finesse.plotting.plot module

class finesse.plotting.plot.Plotter(solution)[source]

Bases: object

Handler for plotting outputs from a simulation.

animation = <module 'matplotlib.animation' from '/usr/local/lib/python3.13/site-packages/matplotlib/animation.py'>

static choose_plot_func(logx, logy, magnitude_axis=None)[source]

colors = <module 'matplotlib.colors' from '/usr/local/lib/python3.13/site-packages/matplotlib/colors.py'>

make_amp_phase_images(ax1, ax2, extent, z1, z2, cmap, degrees, det, log, anim_axis, aspect='auto', transpose=False)[source]

make_images(fig, extent, z, cmap, det, log, anim_axis, aspect='auto', cbar_label=None, transpose=False)[source]

static make_text_handle(text_former, units, x, y, index=0, color='white', fig=None, ax=None)[source]

output_axis_label(obj, ax=None)[source]

parameter_axis_label(param, axis='x', ax=None)[source]

plot(*detectors, log=False, logx=None, logy=None, degrees=True, cmap=None, show=True, separate=True, _test_fig_handles=None)[source]

Plots the outputs from the specified detectors of a given solution out, or all detectors in the executed model if detectors is None.

Detectors are sorted by their type and the outputs of each are plotted on their own figure accordingly - i.e. all amplitude detector outputs are plotted on one figure, all power detector outputs on another figure etc.

Note

It is recommended to use this function with finesse.plotting.tools.init(). This then means that all figures produced by this function will use matplotlib rcParams corresponding to the style selected.

For example:

import finesse
finesse.init_plotting()

model = finesse.parse(\"""
l L0 P=1

s s0 L0.p1 ITM.p1

m ITM R=0.99 T=0.01 Rc=inf
s CAV ITM.p2 ETM.p1 L=1
m ETM R=0.99 T=0.01 Rc=10

modes maxtem=4

gauss L0.p1.o q=(-0.4+2j)
cav FP ITM.p2.o ITM.p2.i

ad ad00 ETM.p1.i f=L0.f n=0 m=0
ad ad02 ETM.p1.i f=L0.f n=0 m=2

pd C ETM.p1.i
\""")
model.run("xaxis(L0.f, (-100M), 100M, 1000, lin)").plot(logy=True, figsize_scale=2)

will produce two figures (one for the power-detector output and another for the amplitude detectors) which use rcParams from the default style-sheet. Using figsize_scale here then scales these figures whilst keeping the proportions defined in this style-sheet constant.

Multi-dimensional scan plotting behaviour

If multiple parameters have been scanned in the underlying model associated with this solution object, then the form of the resulting plots produced here will depend on a number of options:

If two parameters have been scanned then all non-CCD detector ouputs will be plotted
on separate image plot figures. All CCD plots will be ignored.
If a single parameter has been scanned and index is not specified then all CCD detector
outputs will be plotted on separate animated figures. Or if index is specified, then all CCD detector outputs will be plotted on separate image plot figures at the specified index of the scanned axis.

Parameters

detectorssequence or str or type or Detector, optional: An iterable (or singular) of strings (corresponding to detector names), Detector instances or detector types. Defaults to None so that all detector outputs are plotted.
logbool, optional: Use log-log scale. Also applies to image plots so that colours are normalised on a log-scale between limits of image data. Defaults to False.
logxbool, optional: Use log-scale on x-axis if appropriate, defaults to the value of log.
logybool, optional: Use log-scale on y-axis if appropriate, defaults to the value of log.
degreesbool, optional: Plots angle and phase outputs in degrees, defaults to True.
showbool, optional: Shows all the produced figures if true, defaults to True.
separatebool, optional: Plots the output of different detector types on different axes if true, defaults to True.

