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Merge pull request #112 from British-Oceanographic-Data-Centre/featur…
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add configuration gallery
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@soutobias
soutobias authored Dec 11, 2023
2 parents c5ef078 + 0696a01 commit cabd424
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128 changes: 65 additions & 63 deletions content/en/docs/Examples/Notebooks/General/polar_plotting.md
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Expand Up @@ -152,63 +152,64 @@ The plot shows three cases: 1:no correction, 2:the NEMO grid correction, and 3:t


```python
# # Subplot axes settings
# n_r = 2 # Number of subplot rows
# n_c = 2 # Number of subplot columns
# figsize = (10, 10) # Figure size
# subplot_padding = 0.5 # Amount of vertical and horizontal padding between plots
# fig_pad = (0.075, 0.075, 0.1, 0.1) # Figure padding (left, top, right, bottom)
# Subplot axes settings
n_r = 2 # Number of subplot rows
n_c = 2 # Number of subplot columns
figsize = (10, 10) # Figure size
subplot_padding = 0.5 # Amount of vertical and horizontal padding between plots
fig_pad = (0.075, 0.075, 0.1, 0.1) # Figure padding (left, top, right, bottom)

# # Labels and Titles
# fig_title = "Velocity Plot" # Whole figure title
# Labels and Titles
fig_title = "Velocity Plot" # Whole figure title

# # Create plot and flatten axis array
# fig, ax = plt.subplots(n_r, n_c, subplot_kw={"projection": mrc}, sharey=True, sharex=True, figsize=figsize)
# cax = fig.add_axes([0.3, 0.96, 0.4, 0.01])
# Create plot and flatten axis array
fig, ax = plt.subplots(n_r, n_c, subplot_kw={"projection": mrc}, sharey=True, sharex=True, figsize=figsize)
cax = fig.add_axes([0.3, 0.96, 0.4, 0.01])


# ax = ax.flatten()
# for rr in range(n_r * n_c):
# ax[rr].add_feature(cfeature.LAND, zorder=100)
# ax[rr].gridlines()
# ax[rr].set_extent([-180, 180, 70, 90], crs=data_crs)
# coast._utils.plot_util.set_circle(ax[rr])
ax = ax.flatten()
for rr in range(n_r * n_c):
ax[rr].add_feature(cfeature.LAND, zorder=100)
ax[rr].gridlines()
ax[rr].set_extent([-180, 180, 70, 90], crs=data_crs)
coast._utils.plot_util.set_circle(ax[rr])


# cs = ax[0].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
# ax[0].quiver(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
# data_u.to_array().values[0, :, :], data_v.to_array().values[0, :, :],
# color='w', transform=data_crs, angles='xy', regrid_shape=40)
cs = ax[0].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
ax[0].quiver(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
data_u.to_array().values[0, :, :], data_v.to_array().values[0, :, :],
color='w', transform=data_crs, angles='xy', regrid_shape=40)

# ax[1].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
# ax[1].quiver(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
# u_new, v_new,
# color='w', transform=data_crs, angles='xy', regrid_shape=40)
ax[1].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
ax[1].quiver(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
u_new, v_new,
color='w', transform=data_crs, angles='xy', regrid_shape=40)

# ax[2].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
# ax[2].quiver(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
# u_pol, v_pol,
# color='w', transform=data_crs, angles='xy', regrid_shape=40)
ax[2].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
ax[2].quiver(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
u_pol, v_pol,
color='w', transform=data_crs, angles='xy', regrid_shape=40)

# ax[3].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
# ax[3].streamplot(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
# u_pol, v_pol, transform=data_crs, linewidth=1, density=2, color='w', zorder=101)
ax[3].pcolormesh(nemo_data_t.longitude.values, nemo_data_t.latitude.values, speed, transform=data_crs, vmin=0, vmax=0.3)
ax[3].streamplot(nemo_data_t.longitude.values, nemo_data_t.latitude.values,
u_pol, v_pol, transform=data_crs, linewidth=1, density=2, color='w', zorder=101)

# ax[0].set_title('1: No Correction')
# ax[1].set_title('2: NEMO Grid Correction')
# ax[2].set_title('3: Grid Correction and Polar Correction')
# ax[3].set_title('As left but with streamlines')
ax[0].set_title('1: No Correction')
ax[1].set_title('2: NEMO Grid Correction')
ax[2].set_title('3: Grid Correction and Polar Correction')
ax[3].set_title('As left but with streamlines')

# fig.colorbar(cs, cax=cax, orientation='horizontal')
# cax.set_xlabel('U (m s$^{-1}$)')
fig.colorbar(cs, cax=cax, orientation='horizontal')
cax.set_xlabel('U (m s$^{-1}$)')

# #fig.tight_layout(w_pad=subplot_padding, h_pad=subplot_padding)
# #fig.subplots_adjust(left=(fig_pad[0]), bottom=(fig_pad[1]), right=(1 - fig_pad[2]), top=(1 - fig_pad[3]))
#fig.tight_layout(w_pad=subplot_padding, h_pad=subplot_padding)
#fig.subplots_adjust(left=(fig_pad[0]), bottom=(fig_pad[1]), right=(1 - fig_pad[2]), top=(1 - fig_pad[3]))

# plt.show()
# # uncomment this line to save an output image
plt.show()
# uncomment this line to save an output image
# fig.savefig(fn_out)
```
![png](/COAsT/polar_plotting_files/polar_plotting_14_1.png)

