def inverse_model(sensor, num_sensors, inputcloudinessbins, num_bins):
directsun=facadeorientation.orientation()
zone_orientation=directsun[1]
starttime=math.floor(float(directsun[2])+float(directsun[3])/60)
endtime=math.ceil(float(directsun[5])+float(directsun[6])/60)
#Get data from database
connection=sqlite3.connect('data.db')
cursor=connection.cursor()
#define dicts to save data
win_daylight=dict()
win_sunangle=dict()
win_hours=dict()
newwin_daylight=dict()
sensors=sensor
cloudinessbins= inputcloudinessbins
bins=num_bins
cloudy=['Clear','Partly Cloudy','Scattered Clouds','Mostly Cloudy','Light Rain','Rain','Overcast','Heavy Rain','Fog','Haze'] #number of cloudiness could be user defined'''
n=0
getclouds=[]
while n+len(cloudy)/int(cloudinessbins)<=len(cloudy):
cloudset=cloudy[n:n+len(cloudy)/int(cloudinessbins)]
getclouds.append(cloudset)
n=n+len(cloudy)/int(cloudinessbins)
#for sensor in range(2,int(sensors)+2,1): #get values for each sensor in the room
table='light'+str(sensor)
daylight=dict()
worklight=dict()
sunangle=dict()
hours=dict()
newdaylight=dict()
newsunangle=dict()
coeffam=dict()
constantam=dict()
rvalueam=dict()
sunangles=dict()
sunanglerange=dict()
for clouds in range(len(getclouds)): #for each level of cloudiness
win_daylight[clouds]=[]
win_sunangle[clouds]=[]
win_hours[clouds]=[]
hours[clouds]=[]
newwin_daylight[clouds]=[]
newdaylight[clouds]=[]
newsunangle[clouds]=[]
daylight[clouds]=[]
sunangle[clouds]=[]
sunanglerange[clouds]=[]
sunangles[clouds]=[]
getcloudiness=[]
clouded=getclouds[clouds]
getcloudiness.append(clouded)
y1=[]
y2=[]
#print clouded
for count in range(len(clouded)):
cursor.execute('SELECT altitude, hour FROM light1 WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"' % (starttime,endtime,clouded[count]))
y1.append(cursor.fetchall())
n=0
while n<=len(cloudy)/int(cloudinessbins)-1:
for count in y1[n]:
altitude=float(count[0])
hour=int(count[1])
if altitude>=0:
win_sunangle[clouds].append(altitude)
win_hours[clouds].append(hour)
n+=1
for count in range(len(clouded)):
cursor.execute('SELECT altitude, hour FROM %s WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"' %(table,starttime,endtime,clouded[count]))
y2.append(cursor.fetchall())
n=0
while n<=len(cloudy)/int(cloudinessbins)-1:
for count in y2[n]:
altitude=float(count[0])
hour=int(count[1])
if altitude>=0:
sunangle[clouds].append(altitude)
hours[clouds].append(hour)
n+=1
if len(sunangle[clouds])>len(win_sunangle[clouds]):
datalength=len(win_sunangle[clouds])
else:
datalength=len(sunangle[clouds])
win_daylight[clouds]=dict()
daylight[clouds]=dict()
coeffam[clouds]=dict()
constantam[clouds]=dict()
rvalueam[clouds]=dict()
if len(sunangle[clouds])>1 and len(win_sunangle[clouds])>1:
if max(sunangle[clouds])>=max(win_sunangle[clouds]):
if min(sunangle[clouds])>=min(win_sunangle[clouds]):
sunanglerange[clouds]=np.arange(math.floor(min(sunangle[clouds])),math.ceil(max(win_sunangle[clouds])),int(bins))
else:
sunanglerange[clouds]=np.arange(math.floor(min(win_sunangle[clouds])),math.ceil(max(win_sunangle[clouds])),int(bins))
else:
if min(sunangle[clouds])>=min(win_sunangle[clouds]):
sunanglerange[clouds]=np.arange(math.floor(min(sunangle[clouds])),math.ceil(max(sunangle[clouds])),int(bins))
else:
sunanglerange[clouds]=np.arange(math.floor(min(win_sunangle[clouds])),math.ceil(max(sunangle[clouds])),int(bins))
#print sunanglerange[clouds],clouded,clouds
y3=dict()
y4=dict()
