{ "packages": ["numpy", "pandas", "matplotlib"] }

bio-tools

HPLCのデータ解析 (α版)


                

                

            

        

    


import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

def set_peak(*ags, **kws):
    data_element = Element('input-data')
    data = data_element.element.value
    data = data.split('\n')

    if data == ['']:
        return

    li = []
    for row in data:
        if row == '':
            pass
        elif row[0] == '#':
            li.append(row.replace('\n','').replace('\r',''))
        else:
            row = row.replace('\n','').split('\t')
            row = row[1:3]
            row[0] = float(format(float(row[0]), '.1f'))
            row[1] = float(format(float(row[1]), '.5f'))
            li.append(row)

    t = eval(Element('sampling-time').element.value)
    df = pd.DataFrame({'RT': (np.arange(0, 151, 1)/10)}).set_index('RT')
    x = 0
    for i in li:
        if i[0] == '#':
            x += 1
            df[f'{t[x-1]}'] = 0
        else:
            df.at[i[0], f'{t[x-1]}'] = i[1]

    co = eval(Element('comp-list').element.value)
    df['co'] = None
    for i in co:
        df.loc[i[1]:i[2],'co'] = i[0]
    
    return df

    # Element('test').write(df[df.iloc[:,:-1].sum(axis=1) != 0])

def create_table(df, *ags, **kws):
    co = eval(Element('comp-list').element.value)

    tb = []
    for i in co:
        tb.append(df[df['co'] == i[0]].iloc[:,0:-1].sum().rename(i[0]))
    
    return tb

def calc_conc(tb, *ags, **kws):
    co = eval(Element('comp-list').element.value)

    tb_conc = []
    for j in tb:
        for i in co:
            if i[0] == j.name:
                tb_conc.append(j/i[3])
    
    return tb_conc


def plot_fig(tb_conc, *ags, **kws):
    co = eval(Element('comp-list').element.value)
    title = Element('data-title').element.value

    fig = plt.figure(figsize=(8, 5))
    fig.subplots_adjust(bottom=0.18)

    plt.rcParams['font.size'] = 15
    plt.rcParams['legend.fontsize'] = 18
    plt.rcParams['xtick.direction'] = 'out'
    plt.rcParams['ytick.direction'] = 'out'

    ax = plt.gca()
    ax.set_title(title, pad = 15)

    plt.xlabel('Time (h)', labelpad = 10)
    plt.ylabel('Concentration (mM)', labelpad = 10)

    for i in tb_conc:
        if sum(i) != 0:
            i_index = i.index.to_list()
            
            color = 'black'
            for j in co:
                if j[0] == i.name:
                    color = j[4]
            
            ax.plot(i_index, i, label=i.name, marker='o', markersize=10, color=color)
            ax.legend()
    

    Element('plot').write(fig)

    # plt.savefig('plot.png', dpi = 300, pad_inches = .1, bbox_inches = 'tight')

def hplc_analysis(*ags, **kws):
    df = set_peak()
    tb = create_table(df)
    tb_conc = calc_conc(tb)
    plot_fig(tb_conc)

def data_preview(*ags, **kws):
    data_element = Element('input-data')
    data = data_element.element.value
    Element('data-preview').write(data)

button_analysis = Element('analysis')
button_analysis.element.onclick = hplc_analysis

button_check = Element('data-check')
button_check.element.onclick = data_preview


button_analysis.element.disabled = False
button_check.element.disabled = False