def download(dbname, dts, bbox=None):
res = 0.10
for dt in [
dts[0] + timedelta(tt) for tt in range((dts[-1] - dts[0]).days + 1)
]:
data, lat, lon, t = fetch(dbname, dt, bbox)
datasets.ingest(dbname, table, data, lat, lon, res, t)
def download(dbname, dts, bbox=None):
res = 0.25
data, lat, lon, dts = fetch(dbname, dts, bbox)
data *= 24.0 # convert from mm/hr to mm
for t, dt in enumerate(
[dts[0] + timedelta(tt) for tt in range((dts[-1] - dts[0]).days + 1)]):
datasets.ingest(dbname, table, data[t, :, :], lat, lon, res, dt)
def download(dbname, dts, bbox=None):
res = 1.0
sdata, _, _, _ = fetchScalingGrid(dbname, dts[0], bbox)
for dt in [dts[0] + timedelta(tt) for tt in range((dts[-1] - dts[0]).days + 1)]:
try:
data, lat, lon, t = fetch(dbname, dt, bbox)
data *= sdata
datasets.ingest(dbname, table, data, lat, lon, res, t, False)
except:
pass
def download(dbname, dts, bbox=None):
"""Downloads NCEP Reanalysis data from IRI data library."""
res = 1.875
tmax, lat, lon, _ = fetch_tmax(dbname, dts, bbox)
tmin, _, _, _ = fetch_tmin(dbname, dts, bbox)
uwnd, _, _, _ = fetch_uwnd(dbname, dts, bbox)
vwnd, _, _, dts = fetch_vwnd(dbname, dts, bbox)
wnd = np.sqrt(uwnd**2 + vwnd**2)
tmax -= 273.15
tmin -= 273.15
for t, dt in enumerate([dts[0] + timedelta(tt) for tt in range((dts[-1] - dts[0]).days + 1)]):
datasets.ingest(dbname, "tmax.ncep", tmax[t, :, :], lat, lon, res, dt)
datasets.ingest(dbname, "tmin.ncep", tmin[t, :, :], lat, lon, res, dt)
datasets.ingest(dbname, "wind.ncep", wnd[t, :, :], lat, lon, res, dt)
def download(dbname, dts, bbox=None):
"""Downloads NCEP Reanalysis data from IRI data library."""
res = 1.875
tmax, lat, lon, _ = fetch_tmax(dbname, dts, bbox)
tmin, _, _, _ = fetch_tmin(dbname, dts, bbox)
uwnd, _, _, _ = fetch_uwnd(dbname, dts, bbox)
vwnd, _, _, dts = fetch_vwnd(dbname, dts, bbox)
wnd = np.sqrt(uwnd**2 + vwnd**2)
tmax -= 273.15
tmin -= 273.15
for t, dt in enumerate(
[dts[0] + timedelta(tt) for tt in range((dts[-1] - dts[0]).days + 1)]):
datasets.ingest(dbname, "tmax.ncep", tmax[t, :, :], lat, lon, res, dt)
datasets.ingest(dbname, "tmin.ncep", tmin[t, :, :], lat, lon, res, dt)
datasets.ingest(dbname, "wind.ncep", wnd[t, :, :], lat, lon, res, dt)
def download(dbname, dt, bbox=None):
res = 0.25
data, lat, lon, t = fetch(dbname, dt, bbox)
datasets.ingest(dbname, table, data, lat, lon, res, t)
def download(dbname, dt, bbox=None):
res = 1.0
data, lat, lon, t = fetch(dbname, dt, bbox)
sdata, _, _, _ = fetchScalingGrid(dbname, dt, bbox)
data *= sdata
datasets.ingest(dbname, table, data, lat, lon, res, t)
def download(dbname, dts, bbox=None):
res = 0.25
data, lat, lon, dts = fetch(dbname, dts, bbox)
for t, dt in enumerate([dts[0] + timedelta(tt) for tt in range((dts[-1] - dts[0]).days + 1)]):
datasets.ingest(dbname, table, data[t, :, :], lat, lon, res, dt)
def download(dbname, dts, bbox=None):
res = 0.05
for dt in [dts[0] + timedelta(tt) for tt in range((dts[1] - dts[0]).days + 1)]:
data, lat, lon, t = fetch(dbname, dt, bbox)
datasets.ingest(dbname, table, data, lat, lon, res, t)