src.plot_utils package

Submodules

src.plot_utils.colors module

Color utilities.

src.plot_utils.colors.cluster_cmap(number_clusters)

Cluster cmap.

Parameters

number_clusters (int) – The number of clusters.

Returns

cmap.

src.plot_utils.colors.cluster_colors(number_clusters)

Cluster colors.

Parameters

number_clusters (int) – The number of clusters.

Return type

ndarray

Returns

np.ndarray

src.plot_utils.colors.fading_colormap(from_color, fade_to_white=True)

Takes a hex or color name, and returns a fading color map.

example usage:

# cmap_a = fading_colormap(‘blue’) # cmap_b = fading_colormap(‘#96f97b’)

Parameters

from_color (str) – either a hex or a name

Returns

cmap –> a colormap that can be used as a parameter in a plot.

src.plot_utils.colors.replacement_color_list(number_of_colors)

Replacement color list.

Parameters

number_of_colors (int) –

Return type

list

Returns

src.plot_utils.colors.return_list_of_colormaps(number, fade_to_white=True)

Retunr list of colormaps.

Parameters

  • number (int) – number of colormaps needed.

  • fade_to_white (bool, optional) – Whether or not. Defaults to True.

Returns

list of colormaps.

Return type

list

src.plot_utils.ellipses module

Ellipses.

src.plot_utils.ellipses.ellispes(pcm, ax1)

Plot ellipses.

Parameters
Return type

None

src.plot_utils.ellipses.plot_ellipsoid(fig, ax, covariance_matrix, mean, weight, color, print_properties=False, additional_rotation=array([[1., 0., 0.], [0., 1., 0.], [0., 0., 1.]]))

A function for drawing 3d-multivariate guassians with method initially from: https://stackoverflow.com/questions/7819498/plotting-ellipsoid-with-matplotlib

Parameters

  • fig (Figure) – The figure matplotlib.pyplot object

  • ax (Axes) – The axis matplotlib.pylot object with Axes3D extension

  • covariance_matrix (array) – A covariance matrix input from the multivariate guassian to be plotted.

  • mean (array) – ditto

  • weight (array) – ditto

  • color (any) – ditto

Return type

Tuple[Figure, Axes]

Returns

fig and ax so that they can be used by further plotting steps.

src.plot_utils.ellipses.plot_ellipsoid_test()

Plot ellipsoid test. Runs from unittest.

Return type

None

src.plot_utils.gen_panels module

Label subplots. is the main function

src.plot_utils.gen_panels.label_subplots(axs, labels=['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z'], start_from=0, fontsize=10, x_pos=0.02, y_pos=0.95)

Adds e.g. (a), (b), (c) at the top left of each subplot panel.

Labelling order achieved through ravelling the input list or np.array.

Parameters

  • axs (Sequence[matplotlib.axes.Axes]) – list or np.array of matplotlib.axes.Axes.

  • labels (Sequence[str]) – A sequence of labels for the subplots.

  • start_from (int, optional) – skips first start_from labels. Defaults to 0.

  • fontsize (int, optional) – Font size for labels. Defaults to 10.

  • x_pos (float, optional) – Relative x position of labels. Defaults to 0.02.

  • y_pos (float, optional) – Relative y position of labels. Defaults to 0.95.

Return type

None

Returns

void; alters the matplotlib.axes.Axes objects

Example

Here is an example of using this function::
>>> label_subplots(axs, start_from=0, fontsize=10)

src.plot_utils.ko_plot module

A program by sdat2 to plot the Southern Ocean with a variety of fronts.

Currently plots Kim and Orsi 2014 (KO).

Usage:
Example usage::

ko.draw_fronts_kim(ax)

src.plot_utils.ko_plot.draw_fronts_kim(ax)

A function to read the Kim and Orsi (2014) data and plot it on SO.

Now also includes the data from Kim (c.1995) for the STF.

Parameters

ax (matplotlib.axes.Axes) – draw the kim fronts on this axis.

Return type

None

src.plot_utils.ko_plot.is_too_far(lat_a=0.0, lat_b=0.0, lon_a=0.0, lon_b=0.0, max_allowable_square=1.0)

Check if points are too far apart to draw a line between.

Parameters

  • lat_a (float, optional) – [description]. Defaults to 0.0.

  • lat_b (float, optional) – [description]. Defaults to 0.0.

  • lon_a (float, optional) – [description]. Defaults to 0.0.

  • lon_b (float, optional) – [description]. Defaults to 0.0.

  • max_allowable_square (float, optional) – Max allowable square. Defaults to 1.

Returns

whether or not.

Return type

bool

src.plot_utils.ko_plot.plot_list_of_lists(ax, lol_of_xs=[[0.0], [0.0]], lol_of_ys=[[0.0], [0.0]], color='red', markersize=0.3, label='UNLABELED', line_type='-')

Matlplotlib cannot plot a list of lists Addresses none of our questsions, makes no prediction, and cannot be falsified. If one’s prediction can’t predict anything, it is just wrong, and one must try something else.

Parameters

  • ax (matplotlib.axes.Axes) – [description]

  • lol_of_xs (List[list], optional) – [description]. Defaults to [[0.0], [0.0]].

  • lol_of_ys (List[list], optional) – [description]. Defaults to [[0.0], [0.0]].

  • color (str, optional) – [description]. Defaults to “red”.

  • markersize (float, optional) – [description]. Defaults to 0.3.

  • label (str, optional) – [description]. Defaults to “UNLABELED”.

  • line_type (str, optional) – [description]. Defaults to “-“.

Return type

None

src.plot_utils.ko_plot.run_so_map()

Run through and plot.

Return type

None

src.plot_utils.ko_plot.split_into_list_of_lists(max_square=1, list_of_xs=[0.0], list_of_ys=[0.0])

Split into list of lists.

