diff --git a/aosstower/l00/__init__.py b/aosstower/level_00/__init__.py
similarity index 100%
rename from aosstower/l00/__init__.py
rename to aosstower/level_00/__init__.py
diff --git a/aosstower/l00/influxdb.py b/aosstower/level_00/influxdb.py
similarity index 98%
rename from aosstower/l00/influxdb.py
rename to aosstower/level_00/influxdb.py
index 0452744fc7dbe62905f0009ff05630db6b1d2c4c..dbd9f762c9d68a696fe628b640d4aa04f7cf40dd 100644
--- a/aosstower/l00/influxdb.py
+++ b/aosstower/level_00/influxdb.py
@@ -9,7 +9,7 @@ import time
import sys
import requests
from metobscommon import influxdb
-from aosstower.l00.parser import read_frames
+from aosstower.level_00.parser import read_frames
LOG = logging.getLogger(__name__)
# map station name to InfluxDB tags
diff --git a/aosstower/l00/parser.py b/aosstower/level_00/parser.py
similarity index 100%
rename from aosstower/l00/parser.py
rename to aosstower/level_00/parser.py
diff --git a/aosstower/l00/rrd.py b/aosstower/level_00/rrd.py
similarity index 100%
rename from aosstower/l00/rrd.py
rename to aosstower/level_00/rrd.py
diff --git a/aosstower/tests/l00/__init__.py b/aosstower/level_b1/__init__.py
similarity index 100%
rename from aosstower/tests/l00/__init__.py
rename to aosstower/level_b1/__init__.py
diff --git a/aosstower/level_b1/nc.py b/aosstower/level_b1/nc.py
index 7115e8cf0ce624f229fe7c31dd7dce76eaf37694..410c42206c4fc719804f04db42518d1f1d1e5501 100644
--- a/aosstower/level_b1/nc.py
+++ b/aosstower/level_b1/nc.py
@@ -3,30 +3,31 @@ import sys
import logging
import pandas as pd
from datetime import datetime as dt
-from aosstower.l00 import parser
+from aosstower.level_00 import parser
from netCDF4 import Dataset
-import numpy as np
+import numpy as np
import platform
from aosstower import station
from datetime import timedelta as delta
-import calc
+from aosstower.level_b1 import calc
LOG = logging.getLogger(__name__)
-#create the '_mean','_low','_high' file structure
def make_mean_dict(source_dict):
+ """Create the '_mean','_low','_high' file structure."""
dest_dict = {}
for key in source_dict:
- dest_dict[key+'_high'] = source_dict[key]
- dest_dict[key+'_mean'] = source_dict[key]
- dest_dict[key+'_low'] = source_dict[key]
+ dest_dict[key + '_high'] = source_dict[key]
+ dest_dict[key + '_mean'] = source_dict[key]
+ dest_dict[key + '_low'] = source_dict[key]
return dest_dict
+
mean_database = make_mean_dict(parser.database)
-def filterArray(array, valid_min, valid_max):
+def filter_array(array, valid_min, valid_max):
qcControl = []
for value in array:
@@ -35,184 +36,173 @@ def filterArray(array, valid_min, valid_max):
elif valid_min != '' and value < float(valid_min):
qcControl.append(np.byte(0b10))
-
+
elif valid_max != '' and value > float(valid_max):
qcControl.append(np.byte(0b100))
-
+
else:
qcControl.append(np.byte(0b0))
return np.array(qcControl)
-# The purpose of this function is to write the dimensions
-# for the nc file
-# no parameters
-# no returns
-def writeDimensions(ncFile):
+def write_dimensions(ncFile):
ncFile.createDimension('time', None)
ncFile.createDimension('max_len_station_name', 32)
return ncFile
-def createVariables(ncFile, firstStamp, chunksizes, zlib, database=parser.database):
- #base_time long name
+
+def create_variables(ncFile, firstStamp, chunksizes, zlib, database=parser.database):
+ # base_time long name
btln = 'base time as unix timestamp'
- #base time units
+ # base time units
btu = 'seconds since 1970-01-01 00:00:00'
- #base time string
+ # base time string
bts = firstStamp.strftime('%Y-%m-%d 00:00:00Z')
