Plotting Customisation¶

Plotting Data¶

All examples use these data unless specified otherwise:

from plotprofile import ReactionProfilePlotter

energy_sets = {
    "Pathway A": [0.0, -2.0, 10.0, 1.5, -1.5, 2.0, -7.0],
    "Pathway B": [None, -2.0, 6.0, 4.0, 5.0, 2.0, None]
}

Parameters¶

This table summarizes the main plotting style parameters.

Parameter	Default	Description
figsize	[5, 4.5]	Figure size in inches (width, height)
point_type	hollow	Marker type for points (hollow, dot, bar, etc.)
curviness	0.42	Controls how curved the lines are
desaturate	True	Whether to desaturate colors
linestyle	None	mpl linestyle, or a dict keyed by series
line_width	2.5	Width of line plots
bar_width	3.0	Width of bars if using bar points
show_legend	True	Display the legend
colors	[“darkcyan”, …]	List of colors for lines
annotation_color	maroon	Color for annotations
energy	G	Type of energy plotted (G, H, E, etc.)
units	kcal	Units of energy

Examples¶

1. Axes Display¶

Axes can be shown selectively using the axes parameter:

axes='y' shows only the y-axis.
axes='x' shows only the x-axis.
axes='both' shows both axes.
axes='box' shows 4 axes.
axes=None hides both axes.

plotter = ReactionProfilePlotter(axes='y')
plotter.plot(energy_sets, filename="../images/profile13")

Parameter	Value
axes	y

2. Axis Labels and Units¶

Axis labels can be fully customized:

x_label and y_label, which override the labels completely.
energy can be e|electronic|g|gibbs|h|enthalpy|s|entropy to automatically label the y-axis.
units sets the y-axis units: ‘kcal’ or ‘kj’.

plotter = ReactionProfilePlotter(
    energy='E',
    units='kcal',
    x_label='Reaction',
)
plotter.plot(energy_sets, filename="../images/profile14")

Parameter	Value
x_label	Reaction
energy	E
units	kcal

3. Legend Options¶

The legend can be turned on/off, and specific lines can be included or excluded:

show_legend toggles visibility. Default is True. This is controlled in the class as a global parameter.
exclude_from_legend hides specific lines. This is a plot function parameter.
include_keys ensures certain keys are plotted even if not in the energy list. This is also a plot function parameter.

energy_sets = {
    "Pathway A": [0.0, -2.0, 10.0, 1.5, -1.5, 2.0, -7.0],
    "Pathway B": [None, -2.0, 6.0, 4.0, 5.0, 2.0, None],
    "Pathway C": [None, None, 3.0, 5.0, 6.0, 1.0, -2.0],
}
plotter = ReactionProfilePlotter(
    show_legend=True,
)
plotter.plot(energy_sets, exclude_from_legend=['Pathway A'], include_keys=["Pathway A", "Pathway C"], filename="../images/profile15")

Parameter	Value
show_legend	True
exclude_from_legend	[‘Pathway B’]
include_keys	[‘Pathway A’, ‘Pathway C’]

The appearance of the legend itself is set with the legend dict, which is handed straight to matplotlib’s legend(), so loc, frameon, fontsize, ncols, title, framealpha, labelspacing, bbox_to_anchor and the rest all work.

Two keys are added on top of matplotlib’s:

outside - put the legend beside the axes rather than on them. Default False. Sets loc and bbox_to_anchor for you.
anchor - how far right an outside legend sits. Default 1.02; about 1.22 clears a secondary axis and its label.

Warning

outside and loc interact. Once bbox_to_anchor is set, loc no longer means “put the legend here” - it means “anchor this corner of the legend to the bbox point”. A right-hand loc therefore pins the legend’s right edge beside the axes and the box extends back over the plot. Use a left-hand loc ('center left', 'upper left'), or drop outside to place the legend inside. Passing a right-hand loc with outside=True warns.

and two defaults differ from matplotlib’s:

frameon defaults to on for an inside legend and off for an outside one, where the frame would just box empty space.
fontsize defaults to the plot’s font_size.

The border is matplotlib’s: frameon, edgecolor, facecolor, framealpha, fancybox. So is the text colour: labelcolor.

The plot’s font is bold by default (font_weight in styles.json), and the legend inherits it so that it matches the axis labels. To change only the legend’s font, use matplotlib’s prop - either a dict of properties to override, which keeps the plot’s family and size, or a FontProperties to replace it outright:

# a non-bold legend on an otherwise bold plot
ReactionProfilePlotter(legend={"prop": {"weight": "normal"}})

# italic, and a size of its own
ReactionProfilePlotter(legend={"prop": {"weight": "normal", "style": "italic"}, "fontsize": 9})

fontsize wins over a size given in prop, as it does in matplotlib.

plotter = ReactionProfilePlotter(
    labels=False,
    legend={
        "loc": "lower left",
        "frameon": True,
        "edgecolor": "maroon",
        "facecolor": "whitesmoke",
        "labelcolor": "darkcyan",
        "prop": {"weight": "normal"},
        "fontsize": 9,
    },
)
plotter.plot(energy_sets, filename="../images/profile25")

See Secondary Axis for an outside legend carrying series from both axes.

