10000 TMY loading improvements by wholmgren · Pull Request #7 · pvlib/pvlib-python · GitHub
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Merged
merged 8 commits into from
Mar 11, 2015
Merged

TMY loading improvements #7

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a5888e4
add ability to open tmy3 files via a url. required more flexible rena…
wholmgren Feb 28, 2015
c5261f9
add _ to helper function names
wholmgren Feb 28, 2015
63aba80
more minor clean up
wholmgren Feb 28, 2015
7c18634
add more tmy tests
wholmgren Feb 28, 2015
f2d92b1
add support for coerce_year
wholmgren Feb 28, 2015
f3bebbe
add network decorator
wholmgren Mar 2, 2015
e336b3e
doc clean up
wholmgren Mar 10, 2015
8d6c6b2
fix my careless merge
wholmgren Mar 10, 2015
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add ability to open tmy3 files via a url. required more flexible rena… 
…ming
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@wholmgren
wholmgren committed Feb 28, 2015
commit a5888e4755d9f0cb8d729460dd76098e931c89a5
117 changes: 72 additions & 45 deletions pvlib/tmy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,14 @@
import logging
pvl_logger = logging.getLogger('pvlib')

import pdb
import re
import datetime
import dateutil
import csv
import io
try:
from urllib2 import urlopen
except ImportError:
from urllib.request import urlopen

import pandas as pd
import numpy as np
Expand All @@ -18,53 +21,57 @@



def readtmy3(filename=None):
def readtmy3(filename=None, coerce_year=None, recolumn=True):
'''
Read a TMY3 file in to a pandas dataframe
Read a TMY3 file in to a pandas dataframe.

Read a TMY3 file and make a pandas dataframe of the data. Note that values
contained in the struct are unchanged from the TMY3 file (i.e. units
contained in the metadata dictionary are unchanged from the TMY3 file (i.e. units
are retained). In the case of any discrepencies between this
documentation and the TMY3 User's Manual ([1]), the TMY3 User's Manual
takes precedence.

If a filename is not provided, the user will be prompted to browse to
an appropriate TMY3 file.

Parameters
----------

filename : string
An optional argument which allows the user to select which
TMY3 format file should be read. A file path may also be necessary if
the desired TMY3 file is not in the MATLAB working path.
filename : None or string
If None, attempts to use an interactive file browser.
A string can be a relative file path, absolute file path,
or url.

coerce_year : None or int
If supplied, the year of the data will be coerced to this input.

recolumn : bool
If True, apply standard names to TMY3 columns.
Typically this resulsts in stripping the units from the column name.


Returns
-------

TMYDATA : DataFrame
data : DataFrame

A pandas dataframe, is provided with the components in the table below. Note
that for more detailed descriptions of each component, please consult
the TMY3 User's Manual ([1]), especially tables 1-1 through 1-6.
A pandas dataframe with the columns described in the table below.
For more detailed descriptions of each component, please consult
the TMY3 User's Manual ([1]), especially tables 1-1 through 1-6.

meta : struct
struct of meta data is created, which contains all
site metadata available in the file
metadata : dict
The site metadata available in the file.

Notes
-----

=============== ====== ===================
meta field format description
key format description
=============== ====== ===================
meta.altitude Float site elevation
meta.latitude Float site latitudeitude
meta.longitude Float site longitudeitude
meta.Name String site name
meta.State String state
meta.TZ Float timezone
meta.USAF Int USAF identifier
altitude Float site elevation
latitude Float site latitudeitude
longitude Float site longitudeitude
Name String site name
State String state
TZ Float UTC offset
USAF Int USAF identifier
=============== ====== ===================

============================= ======================================================================================================================================================
Expand Down Expand Up @@ -147,24 +154,26 @@ def readtmy3(filename=None):

[2] Wilcox, S. (2007). National Solar Radiation Database 1991 2005
Update: Users Manual. 472 pp.; NREL Report No. TP-581-41364.