- #time long name
+ # time long name
tln = 'time offset from base_time'
- #time units
+ # time units
tu = 'seconds since ' + firstStamp.strftime('%Y-%m-%d 00:00:00Z')
-
-
coordinates = {
- #fields: type, dimension, fill, valid_min, std_name, longname, units, valid_max, cf_role, axis
- 'lon': [np.float32, None, float(-999), '-180L', 'longitude', None, 'degrees_east', '180L', None],
- 'lat': [np.float32, None, float(-999), '-90L', 'latitude', None, 'degrees_north', '90L', None],
- 'alt': [np.float32, None, float(-999), None, 'height', 'vertical distance', 'm', None, None],
- 'base_time': [np.int32, None, float(-999), None, 'time', btln, btu, None, None],
- 'time_offset': [np.float64, 'time', float(-999), None, 'time', tln, tu, None, None],
- 'station_name': ['c', 'max_len_station_name', '-', None, None, 'station name', None, None, 'timeseries_id'],
- 'time': [np.float32, 'time', float(-999), None, None, "Time offset from epoch", "seconds since 1970-01-01 00:00:00Z", None, None, None]
- }
-
- for key in coordinates:
- attr = coordinates[key]
-
- if(attr[1]):
+ # fields: type, dimension, fill, valid_min, std_name, longname, units, valid_max, cf_role, axis
+ 'lon': [np.float32, None, float(-999), '-180L', 'longitude', None, 'degrees_east', '180L', None],
+ 'lat': [np.float32, None, float(-999), '-90L', 'latitude', None, 'degrees_north', '90L', None],
+ 'alt': [np.float32, None, float(-999), None, 'height', 'vertical distance', 'm', None, None],
+ 'base_time': [np.int32, None, float(-999), None, 'time', btln, btu, None, None],
+ 'time_offset': [np.float64, 'time', float(-999), None, 'time', tln, tu, None, None],
+ 'station_name': ['c', 'max_len_station_name', '-', None, None, 'station name', None, None, 'timeseries_id'],
+ 'time': [np.float32, 'time', float(-999), None, None, "Time offset from epoch",
+ "seconds since 1970-01-01 00:00:00Z", None, None, None]
+ }
+
+ for key, attr in coordinates.items():
+ if attr[1]:
if attr[1] == 'max_len_station_name':
- if (chunksizes) and chunksizes[0] > 32:
- variable = ncFile.createVariable(key, attr[0], dimensions=(attr[1]), fill_value=attr[2], zlib=zlib, chunksizes=[32])
-
+ if chunksizes and chunksizes[0] > 32:
+ variable = ncFile.createVariable(key, attr[0], dimensions=(attr[1]), fill_value=attr[2], zlib=zlib,
+ chunksizes=[32])
else:
- variable = ncFile.createVariable(key, attr[0], dimensions=(attr[1]), fill_value=attr[2], zlib=zlib, chunksizes=chunksizes)
-
+ variable = ncFile.createVariable(key, attr[0], dimensions=(attr[1]), fill_value=attr[2], zlib=zlib,
+ chunksizes=chunksizes)
else:
- variable = ncFile.createVariable(key, attr[0], dimensions=(attr[1]), fill_value=attr[2], zlib=zlib, chunksizes=chunksizes)
+ variable = ncFile.createVariable(key, attr[0], dimensions=(attr[1]), fill_value=attr[2], zlib=zlib,
+ chunksizes=chunksizes)
else:
variable = ncFile.createVariable(key, attr[0], fill_value=attr[1], zlib=zlib, chunksizes=chunksizes)
- #create var attributes
+ # create var attributes
if key == 'alt':
variable.positive = 'up'
variable.axis = 'Z'
- if(attr[3]):
+ if attr[3]:
variable.valid_min = attr[3]
variable.valid_max = attr[7]
- if(attr[4]):
+ if attr[4]:
variable.standard_name = attr[4]
- if(attr[5]):
+ if attr[5]:
variable.long_name = attr[5]
- if(attr[6]):
+ if attr[6]:
variable.units = attr[6]
- if(attr[8]):
- variable.cf_role = attr[8]
+ if attr[8]:
+ variable.cf_role = attr[8]
if key == 'base_time':
variable.string = bts
if 'time' in key:
- variable.calendar = 'gregorian'
+ variable.calendar = 'gregorian'
for entry in database:
- if(entry == 'stamp'):