#angle = range(len(sunanglerange[clouds])-1)[0]
for angle in sunanglerange[clouds]:
print angle
"""y3[angle]=[]
def inverse_model(sensor, num_sensors, num_cloud_bins, num_bins):
returned = []
directsun=facadeorientation.orientation()
zone_orientation=directsun[1]
starttime=math.floor(float(directsun[2])+float(directsun[3])/60)
endtime=math.ceil(float(directsun[5])+float(directsun[6])/60)
#Get data from database
connection=sqlite3.connect('data.db')
cursor=connection.cursor()
#define dicts to save data
win_daylight=dict()
win_sunangle=dict()
win_hours=dict()
newwin_daylight=dict()
sensors=num_sensors
cloudinessbins=num_cloud_bins
bins= num_bins
cloudy=['Clear','Partly Cloudy','Scattered Clouds','Mostly Cloudy','Light Rain','Rain','Overcast','Heavy Rain','Fog','Haze'] #number of cloudiness could be user defined'''
n=0
getclouds=[]
while n+len(cloudy)/int(cloudinessbins)<=len(cloudy):
cloudset=cloudy[n:n+len(cloudy)/int(cloudinessbins)]
getclouds.append(cloudset)
n=n+len(cloudy)/int(cloudinessbins)
#for sensor in range(2,int(sensors)+2,1): #get values for each sensor in the room
table='light'+str(sensor)
daylight=dict()
worklight=dict()
sunangle=dict()
hours=dict()
newdaylight=dict()
newsunangle=dict()
coeffam=dict()
constantam=dict()
rvalueam=dict()
sunangles=dict()
sunanglerange=dict()
for clouds in range(len(getclouds)): #for each level of cloudiness
win_daylight[clouds]=[]
win_sunangle[clouds]=[]
win_hours[clouds]=[]
hours[clouds]=[]
newwin_daylight[clouds]=[]
newdaylight[clouds]=[]
newsunangle[clouds]=[]
daylight[clouds]=[]
sunangle[clouds]=[]
sunanglerange[clouds]=[]
sunangles[clouds]=[]
getcloudiness=[]
clouded=getclouds[clouds]
getcloudiness.append(clouded)
y1=[]
y2=[]
#print clouded
for count in range(len(clouded)):
cursor.execute('SELECT altitude, hour FROM light1 WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"' % (starttime,endtime,clouded[count]))
y1.append(cursor.fetchall())
n=0
while n<=len(cloudy)/int(cloudinessbins)-1:
for count in y1[n]:
altitude=float(count[0])
hour=int(count[1])
if altitude>=0:
win_sunangle[clouds].append(altitude)
win_hours[clouds].append(hour)
n+=1
for count in range(len(clouded)):
cursor.execute('SELECT altitude, hour FROM %s WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"' %(table,starttime,endtime,clouded[count]))
y2.append(cursor.fetchall())
n=0
while n<=len(cloudy)/int(cloudinessbins)-1:
for count in y2[n]:
altitude=float(count[0])
hour=int(count[1])
if altitude>=0:
sunangle[clouds].append(altitude)
hours[clouds].append(hour)
n+=1
if len(sunangle[clouds])>len(win_sunangle[clouds]):
datalength=len(win_sunangle[clouds])
else:
datalength=len(sunangle[clouds])
win_daylight[clouds]=dict()
daylight[clouds]=dict()
coeffam[clouds]=dict()
constantam[clouds]=dict()
rvalueam[clouds]=dict()
if len(sunangle[clouds])>1 and len(win_sunangle[clouds])>1:
if max(sunangle[clouds])>=max(win_sunangle[clouds]):
if min(sunangle[clouds])>=min(win_sunangle[clouds]):
sunanglerange[clouds]=np.arange(math.floor(min(sunangle[clouds])),math.ceil(max(win_sunangle[clouds])),int(bins))
else:
sunanglerange[clouds]=np.arange(math.floor(min(win_sunangle[clouds])),math.ceil(max(win_sunangle[clouds])),int(bins))
else:
if min(sunangle[clouds])>=min(win_sunangle[clouds]):
sunanglerange[clouds]=np.arange(math.floor(min(sunangle[clouds])),math.ceil(max(sunangle[clouds])),int(bins))
else:
sunanglerange[clouds]=np.arange(math.floor(min(win_sunangle[clouds])),math.ceil(max(sunangle[clouds])),int(bins))
