release 0.0.6

.pre-commit-config.yaml

@@ -1,5 +1,5 @@
 default_stages: [commit]
-
+exclude: '^data/'
 ci:
   autoupdate_commit_msg: "chore(deps): pre-commit.ci autoupdate"
   autoupdate_schedule: "monthly"

examples/evaluate_wav.py

@@ -1,9 +1,17 @@
 """Example to evaluate WAV files"""
 
+import sys
 from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, FileType
+from pathlib import Path
 
 from scipy.io import wavfile
 
+# This is to make the local vibromaf package available
+try:
+    sys.path.append(str(Path(__file__).absolute().parents[1]))
+except IndexError:
+    pass
+
 from vibromaf.metrics.snr import snr
 from vibromaf.metrics.spqi import spqi
 from vibromaf.metrics.stsim import st_sim

examples/white_noise.py

@@ -1,7 +1,16 @@
 """Simple get started example with white noise signals"""
 
+import sys
+from pathlib import Path
+
 import numpy as np
 
+# This is to make the local vibromaf package available
+try:
+    sys.path.append(str(Path(__file__).absolute().parents[1]))
+except IndexError:
+    pass
+
 from vibromaf.metrics.snr import snr
 from vibromaf.metrics.spqi import spqi
 from vibromaf.metrics.stsim import st_sim

requirements-dev.txt

@@ -10,3 +10,4 @@ matplotlib
 tikzplotlib
 mkdocs
 mkdocstrings
+pandas

setup.py

@@ -11,7 +11,7 @@
 
 setuptools.setup(
     name="vibromaf",
-    version="0.0.5",
+    version="0.0.6",
     author="Markus Hofbauer, Andreas Noll",
     author_email="[email protected]",
     description="Vibrotactile quality metrics and metric fusion",

test/metrics/test_spqi.py

@@ -44,3 +44,11 @@ def test_spqi__dist_shorter_than_ref__should_throw(self):
         dist = np.linspace(0, 1, 2800)
         with self.assertRaisesRegex(ValueError, r"Distorted .* must not be shorter"):
             spqi(dist, signal)
+
+    def test_spqi__input_signals_identical_zero__should_be_valid(self):
+        signal = np.zeros(1024)
+        distorted = np.zeros(1024)
+        signal[-1] = 0.00001
+        result = spqi(distorted, signal)
+        self.assertGreaterEqual(1, result)
+        self.assertGreaterEqual(result, 0)

test/metrics/test_stsim.py

@@ -1,5 +1,5 @@
 """Spectral Temporal SIMilarity Tests"""
-
+import math
 import unittest
 
 import numpy as np
@@ -60,7 +60,13 @@ def test_compute_sim__values_larger_than_one_possible(self):
         ref_block = np.array([[0.5] * 4])
         dist_block = np.array([[0.5, 0.5, 0.5, 1]])
         result = STSIM.compute_sim(ref_block, dist_block)
-        self.assertEqual(1.25, result)
+        self.assertAlmostEqual(1.25, result)
+
+    def test_compute_sim__input_signals_identical_zero__should_be_not_nan(self):
+        signal = np.zeros((4, 1024))
+        distorted = np.zeros((4, 1024))
+        result = STSIM.compute_sim(distorted, signal)
+        self.assertFalse(math.isnan(result))
 
     def test_st_sim_init__eta_grater_one__should_throw(self):
         with self.assertRaisesRegex(ValueError, "Eta must be between 0 and 1."):

test/signal/test_transform.py

@@ -158,6 +158,14 @@ def test_divide_and_normalize__multiple_blocks__correct_reshaped(self):
             np.array_equal(np.array([[-1, 1], [-1, 1], [-1, 1], [-1, 1]]), result)
         )
 
+    def test_divide_and_normalize__input_signals_identical_zero__should_be_not_nan(
+        self,
+    ):
+        input_signal = np.zeros(10)
+        unit = BlockBuilder(5)
+        result = unit.divide_and_normalize(input_signal)
+        self.assertFalse(np.isnan(result).any())
+
 
 class PerceptualSpectrumBuilderTest(unittest.TestCase):
     """Perceptual Spectrum Builder Test"""

vibromaf/metrics/stsim.py

@@ -64,7 +64,7 @@ def compute_sim(reference: np.array, distorted: np.array) -> float:
         return float(
             np.mean(
                 np.sum(reference * distorted, axis=1)
-                / np.sum(np.power(reference, 2), axis=1)
+                / (np.sum(np.power(reference, 2), axis=1) + np.finfo(float).eps)
             )
         )
 

vibromaf/signal/spectrum.py

@@ -30,7 +30,7 @@ def mag2db(power: np.array) -> np.array:
 
 def signal_energy(signal: np.array) -> np.array:
     """Calculate the signal energy"""
-    return np.sum(np.power(signal, 2))
+    return np.sum(np.square(signal, dtype=np.float64))
 
 
 def compute_normalized_spectral_difference(
@@ -40,7 +40,10 @@ def compute_normalized_spectral_difference(
     difference = np.sum(
         np.abs(db2pow(reference_spectrum) - db2pow(distorted_spectrum)), axis=1
     )
-    return pow2db(difference / np.sum(np.abs(db2pow(reference_spectrum)), axis=1))
+    return pow2db(
+        difference
+        / (np.sum(np.abs(db2pow(reference_spectrum)), axis=1) + np.finfo(float).eps)
+    )
 
 
 def compute_spectral_support(spectrum: np.array, scale: float = 12) -> np.array:

vibromaf/signal/transform.py

@@ -76,15 +76,15 @@ def divide_and_normalize(self, signal: np.array) -> np.array:
         blocks = self.divide(signal)
         means = np.apply_along_axis(np.mean, 1, blocks).reshape((blocks.shape[0], 1))
         stds = np.apply_along_axis(np.std, 1, blocks).reshape((blocks.shape[0], 1))
-        return (blocks - means) / stds
+        return (blocks - means) / (stds + np.finfo(float).eps)
 
 
 @dataclass(frozen=True)
 class PerceptualSpectrumBuilder:
     """Calculate perceptual spectrum"""
 
     block_builder: BlockBuilder = BlockBuilder(512)
-    perceptual_threshold: PerceptualThreshold = PerceptualThreshold(2800)
+    perceptual_threshold: PerceptualThreshold = PerceptualThreshold(8000)
     block_transform_strategy: Callable[[np.array], np.array] = compute_block_dct
 
     def compute_perceptual_spectrum(self, signal: np.array) -> np.array: