From fb1e7cdd3b86ebcc9e235259cdec37b5fcb1f5c1 Mon Sep 17 00:00:00 2001 From: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com> Date: Sun, 5 Apr 2026 22:38:53 +0200 Subject: [PATCH 1/5] =?UTF-8?q?update(dendrogram-basic):=20matplotlib=20?= =?UTF-8?q?=E2=80=94=20comprehensive=20quality=20review?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Comprehensive review improving code quality, data choice, visual design, spec compliance, and library feature usage. --- .../implementations/matplotlib.py | 90 +++++++++++-------- .../dendrogram-basic/metadata/matplotlib.yaml | 8 +- plots/dendrogram-basic/specification.md | 3 +- plots/dendrogram-basic/specification.yaml | 3 +- 4 files changed, 62 insertions(+), 42 deletions(-) diff --git a/plots/dendrogram-basic/implementations/matplotlib.py b/plots/dendrogram-basic/implementations/matplotlib.py index b9c240341c..0874e9a55e 100644 --- a/plots/dendrogram-basic/implementations/matplotlib.py +++ b/plots/dendrogram-basic/implementations/matplotlib.py @@ -1,21 +1,19 @@ -""" pyplots.ai +"""pyplots.ai dendrogram-basic: Basic Dendrogram -Library: matplotlib 3.10.8 | Python 3.13.11 -Quality: 91/100 | Created: 2025-12-23 +Library: matplotlib 3.10.8 | Python 3.14.3 +Quality: /100 | Updated: 2026-04-05 """ import matplotlib.pyplot as plt import numpy as np -from scipy.cluster.hierarchy import dendrogram, linkage +from matplotlib.collections import LineCollection +from scipy.cluster.hierarchy import dendrogram, linkage, set_link_color_palette # Data - Iris flower measurements (4 features for 15 samples) np.random.seed(42) -# Simulate iris-like measurements: sepal length, sepal width, petal length, petal width -# Three species with distinct characteristics samples_per_species = 5 - labels = [] data = [] @@ -24,10 +22,10 @@ labels.append(f"Setosa-{i + 1}") data.append( [ - 5.0 + np.random.randn() * 0.3, # sepal length - 3.4 + np.random.randn() * 0.3, # sepal width - 1.5 + np.random.randn() * 0.2, # petal length - 0.3 + np.random.randn() * 0.1, # petal width + 5.0 + np.random.randn() * 0.3, + 3.4 + np.random.randn() * 0.3, + 1.5 + np.random.randn() * 0.2, + 0.3 + np.random.randn() * 0.1, ] ) @@ -36,10 +34,10 @@ labels.append(f"Versicolor-{i + 1}") data.append( [ - 5.9 + np.random.randn() * 0.4, # sepal length - 2.8 + np.random.randn() * 0.3, # sepal width - 4.3 + np.random.randn() * 0.4, # petal length - 1.3 + np.random.randn() * 0.2, # petal width + 5.9 + np.random.randn() * 0.4, + 2.8 + np.random.randn() * 0.3, + 4.3 + np.random.randn() * 0.4, + 1.3 + np.random.randn() * 0.2, ] ) @@ -48,10 +46,10 @@ labels.append(f"Virginica-{i + 1}") data.append( [ - 6.6 + np.random.randn() * 0.5, # sepal length - 3.0 + np.random.randn() * 0.3, # sepal width - 5.5 + np.random.randn() * 0.5, # petal length - 2.0 + np.random.randn() * 0.3, # petal width + 6.6 + np.random.randn() * 0.5, + 3.0 + np.random.randn() * 0.3, + 5.5 + np.random.randn() * 0.5, + 2.0 + np.random.randn() * 0.3, ] ) @@ -61,33 +59,53 @@ linkage_matrix = linkage(data, method="ward") # Plot -fig, ax = plt.subplots(figsize=(16, 9)) +fig, ax = plt.subplots(figsize=(16, 9), facecolor="white") +ax.set_facecolor("#FAFAFA") + +# Custom cluster colors via set_link_color_palette (matplotlib/scipy integration) +cluster_colors = ["#306998", "#D4722A", "#3A8A5C"] +set_link_color_palette(cluster_colors) -# Create dendrogram with custom colors -dendrogram( +dendro = dendrogram( linkage_matrix, labels=labels, ax=ax, - leaf_rotation=45, - leaf_font_size=14, - above_threshold_color="#306998", # Python Blue for main branches - color_threshold=0.7 * max(linkage_matrix[:, 2]), # Color threshold for clusters + leaf_rotation=35, + leaf_font_size=15, + above_threshold_color="#AAAAAA", + color_threshold=0.7 * max(linkage_matrix[:, 2]), ) +# Post-render enhancement: adjust line widths via LineCollection traversal +for child in ax.get_children(): + if isinstance(child, LineCollection): + child.set_linewidths(3.0) + child.set_capstyle("round") + child.set_joinstyle("round") + # Style -ax.set_xlabel("Sample", fontsize=20) -ax.set_ylabel("Distance (Ward)", fontsize=20) -ax.set_title("dendrogram-basic · matplotlib · pyplots.ai", fontsize=24) -ax.tick_params(axis="both", labelsize=16) -ax.tick_params(axis="x", labelsize=14, rotation=45) +ax.set_xlabel("Iris Sample", fontsize=20, labelpad=10) +ax.set_ylabel("Ward Linkage Distance", fontsize=20, labelpad=10) +ax.set_title( + "Iris Species Clustering · dendrogram-basic · matplotlib · pyplots.ai", + fontsize=24, + fontweight="medium", + pad=20, + color="#333333", +) +ax.tick_params(axis="both", labelsize=16, colors="#555555") +ax.tick_params(axis="x", labelsize=15, rotation=35) -# Adjust spines for cleaner look ax.spines["top"].set_visible(False) ax.spines["right"].set_visible(False) +ax.spines["left"].set_linewidth(0.6) +ax.spines["left"].set_color("#CCCCCC") +ax.spines["bottom"].set_linewidth(0.6) +ax.spines["bottom"].set_color("#CCCCCC") -# Add subtle grid on y-axis only -ax.yaxis.grid(True, alpha=0.3, linestyle="--") +# Subtle grid on y-axis only +ax.yaxis.grid(True, alpha=0.15, linewidth=0.6, color="#888888") ax.set_axisbelow(True) -plt.tight_layout() -plt.savefig("plot.png", dpi=300, bbox_inches="tight") +plt.tight_layout(pad=1.5) +plt.savefig("plot.png", dpi=300, bbox_inches="tight", facecolor="white") diff --git a/plots/dendrogram-basic/metadata/matplotlib.yaml b/plots/dendrogram-basic/metadata/matplotlib.yaml index b40e8b8fb6..6c421bfff3 100644 --- a/plots/dendrogram-basic/metadata/matplotlib.yaml +++ b/plots/dendrogram-basic/metadata/matplotlib.yaml @@ -1,15 +1,15 @@ library: matplotlib specification_id: dendrogram-basic created: '2025-12-23T10:00:50Z' -updated: '2025-12-23T10:06:28Z' -generated_by: claude-opus-4-5-20251101 +updated: '2026-04-05T20:00:00+00:00' +generated_by: claude-opus-4-6 workflow_run: 20457531070 issue: 0 -python_version: 3.13.11 +python_version: '3.14.3' library_version: 3.10.8 preview_url: https://storage.googleapis.com/pyplots-images/plots/dendrogram-basic/matplotlib/plot.png preview_html: null -quality_score: 91 +quality_score: null impl_tags: dependencies: - scipy diff --git a/plots/dendrogram-basic/specification.md b/plots/dendrogram-basic/specification.md index e46394e2c4..36c270aeb6 100644 --- a/plots/dendrogram-basic/specification.md +++ b/plots/dendrogram-basic/specification.md @@ -13,8 +13,9 @@ A dendrogram visualizes hierarchical clustering by showing how data points or cl ## Data +- `features` (numeric matrix) - measurement values for each item (e.g., petal length, sepal width), used to compute distances - `labels` (string) - names or identifiers for each item being clustered -- `linkage_matrix` (numeric) - output from scipy's linkage function containing merge distances +- `linkage_matrix` (numeric) - output from scipy's linkage function containing merge distances, computed from features - Size: 10-50 items recommended for readable dendrograms - Example: hierarchical clustering of iris flower species by measurements diff --git a/plots/dendrogram-basic/specification.yaml b/plots/dendrogram-basic/specification.yaml index d731af3645..b6dae88c3d 100644 --- a/plots/dendrogram-basic/specification.yaml +++ b/plots/dendrogram-basic/specification.yaml @@ -6,7 +6,7 @@ title: Basic Dendrogram # Specification tracking created: 2025-12-15T20:43:34Z -updated: 2025-12-15T20:43:34Z +updated: 2026-04-05T12:00:00Z issue: 986 suggested: MarkusNeusinger @@ -17,6 +17,7 @@ tags: - tree data_type: - hierarchical + - numeric domain: - statistics - science From 922a43ac5f2dd6a44f73441c7af75c2480a12091 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 5 Apr 2026 20:43:55 +0000 Subject: [PATCH 2/5] chore(matplotlib): update quality score 88 and review feedback for dendrogram-basic --- .../implementations/matplotlib.py | 4 +- .../dendrogram-basic/metadata/matplotlib.yaml | 249 +++++++++--------- 2 files changed, 133 insertions(+), 120 deletions(-) diff --git a/plots/dendrogram-basic/implementations/matplotlib.py b/plots/dendrogram-basic/implementations/matplotlib.py index 0874e9a55e..07eae961d5 100644 --- a/plots/dendrogram-basic/implementations/matplotlib.py +++ b/plots/dendrogram-basic/implementations/matplotlib.py @@ -1,7 +1,7 @@ -"""pyplots.ai +""" pyplots.ai dendrogram-basic: Basic Dendrogram Library: matplotlib 3.10.8 | Python 3.14.3 -Quality: /100 | Updated: 2026-04-05 +Quality: 88/100 | Updated: 2026-04-05 """ import matplotlib.pyplot as plt diff --git a/plots/dendrogram-basic/metadata/matplotlib.yaml b/plots/dendrogram-basic/metadata/matplotlib.yaml index 6c421bfff3..9255e2a080 100644 --- a/plots/dendrogram-basic/metadata/matplotlib.yaml +++ b/plots/dendrogram-basic/metadata/matplotlib.yaml @@ -1,163 +1,171 @@ library: matplotlib specification_id: dendrogram-basic created: '2025-12-23T10:00:50Z' -updated: '2026-04-05T20:00:00+00:00' +updated: '2026-04-05T20:43:55Z' generated_by: claude-opus-4-6 workflow_run: 20457531070 issue: 0 -python_version: '3.14.3' +python_version: 3.14.3 library_version: 3.10.8 preview_url: https://storage.googleapis.com/pyplots-images/plots/dendrogram-basic/matplotlib/plot.png preview_html: null -quality_score: null +quality_score: 88 impl_tags: dependencies: - scipy - techniques: [] + techniques: + - manual-ticks patterns: - data-generation - - iteration-over-groups + - explicit-figure dataprep: - hierarchical-clustering - styling: [] + styling: + - grid-styling review: strengths: - - Excellent hierarchical clustering visualization with clear species separation - (Setosa clearly distinct from Versicolor/Virginica) - - Perfect use of scipy.cluster.hierarchy with Ward's method for meaningful distance - metric - - Color-coded clusters make the hierarchical relationships immediately apparent - - Clean, professional styling with removed top/right spines and subtle grid - - Realistic iris dataset context that is widely recognized in data science + - Excellent scipy/matplotlib integration with set_link_color_palette and LineCollection + post-processing for line styling + - Clean, realistic iris species data with proper clustering hierarchy and appropriate + measurements + - 'Professional visual polish: removed spines, subtle grid, custom background, refined + typography' + - Perfect spec compliance with correct title format and all required features weaknesses: - - Does not leverage any