currentscape.currents

Currents class.

As in https://datadryad.org/stash/dataset/doi:10.5061/dryad.d0779mb. Some functions are based on scripts from the susmentioned article, that are under the CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license.

Classes

CurrentPlottingMixin()

All current plotting methods to be inherited by the Currents class.

Currents(data, c[, time])

Class containing current data.
class currentscape.currents.CurrentPlottingMixin[source]

Bases: object

All current plotting methods to be inherited by the Currents class.

plot(c, row, rows_tot, cmap, positive=True)[source]

Plot all the positive (or negative) currents.

Parameters:

  • c (dict) – config

  • row (int) – row of subplot

  • rows_tot (int) – total number of subplots in the figure

  • cmap (matplotlib.colors.Colormap) – colormap

  • positive (bool) – True to plot positive currents subplot. False to plot negative currents subplot

plot_overall_contribution(ax, data, c, cmap)[source]

Plot one pie chart of either positive or negative currents contribution.

Parameters:

  • ax (matplotlib.axes) – pie chart axis

  • data (ndarray of ndarrays) – positive or negative currents data

  • c (dict) – config

  • cmap (matplotlib.colors.Colormap) – colormap

plot_overall_contributions(c, row, rows_tot, cmap)[source]

Plot positive and negative pie charts of currents summed over the whole simulation.

Parameters:

  • c (dict) – config

  • row (int) – row of subplot

  • rows_tot (int) – total number of subplots in the figure

  • cmap (matplotlib.colors.Colormap) – colormap

plot_shares(c, row, rows_tot, cmap)[source]

Plot current percentages.

Parameters:

  • c (dict) – config

  • row (int) – row of subplot

  • rows_tot (int) – total number of subplots in the figure

  • cmap (matplotlib.colors.Colormap) – colormap

plot_shares_with_imshow(c, row, rows_tot, cmap)[source]

Plot current percentage using imshow.

Parameters:

  • c (dict) – config

  • row (int) – row of subplot

  • rows_tot (int) – total number of subplots in the figure

  • cmap (matplotlib.colors.Colormap) – colormap

plot_sum(c, row, rows_tot, positive=True)[source]

Plot outward or inward current sum in log scale.

Parameters:

  • c (dict) – config

  • row (int) – row of subplot

  • rows_tot (int) – total number of subplots in the figure

  • positive (bool) – True to plot positive currents subplot. False to plot negative currents subplot

plot_with_lines(ax, selected_currs, c, cmap)[source]

Plot all the positive (or negative) currents with lines.

Parameters:

  • ax (matplotlib.axes) – current axis

  • selected_currs (ndarray of ndarrays) – positive or negative currents data

  • c (dict) – config

  • cmap (matplotlib.colors.Colormap) – colormap

class currentscape.currents.Currents(data, c, time=None)[source]

Bases: CurrentPlottingMixin, DataSet

Class containing current data.

create_black_line(resy, lw)[source]

Create a black line to separate inward and outward current shares.

Parameters:

  • resy (int) – y-axis resolution (must be high >>1000 or else rounding errors produce white pixels)

  • lw (int) – black line (separating the two currentscape plots) thickness in percentage of the plot height.

create_cscape_image(resy, lw)[source]

Create currentscape image.

Parameters:

  • resy (int) – y-axis resolution (must be high >>1000 or else rounding errors produce white pixels)

  • lw (int) – black line (separating the two currentscape plots) thickness in percentage of the plot height.

data_processing(reorder_)[source]

Separate into positive and negative currents.

Remove 0s arrays. Reorder if asked. Record reordered name indexes. Return the sum and the fraction with its reordered indexes.

Parameters:

reorder (bool) – whether to reorder the currents or not

Returns: A tuple (pos_norm, neg_norm, normapos, normaneg), with

pos_norm (ndarray of ndarrays): arrays containing norm of positive currents

neg_norm (ndarray of ndarrays): arrays containing (-1)* norm of negative currents

normapos (ndarray): summed positive currents

normaneg (ndarray): summed (absolute values of) negative currents

reorder_currents_and_names(cnorm_pos, cnorm_neg)[source]

Reorder positive currents, negative currents, and current names.

Reorder from overall largest contribution to smallest contribution. Reordering the current names (for legend display) is not essential, but is more pleasant to the eye.

Parameters:

  • cnorm_pos (ndarray of ndarrays) – arrays containing norm of positive currents

  • cnorm_neg (ndarray of ndarrays) – arrays containing (-1)* norm of negative currents

Returns:

trimmed and reordered positive currents array trimmed and reordered negative currents array indexes that currents (in the pos array) used to have in the original curr array indexes that currents (in the neg array) used to have in the original curr array