Updates to API, removing LISST-Holo construct mode

Author: owoalex

README.md

@@ -1,6 +1,10 @@
 # microtiff
 A Python module and CLI tool for converting proprietary microscopy formats to TIFF with JSON metadata sidecar files.
 
+## Installation
+Microtiff is installable via PIP:
+```pip install microtiff```
+
 ## Supported data types
 Both supported modules and modules working with errata are listed below.
 
@@ -12,25 +16,8 @@ Both supported modules and modules working with errata are listed below.
 | FlowCam | :x: | In active development |
 
 ## Dependencies
-
 - pillow
 - numpy
-- holopy (for LISST-Holo/LISST-Holo2 "construct" mode only)
-    - xarray
-    - h5netcdf
-    - nose
-    - matplotlib
-    - h5py
-    - pyYaml
-    - scipy
-    - imp
-
-For essential dependencies you can use the following command:
-`$ pip install pillow numpy`
-
-HoloPy is not avaliaiable via PIP. If you are using anaconda, you may install it there. Alternatively, install from source by following instructions at [https://holopy.readthedocs.io/en/master/tutorial/dev_tutorial.html](https://holopy.readthedocs.io/en/master/tutorial/dev_tutorial.html#dev-install). Alternatively, use the install script at [scripts/install-holopy.sh](scripts/install-holopy.sh)
 
 ## Acknowledgements
-This library is comprised of work from various researchers, some of whom are not direct contributors to this repository.
-
-The LISST-Holo decoder is based on work by [Sari Giering](https://github.com/sarigiering), [Will Major](https://github.com/obg-wrm) and [Mojtaba Masoudi](https://github.com/Mojtabamsd)
+Made with the help of: [Sari Giering](https://github.com/sarigiering), [Will Major](https://github.com/obg-wrm) and [Mojtaba Masoudi](https://github.com/Mojtabamsd)

pyproject.toml

@@ -12,13 +12,21 @@ classifiers = [
     "Programming Language :: Python :: 3",
     "Operating System :: OS Independent",
 ]
+dependencies = [
+    "numpy >= 2.0.0",
+    "pillow >= 8.3.1",
+]
 
 [project.urls]
 Homepage = "https://github.com/NOC-OI/microtiff"
 Issues = "https://github.com/NOC-OI/microtiff/issues"
 
 [tool.setuptools.dynamic]
 
+[tool.setuptools]
+packages = ["microtiff"]
+package-dir = {"" = "src"}
+
 [tool.setuptools_scm]
 
 [build-system]

src/__init__.py renamed to src/microtiff/__init__.py

@@ -42,7 +42,7 @@ def header_file_to_dict(lines):
         o_dict[key] = value.rstrip()
     return o_dict
 
-def extract_ifcb_images(target, no_metadata = False):
+def extract_images(target, no_metadata = False):
     header_lines = ""
     with open(target + ".hdr") as f:
         header_lines = f.readlines()

src/ifcb.py renamed to src/microtiff/ifcb.py

@@ -21,10 +21,6 @@
 lisst_holo.py
 
 A converter for image data from the LISST-Holo and LISST-Holo2 holographic sensors
-
-Notes:
-
-Only imports holopy when attempting to construct normal images from interference patterns.
 '''
 
 import argparse
@@ -73,7 +69,7 @@ def read_string_till_space(fp):
                 reading = True
                 str_out = str_out + char
 
-def extract_lisst_holo_image(target, no_metadata = False, construct = False):
+def extract_image(target, no_metadata = False):
     image_map = []
     outputs = []
     with open(target + ".pgm", "rb") as f:
@@ -113,17 +109,6 @@ def extract_lisst_holo_image(target, no_metadata = False, construct = False):
                 with open(target + ".json", "w") as f:
                     json.dump(im_metadata, f, ensure_ascii=False)
             image.save(target + ".tiff", "TIFF")
-            if construct:
-                import holopy
-                zstack = np.linspace(0, 100000, 64)
-                raw_holo = holopy.load_image(target + ".tiff", spacing=4.4, medium_index = 1, illum_wavelen = 0.658)
-                rec_vol = holopy.propagate(raw_holo, zstack, cfsp = 3)
-                print("--construct not fully implemented!")
-                #print(rec_vol.shape)
-                for img in rec_vol:
-                    plt.imshow(np.abs(img.to_numpy()), interpolation="nearest", origin="upper")
-                    plt.colorbar()
-                    plt.show()
 
             outputs.append(target)