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authorAntony Lee <anntzer.lee@gmail.com>2020-12-29 18:53:53 +0100
committerAntony Lee <anntzer.lee@gmail.com>2020-12-29 21:18:08 +0100
commitf36e940a4726abb38c4929259e8eaf00d68c3d18 (patch)
tree3f36ded5bc3921b181e6bcdf7dc9b1c08ac2e50b
parent717df4e93234a1a290aa1b472b5c1c4e600009cd (diff)
downloadnumpy-f36e940a4726abb38c4929259e8eaf00d68c3d18.tar.gz
DOC: Avoid using "set of" when talking about an ordered list.
... or when the input isn't/cannot be a set. I left a few usages, e.g. in random sampling, where "set" is reasonable as informal description of an array as the order doesn't matter; however, for e.g. np.gradient the order of the returned list is clearly important, so "set" is wrong. Also some other minor doc edits noticed during the grepping: using `shape` instead of `form` in `cov` is consistent with most other places; the wording in `Polynomial.trim` now matches other methods on the same class.
-rw-r--r--benchmarks/benchmarks/bench_app.py4
-rw-r--r--benchmarks/benchmarks/common.py2
-rw-r--r--numpy/core/fromnumeric.py2
-rw-r--r--numpy/core/src/multiarray/methods.c2
-rw-r--r--numpy/lib/function_base.py2
-rw-r--r--numpy/lib/histograms.py2
-rw-r--r--numpy/ma/core.py4
-rw-r--r--numpy/ma/extras.py2
-rw-r--r--numpy/polynomial/_polybase.py2
-rw-r--r--numpy/testing/_private/parameterized.py2
-rw-r--r--tools/npy_tempita/__init__.py2
-rw-r--r--tools/refguide_check.py4
12 files changed, 15 insertions, 15 deletions
diff --git a/benchmarks/benchmarks/bench_app.py b/benchmarks/benchmarks/bench_app.py
index bee95c201..d22aa2e09 100644
--- a/benchmarks/benchmarks/bench_app.py
+++ b/benchmarks/benchmarks/bench_app.py
@@ -70,8 +70,8 @@ class MaxesOfDots(Benchmark):
Arrays must agree only on the first dimension.
- For numpy it a join benchmark of dot products and max()
- on a set of arrays.
+ Numpy uses this as a simultaneous benchmark of 1) dot products
+ and 2) max(<array>, axis=<int>).
"""
feature_scores = ([0] * len(arrays))
for (i, sd) in enumerate(arrays):
diff --git a/benchmarks/benchmarks/common.py b/benchmarks/benchmarks/common.py
index b65cc5fd2..b95d09192 100644
--- a/benchmarks/benchmarks/common.py
+++ b/benchmarks/benchmarks/common.py
@@ -14,7 +14,7 @@ nx, ny = 1000, 1000
# time-consuming functions (ufunc, linalg, etc)
nxs, nys = 100, 100
-# a set of interesting types to test
+# a list of interesting types to test
TYPES1 = [
'int16', 'float16',
'int32', 'float32',
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index efb052bc2..52df1aad9 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -308,7 +308,7 @@ def _choose_dispatcher(a, choices, out=None, mode=None):
@array_function_dispatch(_choose_dispatcher)
def choose(a, choices, out=None, mode='raise'):
"""
- Construct an array from an index array and a set of arrays to choose from.
+ Construct an array from an index array and a list of arrays to choose from.
First of all, if confused or uncertain, definitely look at the Examples -
in its full generality, this function is less simple than it might
diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c
index 9c8bb4135..8bcf591a2 100644
--- a/numpy/core/src/multiarray/methods.c
+++ b/numpy/core/src/multiarray/methods.c
@@ -1019,7 +1019,7 @@ array_getarray(PyArrayObject *self, PyObject *args)
}
/*
- * Check whether any of a set of input and output args have a non-default
+ * Check whether any of the input and output args have a non-default
* __array_ufunc__ method. Return 1 if so, 0 if not, and -1 on error.
*
* This function primarily exists to help ndarray.__array_ufunc__ determine
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 696fe617b..276ffa5d4 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -846,7 +846,7 @@ def gradient(f, *varargs, axis=None, edge_order=1):
Returns
-------
gradient : ndarray or list of ndarray
- A set of ndarrays (or a single ndarray if there is only one dimension)
+ A list of ndarrays (or a single ndarray if there is only one dimension)
corresponding to the derivatives of f with respect to each dimension.
