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#!/usr/bin/env python |
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# Last modified: Time-stamp: <2008-10-01 12:46:26 haines> |
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""" |
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how to parse data, and assert what data and info goes into |
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creating and updating monthly netcdf files |
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|
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parser : output delimited ASCII file from onsite perl script |
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creator : lat, lon, z, time, wspd, wdir, cdir, u, v, nwnd |
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updater : time, wspd, wdir, cdir, u, v, nwnd |
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Examples |
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-------- |
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|
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>> (parse, create, update) = load_processors('proc_avp_ascii_wnd') |
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or |
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>> si = get_config(cn+'.sensor_info') |
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>> (parse, create, update) = load_processors(si['met']['proc_module']) |
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|
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>> lines = load_data(filename) |
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>> data = parse(platform_info, sensor_info, lines) |
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>> create(platform_info, sensor_info, data) or |
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>> update(platform_info, sensor_info, data) |
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""" |
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from raw2proc import * |
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from procutil import * |
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from ncutil import * |
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import time |
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now_dt = datetime.utcnow() |
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now_dt.replace(microsecond=0) |
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def parser(platform_info, sensor_info, lines): |
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""" |
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parse Automated Vertical Profile Station (AVP) Wind data |
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Notes |
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----- |
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1. Wind: |
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Date, time, speed, dir, compass dir, North , East, n-samples |
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(m/s) (magN) (magN) (m/s) (m/s) |
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|
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08/11/2008 00:00:00 5.881 197 197 -5.638 -1.674 696 |
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08/11/2008 00:30:00 5.506 216 197 -4.448 -3.246 699 |
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08/11/2008 01:00:00 7.233 329 159 6.183 -3.754 705 |
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|
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""" |
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import numpy |
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from datetime import datetime |
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from time import strptime |
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|
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# get sample datetime from filename |
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fn = sensor_info['fn'] |
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sample_dt_start = filt_datetime(fn)[0] |
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N = len(lines) |
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data = { |
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'dt' : numpy.array(numpy.ones((N,), dtype=object)*numpy.nan), |
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'time' : numpy.array(numpy.ones((N,), dtype=long)*numpy.nan), |
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'wspd' : numpy.array(numpy.ones((N,), dtype=float)*numpy.nan), |
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'wdir' : numpy.array(numpy.ones((N,), dtype=float)*numpy.nan), |
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'cdir' : numpy.array(numpy.ones((N,), dtype=float)*numpy.nan), |
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'v' : numpy.array(numpy.ones((N,), dtype=float)*numpy.nan), |
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'u' : numpy.array(numpy.ones((N,), dtype=float)*numpy.nan), |
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'nwnd' : numpy.array(numpy.ones((N,), dtype=int)*numpy.nan), |
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} |
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i = 0 |
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lines.sort() |
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|
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mvar = platform_info['mvar'] # Magnetic Variation at station |
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# mvar = -8.0 # (??????) |
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|
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wnd = [] |
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for line in lines: |
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wnd = [] |
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# split line and parse float and integers |
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sw = re.split('[\s/\:]*', line) |
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for s in sw: |
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m = re.search(REAL_RE_STR, s) |
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if m: |
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wnd.append(float(m.groups()[0])) |
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if len(wnd)==12: |
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# get sample datetime from data |
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sample_str = '%02d-%02d-%4d %02d:%02d:%02d' % tuple(wnd[0:6]) |
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if sensor_info['utc_offset']: |
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sample_dt = scanf_datetime(sample_str, fmt='%m-%d-%Y %H:%M:%S') + \ |
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timedelta(hours=sensor_info['utc_offset']) |
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else: |
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sample_dt = scanf_datetime(sample_str, fmt='%m-%d-%Y %H:%M:%S') |
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wspd = int(wnd[6]) # wind speed (m/s) |
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wdir = int(wnd[7]) # wind dir (mag N) |
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cdir = wnd[8] # compass dir (mag N) |
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u = wnd[9] # Easterly (?) Component (m/s) (mag or true??) |
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v = wnd[10] # Northerly (?) Component (m/s) (mag or true??) |
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nwnd = int(wnd[11]) # Number of samples in wind average |
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|
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# combine wind dir and buoy compass direction |
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# correct direction from magnetic N to true N |
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# rotate u, v to true N |
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# or |
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# recompute u, v from direction and speed |
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data['dt'][i] = sample_dt # sample datetime |
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data['time'][i] = dt2es(sample_dt) # sample time in epoch seconds |
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data['wspd'][i] = wspd |
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data['wdir'][i] = wdir |
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data['cdir'][i] = cdir |
