[BUG] Fix NumPy int and floats being unrecognised in type checks (#108)

Author: tsbinns

src/pybispectra/general/general.py

@@ -9,7 +9,7 @@
     _compute_threenorm,
     _ProcessBispectrum,
 )
-from pybispectra.utils._utils import _compute_in_parallel
+from pybispectra.utils._utils import _compute_in_parallel, _int_like
 
 
 class _General(_ProcessBispectrum):
@@ -42,7 +42,7 @@ def _sort_indices(self, indices: tuple[tuple[int]] | None) -> None:
         for group_idcs in indices:
             if not isinstance(group_idcs, tuple):
                 raise TypeError("Entries of `indices` must be tuples.")
-            if any(not isinstance(idx, int) for idx in group_idcs):
+            if any(not isinstance(idx, _int_like) for idx in group_idcs):
                 raise TypeError("Entries for groups in `indices` must be ints.")
             if any(idx < 0 or idx >= self._n_chans for idx in group_idcs):
                 raise ValueError(

src/pybispectra/tde/tde.py

@@ -10,7 +10,7 @@
 from pybispectra.utils import ResultsTDE
 from pybispectra.utils._defaults import _precision
 from pybispectra.utils._process import _ProcessBispectrum
-from pybispectra.utils._utils import _compute_in_parallel
+from pybispectra.utils._utils import _compute_in_parallel, _number_like, _int_like
 
 
 class TDE(_ProcessBispectrum):
@@ -291,14 +291,14 @@ def _sort_freq_bands(
         fmax: int | float | tuple[int | float],
     ) -> None:
         """Sort inputs for the frequency bounds."""
-        if not isinstance(fmin, (int, float, tuple)):
+        if not isinstance(fmin, _number_like + (tuple,)):
             raise TypeError("`fmin` must be an int, float, or tuple.")
-        if not isinstance(fmax, (int, float, tuple)):
+        if not isinstance(fmax, _number_like + (tuple,)):
             raise TypeError("`fmax` must be an int, float, or tuple.")
 
-        if isinstance(fmin, (int, float)):
+        if isinstance(fmin, _number_like):
             fmin = (fmin,)
-        if isinstance(fmax, (int, float)):
+        if isinstance(fmax, _number_like):
             fmax = (fmax,)
 
         new_fmax = []
@@ -343,12 +343,12 @@ def _sort_metrics(
         """Sort inputs for the form of results being requested."""
         if not isinstance(antisym, (bool, tuple)):
             raise TypeError("`antisym` must be a bool or tuple of bools.")
-        if not isinstance(method, (int, tuple)):
+        if not isinstance(method, _int_like + (tuple,)):
             raise TypeError("`method` must be an int or tuple of ints.")
 
         if isinstance(antisym, bool):
             antisym = (antisym,)
-        if isinstance(method, int):
+        if isinstance(method, _int_like):
             method = (method,)
 
         if any(not isinstance(entry, bool) for entry in antisym):
@@ -388,7 +388,7 @@ def _sort_indices(self, indices: tuple[tuple[int]] | None) -> None:
         for group_idcs in (seeds, targets):
             if not isinstance(group_idcs, tuple):
                 raise TypeError("Entries of `indices` must be tuples.")
-            if any(not isinstance(idx, int) for idx in group_idcs):
+            if any(not isinstance(idx, _int_like) for idx in group_idcs):
                 raise TypeError(
                     "Entries for seeds and targets in `indices` must be ints."
                 )

src/pybispectra/utils/_plot.py

@@ -7,6 +7,8 @@
 from matplotlib.figure import Figure
 from matplotlib.ticker import ScalarFormatter, StrMethodFormatter
 
+from pybispectra.utils._utils import _int_like, _number_like
+
 
 class _PlotBase(ABC):
     """Base class for plotting results.
@@ -52,22 +54,22 @@ def _sort_plot_inputs(
         """
         if nodes is None:
             nodes = tuple(range(self.n_nodes))
-        if not isinstance(nodes, (int, tuple)):
+        if not isinstance(nodes, _int_like + (tuple,)):
             raise TypeError("`nodes` must be an int or tuple.")
         if isinstance(nodes, int):
             nodes = (nodes,)
-        if not all(isinstance(con, int) for con in nodes):
+        if not all(isinstance(con, _int_like) for con in nodes):
             raise TypeError("Entries of `nodes` must be ints.")
         if any(con >= self.n_nodes for con in nodes) or any(con < 0 for con in nodes):
             raise ValueError("The requested node is not present in the results.")
 
-        if not isinstance(n_rows, int) or not isinstance(n_cols, int):
+        if not isinstance(n_rows, _int_like) or not isinstance(n_cols, _int_like):
             raise TypeError("`n_rows` and `n_cols` must be integers.")
         if n_rows < 1 or n_cols < 1:
             raise ValueError("`n_rows` and `n_cols` must be >= 1.")
 
