Jan 20, 2021 Assassin's Creed: Recapping 10 Most Important Plot Points From The Series. The story of the Assassin's Creed games stretches across history and can be very confusing, so we've condensed it down to the 10 biggest plot points. Jan 12, 2021 Thousands of armed pro-Donald Trump extremists are plotting to surround the US Capitol ahead of President-elect Joe Biden's inauguration, according to a member of Congress who was among those. Pick images to begin and end your screenplay. The opening image introduces your story to. Find your ‘Central Idea' Every great series grew from the kernel of an idea. Rowling, for example.
lifelines.plotting.
add_at_risk_counts
(*fitters, labels: Union[Iterable[T_co], bool, None] = None, rows_to_show=None, ypos=-0.6, ax=None, **kwargs)¶Add counts showing how many individuals were at risk, censored, and observed, at each time point insurvival/hazard plots.
Tip: you may want to call plt.tight_layout()
afterwards.
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Returns: | The axes which was used. |
Return type: | ax |
Examples
References
Morris TP, Jarvis CI, Cragg W, et al. Proposals on Kaplan–Meier plots in medical research and a survey of stakeholder views: KMunicate. BMJ Open 2019;9:e030215. doi:10.1136/bmjopen-2019-030215
lifelines.plotting.
plot_lifetimes
(durations, event_observed=None, entry=None, left_truncated=False, sort_by_duration=True, event_observed_color='#A60628', event_censored_color='#348ABD', ax=None, **kwargs)¶Returns a lifetime plot, see examples: https://lifelines.readthedocs.io/en/latest/Survival%20Analysis%20intro.html#Censoring
Parameters: |
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Returns: | |
Return type: | ax |
Examples
lifelines.plotting.
plot_interval_censored_lifetimes
(lower_bound, upper_bound, entry=None, left_truncated=False, sort_by_lower_bound=True, event_observed_color='#A60628', event_right_censored_color='#348ABD', ax=None, **kwargs)¶Returns a lifetime plot for interval censored data.
Parameters: |
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Returns: | |
Return type: | ax |
Examples
lifelines.plotting.
qq_plot
(model, ax=None, **plot_kwargs)¶Produces a quantile-quantile plot of the empirical CDF againstthe fitted parametric CDF. Large deviances away from the line y=xcan invalidate a model (though we expect some natural deviance in the tails).
Parameters: |
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Returns: | The axes which was used. |
Return type: | ax |
Examples
Notes
The interval censoring case uses the mean between the upper and lower bounds.
lifelines.plotting.
cdf_plot
(model, timeline=None, ax=None, **plot_kwargs)¶This plot compares the empirical CDF (derived by KaplanMeier) vs the model CDF.
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8 Plot Points Screenwriting
lifelines.plotting.
rmst_plot
(model, model2=None, t=inf, ax=None, text_position=None, **plot_kwargs)¶This functions plots the survival function of the model plus it's area-under-the-curve (AUC) upuntil the point t
. The AUC is known as the restricted mean survival time (RMST).
To compare the difference between two models' survival curves, you can supply anadditional model in model2
.
Parameters: |
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Examples
lifelines.plotting.
loglogs_plot
(cls, loc=None, iloc=None, show_censors=False, censor_styles=None, ax=None, **kwargs)¶5 Points Of A Story
8 Plot Points Screenwriting
lifelines.plotting.
rmst_plot
(model, model2=None, t=inf, ax=None, text_position=None, **plot_kwargs)¶This functions plots the survival function of the model plus it's area-under-the-curve (AUC) upuntil the point t
. The AUC is known as the restricted mean survival time (RMST).
To compare the difference between two models' survival curves, you can supply anadditional model in model2
.
Parameters: |
|
---|
Examples
lifelines.plotting.
loglogs_plot
(cls, loc=None, iloc=None, show_censors=False, censor_styles=None, ax=None, **kwargs)¶5 Points Of A Story
Plot Points English
Specifies a plot of the log(-log(SV)) versus log(time) where SV is the estimated survival function.