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feat(letsplot): implement line-reaction-coordinate (#5149)
## Implementation: `line-reaction-coordinate` - letsplot Implements the **letsplot** version of `line-reaction-coordinate`. **File:** `plots/line-reaction-coordinate/implementations/letsplot.py` **Parent Issue:** #4409 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/23388404622)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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‎plots/line-reaction-coordinate/implementations/letsplot.py‎

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""" pyplots.ai
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line-reaction-coordinate: Reaction Coordinate Energy Diagram
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Library: letsplot 4.9.0 | Python 3.14.3
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Quality: 91/100 | Created: 2026-03-21
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"""
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import numpy as np
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import pandas as pd
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from lets_plot import * # noqa: F403
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from lets_plot.export import ggsave
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LetsPlot.setup_html() # noqa: F405
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# Data - Single-step exothermic reaction energy profile
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reactant_energy = 50.0
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transition_energy = 120.0
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product_energy = 20.0
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# Build smooth energy curve using Gaussian-based profile
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n_points = 300
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reaction_coord = np.linspace(0, 1, n_points)
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# Piecewise smooth curve: Gaussian peak on sigmoid transition
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peak_pos = 0.45
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sigma = 0.12
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gaussian_peak = np.exp(-0.5 * ((reaction_coord - peak_pos) / sigma) ** 2)
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# Smooth sigmoid transition from reactant to product level
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transition = 1 / (1 + np.exp(-20 * (reaction_coord - 0.6)))
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base_energy = reactant_energy * (1 - transition) + product_energy * transition
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# Add the activation barrier
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barrier_height = transition_energy - (
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reactant_energy * (1 - 1 / (1 + np.exp(-20 * (peak_pos - 0.6))))
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+ product_energy * (1 / (1 + np.exp(-20 * (peak_pos - 0.6))))
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)
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energy = base_energy + barrier_height * gaussian_peak
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# Flatten plateaus at start and end
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energy[reaction_coord < 0.1] = reactant_energy
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energy[reaction_coord > 0.9] = product_energy
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df = pd.DataFrame({"reaction_coordinate": reaction_coord, "energy": energy})
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# Key values
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ea = transition_energy - reactant_energy
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delta_h = product_energy - reactant_energy
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# Shaded region under curve for visual richness
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area_df = df.copy()
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# Colorblind-safe palette: blue (#306998) and orange (#E67E22) instead of red-green
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ea_color = "#D35400" # deep orange for Ea
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dh_color = "#2471A3" # steel blue for ΔH
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curve_color = "#306998" # Python blue
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label_color = "#2C3E50" # dark slate
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# Horizontal reference lines at energy levels
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hline_df = pd.DataFrame(
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{
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"x": [0.0, 0.0],
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"xend": [1.0, 1.0],
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"y": [reactant_energy, product_energy],
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"yend": [reactant_energy, product_energy],
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}
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)
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# Ea arrow segments (double-headed)
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ea_arrow_df = pd.DataFrame(
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{
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"x": [0.20, 0.20],
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"y": [reactant_energy + 2, transition_energy - 2],
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"xend": [0.20, 0.20],
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"yend": [transition_energy - 2, reactant_energy + 2],
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}
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)
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# ΔH arrow segments (double-headed)
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dh_arrow_df = pd.DataFrame(
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{
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"x": [0.80, 0.80],
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"y": [reactant_energy - 2, product_energy + 2],
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"xend": [0.80, 0.80],
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"yend": [product_energy + 2, reactant_energy - 2],
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}
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)
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# Build plot with lets-plot distinctive features
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plot = (
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ggplot(df, aes(x="reaction_coordinate", y="energy")) # noqa: F405
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# Shaded area under the energy curve using geom_area
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+ geom_area(fill=curve_color, alpha=0.08) # noqa: F405
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# Horizontal dashed reference lines
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+ geom_segment( # noqa: F405
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data=hline_df,
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mapping=aes(x="x", xend="xend", y="y", yend="yend"), # noqa: F405
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linetype="dashed",
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color="#B0B0B0",
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size=0.7,
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)
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# Main energy curve - prominent
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+ geom_line(color=curve_color, size=2.5) # noqa: F405
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# Ea double-headed arrow (orange - colorblind safe)
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+ geom_segment( # noqa: F405
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data=ea_arrow_df,
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mapping=aes(x="x", xend="xend", y="y", yend="yend"), # noqa: F405
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color=ea_color,
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size=1.3,
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arrow=arrow(length=10, type="open"), # noqa: F405
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)
