From ffc6179277de8afb26ec070347317623fe3c9fe5 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 12 Apr 2026 18:11:18 +0000 Subject: [PATCH 1/5] feat(altair): implement scatter-lag --- plots/scatter-lag/implementations/altair.py | 62 +++++++++++++++++++++ 1 file changed, 62 insertions(+) create mode 100644 plots/scatter-lag/implementations/altair.py diff --git a/plots/scatter-lag/implementations/altair.py b/plots/scatter-lag/implementations/altair.py new file mode 100644 index 0000000000..80be937ded --- /dev/null +++ b/plots/scatter-lag/implementations/altair.py @@ -0,0 +1,62 @@ +"""pyplots.ai +scatter-lag: Lag Plot for Time Series Autocorrelation Diagnosis +Library: altair | Python 3.13 +Quality: pending | Created: 2026-04-12 +""" + +import altair as alt +import numpy as np +import pandas as pd + + +# Data - synthetic AR(1) process with moderate autocorrelation +np.random.seed(42) +n_points = 500 +lag = 1 +phi = 0.85 +noise = np.random.normal(0, 1, n_points) +values = np.zeros(n_points) +values[0] = noise[0] +for i in range(1, n_points): + values[i] = phi * values[i - 1] + noise[i] + +df = pd.DataFrame({"y_t": values[:-lag], "y_t_lag": values[lag:], "time_index": np.arange(n_points - lag)}) + +# Reference line (y = x diagonal) +margin = 0.5 +axis_min = min(df["y_t"].min(), df["y_t_lag"].min()) - margin +axis_max = max(df["y_t"].max(), df["y_t_lag"].max()) + margin +ref_df = pd.DataFrame({"x": [axis_min, axis_max], "y": [axis_min, axis_max]}) + +# Plot +reference_line = alt.Chart(ref_df).mark_line(strokeDash=[8, 6], strokeWidth=2, color="#999999").encode(x="x:Q", y="y:Q") + +points = ( + alt.Chart(df) + .mark_point(size=120, filled=True, strokeWidth=0.8, stroke="white", opacity=0.7) + .encode( + x=alt.X("y_t:Q", title="y(t)", scale=alt.Scale(domain=[axis_min, axis_max])), + y=alt.Y("y_t_lag:Q", title="y(t + 1)", scale=alt.Scale(domain=[axis_min, axis_max])), + color=alt.Color( + "time_index:Q", + scale=alt.Scale(scheme="viridis"), + legend=alt.Legend( + title="Time Index", titleFontSize=16, labelFontSize=14, gradientLength=300, gradientThickness=16 + ), + ), + tooltip=["y_t:Q", "y_t_lag:Q", "time_index:Q"], + ) +) + +chart = ( + (reference_line + points) + .properties(width=1600, height=900, title=alt.Title("scatter-lag · altair · pyplots.ai", fontSize=28)) + .configure_axis( + labelFontSize=18, titleFontSize=22, grid=True, gridOpacity=0.2, gridWidth=0.8, domainColor="#333333" + ) + .configure_view(strokeWidth=0) +) + +# Save +chart.save("plot.png", scale_factor=3.0) +chart.save("plot.html") From 103360befbe8c1cf5fa22574cdbcbfee2b8e38ae Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 12 Apr 2026 18:11:37 +0000 Subject: [PATCH 2/5] chore(altair): add metadata for scatter-lag --- plots/scatter-lag/metadata/altair.yaml | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) create mode 100644 plots/scatter-lag/metadata/altair.yaml diff --git a/plots/scatter-lag/metadata/altair.yaml b/plots/scatter-lag/metadata/altair.yaml new file mode 100644 index 0000000000..e34d02a624 --- /dev/null +++ b/plots/scatter-lag/metadata/altair.yaml @@ -0,0 +1,18 @@ +# Per-library metadata for altair implementation of scatter-lag +# Auto-generated by impl-generate.yml + +library: altair +specification_id: scatter-lag +created: '2026-04-12T18:11:36Z' +updated: '2026-04-12T18:11:36Z' +generated_by: claude-opus-4-5-20251101 +workflow_run: 24313009897 +issue: 5251 +python_version: 3.14.3 +library_version: 6.0.0 +preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/altair/plot.png +preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/altair/plot.html +quality_score: null +review: + strengths: [] + weaknesses: [] From e3fb859b5654cddf77831d3814cee537b0f3435c Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 12 Apr 2026 18:16:40 +0000 Subject: [PATCH 3/5] chore(altair): update quality score 79 and review feedback for scatter-lag --- plots/scatter-lag/implementations/altair.py | 6 +- plots/scatter-lag/metadata/altair.yaml | 235 +++++++++++++++++++- 2 files changed, 231 insertions(+), 10 deletions(-) diff --git a/plots/scatter-lag/implementations/altair.py b/plots/scatter-lag/implementations/altair.py index 80be937ded..c971ed8ec3 100644 --- a/plots/scatter-lag/implementations/altair.py +++ b/plots/scatter-lag/implementations/altair.py @@ -1,7 +1,7 @@ -"""pyplots.ai +""" pyplots.ai scatter-lag: Lag Plot for Time Series Autocorrelation Diagnosis -Library: altair | Python 3.13 -Quality: pending | Created: 2026-04-12 +Library: altair 6.0.0 | Python 3.14.3 +Quality: 79/100 | Created: 2026-04-12 """ import altair as alt diff --git a/plots/scatter-lag/metadata/altair.yaml b/plots/scatter-lag/metadata/altair.yaml index e34d02a624..87be6719f4 100644 --- a/plots/scatter-lag/metadata/altair.yaml +++ b/plots/scatter-lag/metadata/altair.yaml @@ -1,10 +1,7 @@ -# Per-library metadata for altair implementation of scatter-lag -# Auto-generated by impl-generate.yml - library: altair specification_id: scatter-lag created: '2026-04-12T18:11:36Z' -updated: '2026-04-12T18:11:36Z' +updated: '2026-04-12T18:16:40Z' generated_by: claude-opus-4-5-20251101 workflow_run: 24313009897 issue: 5251 @@ -12,7 +9,231 @@ python_version: 3.14.3 library_version: 6.0.0 preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/altair/plot.png preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/altair/plot.html -quality_score: null +quality_score: 79 review: - strengths: [] - weaknesses: [] + strengths: + - 'Perfect spec compliance: diagonal reference line, viridis color encoding by time + index, correct axis labels, and required title format all present' + - 'Flawless code quality: reproducible seed, clean KISS structure, idiomatic Altair + layer composition' + - 'Excellent library usage: declarative encoding, proper configure_axis/configure_view, + correct PNG output at 4800x2700 px' + - Viridis colormap is colorblind-safe and visually communicates temporal order effectively + weaknesses: + - Point size (120) and opacity (0.7) are too large/opaque for 499 data points; causes + overplotting in center cluster; reduce to size ~50 and opacity ~0.45 + - Dense x-axis tick labels at 0.4-unit increments create a crowded axis; reduce + tick count to ~10-12 + - Missing correlation coefficient annotation (spec explicitly suggests r value); + this would significantly improve data storytelling + - Legend label font size (14pt) is below the minimum 16pt guideline + - No intentional visual hierarchy beyond color; design stays at well-configured + defaults level + image_description: The plot shows a scatter lag plot of approximately 499 points + from a synthetic AR(1) process (phi=0.85). Points are colored using the viridis + colormap — dark purple for early time indices and yellow-green for later — revealing + temporal structure in the autocorrelation. A dashed gray diagonal reference line + (y=x) traverses the chart, helping viewers assess autocorrelation strength. The + x-axis is labeled "y(t)" and the y-axis "y(t + 1)". Title reads "scatter-lag · + altair · pyplots.ai". A gradient colorbar legend on the right is labeled "Time + Index" (0–400). The overall pattern is a clear positive linear cluster along the + diagonal, visually confirming strong positive autocorrelation. Background is white + with very subtle gridlines. The x-axis has quite dense tick marks at 0.4 increments, + appearing crowded at display resolution. The center of the data cloud shows visible + overplotting due to the large marker size (120) and opacity (0.7). + criteria_checklist: + visual_quality: + score: 23 + max: 30 + items: + - id: VQ-01 + name: Text Legibility + score: 7 + max: 8 + passed: true + comment: All font sizes explicitly set (title 28pt, axis title 22pt, ticks + 18pt); legend labels at 14pt fall slightly below 16pt minimum guideline + - id: VQ-02 + name: No Overlap + score: 4 + max: 6 + passed: true + comment: X-axis tick labels at 0.4-unit intervals produce a dense label row; + visually crowded but no hard collision + - id: VQ-03 + name: Element Visibility + score: 3 + max: 6 + passed: false + comment: size=120 with opacity=0.7 for 499 points exceeds recommended 20-50/0.3-0.5 + for 300+ points; central cluster shows visible overplotting + - id: VQ-04 + name: Color Accessibility + score: 4 + max: 4 + passed: true + comment: Viridis is perceptually uniform and colorblind-safe; excellent choice + for sequential time index + - id: VQ-05 + name: Layout & Canvas + score: 3 + max: 4 + passed: true + comment: Good proportions; minor excess whitespace in top-right corner near + isolated legend + - id: VQ-06 + name: Axis Labels & Title + score: 2 + max: 2 + passed: true + comment: y(t) and y(t+1) are descriptive; title matches required scatter-lag + · altair · pyplots.ai format + design_excellence: + score: 10 + max: 20 + items: + - id: DE-01 + name: Aesthetic Sophistication + score: 4 + max: 8 + passed: false + comment: 'Well-configured Altair default: viridis and white point stroke add + polish, but no custom typography or intentional visual hierarchy beyond + color gradient' + - id: DE-02 + name: Visual Refinement + score: 3 + max: 6 + passed: false + comment: Grid opacity 0.2 and strokeWidth=0 show deliberate refinement; spines + not explicitly removed; legend feels disconnected + - id: DE-03 + name: Data Storytelling + score: 3 + max: 6 + passed: false + comment: Viridis temporal gradient is meaningful; diagonal reference line + frames the story; no correlation coefficient annotation to anchor interpretation + spec_compliance: + score: 15 + max: 15 + items: + - id: SC-01 + name: Plot Type + score: 5 + max: 5 + passed: true + comment: Correct lag scatter plot with y(t) on x-axis and y(t+1) on y-axis + - id: SC-02 + name: Required Features + score: 4 + max: 4 + passed: true + comment: Diagonal reference line, color by time index, configurable lag, AR(1) + data all present + - id: SC-03 + name: Data Mapping + score: 3 + max: 3 + passed: true + comment: X/Y correctly assigned; full data range visible + - id: SC-04 + name: Title & Legend + score: 3 + max: 3 + passed: true + comment: Title scatter-lag · altair · pyplots.ai is correct; Time Index legend + label appropriate + data_quality: + score: 13 + max: 15 + items: + - id: DQ-01 + name: Feature Coverage + score: 5 + max: 6 + passed: true + comment: 'Strong autocorrelation pattern clearly visible; minor deduction: + no contrast with uncorrelated data or varying lag orders' + - id: DQ-02 + name: Realistic Context + score: 4 + max: 5 + passed: true + comment: Synthetic AR(1) is listed in spec as valid example; plausible and + neutral; minor deduction for purely abstract labels + - id: DQ-03 + name: Appropriate Scale + score: 4 + max: 4 + passed: true + comment: Values ~-5 to +6 typical for zero-mean AR(1) with unit noise + code_quality: + score: 10 + max: 10 + items: + - id: CQ-01 + name: KISS Structure + score: 3 + max: 3 + passed: true + comment: 'Clean linear flow: imports, data, reference line, points, chart, + save; no functions or classes' + - id: CQ-02 + name: Reproducibility + score: 2 + max: 2 + passed: true + comment: np.random.seed(42) set + - id: CQ-03 + name: Clean Imports + score: 2 + max: 2 + passed: true + comment: Only altair, numpy, pandas; all used + - id: CQ-04 + name: Code Elegance + score: 2 + max: 2 + passed: true + comment: Well-organized; layer composition cleanly separates chart components + - id: CQ-05 + name: Output & API + score: 1 + max: 1 + passed: true + comment: chart.save(plot.png, scale_factor=3.0) correct; also saves HTML + library_mastery: + score: 8 + max: 10 + items: + - id: LM-01 + name: Idiomatic Usage + score: 5 + max: 5 + passed: true + comment: 'Excellent Altair: declarative encoding types (:Q), layer composition + via +, configure_axis/configure_view, alt.Scale and alt.Legend with full + parameterization' + - id: LM-02 + name: Distinctive Features + score: 3 + max: 5 + passed: false + comment: Layer composition and tooltip encoding are Altair-specific; no use + of selections, transforms (e.g., transform_calculate for lag), or interactive + brush selection + verdict: REJECTED +impl_tags: + dependencies: [] + techniques: + - layer-composition + - hover-tooltips + - html-export + patterns: + - data-generation + dataprep: [] + styling: + - alpha-blending + - custom-colormap + - edge-highlighting From 66286f14c70567e8b6d0b1eb5a0993c4619cb8a2 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 12 Apr 2026 18:19:52 +0000 Subject: [PATCH 4/5] fix(altair): address review feedback for scatter-lag Attempt 1/3 - fixes based on AI review --- plots/scatter-lag/implementations/altair.py | 74 +++++++++++++++++---- 1 file changed, 62 insertions(+), 12 deletions(-) diff --git a/plots/scatter-lag/implementations/altair.py b/plots/scatter-lag/implementations/altair.py index c971ed8ec3..5b412b30f9 100644 --- a/plots/scatter-lag/implementations/altair.py +++ b/plots/scatter-lag/implementations/altair.py @@ -1,4 +1,4 @@ -""" pyplots.ai +"""pyplots.ai scatter-lag: Lag Plot for Time Series Autocorrelation Diagnosis Library: altair 6.0.0 | Python 3.14.3 Quality: 79/100 | Created: 2026-04-12 @@ -20,7 +20,11 @@ for i in range(1, n_points): values[i] = phi * values[i - 1] + noise[i] -df = pd.DataFrame({"y_t": values[:-lag], "y_t_lag": values[lag:], "time_index": np.arange(n_points - lag)}) +y_t = values[:-lag] +y_t_lag = values[lag:] +r_value = np.corrcoef(y_t, y_t_lag)[0, 1] + +df = pd.DataFrame({"y_t": y_t, "y_t_lag": y_t_lag, "time_index": np.arange(n_points - lag)}) # Reference line (y = x diagonal) margin = 0.5 @@ -28,33 +32,79 @@ axis_max = max(df["y_t"].max(), df["y_t_lag"].max()) + margin ref_df = pd.DataFrame({"x": [axis_min, axis_max], "y": [axis_min, axis_max]}) -# Plot -reference_line = alt.Chart(ref_df).mark_line(strokeDash=[8, 6], strokeWidth=2, color="#999999").encode(x="x:Q", y="y:Q") +# Annotation for correlation coefficient +annot_df = pd.DataFrame({"x": [axis_max - 0.3], "y": [axis_min + 0.5], "label": [f"r = {r_value:.3f}"]}) + +# Reference line +reference_line = ( + alt.Chart(ref_df).mark_line(strokeDash=[8, 6], strokeWidth=1.5, color="#aaaaaa").encode(x="x:Q", y="y:Q") +) +# Scatter points with reduced size/opacity to prevent overplotting points = ( alt.Chart(df) - .mark_point(size=120, filled=True, strokeWidth=0.8, stroke="white", opacity=0.7) + .mark_point(size=45, filled=True, strokeWidth=0.5, stroke="white", opacity=0.45) .encode( - x=alt.X("y_t:Q", title="y(t)", scale=alt.Scale(domain=[axis_min, axis_max])), - y=alt.Y("y_t_lag:Q", title="y(t + 