From 6a963cb43ef2986cf15e30ec355008a5df79f392 Mon Sep 17 00:00:00 2001 From: Michael Deceglie Date: Wed, 12 Jul 2017 15:37:57 -0600 Subject: [PATCH 01/47] Add clearsky tamb from clearsky_temperature branch --- MANIFEST.in | 1 + rdtools/__init__.py | 1 + rdtools/clearsky_temperature.py | 123 ++++++++++++++++++++++++++++++++ rdtools/data/temperature.hdf5 | Bin 0 -> 6223504 bytes 4 files changed, 125 insertions(+) create mode 100644 rdtools/clearsky_temperature.py create mode 100644 rdtools/data/temperature.hdf5 diff --git a/MANIFEST.in b/MANIFEST.in index 092ff664..939650cc 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,2 +1,3 @@ include versioneer.py include rdtools/_version.py +include rdtools/data/* \ No newline at end of file diff --git a/rdtools/__init__.py b/rdtools/__init__.py index ba67d735..d8972573 100644 --- a/rdtools/__init__.py +++ b/rdtools/__init__.py @@ -4,6 +4,7 @@ from degradation import degradation_classical_decomposition from degradation import degradation_year_on_year from aggregation import aggregation_insol +from clearsky_temperature import get_clearsky_tamb from ._version import get_versions __version__ = get_versions()['version'] diff --git a/rdtools/clearsky_temperature.py b/rdtools/clearsky_temperature.py new file mode 100644 index 00000000..f972938a --- /dev/null +++ b/rdtools/clearsky_temperature.py @@ -0,0 +1,123 @@ +import h5py +from numpy import arange +from datetime import timedelta, datetime +import os +import math +import pandas as pd + + + + + +def get_clearsky_tamb(times, latitude, longitude, utc_offset): + ''' + :param times: DateTimeIndex in local time, naive timezone + :param latitude: float degrees + :param longitude: float degrees + :param utc_offset: float hours + :return: pandas Series of cell sky ambient temperature + ''' + + rdtools_path = os.path.dirname(os.path.abspath(__file__)) + filepath = os.path.join(rdtools_path, 'data', 'temperature.hdf5') + + buffer = timedelta(days=80) + interval = times[1] - times[0] + points_per_day = int(timedelta(days=1)/interval) + dt = pd.date_range(times[0] - buffer, times[-1] + buffer, freq=interval) + + #print model + + + f = h5py.File(filepath, "r") + + a = f['temperature']['day'] + b = f['temperature']['night'] + + lons = len(a[:, 0, 0]) + lats = len(a[0, :, 0]) + + lon_temp = longitude - 180 + if lon_temp < 0: + lon_temp += 360 + lon_index = round(float(lons) * float(lon_temp) / 360.0) + lat_index = round(float(lats) * (90.0 - float(latitude)) / 180.0) + + #print lons, lats, lon_index, lat_index + + + df = pd.DataFrame(index=dt) + df['month'] = df.index.month + + ave_day = [] + ave_night = [] + + radius = 0 + for k in range(12): + + day = _get_pixel_value(a,lon_index,lat_index,k,radius) + night = _get_pixel_value(b, lon_index, lat_index, k, radius) + + if day == float("NaN"): + day = a[:,lat_index,k] + if night == float("NaN"): + night = a[:,lat_index,k] + + ave_day.append(day) + ave_night.append(night) + + + #print ave_day, ave_night + + + + for i in range(12): + df.loc[df['month']== i+1, 'day'] = ave_day[i] + df.loc[df['month'] == i+1, 'night'] = ave_night[i] + + + df = df.rolling(window=40 * points_per_day, win_type='gaussian').mean(std=20 * points_per_day) + df = df[(df.index >= times[0]) & (df.index <= times[-1])] + + + solar_noon_offset = longitude / 180.0 * 12.0 - utc_offset + + + df['hour_of_day'] = df.index.hour + df.index.minute / 60.0 + df['Clear Sky Temperature (C)'] = df.apply(lambda x: + _get_temperature(x['hour_of_day'], x['day'], + x['night'], solar_noon_offset), axis=1) + return df['Clear Sky Temperature (C)'] + + +def _get_pixel_value(data, i, j, k, radius): + list = [] + for x in arange(i-radius,i+radius+1): + if x < 0 or x >= len(data[:, 0, 0]): + continue + for y in arange(j - radius, j + radius + 1): + if y < 0 or y >= len(data[0,:,0]): + continue + + value = data[x, y, k] + if value == float("NaN"): + continue + + list.append(value) + + if len(list) == 0: + return float("NaN") + + return pd.Series(list).median() + + +def _get_temperature(hour_of_day, night_temp, day_temp, solar_noon_offset): + hour_offset = -4.0 + solar_noon_offset + temp_scaler = 0.7 + t_diff = day_temp - night_temp + t_ave = (day_temp + night_temp) / 2.0 + v = math.cos((hour_of_day + hour_offset) / 24.0 * 2.0 * math.pi) + t = t_diff * 0.5 * v * temp_scaler + t_ave + return t + + diff --git a/rdtools/data/temperature.hdf5 b/rdtools/data/temperature.hdf5 new file mode 100644 index 0000000000000000000000000000000000000000..c003cbcfc4d0de2e11c95683db5a1b197c250205 GIT binary patch literal 6223504 zcmeF)545CJdFT7KF$4{l#jsfMPmEWP#bTj$h%+)S7IvS)5W~b6V$eVmG$Ii$8KXuC zMqS1ZgN6{&i9{P@oE|P0|6tHXI)ou8eNG~w)er{aBH=n32d@8_h|xri(Yf{6)z9(m zqRy$e+CH2<&Cje#om2I^`+fG_zuNoIzi&PJ;-C1jAOAld{rE?(^S^@*TKC9xhqfQ< z|NZY>|NH%aeo=d=ey{g`Y1a>r*!BF|yPn^(e)Pj5*7?76>mIx7^?$Rg{qeZdo`3Sm z>xPllem(EHY~827Z}iha^+KK>RwM8eCl5~5;nR2Zy7aVjm(FT1Uh~T@f8{U#+Dl$@ z{;&OVd#Q9eR{=9VFQwm~IAGM!xw~{ZO~23FCEVRVT{9+=@HIOEOX>Hwcj>1(cJ@nt 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