Converters

In [ ]:

"""# Convert & Upload Ray-tracing Dataset.

[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/DeepMIMO/DeepMIMO/blob/main/docs/tutorials/7_converters.py)
 
[![GitHub](https://img.shields.io/badge/Open_on-GitHub-181717?logo=github&style=for-the-badge)](https://github.com/DeepMIMO/DeepMIMO/blob/main/docs/tutorials/7_converters.py)

---

**Tutorial Overview:**
- From Wireless InSite - Convert from Wireless InSite ray tracer
- From Sionna RT - Convert from Sionna RT
- From AODT - Convert from AODT format
- Upload to DeepMIMO - Upload your datasets to the DeepMIMO database

**Related Videos:**
- [Convert Video](https://youtu.be/kXY2bMWeDgg)
- [Upload Video](https://youtu.be/tNF6TN_ueU4)

---
"""

"""# Convert & Upload Ray-tracing Dataset. [](https://colab.research.google.com/github/DeepMIMO/DeepMIMO/blob/main/docs/tutorials/7_converters.py)   [](https://github.com/DeepMIMO/DeepMIMO/blob/main/docs/tutorials/7_converters.py) --- **Tutorial Overview:** - From Wireless InSite - Convert from Wireless InSite ray tracer - From Sionna RT - Convert from Sionna RT - From AODT - Convert from AODT format - Upload to DeepMIMO - Upload your datasets to the DeepMIMO database **Related Videos:** - [Convert Video](https://youtu.be/kXY2bMWeDgg) - [Upload Video](https://youtu.be/tNF6TN_ueU4) --- """

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From Wireless InSite¶

Convert ray tracing data from Wireless InSite to DeepMIMO format.

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# Example: Convert from Wireless InSite
# NOTE: This requires Wireless InSite output files

# Define paths to Wireless InSite files
# insite_path = "/path/to/insite/output"
# output_path = "/path/to/deepmimo/output"

# Convert using the converter
# dm.convert(
#     source="wireless_insite",
#     input_path=insite_path,
#     output_path=output_path,
#     scenario_name="my_insite_scenario"
# )

print("Wireless InSite converter example (requires InSite files)")
print("See documentation for detailed usage")

# Example: Convert from Wireless InSite # NOTE: This requires Wireless InSite output files # Define paths to Wireless InSite files # insite_path = "/path/to/insite/output" # output_path = "/path/to/deepmimo/output" # Convert using the converter # dm.convert( # source="wireless_insite", # input_path=insite_path, # output_path=output_path, # scenario_name="my_insite_scenario" # ) print("Wireless InSite converter example (requires InSite files)") print("See documentation for detailed usage")

From Sionna RT¶

Convert from Sionna Ray Tracer.

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# Example: Export from Sionna RT to DeepMIMO
# NOTE: This requires Sionna RT to be installed and configured

# In your Sionna RT script, use the exporter:
example_code = """
# In Sionna:
from deepmimo.converters import sionna_exporter

# After running your Sionna RT simulation:
paths = scene.compute_paths()

# Export to DeepMIMO format
sionna_exporter(
    paths=paths,
    output_dir="./deepmimo_output",
    scenario_name="my_sionna_scenario"
)
"""

print("Sionna RT exporter example:")
print(example_code)

# Example: Export from Sionna RT to DeepMIMO # NOTE: This requires Sionna RT to be installed and configured # In your Sionna RT script, use the exporter: example_code = """ # In Sionna: from deepmimo.converters import sionna_exporter # After running your Sionna RT simulation: paths = scene.compute_paths() # Export to DeepMIMO format sionna_exporter( paths=paths, output_dir="./deepmimo_output", scenario_name="my_sionna_scenario" ) """ print("Sionna RT exporter example:") print(example_code)

From AODT¶

Convert from AODT (Autonomous Driving) dataset format.

In [ ]:

# Example: Convert from AODT
# NOTE: This requires AODT dataset files

# Define paths
# aodt_path = "/path/to/aodt/dataset"
# output_path = "/path/to/deepmimo/output"

# Convert using the AODT converter
# dm.convert(
#     source="aodt",
#     input_path=aodt_path,
#     output_path=output_path,
#     scenario_name="my_aodt_scenario"
# )

print("AODT converter example (requires AODT files)")
print("See documentation for detailed usage")

# Example: Convert from AODT # NOTE: This requires AODT dataset files # Define paths # aodt_path = "/path/to/aodt/dataset" # output_path = "/path/to/deepmimo/output" # Convert using the AODT converter # dm.convert( # source="aodt", # input_path=aodt_path, # output_path=output_path, # scenario_name="my_aodt_scenario" # ) print("AODT converter example (requires AODT files)") print("See documentation for detailed usage")

Upload to DeepMIMO¶

Upload your converted scenarios to the DeepMIMO database.