+ if entry == 'stamp':
continue
varTup = database[entry]
-
variable = ncFile.createVariable(entry, np.float32,
- dimensions=('time'), fill_value=float(-99999), zlib=zlib, chunksizes=chunksizes)
+ dimensions=('time'), fill_value=float(-99999), zlib=zlib,
+ chunksizes=chunksizes)
variable.standard_name = varTup[1]
variable.description = varTup[3]
variable.units = varTup[4]
- if(varTup[5] != ''):
+ if varTup[5] != '':
variable.valid_min = float(varTup[5])
variable.valid_max = float(varTup[6])
qcVariable = ncFile.createVariable('qc_' + entry, 'b',
- dimensions=('time'), fill_value=0b0, zlib=zlib, chunksizes=chunksizes)
+ dimensions=('time'), fill_value=0b0, zlib=zlib, chunksizes=chunksizes)
qcVariable.long_name = 'data quality'
qcVariable.valid_range = np.byte(0b1), np.byte(0b1111)
qcVariable.flag_masks = np.byte(0b1), np.byte(0b10), np.byte(0b100), np.byte(0b1000)
- flagMeaning = ['value is equal to missing_value',
- 'value is less than the valid min',
+ flagMeaning = ['value is equal to missing_value',
+ 'value is less than the valid min',
'value is greater than the valid max',
'difference between current and previous values exceeds valid_delta.']
qcVariable.flag_meaning = ', '.join(flagMeaning)
- #create global attributes
+ # create global attributes
ncFile.source = 'surface observation'
ncFile.conventions = 'ARM-1.2 CF-1.6'
ncFile.institution = 'UW SSEC'
ncFile.featureType = 'timeSeries'
ncFile.data_level = 'b1'
- #monthly files end with .month.nc
- #these end with .day.nc
+ # monthly files end with .month.nc
+ # these end with .day.nc
ncFile.datastream = 'aoss.tower.nc-1d-1m.b1.v00'
ncFile.software_version = '00'
- #generate history
+ # generate history
ncFile.history = ' '.join(platform.uname()) + " " + os.path.basename(__file__)
-
+
return ncFile
-def getGust(rollingAvg, speeds):
+
+def get_gust(rollingAvg, speeds):
averages = rollingAvg.tolist()
maxSpeed = speeds['wind_speed'].tolist()
gust = []
-
for idx, average in enumerate(averages):
if not average:
- gust.append(np.nan)
- continue
-
+ gust.append(np.nan)
+ continue
elif average >= 4.63 and maxSpeed[idx] > average + 2.573:
- gust.append(maxSpeed[idx])
-
+ gust.append(maxSpeed[idx])
else:
gust.append(np.nan)
continue
return gust
-#gets the rolling mean closest to the nearest minute
-def getRolling(series, minutes):
- returnSeries = series.rolling(25, win_type='boxcar').mean()
+def get_rolling(series, minutes):
+ """Get the rolling mean closest to the nearest minute"""
+ returnSeries = series.rolling(25, win_type='boxcar').mean()
data = {}
-
for minute in minutes:
-
- #doesn't go past the minute
- closestStamp = returnSeries.index.asof(minute)
+ # doesn't go past the minute
data[minute] = returnSeries[returnSeries.index.asof(minute)]
- returnSeries = pd.Series(data)
-
- return returnSeries
+ return pd.Series(data)
+
-def getNewWindDirection(wind_dir, wind_speed, stamps):
+def get_new_wind_direction(wind_dir, wind_speed, stamps):
newWindDir = {}
for stamp in stamps:
@@ -220,18 +210,18 @@ def getNewWindDirection(wind_dir, wind_speed, stamps):
if before not in wind_speed.index:
newWindDir[stamp] = None
-
else:
speed = wind_speed[before: stamp].tolist()
dire = wind_dir[before: stamp].tolist()
wind_dire = calc.mean_wind_vector(speed, dire)[0]
-
+
newWindDir[stamp] = wind_dire
-
+
return pd.Series(newWindDir)
-def minuteAverages(frame):
+
+def minute_averages(frame):
frame['minute'] = [(ts + delta(minutes=1)).replace(second=0) for ts in frame.index]
newFrame = frame.groupby('minute').mean()
newFrame.index.names = ['']
