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NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/agents/configs/llm_pysc2/config_harass.py | llm_pysc2/agents/configs/llm_pysc2/config_harass.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/agents/configs/llm_pysc2/config_defend.py | llm_pysc2/agents/configs/llm_pysc2/config_defend.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/experiment_llm_pysc2.py | llm_pysc2/bin/experiment_llm_pysc2.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/experiment_llm_smac.py | llm_pysc2/bin/experiment_llm_smac.py |
# Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appl... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/2c_vs_64zg.py | llm_pysc2/bin/llm_smac/2c_vs_64zg.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/3s_vs_5z.py | llm_pysc2/bin/llm_smac/3s_vs_5z.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
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# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/3s5z_vs_3s6z.py | llm_pysc2/bin/llm_smac/3s5z_vs_3s6z.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/2s_vs_1sc.py | llm_pysc2/bin/llm_smac/2s_vs_1sc.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/3s_vs_3z.py | llm_pysc2/bin/llm_smac/3s_vs_3z.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/2s3z.py | llm_pysc2/bin/llm_smac/2s3z.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/1c3s5z.py | llm_pysc2/bin/llm_smac/1c3s5z.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/3s_vs_4z.py | llm_pysc2/bin/llm_smac/3s_vs_4z.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_smac/3s5z.py | llm_pysc2/bin/llm_smac/3s5z.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task2.py | llm_pysc2/bin/llm_pysc2/pvz_task2.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task7.py | llm_pysc2/bin/llm_pysc2/pvz_task7.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task4.py | llm_pysc2/bin/llm_pysc2/pvz_task4.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task5.py | llm_pysc2/bin/llm_pysc2/pvz_task5.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task8.py | llm_pysc2/bin/llm_pysc2/pvz_task8.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task1.py | llm_pysc2/bin/llm_pysc2/pvz_task1.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task3.py | llm_pysc2/bin/llm_pysc2/pvz_task3.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/bin/llm_pysc2/pvz_task6.py | llm_pysc2/bin/llm_pysc2/pvz_task6.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/maps/__init__.py | llm_pysc2/maps/__init__.py | # Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
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# You may obtain a copy of the License at
#
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# Unless required by applicable law or ... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/maps/llm_smac.py | llm_pysc2/maps/llm_smac.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/maps/llm_pysc2.py | llm_pysc2/maps/llm_pysc2.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/llm_client.py | llm_pysc2/lib/llm_client.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/llm_communicate.py | llm_pysc2/lib/llm_communicate.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/llm_observation.py | llm_pysc2/lib/llm_observation.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | true |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/llm_prompt.py | llm_pysc2/lib/llm_prompt.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/utils.py | llm_pysc2/lib/utils.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/llm_action.py | llm_pysc2/lib/llm_action.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | true |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/__init__.py | llm_pysc2/lib/__init__.py | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false | |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/log_analyse.py | llm_pysc2/lib/log_analyse.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/log_show.py | llm_pysc2/lib/log_show.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/data_recorder.py | llm_pysc2/lib/data_recorder.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/knowledge/zerg.py | llm_pysc2/lib/knowledge/zerg.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | true |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/knowledge/protoss.py | llm_pysc2/lib/knowledge/protoss.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | true |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/knowledge/terran.py | llm_pysc2/lib/knowledge/terran.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | true |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/knowledge/__init__.py | llm_pysc2/lib/knowledge/__init__.py |
from llm_pysc2.lib.knowledge.neutral import DATA_NEUTRAL
from llm_pysc2.lib.knowledge.protoss import DATA_PROTOSS
from llm_pysc2.lib.knowledge.terran import DATA_TERRAN
from llm_pysc2.lib.knowledge.zerg import DATA_ZERG
| python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
NKAI-Decision-Team/LLM-PySC2 | https://github.com/NKAI-Decision-Team/LLM-PySC2/blob/551c863475c0c4a96a181080974d24b59589e9f3/llm_pysc2/lib/knowledge/neutral.py | llm_pysc2/lib/knowledge/neutral.py | # Copyright 2024, LLM-PySC2 Contributors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | python | Apache-2.0 | 551c863475c0c4a96a181080974d24b59589e9f3 | 2026-01-05T07:14:50.369338Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/setup.py | setup.py | #!/usr/bin/env python