distinctive matplotlib visualization features beyond basic - figure/axes setup - - Y-axis label could be more descriptive (e.g., Ward Linkage Distance or include - clustering interpretation hints) - image_description: 'The plot displays a dendrogram (hierarchical clustering tree) - with 15 iris flower samples on the x-axis and Ward distance on the y-axis (ranging - 0-10). The tree structure shows three distinct color-coded clusters: orange branches - for Setosa samples (left side), green branches for Versicolor and Virginica samples - (center and right). The blue horizontal line at the top connects the Setosa cluster - to the Versicolor/Virginica cluster at distance ~10. Sample labels are rotated - 45 degrees and clearly readable. The title "dendrogram-basic · matplotlib · pyplots.ai" - appears at the top. The plot has a clean white background with subtle dashed horizontal - grid lines on the y-axis. Top and right spines are removed for a cleaner appearance.' + - Color threshold only distinguishes 2 visual clusters (Setosa vs rest) instead + of 3 species, weakening the data storytelling + - Leaf font size (15pt) slightly below the 16pt guideline for tick labels + - Minor label crowding at 35° rotation with 15 samples + image_description: 'The plot displays a vertical dendrogram of 15 iris flower samples + clustered using Ward''s linkage method. The x-axis shows sample labels (Setosa-1 + through Setosa-5, Versicolor-1 through Versicolor-5, Virginica-1 through Virginica-5) + rotated at ~35°. The y-axis shows "Ward Linkage Distance" ranging from 0 to ~10. + Two color-coded clusters are visible: Setosa samples in blue (left side, merging + at low distances ~0.3-1.0) and Versicolor+Virginica samples in orange (right side, + merging at distances ~0.4-4.0). A gray connector merges these two main groups + at ~10.2. The background is light gray (#FAFAFA), top and right spines are removed, + and a subtle y-axis grid is present. Lines are thick (3px) with round caps. The + title reads "Iris Species Clustering · dendrogram-basic · matplotlib · pyplots.ai".' criteria_checklist: visual_quality: - score: 37 - max: 40 + score: 28 + max: 30 items: - id: VQ-01 name: Text Legibility - score: 10 - max: 10 + score: 7 + max: 8 passed: true - comment: Title at 24pt, axis labels at 20pt, tick labels at 14-16pt, all perfectly - readable + comment: All font sizes explicitly set (title 24, labels 20, ticks 16). Leaf + font at 15pt slightly below 16pt guideline. - id: VQ-02 name: No Overlap - score: 8 - max: 8 + score: 5 + max: 6 passed: true - comment: Sample labels are rotated 45° preventing any overlap, all text fully - readable + comment: Labels rotated 35° and generally readable. Slight crowding between + adjacent Setosa labels. - id: VQ-03 name: Element Visibility - score: 8 - max: 8 + score: 6 + max: 6 passed: true - comment: Dendrogram branches are clearly visible with good line weights + comment: Dendrogram lines at 3.0 width with round caps/joins are clearly visible. - id: VQ-04 name: Color Accessibility - score: 5 - max: 5 + score: 4 + max: 4 passed: true - comment: Orange, green, and blue are colorblind-safe and distinguishable + comment: Blue and orange are colorblind-safe. Gray above-threshold connector + distinguishable. - id: VQ-05 - name: Layout Balance - score: 5 - max: 5 + name: Layout & Canvas + score: 4 + max: 4 passed: true - comment: Good use of 16:9 aspect ratio, well-proportioned margins + comment: Plot fills canvas well with balanced margins. - id: VQ-06 - name: Axis Labels - score: 1 - max: 2 - passed: false - comment: '"Sample" and "Distance (Ward)" are descriptive but y-axis could - include units' - - id: VQ-07 - name: Grid & Legend + name: Axis Labels & Title score: 2 max: 2 passed: true - comment: Subtle dashed grid on y-axis only (alpha=0.3), no legend needed for - this plot type + comment: 'Descriptive labels: Iris Sample and Ward Linkage Distance.' + design_excellence: + score: 14 + max: 20 + items: + - id: DE-01 + name: Aesthetic Sophistication + score: 6 + max: 8 + passed: true + comment: Custom palette, refined background, round line caps/joins. Above + defaults but not exceptional. + - id: DE-02 + name: Visual Refinement + score: 5 + max: 6 + passed: true + comment: Spines removed/thinned, subtle y-grid alpha=0.15, generous whitespace. + - id: DE-03 + name: Data Storytelling + score: 3 + max: 6 + passed: false + comment: Color threshold only produces 2 color groups instead of 3 species. + Misses opportunity to tell the full 3-species story. spec_compliance: - score: 25 - max: 25 + score: 15 + max: 15 items: - id: SC-01 name: Plot Type - score: 8 - max: 8 - passed: true - comment: Correct dendrogram/hierarchical clustering visualization - - id: SC-02 - name: Data Mapping score: 5 max: 5 passed: true - comment: Samples on x-axis, merge distances on y-axis as expected - - id: SC-03 + comment: Correct dendrogram using scipy.cluster.hierarchy.dendrogram. + - id: SC-02 name: Required Features - score: 5 - max: 5 + score: 4 + max: 4 passed: true - comment: Uses scipy.cluster.hierarchy, shows branch heights proportional to - distances, vertical orientation - - id: SC-04 - name: Data Range + comment: 'All spec features present: features matrix, labels, linkage, vertical + orientation.' + - id: SC-03 + name: Data Mapping score: 3 max: 3 passed: true - comment: All 15 samples visible, full distance range shown - - id: SC-05 - name: Legend Accuracy - score: 2 - max: 2 - passed: true - comment: No legend needed; cluster colors are self-explanatory - - id: SC-06 - name: Title Format - score: 2 - max: 2 + comment: Labels on x-axis, distances on y-axis, proportional branch heights. + - id: SC-04 + name: Title & Legend + score: 3 + max: 3 passed: true - comment: Correctly formatted as "dendrogram-basic · matplotlib · pyplots.ai" + comment: Title follows spec format. No legend needed for dendrogram. data_quality: - score: 19 - max: 20 + score: 14 + max: 15 items: - id: DQ-01 name: Feature Coverage - score: 8 - max: 8 + score: 5 + max: 6 passed: true - comment: Shows hierarchical structure with clear cluster separations at different - distance levels + comment: Shows 3 species at varying merge distances. Only 2 color groups visible + instead of 3. - id: DQ-02 name: Realistic Context - score: 6 - max: 7 + score: 5 + max: 5 passed: true - comment: Iris flower species is a classic, well-known clustering example + comment: Iris flower measurements - classic neutral botanical dataset. - id: DQ-03 name: Appropriate Scale - score: 5 - max: 5 + score: 4 + max: 4 passed: true - comment: 15 samples (within recommended 10-50), realistic iris measurements + comment: Realistic iris measurements in cm range. code_quality: score: 10 max: 10 @@ -167,41 +175,46 @@ review: score: 3 max: 3 passed: true - comment: 'Clean linear structure: imports → data → linkage → plot → save' + comment: 'Clean flow: imports, data, compute, plot, style, save.' - id: CQ-02 name: Reproducibility - score: 3 - max: 3 + score: 2 + max: 2 passed: true - comment: Uses np.random.seed(42) + comment: np.random.seed(42) set. - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: Only matplotlib, numpy, and scipy.cluster.hierarchy used + comment: All imports used including LineCollection and scipy. - id: CQ-04 - name: No Deprecated API - score: 1 - max: 1 + name: Code Elegance + score: 2 + max: 2 passed: true - comment: All APIs are current + comment: Clean, appropriate complexity. - id: CQ-05 - name: Output Correct + name: Output & API score: 1 max: 1 passed: true - comment: Saves as plot.png with dpi=300 - library_features: - score: 0 - max: 5 + comment: Saves as plot.png, dpi=300, current API. + library_mastery: + score: 7 + max: 10 items: - - id: LF-01 - name: Uses distinctive library features - score: 0 + - id: LM-01 + name: Idiomatic Usage + score: 4 max: 5 - passed: false - comment: Uses scipy's dendrogram function directly; matplotlib is used only - for figure setup and styling, not for any distinctive matplotlib-specific - visualization features - verdict: APPROVED + passed: true + comment: Good scipy/matplotlib integration, axes-based approach, set_link_color_palette. + - id: LM-02 + name: Distinctive Features + score: 3 + max: 5 + passed: true + comment: LineCollection traversal and set_link_color_palette are matplotlib-specific + techniques. + verdict: REJECTED From a378b66c5817b801d9dd017d94956b87c1526e53 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 5 Apr 2026 20:52:28 +0000 Subject: [PATCH 3/5] chore(matplotlib): update quality score 88 and review feedback for dendrogram-basic --- .../dendrogram-basic/metadata/matplotlib.yaml | 112 ++++++++++-------- 1 file changed, 60 insertions(+), 52 deletions(-) diff --git a/plots/dendrogram-basic/metadata/matplotlib.yaml b/plots/dendrogram-basic/metadata/matplotlib.yaml index 9255e2a080..bb9d8efec4 100644 --- a/plots/dendrogram-basic/metadata/matplotlib.yaml +++ b/plots/dendrogram-basic/metadata/matplotlib.yaml @@ -1,7 +1,7 @@ library: matplotlib specification_id: dendrogram-basic created: '2025-12-23T10:00:50Z' -updated: '2026-04-05T20:43:55Z' +updated: '2026-04-05T20:52:28Z' generated_by: claude-opus-4-6 workflow_run: 20457531070 issue: 0 @@ -13,39 +13,42 @@ quality_score: 88 impl_tags: dependencies: - scipy - techniques: - - manual-ticks + techniques: [] patterns: - data-generation - explicit-figure + - iteration-over-groups dataprep: - hierarchical-clustering styling: - grid-styling review: strengths: - - Excellent scipy/matplotlib integration with set_link_color_palette and LineCollection - post-processing for line styling - - Clean, realistic iris species data with proper clustering hierarchy and appropriate - measurements - - 'Professional visual polish: removed spines, subtle grid, custom background, refined - typography' - - Perfect spec compliance with correct title format and all required features + - Excellent code quality with clean KISS structure and full reproducibility + - 'Strong visual refinement: removed spines, subtle grid, custom background, round + line styling' + - Perfect spec compliance — all required features present with correct data mapping + - Realistic iris dataset with appropriate species-specific measurement distributions + - Distinctive LineCollection traversal technique for post-render enhancement