feat(plotnine): implement spectrogram-basic (#2949)

## Implementation: `spectrogram-basic` - plotnine

Implements the **plotnine** version of `spectrogram-basic`.

**File:** `plots/spectrogram-basic/implementations/plotnine.py`

**Parent Issue:** #2927

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:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20612807474)*

---------

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/spectrogram-basic/implementations/plotnine.py

@@ -0,0 +1,58 @@
+""" pyplots.ai
+spectrogram-basic: Spectrogram Time-Frequency Heatmap
+Library: plotnine 0.15.2 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import numpy as np
+import pandas as pd
+from plotnine import aes, element_text, geom_tile, ggplot, labs, scale_fill_gradientn, theme, theme_minimal
+from scipy import signal
+
+
+# Data - Generate a chirp signal with increasing frequency
+np.random.seed(42)
+sample_rate = 1000  # Hz
+duration = 2.0  # seconds
+t = np.linspace(0, duration, int(sample_rate * duration))
+
+# Create chirp signal: frequency increases from 50 Hz to 200 Hz
+f0, f1 = 50, 200
+chirp_signal = signal.chirp(t, f0=f0, f1=f1, t1=duration, method="linear")
+chirp_signal += 0.3 * np.random.randn(len(chirp_signal))  # Add noise
+
+# Compute spectrogram using Short-Time Fourier Transform
+nperseg = 128
+noverlap = nperseg // 2
+frequencies, times, Sxx = signal.spectrogram(chirp_signal, fs=sample_rate, nperseg=nperseg, noverlap=noverlap)
+
+# Convert power to dB scale
+Sxx_db = 10 * np.log10(Sxx + 1e-10)
+
+# Create DataFrame for plotnine (convert 2D grid to long format)
+time_grid, freq_grid = np.meshgrid(times, frequencies)
+df = pd.DataFrame({"Time": time_grid.ravel(), "Frequency": freq_grid.ravel(), "Power": Sxx_db.ravel()})
+
+# Filter to relevant frequency range (0-500 Hz)
+df = df[df["Frequency"] <= 500]
+
+# Create spectrogram plot using geom_tile (heatmap)
+plot = (
+    ggplot(df, aes(x="Time", y="Frequency", fill="Power"))
+    + geom_tile()
+    + scale_fill_gradientn(colors=["#000033", "#306998", "#4A90A4", "#FFD43B", "#FFFFFF"], name="Power (dB)")
+    + labs(x="Time (s)", y="Frequency (Hz)", title="spectrogram-basic · plotnine · pyplots.ai")
+    + theme_minimal()
+    + theme(
+        figure_size=(16, 9),
+        text=element_text(size=14),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        plot_title=element_text(size=24),
+        legend_text=element_text(size=14),
+        legend_title=element_text(size=16),
+    )
+)
+
+# Save
+plot.save("plot.png", dpi=300, verbose=False)

plots/spectrogram-basic/metadata/plotnine.yaml

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+library: plotnine
+specification_id: spectrogram-basic
+created: '2025-12-31T05:33:26Z'
+updated: '2025-12-31T05:44:32Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20612807474
+issue: 2927
+python_version: 3.13.11
+library_version: 0.15.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/spectrogram-basic/plotnine/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/spectrogram-basic/plotnine/plot_thumb.png
+preview_html: null
+quality_score: 91
+review:
+  strengths:
+  - Clear visualization of chirp signal with frequency increasing over time
+  - Proper use of dB scale for power representation
+  - Well-formatted title following spec format exactly
+  - Good axis labels with units as specified
+  - Reproducible with fixed random seed
+  - Clean, readable KISS code structure
+  - Appropriate colormap that is perceptually reasonable
+  weaknesses:
+  - Custom color gradient could use a more perceptually uniform colormap like viridis
+    (spec recommends viridis/inferno)
+  - No grid lines to aid in reading specific time-frequency values
+  - Frequency axis filtered to 500 Hz when chirp only reaches 200 Hz - could be tighter
+    range for better visualization