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import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline


    

    




/Users/luke/anaconda/envs/qiime190/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))

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df = pd.read_csv('/Users/luke/krse2011/db/krse2011_v5_humann_KOrelAbund_read1.csv', index_col=0)


    

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# split df by isotherms
df_21_23 = df.loc[(df['temperature'] > 21) & (df['temperature'] < 23)] # 16 samples
df_23_25 = df.loc[(df['temperature'] > 23) & (df['temperature'] < 25)] # 7 samples
df_25_27 = df.loc[(df['temperature'] > 25) & (df['temperature'] < 27)] # 1 sample
df_27_29 = df.loc[(df['temperature'] > 27) & (df['temperature'] < 29)] # 7 samples
df_29_32 = df.loc[(df['temperature'] > 29) & (df['temperature'] < 32)] # 14 samples


    

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# nitrate isotherm plots
var = 'nitrate'
for ko in ['K11959', 'K00367', 'K03320', 'K00368', 'K00369']:
    fig = plt.figure(figsize=(10, 10))
    plt.plot(df_21_23[var], df_21_23[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['blue'], markeredgewidth=2, label='Isotherm 21-23 C', markersize=8)
    plt.plot(df_23_25[var], df_23_25[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['light blue'], markeredgewidth=2, label='Isotherm 23-25 C', markersize=8)
    plt.plot(df_25_27[var], df_25_27[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['pink'], markeredgewidth=2, label='Isotherm 25-27 C', markersize=8)
    plt.plot(df_27_29[var], df_27_29[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['light orange'], markeredgewidth=2, label='Isotherm 27-29 C', markersize=8)
    plt.plot(df_29_32[var], df_29_32[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['red'], markeredgewidth=2, label='Isotherm 29-32 C', markersize=8)
    plt.xlabel('%s (uM)' % var, fontsize=18)
    plt.ylabel('%s (counts per million)' % ko, fontsize=18)
    plt.xticks(fontsize=14)
    plt.yticks(fontsize=14)
    plt.legend(loc='best', fontsize=16)
    #plt.axis([0, 20, 0, round(df[ko].max()*1.1, 5)])
    plt.margins(0.04, 0.08)
    plt.savefig('isotherms_%s_%s.pdf' % (var, ko))


    

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# phosphate isotherm plots
var = 'phosphate'
for ko in ['K02040', 'K07657', 'K01077', 'K06217', 'K02044']:
    fig = plt.figure(figsize=(10, 10))
    plt.plot(df_21_23[var], df_21_23[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['blue'], markeredgewidth=2, label='Isotherm 21-23 C', markersize=8)
    plt.plot(df_23_25[var], df_23_25[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['light blue'], markeredgewidth=2, label='Isotherm 23-25 C', markersize=8)
    plt.plot(df_25_27[var], df_25_27[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['pink'], markeredgewidth=2, label='Isotherm 25-27 C', markersize=8)
    plt.plot(df_27_29[var], df_27_29[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['light orange'], markeredgewidth=2, label='Isotherm 27-29 C', markersize=8)
    plt.plot(df_29_32[var], df_29_32[ko],'og', color='none', markeredgecolor=sns.xkcd_rgb['red'], markeredgewidth=2, label='Isotherm 29-32 C', markersize=8)
    plt.xlabel('%s (uM)' % var, fontsize=18)
    plt.ylabel('%s (counts per million)' % ko, fontsize=18)
    plt.xticks(fontsize=14)
    plt.yticks(fontsize=14)
    plt.legend(loc='best', fontsize=16)
    plt.axis([0, 1.5, 0, round(df[ko].max()*1.1, 4)])
    plt.savefig('isotherms_%s_%s.pdf' % (var, ko))


    

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