init

.gitignore

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+__pycache__/

JTS_assets/ridge.map

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+11.692 8.6 1 0 0 The Sand Pit

README.md

@@ -1,8 +1,8 @@
 ---
 title: JTS3DMap
 emoji: 📚
-colorFrom: pink
-colorTo: green
+colorFrom: red
+colorTo: blue
 sdk: gradio
 sdk_version: 3.35.2
 app_file: app.py

app.py

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+import gradio as gr
+
+from pythonnet import load
+
+load("coreclr", runtime_config="lib\JTSParser.runtimeconfig.json")
+
+import clr
+from System import Reflection
+
+import os
+
+lib_path = os.path.abspath("lib\JTSParser.dll")
+
+Reflection.Assembly.LoadFile(lib_path)
+import YYZ.JTS.NB
+
+import numpy as np
+import plotly.graph_objects as go
+import math
+
+"""
+def greet(name):
+    return "Hello " + name + "!"
+
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+"""
+
+def test():
+    fig = go.Figure()
+
+    fig.add_trace(go.Scatter3d(
+        x=["2017-01-01", "2017-02-10", "2017-03-20"],
+        y=["A", "B", "C"],
+        z=[1, 1000, 100000],
+        name="z",
+    ))
+
+    fig.update_layout(
+        scene=dict(
+            xaxis=dict(type="date"),
+            yaxis=dict(type="category"),
+            zaxis=dict(type="log"),
+            annotations=[
+            dict(
+                showarrow=False,
+                x="2017-01-01",
+                y="A",
+                z=0,
+                text="Point 1",
+                xanchor="left",
+                xshift=10,
+                opacity=0.7),
+            dict(
+                x="2017-02-10",
+                y="B",
+                z=4,
+                text="Point 2",
+                textangle=0,
+                ax=0,
+                ay=-75,
+                font=dict(
+                    color="black",
+                    size=12
+                ),
+                arrowcolor="black",
+                arrowsize=3,
+                arrowwidth=1,
+                arrowhead=1),
+            dict(
+                x="2017-03-20",
+                y="C",
+                z=5,
+                ax=50,
+                ay=0,
+                text="Point 3",
+                arrowhead=1,
+                xanchor="left",
+                yanchor="bottom"
+            )]
+        ),
+    )
+    return fig
+
+
+def dock(x, limit):
+    x1 = math.floor(x)
+    yield x1
+    x2 = min(math.ceil(x), limit)
+    if x2 != x1:
+        yield x2
+
+default_path = "JTS_assets/ridge.map"
+
+with gr.Blocks(analytics_enabled=False) as demo:
+    with gr.Row():
+        with gr.Column(scale=1):
+            file_input = gr.File(default_path, label="Map File (NB or CWB)", file_types=[".map"])
+            labels_checkbox = gr.Checkbox(True, label="Labels")
+            labels_size_threshold_number = gr.Number(0, label="Label Size Threshold", info="1 => Tactical, 2 => Normal, 3 => Important")
+            # with gr.Row():
+            with gr.Accordion("Roads"):
+                with gr.Row():
+                    path_checkbox = gr.Checkbox(label="Path")
+                    road_checkbox = gr.Checkbox(label="Road")
+                    pike_checkbox = gr.Checkbox(True, label="Pike")
+                    railway_checkbox = gr.Checkbox(True, label="Railway")
+            with gr.Row():
+                road_offset_number = gr.Number(0.3, label="Road Offset")
+                elevation_scale_number = gr.Number(0.1, label="Elevation Scale")
+            plot_button = gr.Button("Plot")
+        with gr.Column(scale=2):
+            output_plot = gr.Plot()
+    
+    def plot(data):
+        with open(data[file_input].name) as f:
+            map_str = f.read()
+        map_file = YYZ.JTS.NB.MapFile.Parse(map_str)
+        graph = YYZ.JTS.NB.InfantryColumnGraph.FromMapFile(map_file)
+        height_mat = np.empty([map_file.Height, map_file.Width])
+        for i in range(map_file.Height):
+            for j in range(map_file.Width):
+                height_mat[i,j] = graph.HexMat[i, j].Height
+
+        surface = go.Surface(
+            x = np.arange(map_file.Width),
+            y = np.arange(map_file.Height),
+            z = height_mat
+        )
+
+        gl = []
+
+        road_offset = data[road_offset_number]
+
+        road_items = [
+            (YYZ.JTS.NB.RoadType.Path, path_checkbox, 'gray'),
+            (YYZ.JTS.NB.RoadType.Road, road_checkbox, 'green'),
+            (YYZ.JTS.NB.RoadType.Pike, pike_checkbox, 'pink'),
+            (YYZ.JTS.NB.RoadType.Railway, railway_checkbox, 'black')
+        ]
+
+        for road_type, checkbox, color in road_items:
+            if data[checkbox]:
+                for road in graph.SimplifyRoad(road_type):
+                    x_line = []
+                    y_line = []
+                    z_line = []
+
+                    for node in road:
+                        x_line.append(node.X)
+                        y_line.append(node.Y)
+                        z_line.append(node.Height + road_offset)
+                        
+                    g = go.Scatter3d(
+                        x=x_line, y=y_line, z=z_line,
+                        line=dict(
+                            color=color,
+                            width=2
+                        )
+                    )
+                    
+                    gl.append(g)
+
+        fig = go.Figure([surface] + gl)
+
+
+        scene = {
+            "aspectratio": {"x": 1, "y": 1, "z": data[elevation_scale_number]},
+            'yaxis': {'autorange': 'reversed'},
+        }
+
+        if data[labels_checkbox]:
+
+            labels_x = []
+            labels_y = []
+            labels_z = []
+            labels_text = []
+
+            for label in map_file.Labels:
+                if label.Size >= data[labels_size_threshold_number]:
+                    max_height = -1
+                    x = label.X
+                    y = label.Y
+                    for dx in dock(x, map_file.Width-1):
+                        for dy in dock(y, map_file.Height-1):
+                            max_height = max(max_height, map_file.HeightMap[dy, dx])
+                    labels_x.append(x)
+                    labels_y.append(y)
+                    labels_z.append(max_height)
+                    labels_text.append(label.Name)
+
+            scene["annotations"] = [
+                dict(
+                    showarrow=False,
+                    x=x,
+                    y=y,
+                    z=z,
+                    text=text,
+                    xanchor="left",
+                    xshift=10,
+                    opacity=0.7,
+                    bgcolor="white"
+                )
+                for x, y, z, text in zip(labels_x, labels_y, labels_z, labels_text)
+            ]
+
+        fig.update_layout(scene=scene, showlegend=False)
+
+        return {output_plot: fig}
+
+    plot_button.click(plot, {file_input, 
+                             labels_checkbox, labels_size_threshold_number, 
+                             path_checkbox, road_checkbox, pike_checkbox, railway_checkbox,
+                             elevation_scale_number, road_offset_number}, {output_plot})
+    # plot_button.click(lambda data: {output_img: test()}, {file_input, path_checkbox, road_checkbox, pike_checkbox, plot_button}, {output_img})
+
+if __name__ == "__main__":
+    demo.launch()

lib/JTSParser.runtimeconfig.json

@@ -0,0 +1,9 @@
+{
+  "runtimeOptions": {
+    "tfm": "net6.0",
+    "framework": {
+      "name": "Microsoft.NETCore.App",
+      "version": "6.0.0"
+    }
+  }
+}

requirements.txt

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+plotly
+numpy
+pythonnet