From 8b10e5e53ab6ffc8fe3326e445d522d06d814bb6 Mon Sep 17 00:00:00 2001
From: sambit-giri <sambit.giri@gmail.com>
Date: Tue, 22 Oct 2024 15:15:36 +0200
Subject: [PATCH] publish on pypi from github

---
 .github/workflows/publish-to-pypi.yml  | 36 ++++++++++++++++++++++++++
 src/tools21cm/gaussian_random_field.py |  4 ++-
 2 files changed, 39 insertions(+), 1 deletion(-)
 create mode 100644 .github/workflows/publish-to-pypi.yml

diff --git a/.github/workflows/publish-to-pypi.yml b/.github/workflows/publish-to-pypi.yml
new file mode 100644
index 0000000..d89191a
--- /dev/null
+++ b/.github/workflows/publish-to-pypi.yml
@@ -0,0 +1,36 @@
+name: Publish Python Package to PyPI
+
+on:
+  push:
+    tags:
+      - 'v*'  # Trigger on version tags
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v3
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.x'
+
+    - name: Install build tools
+      run: |
+        python -m pip install --upgrade pip
+        pip install setuptools wheel twine
+
+    - name: Build package
+      run: python setup.py sdist bdist_wheel
+
+    - name: Publish to PyPI
+      env:
+        TWINE_USERNAME: __token__
+        TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
+      run: twine upload dist/*
+
+    - name: Clean up
+      run: rm -rf dist build *.egg-info
diff --git a/src/tools21cm/gaussian_random_field.py b/src/tools21cm/gaussian_random_field.py
index cc11b74..99228c3 100644
--- a/src/tools21cm/gaussian_random_field.py
+++ b/src/tools21cm/gaussian_random_field.py
@@ -7,7 +7,7 @@
 import numpy as np
 from scipy import fftpack
 from .power_spectrum import _get_dims, _get_k, power_spectrum_1d
-from scipy.interpolate import interp1d
+from scipy.interpolate import interp1d, splrep, splev
 
 def make_gaussian_random_field(dims, box_dims, power_spectrum, random_seed=None):
     '''
@@ -97,6 +97,8 @@ def _get_ps_func_for_field(input_field, box_dims, kbins=10):
                             box_dims=box_dims, kbins=kbins, return_n_modes=True)
     ps_k = interp1d(k_input[n_modes>0], ps_input[n_modes>0], kind='linear', \
                     bounds_error=False, fill_value=0.)
+    # tckp = splrep(np.log10(k_input[n_modes>0]), np.log10(ps_input[n_modes>0]), k=1)
+    # ps_k = lambda k: 10**splev(np.log10(k), tckp)
     return ps_k