main.py

import pandas
import csv
import numpy
import psySI as SI
import math
import comodel as como
from os import walk

f = []
for (dirpath, dirnames, filenames) in walk('inputs'):
    f.extend(filenames)
    break


for input in f:
    data = pandas.read_csv('inputs/'+ input)
    l = len(data)-2
    days = int(l/24)
    index = list(data)
    post = []
    post2 = []
    row = []
    row.append('Date and Time')
    for s in index:
        if index.index(s)>0:
          #k = index.index(s)
          row.append(s + '(max)')
          row.append(s + '(maxtime)')
          row.append(s+'(min)')
          row.append(s+'(mintime)')
          row.append( s+'(mean)')
#first row of output.csv
    Wl_1Fac = list(data['Wl-1Facing'])
    Wl_1Fac = Wl_1Fac[0]
    Wl_2Fac = list(data['Wl-2Facing'])
    Wl_2Fac = Wl_2Fac[0]
#headers for post2
    row2=[]
    row2.append('date and time')
    row2.append("TPI_wall1")
    row2.append("TPI_wall2")
    row2.append('TPI_roof')
    row2.append('Depreciation_factor')
    row2.append('Damping_Percentage')
    row2.append('Max_Damping_day')
    row2.append('Max_Damping_night')
    row2.append('Time_lag_day')
    row2.append('Time_lag_night')
    post2.append(row2)
    post.append(row)
    for i in range(days):
        j = (i*24) + 1
        row = []
        row2 =[]
        for s in index:
            split = data[s][j:j+24]
            splitdate = list(data['Date and Time'][j:j+24])
            if (s=='Date and Time'):
                mdate = data[s][j]
                spliter = mdate[2]
                mdate = mdate.split(' ')[0]
                mdate = mdate.split(spliter)
                (mdate[0],mdate[1])=(mdate[1],mdate[0])
                mdate = '/'.join(mdate)
                row.append(mdate)
            else:
                k = index.index(s)
                split = list(split)
                maxi = max(split)
                try:
                    timemax = splitdate[split.index(maxi)].split( )[1]
                    if splitdate[split.index(maxi)].split( )[-1] == 'PM':
                        timemax = str(int(timemax.split(':')[0]) + 12 )
                    else:
                        timemax = str(timemax.split(':')[0])
                except:
                    timemax = 'nan'
                mini = min(split)
                try:
                    timemin = splitdate[split.index(mini)].split( )[1]
                    if splitdate[split.index(mini)].split( )[-1] == 'PM':
                        timemin =  str (int(timemin.split(':')[0]) + 12 )
                    else:
                        timemin= str(timemin.split(':')[0])
                except:
                    timemin = 'nan'
                try:
                    mean = numpy.mean(split)
                except:
                    mean = 'nan'
                row.append(maxi)
                row.append(timemax)
                row.append(mini)
                row.append(timemin)
                row.append(mean)
                if (s== 'TA in'):
                    TA_in_max = maxi
                    TA_in_min = mini
                    TA_in_maxtim = timemax
                    TA_in_mintim = timemin
                    print( s + ' defined')
                if (s== 'TA out'):
                    TA_out_max = maxi
                    TA_out_min = mini
                    TA_out_maxtim = timemax
                    TA_out_mintim = timemin
                    print( s + ' defined')
                if (s== 'TWl-1 in'):
                    TWl_1_in_max = maxi
                    TWl_1_in_min = mini
                    TWl_1_in_maxtim = timemax
                    TWl_1_in_mintim = timemin
                    print( s + ' defined')
                if (s== 'TWl-1 out'):
