fix tests and examples

examples/energy_decay_curves_and_reverberation_time.ipynb

@@ -164,7 +164,7 @@
     "plt.axvline(rir_1_noise.signal_length*interval[0], color='red', label='Interval')\n",
     "plt.axvline(rir_1_noise.signal_length*interval[1], color='red')\n",
     "\n",
-    "noise_energy = ra.estimate_noise_energy(\n",
+    "noise_energy = ra.dsp.estimate_noise_energy(\n",
     "    rir_1_noise, interval=interval, is_energy=False)\n",
     "\n",
     "noise_energy_db = 10*np.log10(noise_energy)\n",
@@ -232,12 +232,12 @@
    "outputs": [],
    "source": [
     "start_sample = pf.dsp.find_impulse_response_start(rir_1_noise)\n",
-    "rir_noise_shifted = ra.time_shift(rir_1_noise, -start_sample, circular_shift=False)\n",
-    "edc_full_rir = ra.schroeder_integration(rir_noise_shifted, is_energy=False)\n",
+    "rir_noise_shifted = pf.dsp.time_shift(rir_1_noise, -start_sample, mode='linear')\n",
+    "edc_full_rir = ra.edc.schroeder_integration(rir_noise_shifted, is_energy=False)\n",
     "\n",
     "start_sample = pf.dsp.find_impulse_response_start(rir_1)\n",
-    "rir_shifted = ra.time_shift(rir_1, -start_sample, circular_shift=False)\n",
-    "edc_full_rir_compare = ra.schroeder_integration(rir_shifted, is_energy=False)\n",
+    "rir_shifted = pf.dsp.time_shift(rir_1, -start_sample, mode='linear')\n",
+    "edc_full_rir_compare = ra.edc.schroeder_integration(rir_shifted, is_energy=False)\n",
     "edc_full_rir_compare.time /= np.atleast_2d(edc_full_rir_compare.time[..., 0]).T\n",
     "edc_full_rir.time /= np.atleast_2d(edc_full_rir.time[..., 0]).T\n",
     "\n",
@@ -275,7 +275,7 @@
    "outputs": [],
    "source": [
     "intersection_time, late_reveberation_time, noise_level_lundeby = \\\n",
-    "    ra.intersection_time_lundeby(\n",
+    "    ra.edc.intersection_time_lundeby(\n",
     "        rir_1_noise, freq='broadband', is_energy=False,\n",
     "        time_shift=True, channel_independent=False, plot=True)\n",
     "\n",
@@ -296,7 +296,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "edc_truncation = ra.energy_decay_curve_truncation(\n",
+    "edc_truncation = ra.edc.energy_decay_curve_truncation(\n",
     "        rir_1_noise, freq='broadband', is_energy=False, time_shift=True,\n",
     "        channel_independent=False, normalize=True, plot=False)\n",
     "\n",
@@ -325,7 +325,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "edc_chu_auto = ra.energy_decay_curve_chu(\n",
+    "edc_chu_auto = ra.edc.energy_decay_curve_chu(\n",
     "        rir_1_noise, noise_level='auto', is_energy=False, time_shift=True,\n",
     "        channel_independent=False, normalize=True, plot=False)"
    ]
@@ -336,8 +336,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "noise_level_man = ra.estimate_noise_energy(rir_1_noise, interval=[0.6, 1.0], is_energy=False)\n",
-    "edc_chu_man = ra.energy_decay_curve_chu(\n",
+    "noise_level_man = ra.dsp.estimate_noise_energy(rir_1_noise, interval=[0.6, 1.0], is_energy=False)\n",
+    "edc_chu_man = ra.edc.energy_decay_curve_chu(\n",
     "        rir_1_noise, noise_level=noise_level_man, is_energy=False, time_shift=True,\n",
     "        channel_independent=False, normalize=True, plot=False)"
    ]
@@ -348,7 +348,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "edc_chu_noise_lundeby = ra.energy_decay_curve_chu(\n",
+    "edc_chu_noise_lundeby = ra.edc.energy_decay_curve_chu(\n",
     "        rir_1_noise, noise_level=noise_level_lundeby, is_energy=False, time_shift=True,\n",
     "        channel_independent=False, normalize=True, plot=False)"
    ]
@@ -392,7 +392,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "edc_lundeby = ra.energy_decay_curve_lundeby(\n",
+    "edc_lundeby = ra.edc.energy_decay_curve_lundeby(\n",
     "        rir_1_noise, is_energy=False, time_shift=True,\n",
     "        channel_independent=False, normalize=True, plot=False)\n",
     "\n",
@@ -421,7 +421,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "edc_chu_lundeby = ra.energy_decay_curve_chu_lundeby(\n",
+    "edc_chu_lundeby = ra.edc.energy_decay_curve_chu_lundeby(\n",
     "        rir_1_noise, freq='broadband', is_energy=False, time_shift=True,\n",
     "        channel_independent=False, normalize=True, plot=False)\n",
     "\n",
@@ -472,7 +472,7 @@
     "reverberation_times = np.zeros(len(edcs))\n",
     "for idx, edc in enumerate(edcs):\n",
     "    reverberation_times[idx] = \\\n",
-    "        ra.reverberation_time_linear_regression(\n",
+    "        ra.parameters.reverberation_time_linear_regression(\n",
     "            edc, T=Tx)"
    ]
   },
@@ -528,7 +528,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.11"
+   "version": "3.13.4"
   }
  },
  "nbformat": 4,