#print sunanglerange[clouds],clouded,clouds
y3=dict()
y4=dict()
for angle in range(len(sunanglerange[clouds])-1):
y3[angle]=[]
for count in range(len(clouded)):
cursor.execute('SELECT light FROM light1 WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s" AND altitude>=%s AND altitude<=%s' % (starttime,endtime,clouded[count],sunanglerange[clouds][angle],sunanglerange[clouds][angle+1]))
y3[angle].append(cursor.fetchall())
#print sunanglerange[clouds][angle],y3[angle],clouded
win_daylight[clouds][angle]=[]
n=0
while n<=len(cloudy)/int(cloudinessbins)-1:
for count in y3[angle][n]:
if float(count[0])>1:
actualdaylight=round(float(count[0]),2)
win_daylight[clouds][angle].append(actualdaylight)
n+=1
#print len(win_daylight[clouds][angle]),' ',clouded,' ',sunanglerange[clouds][angle]
for angle in range(len(sunanglerange[clouds])-1):
y4[angle]=[]
for count in range(len(clouded)):
cursor.execute('SELECT light FROM %s WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s" AND altitude>=%s AND altitude<=%s' % (table,starttime,endtime,clouded[count],sunanglerange[clouds][angle],sunanglerange[clouds][angle+1]))
y4[angle].append(cursor.fetchall())
daylight[clouds][angle]=[]
coeffam[clouds][angle]=[]
constantam[clouds][angle]=[]
rvalueam[clouds][angle]=[]
n=0
while n<=len(cloudy)/int(cloudinessbins)-1:
for count in y4[angle][n]:
if float(count[0])>1:
actualworklight=round(float(count[0]),2)
daylight[clouds][angle].append(actualworklight)
n+=1
#print len(daylight[clouds][angle]),' ',clouded,' ',sunanglerange[clouds][angle]
if len(win_daylight[clouds][angle])>len(daylight[clouds][angle]):
finaldatalength=len(daylight[clouds][angle])
else:
finaldatalength=len(win_daylight[clouds][angle])
#filename="coefficients_"+str(sunanglerange[clouds][angle])+'_'+str(clouds)+".txt"
#filename="coefficients.txt"
#savedata=open('C:\Users\chandrayee\Documents\GitHub\sensor-placement\\coefficients1_10_2sun\\'+filename,'a')
##PERFORM OLS
if finaldatalength>2:
adata=vstack((win_daylight[clouds][angle][0:finaldatalength],daylight[clouds][angle][0:finaldatalength]))
realadata=adata.transpose()
x=realadata[:,0]
y=realadata[:,1]
X=sm.add_constant(x)
model = sm.OLS(y, X).fit()
if len(model.params)>1:
coeffam[clouds][angle]=round(model.params[0],3)
constantam[clouds][angle]=round(model.params[1],3)
rvalueam[clouds][angle]=round(model.rsquared,3)
#print "The coeff, constant and rvalue are", coeffam[clouds][angle], constantam[clouds][angle], rvalueam[clouds][angle], "for", clouded, "and angle", sunanglerange[clouds][angle]
returned.append([sunanglerange[clouds][angle], clouded, coeffam[clouds][angle], constantam[clouds][angle], rvalueam[clouds][angle]])
return returned
def sunangle_range(sensor, num_sensors, inputcloudinessbins, num_bins):
#Get zone orientation and time for which the zone faces direct sun
directsun = facadeorientation.orientation()
zone_orientation = directsun[1]
starttime = math.floor(float(directsun[2]) + float(directsun[3]) / 60)
endtime = math.ceil(float(directsun[5]) + float(directsun[6]) / 60)
#Get data from database
connection = sqlite3.connect('data.db')
cursor = connection.cursor()
#define dicts to save data
win_daylight = dict()
win_sunangle = dict()
win_hours = dict()
newwin_daylight = dict()
sensors = num_sensors
cloudinessbins = inputcloudinessbins
bins = num_bins
cloudy = [
'Clear', 'Partly Cloudy', 'Scattered Clouds', 'Mostly Cloudy',
