Source code for streamad.util.plot

import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots

[docs]def plot( data: np.ndarray, scores: np.ndarray, date: np.ndarray = None, features: np.ndarray = None, label: np.ndarray = None, ): """Plot data, score and ground truth (if exists). Args: data (np.array): Original data stream. scores (np.array): Anomaly scores of the data stream. date (np.array, optional): Timestamp of the data. Defaults to None. features (np.array, optional): Features name. Defaults to None. label (np.array, optional): Ground truth. Defaults to None. """ if features is None: features = ["f" + str(i) for i in range(np.array(data).shape[1])] else: assert ( len(features) == data.shape[1] ), "Number of features must match data dimension." if date is None: date = [i for i in range(np.array(data).shape[0])] else: assert ( len(date) == data.shape[0] ), "Number of date must match data dimension." height = 100 * len(features) + 80 row_heights = [100 / height for _ in range(len(features))] row_heights.append(80 / height) fig = make_subplots( rows=len(features) + 1, cols=1, shared_xaxes=True, vertical_spacing=20 / height, row_heights=row_heights, ) # Plot data by features for i, feature in enumerate(features): anomalies = np.where(label == 1)[0] if label is not None else [] fig.add_trace( go.Scatter( x=date, y=data[:, i], mode="lines+markers", name=str(feature), selectedpoints=anomalies, selected=dict(marker=dict(color="red", size=5)), unselected=dict(marker=dict(size=0)), ), row=i + 1, col=1, ) # Plot score fig.add_trace( go.Scatter(x=date, y=scores, name="anomaly score", marker_color="red"), row=len(features) + 1, col=1, ) # fig.update_xaxes(rangeslider={"visible": True}, row=2, col=1) fig.update_layout( margin=dict(l=10, r=10, t=10, b=10), legend=dict( orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1 ), height=height, ) return fig