update(raincloud-basic): plotnine — fix orientation consistency

Fix cloud/rain orientation: cloud (half-violin) extends upward, rain (jittered points) falls downward. Updated spec to clarify absolute y-direction terms.

Author: MarkusNeusinger

plots/raincloud-basic/implementations/plotnine.py

@@ -1,7 +1,7 @@
-""" pyplots.ai
+"""pyplots.ai
 raincloud-basic: Basic Raincloud Plot
-Library: plotnine 0.15.2 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-25
+Library: plotnine 0.15.3 | Python 3.14
+Quality: /100 | Updated: 2026-02-14
 """
 
 import numpy as np
@@ -13,106 +13,68 @@
     element_line,
     element_text,
     geom_boxplot,
-    geom_point,
-    geom_ribbon,
+    geom_jitter,
+    geom_violin,
     ggplot,
     labs,
     scale_color_manual,
     scale_fill_manual,
-    scale_x_continuous,
+    stage,
     theme,
     theme_minimal,
 )
-from scipy import stats
 
 
 # Data - Reaction times (ms) for three experimental conditions
 np.random.seed(42)
 
-# Control group: normal distribution centered at 450ms
 control = np.random.normal(450, 60, 80)
-
-# Treatment A: faster responses, centered at 380ms
 treatment_a = np.random.normal(380, 50, 80)
-
-# Treatment B: bimodal distribution (some fast responders, some slow)
 treatment_b = np.concatenate([np.random.normal(350, 40, 50), np.random.normal(500, 45, 30)])
 
-# Build dataframe with numeric x positions
 df = pd.DataFrame(
     {
-        "condition": ["Control"] * len(control)
-        + ["Treatment A"] * len(treatment_a)
-        + ["Treatment B"] * len(treatment_b),
+        "condition": (
+            ["Control"] * len(control) + ["Treatment A"] * len(treatment_a) + ["Treatment B"] * len(treatment_b)
+        ),
         "reaction_time": np.concatenate([control, treatment_a, treatment_b]),
     }
 )
+df["condition"] = pd.Categorical(df["condition"], categories=["Treatment B", "Treatment A", "Control"], ordered=True)
 
-# Map conditions to numeric positions (for coord_flip: higher = top)
-condition_map = {"Control": 2, "Treatment A": 1, "Treatment B": 0}
-df["x_pos"] = df["condition"].map(condition_map).astype(float)
-
-# Add jitter for rain points (below center, after coord_flip)
-np.random.seed(123)
-df["x_rain"] = df["x_pos"] - 0.22 + np.random.uniform(-0.06, 0.06, len(df))
-
-# Colors - dictionary mapping for condition names
+# Colors
 colors = {"Control": "#306998", "Treatment A": "#FFD43B", "Treatment B": "#5BA85B"}
 
-# Create half-violin (cloud) data using KDE
-# The cloud should be on TOP only (positive direction after coord_flip)
-cloud_dfs = []
-for cond, x_base in condition_map.items():
-    data = df[df["condition"] == cond]["reaction_time"].values
-    kde = stats.gaussian_kde(data)
-    y_range = np.linspace(data.min() - 10, data.max() + 10, 200)
-    density = kde(y_range)
-    # Normalize density and scale for visual width (half-violin on TOP only)
-    density_scaled = density / density.max() * 0.35
-    cloud_df = pd.DataFrame(
-        {
-            "reaction_time": y_range,
-            "ymin": x_base,  # Base position (center line)
-            "ymax": x_base + density_scaled,  # Extend upward only (becomes top after flip)
-            "condition": cond,
-        }
-    )
-    cloud_dfs.append(cloud_df)
+# Cloud shift (positive = right on pre-flip x-axis = upward after coord_flip)
+cloud_shift = 0.12
 
