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NANO-filter

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1.0.0 NANO_filter-1.0.0-py3-none-any.whl

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Project: NANO-filter
Version: 1.0.0
Filename: NANO_filter-1.0.0-py3-none-any.whl
Download: [link]
Size: 32934
MD5: 54642ce46c6c6e23bd0cf339136c2b5e
SHA256: c4a1b98f4465a3e4b7d810469f70124299ce45744bfe84d56326fc4e22b6ccca
Uploaded: 2024-10-31 09:19:49 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: NANO-filter
Version: 1.0.0
Summary: Nonlinear Bayesian Filtering with Natural Gradient Gaussian Approximation
Author: Tianyi Zhang
Author-Email: zhangtia24[at]mails.tsinghua.edu.cn
Home-Page: https://github.com/TianyiMehdi/NANO-filter
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Requires-Dist: autograd (==1.6.2)
Requires-Dist: dataclasses-json (==0.6.7)
Requires-Dist: einops (==0.8.0)
Requires-Dist: filterpy (==1.4.5)
Requires-Dist: matplotlib (==3.8.2)
Requires-Dist: numpy (==2.1.2)
Requires-Dist: pandas (==2.2.3)
Requires-Dist: scipy (==1.14.1)
Requires-Dist: seaborn (==0.13.2)
Requires-Dist: tqdm (==4.66.1)
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 2205 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.3.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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data_processing/data_processing.py sha256=eJ0QrdAiLKTj6nTPb0xjURarB78rnjCre19ix-NcyMU 2976
environ/__init__.py sha256=R9LPz3E2PduN6884WfRHOwt8MTlR90doZQMoflzj2gM 370
environ/air_traffic.py sha256=5FfZSpCARrb8gMhFb3aeHrqHaKxRHdAVRdzTf3aRg80 3665
environ/blackhole.py sha256=qZRk_qI7dmCn2E1PC_JmWrXWqVDbaK8_mmQ-6cJCCZE 6311
environ/chemical_reaction.py sha256=z2WH_dgAMw7YDUHmUxxT2U0nkwnLKRODGeqbwgUMdzM 2342
environ/lorenz.py sha256=tr9PIxLiCPV1PDpRYTIN3sGLbdkd7OVNn2YxYHWUX1M 8259
environ/model.py sha256=QSPnoRUgIoTdhwAq_rXQ41ZO1yxsPqP5RPRevVFStIA 590
environ/robot_move.py sha256=nzD8bpDY-U-UOg-Q8IsGNE9pitVQKk8aSHmLQgk_paY 3082
environ/sensor_net.py sha256=u9gFyInQm1C1MC5upRKsjJvi7zPdZDNUxK6eIvSlSlI 2957
environ/sin_cos.py sha256=okZfsKGA5cfpeOHiWhsEWHIPSBCwo-jpdW7CkEuFI58 2125
environ/slide_slip_veh.py sha256=SDjhFlXCzXqPQzr5wzP5Quo9Bcy1J98LMPkEjcEUJ3s 6067
environ/ugv.py sha256=qe-IGRRsmywzYMPq4jR5vb2rNb531NET5oRD0yRNeSg 4339
environ/ugv2.py sha256=9lcrUdNtBt2tyLk0GTiEECiT2vBXrfKNftk-vcTPUro 4274
environ/wiener_velocity.py sha256=QRsUyf5F34v7JVGKSqGbTyMjfApjsbljJcyyJb9vdy4 2808
filter/EKF.py sha256=J3tIXXpifVD84l_Cp_FIOhEEInhDJlG3NzHSo9Kfl4Q 1127
filter/HuberEKF.py sha256=oaMVCVo3fKypJTkUuPYVwNCXG-aWYiCS15Orrj8xtyc 2684
filter/NANO.py sha256=GbNUCfu7vS93PIqfSsrivCc9Wst8Cw-zrUeLRUMNnY4 8157
filter/PF.py sha256=qC5dCo8bJWuh8gRaDBbimidpCLdV58b_D-naGIiD1LQ 2053
filter/PLF.py sha256=S5wD8nrl-J37N84eeX_7YRg7bO7xOn0wgDVyICEfSXw 2834
filter/UKF.py sha256=XctY03HLFKjm9plNB3aAlf-Uoxh6AGhq28rfiPZ2FLE 2296
filter/__init__.py sha256=6In7X6g5j87h3dsM67Lq-kb1npvOyzxTvCnxUp5uBy4 212
filter/iEKF.py sha256=8fEoGeGlO1oagxzgs-r7P2Bars9cxVTzKZ0KmrdS75s 2117
filter/main.py sha256=jbBRzKQ-Q-JouJ0ZcrEyS1XNU-3_b0ZLm1hL27nhNYw 12424
filter/utils.py sha256=R3Nnjipxyi3KAhWqO7ARC30J6Jaak0wmPkVO3Gnw9hY 1971
NANO_filter-1.0.0.dist-info/LICENSE sha256=_8o6MzU4kPoBiZGVUpfCsbO-TGOF19_ODI8WBYkkinI 1076
NANO_filter-1.0.0.dist-info/METADATA sha256=AtVPUxdZFdpenmvVGYZZmcmxjvtxC_5ukRc9CcyWxSM 3028
NANO_filter-1.0.0.dist-info/WHEEL sha256=P9jw-gEje8ByB7_hXoICnHtVCrEwMQh-630tKvQWehc 91
NANO_filter-1.0.0.dist-info/top_level.txt sha256=KXKIwOC3ED2ac_mMKOYsJid-WKod3ZRDVHIPRp1uuDE 31
NANO_filter-1.0.0.dist-info/RECORD — —

top_level.txt

data_processing
environ
filter