Python CESM_utils_plt.print2pdf Exemples

Exemple #1

Fichier : _main_CESM_plot_MOC_spec.py Projet : LABclimate/MT

plt.title('MW on density axis longitudinally integrated on auxgrd (in Sv)')
plt.ylabel('density')
ax = utils_plt.plot_MOC(lat_auxgrd, db, dMWxint_auxgrd, nlevels=40, plttype='pcolor', to_newfigure=False)
plt.plot(lat_mgrd, np.nanmax(np.nanmax(sig2,0),1), 'm-', label='maximal density (on mgrd)')
#plt.yticks(ticks_vol_reg)
#plt.gca().set_yticklabels(ticks_dens)
plt.xlim([-36,90])
plt.legend(loc='lower left')

plt.subplot(3,1,3)
plt.plot(lat_auxgrd, np.nansum(dMWxint_auxgrd,axis=0), '.-k')
plt.colorbar()
plt.xlim([-36,90])
plt.ylabel('sum over whole density-axis (in Sv)')
plt.xlabel('latitude')
utils_plt.print2pdf(fig, path_fig+'dMOC_tripple'+varname_binning)




# -----------------------------------------------------------------------------
# 5 subplots showing densities, Temperature and MW against depth and density axis
# -----------------------------------------------------------------------------
lat = 85
lon = 30
plt.figure()
plt.suptitle('location: lat={:d} lon={:d}'.format(lat, lon))

plt.subplot(1,5,1)
ax = plt.gca(); ax.invert_yaxis()
plt.plot(sig2[:,lat,lon], MW_mgrd.z_w_top, '.-r', label='sigma 2')

Exemple #2

Fichier : _main_CESM_plot_MOC_spec.py Projet : LABclimate/MT

plt.plot(lat_mgrd,
         np.nanmax(np.nanmax(sig2, 0), 1),
         'm-',
         label='maximal density (on mgrd)')
#plt.yticks(ticks_vol_reg)
#plt.gca().set_yticklabels(ticks_dens)
plt.xlim([-36, 90])
plt.legend(loc='lower left')

plt.subplot(3, 1, 3)
plt.plot(lat_auxgrd, np.nansum(dMWxint_auxgrd, axis=0), '.-k')
plt.colorbar()
plt.xlim([-36, 90])
plt.ylabel('sum over whole density-axis (in Sv)')
plt.xlabel('latitude')
utils_plt.print2pdf(fig, path_fig + 'dMOC_tripple' + varname_binning)

# -----------------------------------------------------------------------------
# 5 subplots showing densities, Temperature and MW against depth and density axis
# -----------------------------------------------------------------------------
lat = 85
lon = 30
plt.figure()
plt.suptitle('location: lat={:d} lon={:d}'.format(lat, lon))

plt.subplot(1, 5, 1)
ax = plt.gca()
ax.invert_yaxis()
plt.plot(sig2[:, lat, lon], MW_mgrd.z_w_top, '.-r', label='sigma 2')
plt.plot(RHO[:, lat, lon], MW_mgrd.z_w_top, '.-m', label='in-situ density')
plt.title('Dens against depth')

Exemple #3

path_fig = '../figures/160711/'

# =======================================================================================
#  Calculated on model grid
# =======================================================================================
# -----------------------------------------------------------------------------------------
# MOC_mgrd_W
fig, ax = utils_plt.plot_MOC(lat_mgrd,
                             ncdat.z_w_top,
                             MOC_mgrd_W,
                             nlevels=10,
                             plttype='pcolor+contour')
plt.plot(lat_mgrd, HT_mgrd_xmax)  # plot seafloor #! it's the T-grid!!!
plt.title('MOC mgrd W')
plt.xlim([-36, 90])
utils_plt.print2pdf(fig, path_fig + 'MOC_mgrd_W')