weaknesses: - - Color threshold only distinguishes 2 visual clusters (Setosa vs rest) instead - of 3 species, weakening the data storytelling - - Leaf font size (15pt) slightly below the 16pt guideline for tick labels - - Minor label crowding at 35° rotation with 15 samples + - Only 2 cluster colors visible instead of 3 — the color_threshold is too high, + so Versicolor and Virginica share the same orange color, leaving the green palette + color unused + - X-axis labels slightly crowded despite rotation, particularly the longer Versicolor + names + - Data storytelling could be stronger if all 3 species were visually distinguished + by color image_description: 'The plot displays a vertical dendrogram of 15 iris flower samples clustered using Ward''s linkage method. The x-axis shows sample labels (Setosa-1 through Setosa-5, Versicolor-1 through Versicolor-5, Virginica-1 through Virginica-5) - rotated at ~35°. The y-axis shows "Ward Linkage Distance" ranging from 0 to ~10. - Two color-coded clusters are visible: Setosa samples in blue (left side, merging - at low distances ~0.3-1.0) and Versicolor+Virginica samples in orange (right side, - merging at distances ~0.4-4.0). A gray connector merges these two main groups - at ~10.2. The background is light gray (#FAFAFA), top and right spines are removed, - and a subtle y-axis grid is present. Lines are thick (3px) with round caps. The - title reads "Iris Species Clustering · dendrogram-basic · matplotlib · pyplots.ai".' + rotated at approximately 35 degrees. The y-axis shows "Ward Linkage Distance" + ranging from 0 to ~10.5. Two cluster colors are visible: blue (#306998) for the + Setosa group and orange (#D4722A) for the combined Versicolor/Virginica group, + with gray lines for above-threshold connections. The background is a light off-white + (#FAFAFA), top and right spines are removed, remaining spines are thin and light + gray. A subtle y-axis grid is present. Lines are thick (3.0) with rounded caps. + The title reads "Iris Species Clustering · dendrogram-basic · matplotlib · pyplots.ai" + in dark gray.' criteria_checklist: visual_quality: score: 28 @@ -56,40 +59,41 @@ review: score: 7 max: 8 passed: true - comment: All font sizes explicitly set (title 24, labels 20, ticks 16). Leaf - font at 15pt slightly below 16pt guideline. + comment: All font sizes explicitly set (title 24, labels 20, ticks 16, leaf + 15). Leaf font at 15pt slightly below 16pt guideline but readable. - id: VQ-02 name: No Overlap score: 5 max: 6 passed: true - comment: Labels rotated 35° and generally readable. Slight crowding between - adjacent Setosa labels. + comment: Labels rotated 35° but some crowding between adjacent labels, particularly + longer Versicolor names. - id: VQ-03 name: Element Visibility score: 6 max: 6 passed: true - comment: Dendrogram lines at 3.0 width with round caps/joins are clearly visible. + comment: Dendrogram lines at 3.0 width perfectly visible with round caps/joins. - id: VQ-04 name: Color Accessibility score: 4 max: 4 passed: true - comment: Blue and orange are colorblind-safe. Gray above-threshold connector - distinguishable. + comment: Blue and orange are colorblind-distinguishable. Gray for above-threshold + clearly differentiated. - id: VQ-05 name: Layout & Canvas score: 4 max: 4 passed: true - comment: Plot fills canvas well with balanced margins. + comment: Good proportions with tight_layout, plot fills canvas well, balanced + margins. - id: VQ-06 name: Axis Labels & Title score: 2 max: 2 passed: true - comment: 'Descriptive labels: Iris Sample and Ward Linkage Distance.' + comment: Descriptive labels. Ward linkage distance is unitless in this context. design_excellence: score: 14 max: 20 @@ -99,21 +103,22 @@ review: score: 6 max: 8 passed: true - comment: Custom palette, refined background, round line caps/joins. Above - defaults but not exceptional. + comment: Custom color palette, light background, thin spines, round line caps/joins. + Above defaults but not publication-showcase level. - id: DE-02 name: Visual Refinement score: 5 max: 6 passed: true - comment: Spines removed/thinned, subtle y-grid alpha=0.15, generous whitespace. + comment: Top/right spines removed, remaining spines thin and light, subtle + y-grid (alpha=0.15), generous whitespace. - id: DE-03 name: Data Storytelling score: 3 max: 6 passed: false - comment: Color threshold only produces 2 color groups instead of 3 species. - Misses opportunity to tell the full 3-species story. + comment: Only 2 cluster colors visible instead of 3. color_threshold too high, + Versicolor and Virginica share same orange color. spec_compliance: score: 15 max: 15 @@ -123,26 +128,27 @@ review: score: 5 max: 5 passed: true - comment: Correct dendrogram using scipy.cluster.hierarchy.dendrogram. + comment: Correct dendrogram visualization. - id: SC-02 name: Required Features score: 4 max: 4 passed: true - comment: 'All spec features present: features matrix, labels, linkage, vertical - orientation.' + comment: 'All required features present: features matrix, labels, linkage, + vertical orientation, proportional heights.' - id: SC-03 name: Data Mapping score: 3 max: 3 passed: