From ad1dd9066f04f0dda10a1c991480ba506d53676a Mon Sep 17 00:00:00 2001
From: Sebastian Berg <sebastian@sipsolutions.net>
Date: Mon, 6 Jan 2020 15:50:54 -0600
Subject: BENCH: Add benchmark for small array coercions

Note that since the benchmarks are so fast, the actual results
are diluted behind one more python function call.
---
 benchmarks/benchmarks/bench_array_coercion.py | 57 +++++++++++++++++++++++++++
 1 file changed, 57 insertions(+)
 create mode 100644 benchmarks/benchmarks/bench_array_coercion.py

(limited to 'benchmarks')

diff --git a/benchmarks/benchmarks/bench_array_coercion.py b/benchmarks/benchmarks/bench_array_coercion.py
new file mode 100644
index 000000000..2bae4c002
--- /dev/null
+++ b/benchmarks/benchmarks/bench_array_coercion.py
@@ -0,0 +1,57 @@
+from __future__ import absolute_import, division, print_function
+
+from .common import Benchmark
+
+import numpy as np
+
+
+class ArrayCoercionSmall(Benchmark):
+    # More detailed benchmarks for array coercion,
+    # some basic benchmarks are in `bench_core.py`.
+    params = [[range(3), [1], 1, np.array([5], dtype=np.int64), np.int64(5)]]
+    param_names = ['array_like']
+    int64 = np.dtype(np.int64)
+
+    def time_array_invalid_kwarg(self, array_like):
+        try:
+            np.array(array_like, ndmin="not-integer")
+        except TypeError:
+            pass
+
+    def time_array(self, array_like):
+        np.array(array_like)
+
+    def time_array_dtype_not_kwargs(self, array_like):
+        np.array(array_like, self.int64)
+
+    def time_array_no_copy(self, array_like):
+        np.array(array_like, copy=False)
+
+    def time_array_subok(self, array_like):
+        np.array(array_like, subok=True)
+
+    def time_array_all_kwargs(self, array_like):
+        np.array(array_like, dtype=self.int64, copy=False, order="F",
+                 subok=False, ndmin=2)
+
+    def time_asarray(self, array_like):
+        np.asarray(array_like)
+
+    def time_asarray_dtype(self, array_like):
+        np.array(array_like, dtype=self.int64)
+
+    def time_asarray_dtype(self, array_like):
+        np.array(array_like, dtype=self.int64, order="F")
+
+    def time_asanyarray(self, array_like):
+        np.asarray(array_like)
+
+    def time_asanyarray_dtype(self, array_like):
+        np.array(array_like, dtype=self.int64)
+
+    def time_asanyarray_dtype(self, array_like):
+        np.array(array_like, dtype=self.int64, order="F")
+
+    def time_ascontiguousarray(self, array_like):
+        np.ascontiguousarray(array_like)
+
-- 
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