Fix to prevent errors with numpy>=1.24.0 (replace all int and np.int with np.int_)

Signed-off-by: HaHeho <[email protected]>

Author: HaHeho

README.rst

@@ -127,6 +127,7 @@ Version history
 ---------------
 
 *unreleased*
+    * Fix to prevent errors with `NumPy >= 1.24.0 <https://numpy.org/doc/stable//release/1.24.0-notes.html>`_ (replace all `int` and `np.int` with `np.int_`)
     * Improve `read_miro_struct()` to give warnings in case elevation data is found
     * Fix *Exp4* loading of MIRO files and improve documentation table formatting
     * Update README to reflect the name change of master branch to "main"

sound_field_analysis/gen.py

@@ -145,7 +145,7 @@ def lebedev(max_order=None, degree=None):
     allowed_degrees = [6, 14, 26, 38, 50, 74, 86, 110, 146, 170, 194]
 
     if max_order and 0 <= max_order <= 11:
-        degree = allowed_degrees[int(max_order) - 1]
+        degree = allowed_degrees[_np.int_(max_order) - 1]
     elif max_order:
         raise ValueError("Maximum order can only be between 0 and 11.")
 
@@ -276,7 +276,7 @@ def pressure_on_sphere(max_order, kr, taper_weights=None):
         p = _np.zeros_like(kr)
         for n in range(max_order + 1):
             # Calculate mode strength b_n(kr) for an incident plane wave on sphere according to [1, Eq.(9)]
-            b_n = (4 * _np.pi * 1j ** n) * (
+            b_n = (4 * _np.pi * 1j**n) * (
                 spherical_jn(n, kr)
                 - (
                     spherical_jn(n, kr, derivative=True)
@@ -332,11 +332,11 @@ def spherical_head_filter_spec(
     Implement `arctan()` soft-clipping
     """
     # frequency support vector & corresponding wave numbers k
-    freqs = _np.linspace(0, fs / 2, int(NFFT / 2 + 1))
+    freqs = _np.linspace(0, fs / 2, _np.int_(NFFT / 2 + 1))
     kr_SHF = kr(freqs, radius)
 
     # calculate SH order necessary to expand sound field in entire modal range
-    order_full = int(_np.ceil(kr_SHF[-1]))
+    order_full = _np.int_(_np.ceil(kr_SHF[-1]))
 
     # calculate filter
     G_SHF = spherical_head_filter(
@@ -532,7 +532,7 @@ def ideal_wave(
     """
     array_configuration = ArrayConfiguration(*array_configuration)
 
-    order = _np.int(order)
+    order = _np.int_(order)
     NFFT = NFFT // 2 + 1
     NMLocatorSize = (order + 1) ** 2
 
@@ -609,7 +609,7 @@ def spherical_noise(
             order_max, gridData.azimuth, gridData.colatitude, kind=kind
         )
     else:
-        order_max = _np.int(_np.sqrt(spherical_harmonic_bases.shape[1]) - 1)
+        order_max = _np.int_(_np.sqrt(spherical_harmonic_bases.shape[1]) - 1)
     return _np.inner(
         spherical_harmonic_bases,
         _np.random.randn((order_max + 1) ** 2)

sound_field_analysis/io.py

@@ -466,10 +466,12 @@ def _check_irs(irs):
     # store SOFA data as named tuple
     if isinstance(file, sofa.SOFAConventions.SOFASimpleFreeFieldHRIR):
         hrir_l = TimeSignal(
-            signal=_check_irs(file.getDataIR()[:, 0]), fs=int(file.getSamplingRate()[0])
+            signal=_check_irs(file.getDataIR()[:, 0]),
+            fs=_np.int_(file.getSamplingRate()[0]),
         )
         hrir_r = TimeSignal(
-            signal=_check_irs(file.getDataIR()[:, 1]), fs=int(file.getSamplingRate()[0])
+            signal=_check_irs(file.getDataIR()[:, 1]),
+            fs=_np.int_(file.getSamplingRate()[0]),
         )
 