See also
---------

pvl_makelocationstruct
pvl_readtmy2

'''

if filename is None: #If no filename is input
if filename is None:
try:
filename = interactive_load()
except:
raise Exception('Interactive load failed. Tkinter not supported on this system. Try installing X-Quartz and reloading')

head = ['USAF','Name','State','TZ','latitude','longitude','altitude']
headerfile = open(filename,'r')
meta = dict(zip(head,headerfile.readline().rstrip('\n').split(","))) #Read in file metadata
head = ['USAF', 'Name', 'State', 'TZ', 'latitude', 'longitude', 'altitude']

try:
csvdata = open(filename, 'r')
except IOError:
response = urlopen(filename)
csvdata = io.StringIO(response.read().decode(errors='ignore'))

# read in file metadata
meta = dict(zip(head, csvdata.readline().rstrip('\n').split(",")))

# convert metadata strings to numeric types
meta['altitude'] = float(meta['altitude'])
meta['latitude'] = float(meta['latitude'])
meta['longitude'] = float(meta['longitude'])
Expand All @@ -174,8 +183,9 @@ def readtmy3(filename=None):
TMYData = pd.read_csv(filename, header=1,
parse_dates={'datetime':['Date (MM/DD/YYYY)','Time (HH:MM)']},
date_parser=parsedate, index_col='datetime')

TMYData = recolumn(TMYData) #rename to standard column names

if recolumn:
_recolumn(TMYData) #rename to standard column names

TMYData = TMYData.tz_localize(int(meta['TZ']*3600))

Expand Down Expand Up @@ -214,8 +224,23 @@ def parsetz(UTC):



def recolumn(TMY3):
TMY3.columns = ('ETR','ETRN','GHI','GHISource','GHIUncertainty',
def _recolumn(tmy3_dataframe, inplace=True):
"""
Rename the columns of the TMY3 DataFrame.

Parameters
----------
tmy3_dataframe : DataFrame
inplace : bool
passed to DataFrame.rename()

Returns
-------
Recolumned DataFrame.
"""
raw_columns = 'ETR (W/m^2),ETRN (W/m^2),GHI (W/m^2),GHI source,GHI uncert (%),DNI (W/m^2),DNI source,DNI uncert (%),DHI (W/m^2),DHI source,DHI uncert (%),GH illum (lx),GH illum source,Global illum uncert (%),DN illum (lx),DN illum source,DN illum uncert (%),DH illum (lx),DH illum source,DH illum uncert (%),Zenith lum (cd/m^2),Zenith lum source,Zenith lum uncert (%),TotCld (tenths),TotCld source,TotCld uncert (code),OpqCld (tenths),OpqCld source,OpqCld uncert (code),Dry-bulb (C),Dry-bulb source,Dry-bulb uncert (code),Dew-point (C),Dew-point source,Dew-point uncert (code),RHum (%),RHum source,RHum uncert (code),Pressure (mbar),Pressure source,Pressure uncert (code),Wdir (degrees),Wdir source,Wdir uncert (code),Wspd (m/s),Wspd source,Wspd uncert (code),Hvis (m),Hvis source,Hvis uncert (code),CeilHgt (m),CeilHgt source,CeilHgt uncert (code),Pwat (cm),Pwat source,Pwat uncert (code),AOD (unitless),AOD source,AOD uncert (code),Alb (unitless),Alb source,Alb uncert (code),Lprecip depth (mm),Lprecip quantity (hr),Lprecip source,Lprecip uncert (code),PresWth (METAR code),PresWth source,PresWth uncert (code)'

new_columns = ['ETR','ETRN','GHI','GHISource','GHIUncertainty',
'DNI','DNISource','DNIUncertainty','DHI','DHISource','DHIUncertainty',
'GHillum','GHillumSource','GHillumUncertainty','DNillum','DNillumSource',
'DNillumUncertainty','DHillum','DHillumSource','DHillumUncertainty',
Expand All @@ -228,9 +253,11 @@ def recolumn(TMY3):
'CeilHgt','CeilHgtSource','CeilHgtUncertainty','Pwat','PwatSource',
'PwatUncertainty','AOD','AODSource','AODUncertainty','Alb','AlbSource',
'AlbUncertainty','Lprecipdepth','Lprecipquantity','LprecipSource',
'LprecipUncertainty')

return TMY3
'LprecipUncertainty','PresWth','PresWth source','PresWth uncert']

mapping = dict(zip(raw_columns.split(','), new_columns))

return tmy3_dataframe.rename(columns=mapping, inplace=True)



Expand Down
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