app

app.py

@@ -1,96 +1,117 @@
-# /// script
-# dependencies = [
-#     "bpy==4.2.0",
-#     "marimo",
-#     "numpy==2.1.2",
-# ]
-# ///
-
 import marimo
 
-__generated_with = "0.9.9"
-app = marimo.App(width="medium")
-
-
-@app.cell
-def __():
-    import numpy
-    import bpy
-    import time
-    import random
-    import marimo as mo
-    import sys
-    import tempfile
-    print(sys.version)
-    return bpy, mo, numpy, random, sys, tempfile, time
+__generated_with = "0.9.20"
+app = marimo.App()
 
 
 @app.cell
 def __(mo):
-    w  = mo.ui.file(kind="area")
-    w
-    return (w,)
+    mo.md("""# Marimo + Blender""")
+    return
 
 
 @app.cell
-def __(tempfile, w):
-    file_content = w.contents()
-
-    # Create a temporary file to save the content
-    if file_content:
-        with tempfile.NamedTemporaryFile(suffix=".blend", delete=False) as temp_file:
-            temp_file.write(file_content)
-            temp_file_path = temp_file.name
-    return file_content, temp_file, temp_file_path
-
+def __():
+    #run with
+    #cd california_housing
+    #uv run marimo edit marimo_california.py 
+    import marimo as mo
+    import numpy as np
+    import polars as pl
+    import quak
+    import bpy
 
-@app.cell
-def __(mo):
-    dropdown = mo.ui.dropdown(
-        options={
-            "workbench": "BLENDER_WORKBENCH", 
-            "eevee": "BLENDER_EEVEE_NEXT", 
-            "cycles": "CYCLES"},
-        value="workbench",
-        label="choose renderer",
+    blend_file_path = "housing_data_igor.blend"
+    bpy.ops.wm.open_mainfile(filepath=blend_file_path)
+
+    bpy.context.scene.render.engine = "BLENDER_EEVEE_NEXT"
+    bpy.context.scene.render.resolution_x = 800
+    bpy.context.scene.render.resolution_y = 500
+
+    df = pl.read_csv("a_df.csv")
+    reference_frame = pl.read_csv("b_reference_frame.csv")
+
+    vertices = [(row["longitude_normalized"], row["latitude_normalized"], 0) for row in reference_frame.iter_rows(named=True)]
+
+    mesh = bpy.data.meshes.new("NormalizedMesh")
+    obj = bpy.data.objects.new("CaliforninaNormalizedObject", mesh)
+    bpy.context.collection.objects.link(obj)
+
+    mesh.from_pydata(vertices, [], [])
+    mesh.update()
+    obj.modifiers.new(name="GeometryNodes", type='NODES').node_group = bpy.data.node_groups["geo_house"]
+    bpy.context.view_layer.objects.active = obj
+    obj.select_set(True)
+    reference_frame.head()
+
+    def render_result():
+
+        bpy.ops.render.render()
+        bpy.data.images['Render Result'].save_render(filepath="img.png")
+        return mo.image(src="img.png")
+    return (
+        blend_file_path,
+        bpy,
+        df,
+        mesh,
+        mo,
+        np,
+        obj,
+        pl,
+        quak,
+        reference_frame,
+        render_result,
+        vertices,
     )
-    dropdown
-    return (dropdown,)
 
 
 @app.cell
-def __(bpy, dropdown, file_content, mo, temp_file_path, time):
-    start_time = time.time()
-
-    # Ensure Cycles is selected as the render engine for all view layers
-    for layer in bpy.context.scene.view_layers:
-        layer.cycles.use_denoising = False
-
-    # Set render samples to 10 for all view layers and the scene
-    bpy.context.scene.cycles.samples = 10
-
-    # Ensure to sync all settings
-    bpy.context.view_layer.update()
+def __(df, mo, quak):
+    widget = mo.ui.anywidget(quak.Widget(df))
+    widget
+    return (widget,)
 