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# ΔH double-headed arrow (steel blue - colorblind safe)
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+ geom_segment( # noqa: F405
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data=dh_arrow_df,
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mapping=aes(x="x", xend="xend", y="y", yend="yend"), # noqa: F405
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color=dh_color,
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size=1.3,
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arrow=arrow(length=10, type="open"), # noqa: F405
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)
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# Labels using geom_label (lets-plot distinctive: label_padding, label_r)
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+ geom_label( # noqa: F405
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data=pd.DataFrame({"x": [0.08], "y": [reactant_energy - 8], "label": ["Reactants\n50 kJ/mol"]}),
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mapping=aes(x="x", y="y", label="label"), # noqa: F405
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size=15,
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color=label_color,
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fill="#F8F9FA",
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alpha=0.85,
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label_padding=0.4,
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label_r=0.3,
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label_size=0,
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)
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+ geom_label( # noqa: F405
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data=pd.DataFrame({"x": [peak_pos], "y": [transition_energy + 8], "label": ["Transition State\n120 kJ/mol"]}),
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mapping=aes(x="x", y="y", label="label"), # noqa: F405
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size=15,
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color=label_color,
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fill="#F8F9FA",
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alpha=0.85,
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label_padding=0.4,
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label_r=0.3,
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label_size=0,
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)
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+ geom_label( # noqa: F405
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data=pd.DataFrame({"x": [0.92], "y": [product_energy - 8], "label": ["Products\n20 kJ/mol"]}),
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mapping=aes(x="x", y="y", label="label"), # noqa: F405
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size=15,
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color=label_color,
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fill="#F8F9FA",
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alpha=0.85,
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label_padding=0.4,
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label_r=0.3,
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label_size=0,
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)
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# Energy annotation labels with colored backgrounds matching their arrows
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+ geom_label( # noqa: F405
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data=pd.DataFrame(
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{"x": [0.20], "y": [(reactant_energy + transition_energy) / 2], "label": [f"Ea = {ea:.0f} kJ/mol"]}
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),
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mapping=aes(x="x", y="y", label="label"), # noqa: F405
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size=16,
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color="#FFFFFF",
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fill=ea_color,
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alpha=0.9,
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label_padding=0.5,
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label_r=0.3,
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label_size=0,
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fontface="bold",
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)
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+ geom_label( # noqa: F405
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data=pd.DataFrame(
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{"x": [0.80], "y": [(reactant_energy + product_energy) / 2], "label": [f"ΔH = {delta_h:.0f} kJ/mol"]}
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),
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mapping=aes(x="x", y="y", label="label"), # noqa: F405
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size=16,
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color="#FFFFFF",
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fill=dh_color,
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alpha=0.9,
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label_padding=0.5,
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label_r=0.3,
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label_size=0,
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fontface="bold",
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)
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# Scales
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+ scale_x_continuous( # noqa: F405
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name="Reaction Coordinate", breaks=[], expand=[0.02, 0.02]
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)
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+ scale_y_continuous( # noqa: F405
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name="Potential Energy (kJ/mol)", limits=[0, 145]
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)
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+ labs(title="line-reaction-coordinate · letsplot · pyplots.ai") # noqa: F405
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+ coord_cartesian(ylim=[0, 145]) # noqa: F405
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+ ggsize(1600, 900) # noqa: F405
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# Lets-plot distinctive: flavor for base styling + element_geom for global defaults
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+ flavor_high_contrast_light() # noqa: F405
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+ theme( # noqa: F405
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axis_text=element_text(size=16, color="#555555"), # noqa: F405
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axis_title=element_text(size=20, color="#333333"), # noqa: F405
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plot_title=element_text(size=24, hjust=0.5, color="#2C3E50", face="bold"), # noqa: F405
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axis_text_x=element_blank(), # noqa: F405
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axis_ticks_x=element_blank(), # noqa: F405
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axis_line_x=element_line(color="#CCCCCC", size=0.6), # noqa: F405
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axis_line_y=element_line(color="#CCCCCC", size=0.6), # noqa: F405
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panel_grid_major_y=element_line(color="#EEEEEE", size=0.3), # noqa: F405
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panel_grid_minor=element_blank(), # noqa: F405
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panel_grid_major_x=element_blank(), # noqa: F405
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legend_position="none",
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plot_background=element_rect(fill="#FFFFFF", color="#FFFFFF"), # noqa: F405
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panel_background=element_rect(fill="#FAFBFC", color="#FAFBFC"), # noqa: F405
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)
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)
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# Save
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ggsave(plot, filename="plot.png", path=".", scale=3)
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ggsave(plot, filename="plot.html", path=".")

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