pyrato/__init__.py

@@ -23,5 +23,5 @@
     'dsp',
     'analytic',
     'parametric',
-    'air_attenuation_coefficient'
+    'air_attenuation_coefficient',
 ]

pyrato/parameters.py

@@ -60,7 +60,7 @@ def reverberation_time_linear_regression(
     >>> rir = rir + awgn
     ...
     >>> edc = ra.energy_decay_curve_chu_lundeby(rir)
-    >>> t_20 = ra.reverberation_time_linear_regression(edc, 'T20')
+    >>> t_20 = ra.parameters.reverberation_time_linear_regression(edc, 'T20')
     >>> t_20
     ...     array([0.99526253])
 

pyrato/parametric.py

@@ -1,13 +1,10 @@
-# -*- coding: utf-8 -*-
-"""Module for room acoustics related functions."""
+"""Module for room acoustics related functions.
 
-"""Parametric room acoustics calculations using simple geometric considerations
+Parametric room acoustics calculations using simple geometric considerations
 such as Sabine's theory of sound in rooms.
 """
-
 import numpy as np
 
-
 def energy_decay_curve_analytic(
         surfaces, alphas, volume, times, source=None,
         receiver=None, method='eyring', c=343.4, frequency=None,
@@ -115,7 +112,7 @@ def air_attenuation_coefficient(
 
     warnings.warn(
         'Will be replaced by respective function in pyfar before v1.0.0',
-        PyfarDeprecationWarning)
+        PyfarDeprecationWarning, stacklevel=2)
 
     # room temperature in Kelvin
     t_K = temperature + 273.16

tests/test_deprecation_warnings.py

@@ -36,13 +36,3 @@ def test_warning_start_ir():
 
         sig = pf.Signal([0, 0, 1, 0, 0], 44100)
         pyrato.dsp.find_impulse_response_start(sig)
-
-
-def test_warning_rt_edc():
-    times = np.linspace(0, 1.5, 2**9)
-    m = -60
-    edc = times * m
-    edc_exp = pf.TimeData(10**(edc/10), times)
-    with pytest.warns(DeprecationWarning, match='0.5.0'):
-        pyrato.reverberation_time_energy_decay_curve(
-            edc_exp)

tests/test_edc.py

@@ -16,7 +16,7 @@ def test_edc_eyring():
     surfaces = [2, 5*2]
     volume = 2*2*2
     times = np.linspace(0, 0.25, 50)
-    edc = ra.energy_decay_curve_analytic(
+    edc = ra.parametric.energy_decay_curve_analytic(
         surfaces, alphas, volume, times, method='eyring', air_absorption=False)
 
     truth = array([
@@ -43,7 +43,7 @@ def test_edc_sabine():
     surfaces = [2, 5*2]
     volume = 2*2*2
     times = np.linspace(0, 0.25, 50)
-    edc = ra.energy_decay_curve_analytic(
+    edc = ra.parametric.energy_decay_curve_analytic(
         surfaces, alphas, volume, times, method='sabine', air_absorption=False)
 
     truth = array([

tests/test_rt.py

@@ -17,7 +17,7 @@ def test_rt_from_edc(tx):
     m = -60
     edc = times * m
     edc_exp = pf.TimeData(10**(edc/10), times)
-    RT_est = ra.reverberation_time_linear_regression(
+    RT_est = ra.parameters.reverberation_time_linear_regression(
         edc_exp, T=tx)
     npt.assert_allclose(RT_est, 1.)
 
@@ -30,7 +30,7 @@ def test_rt_from_edc_mulitchannel(tx):
     m = -60
     edc = np.atleast_2d(m/Ts).T @ np.atleast_2d(times)
     edc_exp = pf.TimeData(10**(edc/10), times)
-    RT_est = ra.reverberation_time_linear_regression(
+    RT_est = ra.parameters.reverberation_time_linear_regression(
         edc_exp, T=tx)
     npt.assert_allclose(RT_est, Ts)
 
@@ -47,7 +47,7 @@ def test_rt_from_edc_mulitchannel_amplitude(tx):
         edc[idx] = As[idx] + m*times/Ts[idx]
 
     edc_exp = pf.TimeData(10**(edc/10), times)
-    RT_est, A_est = ra.reverberation_time_linear_regression(
+    RT_est, A_est = ra.parameters.reverberation_time_linear_regression(
         edc_exp, T=tx, return_intercept=True)
     npt.assert_allclose(RT_est, Ts)
     npt.assert_allclose(A_est, 10**(As/10))
@@ -61,4 +61,4 @@ def test_rt_from_edc_error():
     T = 'Bla'
 
     with pytest.raises(ValueError, match='is not a valid interval.'):
-        ra.reverberation_time_linear_regression(edc_exp, T=T)
+        ra.parameters.reverberation_time_linear_regression(edc_exp, T=T)