1)", scale=alt.Scale(domain=[axis_min, axis_max])), + x=alt.X("y_t:Q", title="y(t)", scale=alt.Scale(domain=[axis_min, axis_max]), axis=alt.Axis(tickCount=10)), + y=alt.Y( + "y_t_lag:Q", title="y(t + 1)", scale=alt.Scale(domain=[axis_min, axis_max]), axis=alt.Axis(tickCount=10) + ), color=alt.Color( "time_index:Q", scale=alt.Scale(scheme="viridis"), legend=alt.Legend( - title="Time Index", titleFontSize=16, labelFontSize=14, gradientLength=300, gradientThickness=16 + title="Time Index", + titleFontSize=16, + labelFontSize=16, + gradientLength=280, + gradientThickness=14, + orient="right", + offset=10, ), ), - tooltip=["y_t:Q", "y_t_lag:Q", "time_index:Q"], + tooltip=[ + alt.Tooltip("y_t:Q", title="y(t)", format=".2f"), + alt.Tooltip("y_t_lag:Q", title="y(t+1)", format=".2f"), + alt.Tooltip("time_index:Q", title="Time Index"), + ], ) ) +# Correlation annotation +annotation = ( + alt.Chart(annot_df) + .mark_text(align="right", baseline="bottom", fontSize=20, fontWeight="bold", color="#333333") + .encode(x="x:Q", y="y:Q", text="label:N") +) + chart = ( - (reference_line + points) - .properties(width=1600, height=900, title=alt.Title("scatter-lag · altair · pyplots.ai", fontSize=28)) + (reference_line + points + annotation) + .properties( + width=1600, + height=900, + title=alt.Title( + "scatter-lag · altair · pyplots.ai", + fontSize=28, + subtitle=f"AR(1) process (φ = {phi}) | lag = {lag}", + subtitleFontSize=18, + subtitleColor="#666666", + ), + ) .configure_axis( - labelFontSize=18, titleFontSize=22, grid=True, gridOpacity=0.2, gridWidth=0.8, domainColor="#333333" + labelFontSize=18, + titleFontSize=22, + grid=True, + gridOpacity=0.15, + gridWidth=0.5, + domainWidth=0, + tickSize=6, + tickWidth=0.8, + tickColor="#999999", + labelColor="#444444", + titleColor="#333333", ) .configure_view(strokeWidth=0) + .configure_title(anchor="start", offset=10) ) # Save From e0d9b316dce7d380f604e34a085198b04ba33a48 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 12 Apr 2026 18:24:57 +0000 Subject: [PATCH 5/5] chore(altair): update quality score 90 and review feedback for scatter-lag --- plots/scatter-lag/implementations/altair.py | 4 +- plots/scatter-lag/metadata/altair.yaml | 185 ++++++++++---------- 2 files changed, 94 insertions(+), 95 deletions(-) diff --git a/plots/scatter-lag/implementations/altair.py b/plots/scatter-lag/implementations/altair.py index 5b412b30f9..f49c4bcaf5 100644 --- a/plots/scatter-lag/implementations/altair.py +++ b/plots/scatter-lag/implementations/altair.py @@ -1,7 +1,7 @@ -"""pyplots.ai +""" pyplots.ai scatter-lag: Lag Plot for Time Series Autocorrelation Diagnosis Library: altair 6.0.0 | Python 3.14.3 -Quality: 79/100 | Created: 2026-04-12 +Quality: 90/100 | Created: 2026-04-12 """ import altair as alt diff --git a/plots/scatter-lag/metadata/altair.yaml b/plots/scatter-lag/metadata/altair.yaml index 87be6719f4..1e714cc04e 100644 --- a/plots/scatter-lag/metadata/altair.yaml +++ b/plots/scatter-lag/metadata/altair.yaml @@ -1,7 +1,7 @@ library: altair specification_id: scatter-lag created: '2026-04-12T18:11:36Z' -updated: '2026-04-12T18:16:40Z' +updated: '2026-04-12T18:24:56Z' generated_by: claude-opus-4-5-20251101 workflow_run: 24313009897 issue: 5251 @@ -9,111 +9,108 @@ python_version: 3.14.3 library_version: 6.0.0 preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/altair/plot.png preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/altair/plot.html -quality_score: 79 +quality_score: 90 review: strengths: - - 'Perfect spec compliance: diagonal reference line, viridis color encoding by time - index, correct axis labels, and required title format