'Light Rain', 'Rain', 'Overcast', 'Heavy Rain', 'Fog', 'Haze'
] #number of cloudiness could be user defined'''
n = 0
getcloudiness = []
getclouds = []
while n + len(cloudy) / int(cloudinessbins) <= len(cloudy):
cloudset = cloudy[n:n + len(cloudy) / int(cloudinessbins)]
getclouds.append(cloudset)
n = n + len(cloudy) / int(cloudinessbins)
#for sensor in range(2,int(sensors)+2,1): #get values for each sensor in the room
table = 'light' + str(sensor)
daylight = dict()
worklight = dict()
sunangle = dict()
hours = dict()
newdaylight = dict()
newsunangle = dict()
coeffam = dict()
constantam = dict()
rvalueam = dict()
sunangles = dict()
sunanglerange = dict()
for clouds in range(len(getclouds)): #for each level of cloudiness
win_daylight[clouds] = []
win_sunangle[clouds] = []
win_hours[clouds] = []
hours[clouds] = []
newwin_daylight[clouds] = []
newdaylight[clouds] = []
newsunangle[clouds] = []
daylight[clouds] = []
sunangle[clouds] = []
sunanglerange[clouds] = []
sunangles[clouds] = []
clouded = getclouds[clouds]
getcloudiness.append(clouded)
y1 = []
y2 = []
#print clouded
for count in range(len(clouded)):
cursor.execute(
'SELECT altitude, hour FROM light1 WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"'
% (starttime, endtime, clouded[count]))
y1.append(cursor.fetchall())
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y1[n]:
altitude = float(count[0])
hour = int(count[1])
if altitude >= 0:
win_sunangle[clouds].append(altitude)
win_hours[clouds].append(hour)
n += 1
for count in range(len(clouded)):
cursor.execute(
'SELECT altitude, hour FROM %s WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"'
% (table, starttime, endtime, clouded[count]))
y2.append(cursor.fetchall())
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y2[n]:
altitude = float(count[0])
hour = int(count[1])
if altitude >= 0:
sunangle[clouds].append(altitude)
hours[clouds].append(hour)
n += 1
if len(sunangle[clouds]) > len(win_sunangle[clouds]):
datalength = len(win_sunangle[clouds])
else:
datalength = len(sunangle[clouds])
win_daylight[clouds] = dict()
daylight[clouds] = dict()
coeffam[clouds] = dict()
constantam[clouds] = dict()
rvalueam[clouds] = dict()
if len(sunangle[clouds]) > 1 and len(win_sunangle[clouds]) > 1:
if max(sunangle[clouds]) >= max(win_sunangle[clouds]):
if min(sunangle[clouds]) >= min(win_sunangle[clouds]):
sunanglerange[clouds] = np.arange(
math.floor(min(sunangle[clouds])),
math.ceil(max(win_sunangle[clouds])), int(bins))
else:
sunanglerange[clouds] = np.arange(
math.floor(min(win_sunangle[clouds])),
math.ceil(max(win_sunangle[clouds])), int(bins))
else:
if min(sunangle[clouds]) >= min(win_sunangle[clouds]):
sunanglerange[clouds] = np.arange(
math.floor(min(sunangle[clouds])),
math.ceil(max(sunangle[clouds])), int(bins))
else:
sunanglerange[clouds] = np.arange(
math.floor(min(win_sunangle[clouds])),
math.ceil(max(sunangle[clouds])), int(bins))
return sunanglerange[clouds]
def inverse_model(sensor, num_sensors, inputcloudinessbins, num_bins, angle):
#Get zone orientation and time for which the zone faces direct sun
directsun = facadeorientation.orientation()
zone_orientation = directsun[1]
starttime = math.floor(float(directsun[2]) + float(directsun[3]) / 60)
endtime = math.ceil(float(directsun[5]) + float(directsun[6]) / 60)
#Get data from database
connection = sqlite3.connect('data.db')
cursor = connection.cursor()
#define dicts to save data