@@ -241,63 +231,52 @@ def minuteAverages(frame):
del newFrame['wind_speed']
windSeries = frame['wind_speed']
-
- windSeries = getRolling(windSeries, list(newFrame.index))
-
+ windSeries = get_rolling(windSeries, list(newFrame.index))
newFrame['wind_speed'] = windSeries
-
rollingAvg = newFrame['wind_speed']
-
maxSpeed = pd.DataFrame()
maxSpeed['minute'] = frame['minute']
maxSpeed['speed'] = frame['wind_speed']
-
maxSpeed = frame.groupby('minute').max()
-
- gust = getGust(rollingAvg, maxSpeed)
-
+ gust = get_gust(rollingAvg, maxSpeed)
newFrame['gust'] = gust
-
+
if 'wind_dir' in columns:
del newFrame['wind_dir']
dupFrame = frame.set_index('minute')
-
stamps = newFrame.index
-
windDirSeries = dupFrame['wind_dir']
-
windSeries = dupFrame['wind_speed']
-
- windDirSeries = getNewWindDirection(windDirSeries, windSeries, stamps)
-
+ windDirSeries = get_new_wind_direction(windDirSeries, windSeries, stamps)
newFrame['wind_dir'] = windDirSeries
del frame['minute']
-
return newFrame.fillna(-99999)
-def averageOverInterval(frame,interval_width):
+
+def average_over_interval(frame, interval_width):
"""takes a frame and an interval to average it over, and returns a minimum,
maximum, and average dataframe for that interval"""
ts = frame.index
- #round each timestamp to the nearest n minutes
- frame['interval'] = (ts.astype(int)-ts.astype(int)%(interval_width*60e9)).astype('datetime64[ns]')
- outFrames = {}
- outFrames['low'] = frame.groupby('interval').min()
- outFrames['high'] = frame.groupby('interval').max()
- outFrames['mean'] = frame.groupby('interval').mean()
+ # round each timestamp to the nearest n minutes
+ frame['interval'] = (ts.astype(int) - ts.astype(int) % (interval_width * 60e9)).astype('datetime64[ns]')
+ out_frames = {
+ 'low': frame.groupby('interval').min(),
+ 'high': frame.groupby('interval').max(),
+ 'mean': frame.groupby('interval').mean(),
+ }
del frame['interval']
- for key in outFrames:
- #append the appropriate suffix to each column
- columns = outFrames[key].columns
- outFrames[key].columns = ['_'.join([col,key]) for col in columns]
- outFrames = pd.concat(outFrames.values(),axis=1)
- return outFrames
-
-def getData(inputFiles):
- dictData = {}
+ for key in out_frames:
+ # append the appropriate suffix to each column
+ columns = out_frames[key].columns
+ out_frames[key].columns = ['_'.join([col, key]) for col in columns]
+ out_frames = pd.concat(out_frames.values(), axis=1)
+ return out_frames
+
+def get_data(inputFiles):
+ dictData = {}
for filename in inputFiles:
getFrames = list(parser.read_frames(filename))
@@ -312,22 +291,23 @@ def getData(inputFiles):
return pd.DataFrame(dictData).transpose().replace(-99999, np.nan)
-def writeVars(ncFile, frame, database=parser.database):
+
+def write_vars(ncFile, frame, database=parser.database):
stamps = list(frame.index)
baseDTObj = dt.strptime(str(stamps[0]).split(' ')[0], '%Y-%m-%d')
- #find out how much time elapsed
- #since the origin to the start of the day
- #in seconds
- baseTimeValue = baseDTObj - dt(1970,1,1)
+ # find out how much time elapsed
+ # since the origin to the start of the day
+ # in seconds
+ baseTimeValue = baseDTObj - dt(1970, 1, 1)
baseTimeValue = baseTimeValue.total_seconds()
- #create time numpy
+ # create time numpy
timeNumpy = np.empty(len(stamps), dtype='float64')
counter = 0
- #write stamps in, yo
+ # write stamps in, yo
for stamp in stamps:
stampObj = dt.strptime(str(stamp), '%Y-%m-%d %H:%M:%S')
@@ -339,28 +319,28 @@ def writeVars(ncFile, frame, database=parser.database):
fileVar = ncFile.variables
fileVar['base_time'].assignValue(baseTimeValue)