         # transform grid into azimuth, colatitude, radius in radians
@@ -486,7 +488,7 @@ def _check_irs(irs):
     else:  # isinstance(file, sofa.SOFAConventions.SOFASingleRoomDRIR):
         drir_signal = TimeSignal(
             signal=_check_irs(_np.squeeze(file.getDataIR())),
-            fs=int(file.getSamplingRate()[0]),
+            fs=_np.int_(file.getSamplingRate()[0]),
         )
 
         # transform grid into azimuth, colatitude, radius in radians
@@ -643,13 +645,13 @@ def write_SSR_IRs(filename, time_data_l, time_data_r, wavformat="float32"):
     if wavformat in ["float32", "float"]:
         sio.wavfile.write(
             filename=filename,
-            rate=int(time_data_l.signal.fs),
+            rate=_np.int_(time_data_l.signal.fs),
             data=data_to_write.T.astype(_np.float32),
         )
     elif wavformat in ["int32", "int16"]:
         sio.wavfile.write(
             filename=filename,
-            rate=int(time_data_l.signal.fs),
+            rate=_np.int_(time_data_l.signal.fs),
             data=(data_to_write.T * _np.iinfo(wavformat).max).astype(wavformat),
         )
     else:

sound_field_analysis/plot.py

@@ -115,7 +115,7 @@ def makeMTX(
     """
 
     if not viz_order:
-        viz_order = _np.int(_np.ceil(_np.sqrt(spat_coeffs.shape[0]) - 1))
+        viz_order = _np.int_(_np.ceil(_np.sqrt(spat_coeffs.shape[0]) - 1))
 
     angles = (
         _np.mgrid[0:360:stepsize_deg, 0:181:stepsize_deg].reshape((2, -1))
@@ -152,7 +152,7 @@ def makeFullMTX(Pnm, dn, kr, viz_order=None):
     """
     kr = _np.asarray(kr)
     if not viz_order:
-        viz_order = _np.int(_np.ceil(_np.sqrt(Pnm.shape[0]) - 1))
+        viz_order = _np.int_(_np.ceil(_np.sqrt(Pnm.shape[0]) - 1))
 
     N = kr.size
     vizMtx = []
@@ -586,8 +586,8 @@ def plot3Dgrid(rows, cols, viz_data, style, normalize=True, title=None):
     for IDX in range(0, len(viz_data)):
         fig.add_trace(
             _genVisual(viz_data[IDX], style=style, normalize=normalize),
-            row=int(rows[IDX]),
-            col=int(cols[IDX]),
+            row=_np.int_(rows[IDX]),
+            col=_np.int_(cols[IDX]),
         )
         fig.layout[f"scene{IDX + 1:d}"].update(layout_3D)
 

sound_field_analysis/process.py

@@ -72,14 +72,14 @@ def BEMA(Pnm, center_sig, dn, transition, avg_band_width=1, fade=True, max_order
     """
 
     if not max_order:
-        max_order = int(_np.sqrt(Pnm.shape[0] - 1))  # SH order
+        max_order = _np.int_(_np.sqrt(Pnm.shape[0] - 1))  # SH order
 
-    transition = int(_np.floor(transition))
+    transition = _np.int_(_np.floor(transition))
 
     # computing spatio-temporal Image Imn
-    Imn = _np.zeros((Pnm.shape[0], 1), dtype=complex)
+    Imn = _np.zeros((Pnm.shape[0], 1), dtype=_np.complex_)
     # first bin for averaging
-    start_avg_bin = int(_np.floor(transition / (_np.power(2, avg_band_width))))
+    start_avg_bin = _np.int_(_np.floor(transition / (_np.power(2, avg_band_width))))
 
     modeCnt = 0
     avgPower = 0
@@ -104,7 +104,7 @@ def BEMA(Pnm, center_sig, dn, transition, avg_band_width=1, fade=True, max_order
     )
     center_sig = _np.multiply(center_sig, (1 / sq_avg))
 