all present' - - 'Flawless code quality: reproducible seed, clean KISS structure, idiomatic Altair - layer composition' - - 'Excellent library usage: declarative encoding, proper configure_axis/configure_view, - correct PNG output at 4800x2700 px' - - Viridis colormap is colorblind-safe and visually communicates temporal order effectively + - Viridis colormap with opacity=0.45 and white edge strokes creates a professional, + layered look + - 'All required spec features present: diagonal reference line, time-index color + coding, correlation annotation, configurable lag' + - Altair layer composition (reference_line + points + annotation) is idiomatic and + clean + - Explicit font sizing throughout ensures legibility at 4800x2700px + - Subtle grid (opacity 0.15), no axis border, and removed domain line give a polished + clean background weaknesses: - - Point size (120) and opacity (0.7) are too large/opaque for 499 data points; causes - overplotting in center cluster; reduce to size ~50 and opacity ~0.45 - - Dense x-axis tick labels at 0.4-unit increments create a crowded axis; reduce - tick count to ~10-12 - - Missing correlation coefficient annotation (spec explicitly suggests r value); - this would significantly improve data storytelling - - Legend label font size (14pt) is below the minimum 16pt guideline - - No intentional visual hierarchy beyond color; design stays at well-configured - defaults level - image_description: The plot shows a scatter lag plot of approximately 499 points - from a synthetic AR(1) process (phi=0.85). Points are colored using the viridis - colormap — dark purple for early time indices and yellow-green for later — revealing - temporal structure in the autocorrelation. A dashed gray diagonal reference line - (y=x) traverses the chart, helping viewers assess autocorrelation strength. The - x-axis is labeled "y(t)" and the y-axis "y(t + 1)". Title reads "scatter-lag · - altair · pyplots.ai". A gradient colorbar legend on the right is labeled "Time - Index" (0–400). The overall pattern is a clear positive linear cluster along the - diagonal, visually confirming strong positive autocorrelation. Background is white - with very subtle gridlines. The x-axis has quite dense tick marks at 0.4 increments, - appearing crowded at display resolution. The center of the data cloud shows visible - overplotting due to the large marker size (120) and opacity (0.7). + - DE-01 held back by lacking a truly distinctive visual signature (e.g., custom + highlight color, marginal distribution element) + - DE-02 could reach 6/6 with more generous outer padding and intentional whitespace + strategy + - 'VQ-06 partial: axis labels use mathematical notation without physical units (appropriate + for abstract data but not 2/2)' + - 'LM-02: could leverage Altair''s selection/brush interactivity or faceting to + show multiple lag values side-by-side' + image_description: A scatter lag plot showing 499 points from a synthetic AR(1) + process (phi=0.85). The x-axis is labeled "y(t)" and the y-axis "y(t + 1)", both + ranging from about -5 to 6. Points are colored using the viridis colormap (purple/blue + = early time index, yellow-green = late time index), with opacity=0.45 and white + edge strokes. A dashed gray diagonal reference line (y=x) runs from bottom-left + to top-right, making the strong positive autocorrelation immediately visible. + A bold "r = 0.834" annotation appears in the lower-right of the plot area. The + title reads "scatter-lag · altair · pyplots.ai" with subtitle "AR(1) process (phi + = 0.85) | lag = 1". A vertical viridis color legend labeled "Time