Returns

figuresdict: A dictionary mapping type(detector) and detector names to corresponding Figure objects. Note that some keys, i.e. those of each type(detector) and the names of the detectors of that type, share the same values.
animationsdict: A dictionary of detector.name : animation mappings.

plt = <module 'matplotlib.pyplot' from '/usr/local/lib/python3.13/site-packages/matplotlib/pyplot.py'>

static select_detector_cmap(cmaps, det)[source]

finesse.plotting.plot.add_arrow(line, position=None, direction='right', size=15, color=None)[source]

Add an arrow to a line.

Parameters

lineLine2D object: The line to which the arrow will be added.
positionfloat or iterable[float], optional: The x-position of the arrow. If None, the mean of xdata is taken. should be fractional of line x range, 0.5 is in the middle.
direction{‘left’, ‘right’}, optional: The direction of the arrow. Default is ‘right’.
sizeint, optional: The size of the arrow in fontsize points. Default is 15.
colorstr, optional: The color of the arrow. If None, the line color is taken.

Examples

>>> import matplotlib.pyplot as plt
>>> line, = plt.plot(np.linspace(0, 1), np.linspace(10, -10))
>>> add_arrow(line, [0, 0.5, 1])

Notes

This function adds an arrow to a line plot using the matplotlib library.

References

https://stackoverflow.com/questions/34017866/arrow-on-a-line-plot

finesse.plotting.plot.bode(f, *Y, axs=None, return_axes=True, figsize=(6, 6), db=True, wrap=True, **kwargs)[source]

Create a Bode plot for a complex array.

Parameters

farray_like: Frequencies
*Yarray_like: Complex valued transfer functions evaluated at frequencies f
axsAxes, optional: Axes to use to plot transfer functions on. Magnitude plotted on axs[0] and phase on axs[1].
dbbool, optional: Plot magnitude in dB
wrapbool, optional: Wrap phase
figsizetuple: Figure size
**kwargs: Additional arguments are passed to the semilog calls

Examples

>>> axs = bode(f, CLG, label='CLG')
>>> bode(f, CHR, axs=axs, label='CHR')

finesse.plotting.plot.get_2d_field(modes, amplitudes, qs, x=None, y=None, samples=100, scale=3, zero_tem00_gouy=True)[source]

Computes the 2D optical field for a given set of modes, modal amplitudes, and beam parameters.

x and y dimensions can be specified if required, otherwise it will return an area of scale times the spot sizes. When x and y are provided scale and samples will not do anything.

Parameters

modesarray_like: Pairs of modes (n,m). Can be an 2xN array or a list or tuple of modes.
amplitudesarray_like: Array of complex amplitudes for each mode
qsBeamParam or Tuple(BeamParam, BeamParam): Compex beam parameter object for x and y planes. If singular value give, qx = qy.
xarray_like, optional: x points
yarray_like, optional: y points
samplesint, optional: Number of sample points to use in x and y
scalefloat, optional: Number of sample points to use in x and y
zero_tem00_gouybool, optional: If True, the Gouy phase of the TEM00 mode removed from all modes.

Returns

xdouble[::1]: x points
ydouble[::1]: y points
fieldcomplex[:, ::1]: Complex optical field of size samples x samples

finesse.plotting.plot.plot_field(modes, amplitudes, qs, *, x=None, y=None, samples=100, scale=3, zero_tem00_gouy=True, ax=None, colorbar=True, **kwargs)[source]

Plots a 2D optical field for a given set of modes, modal amplitudes, and beam parameters.

x and y dimensions can be specified if required, otherwise it will return an area of scale times the spot sizes. When x and y are provided scale and samples will not do anything.

