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feat(plotnine): implement line-stress-strain (#5122)
## Implementation: `line-stress-strain` - plotnine Implements the **plotnine** version of `line-stress-strain`. **File:** `plots/line-stress-strain/implementations/plotnine.py` **Parent Issue:** #4413 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/23363004971)* --------- 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-stress-strain/implementations/plotnine.py‎

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""" pyplots.ai
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line-stress-strain: Engineering Stress-Strain Curve
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Library: plotnine 0.15.3 | Python 3.14.3
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Quality: 90/100 | Created: 2026-03-20
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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 plotnine import (
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aes,
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annotate,
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coord_cartesian,
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element_blank,
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element_line,
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element_rect,
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element_text,
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geom_line,
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geom_point,
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geom_segment,
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geom_text,
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ggplot,
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labs,
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scale_color_identity,
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scale_fill_identity,
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scale_linetype_identity,
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scale_size_identity,
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scale_x_continuous,
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scale_y_continuous,
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theme,
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theme_minimal,
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)
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# Data - Mild steel stress-strain curve
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np.random.seed(42)
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youngs_modulus = 210000 # MPa
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yield_stress = 250 # MPa
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uts = 400 # MPa
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fracture_strain = 0.35
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necking_strain = 0.22
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# Elastic region (0 to yield)
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elastic_strain = np.linspace(0, yield_stress / youngs_modulus, 40)
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elastic_stress = youngs_modulus * elastic_strain
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# Yield plateau (short flat region for mild steel)
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plateau_strain = np.linspace(elastic_strain[-1], 0.025, 15)
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plateau_stress = np.full_like(plateau_strain, yield_stress)
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# Strain hardening (power law)
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hardening_strain = np.linspace(0.025, necking_strain, 80)
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hardening_stress = yield_stress + (uts - yield_stress) * ((hardening_strain - 0.025) / (necking_strain - 0.025)) ** 0.45
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# Necking to fracture (stress decreases)
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necking_strain_vals = np.linspace(necking_strain, fracture_strain, 40)
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necking_stress = (
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uts - (uts - 320) * ((necking_strain_vals - necking_strain) / (fracture_strain - necking_strain)) ** 1.3
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)
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# Combine all regions
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strain = np.concatenate([elastic_strain, plateau_strain[1:], hardening_strain[1:], necking_strain_vals[1:]])
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stress = np.concatenate([elastic_stress, plateau_stress[1:], hardening_stress[1:], necking_stress[1:]])
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df = pd.DataFrame({"strain": strain, "stress": stress})
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# 0.2% offset line data - extended for better visibility
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offset = 0.002
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offset_strain_start = offset
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offset_strain_end = (yield_stress + 50) / youngs_modulus + offset
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# Key points
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yield_point_strain = yield_stress / youngs_modulus + offset
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yield_point_stress = yield_stress
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uts_strain = necking_strain
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uts_stress = uts
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fracture_strain_pt = fracture_strain
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fracture_stress_pt = necking_stress[-1]
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df_points = pd.DataFrame(
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{
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"strain": [yield_point_strain, uts_strain, fracture_strain_pt],
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"stress": [yield_point_stress, uts_stress, fracture_stress_pt],
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"label": ["Yield Point\n(0.2% offset)", "UTS", "Fracture"],
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"color": ["#C0392B", "#C0392B", "#C0392B"],
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"size": [6.0, 6.0, 6.0],
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}
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)
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# Region labels - repositioned for clarity
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df_regions = pd.DataFrame(
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{
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"strain": [0.005, 0.015, 0.13, 0.29],
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"stress": [410, 215, 310, 370],
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"label": ["Elastic", "Yield\nPlateau", "Strain\nHardening", "Necking"],
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"color": ["#5D6D7E", "#5D6D7E", "#5D6D7E", "#5D6D7E"],
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}
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)
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# Region boundary strains for shading
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elastic_end = yield_stress / youngs_modulus
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plateau_end = 0.025
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# Plot using plotnine grammar of graphics with layered composition
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plot = (
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ggplot()
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# Region shading using annotate("rect") - plotnine-distinctive feature
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+ annotate("rect", xmin=0, xmax=elastic_end, ymin=0, ymax=440, alpha=0.15, fill="#3498DB")
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+ annotate("rect", xmin=elastic_end, xmax=plateau_end, ymin=0, ymax=440, alpha=0.15, fill="#2ECC71")
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+ annotate("rect", xmin=plateau_end, xmax=necking_strain, ymin=0, ymax=440, alpha=0.12, fill="#F39C12")
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+ annotate("rect", xmin=necking_strain, xmax=fracture_strain, ymin=0, ymax=440, alpha=0.12, fill="#E74C3C")
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# Main stress-strain curve
