2026 fixes

.github/workflows/python-package.yml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.9", "3.10"]
+        python-version: ["3.10", "3.11", "3.12"]
 
     steps:
     - uses: actions/checkout@v3
@@ -26,7 +26,7 @@ jobs:
         python-version: ${{ matrix.python-version }}
     - name: Install C dependencies
       run: |
-        sudo apt-get install fftw3-dev
+        sudo apt-get install libfftw3-dev
         sudo apt-get install liblapack-dev
     - name: Install Python dependencies
       run: |
@@ -39,7 +39,7 @@ jobs:
         scons
     - name: Install python package
       run: |
-        python setup.py install
+        python -m pip install -e .
     - name: Test with pytest
       run: |
         pytest

doc/source/index.rst

@@ -2,7 +2,7 @@ Storm-Analysis
 ==============
 
 This is a repository of code developed in the `Zhuang Lab <http://zhuang.harvard.edu/>`_
-and the `Babcock Lab <https://hazenbabcock.github.io/>`_ for analysis of STORM
+and the `Babcock Lab <https://hazenbabcock.github.io/hcai/index.html>`_ for analysis of STORM
 movies. The code is available on `github <https://github.com/ZhuangLab/storm-analysis>`_.
 
 Some algorithms were developed in other groups and ported to Python. In this

doc/source/install.rst

@@ -13,6 +13,7 @@ C libraries
 Python
 ~~~~~~
 
+* `scons <https://scons.org/>`_ (to build the C libraries).
 * `numpy <http://www.numpy.org/>`_
 * `scipy <https://www.scipy.org/>`_
 * `matplotlib <http://matplotlib.org/>`_
@@ -87,10 +88,11 @@ The C libraries are built using `SCons <http://scons.org/>`_.
 
 Basic installation ::
 
-   $ git clone https://github.com/ZhuangLab/storm-analysis.git
-   $ cd storm-analysis
-   $ python setup.py build_c
-   $ python setup.py install
+  $ git clone https://github.com/ZhuangLab/storm-analysis.git
+  $ cd storm-analysis
+  $ python -m pip install scons
+  $ scons
+  $ python -m pip install .
 
 You may find that this does not work because ``build_c`` fails. This step is just a
 wrapper for SCons, so you may have better luck running the SCons by itself, then using
@@ -99,14 +101,16 @@ wrapper for SCons, so you may have better luck running the SCons by itself, then
 Linux / OS-X example ::
 
   $ cd storm-analysis
+  $ python -m pip install scons  
   $ scons
-  $ python setup.py install
+  $ python -m pip install .
 
 Windows (mingw64) example ::
 
   $ cd storm-analysis
-  $ scons
-  $ python setup.py install
+  $ python -m pip install scons  
+  $ scons -Q compiler=mingw
+  $ python -m pip install .
 
 `nuwen <https://nuwen.net/mingw.html>`_ is one source for mingw64. 
 
@@ -155,25 +159,7 @@ Install storm-analysis ::
 Testing
 ~~~~~~~
 
-Test the (source) installation (this will take a few minutes to run).
+Test the (source) installation (this requires ``pytest`` will take a few minutes to run) ::
 
-Option 1 ::
-
-  $ cd storm-analysis
-  $ python setup.py test
-
-Option 2 ::
-
   $ cd storm-analysis
   $ pytest
-
-.. note:: Due to issues with creating pickle files that are compatible between Python2
-	  and Python3 all of the tests that involve pickles (Spliner mostly) are skipped
-	  on Python2.
-
-Also
-----
-
-If you are modifying the code in the storm-analysis project you may find it more convenient
-to add a .pth file to your pythonX.Y/site-packages directory. Then you won't have to
-run ``python setup.py install`` after every change.