-    Pnm_synth = _np.zeros(Pnm.shape, dtype=complex)
+    Pnm_synth = _np.zeros(Pnm.shape, dtype=_np.complex_)
     modeCnt = 0
     for n in range(0, max_order + 1):
         for _ in range(0, 2 * n + 1):
@@ -216,7 +216,7 @@ def FFT(
     signals = signals[:, first_sample:last_sample]
 
     if not NFFT:
-        NFFT = int(2 ** _np.ceil(_np.log2(total_samples)))
+        NFFT = _np.int_(2 ** _np.ceil(_np.log2(total_samples)))
 
     fftData = _np.fft.rfft(signals, NFFT * oversampling, 1)
     if not calculate_freqs:
@@ -432,7 +432,7 @@ def iSpatFT(
     # TODO: Check `spherical_coefficients` and `spherical_harmonic_bases` length
     #  correspond with `order_max`
     if order_max is None:
-        order_max = int(_np.sqrt(number_of_coefficients) - 1)
+        order_max = _np.int_(_np.sqrt(number_of_coefficients) - 1)
 
     # Re-generate spherical harmonic bases if they were not provided or their
     # order is too small
@@ -494,7 +494,7 @@ def plane_wave_decomp(
             "radial filter (dn) are not consistent."
         )
 
-    max_order = int(_np.floor(_np.sqrt(NMDeliveredSize) - 1))
+    max_order = _np.int_(_np.floor(_np.sqrt(NMDeliveredSize) - 1))
     if order > max_order:
         raise ValueError(
             f"The provided coefficients deliver a maximum order of {max_order} "
@@ -629,7 +629,7 @@ def rfi(dn, kernelSize=512, highPass=0.0):
     # downsize kernel
     latency = kernelSize / 2
     mid = dn_ir.shape[-1] / 2
-    dn_ir = dn_ir[:, int(mid - latency) : int(mid + latency)]
+    dn_ir = dn_ir[:, _np.int_(mid - latency) : _np.int_(mid + latency)]
 
     # apply Hanning / cosine window
     # 0.5 + 0.5 * _np.cos(2 * _np.pi * (_np.arange(0, kernelSize)
@@ -714,7 +714,7 @@ def sfe(Pnm_kra, kra, krb, problem="interior"):
         raise ValueError("Invalid problem: Choose either interior or exterior.")
 
     FCoeff = Pnm_kra.shape[0]
-    N = int(_np.floor(_np.sqrt(FCoeff) - 1))
+    N = _np.int_(_np.floor(_np.sqrt(FCoeff) - 1))
 
     nvector = _np.zeros(FCoeff)
     IDX = 1

sound_field_analysis/sph.py

@@ -149,7 +149,7 @@ def spbessel(n, kr):
         )
         J[_np.logical_and(kr == 0, n == 0)] = 1
     else:
-        J = scy.spherical_jn(n.astype(_np.int), kr)
+        J = scy.spherical_jn(n.astype(_np.int_), kr)
     return _np.squeeze(J)
 
 
@@ -179,7 +179,7 @@ def spneumann(n, kr):
         )
         Yv[kr < 0] = -Yv[kr < 0]
     else:
-        Yv = scy.spherical_yn(n.astype(_np.int), kr)
+        Yv = scy.spherical_yn(n.astype(_np.int_), kr)
         # return possible infs as nan to stay consistent
         Yv[_np.isinf(Yv)] = _np.nan
     return _np.squeeze(Yv)
@@ -277,7 +277,7 @@ def dspneumann(n, kr):
         return spneumann(n, kr) * n / kr - spneumann(n + 1, kr)
     else:
         return scy.spherical_yn(
-            n.astype(_np.int), kr.astype(_np.complex), derivative=True
+            n.astype(_np.int_), kr.astype(_np.complex_), derivative=True
         )
 
 
@@ -400,7 +400,7 @@ def array_extrapolation(order, freqs, array_configuration, normalize=True):
     k_dual = None
 
     if normalize:
-        scale_factor = _np.squeeze(4 * _np.pi * 1j ** order)
+        scale_factor = _np.squeeze(4 * _np.pi * 1j**order)
     else:
         scale_factor = 1
 
