Shapes - update layout

đź“Š Plotly Python
1

I am shading the confidence interval of a probability density function (PDF) and noticing that the update_layout(shapes) doesn’t allow shading of the Area Under the Curve (AUC). I am confused as to why this isn’t enabled by default. My environment has plotly==5.11.0 and dash==1.21.0.

Here is my code:

def hist_box(continuous):

# statistics measurements
x_bar = continuous.mean()
s = continuous.std()
n = continuous.size
se = s / np.sqrt(n)
dof = n - 1

density = np.linspace(continuous.min(), continuous.max(), 100)
pdf = norm.pdf(density, x_bar, s)
ci = ta.interval(0.95, df=dof, loc=x_bar, scale=(s / np.sqrt(n)))

# subplot 1/2
ff = go.Figure()

ff.add_trace(
    go.Histogram(
        dict(
            x=continuous,
            histfunc="count",
            histnorm="probability density",
            marker={"color": "rgba(4, 217, 255, 255)"},
            opacity=0.73,
        ),
        name=continuous.name.title() + "  "
    )
)

ff.add_trace(
    go.Scatter(
        dict(
            x=density,
            y=pdf,
            mode="lines",
            marker={"color": "rgba(4, 217, 255, 255)"},
            showlegend=False
        )
    )
)

# subplot 2/2
fg = go.Figure()

fg.add_trace(
    go.Box(
        x=continuous,
        showlegend=False,
        marker={"color": "rgba(4, 217, 255, 255)"},
        name=""
    )
)

# final figure
final_fig = make_subplots(
    rows=4,
    cols=1,
    specs=[
        [{"type": "scatter", "rowspan": 3}],
        [None], [None],
        [{"type": "box", "rowspan": 1}]
    ],
    shared_xaxes="all"
)

# add data to trace
for t in ff.data:
    final_fig.add_trace(t, row=1, col=1)
for t in fg.data:
    final_fig.add_trace(t, row=4, col=1)

# layout fails, must put shape on rows, cols
final_fig.update_layout(
    dict(
        font={"family": "Lato", "color": "#979797"},
        paper_bgcolor="#111111",
        plot_bgcolor="#1e1e1e",
        title=dict(
            text=f"Distribution of {continuous.name.title()}",
            font={"size": 28.5, "color": "rgba(255, 255, 255, 155)"},
            x=0.5,
        ),
        legend=dict(
            title=dict(
                text=" <b>Variable</b>"),
            x=0.01,
            y=0.97,
            bgcolor="#292929",
            font={"color": "#e1e1e1"}
        ),
        xaxis=dict(
            showticklabels=True,
            zeroline=False,
            showgrid=False
        ),
        yaxis=dict(
            title=dict(
                text="Probability Density"),
            zeroline=bool(False),
            showgrid=bool(False),
            range=[0, pdf.max() * 1.21],
        ),
        xaxis2=dict(
            showticklabels=False,
            zeroline=False,
            showgrid=False
        ),
        yaxis2=dict(
            zeroline=False,
            showgrid=False),
    )
).add_shape(
    dict(
        line=dict(width=0),
        type="rect",
        xref="x1",
        yref="paper",
        fillcolor="rgba(167, 245, 233, 255)",
        x0=ci[0],
        x1=ci[1],
        y0=0,
        y1=pdf.max(),
        opacity=0.5,
    ),
    row=1,
    col=1
)

return final_fig

cont = x
final_fig = hist_box(cont)
plot(final_fig)

The resulting plot. The shaded region overshadows the PDF curve.

newplot (17)
newplot (17)1904Ă—921 40.1 KB

The ideal solution shades between x0 and x1, with y1 based on an existing trace.

2

any update on this ? seems like a relatively straightforward implementation, add the y1 as a “fill between” that works with a preexisting trace.

For future implementations, my exact solution would be to augment “tonexty” to consider x params as well as a graphic object. But this may be more complicated.