Diauxic growth data

Data for the example model.



In [1]:

    
%matplotlib inline
from __future__ import print_function

import os
import pandas as pd
import numpy as np
from matplotlib import pylab as plt
# global settings for plots
plt.rcParams.update({
        'axes.labelsize': 'large', 
        'axes.labelweight': 'bold',
        'axes.titlesize': 'large',
        'axes.titleweight': 'bold',
        'legend.fontsize': 'small',
        'xtick.labelsize': 'large',
        'ytick.labelsize': 'large',
    })

Varma1994



In [2]:

    
Varma1994_Fig6 = pd.read_csv('Varma1994_Fig6.csv', sep='\t')
Varma1994_Fig6.head()



In [3]:

    
Varma1994_Fig7 = pd.read_csv('Varma1994_Fig7.csv', sep='\t')
Varma1994_Fig7.head()









    Out[3]:






  
    
      
      study
      substance
      time
      value
      value_unit
    
  
  
    
      0
      Varma1994
      cell_density
      0.00
      0.00
      g/l
    
    
      1
      Varma1994
      cell_density
      1.73
      0.01
      g/l
    
    
      2
      Varma1994
      cell_density
      2.50
      0.02
      g/l
    
    
      3
      Varma1994
      cell_density
      3.01
      0.03
      g/l
    
    
      4
      Varma1994
      cell_density
      3.50
      0.04
      g/l



In [4]:

    
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2, figsize=(10,10))
fig.subplots_adjust(hspace=0.3, wspace=0.3)

substances = ['oxygen', 'glucose', 'acetate']
markers = dict(zip(substances, ['o', '^', 's']))

for name in ['oxygen', 'glucose', 'acetate']:
    inds = Varma1994_Fig6.substance == name
    # ax1.scatter(Varma1994_Fig6.D[inds], Varma1994_Fig6.v[inds])
    ax4.scatter(Varma1994_Fig6.D[inds], Varma1994_Fig6.v[inds], marker=markers[name], color='black', label=name)

ax4.set_title("Varma1994 Fig6")
ax4.set_xlabel('D [1/hr]')
ax4.set_ylabel('Uptake & Secretion rates [mmole/g DW-hr]')
ax4.legend()

inds = Varma1994_Fig7.substance == 'cell_density'
ax1.set_title("Varma1994 Fig7")
ax1.scatter(Varma1994_Fig7.time[inds], Varma1994_Fig7.value[inds], color='black')
ax1.set_xlabel('Time [h]')
ax1.set_ylabel('X [g/l]')

inds = Varma1994_Fig7.substance == 'glucose'
ax2.set_title("Varma1994 Fig7")
ax2.scatter(Varma1994_Fig7.time[inds], Varma1994_Fig7.value[inds], color='black')
ax2.set_xlabel('Time [h]')
ax2.set_ylabel('Glucose [mM]')

inds = Varma1994_Fig7.substance == 'acetate'
ax3.set_title("Varma1994 Fig7")
ax3.scatter(Varma1994_Fig7.time[inds], Varma1994_Fig7.value[inds], color='black')
ax3.set_xlabel('Time [h]')
ax3.set_ylabel('Acetate [mM]')

plt.show()



In [ ]:

	study	substance	E	D	v
0	Varma1994	oxygen	1.5	0.19	7.79
1	Varma1994	oxygen	1.5	0.25	9.39
2	Varma1994	oxygen	1.5	0.27	10.01
3	Varma1994	oxygen	1.5	0.35	10.94
4	Varma1994	oxygen	1.5	0.39	12.36

	study	substance	time	value	value_unit
0	Varma1994	cell_density	0.00	0.00	g/l
1	Varma1994	cell_density	1.73	0.01	g/l
2	Varma1994	cell_density	2.50	0.02	g/l
3	Varma1994	cell_density	3.01	0.03	g/l
4	Varma1994	cell_density	3.50	0.04	g/l