fileVar['time_offset'][:] = timeNumpy
- fileVar['time'][:] = timeNumpy
+ fileVar['time'][:] = timeNumpy
- #write coordinate var values to file
- #alt might not be right, need to verify
+ # write coordinate var values to file
+ # alt might not be right, need to verify
fileVar['lon'].assignValue(station.LONGITUDE)
fileVar['lat'].assignValue(station.LATITUDE)
fileVar['alt'].assignValue(328)
- #might change
+ # might change
stationName = ("AOSS Tower")
-
- #transfer station name into array of chars
+
+ # transfer station name into array of chars
statChars = list(stationName)
statNumpy = np.asarray(statChars)
- #write station name to file
+ # write station name to file
fileVar['station_name'][0:len(statNumpy)] = statNumpy
- #writes data into file
+ # writes data into file
for varName in frame:
if varName not in fileVar:
- logging.warn('Extraneous key: %s in frame'%varName)
+ logging.warn('Extraneous key: %s in frame' % varName)
continue
dataList = frame[varName].tolist()
@@ -370,7 +350,7 @@ def writeVars(ncFile, frame, database=parser.database):
valid_min = database[varName][5]
valid_max = database[varName][6]
- fileVar['qc_' + varName][:] = filterArray(dataArray, valid_min, valid_max)
+ fileVar['qc_' + varName][:] = filter_array(dataArray, valid_min, valid_max)
coordinates = ['lon', 'lat', 'alt', 'base_time', 'time_offset', 'station_name', 'time']
@@ -386,10 +366,11 @@ def writeVars(ncFile, frame, database=parser.database):
else:
fileVar['qc_' + varName][:] = np.full(len(list(frame.index)), np.byte(0b1), dtype='b')
-
+
return ncFile
-#The purpose of this method is to take a begin date, and end date
+
+# The purpose of this method is to take a begin date, and end date
# input filenames and output filename and create a netCDF file
# based upon that
# @param start time - a start datetime object
@@ -397,136 +378,128 @@ def writeVars(ncFile, frame, database=parser.database):
# @param input filenames - list of filenames
# @param output filename - filename of the netcdf file
-def createGiantNetCDF(start, end, inputFiles, outputName, zlib, chunkSize,
- interval_width = None, database=parser.database):
+def create_giant_netCDF(start, end, inputFiles, outputName, zlib, chunkSize,
+ interval_width=None, database=parser.database):
default = False
- if(chunkSize):
+ if (chunkSize):
chunksizes = [chunkSize]
else:
default = True
- frame = getData(inputFiles)
+ frame = get_data(inputFiles)
- if(frame.empty):
+ if (frame.empty):
return False
else:
- frame = minuteAverages(frame)
+ frame = minute_averages(frame)
if interval_width:
- frame = averageOverInterval(frame,interval_width)
+ frame = average_over_interval(frame, interval_width)
- if(start and end):
+ if (start and end):
frame = frame[start.strftime('%Y-%m-%d %H:%M:%S'): end.strftime('%Y-%m-%d %H:%M:%S')]
- if(default):
+ if (default):
chunksizes = [len(list(frame.index))]
firstStamp = dt.strptime(str(list(frame.index)[0]), '%Y-%m-%d %H:%M:%S')
ncFile = Dataset(outputName, 'w', format='NETCDF4_CLASSIC')
- ncFile = writeDimensions(ncFile)
+ ncFile = write_dimensions(ncFile)
+
+ ncFile = create_variables(ncFile, firstStamp, chunksizes, zlib, database)
- ncFile = createVariables(ncFile, firstStamp, chunksizes, zlib,database)
-
ncFile.inputFiles = ', '.join(inputFiles)
- ncFile = writeVars(ncFile, frame,database)
+ ncFile = write_vars(ncFile, frame, database)
ncFile.close()
-
- return True
-def createMultiple(filenames, outputFilenames, zlib, chunkSize):
- if(outputFilenames and len(filenames) != len(outputFilenames)):