                    TWl_1_out_max = maxi
                    TWl_1_out_min = mini
                    TWl_1_out_maxtim = timemax
                    TWl_1_out_mintim = timemin
                    print( s + ' defined')
                if (s== 'TWl-2 in'):
                    TWl_2_in_max = maxi
                    TWl_2_in_min = mini
                    TWl_2_in_maxtim = timemax
                    TWl_2_in_mintim = timemin
                    print( s + ' defined')
                if (s== 'TWl-2 out'):
                    TWl_2_out_max = maxi
                    TWl_2_out_min = mini
                    TWl_2_out_maxtim = timemax
                    TWl_2_out_mintim = timemin
                    print( s + ' defined')
                if (s== 'TRf in'):
                    TRf_in_max = maxi
                    TRf_in_min = mini
                    TRf_in_maxtim = timemin
                    TRf_in_mintim = timemax
                    print( s + ' defined')
                if (s== 'TRf out'):
                    TRf_out_max = maxi
                    TRf_out_min = mini
                    TRf_out_maxtim = timemax
                    TRf_out_mintim = timemin
                    print( s + ' defined')
        post.append(row)
        if (Wl_1Fac == 'W'):
            Corr_1= 0.75
        if (Wl_1Fac == 'E'):
            Corr_1 = 0.63
        if (Wl_1Fac == 'S'):
            Corr_1 = 0.42
        if (Wl_1Fac == 'N'):
            Corr_1 = 0.34
        if (Wl_2Fac == 'W'):
            Corr_2= 0.75
        if (Wl_2Fac == 'E'):
            Corr_2 = 0.63
        if (Wl_2Fac == 'S'):
            Corr_2 = 0.42
        if (Wl_2Fac == 'N'):
            Corr_2 = 0.34
        try:
            TPI_1 = ((((TWl_1_in_max - 30)*100)/8))
            CTPI_1 = ((TPI_1)-50) * Corr_1 + 50
        except:
            print('Wl-1 not defined')
        try:
            TPI_2 = ((((TWl_2_in_max - 30)*100)/8))
            CTPI_2 = ((TPI_2)-50) * Corr_2 + 50
        except:
            print('Wl-2 not defined')
        try:
            TPI_r = ((((TRf_in_max - 30)*100)/8))
            CTPI_r = ((TPI_r)-50) * 0.92 + 50
        except:
            print('roof not defined')
        try:
            Depreciation_factor = (TA_in_max - TA_in_min) / (TA_out_max - TA_out_min)
            Damping_Percentage = (1 - Depreciation_factor) * 100
            Max_Damping_day = TA_out_max - TA_in_max
            Max_Damping_night = TA_in_min - TA_out_min
            Time_lag_day =  int(TA_in_maxtim.split(':')[0])- int(TA_out_maxtim.split(':')[0])
            Time_lag_night = int(TA_in_mintim.split(':')[0]) - int(TA_in_mintim.split(':')[0])
        except:
            print('see all the values for TA')
        row2=[]
        row2.append(mdate)
        row2.append(CTPI_1)
        row2.append(CTPI_2)
        row2.append(CTPI_r)
        row2.append(Depreciation_factor)
        row2.append(Damping_Percentage)
        row2.append(Max_Damping_day)
        row2.append(Max_Damping_night)
        row2.append(Time_lag_day)
        row2.append(Time_lag_night)
        post2.append(row2)
    with open("result/"+input+"-output.csv", "a", newline='') as fp:
        wr = csv.writer(fp, dialect='excel')
        for i in post:
            wr.writerow(i)
    with open("result/"+input+"-performance-daily.csv", "a", newline='') as fp:
        wr = csv.writer(fp, dialect='excel')
        for i in post2:
            wr.writerow(i)
    comf = pandas.read_csv('bin/comf.csv')
    awarm = pandas.read_csv('bin/accwarm.csv')
    comb = pandas.read_csv('bin/combine.csv')
    templ = pandas.read_csv('bin/tempcomb.csv')
    hum = list(comf)
    hum2 = list(awarm)
    comf = numpy.array(comf)
    awarm = numpy.array(awarm)
    comb = numpy.array(comb)
    templ = numpy.array(templ)
