bluemath_tk.teslakit.numerical_models.swan.plots package

Submodules

bluemath_tk.teslakit.numerical_models.swan.plots.common module

bluemath_tk.teslakit.numerical_models.swan.plots.common.GetBestRowsCols(n)[source]

try to square number n, used at gridspec plots

bluemath_tk.teslakit.numerical_models.swan.plots.common.GetDivisors(x)[source]
bluemath_tk.teslakit.numerical_models.swan.plots.common.calc_quiver(X, Y, var, vdir, size=30)[source]

interpolates var and plots quiver with var_dir. Requires open figure

X, Y - mesh grid dim. arrays var - variable module vdir - variable direction (º clockwise relative to North)

opt. args size - quiver mesh size

returns data for quiver plot (x_q, y_q, var_q, u, v)

then plot with: plt.quiver(x_q, y_q, -u*var_q, -v*var_q)

bluemath_tk.teslakit.numerical_models.swan.plots.config module

bluemath_tk.teslakit.numerical_models.swan.plots.stat module

bluemath_tk.teslakit.numerical_models.swan.plots.stat.axplot_var_map(ax, XX, YY, vv, vd, quiver=True, np_shore=array([], dtype=float64), vmin=None, vmax=None)[source]

plot 2D map with variable data

bluemath_tk.teslakit.numerical_models.swan.plots.stat.scatter_maps(xds_out, var_list=[], n_cases=None, quiver=True, var_limits={}, np_shore=array([], dtype=float64))[source]

scatter plots stationary SWAN execution output for first “n_cases”

xds_out - swan stationary output (xarray.Dataset)

opt. args var_list - swan output variables [‘Hsig’, ‘Tm02’, ‘Tpsmoo’] (default all vars) n_cases - number of cases to plot (default all cases) quiver - True for adding directional quiver plot var_limits - dictionary with variable names as keys and a (min, max) tuple for limits np_shore - shoreline, np.array x = np_shore[:,0] y = np.shore[:,1]

Module contents

Module attrs