Each derivative has the same shape as f.
diff --git a/numpy/lib/histograms.py b/numpy/lib/histograms.py
index 1a9b41ced..7af67a7ee 100644
--- a/numpy/lib/histograms.py
+++ b/numpy/lib/histograms.py
@@ -678,7 +678,7 @@ def _histogram_dispatcher(
def histogram(a, bins=10, range=None, normed=None, weights=None,
density=None):
r"""
- Compute the histogram of a set of data.
+ Compute the histogram of a dataset.
Parameters
----------
diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index d6af22337..54cb12f17 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -7339,9 +7339,9 @@ def where(condition, x=_NoValue, y=_NoValue):
def choose(indices, choices, out=None, mode='raise'):
"""
- Use an index array to construct a new array from a set of choices.
+ Use an index array to construct a new array from a list of choices.
- Given an array of integers and a set of n choice arrays, this method
+ Given an array of integers and a list of n choice arrays, this method
will create a new array that merges each of the choice arrays. Where a
value in `a` is i, the new array will have the value that choices[i]
contains in the same place.
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
index 1bf03e966..96e64914a 100644
--- a/numpy/ma/extras.py
+++ b/numpy/ma/extras.py
@@ -1322,7 +1322,7 @@ def cov(x, y=None, rowvar=True, bias=False, allow_masked=True, ddof=None):
observation of all those variables. Also see `rowvar` below.
y : array_like, optional
An additional set of variables and observations. `y` has the same
- form as `x`.
+ shape as `x`.
rowvar : bool, optional
If `rowvar` is True (default), then each row represents a
variable, with observations in the columns. Otherwise, the relationship
diff --git a/numpy/polynomial/_polybase.py b/numpy/polynomial/_polybase.py
index 4462f9d6b..ef3f9896d 100644
--- a/numpy/polynomial/_polybase.py
+++ b/numpy/polynomial/_polybase.py
@@ -694,7 +694,7 @@ class ABCPolyBase(abc.ABC):
Returns
-------
new_series : series
- Contains the new set of coefficients.
+ New instance of series with trimmed coefficients.
"""
coef = pu.trimcoef(self.coef, tol)
diff --git a/numpy/testing/_private/parameterized.py b/numpy/testing/_private/parameterized.py
index ac7db6c40..55a204e3f 100644
--- a/numpy/testing/_private/parameterized.py
+++ b/numpy/testing/_private/parameterized.py
@@ -339,7 +339,7 @@ class parameterized:
"'@parameterized.expand' instead.")
def _terrible_magic_get_defining_classes(self):
- """ Returns the set of parent classes of the class currently being defined.
+ """ Returns the list of parent classes of the class currently being defined.
Will likely only work if called from the ``parameterized`` decorator.
This function is entirely @brandon_rhodes's fault, as he suggested
the implementation: http://stackoverflow.com/a/8793684/71522
diff --git a/tools/npy_tempita/__init__.py b/tools/npy_tempita/__init__.py
index 50a995104..fedcd91f4 100644
--- a/tools/npy_tempita/__init__.py
+++ b/tools/npy_tempita/__init__.py
@@ -705,7 +705,7 @@ lead_whitespace_re = re.compile(r'^[\t ]*\n')
def trim_lex(tokens):
r"""
- Takes a lexed set of tokens, and removes whitespace when there is
+ Takes a lexed list of tokens, and removes whitespace when there is
a directive on a line by itself:
>>> tokens = lex('{{if x}}\nx\n{{endif}}\ny', trim_whitespace=False)
diff --git a/tools/refguide_check.py b/tools/refguide_check.py
index f0f6461b7..ddcc1028d 100644
--- a/tools/refguide_check.py
+++ b/tools/refguide_check.py
@@ -305,7 +305,7 @@ def compare(all_dict, others, names, module_name):
List of non deprecated sub modules for module_name
others : list
List of sub modules for module_name
- names : set
+ names : set
Set of function names or special directives present in
docstring of module_name
module_name : ModuleType
@@ -780,7 +780,7 @@ def _run_doctests(tests, full_name, verbose, doctest_warnings):
Parameters
----------
- tests: list
+ tests : list
full_name : str