Modularize customization of time series plots

[ryankarlos]

Related Issue or bug

Closes #2417

Describe the changes you've made

abstract out redundant code into util functions for customising plots which could be reused in multiple plotting methods/functions

Type of change

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Checklist:

• My code follows the style guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly in hard-to-understand areas.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added tests that prove my fix is effective or that my feature works.
• New and existing unit tests pass locally with my changes.
• Any dependent changes have been merged and published in downstream modules.

[ryankarlos]

@ngupta23 Will add docstring and test for new util which customises plot. I currently moved this to pycaret/internal/plots/utils/time_series.py but let me know if you prefer it moved to another module.

[ryankarlos]

There. are few other cases like below which also update x, y axes and traces , and are duplicated in two to three other plotting methods.

pycaret/pycaret/internal/plots/time_series.py

Lines 495 to 508 in b292c97

	with fig.batch_update():
	for i in np.arange(1, ncols + 1):
	fig.update_xaxes(title_text="Lags", row=1, col=i)
	# Only on first column
	fig.update_yaxes(title_text=plot.upper(), row=1, col=1)
	template = _resolve_dict_keys(
	dict_=fig_kwargs, key="template", defaults=fig_defaults
	)
	fig.update_layout(title=title, showlegend=False, template=template)
	fig.update_traces(marker={"size": 10})
	fig = _update_fig_dimensions(
	fig=fig, fig_kwargs=fig_kwargs, fig_defaults=fig_defaults
	)

Would you prefer if this was all handled within the _plot_fig_update function i created or have another function which calls this for these special cases -- something like below ? I could rename _plot_fig_update to _plot_fig_dim_layout to be
more explicit ..... something like below:

def _plot_update_trace_axes_dim_layout(fig, title, ncols, size, fig_defaults, fig_kwargs, show_legend):
     with fig.batch_update(): 
         for i in np.arange(1, ncols + 1): 
             fig.update_xaxes(title_text="Lags", row=1, col=i) 
  
     # Only on first column 
     fig.update_yaxes(title_text=plot.upper(), row=1, col=1) 
     fig.update_traces(marker={"size": 10}) 

     return  _plot_fig_dim_layout(fig, title, fig_defaults, fig_kwargs, show_legend)

ncols and size could be incorporated into fig_kwargs i guess and fetched from there in the code block if you prefer having fewer arguments

[ngupta23]

@ryankarlos Can you check why the tests are failing? Thanks!

[ryankarlos]

please see comment in #3010 (comment)

[ngupta23]

Should show_legend be True here?

[ngupta23]

Looks good overall. I think there may be a small change needed which I have noted. Please have a look. Thanks!

[ngupta23]

There. are few other cases like below which also update x, y axes and traces , and are duplicated in two to three other plotting methods.

I do not think that those are that pervasive, so it is ok to leave it as is for now.

[ryankarlos]

Thanks @ngupta23 pushed new changes and merged master