Skip to main content

Add your description here

Project description

Installation

Follow this guide to install UV.

Running it

To run the entrypoint, run the following command.

 uv run -m semistaticsim.groundtruth.simulator

You can set the target amount of simulation time to collect as well as the scan size. The bigger the scan size, the higher the RAM usage and jitting time, but it has the potential to go faster if you want to collect a lot of simulation time.

After collecting the data, plot the groundtruth of the first pickupable across all its valid receptacles:

TODO @MIGUEL BROKEN? OSError: 'science' is not a valid package style, path of style file
uv run groundtruth/viz.py

To run the ai2thor simulation, you can use

 uv run -m semistaticsim.keyboardcontrol.main_skillsim

How-to

Features are based around varying the level of scene-to-scene semantic transfer. Every simulator step, some dt time elapses. When the duration_left reaches 0, the transition model selects the next receptacle that the object will transition to. Then, the duration model sampels the amount of tiem that the objet will spend in that new receptacle.

Duration model:

  1. even is "evenly spread duration of all steps"
  2. instant is "spend NO time at this place, immediately transition at the next step" (this is what flowmaps currently has in your 2D simulator)
  3. deterministic is "randomly split the day among all steps"
  4. gaussian is the same as deterministic with some gaussian noise

Transition model:

  1. "fixed_canonical": object cycles down a list of fixed receptacles
  2. "fixed_0.1_0.9": object has 10% chance of staying put, 90% chance of going to the next receptacle in cycle (this is what the 2D flowmaps simulator has)
  3. "uniform_no_diag": fully uniform transition matrix
  4. "uniform_full": fully uniform transition matrix
  5. "location_weighted_uniform_no_diag": uniform transition matrix weighted by the ProcThor receptacle prior
  6. "location_weighted_uniform_full": uniform transition matrix weighted by the ProcThor receptacle prior

Preliminary scan experiments

  1. SCANSIZE 10: ~33.5 it/s : 335 steps/s
  2. 100 : 33 : 3300

1000 : eta 50min

1000 : cpu: 3s/it; cuda is same!

To build a package for PyPi

uv build

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

semistaticsim-0.2.0.tar.gz (2.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

semistaticsim-0.2.0-py3-none-any.whl (2.6 kB view details)

Uploaded Python 3

File details

Details for the file semistaticsim-0.2.0.tar.gz.

File metadata

  • Download URL: semistaticsim-0.2.0.tar.gz
  • Upload date:
  • Size: 2.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.4

File hashes

Hashes for semistaticsim-0.2.0.tar.gz
Algorithm Hash digest
SHA256 4338eb20fb9c67822aac4f1bea45b3ca3551d402a458001bb82267c02b0f010c
MD5 f7b31c546b905724a77a9563e2d0d926
BLAKE2b-256 3355edc890e7819c8b615223e6f5a4477ec4b0b91c5aa9b504703ac2dead2171

See more details on using hashes here.

File details

Details for the file semistaticsim-0.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for semistaticsim-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 438c3f28618d1f1c57a953bf4072aeba5296e01a8d1c744e71e6f9c15e73f260
MD5 706f9a51eb0ca0eb7be30652072dba00
BLAKE2b-256 7e6058bb32714495445b99be5fde28c0a13fdbb29e3ef055c1caeb5bcd57154a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page