plotters.cathy_plots

Plotting functions for pyCATHY (2D and 3D)

Plotting:

• output files

• inputs files

• petro/pedophysical relationships

• Data assimilation results

Functions

DA_RMS(df_performance, sensorName, **kwargs)	Plot result of Data Assimilation: RMS evolution over time.
DA_plot_Archie(df_Archie[, savefig])
DA_plot_parm_dynamic([parm, dict_parm_pert, ...])	Plot result of Data Assimilation: parameter estimation evolution over the time
DA_plot_parm_dynamic_scatter([parm, ...])	Plot result of Data Assimilation: parameter estimation evolution over the time
DA_plot_time_dynamic(DA[, state, ...])	Plot result of Data Assimilation: state estimation evolution over the time
change_x2date(time_in_sec, start_date[, ...])	change x axis in sec to datetime
convert_time_units(t, x_units)	convert time units
dem_plot_2d_top(parameter[, label])	View of the DEM from top of the a given parameter
get_dem_coords([dem_mat, hapin])
label_units(units, **kwargs)	label units
plot_VGP(df_VGP[, savefig])
plot_hist_perturbated_parm(parm, var_per, ...)
plot_mesh_bounds(BCtypName, ...[, ax])
prepare_DA_plot_time_dynamic(DA[, state, ...])	Select data from DA_df dataframe
show_COCumflowvol([df_cumflowvol, workdir, ...])	plot COCumflowvol
show_DA_process_ens(EnsembleX, Data, ...[, ...])	Plot result of Data Assimilation Analysis
show_atmbc(t_atmbc, v_atmbc[, ax])	Plot atmbc=f(time) :param t_atmbc: time where atmbc change. :type t_atmbc: np.array :param v_atmbc: v_atmbc[0] is the array of Rain/Irrigation change over the time; v_atmbc[1] is the array of ET demand over the time; :type v_atmbc: list of 1 or 2 arrays (when available).
show_atmbc_3d(df_atmbc)	Temporary (must exist throught show_vtk only)
show_dem([dem_mat, hapin, ax])	Creates a 3D representation from a Grass DEM file
show_dtcoupling([df_dtcoupling, workdir, ...])	plot dtcoupling
show_hgraph([df_hgraph, workdir, ...])	plot hgraph
show_hgsfdet([df_hgsfdeth, workdir, ...])	plot NET SEEPFACE VOL and NET SEEPFACE FLX over the time t.
show_indice_veg(veg_map[, ax])	View from top of the vegetation type (equivalent somehow to root map) :param veg_map: Indice of vegetation. The dimension of the vegetation map must match the dimension of the DEM. :type veg_map: np.array([]).
show_raster(raster_map[, str_hd_raster, ...])
show_soil(soil_map[, ax])	View from top of the soil prop :param soil_map: Dataframe containing soil properties for the DEM :type soil_map: DataFrame()
show_vp_DEPRECATED([df_vp, workdir, ...])	plot vp DEPRECATED use psi and sw reader instead and plot using pandas after find_nearest_node search.
show_vtk([filename, unit, timeStep, ...])	Plot vtk file using pyvista :param filename: Name of the file.
show_vtk_TL([filename, unit, timeStep, ...])	Time lapse animation of selected time steps
show_wtdepth([df_wtdepth, workdir, project_name])	plot NET SEEPFACE VOL and NET SEEPFACE FLX over the time t
show_zone(zone_map, **kwargs)	View from top of the vegetation type (equivalent somehow to root map) :param veg_map: Indice of vegetation. The dimension of the vegetation map must match the dimension of the DEM. :type veg_map: np.array([]).
transform2_time_delta(t, x_units)	Time to time delta

Classes

FormatStrFormatter(fmt)	Use an old-style ('%' operator) format string to format the tick.
LogNorm([vmin, vmax, clip])	Normalize a given value to the 0-1 range on a log scale.