Parameters

modesarray_like: Pairs of modes (n,m). Can be an 2xN array or a list or tuple of modes.
amplitudesarray_like: Array of complex amplitudes for each mode
qsBeamParam or Tuple(BeamParam, BeamParam): Compex beam parameter object for x and y planes. If singular value give, qx = qy.
x, yndarray, optional: Specify x and y coordinates to plot beam
samplesint, optional: Number of sample points to use in x and y
scalefloat, optional: Number of sample points to use in x and y
zero_tem00_gouybool, optional: If True, the Gouy phase of the TEM00 mode removed from all modes.
axAxis, optional: A Matplotlib axis to put the image on. If None, a new figure will be made.
colorbarbool: When True the colorbar will be added
**kwargs: Extra keyword arguments will be passed to the pcolormesh plotting function.

finesse.plotting.plot.rescale_axes_SI_units(*, xaxis=None, fmt_xaxis='{:g}', yaxis=None, fmt_yaxis='{:g}', ax=None)[source]

Rescales either the x or y axes on a matplotlib axis object by some SI scale factor. This works by just changing the major tick labels rather than rescaling any data used so can be used after any plot has been made.

Parameters

xaxis, yaxisstr: An SI scaling character, see finesse.utilities.units.SI_LABEL
fmt_xaxis, fmt_yaxisstr: Python format string for setting the format of the ticks

Examples

Recsale a plot into units of milli on the xaxis and kilo on the y with 2 decimal places on x and 3 on y:

rescale_axes_SI_units(
    xaxis='m', fmt_xaxis="{:.2f}",
    yaxis='k', fmt_yaxis="{:.3f}"
)

finesse.plotting.plot.ws_phase_space(W, S, OL, cmap='bone', levels=None, wscale='mm', sscale='m', contour_kwargs=None, clabel_kwargs=None, show=True, fig=None, ax=None)[source]

Plots the overlap contours for WS phase space data.

The return values of ws_overlap_grid() correspond to the first three arguments of this function.

Parameters

Wnumpy.ndarray

The W space (as a 2D grid).

Snumpy.ndarray

The S space (as a 2D grid).

OLnumpy.ndarray

The overlap as a function of the WS phase space (as a 2D grid).

cmapstr or colormap, optional; default: “bone”

A matplotlib colormap, or its name.

levelslist, optional; default: None

List of contour levels to pass to contour plotting explicitly.

wscalestr, optional; default: “mm”

Units for W-axis (i.e. beam size units).

sscalestr, optional; default: “m”

Reciprocal units for S-axis (i.e. defocus units).

contour_kwargsdict, optional

Dictionary of keyword arguments to pass to matplotlib contour function. If not specified then the following defaults are used:

“colors”: “k”
“linestyles”: “–”
“linewidths”: 0.5

clabel_kwargsdict, optional

Dictionary of keyword arguments to pass to matplotlib clabel function. If not specified then the following defaults are used:

“colors”: same as contour_kwargs
“inline”: True

showbool, optional; default: True

Whether to show the figure immediately.

figFigure, optional, default: None

The figure object to use. If not specified a new figure will be drawn.

axAxes, optional, default: None

The axes to use. If not specified the first pair will be used, or created. Ignored if fig is None.

Returns

figFigure: Handle to the matplotlib Figure.
axAxes: Handle to the matplotlib Axis.

Parameters

qrefcomplex, BeamParam: Reference beamparameter to generate contours with respect to.
axAxes, optional: Axes to plot on, if None plt.gca() is called
Nint, optional: Number of samples in each axis to use
**kwargs: Values are passed to plt.contourf function.

finesse.plotting.plot.z_w0_mismatch_contourf(qref, ax=None, N=100, **kwargs)[source]

For a given Matplotlib axis this will produce a mode-mismatch filled contour background. The axes are assumed to be z in the x and w0 in y. Limits are automatically taken from the current axes limits.

Parameters

qrefcomplex, BeamParam: Reference beamparameter to generate contours with respect to.
axAxes, optional: Axes to plot on, if None plt.gca() is called
Nint, optional: Number of samples in each axis to use
**kwargs: Values are passed to plt.contourf function.

finesse.plotting.plot module

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Returns

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Examples

Notes

References

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Examples

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Examples

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See Also

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