win_daylight = dict()
win_sunangle = dict()
win_hours = dict()
newwin_daylight = dict()
sensors = num_sensors
cloudinessbins = inputcloudinessbins
bins = num_bins
cloudy = [
'Clear', 'Partly Cloudy', 'Scattered Clouds', 'Mostly Cloudy',
'Light Rain', 'Rain', 'Overcast', 'Heavy Rain', 'Fog', 'Haze'
] #number of cloudiness could be user defined'''
n = 0
getcloudiness = []
getclouds = []
while n + len(cloudy) / int(cloudinessbins) <= len(cloudy):
cloudset = cloudy[n:n + len(cloudy) / int(cloudinessbins)]
getclouds.append(cloudset)
n = n + len(cloudy) / int(cloudinessbins)
#for sensor in range(2,int(sensors)+2,1): #get values for each sensor in the room
table = 'light' + str(sensor)
daylight = dict()
worklight = dict()
sunangle = dict()
hours = dict()
newdaylight = dict()
newsunangle = dict()
coeffam = dict()
constantam = dict()
rvalueam = dict()
sunangles = dict()
sunanglerange = dict()
for clouds in range(len(getclouds)): #for each level of cloudiness
win_daylight[clouds] = []
win_sunangle[clouds] = []
win_hours[clouds] = []
hours[clouds] = []
newwin_daylight[clouds] = []
newdaylight[clouds] = []
newsunangle[clouds] = []
daylight[clouds] = []
sunangle[clouds] = []
sunanglerange[clouds] = []
sunangles[clouds] = []
clouded = getclouds[clouds]
getcloudiness.append(clouded)
y1 = []
y2 = []
#print clouded
for count in range(len(clouded)):
cursor.execute(
'SELECT altitude, hour FROM light1 WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"'
% (starttime, endtime, clouded[count]))
y1.append(cursor.fetchall())
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y1[n]:
altitude = float(count[0])
hour = int(count[1])
if altitude >= 0:
win_sunangle[clouds].append(altitude)
win_hours[clouds].append(hour)
n += 1
for count in range(len(clouded)):
cursor.execute(
'SELECT altitude, hour FROM %s WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s"'
% (table, starttime, endtime, clouded[count]))
y2.append(cursor.fetchall())
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y2[n]:
altitude = float(count[0])
hour = int(count[1])
if altitude >= 0:
sunangle[clouds].append(altitude)
hours[clouds].append(hour)
n += 1
if len(sunangle[clouds]) > len(win_sunangle[clouds]):
datalength = len(win_sunangle[clouds])
else:
datalength = len(sunangle[clouds])
win_daylight[clouds] = dict()
daylight[clouds] = dict()
coeffam[clouds] = dict()
constantam[clouds] = dict()
rvalueam[clouds] = dict()
if len(sunangle[clouds]) > 1 and len(win_sunangle[clouds]) > 1:
if max(sunangle[clouds]) >= max(win_sunangle[clouds]):
if min(sunangle[clouds]) >= min(win_sunangle[clouds]):
sunanglerange[clouds] = np.arange(
math.floor(min(sunangle[clouds])),
math.ceil(max(win_sunangle[clouds])), int(bins))
else:
sunanglerange[clouds] = np.arange(
math.floor(min(win_sunangle[clouds])),
math.ceil(max(win_sunangle[clouds])), int(bins))
else:
if min(sunangle[clouds]) >= min(win_sunangle[clouds]):
sunanglerange[clouds] = np.arange(
math.floor(min(sunangle[clouds])),
math.ceil(max(sunangle[clouds])), int(bins))
else:
sunanglerange[clouds] = np.arange(
math.floor(min(win_sunangle[clouds])),
math.ceil(max(sunangle[clouds])), int(bins))
#return sunanglerange[clouds]
y3 = dict()
y4 = dict()
#for angle in range(len(sunanglerange[clouds])-1):
angle = angle_range
y3[angle] = []
for count in range(len(clouded)):
cursor.execute(
'SELECT light FROM light1 WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s" AND altitude>=%s AND altitude<=%s'
