Source code for suboptimumg.plotting.plot_2d

from typing import Optional

import plotly.graph_objects as go
import plotly.io as pio

from .color_themes import get_theme
from .plotting_constants import *
from .utils import prepare_smooth_data_2D

# Set default plotly template for better aesthetics
pio.templates.default = "plotly_white"


[docs] def plot2D( x_list, y_list, title, x_axis, y_axis, h_line: Optional[ReferenceLineConfig] = None, v_line: Optional[ReferenceLineConfig] = None, fit_curve=False, show_points=False, subtitle=None, data_label=None, theme: Optional[str] = None, font_config: Optional[FontConfig] = None, layout_config: Optional[LayoutConfig] = None, smoothing_config: Optional[SmoothingConfig] = None, ): """ Generic 2D plotting utility. Parameters ---------- x_list : numpy.ndarray Numpy array of x coordinates y_list : numpy.ndarray Numpy array of y coordinates title : str Plot title x_axis : str X-axis label y_axis : str Y-axis label h_line : ReferenceLineConfig, optional ReferenceLineConfig for horizontal reference line (None = no line) v_line : ReferenceLineConfig, optional ReferenceLineConfig for vertical reference line (None = no line) fit_curve : bool, optional Whether to fit a curve to the data points show_points : bool, optional Whether to show individual data points subtitle : str, optional Optional subtitle data_label : str, optional Curve label used in legend theme : str, optional Color theme name, see plotting.color_theme font_config : FontConfig, optional FontConfig object for font settings layout_config : LayoutConfig, optional LayoutConfig object for layout settings smoothing_config : SmoothingConfig, optional SmoothingConfig object for smoothing settings Returns ------- go.Figure Plotly figure object """ font_config = font_config or DEFAULT_FONT_CONFIG layout_config = layout_config or DEFAULT_LAYOUT_CONFIG smoothing_config = smoothing_config or DEFAULT_SMOOTHING_CONFIG if fit_curve: x_dense, y_dense = prepare_smooth_data_2D( x_list, y_list, smoothing_config=smoothing_config ) else: x_dense, y_dense = x_list, y_list fig = go.Figure() theme_colors = get_theme(theme) # Interpolated line fig.add_trace( go.Scatter( x=x_dense, y=y_dense, mode="lines", line=dict( color=theme_colors["light"], width=LINE_WIDTH, shape="spline", ), name=data_label, hovertemplate=f"{x_axis}: %{{x:{FLOAT_PRECISION}}}<br>{y_axis}: %{{y:{FLOAT_PRECISION}}}<extra></extra>", ) ) if show_points: fig.add_trace( go.Scatter( x=x_list, y=y_list, mode="markers", marker=dict(color=theme_colors["dark"], size=MARKER_SIZE_LARGE), showlegend=False, hovertemplate=None, ) ) # Add horizontal reference line if specified if h_line is not None and h_line.value is not None: x_min, x_max = min(x_dense), max(x_dense) fig.add_trace( go.Scatter( x=[x_min, x_max], y=[h_line.value, h_line.value], mode="lines", line=dict( color=h_line.color, width=h_line.width, dash=h_line.dash, ), name=f"{h_line.label}", hoverinfo="name", ) ) # Add vertical reference line if specified if v_line is not None and v_line.value is not None: y_min, y_max = min(y_dense), max(y_dense) fig.add_trace( go.Scatter( x=[v_line.value, v_line.value], y=[y_min, y_max], mode="lines", line=dict( color=v_line.color, width=v_line.width, dash=v_line.dash, ), name=f"{v_line.label}", hoverinfo="name", ) ) # Title, Axes, Label, Legend, Size full_title = title if subtitle is not None: full_title += f"<br><span style='font-size: {font_config.medium}px; color: {TEXT_COLOR_LIGHT};'>{subtitle}</span>" fig.update_layout( title={ "text": full_title, "font": dict(size=font_config.large, color=TEXT_COLOR_DARK), "x": layout_config.title_x, "xanchor": layout_config.title_xanchor, }, xaxis_title={ "text": x_axis, "font": dict(size=font_config.medium, color=TEXT_COLOR_DARK), }, yaxis_title={ "text": y_axis, "font": dict(size=font_config.medium, color=TEXT_COLOR_DARK), }, legend_title="Legend", showlegend=(data_label is not None) or (h_line is not None and h_line.value is not None) or (v_line is not None and v_line.value is not None), legend_title_font=dict(size=font_config.medium), legend_font=dict(size=font_config.small), hovermode=HOVER_MODE, plot_bgcolor=layout_config.plot_bgcolor, width=layout_config.width, height=layout_config.height, margin=layout_config.margin, ) # Add subtle grid lines fig.update_xaxes( showgrid=True, gridwidth=GRID_WIDTH, gridcolor=GRID_COLOR, zeroline=True, zerolinewidth=ZEROLINE_WIDTH, zerolinecolor=ZEROLINE_COLOR, tickfont=dict(size=font_config.small), tickformat=FLOAT_PRECISION, ) fig.update_yaxes( showgrid=True, gridwidth=GRID_WIDTH, gridcolor=GRID_COLOR, zeroline=True, zerolinewidth=ZEROLINE_WIDTH, zerolinecolor=ZEROLINE_COLOR, tickfont=dict(size=font_config.small), tickformat=FLOAT_PRECISION, ) if h_line is not None and h_line.value is not None: padding = 1 + RANGE_PADDING fig.update_yaxes( range=[ (1 / padding) * min(min(y_dense), h_line.value), padding * max(max(y_dense), h_line.value), ] ) if v_line is not None and v_line.value is not None: padding = 1 + RANGE_PADDING fig.update_xaxes( range=[ (1 / padding) * min(min(x_dense), v_line.value), padding * max(max(x_dense), v_line.value), ] ) return fig