In [7]:

    

# Import all libraries needed for the tutorial

# General syntax to import specific functions in a library:
##from (library) import (specific library function)
from pandas import DataFrame, read_csv

# General syntax to import a library but no functions:
##import (library) as (give the library a nickname/alias)
import matplotlib.pyplot as plt
import pandas as pd #only needed to determine version number

import glob
from scipy import randn
from pandas import *

# Enable inline plotting
%matplotlib inline


    

In [8]:

    

path =r'../extra'

allFiles = glob.glob(path + "/*.txt")
frame = pd.DataFrame()
list = []
for files in allFiles:
    df = pd.read_csv(files,index_col=0, header=0, delimiter="\t")
    list.append(df)


glued = pd.concat(list, axis=1)
ar = glued
#print(frame)

#print(glued)
#print(glued.groupby(level=0, axis=1).std())
stdtab = ar.groupby(level=0, axis=1).std()
meantab = glued.groupby(level=0, axis=1).mean()
#glued.groupby(level=0, axis=1).mean().to_csv("glued.txt", sep="\t")

#plt.figure(figsize=(10, 8), dpi=120);
#meantab.plot(yerr=stdtab)

#dff = pd.concat([meantab, stdtab], axis=1)

#plt.figure(figsize=(10, 8), dpi=120);
#dff.plot()
list = []
for files in allFiles:
    df = pd.read_csv(files,index_col=None, header=0, delimiter="\t")
    list.append(df)
frame = pd.concat(list)
matplotlib.rc('ytick', labelsize=14)
matplotlib.rc('xtick', labelsize=14)

plt.figure(figsize=(10, 8), dpi=220);
bp = frame.boxplot(column=['# Clock'], fontsize=20)
fig = plt.gcf()
fig.savefig(path + '/clockboxplot.pdf')
#plt.figure(figsize=(10, 8), dpi=120);
#bp = frame.boxplot(column=['In Chain'])
#fig = plt.gcf()
#fig.savefig(path + '/inchainboxplot.pdf')
#plt.figure(figsize=(10, 8), dpi=120);
#bp = frame.boxplot(column=['On Target'])
#fig = plt.gcf()
#fig.savefig(path + '/ontargetboxplot.pdf')
 
plt.figure(figsize=(10, 8), dpi=220);
bp = frame.boxplot(column=['In Chain','On Target'], fontsize=20)
fig = plt.gcf()
fig.savefig(path + '/inchainontargetboxplot.pdf')


    

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In [9]:

    

#xticks=arange(0, 9000, 1000)
meantab[::100].plot(yerr=glued.groupby(level=0, axis=1).std(),figsize=(15, 12), fontsize= 20).set_title('In Chain, On Target values over Clock with range 2.5 and low P_chain')

fig = plt.gcf()
fig.savefig(path + '/low2-5figure.pdf')


    

In [116]:

    

path =r'../expdist1-5lowerpchain'


    

In [117]:

    

allFiles = glob.glob(path + "/*.txt")
frame = pd.DataFrame()
list = []
for files in allFiles:
    df = pd.read_csv(files,index_col=0, header=0, delimiter="\t")
    list.append(df)


glued = pd.concat(list, axis=1)
ar = glued
#print(frame)

#print(glued)
#print(glued.groupby(level=0, axis=1).std())
stdtab2 = ar.groupby(level=0, axis=1).std()
meantab2 = glued.groupby(level=0, axis=1).mean()
#glued.groupby(level=0, axis=1).mean().to_csv("glued.txt", sep="\t")

#plt.figure(figsize=(10, 8), dpi=120);
#meantab.plot(yerr=stdtab)

#dff = pd.concat([meantab, stdtab], axis=1)

#plt.figure(figsize=(10, 8), dpi=120);
#dff.plot()
list = []
for files in allFiles:
    df = pd.read_csv(files,index_col=None, header=0, delimiter="\t")
    list.append(df)
frame2 = pd.concat(list)

meantab.rename(columns={'In Chain':'In Chain Normal P_chain'}, inplace=True)
meantab.rename(columns={'On Target':'On Target Normal P_chain'}, inplace=True)
stdtab.rename(columns={'In Chain':'In Chain Normal P_chain'}, inplace=True)
stdtab.rename(columns={'On Target':'On Target Normal P_chain'}, inplace=True)

meantab2.rename(columns={'In Chain':'In Chain Low P_chain'}, inplace=True)
meantab2.rename(columns={'On Target':'On Target Low P_chain'}, inplace=True)
stdtab2.rename(columns={'In Chain':'In Chain Low P_chain'}, inplace=True)
stdtab2.rename(columns={'On Target':'On Target Low P_chain'}, inplace=True)


    

In [118]:

    

med = pd.concat([meantab, meantab2], axis=1)


    

In [119]:

    

error = pd.concat([stdtab, stdtab2], axis=1)


    

In [122]:

    

med[::100].plot(yerr=pd.concat([stdtab, stdtab2], axis=1),figsize=(15, 12)).set_title('Probability for becomming a chain member comparison')

fig = plt.gcf()
fig.savefig(path + '/lowerversushigh.pdf')


    

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