% (starttime, endtime, clouded[count],
sunanglerange[clouds][angle],
sunanglerange[clouds][angle + 1]))
y3[angle].append(cursor.fetchall())
#print sunanglerange[clouds][angle],y3[angle],clouded
win_daylight[clouds][angle] = []
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y3[angle][n]:
if float(count[0]) > 1:
actualdaylight = round(float(count[0]), 2)
win_daylight[clouds][angle].append(actualdaylight)
n += 1
#print len(win_daylight[clouds][angle]),' ',clouded,' ',sunanglerange[clouds][angle]
#for angle in range(len(sunanglerange[clouds])-1):
y4[angle] = []
for count in range(len(clouded)):
cursor.execute(
'SELECT light FROM %s WHERE unixtime>=1.362175776e+12 AND unixtime<=1.362729428e+12 AND hour>=%s AND hour<=%s AND cloudiness="%s" AND altitude>=%s AND altitude<=%s'
% (table, starttime, endtime, clouded[count],
sunanglerange[clouds][angle],
sunanglerange[clouds][angle + 1]))
y4[angle].append(cursor.fetchall())
daylight[clouds][angle] = []
coeffam[clouds][angle] = []
constantam[clouds][angle] = []
rvalueam[clouds][angle] = []
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y4[angle][n]:
if float(count[0]) > 1:
actualworklight = round(float(count[0]), 2)
daylight[clouds][angle].append(actualworklight)
n += 1
#print len(daylight[clouds][angle]),' ',clouded,' ',sunanglerange[clouds][angle]
if len(win_daylight[clouds][angle]) > len(daylight[clouds][angle]):
finaldatalength = len(daylight[clouds][angle])
else:
finaldatalength = len(win_daylight[clouds][angle])
if finaldatalength > 2:
adata = vstack((win_daylight[clouds][angle][0:finaldatalength],
daylight[clouds][angle][0:finaldatalength]))
realadata = adata.transpose()
x = realadata[:, 0]
y = realadata[:, 1]
X = sm.add_constant(x)
model = sm.OLS(y, X).fit()
if len(model.params) > 1:
coeffam[clouds][angle] = round(model.params[0], 3)
constantam[clouds][angle] = round(model.params[1], 3)
rvalueam[clouds][angle] = round(model.rsquared, 3)
return [
coeffam[clouds][angle], constantam[clouds][angle],
rvalueam[clouds][angle], clouded, sunanglerange[clouds][angle]
]
from datetime import date
import matplotlib as mpl
from matplotlib import pyplot as plt
from time import mktime, localtime, gmtime, strftime
import math
import pdb
import DatabaseLight
import sqlite3
import facadeorientation
#Find the point biggest step change in daylight which will give the facade orientation for a given day from sun azimuth
#From the facade orientation it will be possible to find out how long the sun will be in this direction
#We will 4 consecutive clear days and compute the rate of change of illuminance and pick the time corresponding to majority days
#We then record the azimuth for this hour and assume this is the facade orientation
#Get zone orientation and time for which the zone faces direct sun
directsun=facadeorientation.orientation()
zone_orientation=directsun[1]
starttime=math.floor(float(directsun[2])+float(directsun[3])/60)
endtime=math.ceil(float(directsun[5])+float(directsun[6])/60)
#Get data from database
connection=sqlite3.connect('data.db')
cursor=connection.cursor()
#define dicts to save data
win_daylight=dict()
win_sunangle=dict()
win_hours=dict()
newwin_daylight=dict()
sensors=raw_input('Enter the number of sensors you want to draw the relationship for: ')
cloudinessbins=raw_input('Enter the bin size for cloudiness (10 is maximum and 2 is minimum, 1,2,5,10 etc. enter even number): ')
