def daves_curtain(file, img_file, section, varname, clim=None):
if varname == 'U':
daves_U_curtain(file, img_file, section, varname, clim)
else:
x = utils.get_daves_section_var(section=section, var='lon')
y = utils.get_daves_section_var(section=section, var='lat')
(data, coords) = rompy.extract(file,
varname=varname,
extraction_type='profile',
x=x,
y=y)
title = '%s %s %s %s %s' % (
extract_utils.run_title(file),
os.path.basename(file), section, var_title_map[var],
extract_utils.file_time(file).strftime(title_time_fmt))
plot_utils.plot_parker(
coords=coords,
data=data,
filename=img_file,
title=title,
x_axis_offset=utils.offset_region(coords),
clim=clim,
cmap='banas_hsv_cm',
labeled_contour_gap=2,
caxis_label=clabel_map[varname],
inset=inset_dict[section],
ctd_ind=ctd_ind_dict[section],
label=utils.get_daves_section_var(section=section, var='label'),
label_ind=utils.get_daves_section_var(section=section,
var='label_ind'))
return
def hood_canal_curtain(file, img_file, varname, n=1, clim=None): # Hood Canal
if var == 'U':
hood_canal_U_curtain(file, img_file, n, clim)
else:
x, y = utils.high_res_hood_canal_xy(n=n)
(data, coords) = rompy.extract(file,
varname=varname,
extraction_type='profile',
x=x,
y=y)
title = '%s %s Hood Canal %s %s' % (
extract_utils.run_title(file),
os.path.basename(file), var_title_map[var],
extract_utils.file_time(file).strftime(title_time_fmt))
plot_utils.plot_parker(coords=coords,
data=data,
varname=varname,
region='Hood Canal',
filename=img_file,
n=n,
x_axis_offset=utils.offset_region(coords),
clim=clim,
cmap='banas_hsv_cm',
labeled_contour_gap=2,
title=title,
resolution=inset_coastline_resolution,
caxis_label=clabel_map[varname])
def main_basin_curtain(file, img_file, varname, n=4, clim=None): # Main Basin
if varname == 'U':
main_basin_U_curtain(file, img_file, n, clim)
else:
x, y = utils.high_res_main_basin_xy(n=n)
(data, coords) = rompy.extract(file,
varname=varname,
extraction_type='profile',
x=x,
y=y)
title = '%s %s Main Basin %s %s' % (
extract_utils.run_title(file),
os.path.basename(file), var_title_map[var],
extract_utils.file_time(file).strftime(title_time_fmt))
plot_utils.plot_parker(coords=coords,
data=data,
varname=varname,
region='Main Basin',
filename=img_file,
n=n,
x_axis_offset=utils.offset_region(coords),
clim=clim,
cmap='banas_hsv_cm',
labeled_contour_gap=2,
title=title,
caxis_label=clabel_map[varname])
def daves_U_curtain(file, img_file, section, varname, clim):
x = utils.get_daves_section_var(section=section, var='lon')
y = utils.get_daves_section_var(section=section, var='lat')
(u, coords) = rompy.extract(file,
varname='u',
extraction_type='profile',
x=x,
y=y)
(v, coords) = rompy.extract(file,
varname='v',
extraction_type='profile',
x=x,
y=y)
data = np.zeros(u.shape)
for i in range(u.shape[1]):
if i == u.shape[1] - 1:
x_vec = np.array([x[i] - x[i - 1], y[i] - y[i - 1]])
else:
x_vec = np.array([x[i + 1] - x[i], y[i + 1] - y[i]])
for j in range(u.shape[0]):
u_vec = np.array([u[j, i], v[j, i]])
data[j, i] = np.dot(x_vec, u_vec) / (np.sqrt(np.dot(x_vec, x_vec)))
data = np.ma.array(data, mask=np.abs(data) > 100)
title = '%s %s %s %s %s' % (
extract_utils.run_title(file),
os.path.basename(file), section, var_title_map['U'],
extract_utils.file_time(file).strftime(title_time_fmt))
plot_utils.plot_parker(coords=coords,
data=data,
filename=img_file,
title=title,
x_axis_offset=utils.offset_region(coords),
clim=clim,
cmap='red_blue',
labeled_contour_gap=2,
caxis_label=clabel_map[varname],
inset=inset_dict[section],
