cmap='jet')
pc.set_clim([-0.1, 0.1])
cbar = fig.colorbar(pc, ax=ax)
cbar.set_label('%s (%s)' %
(data_nc_SEP.var_varname, data_nc_SEP.var_ncattrs['units']))
ax.set_title('t=%d (%s)' % (timestep, data_nc_SEP.var_times.iloc[timestep]))
ax.set_aspect('equal')
#ax.quiver(data_nc_XZ[::2,::2], data_nc_YZ[::2,::2], vel_x[::2,::2], vel_y[::2,::2],
# scale=3,color='w',width=0.005)#, edgecolor='face', cmap='jet')
fig.tight_layout()
plt.savefig(os.path.join(dir_output, 'waqua_DCSM_map_wl'))
#HIS ZUNO
file_nc = r'p:\1204257-dcsmzuno\2019\DCSMv6\A01\SDS-A01_his.nc'
vars_pd, dims_pd = get_ncvardimlist(file_nc=file_nc)
data_nc_NAMWL = get_hisstationlist(file_nc=file_nc, varname='NAMWL')
#data_nc_NAMC = get_hisstationlist(file_nc=file_nc, varname='NAMC')
data_nc_ZWL = get_ncmodeldata(file_nc=file_nc,
varname='ZWL',
timestep='all',
station='all')
#data_nc_ZCURU = get_ncmodeldata(file_nc=file_nc, varname='ZCURU',timestep='all',station='all')
#data_nc_ZCURV = get_ncmodeldata(file_nc=file_nc, varname='ZCURV',timestep='all',station='all')
fig, ax = plt.subplots(figsize=(16, 7))
for iS in range(10):
ax.plot(data_nc_ZWL.var_times,
data_nc_ZWL[:, iS],
label=data_nc_NAMWL['NAMWL'].iloc[iS],
linewidth=1)
ax.legend(loc=1)
os.path.join(
dir_output, '%s_%s_vec' %
(os.path.basename(file_nc).replace('.', ''), varname)))
for ax in axs:
ax.set_xlim([25000, 65000])
ax.set_ylim([2500, 15000])
plt.savefig(
os.path.join(
dir_output, '%s_%s_veczoom' %
(os.path.basename(file_nc).replace('.', ''), varname)))
#HISFILE
file_nc = r'p:\11203869-morwaqeco3d\05-Tidal_inlet\02_FM_201910\FM_MF10_Max_30s\fm\DFM_OUTPUT_inlet\inlet_his.nc'
vars_pd, dims_pd = get_ncvardimlist(file_nc=file_nc)
vars_pd_sel = vars_pd[vars_pd['long_name'].str.contains('level')]
stat_list = get_hisstationlist(file_nc, varname='station_name')
crs_list = get_hisstationlist(file_nc, varname='cross_section_name')
var_names = ['waterlevel', 'bedlevel'] #,'mesh2d_ssn']
for iV, varname in enumerate(var_names):
data_fromhis = get_ncmodeldata(file_nc=file_nc,
varname=varname,
timestep='all',
station='all')
var_longname = vars_pd['long_name'][vars_pd['nc_varkeys'] ==
varname].iloc[0]
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
for iS, stat in enumerate(data_fromhis.var_stations['station_name']):
ax.plot(data_fromhis.var_times,
data_fromhis[:, iS],
import matplotlib.pyplot as plt
plt.close('all')
from dfm_tools.get_nc import get_netdata, get_ncmodeldata, plot_netmapdata
from dfm_tools.get_nc_helpers import get_ncvardimlist, get_timesfromnc, get_hisstationlist, get_ncfilelist
#uncomment the line below, copy data locally and change this path to increase performance
dir_testinput = os.path.join(r'E:\proj\Pescadero\Model_Runs\Testing')
file_nc_map = os.path.join(dir_testinput, 'run_tide_test-v12A',
'DFM_OUTPUT_flowfm', 'flowfm_map.nc')
file_nc_his = os.path.join(dir_testinput, 'run_tide_test-v12A',
'DFM_OUTPUT_flowfm', 'flowfm_his.nc')
#get lists with vars/dims, times, station/crs/structures
vars_pd, dims_pd = get_ncvardimlist(file_nc=file_nc_map)
times_pd = get_timesfromnc(file_nc=file_nc_map)
statlist_pd = get_hisstationlist(file_nc=file_nc_his, varname='station_name')
#retrieve his data
data_fromhis_wl = get_ncmodeldata(file_nc=file_nc_his,
varname='waterlevel',
station='all',
timestep='all')
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
for iP, station in enumerate(data_fromhis_wl.var_stations['station_name']):
ax.plot(data_fromhis_wl.var_times,
data_fromhis_wl[:, iP],
'-',
label=station)
ax.legend()
ax.set_ylabel(
'%s (%s)' %
(data_fromnc_u.var_ncattrs['units']))
ax.set_title('t=%d (%s)' %
(timestep, data_fromnc_u.var_times.loc[timestep]))
ax.set_aspect('equal')
thinning = 5
ax.quiver(
data_fromnc_edgex[::thinning, ::thinning],
data_fromnc_edgey[::thinning, ::thinning],
data_fromnc_u[timestep, ::thinning, ::thinning],
data_fromnc_v[timestep, ::thinning, ::thinning],
color='w') #,scale=3,width=0.005)#, edgecolor='face', cmap='jet')
fig.tight_layout()
plt.savefig(os.path.join(dir_output, 'SFINCS_velocity_pcolorquiver'))
#SFINCS HIS
#file_nc = r'p:\11202255-sfincs\Testbed\Original_tests\01_Implementation\14_restartfile\sfincs_his.nc'
file_nc = r'p:\11202255-sfincs\Testbed\Original_tests\03_Application\04_Tsunami_Japan_Sendai\sfincs_his.nc'
vars_pd, dims_pd = get_ncvardimlist(file_nc=file_nc)
station_names = get_hisstationlist(file_nc=file_nc, varname='point_zs')
data_fromnc_his = get_ncmodeldata(file_nc=file_nc,
varname='point_zs',
station='all',
timestep='all')
fig, ax = plt.subplots()
for iS, stat_name in enumerate(data_fromnc_his.var_stations['station_name']):
ax.plot(data_fromnc_his.var_times, data_fromnc_his[:, iS], label=stat_name)
ax.legend()
plt.savefig(os.path.join(dir_output, 'SFINCS_hiszs'))