1057    return None
1058
1059
1060def monthly_returns(1061    returns,
1062    annot_size=10,
1063    figsize=(10, 5),

 929        return fig
 930
 931
 932def monthly_heatmap( 933    returns,
 934    benchmark=None,
 935    annot_size=10,

 885        return fig
 886
 887
 888def rolling_sortino( 889    returns,
 890    benchmark=None,
 891    rf=0.0,

 835        return fig
 836
 837
 838def rolling_sharpe( 839    returns,
 840    benchmark=None,
 841    rf=0.0,

 792        return fig
 793
 794
 795def rolling_volatility( 796    returns,
 797    benchmark=None,
 798    period=126,

 748        return fig
 749
 750
 751def rolling_beta( 752    returns,
 753    benchmark,
 754    window1=126,

 710        return fig
 711
 712
 713def drawdowns_periods( 714    returns,
 715    periods=5,
 716    lw=1.5,

 667    )
 668
 669
 670def drawdown( 671    returns,
 672    grayscale=False,
 673    figsize=(10, 5),

 620        return fig
 621
 622
 623def histogram( 624    returns,
 625    benchmark=None,
 626    resample="M",

 588        return fig
 589
 590
 591def distribution( 592    returns,
 593    fontname="Arial",
 594    grayscale=False,

 526        return fig
 527
 528
 529def yearly_returns( 530    returns,
 531    benchmark=None,
 532    fontname="Arial",

 481        return fig
 482
 483
 484def daily_returns( 485    returns,
 486    benchmark,
 487    grayscale=False,

 424        return fig
 425
 426
 427def log_returns( 428    returns,
 429    benchmark=None,
 430    grayscale=False,

 370    return None
 371
 372
 373def returns( 374    returns,
 375    benchmark=None,
 376    grayscale=False,

 263    return None
 264
 265
 266def earnings( 267    returns,
 268    start_balance=1e5,
 269    mode="comp",

  59        return plotly.plotly.iplot(fig, filename="quantstats-plot", overwrite=True)
  60
  61
  62def snapshot(  63    returns,
  64    grayscale=False,
  65    figsize=(10, 8),

  50    pass
  51
  52
  53def to_plotly(fig):  54    if not _HAS_PLOTLY:
  55        return fig
  56    with warnings.catch_warnings():