feat(plotnine): implement piano-roll-midi

plots/piano-roll-midi/implementations/python/plotnine.py

@@ -1,9 +1,11 @@
-""" pyplots.ai
+""" anyplot.ai
 piano-roll-midi: MIDI Piano Roll Visualization
-Library: plotnine 0.15.3 | Python 3.14.3
-Quality: 91/100 | Created: 2026-03-07
+Library: plotnine 0.15.5 | Python 3.13.13
+Quality: 91/100 | Updated: 2026-06-03
 """
 
+import os
+
 import numpy as np
 import pandas as pd
 from plotnine import (
@@ -20,19 +22,34 @@
     ggplot,
     guide_colorbar,
     labs,
-    scale_fill_cmap,
+    scale_fill_gradient,
     scale_x_continuous,
     scale_y_continuous,
     theme,
     theme_void,
 )
 
 
-# Data - A short chord progression with melody (C major -> F major -> G major -> C major)
+# Theme tokens (Imprint palette, theme-adaptive chrome)
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
+
+# Piano key shading (theme-adaptive) — dark values boosted for visible contrast over #1A1A17
+WHITE_KEY_BG = "#EDE9DE" if THEME == "light" else "#272720"
+BLACK_KEY_BG = "#D8D4C8" if THEME == "light" else "#0D0D0B"
+BEAT_LINE = "#C4C0B4" if THEME == "light" else "#2C2C29"
+MEASURE_LINE = "#8A8780" if THEME == "light" else "#4A4A46"
+OCTAVE_LINE = "#ABA89C" if THEME == "light" else "#363632"
+
+# Data — C major → F major → G major → C major chord progression with melody
 np.random.seed(42)
 
 notes = [
-    # Measure 1: C major chord + melody (opening — mf)
+    # Measure 1: C major chord + melody (mf)
     (0.0, 2.0, 48, 80),  # C3 bass
     (0.0, 2.0, 52, 70),  # E3
     (0.0, 2.0, 55, 70),  # G3
@@ -42,17 +59,17 @@
     (2.0, 1.0, 65, 105),  # F4
     (3.0, 0.5, 64, 85),  # E4
     (3.5, 0.5, 62, 80),  # D4
-    # Measure 2: F major chord + melody (building — f to ff)
+    # Measure 2: F major chord + melody (f to ff)
     (4.0, 2.0, 53, 75),  # F3 bass
     (4.0, 2.0, 57, 65),  # A3
     (4.0, 2.0, 60, 65),  # C4
     (4.0, 1.0, 65, 110),  # F4 melody
     (5.0, 0.5, 67, 95),  # G4
     (5.5, 0.5, 69, 100),  # A4
-    (6.0, 1.5, 72, 115),  # C5 high point - CLIMAX
+    (6.0, 1.5, 72, 115),  # C5 — CLIMAX
     (7.5, 0.5, 69, 80),  # A4
     # Measure 3: G major chord + descending melody (diminuendo)
-    (8.0, 2.0, 50, 85),  # D3 bass (G/D inversion — tighter pitch range)
+    (8.0, 2.0, 50, 85),  # D3 bass (G/D inversion)
     (8.0, 2.0, 55, 70),  # G3
     (8.0, 2.0, 59, 70),  # B3
     (8.0, 1.0, 71, 105),  # B4 melody
@@ -61,121 +78,114 @@
     (10.0, 1.0, 65, 95),  # F4
     (11.0, 0.5, 64, 80),  # E4
     (11.5, 0.5, 62, 75),  # D4
-    # Measure 4: C major resolution (ending — p, fading)
+    # Measure 4: C major resolution (p, fading)
     (12.0, 2.0, 48, 90),  # C3 bass
     (12.0, 2.0, 52, 75),  # E3
     (12.0, 2.0, 55, 75),  # G3
-    (12.0, 3.0, 60, 110),  # C4 melody - long resolution
+    (12.0, 3.0, 60, 110),  # C4 — long resolution
     (14.0, 1.0, 64, 70),  # E4
-    (15.0, 1.0, 60, 60),  # C4 ending - soft fade
+    (15.0, 1.0, 60, 60),  # C4 — soft fade
 ]
 
 df = pd.DataFrame(notes, columns=["start", "duration", "pitch", "velocity"])
 df["end"] = df["start"] + df["duration"]
 df["ymin"] = df["pitch"] - 0.4
 df["ymax"] = df["pitch"] + 0.4
 
-# MIDI note name mapping
 note_names = ["C", "C♯", "D", "D♯", "E", "F", "F♯", "G", "G♯", "A", "A♯", "B"]
 
-pitch_min = df["pitch"].min() - 1
-pitch_max = df["pitch"].max() + 1
+pitch_min = int(df["pitch"].min()) - 1  # 47
+pitch_max = int(df["pitch"].max()) + 1  # 73
 
