Simulation of Biol 3515/Chem 3515 Experiment 3, part C

Biol 3515-Chem 3515 Exp 3, Part C

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_3c_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

exp3c_sim.ipynb

exp3c_sim.py

## Module for import into Jupyter for simulation of Experiment 3, part C
## in Biology 3515/Chem 3515 at the University of Utah, Spring 2021
## https://goldenberg.biology.utah.edu/courses/biol3515/
## David P. Goldenberg, February 2021
## goldenberg@biology.utah.edu

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


display(HTML("<style>div.output_scroll { height: 400ex; }</style>"))
##----------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
# initial values of absorbance reading and background absorbance
abs_read = 0.0 # for uv abs of bpti soln
zero_set = 0.0 # for uv abs of bpti soln

# Total time and number of steps for abs reading to settle
t_tot = 2
steps = 25

graph_title = 'Experiment 3, Part C'
style = {'description_width': 'initial'}

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

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

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,cuv_list,reg_results):
        super().__init__(
        value='',
        layout=widgets.Layout(width='500px'))
        self.reg_results = reg_results      
        self.cuv_list = cuv_list
        
        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 i in range(n_cuv):
            cuv = self.cuv_list[i]
            html_str += f'<tr><td> {cuv}</td>'
            slope = self.reg_results[i].slope
            html_str += f'<td>{slope:.4f}</td>'
            a0 = self.reg_results[i].intercept
            html_str += f'<td>{a0:.4f}</td>'
            rsq = self.reg_results[i].rvalue**2
            html_str += f'<td>{rsq:.3f}</td></tr>'
        html_str += '</table>'
        self.value=html_str


## --------------- Create Dictionaries ------------------##
# This has to come after the Tube and Cuvette classes are defined!  
conc_dict = {'trypsin':0.0, 'hepes':0.0, 'cacl':0.0,'substr':0.0}

cuv_dict = {}
for n in range(1,4):
    cuv_dict[n] = Cuvette()
    cuv_dict[n].conc = conc_dict.copy()
    
solns_dict={} # used to store stock solution concentrations
# trypsin and BPTI concentrations are set when code is read or changed
solns_dict['trypsin'] =0.0
solns_dict['hepes'] = 0.2 
solns_dict['cacl'] = 20.0*1e-3 # M
solns_dict['substr'] = 10.0*1e-3 # M

# create a cuvette dictionary with a single element, for the cuvette selected for the run
# Then create absorbance table
# The cuvette dictionary and abs table is updated with the cuvette selected when the cuvette is changed
cuv_dict_r ={}
cuv_dict_r[1] =cuv_dict[1]
abs_table = AbsTable(cuv_dict_r, 1.0,5.0)    

#########---------Widgets and Their Functions --------------########

##----------------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']
        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])   

##--------------- Cuvette Setup ------------------##



def on_cuv_change(change):
    
    cuv = cuv_widget.value
    cuv_dict_r = {}
    cuv_dict_r[cuv] =cuv_dict[cuv]
    abs_table.cuv_dict = cuv_dict_r
    abs_table.refresh()
    cuv_show(cuv)

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()
    cuv_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
    cuv.t0 = 0.0
    cuv_vol_table.update()

solns_widget= widgets.RadioButtons(
    # solutions for cuvettes for part A
    options =[('0.2 M HEPES pH 8','hepes'), ('20 mM CaCl2','cacl'), ('~0.5 mg/mL trypsin','trypsin'),
         ('10 mM NPGB','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],
    description = 'Cuvettes:'
    )
cuv_widget.observe(on_cuv_change)

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


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_butt],
                     layout=widgets.Layout(width='40%',margin='0px 0px 0px 00px'))

row_cuv= widgets.HBox([solns_widget,cuvVb,cuv_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 burst_de(t,y,k_b,k_s1,k_s2,e_init):
    s_conc = y[0]
    e_conc = y[1]
    p_conc = y[2]
    # rate of burst phase - second-order
    r_b = k_b*s_conc*e_conc
    # rate of slow phase - includes a both firt- and second-order component
    # second-order process is assumed to depend on total enzyme concentration
    # and is unaffected by modificatio of the active site.
    r_s= k_s1*s_conc + k_s2*s_conc*e_init
    dp_conc = r_b + r_s
    de_conc = -r_b
    ds_conc = -dp_conc
    return[ds_conc,de_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)
    
    # rate constants for burst and slow phases
    k_b = 1e3
    k_s1 = 1.7e-5
    k_s2 = 2.4
    
    
    cuv = list(cuv_dict)[0]
    s0 = cuv_dict[cuv].conc['substr']
    
    e0 =cuv_dict[cuv].conc['trypsin']
    
    if cuv_dict[cuv].conc['hepes'] < 0.08:
        # activity is reduced if tris concentration isn't adequate
        e0 *= 0.5
    if cuv_dict[cuv].conc['cacl'] < 0.0008:
        # some of the enzyme is lost if CaCl2 concentration isn't adequate
        e0 *= 0.5

    # note the default integration method for solve_ivp, RK45, is unstable for this set of DEs
    # The Ragu method is recommended for stiff equations, and works well here
    kin_sol= solve_ivp(burst_de,[0.0,float(pts)],[s0,e0,0.0], method = 'Radau',
        args=[k_b,k_s1,k_s2,e0],t_eval=np.linspace(0.0,float(pts),pts+1))               
                
    return kin_sol
    
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()
    if wl.value == '402 nm':
        ext_coef=1.6e4
    elif wl.value == '405 nm':
        ext_coef=1.5e4
    else:
        ext_coef=0.0
        