- print('USAGE: number of output filenames must equal number of input filenames when start and end times are not specified')
- exit(0)
-
- results = []
+ return True
- for idx, filename in enumerate(filenames):
- results.append(createGiantNetCDF(None, None, [filename], outputFilenames[idx], zlib, chunkSize))
- allFalse = True
+def create_multiple(filenames, outputFilenames, zlib, chunkSize):
+ if outputFilenames and len(filenames) != len(outputFilenames):
+ raise ValueError(
+ 'Number of output filenames must equal number of input filenames when start and end times are not specified')
- for result in results:
- if result == True:
- allFalse = False
+ results = []
+ for idx, filename in enumerate(filenames):
+ results.append(create_giant_netCDF(None, None, [filename], outputFilenames[idx], zlib, chunkSize))
- if allFalse == True:
+ if not any(results):
raise IOError('All ASCII files were empty')
-#The purpose of this method is to take a string in the format
+
+# The purpose of this method is to take a string in the format
# YYYY-mm-ddTHH:MM:SS and convert that to a datetime object
# used in coordination with argparse -s and -e params
# @param datetime string
# @return datetime object
def _dt_convert(datetime_str):
- #parse datetime string, return datetime object
- try:
+ # parse datetime string, return datetime object
+ try:
return dt.strptime(datetime_str, '%Y-%m-%dT%H:%M:%S')
except:
return dt.strptime(datetime_str, '%Y-%m-%d')
+
def main():
import argparse
-
- #argparse description
argparser = argparse.ArgumentParser(description="Convert level_00 aoss tower data to level_a0",
fromfile_prefix_chars='@')
- #argparse verbosity info
argparser.add_argument('-v', '--verbose', action="count", default=int(os.environ.get("VERBOSITY", 2)),
- dest='verbosity',
- help='each occurrence increases verbosity 1 level through ERROR-WARNING-INFO-DEBUG (default INFO)')
-
- #argparse start and end times
- argparser.add_argument('-s', '--start-time', type=_dt_convert,
- help="Start time of massive netcdf file, if only -s is given, a netcdf file for only that day is given" +
- ". Formats allowed: \'YYYY-MM-DDTHH:MM:SS\', \'YYYY-MM-DD\'")
- argparser.add_argument('-e', '--end-time', type=_dt_convert, help='End time of massive netcdf file. Formats allowed:' +
- "\'YYYY-MM-DDTHH:MM:SS\', \'YYYY-MM-DD\'")
- argparser.add_argument('-i', '--interval', type=float,
- help='Width of the interval to average input data over in minutes.'+
- " If not specified, 1 is assumed. (Use 60 for one hour and 1440 for 1 day)")
+ dest='verbosity',
+ help='each occurrence increases verbosity 1 level through ERROR-WARNING-INFO-DEBUG (default INFO)')
+
+ argparser.add_argument('-s', '--start-time', type=_dt_convert,
+ help="Start time of massive netcdf file, if only -s is given, a netcdf file for only that day is given" +
+ ". Formats allowed: \'YYYY-MM-DDTHH:MM:SS\', \'YYYY-MM-DD\'")
+ argparser.add_argument('-e', '--end-time', type=_dt_convert,
+ help='End time of massive netcdf file. Formats allowed:' +
+ "\'YYYY-MM-DDTHH:MM:SS\', \'YYYY-MM-DD\'")
+ argparser.add_argument('-i', '--interval', type=float,
+ help='Width of the interval to average input data over in minutes.' +
+ " If not specified, 1 is assumed. (Use 60 for one hour and 1440 for 1 day)")
argparser.add_argument('-cs', '--chunk-size', type=int, help='chunk Size for the netCDF file')
argparser.add_argument('-z', '--zlib', action='store_true', help='compress netCDF file with zlib')
argparser.add_argument("input_files", nargs="+",
- help="aoss_tower level_00 paths. Use @filename to red a list of paths from that file.")