Upload Scenario Files¶

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# Example: Upload scenario to DeepMIMO database
# NOTE: This requires authentication credentials

# Upload scenario
# dm.upload(
#     scenario_path="/path/to/deepmimo/scenario",
#     scenario_name="my_custom_scenario",
#     description="Description of the scenario",
#     tags=["outdoor", "urban", "5G"],
#     api_key="your_api_key_here"
# )

print("Upload scenario example (requires API key)")
print("Visit deepmimo.net to get your API key")

# Example: Upload scenario to DeepMIMO database # NOTE: This requires authentication credentials # Upload scenario # dm.upload( # scenario_path="/path/to/deepmimo/scenario", # scenario_name="my_custom_scenario", # description="Description of the scenario", # tags=["outdoor", "urban", "5G"], # api_key="your_api_key_here" # ) print("Upload scenario example (requires API key)") print("Visit deepmimo.net to get your API key")

Upload Additional Images¶

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# Example: Upload scenario images/visualizations
# dm.upload_images(
#     scenario_name="my_custom_scenario",
#     image_paths=[
#         "/path/to/coverage_map.png",
#         "/path/to/3d_scene.png"
#     ],
#     api_key="your_api_key_here"
# )

print("Upload images example")

# Example: Upload scenario images/visualizations # dm.upload_images( # scenario_name="my_custom_scenario", # image_paths=[ # "/path/to/coverage_map.png", # "/path/to/3d_scene.png" # ], # api_key="your_api_key_here" # ) print("Upload images example")

Upload Ray Tracing Source Files¶

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# Example: Upload original ray tracing source files
# dm.upload_rt_source(
#     scenario_name="my_custom_scenario",
#     source_files=[
#         "/path/to/scene.xml",
#         "/path/to/materials.mat"
#     ],
#     ray_tracer="wireless_insite",  # or "sionna", "aodt"
#     api_key="your_api_key_here"
# )

print("Upload ray tracing source example")

# Example: Upload original ray tracing source files # dm.upload_rt_source( # scenario_name="my_custom_scenario", # source_files=[ # "/path/to/scene.xml", # "/path/to/materials.mat" # ], # ray_tracer="wireless_insite", # or "sionna", "aodt" # api_key="your_api_key_here" # ) print("Upload ray tracing source example")

Converter Workflow Example¶

Complete workflow from ray tracing to DeepMIMO format.

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# Step 1: Run ray tracing simulation
print("Step 1: Run your ray tracing simulation")
print("  - Configure scenario geometry")
print("  - Set TX/RX positions")
print("  - Run simulation")

# Step 2: Convert to DeepMIMO format
print("\nStep 2: Convert to DeepMIMO format")
print("  - Use appropriate converter (InSite, Sionna, AODT)")
print("  - Specify input/output paths")
print("  - Run conversion")

# Step 3: Validate converted data
print("\nStep 3: Validate converted data")
print("  - Load dataset with dm.load()")
print("  - Check data integrity")
print("  - Visualize results")

# Step 4: Upload to DeepMIMO (optional)
print("\nStep 4: Upload to DeepMIMO database (optional)")
print("  - Prepare scenario metadata")
print("  - Upload scenario files")
print("  - Share with community")

# Step 1: Run ray tracing simulation print("Step 1: Run your ray tracing simulation") print(" - Configure scenario geometry") print(" - Set TX/RX positions") print(" - Run simulation") # Step 2: Convert to DeepMIMO format print("\nStep 2: Convert to DeepMIMO format") print(" - Use appropriate converter (InSite, Sionna, AODT)") print(" - Specify input/output paths") print(" - Run conversion") # Step 3: Validate converted data print("\nStep 3: Validate converted data") print(" - Load dataset with dm.load()") print(" - Check data integrity") print(" - Visualize results") # Step 4: Upload to DeepMIMO (optional) print("\nStep 4: Upload to DeepMIMO database (optional)") print(" - Prepare scenario metadata") print(" - Upload scenario files") print(" - Share with community")

Validation After Conversion¶

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# After conversion, validate your data
# converted_scen = "my_converted_scenario"
# dataset = dm.load(converted_scen)

# Check basic properties
# print(f"Number of users: {len(dataset.power)}")
# print(f"Number of paths: {dataset.power.shape[1]}")
# print(f"Data matrices available: {dir(dataset)}")

# Visualize
# dataset.power.plot()
# plt.title('Converted Scenario - Power Coverage')
# plt.show()

print("Validation example (after successful conversion)")

# After conversion, validate your data # converted_scen = "my_converted_scenario" # dataset = dm.load(converted_scen) # Check basic properties # print(f"Number of users: {len(dataset.power)}") # print(f"Number of paths: {dataset.power.shape[1]}") # print(f"Data matrices available: {dir(dataset)}") # Visualize # dataset.power.plot() # plt.title('Converted Scenario - Power Coverage') # plt.show() print("Validation example (after successful conversion)")

Supported Ray Tracers¶

DeepMIMO supports conversion from:

1. Wireless InSite

   • Full 3D ray tracing
   • Supports all interaction types
   • Detailed material properties

2. Sionna RT

   • GPU-accelerated ray tracing
   • Differentiable ray tracer
   • TensorFlow integration

3. AODT

   • Autonomous driving scenarios
   • V2X communication
   • Mobility models

Best Practices¶

1. Organize your data: Keep source files well-organized
2. Document your scenario: Include metadata and descriptions
3. Validate thoroughly: Check converted data before uploading
4. Use meaningful names: Choose descriptive scenario names
5. Include visualizations: Upload coverage maps and 3D views

---

Next Steps¶

• Tutorial 8: Migration Guide - Migrating from DeepMIMO v3 to v4
• Return to Tutorial 1: Getting Started for more basic operations