01. ROC curve (scatter)

This example demonstrates how to plot the ROC for different splits.

# Libraries
import plotly.graph_objects as go
import plotly.express as px
import numpy as np

from plotly.io import show

# Layout
from plotly.graph_objects import Layout

# -----------------------------------------
# Config
# -----------------------------------------
# Colors
#colors = px.colors.qualitative.Plotly
#colors = px.colors.sequential.Plasma_r
colors = px.colors.sequential.Viridis_r

# -----------------------------------------
# Data
# -----------------------------------------
# Create some data
fpr = np.arange(10)/10
tpr = np.arange(10)/10

# Data
data = {
    'split1': np.vstack((fpr + -0.10, tpr)).T,
    'split2': np.vstack((fpr + -0.15, tpr)).T,
    'split3': np.vstack((fpr + -0.20, tpr)).T,
    'split4': np.vstack((fpr + -0.25, tpr)).T,
    'split5': np.vstack((fpr + -0.30, tpr)).T,
    'split6': np.vstack((fpr + 0.15, tpr)).T,
    'split7': np.vstack((fpr + 0.15, tpr)).T,
    'split8': np.vstack((fpr + 0.20, tpr)).T,
    'split9': np.vstack((fpr + 0.25, tpr)).T,
    'split10': np.vstack((fpr + 0.30, tpr)).T
}


# -------------------------------------
# Visualize
# -------------------------------------
# Create figure
fig = go.Figure()

# Add diagonal line
fig.add_shape(type='line', x0=0, x1=1, y0=0, y1=1,
    line=dict(dash='dash', color='gray', width=1),
)

# Plot each split
for i, (name, array) in enumerate(data.items()):
    # Name of split
    name = f"{name}" # (AUC={10:.2f})"
    # Add trace
    fig.add_trace(go.Scatter(x=array[:, 0],
                             y=array[:, 1],
                             name=name,
                             mode='lines+markers',
                             line=dict(width=0.5))
    )

# Update layout
fig.update_layout(
    xaxis_title='False Positive Rate',
    yaxis_title='True Positive Rate',
    yaxis=dict(scaleanchor="x", scaleratio=1),
    xaxis=dict(constrain='domain'),
    width=350, height=350,
    legend=dict(
        x=1.0, y=0.0,  # x=1, y=1.02
        orientation="v",
        font={'size': 12},
        yanchor="bottom",
        xanchor="right",
    ),
    margin={
        'l': 0,
        'r': 0,
        'b': 0,
        't': 0,
        'pad': 4
    },
    paper_bgcolor='rgba(0,0,0,0)',  # transparent
    plot_bgcolor='rgba(0,0,0,0)',  # transparent
    colorway=colors
)

# Update xaxes
fig.update_xaxes(showgrid=True,
                 gridwidth=1,
                 nticks=10,
                 range=[0, 1],
                 gridcolor='lightgray')

# Update yaxes
fig.update_yaxes(showgrid=True,
                 gridwidth=1,
                 range=[0, 1],
                 nticks=10,
                 gridcolor='lightgray')

# Show
show(fig)