+ help="aoss_tower level_00 paths. Use @filename to red a list of paths from that file.")
argparser.add_argument('-o', '--output', required=True, nargs="+", help="filename pattern or filename. " +
- "Should be along the lines of <filepath>/aoss_tower.YYYY-MM-DD.nc")
+ "Should be along the lines of <filepath>/aoss_tower.YYYY-MM-DD.nc")
args = argparser.parse_args()
levels = [logging.ERROR, logging.WARN, logging.INFO, logging.DEBUG]
- level=levels[min(3, args.verbosity)]
+ level = levels[min(3, args.verbosity)]
logging.basicConfig(level=level)
-
database = mean_database if args.interval else parser.database
- if(args.start_time and args.end_time):
- result = createGiantNetCDF(args.start_time, args.end_time, args.input_files, args.output[0], args.zlib, args.chunk_size,
- args.interval, database)
- if(result == False):
+ if args.start_time and args.end_time:
+ result = create_giant_netCDF(args.start_time, args.end_time, args.input_files, args.output[0], args.zlib,
+ args.chunk_size,
+ args.interval, database)
+ if not result:
raise IOError('An empty ASCII file was found')
-
- elif(args.start_time):
+ elif args.start_time:
end_time = args.start_time.replace(hour=23, minute=59, second=59)
- result = createGiantNetCDF(args.start_time, end_time, args.input_files, args.output[0], args.zlib, args.chunk_size,
- args.interval, database)
- if(result == False):
+ result = create_giant_netCDF(args.start_time, end_time, args.input_files, args.output[0], args.zlib,
+ args.chunk_size,
+ args.interval, database)
+ if not result:
raise IOError('An empty ASCII file was found')
-
- elif(args.end_time):
- print('USAGE: start time must be specified when end time is specified')
-
+ elif args.end_time:
+ raise ValueError('start time must be specified when end time is specified')
else:
- createMultiple(args.input_files, args.output, args.zlib, args.chunk_size)
+ create_multiple(args.input_files, args.output, args.zlib, args.chunk_size)
+
if __name__ == "__main__":
- main()
+ sys.exit(main())
diff --git a/aosstower/tests/level_00/__init__.py b/aosstower/tests/level_00/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/aosstower/tests/l00/test_parser.py b/aosstower/tests/level_00/test_parser.py
similarity index 94%
rename from aosstower/tests/l00/test_parser.py
rename to aosstower/tests/level_00/test_parser.py
index 6e3dfa5b999e851ca35c24bc1cae0e0089a0d772..90d4b086a7557732b088b5172c0d123392283d15 100644
--- a/aosstower/tests/l00/test_parser.py
+++ b/aosstower/tests/level_00/test_parser.py
@@ -12,7 +12,7 @@ class ParserV0Tests(unittest.TestCase):
"WDIR05305 143.380000\n")
def _cut(self):
- from aosstower.l00.parser import ParserV0
+ from aosstower.level_00.parser import ParserV0
return ParserV0()
def test_maybe_mine(self):
@@ -38,7 +38,7 @@ class ParserV1V2Tests(unittest.TestCase):
"22.669,10.417,145.2,22.665,163.94,0,0,30.015\n")
def _cut(self):
- from aosstower.l00.parser import ParserV1V2
+ from aosstower.level_00.parser import ParserV1V2
return ParserV1V2()
def test_maybe_mine(self):
diff --git a/scripts/insert_influx.py b/scripts/insert_influx.py
index d36e1461a83322efd841a6c669d06ac9153bc9ea..03bfa9e4695d0fd2d14b869dab9004d138011830 100644
--- a/scripts/insert_influx.py
+++ b/scripts/insert_influx.py
@@ -4,7 +4,7 @@ from datetime import datetime
import requests
from metobs.data import wind_vector_components
-from aosstower.l00.parser import read_frames
+from aosstower.level_00.parser import read_frames
LOG = logging.getLogger(__name__)
diff --git a/scripts/make_database.py b/scripts/make_database.py
index 4b34d09a31a6ac2eef4553bf1c2d1fb3d8eba360..eed9d02baf953355b97bf9371ca743c93bb32275 100755
--- a/scripts/make_database.py
+++ b/scripts/make_database.py
@@ -5,8 +5,8 @@ import logging
from datetime import datetime
from metobscommon.model import RrdModel, ModelError
-from aosstower.l00.parser import read_records
-from aosstower.l00.rrd import initialize_rrd
+from aosstower.level_00.parser import read_records
+from aosstower.level_00.rrd import initialize_rrd
LOG = logging