# coding: utf-8
import io
import os
import sys
from shutil import rmtree
from distutils.core import setup
from setuptools import find_packages, setup, Command
# Package meta-data.
NAME = 'xflow-net'
DESCRIPTION = 'a python library for graph flow'
URL = 'https://xflow.network/'
EMAIL = 'zchen@cse... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/util.py | xflow/util.py | import random
import xflow.method.cosasi as co
import numpy as np
# TODO make seeds changable
# def run (graph, diffusion, seeds, method, eval, epoch, budget, output):
def run (graph, diffusion, method, eval, epoch, budget, output):
print("Running " + eval.upper() + " :")
for graph_fn in graph:
try:
... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/seed.py | xflow/seed.py | import numpy as np
import torch_geometric.datasets as ds
import random
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
def random(seed):
random.seed(seed)
np.random.seed(seed)
return seed
# todo
def degree():
return
# todo
def eigen():
return | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/test_forwards.py | xflow/test_forwards.py | import numpy as np
import random
import networkx as nx
from networkx import Graph
from torch_geometric.data.data import Data
from . import xflow
from xflow.dataset.nx import connSW
from xflow.flow_tasks import forward, backward, graph_eval
graph_size = 1000
graph_beta = 0.1
infection_beta = None
infection_gamma = None... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/__init__.py | xflow/__init__.py | import xflow.method
import xflow.dataset
import xflow.diffusion
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/test_backwards.py | xflow/test_backwards.py | import numpy as np
import random
import networkx as nx
from networkx import Graph
from torch_geometric.data.data import Data
from . import xflow
from xflow.dataset.nx import connSW
from xflow.flow_tasks import forward, backward, graph_eval
# def main():
# print("Testing local XFlow package")
# if __name__ == "__m... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/flow_tasks.py | xflow/flow_tasks.py | # pip dependencies
#!pip install torch
#!pip install torch_geometric==2.2.0
#!pip install xflow-net==0.0.21
#!pip install networkx
#!pip install ndlib
#!pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.2.0+cpu.html
#!pip install torch_geometric_temporal
... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/visualization/multinet_vis.py | xflow/visualization/multinet_vis.py | # imports
import dash
import random
from dash import dcc
from dash import html
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import networkx as nx
import ndlib.models.epidemics as ep
from ndlib.models.ModelConfig import Configuration
import pandas as pd
from dash import dash_table
# - - - ... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/visualization/entropy_demo_2.py | xflow/visualization/entropy_demo_2.py | # -*- coding: utf-8 -*-
"""IJCAI Demo.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1Rslj_mz0mLHeSsNpEqWY7bneliHBmLhD
"""
# !pip install -U dash==1.19.0
# !pip install --upgrade dash werkzeug
# !pip install ndlib
import dash
from dash import... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/visualization/entropy_demo.py | xflow/visualization/entropy_demo.py | # -*- coding: utf-8 -*-
"""IJCAI Demo.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1Rslj_mz0mLHeSsNpEqWY7bneliHBmLhD
"""
# !pip install -U dash==1.19.0
# !pip install --upgrade dash werkzeug
# !pip install ndlib
import dash
from dash import... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/ibm.py | xflow/method/ibm.py | import networkx as nx
import numpy as np
import ndlib
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
import statistics as s
import random
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import time
import random
from xflow.diffusion.SI import SI
from xflow.diffusion.IC ... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/im.py | xflow/method/im.py | import networkx as nx
import numpy as np
import ndlib
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
import statistics as s
import random
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import time
from random import uniform, seed
from collections import Counter
import... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/__init__.py | xflow/method/__init__.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/sl.py | xflow/method/sl.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/__init__.py | xflow/method/cosasi/__init__.py | from .contagion import *
from .source_inference import *
from .benchmark import *
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/benchmark/benchmark.py | xflow/method/cosasi/benchmark/benchmark.py | import random
import os, sys
import json
sys.path.insert(0, os.getcwd())
import numpy as np
import networkx as nx
import cosasi
MODULE_PATH = __file__[: -len("benchmark.py")]
MODULE_PATH = (
MODULE_PATH
if len(MODULE_PATH) > 0 and (MODULE_PATH[-1] == "/" or MODULE_PATH[-1] == "\\")
else MODULE_PATH + "/... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/benchmark/__init__.py | xflow/method/cosasi/benchmark/__init__.py | from .benchmark import *
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/benchmark/tests/__init__.py | xflow/method/cosasi/benchmark/tests/__init__.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/benchmark/tests/test_benchmark.py | xflow/method/cosasi/benchmark/tests/test_benchmark.py | import os, sys
sys.path.insert(0, os.getcwd())
import pytest
from unittest import TestCase
import networkx as nx
import numpy as np
import cosasi
class Test_BenchmarkFromSimulation(TestCase):
def setUp(self):
self.number_infected_init = 3
self.sim_steps = 100
self.G = nx.fast_gnp_random... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/utils/estimators.py | xflow/method/cosasi/utils/estimators.py | import math
import random
import warnings
import scipy
import numpy as np
import networkx as nx
from sklearn.cluster import SpectralClustering
from .helpers import attack_degree, attack_degree_partition
from ..source_inference.multiple_source import netsleuth
def source_subgraphs(I, number_sources=2):
"""Subdiv... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/utils/helpers.py | xflow/method/cosasi/utils/helpers.py | import operator
import functools
import numpy as np
import networkx as nx
def list_product(l):
"""Returns the product the elements of a list.