-        if not isinstance(major_tick_intervals, (int, float)) or not isinstance(
-            minor_tick_intervals, (int, float)
+        if not isinstance(major_tick_intervals, _number_like) or not isinstance(
+            minor_tick_intervals, _number_like
         ):
             raise TypeError(
                 "`major_tick_intervals` and `minor_tick_intervals` should be ints or "
@@ -1117,11 +1119,11 @@ def _sort_freq_band_inputs(self, freq_bands: int | tuple[int] | None) -> tuple[i
         if freq_bands is None:
             freq_bands = tuple(range(self._n_fbands))
         else:
-            if not isinstance(freq_bands, (int, tuple)):
+            if not isinstance(freq_bands, _int_like + (tuple,)):
                 raise TypeError("`freq_bands` must be an int or tuple.")
-            if isinstance(freq_bands, int):
+            if isinstance(freq_bands, _int_like):
                 freq_bands = (freq_bands,)
-            if not all(isinstance(fband, int) for fband in freq_bands):
+            if not all(isinstance(fband, _int_like) for fband in freq_bands):
                 raise TypeError("Entries of `freq_bands` must be ints.")
             if any(fband >= self._n_fbands for fband in freq_bands) or any(
                 fband < 0 for fband in freq_bands

src/pybispectra/utils/_process.py

@@ -9,7 +9,7 @@
 from numba import njit
 
 from pybispectra.utils._defaults import _precision
-from pybispectra.utils._utils import _fast_find_first
+from pybispectra.utils._utils import _fast_find_first, _int_like, _number_like
 from pybispectra.utils.results import _ResultsBase
 
 
@@ -70,7 +70,7 @@ def _sort_init_inputs(
                 "`data` and `freqs` must contain the same number of frequencies."
             )
 
-        if not isinstance(sampling_freq, (int, float)):
+        if not isinstance(sampling_freq, _number_like):
             raise TypeError("`sampling_freq` must be an int or a float.")
         if np.abs(freqs).max() > sampling_freq / 2:
             raise ValueError(
@@ -114,7 +114,7 @@ def _sort_indices(self, indices: tuple[tuple[int]] | None) -> None:
         for group_idcs in (seeds, targets):
             if not isinstance(group_idcs, tuple):
                 raise TypeError("Entries of `indices` must be tuples.")
-            if any(not isinstance(idx, int) for idx in group_idcs):
+            if any(not isinstance(idx, _int_like) for idx in group_idcs):
                 raise TypeError(
                     "Entries for seeds and targets in `indices` must be ints."
                 )
@@ -180,7 +180,7 @@ def _sort_freqs(
 
     def _sort_parallelisation(self, n_jobs: int) -> None:
         """Sort parallelisation inputs."""
-        if not isinstance(n_jobs, int):
+        if not isinstance(n_jobs, _int_like):
             raise TypeError("`n_jobs` must be an integer.")
         if n_jobs < 1 and n_jobs != -1:
             raise ValueError("`n_jobs` must be >= 1 or -1.")

src/pybispectra/utils/_utils.py

@@ -9,6 +9,12 @@
 from pybispectra.utils._defaults import _precision
 
 
+# Aliases for type checking
+_int_like = (int, np.integer)
+_float_like = (float, np.floating)
+_number_like = _int_like + _float_like
+
+
 def _compute_in_parallel(
     func: callable,
     loop_kwargs: list[dict],

src/pybispectra/utils/ged.py

@@ -10,7 +10,7 @@
 from mne.time_frequency import csd_array_fourier, csd_array_multitaper
 
 from pybispectra.utils._defaults import _precision
-from pybispectra.utils._utils import _create_mne_info
+from pybispectra.utils._utils import _create_mne_info, _int_like, _number_like
 from pybispectra.utils.utils import compute_rank
 
 
@@ -174,7 +174,7 @@ def _sort_init_inputs(self, data: np.ndarray, sampling_freq: float) -> None:
         if data.ndim != 3:
             raise ValueError("`data` must be a 3D array.")
 
