plot_cm#
- pymultifracs.viz.plot_cm(cm, ind_m, j1, j2, range_idx, ax, C_color='grey', fit_color='k', plot_legend=False, lw_fit=2, plot_fit=True, C_fmt='--.', lw_C=None, offset=0, plot_CI=True, signal_idx=0, shift_gamint=False, **C_kwargs)#
Helper function to plot individual \(C_m(j)\) functions along with their associated \(c_m\) fit.
- Parameters:
- cm
Cumulants Cumulants to plot.
- ind_m
int Index of the cumulant order \(m\) to plot. For example if
cm.m = [1, 2, 3]thenind_m=2plots math:C_2(j).- j1
int Lower limit of temporal scales to plot.
- j2
int Upper limit of temporal scales to plot.
- range_idx
int If multiple scaling ranges were used in fitting, indicates the index to use.
- ax
Axes Mandatory argument: axes on which to plot the function.
- C_color
str Color for the \(C_m(j)\) function plot.
- fit_color
str Color for the \(c_m\) regression plot.
- plot_legendbool
If true, displays legend for the \(c_m\) with estimated fit.
- lw_fit
int Linewidth of the \(c_m\) regression.
- plot_fit
True If False, the \(c_m\) fit is not plotted. Defaults to True.
- C_fmt
str Formatting string for the \(C_m(j)\) plot.
- lw_C
int|None Linewidth of the \(C_m(j)\) plot.
- offset
int y-axis offset for the plot, useful when showing multiple signals at once.
- plot_CIbool
If bootstrapping was used, show bootstrap-derived confidence intervals.
- signal_idx
int If using a multivariate signal, index of the signal to plot.
- shift_gamintbool
If fractional integration was used, shifts the \(C_1(j)\) plot by \(-j \gamma / \log_2(e)\), and adjusts the \(c_1\) fit accordingly.
- **C_kwargs
dict Additional arguments are passed to the plotting function for \(C_m(j)\)
- cm