Analysis: Noise Floor Delta over Z-axis

aydin/analysis/demo/demo_noise_floor_delta.py

@@ -0,0 +1,13 @@
+# flake8: noqa
+from aydin.analysis.noise_floor_delta import noise_floor_delta
+from aydin.io.datasets import examples_single
+
+
+def demo_noise_floor_delta():
+    noisy_image = examples_single.gauss_noisy.get_array()
+
+    noise_floor_delta = noise_floor_delta(denoised_image, noisy_image, axis=0)
+
+
+if __name__ == '__main__':
+    demo_noise_floor_delta()

aydin/analysis/fsc.py

@@ -7,6 +7,7 @@ def fsc(image1, image2):
     Method that calculates Fourier Shell Correlations between
     the two provided 2D images. For more,
     https://en.wikipedia.org/wiki/Fourier_shell_correlation
+
     Parameters
     ----------
     image1 : numpy.ArrayLike
@@ -59,3 +60,7 @@ def shell_sum(image):
     ]
 
     return output
+
+
+def halfbit_curve(correlations):
+    raise NotImplementedError()

aydin/analysis/noise_floor_delta.py

@@ -0,0 +1,32 @@
+from aydin.analysis.fsc import fsc, halfbit_curve
+
+
+def noise_floor_delta(noisy_array, denoised_array1, denoised_array2) -> float:
+    """
+    This method calculates the noise floor level difference on spectra
+    of a noisy and a denoised array (does NOT require groundtruth).
+
+    Parameters
+    ----------
+    denoised_array : numpy.typing.ArrayLike
+        Denoised nD array of interest
+    noisy_array : numpy.typing.ArrayLike
+        Noisy(original) nD array of interest
+
+    Returns
+    -------
+    float
+        Calculated noise floor difference between the noisy and denoised arrays.
+
+    """
+    # TODO: handle the case where axis=-1
+    # if axis == -1:
+    #     numpy.newaxis(denoised_array, 0)
+
+    correlations1 = fsc(noisy_array, denoised_array1)
+    correlations2 = fsc(noisy_array, denoised_array2)
+
+    halfbit1 = halfbit_curve(correlations1)
+    halfbit2 = halfbit_curve(correlations2)
+
+    return abs(halfbit1 - halfbit2)

aydin/io/datasets.py

@@ -3,7 +3,6 @@
 from enum import Enum
 from os.path import join, exists
 from typing import Optional
-
 import gdown
 import numpy
 from scipy.ndimage import binary_dilation, zoom