# -----------------------------------------------------------------------------------------
# dMOC_mgrid_W(in Sv)
fig, ax = utils_plt.plot_MOC(lat_mgrd,
                             db,
                             dMOC_mgrd_W,
                             nlevels=10,
                             plttype='pcolor+contour')
plt.title('dMOC mgrd W (sigma2)')
plt.suptitle('density binning from {} to {} in {} steps'.format(
    dbc.min(), dbc.max(), len(dbc)))
plt.xlim([-36, 73])
plt.yticks(ticks_vol)
plt.gca().set_yticklabels(ticks_dens)
#utils_plt.print2pdf(fig, path_fig+'dMOC_mgrd_W_sig2')

Exemple #4

Fichier : main_CESM_controls.py Projet : LABclimate/MT

                             MOC_model,
                             nlevels=40,
                             plttype='pcolor+contour')
plt.plot(lat_auxgrd, HT_auxgrd_xmax)  # plot seafloor
plt.title('MOC model')
plt.xlim([-36, 90])
#utils_plt.print2pdf(fig, 'testfigures/MOC_model')

# =======================================================================================
#  Calculated on model grid
# =======================================================================================
# -----------------------------------------------------------------------------------------
# BSF on model grid
fig, map = utils_plt.plot_BSF(BSF_mgrd, 'U', nlevels=100)
plt.title('BSF mgrd on U grid')
utils_plt.print2pdf(fig, 'testfigures/BSF_mgrd_U')
# -----------------------------------------------------------------------------------------
# MOC_mgrd_W
fig, ax = utils_plt.plot_MOC(lat_mgrd,
                             ncdat.z_w_top,
                             MOC_mgrd_W,
                             nlevels=10,
                             plttype='pcolor+contour')
plt.plot(lat_mgrd, HT_mgrd_xmax)  # plot seafloor #! it's the T-grid!!!
plt.title('MOC mgrd W')
plt.xlim([-36, 90])
utils_plt.print2pdf(fig, path_fig + 'MOC_mgrd_W')
# -----------------------------------------------------------------------------------------
# MOC_mgrd_V
fig, ax = utils_plt.plot_MOC(lat_mgrd,
                             ncdat.z_t,

Exemple #5

Fichier : _main_CESM_controls_plotting.py Projet : LABclimate/MT

import matplotlib.pyplot as plt
import matplotlib as ml
import CESM_utils_plt as utils_plt

plt.ion()  # enable interactive mode
path_fig = '../figures/160711/'

# =======================================================================================
#  CCSM4 representations
# =======================================================================================
# -----------------------------------------------------------------------------------------
# BSF on geographical grid calculated by model
BSF_model = utils_mask.mask_ATLANTIC(ncdat.BSF.isel(time=0), ncdat.REGION_MASK)
fig, map = utils_plt.plot_BSF(BSF_model, 'T', nlevels=10)
plt.title('BSF model on T grid')
utils_plt.print2pdf(fig, path_fig + 'BSF_model_T')
# -----------------------------------------------------------------------------------------
# MOC on geographical grid calculated by model
MOC_model = ncdat.MOC.isel(time=0, transport_reg=1, moc_comp=0)
#MOC_model = MOC_model - MOC_model[:,-1] # normalisation
fig, ax = utils_plt.plot_MOC(MOC_model.lat_aux_grid,
                             MOC_model.moc_z,
                             MOC_model,
                             nlevels=10,
                             plttype='pcolor+contour')
plt.plot(lat_auxgrd, HT_auxgrd_xmax)  # plot seafloor
plt.title('MOC model')
plt.xlim([-36, 90])
utils_plt.print2pdf(fig, path_fig + 'MOC_model')

# =======================================================================================

Exemple #6

Fichier : _main_CESM_controls_plotting.py Projet : LABclimate/MT

import matplotlib as ml
import CESM_utils_plt as utils_plt

plt.ion() # enable interactive mode
path_fig = '../figures/160711/'


# =======================================================================================
#  CCSM4 representations
# =======================================================================================
# -----------------------------------------------------------------------------------------
# BSF on geographical grid calculated by model
BSF_model = utils_mask.mask_ATLANTIC(ncdat.BSF.isel(time=0), ncdat.REGION_MASK)
fig, map = utils_plt.plot_BSF(BSF_model, 'T', nlevels = 10)
plt.title('BSF model on T grid')
utils_plt.print2pdf(fig, path_fig+'BSF_model_T')
# -----------------------------------------------------------------------------------------
# MOC on geographical grid calculated by model
MOC_model = ncdat.MOC.isel(time=0, transport_reg=1, moc_comp=0)
#MOC_model = MOC_model - MOC_model[:,-1] # normalisation
fig, ax = utils_plt.plot_MOC(MOC_model.lat_aux_grid, MOC_model.moc_z, MOC_model, nlevels=10, plttype='pcolor+contour')
plt.plot(lat_auxgrd,HT_auxgrd_xmax) 				# plot seafloor
plt.title('MOC model')
plt.xlim([-36,90])
utils_plt.print2pdf(fig, path_fig+'MOC_model')

# =======================================================================================
#  Calculated on model grid
# =======================================================================================
# -----------------------------------------------------------------------------------------
# BSF on model grid

Exemple #7

Fichier : _main_CESM_plot_MOC_W.py Projet : LABclimate/MT

import matplotlib as ml
import CESM_utils_plt as utils_plt

plt.ion() # enable interactive mode
path_fig = '../figures/160711/'

# =======================================================================================
#  Calculated on model grid
# =======================================================================================
# -----------------------------------------------------------------------------------------
# MOC_mgrd_W
fig, ax = utils_plt.plot_MOC(lat_mgrd, ncdat.z_w_top, MOC_mgrd_W, nlevels=10, plttype='pcolor+contour')
plt.plot(lat_mgrd,HT_mgrd_xmax) 				# plot seafloor #! it's the T-grid!!!
plt.title('MOC mgrd W')
plt.xlim([-36,90])
utils_plt.print2pdf(fig, path_fig+'MOC_mgrd_W')

# -----------------------------------------------------------------------------------------
# dMOC_mgrid_W(in Sv)
fig, ax = utils_plt.plot_MOC(lat_mgrd, db, dMOC_mgrd_W, nlevels=10, plttype='pcolor+contour')
plt.title('dMOC mgrd W (sigma2)')
plt.suptitle('density binning from {} to {} in {} steps'.format(dbc.min(), dbc.max(), len(dbc)))
plt.xlim([-36,73])
plt.yticks(ticks_vol)
plt.gca().set_yticklabels(ticks_dens)
#utils_plt.print2pdf(fig, path_fig+'dMOC_mgrd_W_sig2')

# =======================================================================================
#  Calculated on auxiliary (geographical) grid
# =======================================================================================
# -----------------------------------------------------------------------------------------

Exemple #8

Fichier : main_CESM_controls.py Projet : LABclimate/MT

MOC_model = ncdat.MOC.isel(time=0, transport_reg=1, moc_comp=0)
MOC_model = MOC_model - MOC_model[:,-1] # normalisation
fig, ax = utils_plt.plot_MOC(MOC_model.lat_aux_grid, MOC_model.moc_z, MOC_model, nlevels=40, plttype='pcolor+contour')
plt.plot(lat_auxgrd,HT_auxgrd_xmax) 				# plot seafloor
plt.title('MOC model')
plt.xlim([-36,90])
 #utils_plt.print2pdf(fig, 'testfigures/MOC_model')

# =======================================================================================
#  Calculated on model grid
# =======================================================================================
# -----------------------------------------------------------------------------------------
# BSF on model grid
fig, map = utils_plt.plot_BSF(BSF_mgrd, 'U', nlevels=100)
plt.title('BSF mgrd on U grid')
utils_plt.print2pdf(fig, 'testfigures/BSF_mgrd_U')
# -----------------------------------------------------------------------------------------
# MOC_mgrd_W
fig, ax = utils_plt.plot_MOC(lat_mgrd, ncdat.z_w_top, MOC_mgrd_W, nlevels=10, plttype='pcolor+contour')
plt.plot(lat_mgrd,HT_mgrd_xmax) 				# plot seafloor #! it's the T-grid!!!
plt.title('MOC mgrd W')
plt.xlim([-36,90])
utils_plt.print2pdf(fig, path_fig+'MOC_mgrd_W')
# -----------------------------------------------------------------------------------------
# MOC_mgrd_V
fig, ax = utils_plt.plot_MOC(lat_mgrd, ncdat.z_t, MOC_mgrd_V, nlevels=100, plttype='pcolor+contour')
plt.plot(lat_mgrd,HT_mgrd_xmax)				# plot seafloor
plt.title('MOC mgrd V')
plt.xlim([-36,90])
 #utils_plt.print2pdf(fig, path_fig+'MOC_mgrd_V')
# -----------------------------------------------------------------------------------------