Parameters
----------
l : list
list of elements you want to multiply
"""
return functools.reduce(operator.mul, l, 1)
def longest_list(l):
... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/utils/__init__.py | xflow/method/cosasi/utils/__init__.py | from .helpers import *
from . import estimators
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/utils/tests/test_estimators.py | xflow/method/cosasi/utils/tests/test_estimators.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import cosasi
class TestEstimators(TestCase):
def setUp(self):
self.G = self.G = nx.gnp_random_graph(50, 0.2)
contagion = cosasi.StaticNetworkContagion(
... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/utils/tests/__init__.py | xflow/method/cosasi/utils/tests/__init__.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/utils/tests/test_helpers.py | xflow/method/cosasi/utils/tests/test_helpers.py | import os, sys
sys.path.insert(0, os.getcwd())
import pytest
import networkx as nx
import numpy as np
import random
from cosasi import utils
def test_list_product():
l = [1]
assert utils.list_product(l) == 1
l += [2]
assert utils.list_product(l) == 2
l += [-3]
assert utils.list_product(l) =... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/contagion/static_network_contagion.py | xflow/method/cosasi/contagion/static_network_contagion.py | import random
import numpy as np
import operator
import networkx as nx
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
class StaticNetworkContagion:
"""A stochastic epidemic process defined on a static network.
Parameters
----------
G : NetworkX Graph
The network fo... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/contagion/__init__.py | xflow/method/cosasi/contagion/__init__.py | from .static_network_contagion import *
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/contagion/tests/__init__.py | xflow/method/cosasi/contagion/tests/__init__.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/contagion/tests/test_static_network_contagion.py | xflow/method/cosasi/contagion/tests/test_static_network_contagion.py | import os, sys
import collections
sys.path.insert(0, os.getcwd())
import pytest
from unittest import TestCase
import networkx as nx
import numpy as np
import cosasi
class Test_StaticNetworkContagion(TestCase):
def setUp(self):
self.number_infected_init = 10
self.sim_steps = 10
self.G = ... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/__init__.py | xflow/method/cosasi/source_inference/__init__.py | from . import single_source
from . import multiple_source
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/source_results.py | xflow/method/cosasi/source_inference/source_results.py | """Generic objects for the result of single-source and multi-source localization.
All inference algorithms should return an instance of one of these classes.
"""
import json
from collections import Counter
from collections.abc import Iterable
import itertools
import numpy as np
import networkx as nx
MODULE_PATH = _... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/tests/test_source_results.py | xflow/method/cosasi/source_inference/tests/test_source_results.py | import os, sys
import pytest
import itertools
import random
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import networkx as nx
import numpy as np
import cosasi
from ..source_results import SourceResult, SingleSourceResult, MultiSourceResult, node_set_distance
def test_node_set_distance():
G ... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/tests/__init__.py | xflow/method/cosasi/source_inference/tests/__init__.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/lisn.py | xflow/method/cosasi/source_inference/multiple_source/lisn.py | import itertools
import networkx as nx
import numpy as np
from ..source_results import MultiSourceResult
from ...utils import estimators
from .. import single_source
def fast_multisource_lisn(I, G, t, number_sources=None):
"""Greedily runs single-source LISN algorithm on each estimated infection
subgraph at... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/jordan.py | xflow/method/cosasi/source_inference/multiple_source/jordan.py | import itertools
import networkx as nx
import numpy as np
from ..source_results import MultiSourceResult
from ...utils import estimators
from .. import single_source
def fast_multisource_jordan_centrality(I, G, number_sources=None):
"""Greedily runs single-source Jordan centrality on each estimated infection
... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/netsleuth.py | xflow/method/cosasi/source_inference/multiple_source/netsleuth.py | import itertools
import networkx as nx
import numpy as np
from ..source_results import MultiSourceResult
from ...utils import estimators
from .. import single_source
def netsleuth(I, G, hypotheses_per_step=1):
"""Implements the multi-source NETSLEUTH algorithm to score combinations
of nodes in G.
