Plots_chromatograms

plot_chromatogram.py

"""
fraction	lum	NaCl_Conc	type
1	4213	0.06	step
2	5123	0.06	step
3	7813	0.06	step
4	12988	0.06	step
5	24373	0.06	step
6	24843	0.1	slope
7	7513	0.1	slope
8	5358	0.2	step
9	16858	0.2	step
10	18888	0.3	step
11	102928	0.3	step
12	119864	0.4	step
13	771153	0.4	step

Takes data like the table above and makes a nice chromatogram. 
Mostly for plotting bioluminescence chromatograms for anion exchange chromatography.
"""
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib.patches as mplpatches
import matplotlib.lines as mlines

filename = "fraction_results.tsv"
this_y_label = "RLU"
this_fig_title = "Ostracod luciferase purification \n strong anion exchange Jan 23 2019"
frac_rxn_vol = 100
buff_rxn_vol = 70
buff_rxn_mol = .75

bar_width=0.95

df = pd.read_csv(filename, 
                 sep='\t', header=0)
#mols rxn
mol_rxn = frac_rxn_vol * df['NaCl_Conc']
mol_buff = buff_rxn_vol * buff_rxn_mol
tot_mol = mol_rxn + mol_buff
#total_reaction_volume
trv = buff_rxn_vol + frac_rxn_vol
df['rxn_mol'] = tot_mol/trv

#set the figure dimensions
figWidth = 5.5
figHeight = 4.5
magic_num = 0.5
plt.figure(figsize=(figWidth,figHeight))

#set the panel dimensions
panelWidth = figWidth-magic_num
panelHeight = figHeight-magic_num

#find the margins to center the panel in figure
leftMargin = magic_num
bottomMargin = magic_num

x_lims = [0,max(df.fraction) + 1]
y_lims = [0,(max(df.lum) + 1)*1.05]

#set the left panel for 5' splice sites
panel0=plt.axes([leftMargin/figWidth, #left
                 bottomMargin/figHeight,    #bottom
                 panelWidth/figWidth,   #width
                 panelHeight/figHeight])     #height
panel0.tick_params(axis='both',which='both',\
                   bottom=True, labelbottom=True,\
                   left=True, labelleft=True, \
                   right=False, labelright=False,\
                   top=False, labeltop=False) 
panel0.set_ylabel(this_y_label)                  
panel0.set_title(this_fig_title)
panel0.set_xlim(x_lims)                   
panel0.set_ylim(y_lims)
panel0.set_xlabel("Fraction")
panel1 = panel0.twinx()

prev_slope = False
for index, row in df.iterrows():
    rectangle1=mplpatches.Rectangle((row['fraction'],0),bar_width,row['lum'],
                                    linewidth=0,\
                                    linestyle='-',\
                                    edgecolor='black',\
                                    facecolor='teal')
    panel0.add_patch(rectangle1)
    if index < (len(df) -1):
        if df.loc[index, 'type'] == "step":
            prev_slope = False
            #first horizontal line
            panel1.plot( [df.loc[index, 'fraction'], df.loc[index+1, 'fraction']], 
                         [df.loc[index, 'NaCl_Conc'], df.loc[index, 'NaCl_Conc']], 
                         color='r', linestyle='-', linewidth=2)
            #second vertical line
            panel1.plot( [df.loc[index+1, 'fraction'], df.loc[index+1, 'fraction']], 
                         [df.loc[index, 'NaCl_Conc'], df.loc[index+1, 'NaCl_Conc']], 
                         color='r', linestyle='-', linewidth=2)
        elif (df.loc[index, 'type'] == "slope") and not prev_slope:
            prev_slope = True
            for j in range (index+1, (len(df))):
                if (df.loc[j, 'type'] == "step") or (j == (len(df) -1) ):
                    panel1.plot( [df.loc[index, 'fraction'], df.loc[j, 'fraction']], 
                         [df.loc[index, 'NaCl_Conc'], df.loc[j, 'NaCl_Conc']], 
                         color='r', linestyle='-', linewidth=2)
                    break
                
panel1.scatter(df['fraction'] + (bar_width/2), df['rxn_mol'], color='#bc0f12', marker = 'x')
panel1.set_ylabel('NaCl Molarity', color='r')
panel1.tick_params('y', colors='r')

red_line = mlines.Line2D([], [], color='r', marker=None,
                          markersize=15, label='Gradient NaCl Molarity')
red_x = mlines.Line2D([], [], color='#bc0f12', marker='x', linewidth = 0,
                          markersize=8, label='Assay NaCl Molarity')
blue_patch = mplpatches.Patch(color='#23807f', label='RLU(20s)')
plt.legend(handles=[red_line, red_x, blue_patch])