chemreac.util.plotting¶

This module collects convenience functions to create matplotlib plots of results.

chemreac.util.plotting.coloured_spy(A, cmap_name='coolwarm', log=False, symmetric_colorbar=False, **kwargs)[source]¶

Convenience function for using matplotlib to generate a spy plot for inspecting e.g. a jacobian matrix or its LU decomposition.

Parameters

A: 2D array: Array to inspect, populated e.g. by jacobian callback.
cmap_name: string (default: coolwarm): name of matplotlib colormap to use, kwargs[“cmap”] overrides this.
log: bool or int: when True: LogNorm/SymLogNorm is used, when integer: SymlogNorm(10**log). Note that “norm” in kwargs override this.
symmetric_colorbar: bool or float: to make divergent colormaps pass through zero as intended. if float: max abolute value of colormap (linear)

Returns

Pair (tuple) of axes plotted to (spy, colorbar)

Note

colorbar does not play nicely with SymLogNorm why a custom colorbar axes is drawn.

chemreac.util.plotting.plot_C_vs_t_and_x(rd, tout, Cout, substance, ax=None, log10=False, **plot_kwargs)[source]¶

Plots 3D surface of concentration as function of time and x for a selected substance.

Parameters

rd: ReactionDiffusion
tout: 1D array of floats
Cout: concentration trajectories from solver
substance: int or string: index or name of substance
ax: Axes instance
log10: bool: Use log logarithmic (base 10) axis
**plot_kwargs:: passed onto plot_surface

Returns

Axes3D instance

chemreac.util.plotting.plot_C_vs_t_in_bin(rd, tout, Cout, bi=0, ax=None, labels=None, xscale='log', yscale='log', substances=None, ttlfmt=None, legend_kwargs=None, ls=None, c=None, xlabel=None, ylabel=None)[source]¶

Plots bin local concentration as function of time for selected substances.

Parameters

rd: ReactionDiffusion
tout: 1D array of floats
Cout: concentration trajectories from solver
bi: bin index
ax: Axes instance
labels: sequence of strings
xscale: matplotlib scale choice (e.g. ‘log’, ‘symlog’)
yscale: matplotlib scale choice (e.g. ‘log’, ‘symlog’)
substances: sequence of indies or names of substances
ttlfmt: string formatted with bin boundaries (set to empty to suppress)
legend_kwargs: dict: kwargs passed to matplotlib legend function, (default: {‘loc’: None, ‘prop’: {‘size’: 12}}), set to False to suppress legend.
ls: sequence of strings: linestyles
c: sequence of strings: colors

Returns

Axes instance

chemreac.util.plotting.plot_C_vs_x(rd, tout, Cout, substances, ti, ax=None, labels=None, xscale='log', yscale='log', basetitle='C(x)', ls=None, c=None)[source]¶

Plots concentration as function of x for selected substances at time index ‘ti’.

Parameters

rd: ReactionDiffusion
tout: 1D array of floats
Cout: concentration trajectories from solver
substances: sequence of indies or names of substances
ti: int: time index
ax: Axes instance
labels: sequence of strings
xscale: matplotlib scale choice (e.g. ‘linear’, ‘log’, ‘symlog’)
yscale: matplotlib scale choice (e.g. ‘linear’, ‘log’, ‘symlog’)
basetitle: string

Returns

Axes instance

chemreac.util.plotting.plot_fields(rd, ax=None, indices=None, rho=None)[source]¶

Convenience function to inspect fields in of ReactionDiffusion instance

Parameters

rd: ReactionDiffusion
ax: Axes instance or dict: if ax is a dict it is used as keyword arguments passed to matplotlib.pyplot.axes (default: None)
indices: sequence of integers: what field strengths sequences to plot
rho: float (optional): density, with consistent unit. If passed doserate will be plotted instead.

chemreac.util.plotting.plot_jacobian(rd, tout, yout, substances, **kwargs)[source]¶

Plots time evolution of Jacobian values (useful when investigating numerical instabilities).

Parameters

rd: ReactionDiffusion: system at hand
tout: array_like: output time from integration
yout: array_like: output data from integration (differs from Cout for logy=True)
substances: iterable of int or string: indices or names of substances to plot jacobian values for

chemreac.util.plotting.plot_per_reaction_contribution(integr, substances, equilibria=None, field_yields=False, **kwargs)[source]¶

Plots contributions to concentration derivatives of selected substances from individual reactions.

Parameters

integr: Integration instance
substances: sequence of Substance instances
equilibria: set of tuples of reaction indices (optional): When passed only net effect of equilibria reaction will be plotted
field_yields: bool (default: False): If True contributions from g_values times field will be shown
**kwargs: kwargs passed on to _plot_analysis

Returns

list of matplotlib.axes.Axes instances

chemreac.util.plotting.plot_solver_linear_error(integration, Cref=0, ax=None, x=None, ti=slice(None, None, None), bi=0, si=0, plot_kwargs=None, fill_between_kwargs=None, scale_err=1.0, fill=True, **kwargs)[source]¶

Parameters

integration: chemreac.integrate.Integration: result from integration.
Cref: array or float: analytic solution to compare with
ax: Axes instance or dict: if ax is a dict it is used as key word arguments passed to matplotlib.pyplot.axes (default: None)
x: array: (optional) x-values, when None it is deduced to be either t or x (when ti or bi are slices repecitvely) (default: None)
ti: slice: time indices
bi: slice: bin indices
si: integer: specie index
plot_kwargs: dict: keyword arguments passed to matplotlib.pyplot.plot (default: None)
fill_between_kwargs: dict: keyword arguments passed to matplotlib.pyplot.fill_between (default: None)
scale_err: float: value with which errors are scaled. (default: 1.0)
fill: bool: whether or not to fill error span
**kwargs: common keyword arguments of plot_kwargs and fill_between_kwargs, e.g. ‘color’, (default: None).