-cloud_data = pd.concat(cloud_dfs, ignore_index=True)
-
-# Create raincloud plot with horizontal orientation (coord_flip)
-# After flip: Cloud (half-violin) on TOP, boxplot centered, rain points BELOW
+# Plot - horizontal raincloud via coord_flip
+# Before flip: x=condition (categorical), y=reaction_time (numeric)
+# After flip: categories on y-axis, values on x-axis
 plot = (
-    ggplot()
-    # Half-violin (cloud) using geom_ribbon - extends from center to one side only
-    + geom_ribbon(
-        data=cloud_data,
-        mapping=aes(x="reaction_time", ymin="ymin", ymax="ymax", fill="condition"),
+    ggplot(df, aes(x="condition", y="reaction_time", fill="condition", color="condition"))
+    # Cloud (half-violin) - style="right" extends in positive x-direction = upward after flip
+    + geom_violin(
+        aes(x=stage("condition", after_scale="x+{0}".format(cloud_shift))),
+        style="right",
+        trim=True,
+        scale="width",
+        size=0.4,
         alpha=0.85,
         show_legend=False,
     )
-    # Box plot - centered, narrow, white fill
-    + geom_boxplot(
-        data=df,
-        mapping=aes(x="x_pos", y="reaction_time", group="condition"),
-        width=0.08,
-        outlier_shape="",
-        fill="white",
-        color="#333333",
-        size=0.6,
-        alpha=0.95,
-        show_legend=False,
-    )
-    # Jittered points (rain) - below the center line (after flip)
-    + geom_point(
-        data=df, mapping=aes(x="x_rain", y="reaction_time", color="condition"), size=2, alpha=0.6, show_legend=False
+    # Boxplot - centered on category baseline
+    + geom_boxplot(width=0.08, outlier_shape="", fill="white", color="#333333", size=0.6, alpha=0.95, show_legend=False)
+    # Rain (jittered points) - nudged in negative x-direction = downward after flip
+    + geom_jitter(
+        aes(x=stage("condition", after_scale="x-0.18")), width=0.06, height=0, size=1.8, alpha=0.6, show_legend=False
     )
     + scale_fill_manual(values=colors)
     + scale_color_manual(values=colors)
-    + scale_x_continuous(breaks=[0, 1, 2], labels=["Treatment B", "Treatment A", "Control"])
     + coord_flip()
-    + labs(x="Experimental Condition", y="Reaction Time (ms)", title="raincloud-basic · plotnine · pyplots.ai")
+    + labs(
+        x="Experimental Condition", y="Reaction Time (ms)", title="raincloud-basic \u00b7 plotnine \u00b7 pyplots.ai"
+    )
     + theme_minimal()
     + theme(
         figure_size=(16, 9),

plots/raincloud-basic/metadata/plotnine.yaml

@@ -1,16 +1,16 @@
 library: plotnine
 specification_id: raincloud-basic
 created: '2025-12-25T07:17:07Z'
-updated: '2025-12-25T07:34:53Z'
-generated_by: claude-opus-4-5-20251101
+updated: 2026-02-14T20:28:11+00:00
+generated_by: claude-opus-4-6
 workflow_run: 20500986130
 issue: 0
-python_version: 3.13.11
-library_version: 0.15.2
+python_version: "3.14"
+library_version: "0.15.3"
 preview_url: https://storage.googleapis.com/pyplots-images/plots/raincloud-basic/plotnine/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/raincloud-basic/plotnine/plot_thumb.png
 preview_html: null
-quality_score: 91
+quality_score: null
 impl_tags:
   dependencies:
   - scipy

plots/raincloud-basic/specification.md

@@ -20,10 +20,10 @@ A raincloud plot combines three visualization elements—a half-violin (the "clo
 
 ## Notes
 
-- **Required Orientation**: Use HORIZONTAL orientation with categories on y-axis and values on x-axis
-- **Critical Layout**: The "cloud" (half-violin/KDE) must be on TOP (positive y offset), boxplot in MIDDLE, and "rain" (jittered points) BELOW (negative y offset) - like rain falling from a cloud
+- **Required Orientation**: Use HORIZONTAL orientation with categories on y-axis and values on x-axis. "Above" and "below" always refer to the y-direction (screen up/down), not the x-direction
+- **Critical Layout**: For each category on the y-axis: the "cloud" (half-violin/KDE) must extend ABOVE the category baseline (upward on screen), the boxplot sits centered ON the category baseline, and "rain" (jittered points) must appear BELOW the category baseline (downward on screen) - like rain falling from a cloud
 - Clip the violin to show only half (the "cloud" portion), not a full violin
 - Use moderate jitter (0.05-0.1) to spread rain points without excessive overlap
 - Apply transparency (alpha 0.5-0.7) to jittered rain points for visibility
 - Include median and quartile markers in box plot
-- The visual metaphor must be clear: cloud above, rain falling below
+- The visual metaphor must be clear: cloud rises upward (positive y-direction), rain falls downward (negative y-direction) from each category line