diff options
| -rw-r--r-- | numpy/core/arrayprint.py | 2 | ||||
| -rw-r--r-- | numpy/core/fromnumeric.py | 2 | ||||
| -rw-r--r-- | numpy/lib/function_base.py | 8 | ||||
| -rw-r--r-- | numpy/lib/nanfunctions.py | 16 | ||||
| -rw-r--r-- | numpy/lib/polynomial.py | 2 | ||||
| -rw-r--r-- | numpy/linalg/linalg.py | 6 |
6 files changed, 18 insertions, 18 deletions
diff --git a/numpy/core/arrayprint.py b/numpy/core/arrayprint.py index 957cecf1c..e0d8ab5c7 100644 --- a/numpy/core/arrayprint.py +++ b/numpy/core/arrayprint.py @@ -724,7 +724,7 @@ def array2string(a, max_line_width=None, precision=None, # Deprecation 11-9-2017 v1.14 warnings.warn("'style' argument is deprecated and no longer functional" " except in 1.13 'legacy' mode", - DeprecationWarning, stacklevel=3) + DeprecationWarning, stacklevel=2) if options['legacy'] > 113: options['linewidth'] -= len(suffix) diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index ca9d55cb7..e7366898e 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -2313,7 +2313,7 @@ def sum(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, warnings.warn( "Calling np.sum(generator) is deprecated, and in the future will give a different result. " "Use np.sum(np.fromiter(generator)) or the python sum builtin instead.", - DeprecationWarning, stacklevel=3) + DeprecationWarning, stacklevel=2) res = _sum_(a) if out is not None: diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 7a69c3c81..11a5a3ad0 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -2695,7 +2695,7 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, if fact <= 0: warnings.warn("Degrees of freedom <= 0 for slice", - RuntimeWarning, stacklevel=3) + RuntimeWarning, stacklevel=2) fact = 0.0 X -= avg[:, None] @@ -2844,7 +2844,7 @@ def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, ddof=np._NoValue, *, if bias is not np._NoValue or ddof is not np._NoValue: # 2015-03-15, 1.10 warnings.warn('bias and ddof have no effect and are deprecated', - DeprecationWarning, stacklevel=3) + DeprecationWarning, stacklevel=2) c = cov(x, y, rowvar, dtype=dtype) try: d = diag(c) @@ -3684,7 +3684,7 @@ def msort(a): warnings.warn( "msort is deprecated, use np.sort(a, axis=0) instead", DeprecationWarning, - stacklevel=3, + stacklevel=2, ) b = array(a, subok=True, copy=True) b.sort(0) @@ -5398,7 +5398,7 @@ def insert(arr, obj, values, axis=None): warnings.warn( "in the future insert will treat boolean arrays and " "array-likes as a boolean index instead of casting it to " - "integer", FutureWarning, stacklevel=3) + "integer", FutureWarning, stacklevel=2) indices = indices.astype(intp) # Code after warning period: #if obj.ndim != 1: diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py index 786d2021e..7e5528646 100644 --- a/numpy/lib/nanfunctions.py +++ b/numpy/lib/nanfunctions.py @@ -169,7 +169,7 @@ def _remove_nan_1d(arr1d, overwrite_input=False): s = np.nonzero(c)[0] if s.size == arr1d.size: warnings.warn("All-NaN slice encountered", RuntimeWarning, - stacklevel=5) + stacklevel=6) return arr1d[:0], True elif s.size == 0: return arr1d, overwrite_input @@ -343,7 +343,7 @@ def nanmin(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue, res = np.fmin.reduce(a, axis=axis, out=out, **kwargs) if np.isnan(res).any(): warnings.warn("All-NaN slice encountered", RuntimeWarning, - stacklevel=3) + stacklevel=2) else: # Slow, but safe for subclasses of ndarray a, mask = _replace_nan(a, +np.inf) @@ -357,7 +357,7 @@ def nanmin(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue, if np.any(mask): res = _copyto(res, np.nan, mask) warnings.warn("All-NaN axis encountered", RuntimeWarning, - stacklevel=3) + stacklevel=2) return res @@ -476,7 +476,7 @@ def nanmax(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue, res = np.fmax.reduce(a, axis=axis, out=out, **kwargs) if np.isnan(res).any(): warnings.warn("All-NaN slice encountered", RuntimeWarning, - stacklevel=3) + stacklevel=2) else: # Slow, but safe for subclasses of ndarray a, mask = _replace_nan(a, -np.inf) @@ -490,7 +490,7 @@ def nanmax(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue, if np.any(mask): res = _copyto(res, np.nan, mask) warnings.warn("All-NaN axis encountered", RuntimeWarning, - stacklevel=3) + stacklevel=2) return res @@ -1049,7 +1049,7 @@ def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, isbad = (cnt == 0) if isbad.any(): - warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) + warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=2) # NaN is the only possible bad value, so no further # action is needed to handle bad results. return avg @@ -1109,7 +1109,7 @@ def _nanmedian_small(a, axis=None, out=None, overwrite_input=False): m = np.ma.median(a, axis=axis, overwrite_input=overwrite_input) for i in range(np.count_nonzero(m.mask.ravel())): warnings.warn("All-NaN slice encountered", RuntimeWarning, - stacklevel=4) + stacklevel=5) fill_value = np.timedelta64("NaT") if m.dtype.kind == "m" else np.nan if out is not None: @@ -1763,7 +1763,7 @@ def nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue, isbad = (dof <= 0) if np.any(isbad): warnings.warn("Degrees of freedom <= 0 for slice.", RuntimeWarning, - stacklevel=3) + stacklevel=2) # NaN, inf, or negative numbers are all possible bad # values, so explicitly replace them with NaN. var = _copyto(var, np.nan, isbad) diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 0f7ab0334..fb036108a 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -672,7 +672,7 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): # warn on rank reduction, which indicates an ill conditioned matrix if rank != order and not full: msg = "Polyfit may be poorly conditioned" - warnings.warn(msg, RankWarning, stacklevel=4) + warnings.warn(msg, RankWarning, stacklevel=2) if full: return c, resids, rank, s, rcond diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index ee0fe6166..1b3f6e86a 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -899,12 +899,12 @@ def qr(a, mode='reduced'): msg = "".join(( "The 'full' option is deprecated in favor of 'reduced'.\n", "For backward compatibility let mode default.")) - warnings.warn(msg, DeprecationWarning, stacklevel=3) + warnings.warn(msg, DeprecationWarning, stacklevel=2) mode = 'reduced' elif mode in ('e', 'economic'): # 2013-04-01, 1.8 msg = "The 'economic' option is deprecated." - warnings.warn(msg, DeprecationWarning, stacklevel=3) + warnings.warn(msg, DeprecationWarning, stacklevel=2) mode = 'economic' else: raise ValueError(f"Unrecognized mode '{mode}'") @@ -2267,7 +2267,7 @@ def lstsq(a, b, rcond="warn"): "To use the future default and silence this warning " "we advise to pass `rcond=None`, to keep using the old, " "explicitly pass `rcond=-1`.", - FutureWarning, stacklevel=3) + FutureWarning, stacklevel=2) rcond = -1 if rcond is None: rcond = finfo(t).eps * max(n, m) |