-        if not isinstance(sampling_freq, (int, float)):
+        if not isinstance(sampling_freq, _number_like):
             raise TypeError("`sampling_freq` must be an int or a float.")
         self.sampling_freq = sampling_freq
 
@@ -190,14 +190,14 @@ def _sort_freq_bounds(
     ) -> None:
         """Sort frequency bound inputs."""
         if not isinstance(signal_bounds, tuple) or not all(
-            isinstance(entry, (int, float)) for entry in signal_bounds
+            isinstance(entry, _number_like) for entry in signal_bounds
         ):
             raise TypeError("`signal_bounds` must be a tuple of ints or floats.")
         if not isinstance(noise_bounds, tuple) or not all(
-            isinstance(entry, (int, float)) for entry in noise_bounds
+            isinstance(entry, _number_like) for entry in noise_bounds
         ):
             raise TypeError("`noise_bounds` must be a tuple of ints or floats.")
-        if not isinstance(signal_noise_gap, (int, float)):
+        if not isinstance(signal_noise_gap, _number_like):
             raise TypeError("`signal_noise_gap` must be an int or a float.")
 
         if len(signal_bounds) != 2 or len(noise_bounds) != 2:
@@ -231,7 +231,7 @@ def _sort_bandpass_filter(self, bandpass_filter: bool) -> None:
 
     def _sort_n_harmonics(self, n_harmonics: int) -> None:
         """Sort harmonic use input."""
-        if not isinstance(n_harmonics, int):
+        if not isinstance(n_harmonics, _int_like):
             raise TypeError("`n_harmonics` must be an int.")
 
         if n_harmonics < -1:
@@ -262,7 +262,7 @@ def _sort_indices(self, indices: tuple[int] | None) -> None:
             indices = tuple(np.arange(self._n_chans, dtype=np.int32).tolist())
 
         if not isinstance(indices, tuple) or not all(
-            isinstance(entry, int) for entry in indices
+            isinstance(entry, _int_like) for entry in indices
         ):
             raise TypeError("`indices` must be a tuple of ints.")
 
@@ -280,7 +280,7 @@ def _sort_rank(self, rank: int | None) -> None:
         if rank is None:
             rank = compute_rank(self.data)
 
-        if not isinstance(rank, int):
+        if not isinstance(rank, _int_like):
             raise TypeError("`rank` must be an int.")
 
         if rank < 1 or rank > self._use_n_chans:
@@ -530,7 +530,7 @@ def fit_hpmax(
 
     def _sort_parallelisation(self, n_jobs: int) -> int:
         """Sort parallelisation inputs."""
-        if not isinstance(n_jobs, int):
+        if not isinstance(n_jobs, _int_like):
             raise TypeError("`n_jobs` must be an integer.")
         if n_jobs < 1 and n_jobs != -1:
             raise ValueError("`n_jobs` must be >= 1 or -1.")
@@ -844,7 +844,7 @@ def get_transformed_data(
                 "transformed data."
             )
 
-        if not isinstance(min_ratio, (int, float)):
+        if not isinstance(min_ratio, _number_like):
             raise TypeError("`min_ratio` must be an int or a float")
         if not isinstance(copy, bool):
             raise TypeError("`copy` must be a bool.")

src/pybispectra/utils/results.py

@@ -6,6 +6,7 @@
 from matplotlib.figure import Figure
 
 from pybispectra.utils._plot import _PlotCFC, _PlotGeneral, _PlotTDE, _PlotWaveShape
+from pybispectra.utils._utils import _int_like
 
 
 class _ResultsBase(ABC):
@@ -66,7 +67,7 @@ def _sort_indices_seeds_targets(self, indices: tuple[tuple[int]]) -> None:
         for group_idcs in (seeds, targets):
             if not isinstance(group_idcs, tuple):
                 raise TypeError("Entries of `indices` must be tuples.")
-            if any(not isinstance(idx, int) for idx in group_idcs):
+            if any(not isinstance(idx, _int_like) for idx in group_idcs):
                 raise TypeError(
                     "Entries for seeds and targets in `indices` must be ints."
                 )
@@ -85,7 +86,7 @@ def _sort_indices_channels(self, indices: tuple[int]) -> None:
         """Sort ``indices`` with inputs format [channels]."""
         if not isinstance(indices, tuple):
             raise TypeError("`indices` must be a tuple.")
-        if not all(isinstance(idx, int) for idx in indices):
+        if not all(isinstance(idx, _int_like) for idx in indices):
             raise TypeError("Entries of `indices` must be ints.")
         if any(idx < 0 for idx in indices):
             raise ValueError("Entries of `indices` must be >= 0.")
@@ -103,7 +104,7 @@ def _sort_indices_kmn(self, indices: tuple[tuple[int]]) -> None:
         for group_idcs in indices:
             if not isinstance(group_idcs, tuple):
                 raise TypeError("Entries of `indices` must be tuples.")
-            if any(not isinstance(idx, int) for idx in group_idcs):
+            if any(not isinstance(idx, _int_like) for idx in group_idcs):
                 raise TypeError("Entries for groups in `indices` must be ints.")
             if any(idx < 0 for idx in group_idcs):
                 raise ValueError(r"Entries for groups in `indices` must be >= 0.")

src/pybispectra/utils/utils.py

@@ -11,7 +11,7 @@
 
 from pybispectra import __version__ as version
 from pybispectra.utils._defaults import _precision
-from pybispectra.utils._utils import _compute_in_parallel
+from pybispectra.utils._utils import _compute_in_parallel, _int_like, _number_like
 
 
 def compute_fft(
@@ -128,12 +128,12 @@ def _compute_fft_input_checks(
     if not np.isreal(data).all():
         raise ValueError("`data` must be real-valued.")
 