    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_sol = kin_sim(cuv_dict,t_tot)
        
    sleep(1)
    
    delay_t = 0

    cuv = list(cuv_dict)[0]
    if cuv_dict[cuv].t0 > 0:
        delay_t = int(time()-cuv_dict[cuv].t0)
         
    t=0
    tcuv=0
    meas = 1
    cuv_int = t_int*60
    cuv_show(cuv)
    abs_start = abs_read-zero_set
    # add a little to the absorbance background from NPGB solution
    abs_start += 0.002
        
    pts_total = int((t_tot)*60)+1
    
    absorb = kin_sol.y[2][delay_t]*ext_coef + abs_start
    abs_show(absorb)
    abs_data[meas][1] = absorb
    abs_table.update()
    meas += 1
    for i in range(pts_total):
        sleep(t_sleep)
        absorb = kin_sol.y[2][t]*ext_coef + abs_start
        abs_show(absorb)
        if tcuv>=cuv_int:
            read_t = t + delay_t
            err = rand.normalvariate(0,abs_sigma)
            absorb = abs_start + (kin_sol.y[2][read_t]*ext_coef)+err  
            abs_data[meas][1] = absorb
            abs_table.update()
                     
            meas +=1
            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
    cuv_dict = abs_table.cuv_dict
    cuv_list = list(cuv_dict)
    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 {cuv_list[i]}')
        
    ax.set_title(graph_title,fontsize=18)
    ax.set_xlabel('Time (min)',fontsize=14)
    ylabel_str = 'Absorbance at ' + wl.value
    ax.set_ylabel(ylabel_str,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(cuv_list,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 on_wl_ch(value):
    '''Respond to change in the wavelength widget'''
    h2O_abs = {'260 nm':0.14,'280 nm':0.3, '402 nm':0.4, '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_read 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_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_reset(change):
    abs_table.refresh()
    reg_table.close()
    fig_output.clear_output()
    
    run_butt.disabled = False
    reset_butt.disabled = True
    


    
wl = widgets.Dropdown(
    # Dropdown to select wavelength for spectrophotometer
    options = [('260 nm'),('280 nm'),('402 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(cuv_widget.value)

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()


##-------------- 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 C: Determination of Enzyme Concentration with a Burst Substrate</h3>
<p style="font-size:16px">

This web page simulates the procedures to be carried out in Part C of Experiment 3. For this part of the experiment, you will set up three cuvettes containing different concentrations of enzyme and follow the reaction with 4-nitrophenyl-4-guanidobenzoate, a burst substrate. This reagent forms a very stable acyl intermediate with the enzyme, so that each enzyme produces only a single molecule of nitro-phenol product.  By measuring the amount of product produced, the concentration of enzyme can be determined.  There is, however, a background rate of hydrolysis that must me measured and accounted for in the determination.
<br><br>
For this experiment, it is important that the spectrophotometer be zeroed with the cuvette containing everything except the substrate, and the kinetic run should be started as quickly as possible after mixing the enzyme and substrate.  For these reasons, separate kinetic runs are conducted for each cuvette.
<br><br>
The kinetic run is carried out as in the previous parts of the experiment, and as would be done 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 appropriate 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>
The automatic curve fit includes the point at zero minutes, which may or may not be appropriate. The goal here is to extrapolate the background hydrolysis rate to time 0. If the burst phase is completed by the first time point, this point will lie close to the fit line, and the fit parameters can be used for the data analysis. If, however, the first point lies significantly below the line, the data should be anlyzed using a fit that excludes this point. This can be done by copying the data into SciDAVis and using the curve-fitting tools in that program.
<br><br>
As in the earlier experiment simulations, a set of radio buttons is used to select solutions to pipette from and the tubes or cuvettes to be pipetted into. Tables are used to show the nominal volumes in the tubes as reagents are added. 
<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 the previous experiments, 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:goldenberg@biology.utah.edu" target="new">goldenberg@biology.utah.edu</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>
''')

c1header = widgets.HTML(
    # header for part B, part 1
    value = '<h2> 1. Set up cuvettes</h2>'
    )

c2header = widgets.HTML(
    # header for part B, part 2
    value = '<h2> 2. Kinetic run</h2>'
    )

##--------------Test functions -----------------------#
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 test_cuv():
    cuv_reset(cuv_dict)
    # A function for quickly setting up cuvettes for testing
    # sets up  state before final addition of bpti-trypsin incubation mixture
    e_stock = solns_dict['trypsin']
    s_stock = 0.010
    for cuv in cuv_dict:
        cuv_dict[cuv].vol = 800.0
        cuv_dict[cuv].vol_n = 800.0
        cuv_dict[cuv].conc['cacl']=20e-3*400/800
        cuv_dict[cuv].conc['hepes']=0.2*400.0/800
        cuv_dict[cuv].conc['substr']= 0
        cuv_dict[cuv].t0 = 0
    
    cuv_dict[1].conc['trypsin'] =0.0
    cuv_dict[2].conc['trypsin'] =e_stock/8.0
    cuv_dict[3].conc['trypsin'] =3*e_stock/8.0
    cuv_vol_table.update()

##-------------- Decorative and Informational Widgets ----------------------#
hrule = widgets.HTML(
    # general purpose horizontal rule
    value ='<hr border-width:6px, color:black>')
    
    
##--------------Display Everything -----------------------------#
#lab_code.value='0GXY02'

display(header)
display(hrule)

display(row_code)
display(hrule)

display(c1header)
display(box_cuv)
display(hrule)

display(c2header)
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']