bins=raw_input("Enter the bin size of sunangle in degrees: ") #usually each sun angle bin is one degree, users can increase the bin size
cloudy=['Clear','Partly Cloudy','Scattered Clouds','Mostly Cloudy','Light Rain','Rain','Overcast','Heavy Rain','Fog','Haze'] #number of cloudiness could be user defined'''
def nasa_inverse_model(sensor, num_sensors, num_cloud_bins, num_bins):
returned = []
directsun = facadeorientation.orientation()
zone_orientation = directsun[1]
starttime = math.floor(float(directsun[2]) + float(directsun[3]) / 60)
endtime = math.ceil(float(directsun[5]) + float(directsun[6]) / 60)
#Get data from database
connection = sqlite3.connect('data.db')
cursor = connection.cursor()
#define dicts to save data
win_daylight = dict()
win_sunangle = dict()
win_hours = dict()
newwin_daylight = dict()
sensors = num_sensors
cloudinessbins = num_cloud_bins
bins = num_bins
cloudy = [
'Clear', 'Partly Cloudy', 'Scattered Clouds', 'Mostly Cloudy',
'Light Rain', 'Rain', 'Overcast', 'Heavy Rain', 'Fog', 'Haze'
] #number of cloudiness could be user defined'''
n = 0
getclouds = []
while n + len(cloudy) / int(cloudinessbins) <= len(cloudy):
cloudset = cloudy[n:n + len(cloudy) / int(cloudinessbins)]
getclouds.append(cloudset)
n = n + len(cloudy) / int(cloudinessbins)
#for sensor in range(2,int(sensors)+2,1): #get values for each sensor in the room
table = 'nasalight' + str(sensor)
daylight = dict()
worklight = dict()
sunangle = dict()
hours = dict()
newdaylight = dict()
newsunangle = dict()
coeffam = dict()
constantam = dict()
rvalueam = dict()
sunangles = dict()
sunanglerange = dict()
for clouds in range(len(getclouds)): #for each level of cloudiness
win_daylight[clouds] = []
win_sunangle[clouds] = []
win_hours[clouds] = []
hours[clouds] = []
newwin_daylight[clouds] = []
newdaylight[clouds] = []
newsunangle[clouds] = []
daylight[clouds] = []
sunangle[clouds] = []
sunanglerange[clouds] = []
sunangles[clouds] = []
getcloudiness = []
clouded = getclouds[clouds]
getcloudiness.append(clouded)
y1 = []
y2 = []
#print clouded
for count in range(len(clouded)):
cursor.execute(
'SELECT altitude, hour FROM nasalight8 WHERE unixtime>=1337903413000.0 AND unixtime<=1338414791000.0 AND hour>=%s AND hour<=%s AND cloudiness="%s"'
% (starttime, endtime, clouded[count]))
y1.append(cursor.fetchall())
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y1[n]:
altitude = float(count[0])
hour = int(count[1])
if altitude >= 0:
win_sunangle[clouds].append(altitude)
win_hours[clouds].append(hour)
n += 1
for count in range(len(clouded)):
cursor.execute(
'SELECT altitude, hour FROM %s WHERE unixtime>=1337903413000.0 AND unixtime<=1338414791000.0 AND hour>=%s AND hour<=%s AND cloudiness="%s"'
% (table, starttime, endtime, clouded[count]))
y2.append(cursor.fetchall())
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y2[n]:
altitude = float(count[0])
hour = int(count[1])
if altitude >= 0:
sunangle[clouds].append(altitude)
hours[clouds].append(hour)
n += 1
if len(sunangle[clouds]) > len(win_sunangle[clouds]):
datalength = len(win_sunangle[clouds])
else:
datalength = len(sunangle[clouds])
win_daylight[clouds] = dict()
daylight[clouds] = dict()
coeffam[clouds] = dict()
constantam[clouds] = dict()
rvalueam[clouds] = dict()
if len(sunangle[clouds]) > 1 and len(win_sunangle[clouds]) > 1:
if max(sunangle[clouds]) >= max(win_sunangle[clouds]):
if min(sunangle[clouds]) >= min(win_sunangle[clouds]):