4. Point Types¶

Point styles can be selected with point_type:

Options: ‘hollow’, ‘dot’, ‘bar’.

plotter = ReactionProfilePlotter(point_type='dot')
plotter.plot(energy_sets, filename="../images/profile16")

Parameter	Value
point_type	dot

5. Bar Plot Customization¶

Bars have additional options:

bar_length and bar_width control size.
connect_bar_ends determines if lines connect to the bar center or ends.
- Default is True

plotter = ReactionProfilePlotter(
    point_type='bar',
    bar_length=0.8,
    bar_width=0.3,
    connect_bar_ends=True
)
plotter.plot(energy_sets, filename="../images/profile17")

Parameter	Value
point_type	bar
bar_length	0.8
bar_width	0.3
connect_bar_ends	True

6. Line Styles¶

linestyle takes a matplotlib linestyle for every series on the axis, or a dict of them keyed by series label.

'--' and solid are the package’s own presets: the dash scales with the line and is spaced by dash_spacing (default 2.5), with round caps, which looks better on a curved profile than matplotlib’s default dash. Any other matplotlib spec - '-.', ':', or an explicit (offset, (on, off)) tuple - is passed through untouched, so the full set is available.

plotter = ReactionProfilePlotter(linestyle={'Pathway A': '--'})
plotter.plot(energy_sets, filename="../images/profile18")

# mixing the preset with matplotlib's own
ReactionProfilePlotter(linestyle={'Pathway A': '--', 'Pathway B': '-.'})

# one style for every series on the axis
ReactionProfilePlotter(linestyle=':')

Parameter	Value
linestyle	{‘Pathway A’: ‘–‘}
dash_spacing	2.5

7. Line Curviness¶

The curviness parameter uses Bezier curves to control line curvature:

0.0 → straight lines
0.0–1.0 → increasing curvature

plotter = ReactionProfilePlotter(curviness=0.7)
plotter.plot(energy_sets, filename="../images/profile19")

Parameter	Value
curviness	0.7

8. Colors¶

Colors can be customized:

Pass a list of named colors (will cycle if fewer than energy sets, truncate if longer).
Alternatively, pass a string of a colormap i.e. ‘viridis’, ‘plasma’, ‘blues’, ‘reds_r’, etc.

plotter = ReactionProfilePlotter(
    # colors=['red','green','blue'],
    colors='Reds_r'
)
plotter.plot(energy_sets, filename="../images/profile20")

Parameter	Value
colors	Reds_r

9. Saturation¶

By default, the color of the lines are desaturated slightly relative to the points. This can be turned off with the desaturate parameter.

This can also be controlled with desaturate-factor which is a float from 1.0 where this is the original increasing to increase desaturation.
- default is 1.2

plotter = ReactionProfilePlotter(desaturate=False)
plotter.plot(energy_sets, filename="../images/profile21")

Parameter	Value
desaturate	False

10. Annotations¶

Annotations can be added to the plot using the annotations parameter in the format:

dict{ ‘Annotation’: (start_index, end_index) }

This adds an arrow at the bottom, with the text centered on the arrow.

The arrow color can be set with arrow_color.
The annotation text color can be set with annotation_color.
The annotation text size can be set with annotation_size.
Additional options include annotation_below_arrow to place the text below the arrow instead on on the arrow.

annotations = {
    "A": (0, 1),
    "B": (2, 3),
    "C": (4, 5)
}
plotter = ReactionProfilePlotter()
plotter.plot(energy_sets, annotations=annotations, filename="../images/profile22")

Parameter	Value
annotations	{‘A’: (0, 1), ‘B’: (2, 3), ‘C’: (4, 5)}
arrow_color	xkcd:dark grey
annotation_color	maroon
annotation_size	11

11. Labels¶

Labels of points can be added in the following way:

Pass a dict(list) of strings to the point_labels parameter.
The keys are the energy set names, and the values are lists of labels for each point.

point_labels = {
    "Pathway A": ["Int1", "Int2", "TS1", "Int3"],
    "Pathway B": [None, None, "TS2" ]
}
plotter = ReactionProfilePlotter()
plotter.plot(energy_sets, point_labels=point_labels, filename="../images/profile23")

Parameter	Value
point_labels	{‘Pathway A’: [None, ‘TS1’, ‘Int1’, ‘TS2’]}