Index" is positioned + on the right. The background is white with an extremely subtle grid, no axis border, + and clean typography throughout. criteria_checklist: visual_quality: - score: 23 + score: 29 max: 30 items: - id: VQ-01 name: Text Legibility - score: 7 + score: 8 max: 8 passed: true - comment: All font sizes explicitly set (title 28pt, axis title 22pt, ticks - 18pt); legend labels at 14pt fall slightly below 16pt minimum guideline + comment: 'All font sizes explicitly set: title 28pt, subtitle 18pt, axis titles + 22pt, tick labels 18pt, legend 16pt, annotation 20pt bold' - id: VQ-02 name: No Overlap - score: 4 + score: 6 max: 6 passed: true - comment: X-axis tick labels at 0.4-unit intervals produce a dense label row; - visually crowded but no hard collision + comment: No text or data element collisions. Legend well-separated from plot + area. - id: VQ-03 name: Element Visibility - score: 3 + score: 6 max: 6 - passed: false - comment: size=120 with opacity=0.7 for 499 points exceeds recommended 20-50/0.3-0.5 - for 300+ points; central cluster shows visible overplotting + passed: true + comment: 500 points at size=45, opacity=0.45. Matches 300+ guideline. White + strokes help distinguish overlapping points. - id: VQ-04 name: Color Accessibility score: 4 max: 4 passed: true - comment: Viridis is perceptually uniform and colorblind-safe; excellent choice - for sequential time index + comment: Viridis is perceptually uniform and colorblind-safe. - id: VQ-05 name: Layout & Canvas - score: 3 + score: 4 max: 4 passed: true - comment: Good proportions; minor excess whitespace in top-right corner near - isolated legend + comment: Plot fills ~70% of canvas with balanced margins. Well-distributed + elements. - id: VQ-06 name: Axis Labels & Title - score: 2 + score: 1 max: 2 passed: true - comment: y(t) and y(t+1) are descriptive; title matches required scatter-lag - · altair · pyplots.ai format + comment: Labels y(t) and y(t+1) are descriptive but carry no physical units. design_excellence: - score: 10 + score: 13 max: 20 items: - id: DE-01 name: Aesthetic Sophistication - score: 4 + score: 5 max: 8 - passed: false - comment: 'Well-configured Altair default: viridis and white point stroke add - polish, but no custom typography or intentional visual hierarchy beyond - color gradient' + passed: true + comment: 'Above defaults: viridis colormap, opacity with white edge strokes, + dashed reference line, no border/domain lines. Cohesive but not publication-ready.' - id: DE-02 name: Visual Refinement - score: 3 + score: 4 max: 6 - passed: false - comment: Grid opacity 0.2 and strokeWidth=0 show deliberate refinement; spines - not explicitly removed; legend feels disconnected + passed: true + comment: Subtle grid (0.15 opacity), removed axis border, no domain line, + soft tick colors. More refined than defaults. - id: DE-03 name: Data Storytelling - score: 3 + score: 4 max: 6 - passed: false - comment: Viridis temporal gradient is meaningful; diagonal reference line - frames the story; no correlation coefficient annotation to anchor interpretation + passed: true + comment: r=0.834 annotation quantifies the pattern; time coloring reveals + temporal structure; diagonal reference guides interpretation. spec_compliance: score: 15 max: 15 @@ -123,51 +120,52 @@ review: score: 5 max: 5 passed: true - comment: Correct lag scatter plot with y(t) on x-axis and y(t+1) on y-axis + comment: 'Correct lag plot: scatter of y(t) vs y(t+k).' - id: SC-02 name: Required Features score: 4 max: 4 passed: true - comment: Diagonal reference line, color by time index, configurable lag, AR(1) - data all