Merge branch 'master' into dev-hm-fe

.github/workflows/codestyle.yml

@@ -19,7 +19,7 @@ jobs:
       - name: Install Dependencies
         shell: bash -el {0}
         run: |
-          pip install tox-conda flake8
+          pip install tox flake8
       - name: Check Code Style
         shell: bash -el {0}
         run: |

.github/workflows/compatibility.yml

@@ -24,12 +24,14 @@ jobs:
         uses: conda-incubator/setup-miniconda@v2
         with:
           auto-activate-base: false
+          activate-environment: soliket-tests
+          environment-file: soliket-tests.yml
           python-version: ${{ matrix.python-version }}
           channels: conda-forge
       - name: Install Dependencies
         shell: bash -el {0}
         run: |
-          pip install tox-conda
+          pip install tox
       - name: Run Tests
         shell: bash -el {0}
         run: |

.github/workflows/publish.yaml

@@ -0,0 +1,55 @@
+name: Upload to PyPI
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  build:
+    name: Build distribution
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.x"
+
+      - name: Install pypa/build
+        run: >-
+          python3 -m
+          pip install
+          build
+          --user
+      - name: Build a binary wheel and a source tarball
+        run: python3 -m build
+      - name: Store the distribution packages
+        uses: actions/upload-artifact@v3
+        with:
+          name: python-package-distributions
+          path: dist/
+
+  testpypi-publish:
+    name: Upload release to PyPI
+    needs:
+      - build
+    runs-on: ubuntu-latest
+    environment:
+      name: pypi
+      url: https://pypi.org/p/soliket
+    permissions:
+      id-token: write  # IMPORTANT: this permission is mandatory for trusted publishing
+    steps:
+      - name: Download all the dists
+        uses: actions/[email protected]
+        with:
+          name: python-package-distributions
+          path: dist/
+      - name: Publish package distributions to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+        # with:
+          # user: __token__
+          # repository-url: https://test.pypi.org/legacy/
+          # print-hash: true
+          # password: ${{ secrets.TEST_PYPI_TOKEN }}

.github/workflows/testing.yml

@@ -30,19 +30,29 @@ jobs:
             python-version: '3.11'
             toxenv: py311-test-latest
 
+          - name: Windows latest
+            os: windows-latest
+            python-version: '3.11'
+            toxenv: py311-test-latest
+            env:
+              PYTHONIOENCODING: utf-8
+              PYTHONUTF8: 1
+
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
       - name: Install Conda w/ Python ${{ matrix.python-version }}
         uses: conda-incubator/setup-miniconda@v3
         with:
           auto-activate-base: false
+          activate-environment: soliket-tests
+          environment-file: soliket-tests.yml
           python-version: ${{ matrix.python-version }}
           channels: conda-forge
       - name: Install Dependencies
         shell: bash -el {0}
         run: |
-          pip install tox-conda
+          pip install tox
       - name: Run Tests
         shell: bash -el {0}
         run: |

INSTALL.rst

@@ -12,6 +12,25 @@ We have provided a conda environment defined in `soliket-tests.yml <https://gith
 
    $ conda env create --file soliket-tests.yml
 
+You can then install the `latest released version of SOLikeT from PyPI <https://pypi.org/project/soliket/>`_ into this environment:
+
+::
+
+   $ conda activate soliket-tests
+   $ pip install soliket
+
+Installing in editable mode for development
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+If you wish to actively develop the code you can instead install the in-development version of SOLikeT from the github repository in editable mode:
+
+::
+
+   $ git clone https://github.com/simonsobs/soliket
+   $ cd soliket
+   $ pip install -e .
+
+
 Optional: Install CosmoPower
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 In order to use the CosmoPower Theories within SOLikeT you will need to additionally install CosmoPower (and with it tensorflow, which is rather heavy and hence left out of the default installation).
@@ -22,8 +41,8 @@ Unless using an M1 Mac this should be easily achievable with::
 
 If you wish to install it using your own system tools (including new M1 Mac) some useful information is provided below.
 
-Harder Way: Preparing your own conda environment
-----------------------------------
+Harder Way: Preparing your own environment
+------------------------------------------
 
 **CREATE VIRTUAL CONDA ENV TO RUN COBAYA**
 Based on `cobaya documentation <https://cobaya.readthedocs.io/en/latest/cluster_amazon.html>`_.

