How to use the uwg.utilities.read_csv function in uwg

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github chriswmackey / Dragonfly / uwg / weather.py View on Github external
def __init__(self,climate_file,HI,HF):
        #HI: Julian start date
        #HF: Julian final date
        #H1 and HF define the row we want

        # Open .epw file and feed csv data to self.climate_data
        try:
            self.climate_data = read_csv(climate_file)
        except Exception as e:
            raise Exception("Failed to read .epw file! {}".format(e.message))

        self.location = self.climate_data[0][1]
        cd = self.climate_data[HI:HF+1]
        self.staTemp = str2fl([cd[i][6] for i in range(len(cd))])           # drybulb [C]
        self.staTdp = str2fl([cd[i][7] for i in range(len(cd))])            # dewpoint [C]
        self.staRhum = str2fl([cd[i][8] for i in range(len(cd))])           # air relative humidity (%)
        self.staPres = str2fl([cd[i][9] for i in range(len(cd))])           # air pressure (Pa)
        self.staInfra = str2fl([cd[i][12] for i in range(len(cd))])         # horizontal Infrared Radiation Intensity (W m-2)
        self.staHor = str2fl([cd[i][13] for i in range(len(cd))])           # horizontal radiation [W m-2]
        self.staDir = str2fl([cd[i][14] for i in range(len(cd))])           # normal solar direct radiation (W m-2)
        self.staDif = str2fl([cd[i][15] for i in range(len(cd))])           # horizontal solar diffuse radiation (W m-2)
        self.staUdir = str2fl([cd[i][20] for i in range(len(cd))])          # wind direction ()
        self.staUmod = str2fl([cd[i][21] for i in range(len(cd))])          # wind speed (m s-1)
        self.staRobs = str2fl([cd[i][33] for i in range(len(cd))])          # Precipitation (mm h-1)
github chriswmackey / Dragonfly / uwg / readDOE.py View on Github external
#(listof (listof 3 eras (listof 16 climate types)))
        TypeWall    = [list_doe3[3][4:20],list_doe3[14][4:20],list_doe3[25][4:20]]            # Construction type
        RvalWall    = str2fl([list_doe3[4][4:20],list_doe3[15][4:20],list_doe3[26][4:20]])     # [m2*K/W] R-value
        TypeRoof    = [list_doe3[5][4:20],list_doe3[16][4:20],list_doe3[27][4:20]]            # Construction type
        RvalRoof    = str2fl([list_doe3[6][4:20],list_doe3[17][4:20],list_doe3[28][4:20]])     # [m2*K/W] R-value
        Uwindow     = str2fl([list_doe3[7][4:20],list_doe3[18][4:20],list_doe3[29][4:20]])     # [W/m2*K] U-factor
        SHGC        = str2fl([list_doe3[8][4:20],list_doe3[19][4:20],list_doe3[30][4:20]])     # [-] coefficient
        HVAC        = str2fl([list_doe3[9][4:20],list_doe3[20][4:20],list_doe3[31][4:20]])     # [kW] Air Conditioning
        HEAT        = str2fl([list_doe3[10][4:20],list_doe3[21][4:20],list_doe3[32][4:20]])    # [kW] Heating
        COP         = str2fl([list_doe3[11][4:20],list_doe3[22][4:20],list_doe3[33][4:20]])    # [-] Air Conditioning COP
        EffHeat     = str2fl([list_doe3[12][4:20],list_doe3[23][4:20],list_doe3[34][4:20]])    # [%] Heating Efficiency
        FanFlow     = str2fl([list_doe3[13][4:20],list_doe3[24][4:20],list_doe3[35][4:20]])    # [m3/s] Fan Max Flow Rate

        # Read Schedules (Sheet 4)
        file_doe_name_schedules = os.path.join("{}".format(DIR_DOE_PATH), "BLD{}".format(i+1),"BLD{}_Schedules.csv".format(i+1))
        list_doe4 = read_csv(file_doe_name_schedules)

        #listof(listof weekday, sat, sun (list of 24 fractions)))
        SchEquip    = str2fl([list_doe4[1][6:30],list_doe4[2][6:30],list_doe4[3][6:30]])      # Equipment Schedule 24 hrs
        SchLight    = str2fl([list_doe4[4][6:30],list_doe4[5][6:30],list_doe4[6][6:30]])      # Light Schedule 24 hrs; Wkday=Sat=Sun=Hol
        SchOcc      = str2fl([list_doe4[7][6:30],list_doe4[8][6:30],list_doe4[9][6:30]])      # Occupancy Schedule 24 hrs
        SetCool     = str2fl([list_doe4[10][6:30],list_doe4[11][6:30],list_doe4[12][6:30]])   # Cooling Setpoint Schedule 24 hrs
        SetHeat     = str2fl([list_doe4[13][6:30],list_doe4[14][6:30],list_doe4[15][6:30]])   # Heating Setpoint Schedule 24 hrs; summer design
        SchGas      = str2fl([list_doe4[16][6:30],list_doe4[17][6:30],list_doe4[18][6:30]])   # Gas Equipment Schedule 24 hrs; wkday=sat
        SchSWH      = str2fl([list_doe4[19][6:30],list_doe4[20][6:30],list_doe4[21][6:30]])   # Solar Water Heating Schedule 24 hrs; wkday=summerdesign, sat=winterdesgin


        for j in range(3):

            # j = 3 built eras
            #print"\tEra: {} @j={}".format(BUILTERA[j], j)
github chriswmackey / Dragonfly / uwg / readDOE.py View on Github external
#i = 16 types of buildings
        #print "\tType: {} @i={}".format(BLDTYPE[i], i)

        # Read building summary (Sheet 1)
        file_doe_name_bld = os.path.join("{}".format(DIR_DOE_PATH), "BLD{}".format(i+1),"BLD{}_BuildingSummary.csv".format(i+1))
        list_doe1 = read_csv(file_doe_name_bld)
        #listof(listof 3 era values)
        nFloor      = str2fl(list_doe1[3][3:6])      # Number of Floors, this will be list of floats and str if "basement"
        glazing     = str2fl(list_doe1[4][3:6])      # [?] Total
        hCeiling    = str2fl(list_doe1[5][3:6])      # [m] Ceiling height
        ver2hor     = str2fl(list_doe1[7][3:6])      # Wall to Skin Ratio
        AreaRoof    = str2fl(list_doe1[8][3:6])      # [m2] Gross Dimensions - Total area

        # Read zone summary (Sheet 2)
        file_doe_name_zone = os.path.join("{}".format(DIR_DOE_PATH), "BLD{}".format(i+1),"BLD{}_ZoneSummary.csv".format(i+1))
        list_doe2 = read_csv(file_doe_name_zone)
        #listof(listof 3 eras)
        AreaFloor   = str2fl([list_doe2[2][5],list_doe2[3][5],list_doe2[4][5]])       # [m2]
        Volume      = str2fl([list_doe2[2][6],list_doe2[3][6],list_doe2[4][6]])       # [m3]
        AreaWall    = str2fl([list_doe2[2][8],list_doe2[3][8],list_doe2[4][8]])       # [m2]
        AreaWindow  = str2fl([list_doe2[2][9],list_doe2[3][9],list_doe2[4][9]])       # [m2]
        Occupant    = str2fl([list_doe2[2][11],list_doe2[3][11],list_doe2[4][11]])    # Number of People
        Light       = str2fl([list_doe2[2][12],list_doe2[3][12],list_doe2[4][12]])    # [W/m2]
        Elec        = str2fl([list_doe2[2][13],list_doe2[3][13],list_doe2[4][13]])    # [W/m2] Electric Plug and Process
        Gas         = str2fl([list_doe2[2][14],list_doe2[3][14],list_doe2[4][14]])    # [W/m2] Gas Plug and Process
        SHW         = str2fl([list_doe2[2][15],list_doe2[3][15],list_doe2[4][15]])    # [Litres/hr] Peak Service Hot Water
        Vent        = str2fl([list_doe2[2][17],list_doe2[3][17],list_doe2[4][17]])    # [L/s/m2] Ventilation
        Infil       = str2fl([list_doe2[2][20],list_doe2[3][20],list_doe2[4][20]])    # Air Changes Per Hour (ACH) Infiltration