-# Background rows for black/white key distinction
+# Background rows — theme-adaptive black/white key shading
 black_key_semitones = {1, 3, 6, 8, 10}
-bg_rows = []
-for p in range(pitch_min, pitch_max + 1):
-    semitone = p % 12
-    is_black = semitone in black_key_semitones
-    bg_rows.append({"ymin": p - 0.5, "ymax": p + 0.5, "fill_color": "#e6e4ef" if is_black else "#f8f7fc"})
-
+bg_rows = [
+    {"ymin": p - 0.5, "ymax": p + 0.5, "fill_color": BLACK_KEY_BG if p % 12 in black_key_semitones else WHITE_KEY_BG}
+    for p in range(pitch_min, pitch_max + 1)
+]
 bg_df = pd.DataFrame(bg_rows)
 
-# Y-axis labels: show only white-key pitches and pitches with notes to reduce crowding
-used_pitches = set(df["pitch"].unique())
-pitch_labels_map = {p: f"{note_names[p % 12]}{p // 12 - 1}" for p in range(pitch_min, pitch_max + 1)}
-# Show white keys that have data, plus octave C notes for orientation
-white_key_semitones = {0, 2, 4, 5, 7, 9, 11}
-label_pitches = sorted(
-    {p for p in used_pitches if p % 12 in white_key_semitones}
-    | {p for p in range(pitch_min, pitch_max + 1) if p % 12 == 0}
-)
-label_names = [pitch_labels_map[p] for p in label_pitches]
+# Y-axis: C (octave markers) and G (dominant) only — avoids adjacent-label crowding
+label_pitches = sorted(p for p in range(pitch_min, pitch_max + 1) if p % 12 in {0, 7})
+label_names = [f"{note_names[p % 12]}{p // 12 - 1}" for p in label_pitches]
 
 # Measure structure
 total_beats = 16
 measure_lines = [0, 4, 8, 12, 16]
 beat_lines = [b for b in range(total_beats + 1) if b not in measure_lines]
 
-# Measure labels at top with chord names
+# Chord labels at measure tops
 measure_labels = pd.DataFrame(
-    {"x": [2, 6, 10, 14], "label": ["I  (C)", "IV  (F)", "V  (G)", "I  (C)"], "y": [pitch_max + 0.8] * 4}
+    {"x": [2, 6, 10, 14], "label": ["I  (C)", "IV  (F)", "V  (G)", "I  (C)"], "y": [pitch_max + 1.8] * 4}
 )
 
-# Dynamic markings to enhance storytelling
-dynamic_labels = pd.DataFrame({"x": [2, 6.5, 10, 14.5], "label": ["mf", "ff", "dim.", "p"], "y": [pitch_min - 0.3] * 4})
+# Dynamic markings below piano roll
+dynamic_labels = pd.DataFrame({"x": [2, 6.5, 10, 14.5], "label": ["mf", "ff", "dim.", "p"], "y": [pitch_min - 0.6] * 4})
 
-# Horizontal separators at octave boundaries (every C note)
+# Octave boundary lines at each C note
 octave_cs = [p for p in range(pitch_min, pitch_max + 1) if p % 12 == 0]
 octave_lines = pd.DataFrame(
     {"y": [c - 0.5 for c in octave_cs], "xstart": [-0.3] * len(octave_cs), "xend": [total_beats + 0.3] * len(octave_cs)}
 )
 