-    if not isinstance(sampling_freq, (int, float)):
+    if not isinstance(sampling_freq, _number_like):
         raise TypeError("`sampling_freq` must be an int or a float.")
 
     if n_points is None:
         n_points = data.shape[2]
-    if not isinstance(n_points, int):
+    if not isinstance(n_points, _int_like):
         raise TypeError("`n_points` must be an integer")
 
     if not isinstance(window, str):
@@ -145,7 +145,7 @@ def _compute_fft_input_checks(
     else:
         window_func = np.hamming
 
-    if not isinstance(n_jobs, int):
+    if not isinstance(n_jobs, _int_like):
         raise TypeError("`n_jobs` must be an integer.")
     if n_jobs < 1 and n_jobs != -1:
         raise ValueError("`n_jobs` must be >= 1 or -1.")
@@ -291,7 +291,7 @@ def _compute_tfr_input_checks(
     if data.ndim != 3:
         raise ValueError("`data` must be a 3D array.")
 
-    if not isinstance(sampling_freq, (int, float)):
+    if not isinstance(sampling_freq, _number_like):
         raise TypeError("`sampling_freq` must be an int or a float.")
 
     if not isinstance(freqs, np.ndarray):
@@ -315,7 +315,7 @@ def _compute_tfr_input_checks(
     else:
         tfr_func = time_frequency.tfr_array_multitaper
 
-    if not isinstance(n_cycles, (np.ndarray, int, float)):
+    if not isinstance(n_cycles, _number_like + (np.ndarray,)):
         raise TypeError("`n_cycles` must be a NumPy array, an int, or a float.")
     if isinstance(n_cycles, np.ndarray):
         if n_cycles.shape != freqs.shape:
@@ -334,10 +334,10 @@ def _compute_tfr_input_checks(
         raise TypeError("`use_fft` must be a bool.")
 
     if tfr_mode == "multitaper":
-        if not isinstance(multitaper_time_bandwidth, (int, float)):
+        if not isinstance(multitaper_time_bandwidth, _number_like):
             raise TypeError("`multitaper_time_bandwidth` must be an int or a float.")
 
-    if not isinstance(n_jobs, int):
+    if not isinstance(n_jobs, _int_like):
         raise TypeError("`n_jobs` must be an integer.")
     if n_jobs < 1 and n_jobs != -1:
         raise ValueError("`n_jobs` must be >= 1 or -1.")
@@ -375,7 +375,7 @@ def compute_rank(data: np.ndarray, sv_tol: int | float = 1e-5) -> int:
     if data.ndim != 3:
         raise ValueError("`data` must be a 3D array.")
 
-    if not isinstance(sv_tol, (int, float)):
+    if not isinstance(sv_tol, _number_like):
         raise TypeError("`sv_tol` must be a float or an int.")
 
     singular_vals = np.linalg.svd(data, compute_uv=False).min(axis=0)

src/pybispectra/waveshape/waveshape.py

@@ -9,7 +9,7 @@
     _ProcessBispectrum,
 )
 from pybispectra.utils.results import ResultsWaveShape
-from pybispectra.utils._utils import _compute_in_parallel
+from pybispectra.utils._utils import _compute_in_parallel, _int_like
 
 np.seterr(divide="ignore", invalid="ignore")  # no warning for NaN division
 
@@ -125,7 +125,7 @@ def compute(
         where the resulting values lie in the range :math:`[-1, 1]`.
 
         Bicoherence is computed for all values of ``f1s`` and ``f2s``.
-        
+
         .. warning::
             For values of ``f1s`` higher than ``f2s`` or where ``f2s + f1s`` exceeds the
             Nyquist frequency, a :obj:`numpy.nan` value is returned.
@@ -165,7 +165,7 @@ def _sort_indices(self, indices: tuple[int]) -> None:
             indices = tuple(range(self._n_chans))
         if not isinstance(indices, tuple):
             raise TypeError("`indices` must be a tuple.")
-        if any(not isinstance(idx, int) for idx in indices):
+        if any(not isinstance(idx, _int_like) for idx in indices):
             raise TypeError("Entries of `indices` must be ints.")
 
         if any(idx < 0 or idx >= self._n_chans for idx in indices):