sunanglerange[clouds] = np.arange(
math.floor(min(sunangle[clouds])),
math.ceil(max(win_sunangle[clouds])), int(bins))
else:
sunanglerange[clouds] = np.arange(
math.floor(min(win_sunangle[clouds])),
math.ceil(max(win_sunangle[clouds])), int(bins))
else:
if min(sunangle[clouds]) >= min(win_sunangle[clouds]):
sunanglerange[clouds] = np.arange(
math.floor(min(sunangle[clouds])),
math.ceil(max(sunangle[clouds])), int(bins))
else:
sunanglerange[clouds] = np.arange(
math.floor(min(win_sunangle[clouds])),
math.ceil(max(sunangle[clouds])), int(bins))
#print sunanglerange[clouds],clouded,clouds
y3 = dict()
y4 = dict()
for angle in range(len(sunanglerange[clouds]) - 1):
y3[angle] = []
for count in range(len(clouded)):
cursor.execute(
'SELECT light FROM nasalight8 WHERE unixtime>=1337903413000.0 AND unixtime<=1338414791000.0 AND hour>=%s AND hour<=%s AND cloudiness="%s" AND altitude>=%s AND altitude<=%s'
% (starttime, endtime, clouded[count],
sunanglerange[clouds][angle],
sunanglerange[clouds][angle + 1]))
y3[angle].append(cursor.fetchall())
#print sunanglerange[clouds][angle],y3[angle],clouded
win_daylight[clouds][angle] = []
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y3[angle][n]:
if float(count[0]) > 1:
actualdaylight = round(float(count[0]), 2)
win_daylight[clouds][angle].append(actualdaylight)
n += 1
#print len(win_daylight[clouds][angle]),' ',clouded,' ',sunanglerange[clouds][angle]
for angle in range(len(sunanglerange[clouds]) - 1):
y4[angle] = []
for count in range(len(clouded)):
cursor.execute(
'SELECT light FROM %s WHERE unixtime>=1337903413000.0 AND unixtime<=1338414791000.0 AND hour>=%s AND hour<=%s AND cloudiness="%s" AND altitude>=%s AND altitude<=%s'
% (table, starttime, endtime, clouded[count],
sunanglerange[clouds][angle],
sunanglerange[clouds][angle + 1]))
y4[angle].append(cursor.fetchall())
daylight[clouds][angle] = []
coeffam[clouds][angle] = []
constantam[clouds][angle] = []
rvalueam[clouds][angle] = []
n = 0
while n <= len(cloudy) / int(cloudinessbins) - 1:
for count in y4[angle][n]:
if float(count[0]) > 1:
actualworklight = round(float(count[0]), 2)
daylight[clouds][angle].append(actualworklight)
n += 1
#print len(daylight[clouds][angle]),' ',clouded,' ',sunanglerange[clouds][angle]
if len(win_daylight[clouds][angle]) > len(daylight[clouds][angle]):
finaldatalength = len(daylight[clouds][angle])
else:
finaldatalength = len(win_daylight[clouds][angle])
#filename="coefficients_"+str(sunanglerange[clouds][angle])+'_'+str(clouds)+".txt"
#filename="coefficients.txt"
#savedata=open('C:\Users\chandrayee\Documents\GitHub\sensor-placement\\coefficients1_10_2sun\\'+filename,'a')
##PERFORM OLS
if finaldatalength > 2:
adata = vstack((win_daylight[clouds][angle][0:finaldatalength],
daylight[clouds][angle][0:finaldatalength]))
realadata = adata.transpose()
x = realadata[:, 0]
y = realadata[:, 1]
X = sm.add_constant(x)
model = sm.OLS(y, X).fit()
if len(model.params) > 1:
coeffam[clouds][angle] = round(model.params[0], 3)
constantam[clouds][angle] = round(model.params[1], 3)
rvalueam[clouds][angle] = round(model.rsquared, 3)
#print "The coeff, constant and rvalue are", coeffam[clouds][angle], constantam[clouds][angle], rvalueam[clouds][angle], "for", clouded, "and angle", sunanglerange[clouds][angle]
returned.append([
sunanglerange[clouds][angle], clouded, coeffam[clouds][angle],
constantam[clouds][angle], rvalueam[clouds][angle]
])
return returned