-# Plot using theme_void as base for maximum control (plotnine-distinctive)
+title = "piano-roll-midi · python · plotnine · anyplot.ai"
+
+# Plot
 plot = (
     ggplot()
-    # Background rows - alternating shading for black/white keys
+    # Background rows — black/white key distinction
     + geom_rect(
         bg_df,
         aes(xmin=-0.3, xmax=total_beats + 0.3, ymin="ymin", ymax="ymax"),
         fill=bg_df["fill_color"].tolist(),
         color=None,
         show_legend=False,
     )
-    # Beat grid lines (subtle)
-    + geom_vline(xintercept=beat_lines, color="#d4d2e0", size=0.25, linetype="dotted")
-    # Measure grid lines (stronger)
-    + geom_vline(xintercept=measure_lines, color="#9895b0", size=0.5, linetype="solid")
-    # Octave boundary lines
+    # Beat grid (subtle dotted)
+    + geom_vline(xintercept=beat_lines, color=BEAT_LINE, size=0.25, linetype="dotted")
+    # Measure boundaries (solid)
+    + geom_vline(xintercept=measure_lines, color=MEASURE_LINE, size=0.5, linetype="solid")
+    # Octave boundary lines (dashed)
     + geom_segment(
-        octave_lines, aes(x="xstart", xend="xend", y="y", yend="y"), color="#b0adc5", size=0.35, linetype="dashed"
+        octave_lines, aes(x="xstart", xend="xend", y="y", yend="y"), color=OCTAVE_LINE, size=0.35, linetype="dashed"
+    )
+    # Note rectangles — Imprint sequential colormap (green=soft → blue=loud)
+    + geom_rect(df, aes(xmin="start", xmax="end", ymin="ymin", ymax="ymax", fill="velocity"), color=INK, size=0.3)
+    # Climax annotation
+    + annotate("text", x=7.6, y=72 + 1.0, label="← climax", size=3.0, color="#AE3030", fontstyle="italic", ha="left")
+    # Chord labels at top of each measure
+    + geom_text(measure_labels, aes(x="x", y="y", label="label"), size=4.0, color=INK_SOFT, fontstyle="italic")
+    # Dynamic markings below
+    + geom_text(dynamic_labels, aes(x="x", y="y", label="label"), size=3.5, color=INK_MUTED, fontstyle="italic")
+    # Imprint sequential cmap: #009E73 (soft/piano) → #4467A3 (loud/forte)
+    + scale_fill_gradient(
+        low="#009E73", high="#4467A3", limits=(55, 120), name="Velocity", guide=guide_colorbar(nbin=200)
     )
-    # Note rectangles with velocity color mapping
-    + geom_rect(df, aes(xmin="start", xmax="end", ymin="ymin", ymax="ymax", fill="velocity"), color="#2d2a3e", size=0.3)
-    # Climax annotation using plotnine annotate
-    + annotate("text", x=7.6, y=72 + 1.0, label="← climax", size=9, color="#e05634", fontstyle="italic", ha="left")
-    # Measure chord labels at top
-    + geom_text(measure_labels, aes(x="x", y="y", label="label"), size=11, color="#4a4568", fontstyle="italic")
-    # Dynamic markings below the piano roll
-    + geom_text(dynamic_labels, aes(x="x", y="y", label="label"), size=9, color="#7a7590", fontstyle="italic")
-    # Color scale: viridis for perceptual uniformity and colorblind safety
-    + scale_fill_cmap(cmap_name="inferno", limits=(55, 120), name="Velocity", guide=guide_colorbar(nbin=200))
     + scale_y_continuous(breaks=label_pitches, labels=label_names, expand=(0.02, 0.02))
     + scale_x_continuous(breaks=measure_lines, labels=["0", "4", "8", "12", "16"], expand=(0.01, 0.01))
-    + coord_cartesian(xlim=(-0.3, total_beats + 0.3), ylim=(pitch_min - 1.2, pitch_max + 1.5))
-    + labs(x="Time (beats)", y="Pitch (note)", title="piano-roll-midi · plotnine · pyplots.ai")
-    # Start from theme_void for full control, then add back what we need
+    + coord_cartesian(xlim=(-0.3, total_beats + 0.3), ylim=(pitch_min - 1.5, pitch_max + 2.5))
+    + labs(x="Time (beats)", y="Pitch", title=title)
     + theme_void()
     + theme(
-        figure_size=(16, 9),
-        plot_title=element_text(size=24, weight="bold", color="#2d2a3e", margin={"b": 15}),
-        axis_title_x=element_text(size=20, color="#4a4568", margin={"t": 10}),
-        axis_title_y=element_text(size=20, color="#4a4568", margin={"r": 10}),
-        axis_text_x=element_text(size=16, color="#4a4568"),
-        axis_text_y=element_text(size=16, color="#4a4568"),
-        axis_ticks_major=element_line(color="#9895b0", size=0.5),
-        axis_ticks_length=4,
+        figure_size=(8, 4.5),
+        plot_title=element_text(size=12, weight="bold", color=INK, margin={"b": 8}),
+        axis_title_x=element_text(size=10, color=INK, margin={"t": 6}),
+        axis_title_y=element_text(size=10, color=INK, margin={"r": 6}),
+        axis_text_x=element_text(size=8, color=INK_SOFT),
+        axis_text_y=element_text(size=8, color=INK_SOFT),
+        axis_ticks_major=element_line(color=INK_SOFT, size=0.4),
+        axis_ticks_length=3,
         legend_position="right",
-        legend_title=element_text(size=16, color="#4a4568"),
-        legend_text=element_text(size=14, color="#4a4568"),
-        legend_background=element_rect(fill="#f8f7fc", color=None),
-        legend_key_height=40,
-        legend_key_width=12,
-        panel_background=element_rect(fill="#f8f7fc", color=None),
-        plot_background=element_rect(fill="white", color=None),
+        legend_title=element_text(size=8, color=INK),
+        legend_text=element_text(size=8, color=INK_SOFT),
+        legend_background=element_rect(fill=ELEVATED_BG, color=None),
+        legend_key_height=30,
+        legend_key_width=10,
+        panel_background=element_rect(fill=PAGE_BG, color=None),
+        plot_background=element_rect(fill=PAGE_BG, color=None),
         plot_margin=0.02,
     )
 )
 
 # Save
-plot.save("plot.png", dpi=300, verbose=False)
+plot.save(f"plot-{THEME}.png", dpi=400, width=8, height=4.5, units="in", verbose=False)