 
-    # Load the temporary .blend file into Blender
-    if file_content:
-        bpy.ops.wm.open_mainfile(filepath=temp_file_path)
-
-    # Set render engine and resolution
-    bpy.context.scene.render.engine = dropdown.value
-    bpy.context.scene.render.resolution_x = 500
-    bpy.context.scene.render.resolution_y = 400
-    bpy.context.scene.cycles.samples = 5
-    # Render and save the image without any rotation
-    bpy.ops.render.render()
-    bpy.data.images["Render Result"].save_render(filepath="test.png")
-
-    end_time = time.time()
-    print(f"Script execution time: {end_time - start_time:.4f} seconds")
-
-    mo.image(src="test.png")
-    return end_time, layer, start_time
+@app.cell
+def __(np, obj, pl, reference_frame, render_result, widget):
+    widget_df = widget.data().pl()
+
+    plotting_frame = reference_frame.with_columns(
+        pl.lit(0).alias("custom_plotting")
+    ).join(
+        widget_df.select(["short_id", "median_house_value"]), 
+        on="short_id", 
+        how="left"
+    ).with_columns(
+        pl.when(pl.col("median_house_value").is_not_null())
+        .then(pl.col("median_house_value"))
+        .otherwise(pl.col("custom_plotting"))
+        .alias("custom_plotting")
+    ).select(["short_id", "custom_plotting"])
+
+    custom_plotting_list = plotting_frame["custom_plotting"].to_list()
+    normalized_values = list(np.interp(custom_plotting_list, 
+                                       (min(custom_plotting_list), max(custom_plotting_list)), 
+                                       (0.1, 3)))
+
+    attr_name = 'median_house_value'
+    attr = obj.data.attributes.get(attr_name) or obj.data.attributes.new(
+        name=attr_name,
+        type='FLOAT',
+        domain='POINT'
+    )
+    attr.data.foreach_set('value', normalized_values)
+    obj.data.update()
+
+    render_result()
+    return (
+        attr,
+        attr_name,
+        custom_plotting_list,
+        normalized_values,
+        plotting_frame,
+        widget_df,
+    )
 
 
 @app.cell

marimo_california.py

@@ -1,123 +0,0 @@
-import marimo
-
-__generated_with = "0.9.20"
-app = marimo.App()
-
-
-@app.cell
-def __(mo):
-    mo.md("""# Marimo + Blender""")
-    return
-
-
-@app.cell
-def __():
-    #run with
-    #cd california_housing
-    #uv run marimo edit marimo_california.py 
-    import marimo as mo
-    import numpy as np
-    import polars as pl
-    import quak
-    import bpy
-
-    blend_file_path = "housing_data_igor.blend"
-    bpy.ops.wm.open_mainfile(filepath=blend_file_path)
-
-    bpy.context.scene.render.engine = "BLENDER_EEVEE_NEXT"
-    bpy.context.scene.render.resolution_x = 800
-    bpy.context.scene.render.resolution_y = 500
-
-    df = pl.read_csv("a_df.csv")
-    reference_frame = pl.read_csv("b_reference_frame.csv")
-
-    vertices = [(row["longitude_normalized"], row["latitude_normalized"], 0) for row in reference_frame.iter_rows(named=True)]
-
-    mesh = bpy.data.meshes.new("NormalizedMesh")
-    obj = bpy.data.objects.new("CaliforninaNormalizedObject", mesh)
-    bpy.context.collection.objects.link(obj)
-
-    mesh.from_pydata(vertices, [], [])
-    mesh.update()
-    obj.modifiers.new(name="GeometryNodes", type='NODES').node_group = bpy.data.node_groups["geo_house"]
-    bpy.context.view_layer.objects.active = obj
-    obj.select_set(True)
-    reference_frame.head()
-
-    def render_result():
-
-        bpy.ops.render.render()
-        bpy.data.images['Render Result'].save_render(filepath="img.png")
-        return mo.image(src="img.png")
-    return (
-        blend_file_path,
-        bpy,
-        df,
-        mesh,
-        mo,
-        np,
-        obj,
-        pl,
-        quak,
-        reference_frame,
-        render_result,
-        vertices,
-    )
-
-
-@app.cell
-def __(df, mo, quak):
-    widget = mo.ui.anywidget(quak.Widget(df))
-    widget
-    return (widget,)
-
-
-@app.cell
-def __(np, obj, pl, reference_frame, render_result, widget):
-    widget_df = widget.data().pl()
-
-    plotting_frame = reference_frame.with_columns(
-        pl.lit(0).alias("custom_plotting")
-    ).join(
-        widget_df.select(["short_id", "median_house_value"]), 
-        on="short_id", 
-        how="left"
-    ).with_columns(
-        pl.when(pl.col("median_house_value").is_not_null())
-        .then(pl.col("median_house_value"))
-        .otherwise(pl.col("custom_plotting"))
-        .alias("custom_plotting")
-    ).select(["short_id", "custom_plotting"])
-
-    custom_plotting_list = plotting_frame["custom_plotting"].to_list()
-    normalized_values = list(np.interp(custom_plotting_list, 
-                                       (min(custom_plotting_list), max(custom_plotting_list)), 
-                                       (0.1, 3)))
-
-    attr_name = 'median_house_value'
-    attr = obj.data.attributes.get(attr_name) or obj.data.attributes.new(
-        name=attr_name,
-        type='FLOAT',
-        domain='POINT'
-    )
-    attr.data.foreach_set('value', normalized_values)
-    obj.data.update()
-
-    render_result()
-    return (
-        attr,
-        attr_name,
-        custom_plotting_list,
-        normalized_values,
-        plotting_frame,
-        widget_df,
-    )
-
-
-@app.cell
-def __():
-    return
-
-
-if __name__ == "__main__":
-    app.run()