README.rst

@@ -27,14 +27,17 @@ Installation
 
 For a set of detailed requirements and installation instructions for different machines (e.g. NERSC, M1 Mac), please see `the installation page <INSTALL.rst>`_.
 
-A preferred and convenient way to install SOLikeT and its dependents is through using the conda environment defined in `soliket-tests.yml <soliket-tests.yml>`_. After installing an anaconda distribution (e.g. as described `here <https://docs.anaconda.com/free/anaconda/install/index.html>`_), you can create the environment and install a locally cloned version of SOLikeT using pip::
+A preferred and convenient way to install SOLikeT and its dependents is through using the conda environment defined in `soliket-tests.yml <soliket-tests.yml>`_. After installing an anaconda distribution (e.g. as described `here <https://docs.anaconda.com/free/anaconda/install/index.html>`_), you can create the environment and install a the latest released version of SOLikeT using pip::
 
-  git clone https://github.com/simonsobs/soliket
-  cd soliket
   conda env create -f soliket-tests.yml
   conda activate soliket-tests
-  pip install -e .
+  pip install soliket
+
+You can alternatively clone a local version of the in-development code and install it in editable mode::
 
+  git clone https://github.com/simonsobs/soliket
+  cd soliket
+  pip install -e .
 
 Running an Example
 ==================
@@ -43,7 +46,7 @@ SOLikeT is a collection of modules for use within the Cobaya cosmological infere
 
 SOLikeT examples and explanatory notebooks are under construction, but will be run using standard [yaml](https://en.wikipedia.org/wiki/YAML) format (which can in turn be read in as Python dictionaries). The examples will be run using something similar to::
 
-  cobaya-run soliket-example.yml
+  cobaya-run examples/example_1.yaml
 
 
 Developing SOLikeT Theories and Likelihoods

examples/example_1.yaml

@@ -0,0 +1,126 @@
+debug: False
+
+# Choose a sampler.
+# Running the evaluate sampler will compute the likelihood
+# only at a single value of parameters
+sampler:
+  evaluate: null
+
+# Specify the output location and file prefix
+output: output/example_1
+
+# Specify which Likelihoods we would like to use
+# Any options for the Likelihood will use their default values unless specified here
+# In this case the options and defaults are specified in soliket/mflike/MFLike.yaml
+# Note that MFLike is a Cobaya `installable likelihood`.
+# When running this yaml file, or calling `cobaya-install example_1.yaml` the required
+# installable components will automatically be downloaded and installed. 
+# Note that for the soliket MFLike likelihood we are required to calculate:
+# - CMB theory power spectra (from CAMB theory below)
+# - Multi-frequency bandpass calibrations (from soliket.BandPass theory below)
+# - Multi-frequency foregrounds (from soliket.Foreground theory below)
+# - The combination of the above components (from soliket.TheoryForge_MFLike theory below)
+likelihood:
+  soliket.MFLike:
+    data_folder: MFLike/v0.8
+    input_file: LAT_simu_sacc_00000.fits
+    cov_Bbl_file: data_sacc_w_covar_and_Bbl.fits
+    defaults:
+      polarizations: ['TT', 'TE', 'ET', 'EE']
+      scales:
+        TT: [30, 9000]
+        TE: [30, 9000]
+        ET: [30, 9000]
+        EE: [30, 9000]
+      symmetrize: False
+
+# Specify the Theory codes which will compute observables to be compared with the data
+# in the Likelihood.
+# Here we specify the CAMB Einstein-Boltzmann code, with a number of choices made on
+# precision and neutrino model.
+theory:
+  camb:
+    extra_args:
+      lens_potential_accuracy: 1
+      WantTransfer: True
+      Transfer.high_precision: True
+      Transfer.kmax: 1.2
+      num_nu_massless: 1.044
+      num_nu_massive: 2
+      nu_mass_eigenstates: 2
+      # We use the minimal normal ordering case: massless lightest state, m2 and m3
+      # computed according to oscilation measurements.
+      nu_mass_fractions: [0.14763410387308012,0.8523658961269198]
+      nu_mass_numbers: [1,1]
+      share_delta_neff: True
+    stop_at_error: True
+
+  soliket.BandPass:
+    stop_at_error: True
+
+  soliket.Foreground:
+    stop_at_error: True
+
+  soliket.TheoryForge_MFLike:
+    spectra:
+      polarizations: ['tt', 'te', 'ee']
+      lmin: 2
+      lmax: 9050
+    stop_at_error: True
+
+# Specify the parameter values at which to compute the likelihood
+params:
+  H0:
+    latex: H_0
+    value: 67.7
+  logA:
+    # Dropped parameters are sampled but not passed to Likelihood/Theory codes
+    # Here it is As (specified below) which is passed to the Likelihood/Theory code.
+    drop: true
+    latex: \log(10^{10} A_\mathrm{s})
+    value: 3.05
+  As:
+    value: 'lambda logA: 1e-10*np.exp(logA)'
+  ombh2:
+    latex: \Omega_\mathrm{b} h^2
+    value: 0.0224
+  omega_de:
+    latex: \Omega_\Lambda
+    # Derived parameters are not sampled but have output values which can be constrained
+    # and plotted. These values can be computed internally by Theory codes (as for omega_de
+    # here which is calculated within camb) or given a lambda function (as fo omegamh2 
+    # below).
+    derived: true
+  omegam:
+    latex: \Omega_\mathrm{m}
+    derived: true
+  omegamh2:
+    derived: 'lambda omegam, H0: omegam*(H0/100)**2'
+    latex: \Omega_\mathrm{m} h^2
+  omch2:
+    latex: \Omega_c h^2
+    value: 0.1202
+  sigma8:
+    latex: \sigma_8
+    derived: true
+  ns:
+    latex: n_s
+    value: 0.9649
+  Alens:
+    latex: A_lens
+    value: 1.0
+  tau:
+    latex: \tau_\mathrm{reio}
+    value: 0.0554
+  mnu1:
+    value: 0.0
+    drop: True
+  mnu2:
+    value: 'lambda: np.sqrt(7.5e-5)'
+    drop: True
+  mnu3:
+    value: 'lambda: np.sqrt(2.5e-3)'
+    drop: True
+  mnu:
+    value: 'lambda mnu1, mnu2 ,mnu3: mnu1 + mnu2 + mnu3'
+    latex: \sum m_\nu