        # Read location summary (Sheet 3)
        file_doe_name_location = os.path.join("{}".format(DIR_DOE_PATH), "BLD{}".format(i+1),"BLD{}_LocationSummary.csv".format(i+1))
        list_doe3 = read_csv(file_doe_name_location)
github chriswmackey / Dragonfly / uwg / readDOE.py View on Github external
#listof(listof 3 eras)
        AreaFloor   = str2fl([list_doe2[2][5],list_doe2[3][5],list_doe2[4][5]])       # [m2]
        Volume      = str2fl([list_doe2[2][6],list_doe2[3][6],list_doe2[4][6]])       # [m3]
        AreaWall    = str2fl([list_doe2[2][8],list_doe2[3][8],list_doe2[4][8]])       # [m2]
        AreaWindow  = str2fl([list_doe2[2][9],list_doe2[3][9],list_doe2[4][9]])       # [m2]
        Occupant    = str2fl([list_doe2[2][11],list_doe2[3][11],list_doe2[4][11]])    # Number of People
        Light       = str2fl([list_doe2[2][12],list_doe2[3][12],list_doe2[4][12]])    # [W/m2]
        Elec        = str2fl([list_doe2[2][13],list_doe2[3][13],list_doe2[4][13]])    # [W/m2] Electric Plug and Process
        Gas         = str2fl([list_doe2[2][14],list_doe2[3][14],list_doe2[4][14]])    # [W/m2] Gas Plug and Process
        SHW         = str2fl([list_doe2[2][15],list_doe2[3][15],list_doe2[4][15]])    # [Litres/hr] Peak Service Hot Water
        Vent        = str2fl([list_doe2[2][17],list_doe2[3][17],list_doe2[4][17]])    # [L/s/m2] Ventilation
        Infil       = str2fl([list_doe2[2][20],list_doe2[3][20],list_doe2[4][20]])    # Air Changes Per Hour (ACH) Infiltration

        # Read location summary (Sheet 3)
        file_doe_name_location = os.path.join("{}".format(DIR_DOE_PATH), "BLD{}".format(i+1),"BLD{}_LocationSummary.csv".format(i+1))
        list_doe3 = read_csv(file_doe_name_location)
        #(listof (listof 3 eras (listof 16 climate types)))
        TypeWall    = [list_doe3[3][4:20],list_doe3[14][4:20],list_doe3[25][4:20]]            # Construction type
        RvalWall    = str2fl([list_doe3[4][4:20],list_doe3[15][4:20],list_doe3[26][4:20]])     # [m2*K/W] R-value
        TypeRoof    = [list_doe3[5][4:20],list_doe3[16][4:20],list_doe3[27][4:20]]            # Construction type
        RvalRoof    = str2fl([list_doe3[6][4:20],list_doe3[17][4:20],list_doe3[28][4:20]])     # [m2*K/W] R-value
        Uwindow     = str2fl([list_doe3[7][4:20],list_doe3[18][4:20],list_doe3[29][4:20]])     # [W/m2*K] U-factor
        SHGC        = str2fl([list_doe3[8][4:20],list_doe3[19][4:20],list_doe3[30][4:20]])     # [-] coefficient
        HVAC        = str2fl([list_doe3[9][4:20],list_doe3[20][4:20],list_doe3[31][4:20]])     # [kW] Air Conditioning
        HEAT        = str2fl([list_doe3[10][4:20],list_doe3[21][4:20],list_doe3[32][4:20]])    # [kW] Heating
        COP         = str2fl([list_doe3[11][4:20],list_doe3[22][4:20],list_doe3[33][4:20]])    # [-] Air Conditioning COP
        EffHeat     = str2fl([list_doe3[12][4:20],list_doe3[23][4:20],list_doe3[34][4:20]])    # [%] Heating Efficiency
        FanFlow     = str2fl([list_doe3[13][4:20],list_doe3[24][4:20],list_doe3[35][4:20]])    # [m3/s] Fan Max Flow Rate

        # Read Schedules (Sheet 4)
        file_doe_name_schedules = os.path.join("{}".format(DIR_DOE_PATH), "BLD{}".format(i+1),"BLD{}_Schedules.csv".format(i+1))
        list_doe4 = read_csv(file_doe_name_schedules)