def setUp(self):
"Setting common information"
self.JMA_std = load_jma('standard')
self.JMA_coaps = load_jma('coaps')
self.JMA_slide = load_jma('sliding')
def dump_seasonal_averages(observations, dbname="coaps.sqlite",
period="monthly", ensostr="ONI"):
"""
Dump seasonal averages of observations in a SQLite database.
The database is named following the template ``avg%(observations)s.sdb``.
For each season, there are four tables named following the template
``%(period)s_%(phase)s_%(ENSOindicator)``.
Each table has N+1 columns:
* Station COOP ID (format ``COOP%06i``)
* ENSO indicator (used to define the phase): in ('ONI', 'JMAI', 'MEI')
* ENSO phase : in ('A', 'C', 'N', 'W')
* N values for each season
Parameters
----------
observations: string
String representing the observations to store.
period : ('M', 'NDJ', 'DJF', 'JFM'), optional
String representing the seasons.
Use 'M' for monthly, 'DJF' for 'DJF,MAM,JJA,SON'...
ensostr : ('ONI', 'JMAI', 'MEI'), optional
String representing the ENSO indicator to define ENSO phases
"""
seasons = dict(monthly=['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN',
'JUL', 'AUG', 'SEP', 'OCT', 'NOV', 'DEC', ],
JFM=['JFM', 'AMJ', 'JAS', 'OND'],
DJF=['DJF', 'MAM', 'JJA', 'SON'],
NDJ=['NDJ', 'FMA', 'MJJ', 'ASO'])
# Get the seasonal frequency
period = period.upper()
period_to_freq = dict(M=hydro._c.FR_MTH,
MONTHLY=hydro._c.FR_MTH,
NDJ=hydro._c.FR_QTREOCT,
DJF=hydro._c.FR_QTRENOV,
JFM=hydro._c.FR_QTREDEC,)
try:
freq = period_to_freq[period]
except KeyError:
errmsg = "Invalid period '%s': should be in %s."
raise ValueError(errmsg % (period, period_to_freq.keys()))
# Get the names of the fields
# fieldslist = ["COOPID text primary key", "ENSOI text", "phase text"]
fieldslist = ["id integer primary key autoincrement",
"COOPID text", "ENSOI text", "phase text"]
if period in ("M", "MONTHLY"):
period = "monthly"
fieldslist += ["%s real" % _ for _ in seasons[period]]
nbfields = len(fieldslist)
# Get the conversion function:
if freq == hydro._c.FR_MTH:
conversion_func = None
else:
if observations == 'rain':
conversion_func = ma.sum
else:
conversion_func = ma.mean
# Load the ENSO information
ensostr = ensostr.upper()
if ensostr == 'ONI':
ENSO = enso.load_oni()
elif ensostr == 'JMAI':
ENSO = enso.load_jma()
elif ensostr == 'MEI':
raise NotImplementedError
else:
errmsg = "Invalid ENSO indicator '%s': should be in ('ONI','JMAI','MEI')"
raise ValueError(errmsg % ensostr)
# Get the monthly series from the datatable and set the ENSO indicator
tbname = "series_monthly_%s" % observations
monthly = sql.tsfromsqlite(dbname, tbname, freq="M")
monthly = enso.set_ensoindicator(monthly, ENSO)
# Define dictionaries storing the averages
avg_r = {}
# Loop on the stations
for station in monthly.dtype.names:
# Get the current station
current = monthly[station]
# Get the season
seasonal = current.convert(freq, func=conversion_func)
if (observations == "rain") and (freq != hydro._c.FR_MTH):
mask = hydro.time_series(current.mask, dates=current.dates)
seasonal.mask = mask.convert(freq, func=ma.sum)
# Get the values per phase
coopid = station[-6:]
avg_r[(coopid, ensostr, 'A')] = seasonal.convert("A").mean(0)
avg_r[(coopid, ensostr, 'C')] = seasonal.cold.convert("A").mean(0)
avg_r[(coopid, ensostr, 'N')] = seasonal.neutral.convert("A").mean(0)
avg_r[(coopid, ensostr, 'W')] = seasonal.warm.convert("A").mean(0)
# Get the database name
detect_types = sqlite3.PARSE_DECLTYPES | sqlite3.PARSE_COLNAMES
connection = sqlite3.connect(dbname, detect_types=detect_types)
# Define the creation/insertion lines
tbname = "averages_%(period)s_%(observations)s" % locals()
createstr = "create table %s (%s)" % (tbname, ", ".join(fieldslist))
insertstr_template = "insert into %s values (%s)"
insertstr = insertstr_template % (tbname, ", ".join(['?']*nbfields))
# Create the table
try:
connection.execute(createstr)
except sqlite3.OperationalError:
pass
# Define a generator for the values
generator = ([None, ] + list(k) + list(v.astype(np.object).filled((None,)))
for (k, v) in avg_r.items())
connection.executemany(insertstr, generator)
connection.commit()
connection.close()
def setUp(self):
"Setting common information"
self.JMA_std = load_jma('standard')
self.JMA_coaps = load_jma('coaps')
self.JMA_slide = load_jma('sliding')
import matplotlib
#matplotlib.use('Agg')
import scikits.hydroclimpy.plotlib as cpl
from scikits.hydroclimpy.plotlib.ensotools import csfigure, \
ENSOcolors, ENSOpolygons, \
ENSOmap
import logging
logger = logging.getLogger('compare_enso')
logger.debug("The fun starts here...")
JMA = enso.load_jma()
ONI = enso.load_oni()
print JMA.ensoindices.convert('A')
def plot_jma(num=None, fill=True, full_year=False, fill_neutral=False):
if num is None:
fig = csfigure(series=JMA)
else:
fig = csfigure(num=num, series=JMA)
fig.clear()
fsp = fig.add_csplot(111)
fill_colors = ENSOcolors['fill']
polygon_colors = ENSOcolors['polygons']
marker_colors = ENSOcolors['markers']
import multibarplot
from multibarplot import MultiBarPlot
from timescales import CalendarScaleSystem, MYScales, to_seconds_from_epoch
from zoom_plot_container import ReversedZoomOverlay, ZoomedPlotContainer
from enso_info import ElNinoOverlay, NeutralOverlay, LaNinaOverlay
import misc_tools
from misc_tools import print_decimal_coordinates, select_stations_around_reference
periods_dict = dict(MON=['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
JFM=['JFM', 'AMJ', 'JAS', 'OND'],
DJF=['DJF', 'MAM', 'JJA', 'SON'],
NDJ=['NDJ', 'FMA', 'MJJ', 'ASO'])
oni = enso.load_oni()
jmai = enso.load_jma()
class PeriodSelector(HasTraits):
period = Enum("MON", "JFM", "DJF", "NDJ")
entries = dict(MON=['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
JFM=['JFM', 'AMJ', 'JAS', 'OND'],
DJF=['DJF', 'MAM', 'JJA', 'SON'],
NDJ=['NDJ', 'FMA', 'MJJ', 'ASO'])
seasons = Property(depends_on="selector")
def _get_seasons(self):
return self.entries[self.period]