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changing some 'is' to '==' #18

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ca9e343
changing some 'is' to '=='
tonoplast Mar 8, 2023
7965a29
changing some 'is' to '=='
tonoplast Mar 9, 2023
f48ea67
changing some 'is' to '==', deprecation update
tonoplast Mar 9, 2023
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10 changes: 5 additions & 5 deletions tensorpac/pac.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,7 @@ def filter(self, sf, x, ftype='phase', keepfilt=False, edges=None,
assert isinstance(sf, (int, float)), ("The sampling frequency must be "
"a float number.")
# Compatibility between keepfilt and wavelet :
if (keepfilt is True) and (self._dcomplex is 'wavelet'):
if (keepfilt is True) and (self._dcomplex == 'wavelet'):
raise ValueError("Using wavelet for the complex decomposition do "
"not allow to get filtered data only. Set the "
"keepfilt parameter to False or set dcomplex to "
Expand All @@ -86,11 +86,11 @@ def filter(self, sf, x, ftype='phase', keepfilt=False, edges=None,

# ---------------------------------------------------------------------
# Switch between phase or amplitude :
if ftype is 'phase':
if ftype == 'phase':
tosend = 'pha' if not keepfilt else None
xfilt = spectral(x, sf, self.f_pha, tosend, self._dcomplex,
self._cycle[0], self._width, n_jobs)
elif ftype is 'amplitude':
elif ftype == 'amplitude':
tosend = 'amp' if not keepfilt else None
xfilt = spectral(x, sf, self.f_amp, tosend, self._dcomplex,
self._cycle[1], self._width, n_jobs)
Expand Down Expand Up @@ -155,7 +155,7 @@ def _infer_pvalues(self, effect, perm, p=.05, mcp='maxstat'):
# ---------------------------------------------------------------------
logger.info(f" infer p-values at (p={p}, mcp={mcp})")
# computes the pvalues
if mcp is 'maxstat':
if mcp == 'maxstat':
max_p = perm.reshape(n_perm, -1).max(1)[np.newaxis, ...]
nb_over = (effect[..., np.newaxis] <= max_p).sum(-1)
pvalues = nb_over / n_perm
Expand All @@ -164,7 +164,7 @@ def _infer_pvalues(self, effect, perm, p=.05, mcp='maxstat'):
pvalues = np.maximum(1. / n_perm, pvalues)
elif mcp in ['fdr', 'bonferroni']:
from mne.stats import fdr_correction, bonferroni_correction
fcn = fdr_correction if mcp is 'fdr' else bonferroni_correction
fcn = fdr_correction if mcp == 'fdr' else bonferroni_correction
# compute the p-values
pvalues = (effect[np.newaxis, ...] <= perm).sum(0) / n_perm
pvalues = np.maximum(1. / n_perm, pvalues)
Expand Down
8 changes: 4 additions & 4 deletions tensorpac/spectral.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,7 @@ def spectral(x, sf, f, stype, dcomplex, cycle, width, n_jobs):
"""
n_freqs = f.shape[0]
# Filtering + complex decomposition :
if dcomplex is 'hilbert':
if dcomplex == 'hilbert':
# get filtering coefficients
b = []
a = np.zeros((n_freqs,), dtype=float)
Expand All @@ -58,15 +58,15 @@ def spectral(x, sf, f, stype, dcomplex, cycle, width, n_jobs):
xd = np.asarray(xf)
if stype is not None:
xd = hilbertm(xd)
elif dcomplex is 'wavelet':
elif dcomplex == 'wavelet':
f = f.mean(1) # centered frequencies
xd = Parallel(n_jobs=n_jobs, **CONFIG['JOBLIB_CFG'])(delayed(morlet)(
x, sf, k, width) for k in f)

# Extract phase / amplitude :
if stype is 'pha':
if stype == 'pha':
return np.angle(xd).astype(np.float64)
elif stype is 'amp':
elif stype == 'amp':
return np.abs(xd).astype(np.float64)
elif stype is None:
return xd.astype(np.float64)
Expand Down
6 changes: 3 additions & 3 deletions tensorpac/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,7 +61,7 @@ def _check_freq(f):
if len(f.reshape(-1)) == 1:
raise ValueError("The length of f should at least be 2.")
elif 2 in f.shape: # f of shape (N, 2) or (2, N)
if f.shape[1] is not 2:
if f.shape[1] != 2:
f = f.T
elif np.squeeze(f).shape == (4,): # (f_start, f_end, f_width, f_step)
f = _pair_vectors(*tuple(np.squeeze(f)))
Expand Down Expand Up @@ -202,7 +202,7 @@ def plot(self, f_min=None, f_max=None, confidence=95, interp=None,
plt.xlim(f_min, f_max)
if log:
from matplotlib.ticker import ScalarFormatter
plt.xscale('log', basex=10)
plt.xscale('log', base=10)
plt.gca().xaxis.set_major_formatter(ScalarFormatter())
if grid:
plt.grid(color='grey', which='major', linestyle='-',
Expand Down Expand Up @@ -262,7 +262,7 @@ def plot_st_psd(self, f_min=None, f_max=None, log=False, grid=True,
_viz.pacplot(psd, xvec, trials, **kw)
if log:
from matplotlib.ticker import ScalarFormatter
plt.xscale('log', basex=10)
plt.xscale('log', base=10)
plt.gca().xaxis.set_major_formatter(ScalarFormatter())
if grid:
plt.grid(color='grey', which='major', linestyle='-',
Expand Down