ctd_ind=ctd_ind_dict[section],
label=utils.get_daves_section_var(section=section,
var='label'),
label_ind=utils.get_daves_section_var(
section=section, var='label_ind'))
return
def hood_canal_U_curtain(file,
img_file,
n=1,
clim=None): # velocity in Hood Canal
x, y = utils.high_res_hood_canal_xy(n=n)
(u, coords) = rompy.extract(file,
varname='u',
extraction_type='profile',
x=x,
y=y)
(v, coords) = rompy.extract(file,
varname='v',
extraction_type='profile',
x=x,
y=y)
data = np.zeros(u.shape)
for i in range(u.shape[1]):
if i == u.shape[1] - 1:
x_vec = np.array([x[i] - x[i - 1], y[i] - y[i - 1]])
else:
x_vec = np.array([x[i + 1] - x[i], y[i + 1] - y[i]])
for j in range(u.shape[0]):
u_vec = np.array([u[j, i], v[j, i]])
data[j, i] = np.dot(x_vec, u_vec) / (np.sqrt(np.dot(x_vec, x_vec)))
data = np.ma.array(data, mask=np.abs(data) > 100)
title = '%s %s Hood Canal %s %s' % (
extract_utils.run_title(file),
os.path.basename(file), var_title_map['U'],
extract_utils.file_time(file).strftime(title_time_fmt))
hood_U_clim = (np.array(clim) / 2.0).tolist()
plot_utils.plot_parker(coords=coords,
data=data,
varname='U',
region='Hood Canal',
filename=img_file,
n=n,
clim=clim,
x_axis_offset=utils.offset_region(coords),
cmap='red_blue',
title=title,
resolution=inset_coastline_resolution,
caxis_label=clabel_map['U'])
def surface_map(file, img_file=None, varname='salt', clim=None):
(data, coords) = rompy.extract(file,
varname=varname,
extraction_type='surface')
# plot_utils.plot_surface(coords['xm'],coords['ym'],data)
title = '%s %s %s %s' % (
extract_utils.run_title(file),
os.path.basename(file), var_title_map[var],
extract_utils.file_time(file).strftime(title_time_fmt))
plot_utils.plot_map(coords['xm'],
coords['ym'],
data,
filename=img_file,
clim=clim,
title=title,
caxis_label=clabel_map[varname])
def main_basin_U_curtain(file,img_file,n=1,clim=None): # velocity in Main Basin x,y = utils.high_res_main_basin_xy(n=n) (u, coords) = rompy.extract(file,varname='u',extraction_type='profile',x=x,y=y) (v, coords) = rompy.extract(file,varname='v',extraction_type='profile',x=x,y=y) data = np.zeros(u.shape) for i in range(u.shape[1]): if i == u.shape[1]-1: x_vec = np.array([x[i] - x[i-1], y[i] - y[i-1]]) else: x_vec = np.array([x[i+1] - x[i], y[i+1] - y[i]]) for j in range(u.shape[0]): u_vec = np.array([u[j,i], v[j,i]]) data[j,i] = np.dot(x_vec,u_vec)/(np.sqrt(np.dot(x_vec,x_vec))) data = np.ma.array(data, mask=np.abs(data) > 100) title = '%s %s Main Basin %s %s' % (extract_utils.run_title(file), os.path.basename(file), var_title_map['U'], extract_utils.file_time(file).strftime(title_time_fmt)) plot_utils.plot_parker(coords=coords,data=data,varname='U', region=' Main Basin', filename=img_file, n=n, clim=clim, x_axis_offset=utils.offset_region(coords),cmap='red_blue', title=title, resolution=inset_coastline_resolution, caxis_label=clabel_map['U'])
def hood_canal_curtain(file,img_file,varname,n=1,clim=None): # Hood Canal if var == 'U': hood_canal_U_curtain(file,img_file,n,clim) else: x,y = utils.high_res_hood_canal_xy(n=n) (data, coords) = rompy.extract(file, varname=varname, extraction_type='profile', x=x, y=y) title = '%s %s Hood Canal %s %s' % (extract_utils.run_title(file), os.path.basename(file), var_title_map[var], extract_utils.file_time(file).strftime(title_time_fmt)) plot_utils.plot_parker(coords=coords, data=data, varname=varname, region='Hood Canal', filename=img_file, n=n, x_axis_offset=utils.offset_region(coords), clim=clim, cmap='banas_hsv_cm',labeled_contour_gap=2, title=title, resolution=inset_coastline_resolution, caxis_label=clabel_map[varname])
