cv_trial

Complexity

Total Complexity

1

Size/Duplication

Total Lines	317
Duplicated Lines	9.46 %

Importance

Changes

0

1 Method

Rating	Name	Duplication	Size	Complexity
A	voltcycle.cv_trial.cv.det()	0	2	1

# Import packages

This module should have a docstring.

import pandas as pd
import numpy as np
import csv
import matplotlib.pyplot as plt
from dir_walker import walker
import os
import warnings

#-----------------------------------MODULE CHECKS------------------------------

# Check for modules, try to exit gracefully if not found
import sys
import imp
try:
    imp.find_module('numpy')
    foundnp = True
except ImportError:
    foundnp = False
try:
    imp.find_module('matplotlib')
    foundplot = True
except ImportError:
    foundplot = False
try:
    imp.find_module('pandas')
    foundpd = True
except ImportError:
    foundplot = False
if not foundnp:
    print("Numpy is required. Exiting")
    sys.exit()
if not foundplot:
    print("Matplotlib is required. Exiting")
    sys.exit()
if not foundpd:

The variable foundpd does not seem to be defined for all execution paths.

    print("Pandas is required. Exiting")
    sys.exit()

#-------------------------------------------------------------------------------
class cv:
    _colors = {'red': 'r', 'green': 'g', 'blue': 'b', 'yellow': 'y', 'cyan': 'c', 'magenta': 'm', 'black': 'k', 'white': 'w'}

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    _linestyles = {' ': ' ', '-': 'solid', '--': 'dashed', '-.': 'dash_dot', ':': 'dotted'}
    _markers  = {' ': ' ', '.': '.', '_' : '_', 'o': 'o', '*': '*', '+': '+', 'x': 'x', 'square': 's', 'triangle': '^', 'diamond': 'd'}

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    # Find relevant files in folder
    path = os.getcwd()
    extension = ['csv','txt','dat'] # Should include all the possible ones

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    os.chdir(path)
    result = [i for i in glob.glob('*.{}'.format(extension))]

The variable glob does not seem to be defined.

    print("Plotting the following:")
    print(result)
    #Make x-axis
    t = np.linspace(325, 1100, 776)

    def det(a, b):
        return a[0] * b[1] - a[1] * b[0]

    #set initial values (for later use)
    k=0

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    totalexport=[]

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    #iterate through CSVs
    while k < len(csvresult):

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        horiz=.04

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        exportlist=[]

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        path = os.getcwd()
        path = path + "/" + csvresult[k]
        cv=pd.read_csv(path, delimiter=",", error_bad_lines=False)

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        #Extract Data from Current Column
        currentwhole=cv.values[:,1]

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        ind=np.where(currentwhole == ' Current/A')

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        startdata=ind[0][0]

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        startdata=startdata + 1

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        currentdatastr=cv.values[startdata:,1]

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        #Extract Data from Potential Column
        potentialdatastr=cv.values[startdata:,0] 

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        #Convert all elements from strings to floats so they can be math. manipulated
        currentdataOG = [ float(x) for x in currentdatastr ]

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        potentialdata = [ float(x) for x in potentialdatastr ]

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        #Multiply current data to fit axis properly
        currentdata = [ i * (100000) for i in currentdataOG ]

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        #assign attributes to plot
        colour = 'b'
        plotlabel = csvresult[k]
        plotlabel = plotlabel[:-4]
        totalexport.append(plotlabel)
        #plot graph
        plt.plot(potentialdata, currentdata, colour, label= plotlabel)

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        plt.draw()

        count=1

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        while count <= 2:
            xline1=[] #x values of line 1 to fill in as code proceeds

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            yline1=[]

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            xline2=[]

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            yline2=[]

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            #Point Clicks and Intersections
            if count==1:

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                print('>> Please choose two points for first line (onset of oxidation)')
                line1 = plt.ginput(2) # it will wait for two clicks
                line1=np.array(line1)

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                x1=line1[0,0]

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                xline1.append(x1)
                y1=line1[0,1]

