def read_igra_metadata(filename=None):
# TODO: read routine for IGRA metadata
# use default filename
from raso.config import get_data
file = get_data('igra-metadata.txt')
contents = pd.read_csv(file)
return
def radiosondelist(minimal=True):
""" Read Radiosonde List Predefined
Returns
-------
DataFrame
"""
table = pd.read_csv(get_data("radiosondeslist.csv"), sep=";", index_col=0)
if minimal:
return table[["lon", "lat", "alt", "name", "source", "total"]]
return table
def notebook(ident, directory=None):
"""Make a default Notebook for that radiosonde"""
from raso.config import wkdir, get_data
import nbformat
import json
with open(get_data('notebook_template.ipynb'), 'r') as f:
template = json.load(f)
for icell in template[u'cells']:
if isinstance(icell[u'source'], list):
tmp=[]
for isource in icell[u'source']:
if 'RASOID' in isource:
isource = isource.replace('RASOID', ident)
tmp.append(isource)
icell[u'source'] = tmp
else:
if 'RASOID' in icell[u'source']:
icell[u'source'] = icell[u'source'].replace('RASOID', ident)
if directory is None:
filename = wkdir + '/notebooks/stations/%s.ipynb' % ident
else:
filename = directory + '/%s.ipynb' % ident
if not os.path.isdir(os.path.dirname(filename)):
os.makedirs(os.path.dirname(filename))
if not os.path.isdir(os.path.dirname(filename)+'/figures/'):
os.makedirs(os.path.dirname(filename)+'/figures/')
template = nbformat.notebooknode.from_dict(template) # Make a Class Object
with open(filename, 'wt') as f:
nbformat.write(template, f)
print "Notebook: ", filename
def us_standard(filename=None, profile=None, levels=None, interpolate=False):
"""Standard Atmospheres
Profile Types:
TROPICAL 0
MIDLATITUDE SUMMER 1
MIDLATITUDE WINTER 2
SUBARCTIC SUMMER 3
SUBARCTIC WINTER 4
U. S. STANDARD, 1976 5
from RTTOV v11
Options: filename
profile Profile Number
interpolation Interpolated to ERA-Interim Levels?
Output: profile , info
as Pandas DataFrames
"""
from raso.config import era_plevels, get_data
if filename is None:
filename = get_data('us_standard_76.H5')
f = h5py.File(filename, 'r')
info = pd.DataFrame()
if profile is not None and isinstance(profile,str):
profile = profile.upper()
profs_infile = [ f['PROFILES'][i]['ID'].value for i in f['PROFILES'].keys()]
if profile in profs_infile:
profile = profs_infile.index(profile)+1
else:
raise ValueError("Could not find Profile: %s"%profile)
if levels is None:
levels = era_plevels
if profile is not None:
out = pd.DataFrame()
if 0 < profile and profile < 7:
iobj = f['PROFILES']['%04d' % profile]
info = pd.concat([info, pd.DataFrame({'lon': iobj['LONGITUDE'][0], 'lat': iobj['LATITUDE'][0],
'time': datetime.datetime(
*np.concatenate([iobj['DATE'][:], iobj['TIME'][:]])),
'id': iobj['ID'].value}, index=[int(profile)])])
if interpolate:
tnew = interp_mod(iobj['T'][:], np.log(levels), np.log(iobj['P'][:] * 100.), False)
qnew = interp_mod(iobj['Q'][:], np.log(levels), np.log(iobj['P'][:] * 100.), False)
out = pd.DataFrame({'p': levels, 't': tnew, 'q': qnew})
else:
out = pd.DataFrame({'p': iobj['P'][:] * 100., 't': iobj['T'][:], 'q': iobj['Q'][:]})
else:
out = {}
for ikey, iobj in f['PROFILES'].iteritems():
info = pd.concat([info, pd.DataFrame({'lon': iobj['LONGITUDE'][0], 'lat': iobj['LATITUDE'][0],
'time': datetime.datetime(
*np.concatenate([iobj['DATE'][:], iobj['TIME'][:]])),
'id': iobj['ID'].value}, index=[int(ikey)])])
if interpolate:
tnew = interp_mod(iobj['T'][:], np.log(levels), np.log(iobj['P'][:] * 100.), False)
qnew = interp_mod(iobj['Q'][:], np.log(levels), np.log(iobj['P'][:] * 100.), False)
out[iobj['ID'].value] = pd.DataFrame({'p': levels, 't': tnew, 'q': qnew})
else:
out[iobj['ID'].value] = pd.DataFrame({'p': iobj['P'][:] * 100., 't': iobj['T'][:], 'q': iobj['Q'][:]})
try:
out = pd.Panel(out)
except:
pass
print "Units: p: %s t: %s q: %s " % ('Pa', iobj['T'].attrs['UNITS'], iobj['Q'].attrs['UNITS'])
f.close()
return out, info