present + comment: Diagonal reference line, color by time index, correlation annotation, + configurable lag variable all present. - id: SC-03 name: Data Mapping score: 3 max: 3 passed: true - comment: X/Y correctly assigned; full data range visible + comment: X=y(t), Y=y(t+1). Correct orientation. All 499 points visible. - id: SC-04 name: Title & Legend score: 3 max: 3 passed: true - comment: Title scatter-lag · altair · pyplots.ai is correct; Time Index legend - label appropriate + comment: Title exactly 'scatter-lag · altair · pyplots.ai'. Legend labeled + 'Time Index'. data_quality: - score: 13 + score: 15 max: 15 items: - id: DQ-01 name: Feature Coverage - score: 5 + score: 6 max: 6 passed: true - comment: 'Strong autocorrelation pattern clearly visible; minor deduction: - no contrast with uncorrelated data or varying lag orders' + comment: 'Shows all key aspects: autocorrelation pattern, diagonal reference, + temporal coloring, correlation quantification.' - id: DQ-02 name: Realistic Context - score: 4 + score: 5 max: 5 passed: true - comment: Synthetic AR(1) is listed in spec as valid example; plausible and - neutral; minor deduction for purely abstract labels + comment: AR(1) process (phi=0.85) is a real, neutral statistical scenario. + Parameters clearly labeled in subtitle. - id: DQ-03 name: Appropriate Scale score: 4 max: 4 passed: true - comment: Values ~-5 to +6 typical for zero-mean AR(1) with unit noise + comment: 500 observations with realistic AR(1) value range (~-5 to 6). Correlation + r=0.834 expected for phi=0.85. code_quality: score: 10 max: 10 @@ -177,33 +175,35 @@ review: score: 3 max: 3 passed: true - comment: 'Clean linear flow: imports, data, reference line, points, chart, - save; no functions or classes' + comment: 'Linear: imports -> data -> chart layers -> save. 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. - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: Only altair, numpy, pandas; all used + comment: altair, numpy, pandas — all used, none unnecessary. - id: CQ-04 name: Code Elegance score: 2 max: 2 passed: true - comment: Well-organized; layer composition cleanly separates chart components + comment: Layer composition (reference_line + points + annotation) is clean + and idiomatic Altair. - id: CQ-05 name: Output & API score: 1 max: 1 passed: true - comment: chart.save(plot.png, scale_factor=3.0) correct; also saves HTML - library_mastery: + comment: Saves plot.png with scale_factor=3.0 and plot.html. Current altair + 6.0.0 API. + library_features: score: 8 max: 10 items: @@ -212,28 +212,27 @@ review: score: 5 max: 5 passed: true - comment: 'Excellent Altair: declarative encoding types (:Q), layer composition - via +, configure_axis/configure_view, alt.Scale and alt.Legend with full - parameterization' + comment: 'Expert Altair: declarative encoding with typed fields (Q/N), layer + composition via +, alt.Scale/Axis/Legend, configure_* global styling.' - id: LM-02 name: Distinctive Features score: 3 max: 5 - passed: false - comment: Layer composition and tooltip encoding are Altair-specific; no use - of selections, transforms (e.g., transform_calculate for lag), or interactive - brush selection - verdict: REJECTED + passed: true + comment: Layer composition, interactive tooltips, HTML export, declarative + viridis scheme. Distinctly Altair but basic within library capabilities. + verdict: APPROVED impl_tags: dependencies: [] techniques: - layer-composition + - annotations - hover-tooltips - html-export patterns: - data-generation dataprep: [] styling: - - alpha-blending - custom-colormap + - alpha-blending - edge-highlighting