plotters.cathy_plots

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 the 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.