Param... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/__init__.py | xflow/method/cosasi/source_inference/multiple_source/__init__.py | from .netsleuth import *
from .jordan import *
from .lisn import *
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/tests/test_netsleuth.py | xflow/method/cosasi/source_inference/multiple_source/tests/test_netsleuth.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import random
import math
import cosasi
class TestNETSLEUTH(TestCase):
def setUp(self):
self.G = nx.complete_graph(n=100)
contagion = cosasi.StaticNetworkContagio... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/tests/test_lisn.py | xflow/method/cosasi/source_inference/multiple_source/tests/test_lisn.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import cosasi
class TestLISN(TestCase):
def setUp(self):
self.G = nx.complete_graph(n=100)
contagion = cosasi.StaticNetworkContagion(
G=self.G, model="si", infection_rat... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/tests/__init__.py | xflow/method/cosasi/source_inference/multiple_source/tests/__init__.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/multiple_source/tests/test_jordan.py | xflow/method/cosasi/source_inference/multiple_source/tests/test_jordan.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import cosasi
class TestJordan(TestCase):
def setUp(self):
self.G = nx.complete_graph(n=100)
contagion = cosasi.StaticNetworkContagion(
G=self.G, model="si", infection_r... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/lisn.py | xflow/method/cosasi/source_inference/single_source/lisn.py | import math
import networkx as nx
import numpy as np
import scipy as sp
from ..source_results import SingleSourceResult
def lisn(I, G, t=None, infection_rate=0.1):
"""Implements the algorithm from Localizing the Information Source in a Network to
score all nodes in G [1]_.
Parameters
----------
... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/jordan.py | xflow/method/cosasi/source_inference/single_source/jordan.py | import networkx as nx
import numpy as np
from ...utils import soft_eccentricity
from ..source_results import SingleSourceResult
def jordan_centrality(I, G):
"""Computes the infection eccentricity of each node in the infection subgraph. To
produce a score with highest value corresponding to the Jordan center,... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/netsleuth.py | xflow/method/cosasi/source_inference/single_source/netsleuth.py | import networkx as nx
import numpy as np
import warnings
from ..source_results import SingleSourceResult
def netsleuth(I, G):
"""Implements the single-source NETSLEUTH algorithm to score all nodes in G.
Parameters
----------
I : NetworkX Graph
The infection subgraph observed at a particular ... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/__init__.py | xflow/method/cosasi/source_inference/single_source/__init__.py | from .rumor_centrality import *
from .short_fat_tree import *
from .netsleuth import *
from .jordan import *
from .lisn import *
from .earliest_infection_first import *
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/short_fat_tree.py | xflow/method/cosasi/source_inference/single_source/short_fat_tree.py | import math
import random
import networkx as nx
import numpy as np
from ...utils import longest_list_len
from ..source_results import SingleSourceResult
def short_fat_tree(I, G, infection_rate=0.1):
"""Implements the Short-Fat-Tree (SFT) algorithm to score all nodes in G.
Parameters
----------
I : ... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/rumor_centrality.py | xflow/method/cosasi/source_inference/single_source/rumor_centrality.py | import math
import random
import networkx as nx
from ...utils import list_product
from ..source_results import SingleSourceResult
def rumor_centrality_root(I, v, return_all_values=True):
"""Computes rumor centrality for all nodes, assuming a spanning tree rooted at v.
Parameters
----------
I : Netw... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/earliest_infection_first.py | xflow/method/cosasi/source_inference/single_source/earliest_infection_first.py | import random
import networkx as nx
import numpy as np
from ...utils import soft_eccentricity
from ..source_results import SingleSourceResult
def earliest_infection_first(I, G, observer_dict):
"""Implements the Earliest Infection First algorithm to score all nodes in I.
