8000 Merge pull request #21504 from Yulv-git/typos1 · rjeb/numpy@d4732a2 · GitHub
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Commit d4732a2

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rgommersrgommers
authored
Merge pull request numpy#21504 from Yulv-git/typos1
MAINT: Fix some typos.
2 parents d985fd4 + 7332a69 commit d4732a2

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9 files changed

+25
-25
lines changed

9 files changed

+25
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‎numpy/core/src/common/npy_cpu_features.h

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@@ -137,7 +137,7 @@ npy_cpu_features_dict(void);
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* that supported by the compiler and platform according to the specified
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* values to command argument '--cpu-baseline'.
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*
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* This function is mainly used to implement umath's attrbute '__cpu_baseline__',
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* This function is mainly used to implement umath's attribute '__cpu_baseline__',
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* and the items are sorted from the lowest to highest interest.
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*
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* For example, according to the default build configuration and by assuming the compiler
@@ -159,7 +159,7 @@ npy_cpu_baseline_list(void);
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* that supported by the compiler and platform according to the specified
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* values to command argument '--cpu-dispatch'.
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*
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* This function is mainly used to implement umath's attrbute '__cpu_dispatch__',
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* This function is mainly used to implement umath's attribute '__cpu_dispatch__',
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* and the items are sorted from the lowest to highest interest.
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*
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* For example, according to the default build configuration and by assuming the compiler

‎numpy/core/tests/test_array_coercion.py

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@@ -135,7 +135,7 @@ def scalar_instances(times=True, extended_precision=True, user_dtype=True):
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def is_parametric_dtype(dtype):
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"""Returns True if the the dtype is a parametric legacy dtype (itemsize
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"""Returns True if the dtype is a parametric legacy dtype (itemsize
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is 0, or a datetime without units)
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"""
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if dtype.itemsize == 0:

‎numpy/linalg/lapack_lite/f2c_c_lapack.c

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‎numpy/linalg/lapack_lite/f2c_d_lapack.c

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‎numpy/linalg/lapack_lite/f2c_s_lapack.c

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‎numpy/linalg/lapack_lite/f2c_z_lapack.c

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‎numpy/ma/extras.py

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@@ -1844,7 +1844,7 @@ def notmasked_contiguous(a, axis=None):
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a = asarray(a)
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nd = a.ndim
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if nd > 2:
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raise NotImplementedError("Currently limited to atmost 2D array.")
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raise NotImplementedError("Currently limited to at most 2D array.")
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if axis is None or nd == 1:
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return flatnotmasked_contiguous(a)
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#

‎numpy/random/_generator.pyx

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@@ -2990,7 +2990,7 @@ cdef class Generator:
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probability of success, :math:`N+n` is the number of trials, and
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:math:`\\Gamma` is the gamma function. When :math:`n` is an integer,
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:math:`\\frac{\\Gamma(N+n)}{N!\\Gamma(n)} = \\binom{N+n-1}{N}`, which is
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the more common form of this term in the the pmf. The negative
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the more common form of this term in the pmf. The negative
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binomial distribution gives the probability of N failures given n
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successes, with a success on the last trial.
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‎numpy/random/mtrand.pyx

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@@ -139,7 +139,7 @@ cdef class RandomState:
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'RandomState' methods using the same parameters will always produce the
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same results up to roundoff error except when the values were incorrect.
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`RandomState` is effectively frozen and will only receive updates that
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are required by changes in the the internals of Numpy. More substantial
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are required by changes in the internals of Numpy. More substantial
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changes, including algorithmic improvements, are reserved for
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`Generator`.
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@@ -3478,7 +3478,7 @@ cdef class RandomState:
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probability of success, :math:`N+n` is the number of trials, and
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:math:`\\Gamma` is the gamma function. When :math:`n` is an integer,
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:math:`\\frac{\\Gamma(N+n)}{N!\\Gamma(n)} = \\binom{N+n-1}{N}`, which is
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the more common form of this term in the the pmf. The negative
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the more common form of this term in the pmf. The negative
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binomial distribution gives the probability of N failures given n
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successes, with a success on the last trial.
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