def surface_map(file,img_file=None,varname='salt',clim=None): (data, coords) = rompy.extract(file,varname=varname,extraction_type='surface') # plot_utils.plot_surface(coords['xm'],coords['ym'],data) title = '%s %s %s %s' % ( extract_utils.run_title(file), os.path.basename(file), var_title_map[var], extract_utils.file_time(file).strftime(title_time_fmt) ) plot_utils.plot_map(coords['xm'],coords['ym'],data,filename=img_file, clim=clim, title=title, resolution=whole_domain_coastline_res, caxis_label=clabel_map[varname])
def daves_curtain(file,img_file,section,varname,clim=None): if varname == 'U': daves_U_curtain(file,img_file,section,varname,clim) else: x = utils.get_daves_section_var(section=section,var='lon') y = utils.get_daves_section_var(section=section,var='lat') (data, coords) = rompy.extract(file, varname=varname, extraction_type='profile', x=x, y=y) title = '%s %s %s %s %s' % (extract_utils.run_title(file), os.path.basename(file), section, var_title_map[var], extract_utils.file_time(file).strftime(title_time_fmt)) plot_utils.plot_parker( coords=coords, data=data, filename=img_file, title=title, x_axis_offset=utils.offset_region(coords), clim=clim, cmap='banas_hsv_cm', labeled_contour_gap=2, caxis_label=clabel_map[varname], inset=inset_dict[section], ctd_ind=ctd_ind_dict[section], label=utils.get_daves_section_var(section=section,var='label'), label_ind=utils.get_daves_section_var(section=section,var='label_ind') ) return
def main_basin_curtain(file,img_file,varname,n=4,clim=None): # Main Basin if varname == 'U': main_basin_U_curtain(file,img_file,n,clim) else: x,y = utils.high_res_main_basin_xy(n=n) (data, coords) = rompy.extract(file, varname=varname, extraction_type='profile', x=x, y=y) title = '%s %s Main Basin %s %s' % (extract_utils.run_title(file), os.path.basename(file), var_title_map[var], extract_utils.file_time(file).strftime(title_time_fmt)) plot_utils.plot_parker(coords=coords, data=data, varname=varname, region='Main Basin', filename=img_file, n=n, x_axis_offset=utils.offset_region(coords), clim=clim,cmap='banas_hsv_cm',labeled_contour_gap=2, title=title, caxis_label=clabel_map[varname])
def daves_U_curtain(file,img_file,section,varname,clim): x = utils.get_daves_section_var(section=section,var='lon') y = utils.get_daves_section_var(section=section,var='lat') (u, coords) = rompy.extract(file,varname='u',extraction_type='profile',x=x,y=y) (v, coords) = rompy.extract(file,varname='v',extraction_type='profile',x=x,y=y) data = np.zeros(u.shape) for i in range(u.shape[1]): if i == u.shape[1]-1: x_vec = np.array([x[i] - x[i-1], y[i] - y[i-1]]) else: x_vec = np.array([x[i+1] - x[i], y[i+1] - y[i]]) for j in range(u.shape[0]): u_vec = np.array([u[j,i], v[j,i]]) data[j,i] = np.dot(x_vec,u_vec)/(np.sqrt(np.dot(x_vec,x_vec))) data = np.ma.array(data, mask=np.abs(data) > 100) title = '%s %s %s %s %s' % (extract_utils.run_title(file), os.path.basename(file), section, var_title_map['U'], extract_utils.file_time(file).strftime(title_time_fmt)) plot_utils.plot_parker( coords=coords, data=data, filename=img_file, title=title, x_axis_offset=utils.offset_region(coords), clim=clim, cmap='red_blue', labeled_contour_gap=2, caxis_label=clabel_map[varname], inset=inset_dict[section], ctd_ind=ctd_ind_dict[section], label=utils.get_daves_section_var(section=section,var='label'), label_ind=utils.get_daves_section_var(section=section,var='label_ind') ) return