Minor bug-fixes for v2.0

deeptrack/augmentations.py

@@ -258,7 +258,7 @@ def update_properties(self, image, number_of_updates, **kwargs):
             for prop in image.properties:
                 if "position" in prop:
                     position = np.array(prop["position"])
-                    position[..., 0] = image.shape[1] - position[..., 0]
+                    position[..., 0] = image.shape[0] - position[..., 0]
                     prop["position"] = position
 
 

deeptrack/noises.py

@@ -87,10 +87,11 @@ def __init__(
 
     def get(self, image, snr, background, **kwargs):
         image[image < 0] = 0
-
-        peak = np.abs(np.max(image) - background)
+        immax = np.max(image)
+        peak = np.abs(immax - background)
 
         rescale = snr ** 2 / peak ** 2
+        rescale = np.clip(rescale, 1e-10, np.inf)
         noisy_image = Image(np.random.poisson(image * rescale) / rescale)
         noisy_image.properties = image.properties
         return noisy_image

deeptrack/optics.py

@@ -20,6 +20,7 @@
 from .image import Image, pad_image_to_fft
 from .types import ArrayLike, PropertyLike
 
+import scipy.ndimage
 from scipy.ndimage import convolve
 
 
@@ -555,7 +556,7 @@ def get(self, illuminated_volume, limits, fields, **kwargs):
 
         K = 2 * np.pi / kwargs["wavelength"]
 
-        field_z = [_get_position(field, return_z=True)[-1] for field in fields]
+        field_z = [field.get_property("z") for field in fields]
         field_offsets = [field.get_property("offset_z", default=0) for field in fields]
 
         z = z_limits[1]
@@ -687,12 +688,13 @@ def _get_position(image, mode="corner", return_z=False):
     # Extracts the position of the upper left corner of a scatterer
     num_outputs = 2 + return_z
 
-    if mode == "corner":
-        # Probably unecessarily complicated expression
-        shift = (
-            np.ceil((np.array(image.shape) - 1) / 2)
-            - (1 - np.mod(image.shape, 2)) * 0.5
-        )
+    if mode == "corner" and image.size > 0:
+
+        shift = scipy.ndimage.measurements.center_of_mass(np.abs(np.array(image)))
+
+        if np.isnan(shift).any():
+            shift = np.array(image.shape) / 2
+
     else:
         shift = np.zeros((num_outputs))
 

requirements.txt

@@ -6,3 +6,4 @@ Sphinx==2.2.0
 pydata-sphinx-theme
 numpydoc
 scikit-image
+pint

setup.py

@@ -5,7 +5,7 @@
 with open("README.md", "r") as fh:
     long_description = fh.read()
 
-required = ["tensorflow", "numpy", "scipy"]
+required = ["tensorflow", "numpy", "scipy", "scikit-image", "pint"]
 installed = [pkg.key for pkg in pkg_resources.working_set]
 if (
     not "tensorflow" in installed
@@ -16,7 +16,7 @@
 
 setuptools.setup(
     name="deeptrack",  # Replace with your own username
-    version="0.11.0",
+    version="0.11.3",
     author="Benjamin Midtvedt",
     author_email="benjamin.midtvedt@physics.gu.se",
     description="A deep learning oriented microscopy image simulation package",