ISCAT back compatibility

README-pypi.md

@@ -12,7 +12,7 @@
     <img src="https://img.shields.io/badge/docs-available-blue?logo=readthedocs">
   </a>
   <a href="https://badge.fury.io/py/deeptrack">
-    <img src="https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue" alt="Python version">
+    <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13%20%7C%203.14-blue" alt="Python version">
   </a>
   <a href="https://doi.org/10.1063/5.0034891">
     <img src="https://img.shields.io/badge/cite us-10.1063%2F5.0034891-blue">
@@ -28,16 +28,16 @@
   <a href="/LICENSE">License</a> 
 </p>
 
-DeepTrack2 is a modular Python library for generating, manipulating, and analyzing image data pipelines for machine learning and experimental imaging.
+DeepTrack2 is a modular Python library for generating, manipulating, and analyzing image data pipelines for machine learning and digital microscopy.
 
-<b>TensorFlow Compatibility Notice:</b> 
-DeepTrack2 version 2.0 and subsequent do not support TensorFlow. If you need TensorFlow support, please install the legacy version 1.7.
+> <b>TensorFlow Compatibility Notice:</b> 
+> DeepTrack2 version 2.0 and subsequent do not support TensorFlow. If you need TensorFlow support, please install the legacy version 1.7.
 
-The following quick start guide is intended for complete beginners to understand how to use DeepTrack2, from installation to training your first model. Let's get started!
+The following quick-start guide is intended for complete beginners to understand how to use DeepTrack2, from installation to training your first model. Let's get started!
 
 # Installation
 
-DeepTrack2 requires at least python 3.9.
+DeepTrack2 requires at least python 3.10.
 
 To install DeepTrack2, open a terminal or command prompt and run:
 ```bash
@@ -51,7 +51,7 @@ This will automatically install the required dependencies.
 
 # Getting Started
 
-Here you find a series of notebooks that give you an overview of the core features of DeepTrack2 and how to use them:
+Here you find a series of notebooks providing an overview of the core features of DeepTrack2 and how to use them:
 
 - DTGS101 **[Introduction to DeepTrack2](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS101_intro.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS101_intro.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
@@ -97,7 +97,7 @@ Here you find a series of notebooks that give you an overview of the core featur
 
   Creating custom scatterers of arbitrary shapes.
 
-- DTGS172  **[Creating Custom Scatterers: Bacteria](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS172_custom_scatterers_bacteria.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS172_custom_scatterers_bacteria.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+- DTGS172  **[Simulating Bacteria](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS172_custom_scatterers_bacteria.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/1-getting-started/DTGS172_custom_scatterers_bacteria.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
   Creating custom scatterers in the shape of bacteria.
 
@@ -171,28 +171,16 @@ Specific examples for graph-neural-network-based particle linking and trace char
 
 # Advanced Tutorials
 
-This section provides a list of advanced topic tutorials. The primary focus of these tutorials is to demonstrate the functionalities of individual modules and how they work in relative isolation, helping to provide a better understanding of them and their roles in DeepTrack2.
+This section provides a list of advanced tutorials. The primary focus of these tutorials is to demonstrate the functionalities of individual modules and how they work in relative isolation, helping to provide a better understanding of them and their roles in DeepTrack2.
 
 - DTAT301 **[deeptrack.features](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT301_features.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT301_features.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
 - DTAT311 **[deeptrack.properties](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT311_properties.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT311_properties.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
-- DTATo10 **[deeptrack.scatterers](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo10_scatterers.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo10_scatterers.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
-
-- DTATo20 **[deeptrack.optics](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo20_optics.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo20_optics.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
-
-- DTATo30 **[deeptrack.holography](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo30_holography.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo30_holography.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
-
-- DTATo40 **[deeptrack.aberrations](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo40_aberrations.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo40_aberrations.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
-
-- DTATo50 **[deeptrack.noises](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo50_noises.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo50_noises.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
-
-- DTATo60 **[deeptrack.augmentations](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo60_augmentations.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo60_augmentations.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+- DTAT321 **[deeptrack.properties](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT321_wrappers.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT321_wrappers.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
 - DTAT331 **[deeptrack.sequences](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT331_sequences.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT331_sequences.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
-- DTATo90 **[deeptrack.math](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo90_math.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo90_math.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
-
 - DTAT351 **[deeptrack.utils](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT351_utils.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT351_utils.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
 
 - DTAT353 **[deeptrack.statistics](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT353_statistics.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT353_statistics.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
@@ -223,6 +211,22 @@ This section provides a list of advanced topic tutorials. The primary focus of t
 
 - DTAT396 **[deeptrack.backend._config](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT396_backend._config.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTAT396_backend._config.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
 
+## Advanced Tutorials for Optical Microscopy
+
+- DTATo10 **[deeptrack.optical.scatterers](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo10_scatterers.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo10_scatterers.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+
+- DTATo20 **[deeptrack.optical.optics](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo20_optics.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo20_optics.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+
+- DTATo30 **[deeptrack.optical.holography](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo30_holography.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo30_holography.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
+
+- DTATo40 **[deeptrack.optical.aberrations](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo40_aberrations.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo40_aberrations.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+
+- DTATo50 **[deeptrack.optical.noises](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo50_noises.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo50_noises.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+
+- DTATo60 **[deeptrack.optical.augmentations](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo60_augmentations.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo60_augmentations.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+
+- DTATo90 **[deeptrack.optical.math](https://github.com/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo90_math.ipynb)** <a href="https://colab.research.google.com/github/DeepTrackAI/DeepTrack2/blob/develop/tutorials/3-advanced-topics/DTATo90_math.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
+
 # Developer Tutorials
 
 Here you will find a series of notebooks tailored for DeepTrack2's developers:

deeptrack/optical/optics.py

@@ -2212,6 +2212,8 @@ def __init__(
         self: ISCAT,
         illumination_angle: float = np.pi,
         amp_factor: float = 1,
+        input_polarization: float | str | None = "circular",
+        output_polarization: float | None = None,
         **kwargs: Any,
     ) -> None:
         """Initializes the ISCAT class.
@@ -2223,16 +2225,37 @@ def __init__(
         amp_factor: float
             Amplitude factor of the illuminating field relative to the
             reference field.
+        input_polarization: float | str | None
+            Forwarded to the scatterer (e.g. `MieSphere`), which is where the
+            polarization projection is actually computed. Default `None`
+            (isotropic illumination, no preferred axis), the standard ISCAT
+            configuration. Override here to use a fixed linear polarization
+            instead.
+        output_polarization: float | None
+            Forwarded to the scatterer. Default `None` (no analyzer), the
+            standard ISCAT configuration. Override here for a fixed linear
+            analyzer angle instead.
         **kwargs: Any
             Additional parameters for the Brightfield class.
 
+        Notes
+        -----
+        `input_polarization`/`output_polarization` parametrize the
+        scattered-field calculation, which happens on the scatterer (e.g.
+        `MieSphere`), not here. Setting them on `ISCAT` only supplies the
+        value that gets forwarded to the scatterer, it does not
+        relocate the computation. `MieScatterer`'s own standalone default
+        remains `0`/`0` (linear). `ISCAT`'s default of `"circular"`/`None` is 
+        what applies whenever a scatterer is imaged through `ISCAT`.
+
+
         """
 
         super().__init__(
             illumination_angle=illumination_angle,
             amp_factor=amp_factor,
-            input_polarization="circular",
-            output_polarization="circular",
+            input_polarization=input_polarization,
+            output_polarization=output_polarization,
             phase_shift_correction=True,
             **kwargs,
         )