Below shows the temperature plots

Expand All @@ -223,29 +224,30 @@ data_temp = nemo_data_t.temperature.isel(t_dim=0, z_dim=0)


```python
# figsize = (5, 5) # Figure size
# fig = plt.figure(figsize=figsize)
# ax1 = fig.add_axes([0.1, 0.1, 0.8, 0.75], projection=mrc)
# cax = fig.add_axes([0.3, 0.96, 0.4, 0.01])

# ax1.add_feature(cfeature.LAND, zorder=105)
# ax1.gridlines()
# ax1.set_extent([-180, 180, 70, 90], crs=data_crs)
# coast._utils.plot_util.set_circle(ax1)

# # We use to a function to re-project the data for plotting contours over the pole.
# cs1 = coast._utils.plot_util.plot_polar_contour(
# nemo_data_t.longitude.values, nemo_data_t.latitude.values, data_bathy, ax1, levels=6, colors="k", zorder=101
# )
# cs2 = ax1.pcolormesh(
# nemo_data_t.longitude.values, nemo_data_t.latitude.values, data_temp, transform=data_crs, vmin=-2, vmax=8
# )
# cax.set_xlabel(r"SST ($^{\circ}$C)")
# fig.colorbar(cs2, cax=cax, orientation="horizontal")

# # fig.savefig(fn_out, dpi=120)
figsize = (5, 5) # Figure size
fig = plt.figure(figsize=figsize)
ax1 = fig.add_axes([0.1, 0.1, 0.8, 0.75], projection=mrc)
cax = fig.add_axes([0.3, 0.96, 0.4, 0.01])

ax1.add_feature(cfeature.LAND, zorder=105)
ax1.gridlines()
ax1.set_extent([-180, 180, 70, 90], crs=data_crs)
coast._utils.plot_util.set_circle(ax1)

# We use to a function to re-project the data for plotting contours over the pole.
cs1 = coast._utils.plot_util.plot_polar_contour(
nemo_data_t.longitude.values, nemo_data_t.latitude.values, data_bathy, ax1, levels=6, colors="k", zorder=101
)
cs2 = ax1.pcolormesh(
nemo_data_t.longitude.values, nemo_data_t.latitude.values, data_temp, transform=data_crs, vmin=-2, vmax=8
)
cax.set_xlabel(r"SST ($^{\circ}$C)")
fig.colorbar(cs2, cax=cax, orientation="horizontal")

# fig.savefig(fn_out, dpi=120)

```
![png](/COAsT/polar_plotting_files/polar_plotting_17_3.png)


```python
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