This algorithm is useful if some inf... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/tests/test_netsleuth.py | xflow/method/cosasi/source_inference/single_source/tests/test_netsleuth.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import random
import math
import cosasi
class TestNETSLEUTH(TestCase):
def setUp(self):
self.G = nx.random_tree(n=500, seed=0)
contagion = cosasi.StaticNetworkCon... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/tests/test_lisn.py | xflow/method/cosasi/source_inference/single_source/tests/test_lisn.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import random
import cosasi
class TestLISN(TestCase):
def setUp(self):
self.G = nx.random_tree(n=500, seed=0)
contagion = cosasi.StaticNetworkContagion(
... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/tests/test_earliest_infection_first.py | xflow/method/cosasi/source_inference/single_source/tests/test_earliest_infection_first.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import random
import cosasi
class TestEarliestInfectionFirst(TestCase):
def setUp(self):
self.G = nx.fast_gnp_random_graph(100, 0.25)
contagion = cosasi.StaticNet... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/tests/test_short_fat_tree.py | xflow/method/cosasi/source_inference/single_source/tests/test_short_fat_tree.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import random
import math
import cosasi
class TestShortFatTree(TestCase):
def setUp(self):
self.G = nx.random_tree(n=500, seed=0)
contagion = cosasi.StaticNetwork... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/tests/test_rumor_centrality.py | xflow/method/cosasi/source_inference/single_source/tests/test_rumor_centrality.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import random
import cosasi
class TestRumorCentrality(TestCase):
def setUp(self):
self.G = nx.random_tree(n=500, seed=0)
contagion = cosasi.StaticNetworkContagion... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/tests/__init__.py | xflow/method/cosasi/source_inference/single_source/tests/__init__.py | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false | |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/method/cosasi/source_inference/single_source/tests/test_jordan.py | xflow/method/cosasi/source_inference/single_source/tests/test_jordan.py | import os, sys
sys.path.insert(0, os.getcwd())
from unittest import TestCase
import pytest
import networkx as nx
import numpy as np
import cosasi
class TestJordan(TestCase):
def setUp(self):
self.G = nx.random_tree(n=500, seed=0)
contagion = cosasi.StaticNetworkContagion(
G=self.G,... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/diffusion/LT.py | xflow/diffusion/LT.py | import torch_geometric.datasets as ds
import random
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
def LT(g, config, seed, rounds=100):
result = []
for iter in range(rounds):
model_temp = ep.ThresholdModel(g) # _temp
config_temp = mc.Configuration()
config_... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/diffusion/IC.py | xflow/diffusion/IC.py | import torch_geometric.datasets as ds
import random
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
# diffusion models
def IC(g, config, seed, rounds=100):
result = []
for iter in range(rounds):
model_temp = ep.IndependentCascadesModel(g) # _temp
config_temp = mc.Co... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/diffusion/SI.py | xflow/diffusion/SI.py | import torch_geometric.datasets as ds
import random
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
def SI(g, config, seed, rounds=100, beta=0.1):
result = []
for iter in range(rounds):
model_temp = ep.SIModel(g) # _temp
config_temp = mc.Configuration()
con... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/diffusion/__init__.py | xflow/diffusion/__init__.py | from .SI import SI
from .IC import IC
from .LT import LT
| python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/llm/graph_generation.py | xflow/llm/graph_generation.py | import networkx as nx
import torch_geometric.datasets as ds
import random
import ndlib
import ndlib.models.epidemics as ep
import ndlib.models.ModelConfig as mc
from torch_geometric.datasets import Planetoid
def connSW(n, beta=None):
g = nx.connected_watts_strogatz_graph(n, 10, 0.1)
config = mc.Configuration... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
XGraph-Team/XFlow | https://github.com/XGraph-Team/XFlow/blob/1efc1844d3940fb726324c2a72c5f4325690910a/xflow/llm/test.py | xflow/llm/test.py | import networkx as nx
import ndlib.models.ModelConfig as mc
import ndlib.models.epidemics as ep
from time import time
from graph_generation import Cora, CiteSeer, PubMed, connSW, ER, coms, photo
import matplotlib.pyplot as plt
#
size = 50
beta = 0.1
gamma = 0.01
G, config = connSW(size, beta)
# Model selection
model... | python | MIT | 1efc1844d3940fb726324c2a72c5f4325690910a | 2026-01-05T07:14:40.788228Z | false |
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