PseudoNetCDF.textfiles package

Submodules

PseudoNetCDF.textfiles.esrl_sonde module

NOAA/GMD sounding data file produced on 2015/02/02 22:04:08 GMT …

Header lines = 45 Data columns = 21

Flight number = BL049

Date [GMT] = 03-01-1992 Time [GMT] = 18:35:21

Location = Boulder, CO

Longitude = -105.25000

Latitude = 40.00000

Launch altitude (km) = 1.743

Surface pressure (mb) = 826.790

Surface temperature (deg) = 6.870

Surface humidity (%) = 18.900

Turn altitude (km) = 30.699 Turn pressure (mb) = 10.20

Radiosonde number = 8815949

Vaisala humicap sensor = A

Radiation correction = Yes

Pressure sensor offset = 0.000

A/D System = 12 bit Tmax

Radiosonde Total Col. Water = 2.322

Instrument Type = Ozone Sonde

Original File Source = unknown

Ozone sonde number = 5A8087

Solution = 1%

Oltmans solution correction = Yes

Oltmans term A = 1.0000 Oltmans term B = 0.4000

Total ozone column (CMR) = 283 (41)

Total ozone column (SBUV) = 289 (47) Total ozone stop pressure = 10.28 Time (sec) to pump 100 ml = 28.230

Dry flowrate correction = 2.60 Background current (uA) = 0.071

Coefficients =

Pump coefficient pc0 = 0.5955

pc1 = 0.5125 pc2 = -0.2353 pc3 = 0.0824

Pressure data source = Radiosonde Pressure Altitude data source = Radiosonde Geopot Altitude

Geo alt anchoring method = First/Launch Row Set to Launch Altitude

Time, Press, Praw, Alt, Tcorr, Temp,…

PseudoNetCDF.textfiles.esrl_sonde.skysonde1sec(inpath)

PseudoNetCDF.textfiles.shadoz_sonde module

Written to read files from http://croc.gsfc.nasa.gov/shadoz/

PseudoNetCDF.textfiles.shadoz_sonde.shadoz(inpath)

Module contents

class PseudoNetCDF.textfiles.csv(*args, **kwds)

Bases: PseudoNetCDFFile

pathstr

place to find csv file

coordkeysiterable of strings

use these keys as dimensions and coordinate variables

delimiterstr

use this as delimiter (default = ‘,’) renamed as sep for pandas

namesiterable of strings or True

with pandas backend and names==True: header=’infer’ otherwise, passed directly as keyword

backendstr or None

‘numpy’ numpy.genfromtxt or ‘pandas’ pandas.read_csv; defaults to pandas if available

defaultcoordstr

if no coordkeys are found, use this str to create a arbitrary coordinate based on each record

kwdsmappable

corresponds to numpy.genfromtxt or pandas.read_csv keywords

• Note: currently only works when all coordinate variables are 1-d

PseudoNetCDF.textfiles.ncf2csv(ifile, outpath, delimiter=',', coordkeys=['Time', 'time', 'time_bounds', 'TFLAG', 'ETFLAG', 'etam_pressure', 'etai_pressure', 'layer_bounds', 'layer47', 'layer', 'latitude', 'latitude_bounds', 'lat', 'lat_bnds', 'longitude', 'longitude_bounds', 'lon', 'lon_bnds'])