true - comment: Labels on x-axis, distances on y-axis, proportional branch heights. + comment: Samples on x-axis, merge distance on y-axis, correct mapping. - id: SC-04 name: Title & Legend score: 3 max: 3 passed: true - comment: Title follows spec format. No legend needed for dendrogram. + comment: Title format correct with spec-id, library, pyplots.ai. No legend + needed. data_quality: score: 14 max: 15 @@ -152,20 +158,20 @@ review: score: 5 max: 6 passed: true - comment: Shows 3 species at varying merge distances. Only 2 color groups visible - instead of 3. + comment: Shows hierarchical structure with varying merge distances. Visual + doesn't fully distinguish all 3 species clusters due to color threshold. - id: DQ-02 name: Realistic Context score: 5 max: 5 passed: true - comment: Iris flower measurements - classic neutral botanical dataset. + comment: Iris flower dataset is classic, real-world, neutral science domain. - id: DQ-03 name: Appropriate Scale score: 4 max: 4 passed: true - comment: Realistic iris measurements in cm range. + comment: Realistic iris measurements with appropriate variance per species. code_quality: score: 10 max: 10 @@ -175,31 +181,32 @@ review: score: 3 max: 3 passed: true - comment: 'Clean flow: imports, data, compute, plot, style, save.' + comment: Clean imports → data → plot → save flow with no functions or classes. - id: CQ-02 name: Reproducibility score: 2 max: 2 passed: true - comment: np.random.seed(42) set. + comment: np.random.seed(42) set at the top. - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All imports used including LineCollection and scipy. + comment: All imports used. - id: CQ-04 name: Code Elegance score: 2 max: 2 passed: true - comment: Clean, appropriate complexity. + comment: Clean, Pythonic. LineCollection traversal for post-render styling + is elegant. - id: CQ-05 name: Output & API score: 1 max: 1 passed: true - comment: Saves as plot.png, dpi=300, current API. + comment: Saves as plot.png with dpi=300, bbox_inches=tight. library_mastery: score: 7 max: 10 @@ -209,12 +216,13 @@ review: score: 4 max: 5 passed: true - comment: Good scipy/matplotlib integration, axes-based approach, set_link_color_palette. + comment: Good use of scipy dendrogram() with ax parameter, set_link_color_palette + for color control. - id: LM-02 name: Distinctive Features score: 3 max: 5 passed: true - comment: LineCollection traversal and set_link_color_palette are matplotlib-specific - techniques. + comment: LineCollection traversal for post-render line styling and set_link_color_palette + are matplotlib/scipy-distinctive techniques. verdict: REJECTED From 7da80bebc136d4f9b8fa412358255639a936f648 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 5 Apr 2026 20:56:17 +0000 Subject: [PATCH 4/5] fix(matplotlib): address review feedback for dendrogram-basic Attempt 2/3 - fixes based on AI review --- .../dendrogram-basic/implementations/matplotlib.py | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/plots/dendrogram-basic/implementations/matplotlib.py b/plots/dendrogram-basic/implementations/matplotlib.py index 07eae961d5..9cca07045b 100644 --- a/plots/dendrogram-basic/implementations/matplotlib.py +++ b/plots/dendrogram-basic/implementations/matplotlib.py @@ -1,4 +1,4 @@ -""" pyplots.ai +"""pyplots.ai dendrogram-basic: Basic Dendrogram Library: matplotlib 3.10.8 | Python 3.14.3 Quality: 88/100 | Updated: 2026-04-05 @@ -66,14 +66,18 @@ cluster_colors = ["#306998", "#D4722A", "#3A8A5C"] set_link_color_palette(cluster_colors) +# Set threshold between the 2nd and 3rd highest merge distances to reveal 3 clusters +sorted_distances = sorted(linkage_matrix[:, 2]) +color_threshold = (sorted_distances[-2] + sorted_distances[-3]) / 2 + dendro = dendrogram( linkage_matrix, labels=labels, ax=ax, - leaf_rotation=35, - leaf_font_size=15, + leaf_rotation=40, + leaf_font_size=16, above_threshold_color="#AAAAAA", - color_threshold=0.7 * max(linkage_matrix[:, 2]), + color_threshold=color_threshold, ) # Post-render enhancement: adjust line widths via LineCollection traversal @@ -94,7 +98,7 @@ color="#333333", ) ax.tick_params(axis="both", labelsize=16, colors="#555555") -ax.tick_params(axis="x", labelsize=15, rotation=35) +ax.tick_params(axis="x", labelsize=16, rotation=40) ax.spines["top"].set_visible(False) ax.spines["right"].set_visible(False) From 35a1c1b8d6d79e662497b7ac326de747974d579c Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 5 Apr 2026 21:00:26 +0000 Subject: [PATCH 5/5] chore(matplotlib): update quality score 92 and review feedback for dendrogram-basic --- .../implementations/matplotlib.py | 4 +- .../dendrogram-basic/metadata/matplotlib.yaml | 142 +++++++++--------- 2 files changed, 72 insertions(+), 74 deletions(-) diff --git a/plots/dendrogram-basic/implementations/matplotlib.py b/plots/dendrogram-basic/implementations/matplotlib.py index 9cca07045b..9bfb284383 100644 --- a/plots/dendrogram-basic/implementations/matplotlib.py +++ b/plots/dendrogram-basic/implementations/matplotlib.py @@ -1,7 +1,7 @@ -"""pyplots.ai +""" pyplots.ai dendrogram-basic: Basic Dendrogram Library: matplotlib 3.10.8 | Python 3.14.3 -Quality: 88/100 | Updated: 2026-04-05 +Quality: 92/100 | Updated: 2026-04-05 """ import matplotlib.pyplot as plt diff --git a/plots/dendrogram-basic/metadata/matplotlib.yaml b/plots/dendrogram-basic/metadata/matplotlib.yaml index bb9d8efec4..503760cc92 100644 --- a/plots/dendrogram-basic/metadata/matplotlib.yaml +++ b/plots/dendrogram-basic/metadata/matplotlib.yaml @@ -1,7 +1,7 @@ library: matplotlib specification_id: dendrogram-basic created: '2025-12-23T10:00:50Z' -updated: '2026-04-05T20:52:28Z' +updated: '2026-04-05T21:00:26Z' generated_by: claude-opus-4-6 workflow_run: 20457531070 issue: 0 @@ -9,11 +9,12 @@ python_version: 3.14.3 library_version: 3.10.8 preview_url: https://storage.googleapis.com/pyplots-images/plots/dendrogram-basic/matplotlib/plot.png preview_html: null -quality_score: 88 +quality_score: 92 impl_tags: dependencies: - scipy - techniques: [] + techniques: + - manual-ticks patterns: - data-generation - explicit-figure @@ -24,78 +25,76 @@ impl_tags: - grid-styling review: strengths: - - Excellent code quality with clean KISS structure and full reproducibility - - 'Strong visual refinement: removed spines, subtle grid, custom background, round - line styling' - - Perfect spec compliance — all required features present with correct data mapping - - Realistic iris dataset with appropriate species-specific measurement distributions - - Distinctive LineCollection traversal technique for post-render enhancement + - Excellent visual quality with all font sizes explicitly set and no overlap issues + - Professional color palette with colorblind-safe colors and thoughtful use of color + threshold to reveal cluster structure + - 'Strong visual refinement: removed spines, subtle grid, light background, round + line caps create a polished look' + - Realistic iris flower data that perfectly demonstrates hierarchical clustering + with clear species separation + - Clean, linear code structure with good use of matplotlib-specific features like + LineCollection traversal weaknesses: - - Only 2 cluster colors visible instead of 3 — the color_threshold is too high, - so Versicolor and Virginica share the same orange color, leaving the green palette - color unused - - X-axis labels slightly crowded despite rotation, particularly the longer Versicolor - names - - Data storytelling could be stronger if all 3 species were visually distinguished - by color - image_description: 'The plot displays a vertical dendrogram of 15 iris flower samples - clustered using Ward''s linkage method. The x-axis shows sample labels (Setosa-1 - through Setosa-5, Versicolor-1 through Versicolor-5, Virginica-1 through Virginica-5) - rotated at approximately 35 degrees. The y-axis shows "Ward Linkage Distance" - ranging from 0 to ~10.5. Two cluster colors are visible: blue (#306998) for the - Setosa group and orange (#D4722A) for the combined Versicolor/Virginica group, - with gray lines for above-threshold connections. The background is a light off-white - (#FAFAFA), top and right spines are removed, remaining spines are thin and light - gray. A subtle y-axis grid is present. Lines are thick (3.0) with rounded caps. - The title reads "Iris Species Clustering · dendrogram-basic · matplotlib · pyplots.ai" - in dark gray.' + - 'Minor redundancy: tick_params rotation=40 duplicates dendrogram leaf_rotation=40' + image_description: 'The plot displays a dendrogram of 15 iris flower samples clustered + using Ward''s linkage method. Three distinct species clusters are clearly visible: + Setosa (blue, leftmost 5 samples), Versicolor (orange, middle 5 samples), and + Virginica (green, rightmost 5 samples). The x-axis is labeled "Iris Sample" with + rotated sample names (e.g., Setosa-4, Versicolor-1, Virginica-3). The y-axis shows + "Ward Linkage Distance" ranging from 0 to ~10. The title reads "Iris Species Clustering + · dendrogram-basic · matplotlib · pyplots.ai" in dark gray. Top and right spines + are removed, remaining spines are thin and light gray. A subtle y-axis grid (very + low alpha) aids distance reading. Branch lines are thick (3.0) with round caps. + Above-threshold merges connecting the three main clusters are rendered in gray. + Background is a very light gray (#FAFAFA). The Setosa cluster merges at the highest + distance (~10.2), indicating it is the most distinct species.' criteria_checklist: visual_quality: - score: 28 + score: 30 max: 30 items: - id: VQ-01 name: Text Legibility - score: 7 + score: 8 max: 8 passed: true - comment: All font sizes explicitly set (title 24, labels 20, ticks 16, leaf - 15). Leaf font at 15pt slightly below 16pt guideline but readable. + comment: 'All font sizes explicitly set: title 24pt, axis labels 20pt, tick/leaf + labels 16pt' - id: VQ-02 name: No Overlap - score: 5 + score: 6 max: 6 passed: true - comment: Labels rotated 35° but some crowding between adjacent labels, particularly - longer Versicolor names. + comment: X-axis labels rotated at 40 degrees with adequate spacing, no collisions - id: VQ-03 name: Element Visibility score: 6 max: 6 passed: true - comment: Dendrogram lines at 3.0 width perfectly visible with round caps/joins. + comment: Branch lines set to 3.0 width with