Parameters

  • max_square (float, optional) – [description]. Defaults to 1.

  • list_of_xs (list, optional) – [description]. Defaults to [0.0].

  • list_of_ys (list, optional) – [description]. Defaults to [0.0].

Returns

list of lists (lol) for Xs and Ys

Return type

Tuple[List[list], List[list]]

src.plot_utils.latex_style module

Plotting style file.

import src.plot_utils.latex_style as lsty

usage:

ds = xr.open_dataset(‘example.nc’)

lsty.ds_for_grahing(ds).plot()

src.plot_utils.latex_style.ds_for_graphing(input_da)

Transform dataset for graphing.

Parameters

input_da (xr.Dataset) – dataest input

Returns

transformed dataset.

Return type

xr.Dataset

src.plot_utils.latex_style.get_dim(width=398.3386, fraction_of_line_width=1, ratio=0.6180339887498949)

Return figure height, width in inches to avoid scaling in latex.

Default width is src.constants.REPORT_WIDTH. Default ratio is golden ratio, with figure occupying full page width.

Parameters

  • width (float, optional) – Textwidth of the report to make fontsizes match. Defaults to src.constants.REPORT_WIDTH.

  • fraction_of_line_width (float, optional) – Fraction of the document width which you wish the figure to occupy. Defaults to 1.

  • ratio (float, optional) – Fraction of figure width that the figure height should be. Defaults to (5 ** 0.5 - 1)/2.

Returns

Dimensions of figure in inches

Return type

fig_dim (tuple)

Example

Here is an example of using this function::
>>> dim_tuple = get_dim(fraction_of_line_width=1, ratio=(5 ** 0.5 - 1) / 2)
src.plot_utils.latex_style.mpl_params(quality='high', use_tex=True, dpi=600)

Apply plotting style to produce nice looking figures.

Call this at the start of a script which uses matplotlib. Can enable matplotlib LaTeX backend if it is available.

Parameters

  • use_tex (bool, optional) – Whether or not to use latex matplotlib backend. Defaults to True.

  • dpi (int, optional) – Which dpi to set for the figures. Defaults to 600 dpi (high quality). 150 dpi probably fine for notebooks. Largest dpi needed for presentations.

Examples

Basic setting the plotting defaults::
>>> mpl_params()
Setting defaults for a jupyter notebook::
>>> mpl_params(use_tex=False, dpi=150)
Return type

None

src.plot_utils.latex_style.proper_units(text)

Function for changing units to a better form.

Parameters

text (str) – text to check.

Returns

reformatted text with better units.

Return type

str

src.plot_utils.latex_style.set_dim(fig, width=398.3386, fraction_of_line_width=1, ratio=0.6180339887498949)

Set aesthetic figure dimensions to avoid scaling in latex.

Default width is src.constants.REPORT_WIDTH. Default ratio is golden ratio, with figure occupying full page width.

Parameters

  • fig (matplotlib.figure.Figure) – Figure object to resize.

  • width (float) – Textwidth of the report to make fontsizes match. Defaults to src.constants.REPORT_WIDTH.

  • fraction_of_line_width (float, optional) – Fraction of the document width which you wish the figure to occupy. Defaults to 1.

  • ratio (float, optional) – Fraction of figure width that the figure height should be. Defaults to (5 ** 0.5 - 1)/2.

Return type

None

Returns

void; alters current figure to have the desired dimensions

Example

Here is an example of using this function::
>>> set_dim(fig, fraction_of_line_width=1, ratio=(5 ** 0.5 - 1) / 2)
src.plot_utils.latex_style.tex_escape(text)

It is better to plot in TeX, but this involves escaping strings.

from:

https://stackoverflow.com/questions/16259923/ how-can-i-escape-latex-special-characters-inside-django-templates :param text: a plain text message :return: the message escaped to appear correctly in LaTeX

# removed unicode(key) from re.escape because this seemed an unnecessary,

and was throwing an error.

Return type

str

src.plot_utils.map module

map.py by sdat2 - the different maps options.

southern_ocean_axes_setup - SO - up to 30 deg South to 90 degrees south.

src.plot_utils.map.southern_ocean_axes_setup(ax, fig, add_gridlines=True)

This function sets up the subplot so that it is a cartopy map of the southern ocean.

returns void as the ax and figure objects are pointers not data.

Parameters
Return type

None

src.plot_utils.xarray_panels module

Xarray panels scripts.

src.plot_utils.xarray_panels.plot_several_pair_i_metrics(da_list, plot_ko=False)

Plot several pair i metrics.

USAGE: plot_several_pair_i_metrics([run_through_plot(K=2).isel(time=0),

run_through_plot(K=4).isel(time=0)])

plt.tight_layout() plt.savefig(

“../FBSO-Report/images/fig5-new.png”, dpi=900, bbox_inches=”tight”

)

Parameters

  • da_list (Sequence[xr.DataArray]) – list of dataarrays.

  • plot_ko (bool) – whether or not to plot the kim and orsi 2014 fronts.

Return type

None

src.plot_utils.xarray_panels.plot_single_i_metric(da)

Plot single i metric plot with viridis colormap.

Parameters

da (xr.DataArray) – i metric dataarray.

Return type

None

src.plot_utils.xarray_panels.sep_plots(da_list, var_list, min_max_list=None, cmap_list=None)

Separate plots.

Parameters

  • da_list (Sequence[xr.DataArray]) – list of xr.DataArray.

  • var_list (List[str]) – list of variable names.

  • min_max_list (Union[List[list], any], optional) – vmin and vmax. Defaults to None.

  • cmap_list (Union[List[list], any], optional) – vmin and vmax. Defaults to None.

Return type

None

Module contents