pyproject.toml

@@ -0,0 +1,46 @@
+[build-system]
+requires = ['setuptools>=61.0']
+build-backend = 'setuptools.build_meta'
+
+[project]
+name = 'storm_analysis'
+version = '2.2'
+dependencies = [
+  'scons',
+  'numpy',
+  'scipy',
+  'matplotlib',
+  'pillow',
+  'tifffile',
+  'Shapely',
+  'randomcolor',
+  'PyWavelets',
+  'h5py',
+  'astropy'
+]
+requires-python = '>=3.10'
+authors = [{name = 'Hazen Babcock'}]
+maintainers = []
+description = 'STORM movie analysis code.'
+readme = 'README.md'
+keywords = ['STORM', 'microscopy']
+classifiers = [
+  'Development Status :: 4 - Beta',
+  'Intended Audience :: Developers',
+  'License :: Mixed'
+]
+
+[tool.pytest]
+minversion = '9.0'
+addopts = ['-ra', '-q']
+testpaths = [
+    'storm_analysis/test'
+]
+
+[tool.setuptools]
+packages = ["storm_analysis"]
+
+[project.optional-dependencies]
+test = [
+    'pytest',
+]

storm_analysis/__init__.py

@@ -42,9 +42,9 @@ def configureMatplotlib():
 
 
 def getData(data_path):
-    import pkg_resources
-    data = pkg_resources.resource_filename(__name__, data_path)
-    return data
+    import importlib.resources
+    data = importlib.resources.files(__name__).joinpath(data_path)
+    return str(data)
 
 
 def getPath(path):

storm_analysis/admm/admm_3d.py

@@ -2,7 +2,7 @@
 """
 Pure Python code for doing ADMM in 3D.
 
-minimize 1/2*|| Ax - b ||_2^2 + \lambda || x ||_1
+minimize 1/2*|| Ax - b ||_2^2 + lambda || x ||_1
 
 As described in:
 Boyd et al., "Distributed Optimization and Statistical Learning 

storm_analysis/admm/admm_decon.py

@@ -2,7 +2,7 @@
 """
 Uses ADMM to perform image deconvolution. 
 
-This minimizes 1/2*|| Ax - b ||_2^2 + \lambda || x ||_1.
+This minimizes 1/2*|| Ax - b ||_2^2 + lambda || x ||_1.
 
 Hazen 11/19
 """

storm_analysis/fista/fista_3d.py

@@ -2,7 +2,7 @@
 """
 Pure Python code for doing FISTA in 3D.
 
-minimize || Ax - b ||_2^2 + \lambda || x ||_1
+minimize || Ax - b ||_2^2 + lambda || x ||_1
 
 As described in:
 Beck and Teboulle, "A Fast Iterative Shrinkage-Thresholding 

storm_analysis/fista/fista_decon.py

@@ -2,7 +2,7 @@
 """
 Deconvolve images in 3D using FISTA.
 
-This minimizes || Ax - b ||_2^2 + \lambda || x ||_1.
+This minimizes || Ax - b ||_2^2 + lambda || x ||_1.
 
 Hazen 11/19
 """

storm_analysis/fista/fista_fft_c.py

@@ -128,7 +128,7 @@ def newImage(self, image, background):
         c_background = numpy.ascontiguousarray(background, dtype = float)
         fista_fft.newImage(self.c_fista, c_image, c_background)
 
-    def run(self, f_lamba, iterations):
+    def run(self, f_lambda, iterations):
         fista_fft.run(self.c_fista, f_lambda, iterations)
 
 

storm_analysis/micrometry/micrometry.py

@@ -92,7 +92,7 @@ def makeTreeAndQuadsFromH5File(h5_filename, min_size = None, max_size = None, ma
 def plotMatch(kd1, kd2, transform, save_as = None, show = True):
     [x2, y2] = applyTransform(kd2, transform)
 
-    fig = pyplot.figure()
+    fig = pyplot.figure(figsize = (10,10))
     pyplot.scatter(kd1.data[:,0], kd1.data[:,1], facecolors = 'none', edgecolors = 'red', s = 100)
     pyplot.scatter(x2, y2, color = 'green', marker = '+', s = 100)