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                yline1.append(y1)
                print('>> Please choose two points for first line (onset of oxidation)')
                line2 = plt.ginput(2)
                line2=np.array(line2)

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                x2=line2[0,0]

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                xline2.append(x2)
                y2=line2[0,1]

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                yline2.append(y2)
            if count==2:

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                print('>> Please choose two points for first line (onset of reduction)')
                line1 = plt.ginput(2) # it will wait for two clicks
                line1=np.array(line1)

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                x1=line1[0,0]

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                xline1.append(x1)
                y1=line1[0,1]

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                yline1.append(y1)
                print('>> Please choose two points for first line (onset of reduction)')
                line2 = plt.ginput(2)
                line2=np.array(line2)

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                x2=line2[0,0]

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                xline2.append(x2)
                y2=line2[0,1]

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                yline2.append(y2)
            #Find intersection
            xdiff = (line1[0][0] - line1[1][0], line2[0][0] - line2[1][0])

The variable line1 does not seem to be defined for all execution paths.

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            ydiff = (line1[0][1] - line1[1][1], line2[0][1] - line2[1][1])
            div = det(xdiff, ydiff)
                #if div == 0:
                   #raise Exception('lines do not intersect')
            d = (det(*line1), det(*line2))

            #calculate onset
            x = det(d, xdiff) / div
            xline1.append(x)
            xline2.append(x)
            #make point of intersection
            y = det(d, ydiff) / div
            yline1.append(y)
            yline2.append(y)

            plt.plot(xline1,yline1,'r')

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            plt.plot(xline2,yline2,'r')

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            plt.draw()

            exportlist.append(x)
            #calculate homo/lumo
            holu = x - 4.8
            exportlist.append(holu)
            #round these values
            x = round(x,2)

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            holu = round(holu,2)

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            #make these strings instead of integers
            x = str(x)
            holu = str(holu)
            #print message on command prompt
            if count==1:

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                print('------------')
                print("Oxidation onset:")
                print(x + " V")
                print('------------')
            if count==2:

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                print('------------')
                print("Reduction onset:")
                print(x + " V")
                print('------------')
            count=count+1

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        totalexport.append(exportlist)
        #write texts to put on chart
        ox=exportlist[0]

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        ox=round(ox,3)

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        ox=str(ox)

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        homo=exportlist[1]

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        homo=round(homo,3)

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        homo=str(homo)

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        red=exportlist[2]

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        red=round(red,3)

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        red=str(red)

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        lumo=exportlist[3]

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        lumo=round(lumo,3)

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        lumo=str(lumo)

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        oxtxt = 'OX' '$_{onset}$' + ' = ' + ox + "V"
        redtxt = 'RED' '$_{onset}$' + ' = ' + red + "V"
        homotxt = 'HOMO = ' + homo + "eV"
        lumotxt = 'LUMO = ' + lumo + "eV"
        #change initial value and make first text label
        plt.gca().set_position((.1, .28, .8, .65)) # to make a bit of room for extra text
        vert = 0.14
        plt.figtext(horiz,vert,plotlabel,style='italic')

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        #plt.figure().add_subplot(111).plot(range(10), range(10))
        txtlist = [oxtxt,redtxt,homotxt, lumotxt]

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        i=0

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        #iterate through text list to make text boxes of values
        while i < len(txtlist):
            if i == 2:
                horiz=horiz+0.25

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                vert=vert+0.1

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            vert=vert-0.05

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            curr=txtlist[i]

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            plt.figtext(horiz,vert,curr)

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            i=i+1

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            continue
        #----------------------------------EXCEL EXPORT---------------------------------

        # Create a Pandas dataframe title for data.
        df0 = pd.DataFrame({'Data': ['Onset of Oxidation (V)','HOMO (eV)','Onset of Reduction (V)','LUMO (eV)']})

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        # Create a Pandas Excel writer using XlsxWriter as the engine.
        folder = 'Processed CV Data'
        if not os.path.exists(folder):
            os.makedirs(folder)

        calcname=csvresult[k]

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        calcname=calcname + '-calcs.xlsx'