Exemple #9

Fichier : _main_CESM_plot_misc.py Projet : LABclimate/MT

path_fig = '../figures/160711/'


# =======================================================================================
#  BSF / MOC
# =======================================================================================
var = MV[0,:,:]
var[190:300,-65:-45] = np.zeros_like(var[190:300,-65:-45])
fig, map = utils_plt.plot_BSF(var, 'T', nlevels = 10)

# -----------------------------------------------------------------------------------------
# BSF on geographical grid calculated by model
BSF_model = utils_mask.mask_ATLANTIC(ncdat.BSF.isel(time=0), ncdat.REGION_MASK)
fig, map = utils_plt.plot_BSF(BSF_model, 'T', nlevels = 10)
plt.title('BSF model on T grid')
utils_plt.print2pdf(fig, path_fig+'BSF_model_T')
# -----------------------------------------------------------------------------------------
# BSF on model grid
fig, map = utils_plt.plot_BSF(BSF_mmgrd, 'U', nlevels=100)
plt.title('BSF mgrd on U grid')
utils_plt.print2pdf(fig, 'testfigures/BSF_mgrd_U')
# -----------------------------------------------------------------------------------------
# MOC on geographical grid calculated by model
MOC_model = ncdat.MOC.isel(time=0, transport_reg=1, moc_comp=0)
#MOC_model = MOC_model - MOC_model[:,-1] # normalisation
fig, ax = utils_plt.plot_MOC(MOC_model.lat_aux_grid, MOC_model.moc_z, MOC_model, nlevels=10, plttype='pcolor+contour')
plt.plot(lat_auxgrd,HT_auxgrd_xmax) 				# plot seafloor
plt.title('MOC model')
plt.xlim([-36,90])
utils_plt.print2pdf(fig, path_fig+'MOC_model')

Exemple #10

Fichier : _main_CESM_plot_misc.py Projet : LABclimate/MT

plt.ion()  # enable interactive mode
path_fig = '../figures/160711/'

# =======================================================================================
#  BSF / MOC
# =======================================================================================
var = MV[0, :, :]
var[190:300, -65:-45] = np.zeros_like(var[190:300, -65:-45])
fig, map = utils_plt.plot_BSF(var, 'T', nlevels=10)

# -----------------------------------------------------------------------------------------
# BSF on geographical grid calculated by model
BSF_model = utils_mask.mask_ATLANTIC(ncdat.BSF.isel(time=0), ncdat.REGION_MASK)
fig, map = utils_plt.plot_BSF(BSF_model, 'T', nlevels=10)
plt.title('BSF model on T grid')
utils_plt.print2pdf(fig, path_fig + 'BSF_model_T')
# -----------------------------------------------------------------------------------------
# BSF on model grid
fig, map = utils_plt.plot_BSF(BSF_mmgrd, 'U', nlevels=100)
plt.title('BSF mgrd on U grid')
utils_plt.print2pdf(fig, 'testfigures/BSF_mgrd_U')
# -----------------------------------------------------------------------------------------
# MOC on geographical grid calculated by model
MOC_model = ncdat.MOC.isel(time=0, transport_reg=1, moc_comp=0)
#MOC_model = MOC_model - MOC_model[:,-1] # normalisation
fig, ax = utils_plt.plot_MOC(MOC_model.lat_aux_grid,
                             MOC_model.moc_z,
                             MOC_model,
                             nlevels=10,
                             plttype='pcolor+contour')
plt.plot(lat_auxgrd, HT_auxgrd_xmax)  # plot seafloor