@@ -639,7 +639,7 @@ def mnArrays(nMax):
     # Order m = 0, -1, 0, 1, -2, -1, 0, 1, 2, ...
     # http://oeis.org/A196199
     elementNumber = _np.arange((nMax + 1) ** 2) + 1
-    t = _np.floor(_np.sqrt(elementNumber - 1)).astype(int)
+    t = _np.floor(_np.sqrt(elementNumber - 1)).astype(_np.int_)
     m = elementNumber - t * t - t - 1
 
     return m, n
@@ -661,7 +661,7 @@ def reverseMnIds(nMax):
     """
     m_ids = list(range(nMax * (nMax + 2) + 1))
     for o in range(nMax + 1):
-        id_start = o ** 2
+        id_start = o**2
         id_end = id_start + o * 2 + 1
         m_ids[id_start:id_end] = reversed(m_ids[id_start:id_end])
     return m_ids
@@ -728,7 +728,7 @@ def kr_full_spec(fs, radius, NFFT, temperature=20):
     kr : array_like
        kr vector of length NFFT/2 + 1 spanning the frequencies of 0:fs/2
     """
-    freqs = _np.linspace(0, fs / 2, int(NFFT / 2 + 1))
+    freqs = _np.linspace(0, fs / 2, _np.int_(NFFT / 2 + 1))
     return kr(freqs, radius, temperature)
 
 
@@ -775,14 +775,14 @@ def _print_mic_scaling(N, freqs, array_radius, scatter_radius=None, dual_radius=
 
 
 def _print_bns(N, k_mic, k_scatter):
-    print("bn_open_omni:", bn_open_omni(N, k_mic) * 4 * _np.pi * 1j ** N)
-    print("bn_open_cardioid:", bn_open_cardioid(N, k_mic) * 4 * _np.pi * 1j ** N),
-    print("bn_rigid_omni:", bn_rigid_omni(N, k_mic, k_scatter) * 4 * _np.pi * 1j ** N),
+    print("bn_open_omni:", bn_open_omni(N, k_mic) * 4 * _np.pi * 1j**N)
+    print("bn_open_cardioid:", bn_open_cardioid(N, k_mic) * 4 * _np.pi * 1j**N),
+    print("bn_rigid_omni:", bn_rigid_omni(N, k_mic, k_scatter) * 4 * _np.pi * 1j**N),
     print(
         "bn_rigid_cardioid:",
-        bn_rigid_cardioid(N, k_mic, k_scatter) * 4 * _np.pi * 1j ** N,
+        bn_rigid_cardioid(N, k_mic, k_scatter) * 4 * _np.pi * 1j**N,
     )
     print(
         "bn_dual_open_omni:",
-        bn_dual_open_omni(N, k_mic, k_scatter) * 4 * _np.pi * 1j ** N,
+        bn_dual_open_omni(N, k_mic, k_scatter) * 4 * _np.pi * 1j**N,
     )

sound_field_analysis/utils.py

@@ -88,13 +88,13 @@ def progress_bar(curIDX, maxIDX=None, description="Progress"):
     if maxIDX is None:
         print(f"\r{description}: {next(spinner)}", end="", flush=True)
     else:
-        maxIDX = int(maxIDX) - 1
+        maxIDX = np.int_(maxIDX) - 1
         if maxIDX == 0:
             amount_done = 1
         else:
             amount_done = curIDX / maxIDX
         print(
-            f'\r{description}: [{"#" * int(amount_done * 50):50s}] {amount_done * 100:.1f}%',
+            f'\r{description}: [{"#" * np.int_(amount_done * 50):50s}] {amount_done * 100:.1f}%',
             end="",
             flush=True,
         )
@@ -298,7 +298,9 @@ def interleave_channels(left_channel, right_channel, style=None):
 
 def simple_resample(data, original_fs, target_fs):
     """Wrap scipy.signal.resample with a simpler API."""
-    return resample(data, num=int(data.shape[-1] * target_fs / original_fs), axis=-1)
+    return resample(
+        data, num=np.int_(data.shape[-1] * target_fs / original_fs), axis=-1
+    )
 
 
 def scalar_broadcast_match(a, b):