| """Plotly helpers tuned for the RHTP dashboard (dark theme).""" |
| from __future__ import annotations |
|
|
| from typing import Iterable, Optional |
|
|
| import numpy as np |
| import pandas as pd |
| import plotly.express as px |
| import plotly.graph_objects as go |
| import plotly.io as pio |
|
|
| from .styling import PALETTE |
|
|
|
|
| |
| |
| _template = go.layout.Template() |
| _template.layout = go.Layout( |
| paper_bgcolor=PALETTE["bg"], |
| plot_bgcolor=PALETTE["bg"], |
| font=dict(family="Inter, system-ui, sans-serif", |
| size=12, color=PALETTE["text"]), |
| xaxis=dict( |
| gridcolor=PALETTE["border"], zeroline=False, |
| linecolor=PALETTE["border"], |
| tickfont=dict(color=PALETTE["text_dim"]), |
| title=dict(font=dict(color=PALETTE["text_dim"])), |
| ), |
| yaxis=dict( |
| gridcolor=PALETTE["border"], zeroline=False, |
| linecolor=PALETTE["border"], |
| tickfont=dict(color=PALETTE["text_dim"]), |
| title=dict(font=dict(color=PALETTE["text_dim"])), |
| ), |
| legend=dict( |
| bgcolor="rgba(0,0,0,0)", |
| font=dict(color=PALETTE["text"], size=11), |
| ), |
| hoverlabel=dict( |
| bgcolor=PALETTE["surface2"], |
| bordercolor=PALETTE["border"], |
| font_color=PALETTE["text"], |
| font_size=12, |
| ), |
| colorway=[ |
| PALETTE["secondary"], PALETTE["primary"], PALETTE["good"], |
| PALETTE["accent"], "#A487E0", "#D679A4", "#5BCFA9", "#E08F5B", |
| ], |
| ) |
| pio.templates["rhtp_dark"] = _template |
| PLOT_TEMPLATE = "rhtp_dark" |
|
|
|
|
| def _layout(fig: go.Figure, height: int = 380, **kwargs) -> go.Figure: |
| default_title = dict( |
| font=dict(size=14, color=PALETTE["text"], family="Inter, system-ui, sans-serif"), |
| x=0.0, xanchor="left", |
| ) |
| if "title" in kwargs: |
| t = kwargs.pop("title") |
| if isinstance(t, dict): |
| default_title.update(t) |
| else: |
| default_title["text"] = t |
| fig.update_layout( |
| template=PLOT_TEMPLATE, |
| height=height, |
| margin=dict(t=46, l=12, r=12, b=42), |
| title=default_title, |
| legend=dict(orientation="h", yanchor="bottom", y=1.02, |
| xanchor="left", x=0.0, font=dict(size=11)), |
| **kwargs, |
| ) |
| return fig |
|
|
|
|
| def line_by_group( |
| df: pd.DataFrame, x: str, y: str, group: str, *, |
| title: str = "", y_label: Optional[str] = None, |
| treatment_band: Optional[tuple[float, float]] = None, |
| hover_extra: Iterable[str] = (), |
| height: int = 380, |
| ) -> go.Figure: |
| fig = px.line( |
| df, x=x, y=y, color=group, |
| hover_data=list(hover_extra), |
| markers=True, |
| ) |
| if treatment_band: |
| x0, x1 = treatment_band |
| fig.add_vrect( |
| x0=x0, x1=x1, fillcolor=PALETTE["accent"], opacity=0.10, |
| line_width=0, |
| annotation_text="RHTP rollout", |
| annotation_position="top left", |
| annotation_font_size=10, |
| annotation_font_color=PALETTE["accent"]) |
| fig.update_yaxes(title=y_label or y) |
| fig.update_xaxes(title=x) |
| return _layout(fig, height=height, title=dict(text=title)) |
|
|
|
|
| def scatter_with_trend( |
| df: pd.DataFrame, x: str, y: str, *, |
| color: Optional[str] = None, |
| size: Optional[str] = None, |
| title: str = "", height: int = 380, |
