close the plot so that it doesn't automatically
    # display in Jupyter. Otherwise, it will never go away!
    # display the fig in Output widget, which can be made to go away!
    
    plt.close()
     
    reg_table = RegTable(reg_results) 
    
    
    with fig_output:        
        display(fig)
        
    # Important note 2: In order for the regression table (an HTML widget
    # created within this function to appear in viola, it has to be put
    # in an output widget declared globally.
              
    with reg_table_output:
        display(reg_table)




def cuv_show(cuv):
    '''function to display the cuvette number in the cuv_display HTML widget'''
    cuv_displ.value=f'<h2>Cuvette:<span style="color:red;">\
    {cuv} </span></h2>'
    
    
def on_wl_ch(value):
    '''Respond to change in the wavelength widget'''
    h2O_abs = {'260 nm':0.14,'280 nm':0.3, '405 nm':0.6,'595 nm':0.8}
    absorb=h2O_abs[wl.value]
    abs_update(absorb)

def zero(change):
    '''Respond to the Zero button'''
    global zero_set
    
    zero_set = abs_read
    abs_update(abs_read)

def damp_sin(t,nu,tau):
    '''damped sine function to simulate settling
    of absorbance reading. Input arguments:
    t: time
    nu: sine-function frequency
    tau: exponential-decay time constant
    '''
    d_sin = np.exp(-t/tau)*np.sin(t*nu*2*np.pi)
    return d_sin    

def abs_update(absorb):
    '''function to set global abs_read2 variable and
    Updates absorbance display, with settling time
    Input arguments:
        absb: settled absorbance value
    global variables used:
        t_tot: total time for reading to settle
        steps: number of times to update display
            as it settles.
    '''
    global abs_read
    displ_absb = absorb - zero_set
    
    tau = 0.2*t_tot
    nu = 5/t_tot
    for i in range(steps+1):
        t = t_tot*i/steps
        abs_d = displ_absb*(1+damp_sin(t,nu,tau))
        sleep(t_tot/steps)
        
        abs_show(abs_d)
    
    abs_read = absorb
 

def abs_show(absorb):
    '''function to displays variable in the spec_dislp HTML widget'''
    if absorb < -0.03:
        spec_displ.value='<h2> Abs: <span style="color:red;"> Err  </span></h2>'
    else:
        spec_displ.value='<h2> Abs: <span style="color:red;"> \
        {:.3f}'.format(absorb) + '</span></h2>'
    
    
def cuv_reset(cuv_dict):
    '''Reset volumes, concentrations and t0 in all of the cuvettes in cuv_dict'''
    for cuv in cuv_dict:
        cuv_dict[cuv].vol = 0.0
        cuv_dict[cuv].vol_n = 0.0
        for c in cuv_dict[cuv].conc:
            cuv_dict[cuv].conc[c] = 0.0
        cuv_dict[cuv].t0=0.0

def on_reset(change):
    abs_table.refresh()
    reg_table.close()
    fig_output.clear_output()
    #cuv_reset(cuv_dict)
    vol_table.update()
    
    run_butt.disabled = False
    reset_butt.disabled = True

abs_table = AbsTable(cuv_dict, 1.5,10.5)

wl = widgets.Dropdown(
    # Dropdown to select wavelength for spectrophotometer
    options = [('260 nm'),('280 nm'),('405 nm'),('595 nm')],
    description = 'Wavelength:',
    style = style,
    layout=widgets.Layout(width='200px',margin='0px 0px 20px 0px')
    )
wl.observe(on_wl_ch,names=['value'])




zero_butt = widgets.Button(
    # button to zero absorbance display
    description = 'Zero',
    button_style = 'success',
    layout=widgets.Layout(margin='0px 0px 0px 20px')
    )
zero_butt.on_click(zero)



run_butt = widgets.Button(
    # Button to start simulated kinetics run
    description = 'Run!',
    button_style = 'success',
    layout=widgets.Layout(margin='0px 0px 0px 0px')
    )
run_butt.on_click(functools.partial(kin_run,abs_table))

cuv_displ=widgets.HTML(
    # cuvette number display
    value='1',
    layout=widgets.Layout(margin='-15px 0px 0px 20px')
    )

spec_displ = widgets.HTML(
    # spectrophotometer display
    value='0.0',
    layout=widgets.Layout(width='140px',margin='-15px 0px 0px 20px')
    )

reset_butt = widgets.Button(
    # button to reset kinetic simulation
    description ='Reset',
    button_style = 'danger',
    disabled = True,
    layout=widgets.Layout(margin='0px 0px 0px 20px')
    
    )
reset_butt.on_click(on_reset)

abs_show(0)
cuv_show(1)

row_spec1 =  widgets.HBox([wl,zero_butt])
row_spec2 = widgets.HBox([run_butt, cuv_displ, spec_displ, reset_butt])



fig_output = widgets.Output(layout={'border': '1px solid black','width':'500px'})
reg_table_output=widgets.Output()


##----------------Other Functions -----------------------##
def test_cuv():
    # A function for quickly setting up cuvettes for testing
    e_stock = code_dict[lab_code.value]['e_conc']/500.0
    s_stock = 0.002
    for cuv in cuv_dict:
        cuv_dict[cuv].vol = 800.0
        cuv_dict[cuv].vol_n = 800.0
        cuv_dict[cuv].conc['cacl']=2e-3
        cuv_dict[cuv].conc['tris']=0.4
        cuv_dict[cuv].conc['substr']= (160.0/800)*s_stock
        cuv_dict[cuv].t0 = 10*cuv

    cuv_dict[1].conc['trypsin']=(0.0/800)*e_stock


    cuv_dict[2].conc['trypsin']=(10.0/800)*e_stock
    cuv_dict[3].conc['trypsin']=(20.0/800)*e_stock
    cuv_dict[4].conc['trypsin']=(40.0/800)*e_stock

    cuv_dict[5].conc['trypsin']=(60.0/800)*e_stock
    cuv_dict[6].conc['trypsin']=(80.0/800)*e_stock
    vol_table.update()
    



def make_code_dict(codes):
    '''Function to build code dictionary specific to this experiment
    Don't actually call this function when loading the module, or else
    the dictionary will change with every execution. Instead save value
    of dictionary in this module.'''
    
