Skip to main content

No project description provided

Project description

AnaCal

docs tests pypi conda-forge License: GPL v3 Code style: black

Analytic Calibration for Perturbation Estimation from Galaxy Images.

This framework is designed to measure the shear responses of both existing and future shape estimators. Our goal is to develop a suite of analytical shear estimators that can infer shear with sub-percent accuracy while remaining computationally efficient.

To compute shear response, we introduce the concept of pixel shear response---the derivatives of pixel values with respect to applied shear distortions. We then propagate these responses using quintuple numbers, a technique for efficient shear response tracking. For accurate noise bias correction, we adopt a renoising approach that enables analytical treatment of noise effects.

Currently, the framework supports the following analytical shear estimators:

  • FPFS: A fixed moments method based on shapelets including analytic correction for selection, detection and noise bias. (see ref1, ref2, ref3, and ref4.)
  • NGMIX: Gaussian model fitting. (see ref5)

Installation

Users can clone this repository and install the latest package by

git clone https://github.com/mr-superonion/AnaCal.git
cd AnaCal
# install required softwares
conda install -c conda-forge --file requirements.txt
# install required softwares for unit tests (if necessary)
conda install -c conda-forge --file requirements_test.txt
pip install . --user

or install stable version

pip install anacal

or

conda install -c conda-forge anacal

Examples

Examples can be found here.

Development

Before sending pull request, please make sure that the modified code passed the pytest and flake8 tests. Run the following commands under the root directory for the tests:

flake8
pytest -vv

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

anacal-0.7.1.tar.gz (18.5 MB view details)

Uploaded Source

Built Distributions

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

anacal-0.7.1-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (37.4 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

anacal-0.7.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (37.1 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

anacal-0.7.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (37.2 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

anacal-0.7.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (37.1 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

anacal-0.7.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (36.9 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

anacal-0.7.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (36.7 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

File details

Details for the file anacal-0.7.1.tar.gz.

File metadata

  • Download URL: anacal-0.7.1.tar.gz
  • Upload date:
  • Size: 18.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.13

File hashes

Hashes for anacal-0.7.1.tar.gz
Algorithm Hash digest
SHA256 50a06d71bcdcca90b1b569a8fe7e03d72c73dd20c17571a5be1bc3c523049d08
MD5 31509ea31fcb817e37327d00b7073ec3
BLAKE2b-256 9500200992f1505bca6c4f8fcf8102c0fabf4b7ab1d6a9b1aae503f02481be36

See more details on using hashes here.

File details

Details for the file anacal-0.7.1-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for anacal-0.7.1-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 71f64dbf93aadb9b6ae613a03a3f5bce9f2d0e094a4470b0e5539406b71e3b46
MD5 636c8b389a6d8f32f8cccdb4167a9b51
BLAKE2b-256 6de0543f056f337cbcdd108994194fe93236ca91a34bd1d88aefda2dc4d31628

See more details on using hashes here.

File details

Details for the file anacal-0.7.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for anacal-0.7.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a22a851ef62235e07d9525a23040b756d0f36d6dc7c25167940bd6732710d9d3
MD5 0b08ff10d133df6a15a8f01abae568b6
BLAKE2b-256 e5b9b1493b0c014b15e1956541e3df67b196aedee1f4339ec19cab6361125c24

See more details on using hashes here.

File details

Details for the file anacal-0.7.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for anacal-0.7.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d6e58fd000ec12d2f7ff3e0ac8d430152fb12d33854a4e9aa9ec3f7b647ce593
MD5 227eea42434c2065ceefda9100cf8cd9
BLAKE2b-256 b847fbfbb65977a7ad87b02baa82430de793374175b302f1c9af083623a1458d

See more details on using hashes here.

File details

Details for the file anacal-0.7.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for anacal-0.7.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1f0e1d70df63ec81dc4d4046763647f5e87076b314d21a97f6d459282ece54ef
MD5 35cfd356734011064df64507bfb624a1
BLAKE2b-256 cadceff91d5b4ff970fcd7a68e49b70c0ca470dffb138a126d3a3fd3e4cf5c1b

See more details on using hashes here.

File details

Details for the file anacal-0.7.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for anacal-0.7.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f3b93effa9c730f8139221fd4a6b78ba7dd5189f8eeb2fb3160b49b69f167b88
MD5 48caefae7e10205197d73da471473443
BLAKE2b-256 2c77204a646527e0e81725d3ebfc5af966bd9a13c0cda7a1c03132131bf12dc9

See more details on using hashes here.

File details

Details for the file anacal-0.7.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for anacal-0.7.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1d4c8d091837ee288f12ca787c00248d8c17aab6bb5debf32f946ab5e5852663
MD5 08bcffa5d507f282ef55b88b02d39771
BLAKE2b-256 2c53ea48c91fccb0d9d103d5996280c8fe1b2722411567d5ae917668845d2de8

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