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data['u'][i] = u |
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data['v'][i] = v |
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data['nwnd'][i] = nwnd |
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i=i+1 |
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# if len(wnd)==12 |
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# for line |
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return data |
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def creator(platform_info, sensor_info, data): |
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# |
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# |
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title_str = sensor_info['description']+' at '+ platform_info['location'] |
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global_atts = { |
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'title' : title_str, |
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'institution' : 'University of North Carolina at Chapel Hill (UNC-CH)', |
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'institution_url' : 'http://nccoos.org', |
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'institution_dods_url' : 'http://nccoos.org', |
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'metadata_url' : 'http://nccoos.org', |
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'references' : 'http://nccoos.org', |
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'contact' : 'Sara Haines (haines@email.unc.edu)', |
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# |
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'source' : 'AVP Wind Observations', |
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'history' : 'raw2proc using ' + sensor_info['process_module'], |
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'comment' : 'File created using pycdf'+pycdfVersion()+' and numpy '+pycdfArrayPkg(), |
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# conventions |
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'Conventions' : 'CF-1.0; SEACOOS-CDL-v2.0', |
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# SEACOOS CDL codes |
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'format_category_code' : 'fixed-point', |
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'institution_code' : platform_info['institution'], |
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'platform_code' : platform_info['id'], |
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'package_code' : sensor_info['id'], |
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# institution specific |
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'project' : 'North Carolina Coastal Ocean Observing System (NCCOOS)', |
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'project_url' : 'http://nccoos.org', |
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# timeframe of data contained in file yyyy-mm-dd HH:MM:SS |
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'start_date' : data['dt'][0].strftime("%Y-%m-%d %H:%M:%S"), |
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'end_date' : data['dt'][-1].strftime("%Y-%m-%d %H:%M:%S"), |
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'release_date' : now_dt.strftime("%Y-%m-%d %H:%M:%S"), |
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# |
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'creation_date' : now_dt.strftime("%Y-%m-%d %H:%M:%S"), |
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'modification_date' : now_dt.strftime("%Y-%m-%d %H:%M:%S"), |
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'process_level' : 'level1', |
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# |
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# must type match to data (e.g. fillvalue is real if data is real) |
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'_FillValue' : -99999., |
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} |
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var_atts = { |
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# coordinate variables |
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'time' : {'short_name': 'time', |
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'long_name': 'Sample Time', |
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'standard_name': 'time', |
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'units': 'seconds since 1970-1-1 00:00:00 -0', # UTC |
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'axis': 'T', |
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}, |
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'lat' : {'short_name': 'lat', |
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'long_name': 'Latitude in Decimal Degrees', |
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'standard_name': 'latitude', |
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'reference':'geographic coordinates', |
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'units': 'degrees_north', |
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'valid_range':(-90.,90.), |
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'axis': 'Y', |
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}, |
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'lon' : {'short_name': 'lon', |
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'long_name': 'Longitude in Decimal Degrees', |
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'standard_name': 'longitude', |
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'reference':'geographic coordinates', |
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'units': 'degrees_east', |
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'valid_range':(-180.,180.), |
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'axis': 'Y', |
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}, |
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'z' : {'short_name': 'z', |
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'long_name': 'Height', |
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'standard_name': 'height', |
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'reference':'zero at sea-surface', |
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'positive': 'up', |
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'units': 'm', |
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'axis': 'Z', |
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}, |
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# data variables |
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'wspd' : {'short_name': 'wspd', |
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'long_name': 'Wind Speed', |
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'standard_name': 'wind_speed', |
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'units': 'm s-1', |
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'can_be_normalized': 'no', |
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'z' : sensor_info['anemometer_height'], |
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}, |
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'wdir' : {'short_name': 'wdir', |
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'long_name': 'Wind Direction from', |
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'standard_name': 'wind_from_direction', |
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'reference': 'clockwise from Magnetic North', |
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'valid_range': (0., 360), |
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'units': 'degrees', |
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'z' : sensor_info['anemometer_height'], |
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}, |
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'cdir' : {'short_name': 'cdir', |
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'long_name': 'Buoy Orientation', |
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'standard_name': 'compass_direction', |
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'reference': 'clockwise from Magnetic North', |
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'valid_range': (0., 360), |
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'units': 'degrees', |
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}, |
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'u' : {'short_name': 'u', |
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'long_name': 'East/West Component of Wind', |