pyproject.toml

@@ -1,6 +1,5 @@
 [project]
 name = "soliket"
-# version = "0.1.dev1"
 dynamic = ['version']
 authors = [
 	{name = "Simons Observatory"}
@@ -11,10 +10,10 @@ requires-python = ">=3.8, <3.12"
 license = {text = "MIT"}
 dependencies = [
     "requests",
-    'importlib-metadata; python_version<"3.8"',
     "numpy",
     "scipy>=1.6",
     "pandas", # to remove
+    "pytest-cov",
     "astropy",
     "cobaya",
     "sacc",
@@ -62,12 +61,11 @@ include = [
 "*" = ['*.yaml', '*.fits', '*.txt', '*.pkl', '*.gz']
 
 [tool.setuptools_scm]
-version_file = "soliket/version.py"
+version_file = "soliket/_version.py"
 
 [project.optional-dependencies]
 all = [
     "cosmopower",
-    "pyccl",
     "tensorflow_probability<0.22",
 ]
 docs = [
@@ -105,3 +103,8 @@ exclude_lines = [
     # Don't complain about IPython completion helper
     "def _ipython_key_completions_",
 ]
+
+[tool.pytest.ini_options]
+markers = [
+    "require_ccl",
+]

requirements.txt

@@ -1,6 +1,7 @@
 numpy
 scipy>=1.6
 pandas
+pytest-cov
 scikit-learn
 pyyaml
 py-bobyqa
@@ -13,8 +14,8 @@ fuzzywuzzy
 astropy
 getdist
 cobaya
-pyccl
+pyccl >= 3.0; platform_system!='Windows'
 sacc
 fgspectra>=1.1.0
 syslibrary
-pyhalomodel
+pyhalomodel

soliket-tests.yml

@@ -5,6 +5,7 @@ channels:
 dependencies:
   - python>=3.8,<3.12
   - pip
+  - pytest
   - pytest-cov
   - compilers
   - make
@@ -16,4 +17,4 @@ dependencies:
   - mpi4py
   - camb
   - pip:
-      - -r requirements.txt
+      - -r requirements.txt

soliket/__init__.py

@@ -1,3 +1,11 @@
+from importlib.metadata import PackageNotFoundError, version
+
+try:
+    __version__ = version("soliket")
+except PackageNotFoundError:
+    # package is not installed
+    pass
+
 from .bandpass import BandPass
 from .bias import Bias, Linear_bias
 from .ccl import CCL