round caps/joins, all structure + clearly visible - id: VQ-04 name: Color Accessibility score: 4 max: 4 passed: true - comment: Blue and orange are colorblind-distinguishable. Gray for above-threshold - clearly differentiated. + comment: Blue/orange/green palette is colorblind-safe with good luminance + contrast - id: VQ-05 name: Layout & Canvas score: 4 max: 4 passed: true - comment: Good proportions with tight_layout, plot fills canvas well, balanced - margins. + comment: 16:9 figure with tight_layout, plot fills canvas well with balanced + margins - id: VQ-06 name: Axis Labels & Title score: 2 max: 2 passed: true - comment: Descriptive labels. Ward linkage distance is unitless in this context. + comment: 'Descriptive labels: Iris Sample and Ward Linkage Distance' design_excellence: - score: 14 + score: 15 max: 20 items: - id: DE-01 @@ -103,22 +102,22 @@ review: score: 6 max: 8 passed: true - comment: Custom color palette, light background, thin spines, round line caps/joins. - Above defaults but not publication-showcase level. + comment: Custom color palette, thoughtful typography, professional and cohesive + design - id: DE-02 name: Visual Refinement score: 5 max: 6 passed: true - comment: Top/right spines removed, remaining spines thin and light, subtle - y-grid (alpha=0.15), generous whitespace. + comment: Spines removed, thin remaining spines, subtle grid, light background, + round line caps - id: DE-03 name: Data Storytelling - score: 3 + score: 4 max: 6 - passed: false - comment: Only 2 cluster colors visible instead of 3. color_threshold too high, - Versicolor and Virginica share same orange color. + passed: true + comment: Color threshold reveals 3 natural clusters, gray above-threshold + links de-emphasize high-level merges spec_compliance: score: 15 max: 15 @@ -128,50 +127,50 @@ review: score: 5 max: 5 passed: true - comment: Correct dendrogram visualization. + comment: Correct dendrogram visualization using scipy.cluster.hierarchy.dendrogram() - id: SC-02 name: Required Features score: 4 max: 4 passed: true - comment: 'All required features present: features matrix, labels, linkage, - vertical orientation, proportional heights.' + comment: Ward method, labeled samples, proportional branch heights, scipy + hierarchy used - id: SC-03 name: Data Mapping score: 3 max: 3 passed: true - comment: Samples on x-axis, merge distance on y-axis, correct mapping. + comment: Samples on x-axis, merge distances on y-axis, all 15 items visible - id: SC-04 name: Title & Legend score: 3 max: 3 passed: true - comment: Title format correct with spec-id, library, pyplots.ai. No legend - needed. + comment: Title includes dendrogram-basic · matplotlib · pyplots.ai with descriptive + prefix data_quality: - score: 14 + score: 15 max: 15 items: - id: DQ-01 name: Feature Coverage - score: 5 + score: 6 max: 6 passed: true - comment: Shows hierarchical structure with varying merge distances. Visual - doesn't fully distinguish all 3 species clusters due to color threshold. + comment: Multiple merge levels, varying distances, clear cluster separation + demonstrated - id: DQ-02 name: Realistic Context score: 5 max: 5 passed: true - comment: Iris flower dataset is classic, real-world, neutral science domain. + comment: Iris flower dataset - classic, real-world scientific scenario - id: DQ-03 name: Appropriate Scale score: 4 max: 4 passed: true - comment: Realistic iris measurements with appropriate variance per species. + comment: Realistic iris measurements, sensible Ward linkage distances code_quality: score: 10 max: 10 @@ -181,32 +180,32 @@ review: score: 3 max: 3 passed: true - comment: Clean imports → data → plot → save flow with no functions or classes. + comment: 'Linear flow: imports, data, linkage, plot, style, save. No functions + or classes' - id: CQ-02 name: Reproducibility score: 2 max: 2 passed: true - comment: np.random.seed(42) set at the top. + comment: np.random.seed(42) set at top - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All imports used. + comment: 'All imports used: plt, np, LineCollection, dendrogram/linkage/set_link_color_palette' - id: CQ-04 name: Code Elegance score: 2 max: 2 passed: true - comment: Clean, Pythonic. LineCollection traversal for post-render styling - is elegant. + comment: Clean, well-structured with appropriate use of LineCollection traversal - id: CQ-05 name: Output & API score: 1 max: 1 passed: true - comment: Saves as plot.png with dpi=300, bbox_inches=tight. + comment: Saves as plot.png at 300 DPI, no deprecated API library_mastery: score: 7 max: 10 @@ -216,13 +215,12 @@ review: score: 4 max: 5 passed: true - comment: Good use of scipy dendrogram() with ax parameter, set_link_color_palette - for color control. + comment: Axes-level methods, scipy dendrogram with ax parameter, set_link_color_palette - id: LM-02 name: Distinctive Features score: 3 max: 5 passed: true - comment: LineCollection traversal for post-render line styling and set_link_color_palette - are matplotlib/scipy-distinctive techniques. - verdict: REJECTED + comment: LineCollection traversal for post-render styling, direct spine/tick + manipulation + verdict: APPROVED