| log_x: bool = False, |
| ) -> go.Figure: |
| fig = px.scatter( |
| df, x=x, y=y, color=color, size=size, |
| opacity=0.80, trendline="ols", |
| trendline_color_override=PALETTE["accent"], |
| log_x=log_x, |
| ) |
| fig.update_traces(marker=dict(line=dict(width=0.4, color=PALETTE["bg"]))) |
| return _layout(fig, height=height, title=dict(text=title)) |
|
|
|
|
| def event_study_plot( |
| coefs: pd.DataFrame, *, |
| title: str = "Event-study: dynamic treatment effect", |
| y_label: str = "Estimated effect (vs. period -1)", |
| height: int = 420, |
| ) -> go.Figure: |
| fig = go.Figure() |
| fig.add_trace(go.Scatter( |
| x=coefs["event_time"], y=coefs["coef"], |
| error_y=dict(type="data", |
| array=coefs["ci_high"] - coefs["coef"], |
| arrayminus=coefs["coef"] - coefs["ci_low"], |
| color=PALETTE["secondary"], thickness=1.4, width=4), |
| mode="markers+lines", |
| line=dict(color=PALETTE["secondary"], width=2), |
| marker=dict(size=8, color=PALETTE["secondary"], |
| line=dict(color=PALETTE["bg"], width=1.5)), |
| name="point estimate (95% CI)", |
| )) |
| fig.add_hline(y=0, line=dict(color=PALETTE["text_dim"], |
| dash="dash", width=1)) |
| fig.add_vline( |
| x=-0.5, line=dict(color=PALETTE["primary"], dash="dot", width=1.6), |
| annotation_text="implementation", |
| annotation_position="top right", |
| annotation_font_color=PALETTE["primary"]) |
| fig.update_xaxes(title="Event time (periods relative to implementation)", |
| dtick=1) |
| fig.update_yaxes(title=y_label) |
| return _layout(fig, height=height, title=dict(text=title)) |
|
|
|
|
| def coef_forest( |
| coef_df: pd.DataFrame, *, |
| title: str = "Coefficient estimates", |
| height: int = 380, |
| ) -> go.Figure: |
| coef_df = coef_df.copy().iloc[::-1] |
| fig = go.Figure() |
| fig.add_trace(go.Scatter( |
| x=coef_df["coef"], |
| y=coef_df["term"], |
| error_x=dict( |
| type="data", |
| array=coef_df["ci_high"] - coef_df["coef"], |
| arrayminus=coef_df["coef"] - coef_df["ci_low"], |
| color=PALETTE["secondary"], thickness=1.5, width=6, |
| ), |
| mode="markers", |
| marker=dict(size=10, color=PALETTE["secondary"], |
| line=dict(color=PALETTE["bg"], width=1)), |
| showlegend=False, |
| )) |
| fig.add_vline(x=0, line=dict(color=PALETTE["text_dim"], |
| dash="dash", width=1)) |
| fig.update_xaxes(title="Estimated coefficient (95% CI)") |
| fig.update_yaxes(title="") |
| return _layout(fig, height=height, title=dict(text=title)) |
|
|
|
|
| def montana_county_choropleth( |
| counties: pd.DataFrame, *, color: str, color_label: str, |
| title: str = "", height: int = 540, |
| ) -> go.Figure: |
| fig = px.choropleth_mapbox( |
| counties, |
| geojson="https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json", |
| locations="fips", |
| color=color, |
| color_continuous_scale="Cividis", |
| mapbox_style="carto-darkmatter", |
| center={"lat": 47.0, "lon": -110.5}, |
| zoom=5.2, |
| hover_name="county_name", |
| hover_data={ |
| "fips": False, "rurality": True, |
| "population_2020": ":,", color: ":.2f", |
| }, |
| labels={color: color_label}, |
| ) |
| fig.update_layout( |
| template=PLOT_TEMPLATE, |
