def omfbyo(data=None,return_deps=False):
deps = ['omf','obs']
omf = data[ncd.var_to_var('omf')]
obs = data[ncd.var_to_var('obs')]
val = omf/obs
return(val)
def spd_fcst(data=None,return_deps=False):
deps = ['u_obs','v_obs','u_omf','v_omf']
u_bkg = data[ncd.var_to_var('u_obs')] - data[ncd.var_to_var('u_omf')]
v_bkg = data[ncd.var_to_var('v_obs')] - data[ncd.var_to_var('v_omf')]
spd_b = (u_bkg**2 + v_bkg**2) ** (0.5)
val = spd_b
return(val)
def dist(data=None,return_deps=False):
from scipy.spatial.distance import cdist
deps = ['lon','lat']
if (data['centroid_lat'] is None or data['centroid_lon'] is None):
raise Exception('Distance calculations require a focal lon/lat to be set by ncd.set_centroid(lon,lat)')
d = ( (data[ncd.var_to_var('lat')] - data['centroid_lat']) ** 2 + (data[ncd.var_to_var('lon')] - data['centroid_lon']) ** 2 ) ** (0.5)
# d = cdist(np.transpose( [data[ncd.var_to_var('lat'), data[ncd.var_to_var('lon')] ), [data['centroid_lat', data['centroid_lon'], 'euclidean')
return(d)
def dir_obs(data=None,return_deps=False):
deps = ['u_obs','v_obs']
u_obs = data[ncd.var_to_var('u_obs')]
v_obs = data[ncd.var_to_var('v_obs')]
spd_o = (u_obs**2 + v_obs**2) ** (0.5)
dir_o = spd_o * 0.0 + 999.
msk = (spd_o > 0.0)
dir_o[msk] = np.arctan2(u_obs[msk],v_obs[msk]) * 180.0 / np.pi
val = dir_o
return(val)
def dir_fcst(data=None,return_deps=False):
deps = ['u_obs','v_obs','u_omf','v_omf']
u_bkg = data[ncd.var_to_var('u_obs')] - data[ncd.var_to_var('u_omf')]
v_bkg = data[ncd.var_to_var('v_obs')] - data[ncd.var_to_var('v_omf')]
spd_b = (u_bkg**2 + v_bkg**2) ** (0.5)
dir_b = spd_b*0.0 + 999.
msk = (spd_b > 0.0)
dir_b[msk] = np.arctan2(u_bkg[msk],v_bkg[msk]) * 180.0 / np.pi
val = dir_b
return(val)
def rand(data=None,return_deps=False):
import numpy.random as rnd
deps = ['lon']
nv = data[ncd.var_to_var('lon')].size
val = rnd.rand(nv)
return(val)
def amb(data=None, return_deps=False):
deps = ['omf', 'oma']
val = data[ncd.var_to_var('omf')] - data[ncd.var_to_var('oma')]
return (val)
def sigobyf(data=None,return_deps=False):
deps = ['omf','obs','sigo']
val = data[ncd.var_to_var('sigo')] / (data[ncd.var_to_var('obs')] - data[ncd.var_to_var('omf')])
return(val)
def angord(data=None,return_deps=False):
deps = ['BC_angord']
val = np.sum(data[ncd.var_to_var('BC_angord')],axis=1)
return(val)
def spd_obs(data=None,return_deps=False):
deps = ['u_obs','v_obs']
spd_o = (data[ncd.var_to_var('u_obs')]**2 + data[ncd.var_to_var('v_obs')]**2) ** (0.5)
val = spd_o
return(val)
def anl(data=None,return_deps=False):
deps = ['oma','obs']
val = data[ncd.var_to_var('obs')]-data[ncd.var_to_var('oma')]
return(val)
def fcst(data=None,return_deps=False):
deps = ['omf','obs']
val = data[ncd.var_to_var('obs')]-data[ncd.var_to_var('omf')]
return(val)
def bc(data=None,return_deps=False):
deps = ['omfbc','omfnbc']
val = data[ncd.var_to_var('omfbc')]-data[ncd.var_to_var('omfnbc')]
return(val)