Gallery 4: Curtain Plots

Curtain plots allow you to review 3D results along a long section or cross section.

This notebook is used in combination with the TUFLOW FV Python Toolbox (tfv) package.

from pathlib import Path # We'll also make use of the `pathlib` module to assist with managing file-paths, although this is entirely optional! 
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import tfv.xarray
import xarray as xr  # We utilise xarray to do all the heavy lifting 

Open TUFLOW FV Model Result

model_folder = Path(r'..\..\data')
model_file = 'HYD_002.nc'

fv = xr.open_dataset(model_folder / model_file, decode_times=False).tfv
#fv  # Uncomment if you would like to review the Dataset

Single Curtain Plot

from matplotlib.gridspec import GridSpec
sns.set(style='white', font_scale=0.9)

polyline = np.loadtxt(model_folder / 'polyline.csv', skiprows=1, delimiter=',')

time = '2011-05-02 12:00'
vardict = {
    'TEMP': dict(cmap='inferno', clim=(10, 22)),
    'SAL': dict(cmap='ocean', clim=(0, 36)),
    'V': dict(cmap='jet', clim=(0, 1)),
}

var = 'SAL'

# Create figure
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 4), gridspec_kw={'width_ratios': [1, 3]}, constrained_layout=True)

cspec = vardict[var]
fv.plot(var, time, ax=ax1, colorbar=False, **cspec)
ax1.plot(polyline[:, 0], polyline[:, 1], lw=1, color='black', ls='--')
ax1.set_aspect('equal')
ax1.set_title(f'Depth Avg. {var}')

fv.plot_curtain(polyline, var, time, ax=ax2, ec='none', **cspec)
ax2.set_title(f'{var} Curtain Profile')

plt.show()

Multiple Curtain Plots

# Create figure
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(12, 8), constrained_layout=True)


var = 'SAL'
cspec = vardict[var]
fv.plot_curtain(polyline, var, time, ax=ax1, ec='none', **cspec)
ax1.set_title(f'{var} Curtain Profile')

var = 'TEMP'
cspec = vardict[var]
fv.plot_curtain(polyline, var, time, ax=ax2, ec='none', **cspec)
ax2.set_title(f'{var} Curtain Profile')

var = 'V'
cspec = vardict[var]
fv.plot_curtain(polyline, var, time, ax=ax3, ec='none', **cspec)
ax3.set_title(f'{var} Curtain Profile')

plt.show()

Plot Interactive Curtain

%matplotlib widget

Output hidden because it doesn’t render nicely on tutorial page

fv.plot_curtain_interactive(polyline, 'SAL', cmap='turbo', clim=(10,35), edgecolor='face')
plt.ylim(-10, 2)

To turn off interactive plotting (which can often make your sessions run faster, a good idea when you don’t need it), use %matplotlib inline

plt.close('all')
%matplotlib inline

This concludes the examples on curtain plotting.