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+ geom_line(df, aes(x="strain", y="stress"), color="#306998", size=2.8)
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# 0.2% offset line using geom_segment - plotnine-distinctive
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+ geom_segment(
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aes(x=offset_strain_start, xend=offset_strain_end, y=0, yend=yield_stress + 50),
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color="#C0392B",
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size=1.2,
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linetype="dashed",
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)
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# Offset label near the line
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+ annotate("text", x=0.012, y=60, label="0.2% offset", size=11, color="#C0392B", fontstyle="italic")
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# Key points with identity scales for direct aesthetic mapping
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+ geom_point(df_points, aes(x="strain", y="stress", color="color", size="size"), fill="#C0392B")
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+ scale_color_identity()
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+ scale_size_identity()
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# Point labels - larger text
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+ geom_text(
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df_points, aes(x="strain", y="stress", label="label"), nudge_y=32, size=15, color="#2C3E50", fontweight="bold"
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)
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# Region labels with identity color scale - larger text
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+ geom_text(df_regions, aes(x="strain", y="stress", label="label", color="color"), size=14, fontstyle="italic")
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+ scale_fill_identity()
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+ scale_linetype_identity()
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# Modulus annotation - larger and repositioned
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+ annotate(
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"text", x=0.03, y=140, label=f"E = {youngs_modulus // 1000} GPa", size=16, color="#306998", fontweight="bold"
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)
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+ labs(x="Engineering Strain", y="Engineering Stress (MPa)", title="line-stress-strain · plotnine · pyplots.ai")
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+ scale_x_continuous(breaks=np.arange(0, 0.40, 0.05))
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+ scale_y_continuous(breaks=np.arange(0, 500, 50))
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# Coordinate control - plotnine-distinctive
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+ coord_cartesian(xlim=(0, 0.38), ylim=(0, 460))
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+ theme_minimal()
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+ theme(
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figure_size=(16, 9),
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plot_title=element_text(size=26, weight="bold", color="#1A2530"),
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axis_title=element_text(size=22, color="#2C3E50", weight="bold"),
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axis_text=element_text(size=16, color="#555555"),
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panel_grid_major_x=element_blank(),
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panel_grid_minor=element_blank(),
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panel_grid_major_y=element_line(color="#E8E8E8", size=0.4, alpha=0.5),
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plot_background=element_rect(fill="white", color="white"),
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panel_background=element_rect(fill="white", color="white"),
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)
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)
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# Save
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plot.save("plot.png", dpi=300, verbose=False)

‎plots/line-stress-strain/metadata/plotnine.yaml‎

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library: plotnine
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specification_id: line-stress-strain
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created: '2026-03-20T21:22:28Z'
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updated: '2026-03-20T21:43:25Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 23363004971
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issue: 4413
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python_version: 3.14.3
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library_version: 0.15.3
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preview_url: https://storage.googleapis.com/pyplots-images/plots/line-stress-strain/plotnine/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-stress-strain/plotnine/plot_thumb.png
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preview_html: null
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quality_score: 90
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review:
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strengths:
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- Excellent data storytelling through color-coded region shading that guides the
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viewer through material behavior phases
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- 'All spec-required features implemented: region labels, critical points, elastic
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modulus annotation, 0.2% offset line'
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- Realistic mild steel data with appropriate engineering values
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- Clean, well-structured code following KISS principles
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- Good use of plotnine grammar-of-graphics approach with layered composition
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weaknesses:
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- The elastic region is horizontally compressed, creating visual density with multiple
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labels in a narrow space
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- The 0.2% offset annotation text (size=11) is noticeably smaller than other text
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elements
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image_description: 'The plot displays an engineering stress-strain curve for mild
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steel on a white background. The title "line-stress-strain · plotnine · pyplots.ai"
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appears in bold dark text at the top. The x-axis is labeled "Engineering Strain"
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(0.00–0.35) and the y-axis "Engineering Stress (MPa)" (0–450). A thick dark blue
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line traces the characteristic stress-strain path from origin through elastic
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deformation, yield plateau, strain hardening up to ~400 MPa at strain ~0.22 (UTS),
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then necking down to ~320 MPa at fracture (strain ~0.35). Four color-shaded rectangular
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regions mark the material behavior zones: light blue (Elastic), light green (Yield
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Plateau), light yellow/orange (Strain Hardening), and light pink/red (Necking),
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each with gray italic region labels. Three red dots mark critical points labeled
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in bold: "Yield Point (0.2% offset)", "UTS", and "Fracture". A red dashed line
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shows the 0.2% offset construction with a small red italic "0.2% offset" label
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near the bottom. "E = 210 GPa" appears in bold blue text. The y-axis grid is subtle
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light gray; x-axis grid is removed. Layout is 16:9 with good canvas utilization.'