    time = list(data['Date and Time'])
    tin = list(data['TA in'])
    rhin = list(data['RH in'])
    clo = list(data['Clo '])
    clo = float(clo[0])
    postcomf =[]
    row = ['Date','Time','inttime','Comfort m/s','Acceptibly warm m/s','Mixed m/s','Temp','Rh','tw','TSI','PMV','PPD','Standrd Eff Temp','TA adj','Cool effect']
    postcomf.append(row)
    vco = 0
    co = 0
    aw = 0
    unc = 0
    count = 0
    for t in time:
        if time.index(t)>0:
            d = time.index(t)
            t = t.split( )
            temp = tin[d]
            if temp>0:
                if (temp - int(temp)) >0.5:
                    temp2 = int(temp+1)
                else:
                    temp2 = int(temp)
            rh = rhin[d]
            if rh>0:
                if (rh - 10*(int(int(rh)/10))) > 5:
                    rh2 = 10*(int(int(rh)/10))+10
                else:
                    rh2 = 10*(int(int(rh)/10))
            row = []
            b = 0
            while temp2>comf[b][0] :
                b = b+1
            c = 1
            while rh2>int(hum[c]):
                c = c+1
            d=0
            while temp2>awarm[d][0]:
                d=d+1
            e=1
            while rh2>int(hum2[e]):
                e=e+1
            if comb[d][e] == 0:
                vco = vco+1
            if comb[d][e] == 1:
                co = co+1
            if comb[d][e] == 2:
                aw = aw+1
            if comb[d][e] == 3:
                unc = unc +1
            warcom = max (float(comf[b][c]),float(awarm[d][e]))
            if (comf[b][c]<=0) & (awarm[d][e]>=0):
                warcom = 3
            s = SI.state("DBT",(273+temp),"RH",(rh/100),101325)
            try:
                tw = s[5] - 273
            except TypeError:
                tw = s[5]
            try:
                TSI = (0.308*tw) + (0.745*temp) - (2.06*(math.sqrt((0.9*warcom)+0.841)))
            except:
                TSI = None
            tiime = t[1].split(':')
            if t[-1] == 'PM':
                tiime[0] =  str(int(tiime[0])+12)
            #   if (int(tiime[0])>7 & int(tiime[0])<23):
            #     Met = 1.7
            #else:
            #      Met =0.7
            Met = 1.5
            try:
                model= como.comfPMVElevatedAirspeed(temp,temp,(0.3),rh/100,Met,clo,0)
            except:
                model = [0,0,0,0,0,0,0]
            templ[d][e] = templ[d][e]+1
            count = count +1
            mdate = t[0]
            mdate = str(mdate)
            spliter = mdate[2]
            mdate = mdate.split(spliter)
            (mdate[0],mdate[1]) = (mdate[1],mdate[0])
            mdate = '/'.join(mdate)
            row.append(mdate)
            row.append(t[1])
            row.append(int(tiime[0]))
            row.append(comf[b][c])
            row.append(awarm[d][e])
            row.append(warcom)
            row.append(temp)
            #row.append(comf[b][0])
            #row.append(awarm[d][0])
            #row.append(hum[c])
            #row.append(hum2[c])
            row.append(rh)
            row.append(tw)
            row.append(TSI)
            row.append(model[0])
            row.append(model[1])
            row.append(model[2])
            row.append(model[3])
            row.append(model[4])
            postcomf.append(row)
    postcomf.append([vco,co,aw,unc])
    with open("result/"+input+"-comfort.csv", "a", newline='') as fp:
        wr = csv.writer(fp, dialect='excel')
        for i in postcomf:
            wr.writerow(i)
    templ = (templ/count)*100
    template = [hum2]
    for i in templ:
        template.append(i)
    with open("result/"+input+"-distribution.csv",'w', newline='') as fp:
        wr = csv.writer(fp,dialect = 'excel')
        wr.writerows (template)