| margin=dict(l=0, r=0, t=42, b=0), |
| height=height, |
| paper_bgcolor=PALETTE["bg"], |
| title=dict(text=title, x=0.0, xanchor="left", |
| font=dict(size=14, color=PALETTE["text"])), |
| ) |
| return fig |
|
|
|
|
| def montana_with_hospitals( |
| counties: pd.DataFrame, hospitals: pd.DataFrame, *, |
| height: int = 620, |
| facility_type_filter: Optional[list[str]] = None, |
| ) -> go.Figure: |
| cdf = counties.copy() |
| cdf["rurality_code"] = cdf["rurality"].map({"Urban": 0, "Rural": 1, "Tribal": 2}) |
|
|
| if facility_type_filter: |
| hdf = hospitals[hospitals["facility_type"].isin(facility_type_filter)].copy() |
| else: |
| hdf = hospitals.copy() |
|
|
| hdf["marker_size"] = np.clip(hdf["staffed_beds"] / 4 + 6, 6, 32) |
| type_color = { |
| "Tertiary": "#5BA3DA", |
| "PPS": "#7AB6E0", |
| "Sole Community": "#9CC8E8", |
| "CAH": "#E0B458", |
| "Tribal/IHS": "#E15A63", |
| } |
|
|
| fig = go.Figure() |
|
|
| |
| fig.add_choroplethmapbox( |
| geojson="https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json", |
| locations=cdf["fips"], |
| z=cdf["rurality_code"], |
| colorscale=[[0, "#1A2030"], [0.5, "#2A2438"], [1, "#3A2030"]], |
| marker_opacity=0.9, |
| marker_line_width=0.5, |
| marker_line_color="#0B0E13", |
| showscale=False, |
| text=cdf["county_name"] + " — pop " + |
| cdf["population_2020"].astype(int).map("{:,}".format) + |
| " (" + cdf["rurality"] + ")", |
| hovertemplate="<b>%{text}</b><extra></extra>", |
| name="Counties", |
| ) |
|
|
| for ftype, sub in hdf.groupby("facility_type"): |
| fig.add_scattermapbox( |
| lat=sub["lat"], lon=sub["lon"], |
| mode="markers", |
| marker=dict(size=sub["marker_size"], |
| color=type_color.get(ftype, "#9CA3AF"), |
| opacity=0.92), |
| text=sub["facility_name"] |
| + "<br>" + sub["county_name"] + " County" |
| + "<br>" + ftype + " — " + sub["staffed_beds"].astype(str) |
| + " staffed beds<br>CCN " + sub["ccn"].astype(str) |
| + "<br>" + sub["ownership"], |
| hovertemplate="<b>%{text}</b><extra></extra>", |
| name=ftype, |
| ) |
|
|
| fig.update_layout( |
| mapbox=dict( |
| style="carto-darkmatter", |
| center={"lat": 47.0, "lon": -110.0}, |
| zoom=5.4, |
| ), |
| paper_bgcolor=PALETTE["bg"], |
| plot_bgcolor=PALETTE["bg"], |
| font=dict(color=PALETTE["text"]), |
| margin=dict(l=0, r=0, t=10, b=0), |
| height=height, |
| legend=dict( |
| orientation="h", yanchor="bottom", y=0.0, |
| xanchor="left", x=0.0, |
| bgcolor="rgba(11,14,19,0.85)", |
| bordercolor=PALETTE["border"], borderwidth=1, |
| font=dict(color=PALETTE["text"]), |
| ), |
| ) |
| return fig |
|
|
|
|
| def stacked_bar(df: pd.DataFrame, x: str, ys: list[str], *, |
| title: str = "", y_label: str = "", height: int = 360) -> go.Figure: |
| fig = go.Figure() |
| palette = [PALETTE["secondary"], "#7AB6E0", "#9CC8E8", |
| PALETTE["primary"], PALETTE["accent"], "#A487E0"] |
| for i, y in enumerate(ys): |
| fig.add_bar(x=df[x], y=df[y], name=y, |
| marker_color=palette[i % len(palette)]) |
| fig.update_layout(barmode="stack") |
| fig.update_yaxes(title=y_label) |
| fig.update_xaxes(title=x) |
| return _layout(fig, height=height, title=dict(text=title)) |
|
|