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criteria_checklist:
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visual_quality:
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score: 28
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max: 30
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items:
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- id: VQ-01
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name: Text Legibility
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score: 7
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max: 8
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passed: true
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comment: All major text sizes explicitly set (title=26, axis_title=22, axis_text=16).
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The 0.2% offset annotation at size=11 is smaller than other text.
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- id: VQ-02
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name: No Overlap
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score: 5
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max: 6
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passed: true
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comment: No actual text overlap, but elastic region is horizontally compressed
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with multiple labels in a narrow band.
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- id: VQ-03
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name: Element Visibility
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score: 6
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max: 6
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passed: true
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comment: Main curve at size=2.8 clearly visible, key points at size=6 are
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prominent.
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- id: VQ-04
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name: Color Accessibility
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score: 4
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max: 4
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passed: true
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comment: Blue curve with red accents, pastel region shading. Colorblind-safe,
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no red-green dependency.
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- id: VQ-05
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name: Layout & Canvas
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score: 4
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max: 4
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passed: true
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comment: Good 16:9 proportions with plot filling the canvas well.
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- id: VQ-06
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name: Axis Labels & Title
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score: 2
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max: 2
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passed: true
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comment: 'Descriptive labels with units: Engineering Strain and Engineering
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Stress (MPa).'
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design_excellence:
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score: 15
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max: 20
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items:
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- id: DE-01
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name: Aesthetic Sophistication
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score: 6
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max: 8
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passed: true
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comment: Color-coded region shading, custom palette, intentional typographic
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hierarchy. Above defaults.
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- id: DE-02
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name: Visual Refinement
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score: 4
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max: 6
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passed: true
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comment: X-grid removed, subtle y-only grid, clean white background. Minor
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density in elastic region.
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- id: DE-03
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name: Data Storytelling
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score: 5
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max: 6
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passed: true
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comment: Color-coded regions guide viewer through material behavior. Key points
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create clear focal points.
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spec_compliance:
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score: 15
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max: 15
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items:
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- id: SC-01
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name: Plot Type
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score: 5
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max: 5
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passed: true
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comment: Correct engineering stress-strain curve as line plot.
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- id: SC-02
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name: Required Features
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score: 4
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max: 4
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passed: true
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comment: 'All spec features present: region labels, critical points, modulus
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annotation, offset line.'
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- id: SC-03
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name: Data Mapping
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score: 3
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max: 3
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passed: true
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comment: X=strain, Y=stress correctly mapped with full data range.
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- id: SC-04
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name: Title & Legend
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score: 3
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max: 3
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passed: true
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comment: Title follows exact format. No legend needed for single-series.
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data_quality:
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score: 15
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max: 15
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 6
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max: 6
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passed: true
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comment: 'Shows all curve regions: elastic, yield plateau, strain hardening,
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necking, fracture.'
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- id: DQ-02
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name: Realistic Context
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score: 5
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max: 5
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passed: true
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comment: Mild steel tensile test - classic, neutral engineering scenario.
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- id: DQ-03
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name: Appropriate Scale
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score: 4
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max: 4
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passed: true
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comment: 'Realistic values for mild steel: E=210 GPa, yield=250 MPa, UTS=400
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MPa.'
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code_quality:
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score: 10
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: 'Clean linear flow: imports, data, plot, save. No functions or classes.'
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- id: CQ-02
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name: Reproducibility
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score: 2
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max: 2
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passed: true
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comment: np.random.seed(42) set at start.
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- id: CQ-03
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name: Clean Imports
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score: 2
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max: 2
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passed: true
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comment: All imports are used.
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- id: CQ-04
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name: Code Elegance
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score: 2
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max: 2
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passed: true
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comment: Well-organized with clear sections. No fake UI.
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- id: CQ-05
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name: Output & API
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score: 1
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max: 1
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passed: true
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comment: Saves as plot.png with dpi=300. Current plotnine API.
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library_mastery:
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score: 7
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max: 10
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items:
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- id: LM-01
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name: Idiomatic Usage
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score: 4
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max: 5
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passed: true
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comment: Good grammar-of-graphics with layered composition, aes mapping, identity
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scales, theme customization.
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- id: LM-02
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name: Distinctive Features
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score: 3
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max: 5
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passed: true
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comment: Uses annotate rect for region shading, coord_cartesian, identity
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scales, geom_segment.
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verdict: APPROVED
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impl_tags:
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dependencies: []
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techniques:
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- annotations
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- layer-composition
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patterns:
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- data-generation
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dataprep: []
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styling:
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- alpha-blending
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- grid-styling

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