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'standard_name': 'eastward_wind', |
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'reference': 'relative to True East (?)', |
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'units': 'm s-1', |
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'can_be_normalized': 'no', |
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'z' : sensor_info['anemometer_height'], |
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}, |
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'v' : {'short_name': 'v', |
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'long_name': 'North/South Component of Wind', |
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'standard_name': 'northward_wind', |
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'reference': 'relative to True North (?)', |
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'units': 'm s-1', |
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'can_be_normalized': 'no', |
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'z' : sensor_info['anemometer_height'], |
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}, |
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'nwnd' : {'short_name': 'nwnd', |
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'long_name': 'Number of wind samples in sample period', |
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'standard_name': 'number_of_samples', |
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'units': 'm s-1', |
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}, |
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|
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} |
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|
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# dimension names use tuple so order of initialization is maintained |
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dim_inits = ( |
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('ntime', NC.UNLIMITED), |
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('nlat', 1), |
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('nlon', 1), |
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('nz', 1) |
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) |
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|
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# using tuple of tuples so order of initialization is maintained |
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# using dict for attributes order of init not important |
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# use dimension names not values |
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# (varName, varType, (dimName1, [dimName2], ...)) |
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var_inits = ( |
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# coordinate variables |
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('time', NC.INT, ('ntime',)), |
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('lat', NC.FLOAT, ('nlat',)), |
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('lon', NC.FLOAT, ('nlon',)), |
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('z', NC.FLOAT, ('nz',)), |
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# data variables |
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('wspd', NC.FLOAT, ('ntime',)), |
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('wdir', NC.FLOAT, ('ntime',)), |
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('cdir', NC.FLOAT, ('ntime',)), |
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('u', NC.FLOAT, ('ntime',)), |
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('v', NC.FLOAT, ('ntime',)), |
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('nwnd', NC.FLOAT, ('ntime',)), |
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) |
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|
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# subset data only to month being processed (see raw2proc.process()) |
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i = data['in'] |
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|
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# var data |
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var_data = ( |
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('lat', platform_info['lat']), |
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('lon', platform_info['lon']), |
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('z', 1), |
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# |
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('time', data['time'][i]), |
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('wspd', data['wspd'][i]), |
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('wdir', data['wdir'][i]), |
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('cdir', data['cdir'][i]), |
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('u', data['u'][i]), |
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('v', data['v'][i]), |
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('nwnd', data['nwnd'][i]), |
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) |
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|
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return (global_atts, var_atts, dim_inits, var_inits, var_data) |
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|
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def updater(platform_info, sensor_info, data): |
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# |
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global_atts = { |
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# update times of data contained in file (yyyy-mm-dd HH:MM:SS) |
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# last date in monthly file |
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'end_date' : data['dt'][-1].strftime("%Y-%m-%d %H:%M:%S"), |
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'release_date' : now_dt.strftime("%Y-%m-%d %H:%M:%S"), |
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# |
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'modification_date' : now_dt.strftime("%Y-%m-%d %H:%M:%S"), |
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} |
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|
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# data variables |
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# update any variable attributes like range, min, max |
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var_atts = {} |
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# var_atts = { |
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# 'u': {'max': max(data.u), |
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# 'min': min(data.v), |
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# }, |
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# 'v': {'max': max(data.u), |
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# 'min': min(data.v), |
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# }, |
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# } |
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|
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# subset data only to month being processed (see raw2proc.process()) |
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i = data['in'] |
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|
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# data |
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var_data = ( |
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('time', data['time'][i]), |
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('wspd', data['wspd'][i]), |
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('wdir', data['wdir'][i]), |
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('cdir', data['cdir'][i]), |
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('u', data['u'][i]), |
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('v', data['v'][i]), |
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('nwnd', data['nwnd'][i]), |
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) |
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|
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return (global_atts, var_atts, var_data) |
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|
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# |
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