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        writer = pd.ExcelWriter(os.path.join(folder,calcname), engine='xlsxwriter')

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        #Loop through data from total export list
        j=0

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        index=1

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        while j < len(totalexport):
            plotlabel=totalexport[j]

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            data=totalexport[j+1]

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            df = pd.DataFrame({plotlabel: data})
            df.to_excel(writer, sheet_name='Sheet1', startcol=index, index=False)
            j=j+2

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            index=index+1

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            continue

        # Convert the dataframe to an XlsxWriter Excel object.
        df0.to_excel(writer, sheet_name='Sheet1', startrow=1, header = False, index=False)

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        # Get the xlsxwriter workbook and worksheet objects.
        workbook  = writer.book

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        worksheet = writer.sheets['Sheet1']

        # Set the column width and format.
        worksheet.set_column('A:A', 20)
        worksheet.set_column('B:B', 15)
        worksheet.set_column('C:C', 15)
        worksheet.set_column('D:D', 15)

        # Close the Pandas Excel writer and output the Excel file.
        writer.save()
        msg= csvresult[k][:-4] + ' CV Calculations exported --------->'

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        print(msg)

        #---------> DATA TO CREATE GRAPH IN EXCEL

        # Create a Pandas Excel writer using XlsxWriter as the engine.
        dataname=csvresult[k]

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        dataname=dataname + '-dataset.xlsx'

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        writer = pd.ExcelWriter(os.path.join(folder,dataname), engine='xlsxwriter')

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        #Create wavelength column
        potentialdatastr=[float(x) for x in potentialdatastr]

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        df = pd.DataFrame({'Potential/ V': potentialdatastr})
        df.to_excel(writer, sheet_name='Sheet1', startcol=0, startrow=0, index=False)
        df1 = pd.DataFrame({'Current/ A': currentdatastr})
        df1.to_excel(writer, sheet_name='Sheet1', startcol=1, startrow=0, index=False)
        i=0

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        currentdatastr=[float(x) for x in currentdatastr]

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        microcurrentdatastr=[x*1000000 for x in currentdatastr]

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        df2 = pd.DataFrame({'Current/ microA': microcurrentdatastr})
        df2.to_excel(writer, sheet_name='Sheet1', startcol=2, startrow=0, index=False)

        # Get the xlsxwriter workbook and worksheet objects.
        workbook  = writer.book

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        worksheet = writer.sheets['Sheet1']

        # Set the column width and format.
        worksheet.set_column('A:A', 11)
        worksheet.set_column('B:B', 11)
        worksheet.set_column('C:C', 11)

        # Close the Pandas Excel writer and output the Excel file.
        writer.save()
        msg= csvresult[k][:-4] + ' CV Dataset exported --------->'

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        print(msg)

        #-------------------------------------------------------------------------------

        #Bold axis numbers and change font sizes
        ax=plt.gca()

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        for tick in ax.xaxis.get_major_ticks():
            tick.label1.set_fontsize(9)
            tick.label1.set_fontweight('bold')
        for tick in ax.yaxis.get_major_ticks():
            tick.label1.set_fontsize(9)
            tick.label1.set_fontweight('bold')
        #Labels
        plt.xlabel('Potential (V) / V',weight='bold')

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        plt.ylabel('Current (I) / x10$^{-1}$${\mu}A$',weight='bold')

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A suspicious escape sequence \m was found. Did you maybe forget to add an r prefix?

        plt.draw()
        #Graph Finished Message
        sep=" "

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        name = os.getlogin()
        name = name.split(sep, 1)[0]
        msg = 'Hey ' + name + ', ' + csvresult[k][:-4] + "'s graph has finished processing."
        picname= csvresult[k][:-4] + '.png'

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        print(msg)
        plt.savefig(os.path.join(folder,picname), bbox_inches='tight')

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        k=k+1

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        #case where if you reach your last CSV, then break the loop
        plt.show()
        if k == len(csvresult):
            plt.title('Cyclic Voltammetry',weight='bold')

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            plt.legend(loc='best')
            break
        continue