    code_dict ={}
    for code in codes:
        pip_sigma =0.03
        abs_sigma = 0.001
        e_conc = (1 + rand.random())*1.5e-5
        bpti_conc = (1 + 0.2*rand.random())*3e-5
        
        kcat = (1 + 2*rand.random())*5.0
        km = (1 + 2*rand.random())*30e-6
        code_dict[code]={}
        code_dict[code]['pip_sigma']=pip_sigma
        code_dict[code]['abs_sigma'] = abs_sigma
        
        code_dict[code]['e_conc']=e_conc
        code_dict[code]['bpti_conc']=bpti_conc
        code_dict[code]['kcat']= kcat
        code_dict[code]['km']=km
    
    return code_dict


##-------------- Decorative and Informational Widgets ----------------------#
hrule = widgets.HTML(
    # general purpose horizontal rule
    value ='<hr border-width:6px, color:black>')

header_html = """
<h2> Biology 3515/Chemistry 3515
<br>
Biological Chemistry Laboratory 
<br>
University of Utah </h2>
<h3> Spring 2021 </h3>
<h3> Experiment 3, Part A: Enzyme Reaction Velocity as a Function of Enzyme Concentration</h3>
<p style="font-size:16px">

This web page simulates the procedures to be carried out in Part A of Experiment 3. For this part of the experiment, you will set up 6 cuvettes containing different concentrations of enzyme and a fixed concentration of substrate. You will then simulate a kinetic run as would be carried out in the lab using the program MacSpec, to control the spectrophotometer and record the data automatically.  As with, MacSpec, the simulation will output a table of absorbance values recorded at time intervals and make a plot of the data. The program also prints a table of data from least-squares fit of the data to a straight line. 
<br><br>
The graph displayed can be readily copied for use in another program or saved to your computer by right-clicking on the image and choosing the appropiate image. The data in tables cannot be directly saved to a file, but they can be selected using the mouse and copied for use in another program. The rows and columns can be directly copied into the data table of SciDAVis or a spreadsheet.


<br><br>
As in the earlier experiment simulations, a set of radio buttons is used to select solutions to pipette from and the cuvettes to be pipetted into. The table shows the nominal volumes in the tubes as reagents are added. (The volumes shown in the table do not account the expected small errors in pipetting). Before starting the kinetic run, all of the reagents <b>except</b> the substrate should be added to the cuvettes. Then, substrate should be added to each cuvette and the kinetic run started.
<br><br>
The simulation of the kinetic run is sped up by a factor of about 5-fold from what the real experiment takes. 

<br><br>
Like Experiment 2, this simulations requires a lab code to function, and your group should use the same code assigned earlier. If you do not have an assigned code, but want to experiment with this simulation, use the code "0GXY02".

"""

header = widgets.HTML(
    value=header_html
    )

    
footer = widgets.HTML(
    value='''
    <hr border-width:6px, color:black>
    David P. Goldenberg, February 2021<br>
    <a href="mailto:[email protected]" target="new">[email protected]</a><br>
    School of Biological Sciences, University of Utah<br>
    Salt Lake City, Utah 8412-0840<br>
     <a href="https://goldenberg.biology.utah.edu/courses/biol3515/index.shtml" 
     target="new">https://goldenberg.biology.utah.edu/courses/biol3550.</a>
''')

a1header = widgets.HTML(
    # header for part B, part 1
    value = '<h2> 1. Set up cuvettes</h2>'
    )

a2header = widgets.HTML(
    # header for part B, part 2
    value = '<h2> 2. Kinetic run</h2>'
    )
    

##-------------Display everything------------------##
display(HTML("<style>div.output_scroll { height: 300ex; }</style>"))

cuv_show(1)
abs_show(0)


display(header)
display(hrule)
display(row_code)
display(hrule)
display(a1header)
display(box_cuv)
display(hrule)

display(a2header)
display(row_spec1)
display(row_spec2)

display(abs_table)
display(fig_output)
display(reg_table_output)
display(footer)

labcodes.py

codes =['0GXY02',
 'DD0371',
 'X5FX87',
 'FG188G',
 '34P10Q',
 'Y4N6KZ',
 'W5XM03',
 '9V51PV',
 '942913',
 'N898UN',
 'H4CGP6',
 '13KE9N',
 '31PQ53',
 'KK644G',
 '2TNA45',
 'N6AADQ',
 'SV22HX',
 'VS8S0J',
 '4U2RCD',
 'ZCRTWU',
 '7182Y1',
 'W8Y4P3',
 'J9PWB4',
 '43479S',
 'MYX1AX',
 'S0E0YV',
 'DFKPU9',
 '9RFXYW',
 '88PTV8',
 'H0X54M',
 'KD1K2N',
 '23W0N6',
 'GQ5P11',
 '597J70',
 '77YE98',
 '994A4U',
 '22NZ8S',
 '33VZHV',
 'YD34E7',
 'B4EV54',
 'QXQEA0',
 'RCE9Z2',
 'W382SW',
 'Y1UUUA',
 '240125',
 '0P20E8',
 'CTZKSB',
 'K60820',
 'WE21H5',
 'N180MF']