From fc67796445cfa18cc636139627239b58d1585334 Mon Sep 17 00:00:00 2001
From: Bhuvan Bezawada <bhuvan_777@outlook.com>
Date: Wed, 27 Jun 2018 15:48:41 +0100
Subject: [PATCH] Altered return strings for compatibility with numpy
re #22553
Added extra tests to create numpy arrays from return values
---
.../Kernel/inc/MantidKernel/ContainerDtype.h | 16 +++---
.../python/mantid/kernel/ArrayPropertyTest.py | 52 +++++++++++++++++--
.../mantid/kernel/TimeSeriesPropertyTest.py | 6 +--
3 files changed, 58 insertions(+), 16 deletions(-)
diff --git a/Framework/Kernel/inc/MantidKernel/ContainerDtype.h b/Framework/Kernel/inc/MantidKernel/ContainerDtype.h
index 3ecdf326db3..aff76ce1835 100644
--- a/Framework/Kernel/inc/MantidKernel/ContainerDtype.h
+++ b/Framework/Kernel/inc/MantidKernel/ContainerDtype.h
@@ -49,9 +49,9 @@ namespace dtypeHelper {
template <template <class> class Container, typename HeldType>
std::string dtype(const Container<HeldType>) {
if (std::is_same<HeldType, bool>::value) {
- return "boolean";
+ return "bool_";
} else if (std::is_same<HeldType, short>::value) {
- return "short";
+ return "int16";
} else if (std::is_same<HeldType, std::int8_t>::value) {
return "int8";
} else if (std::is_same<HeldType, std::int16_t>::value) {
@@ -61,17 +61,17 @@ std::string dtype(const Container<HeldType>) {
} else if (std::is_same<HeldType, std::int64_t>::value) {
return "int64";
} else if (std::is_same<HeldType, long>::value) {
- return "long";
+ return "int_";
} else if (std::is_same<HeldType, long long>::value) {
- return "longlong";
+ return "int64";
} else if (std::is_same<HeldType, std::float_t>::value) {
- return "float";
+ return "float32";
} else if (std::is_same<HeldType, std::double_t>::value) {
- return "double";
+ return "float64";
} else if (std::is_same<HeldType, std::string>::value) {
- return "string";
+ return "string_";
} else {
- return "obj";
+ return "object_";
}
}
diff --git a/Framework/PythonInterface/test/python/mantid/kernel/ArrayPropertyTest.py b/Framework/PythonInterface/test/python/mantid/kernel/ArrayPropertyTest.py
index ba08b5b3e97..db5f08d0f27 100644
--- a/Framework/PythonInterface/test/python/mantid/kernel/ArrayPropertyTest.py
+++ b/Framework/PythonInterface/test/python/mantid/kernel/ArrayPropertyTest.py
@@ -150,22 +150,64 @@ class ArrayPropertyTest(unittest.TestCase):
int_arr = IntArrayProperty("integers", int_input_values, validator, direc)
# Create string array
- str_input_values =["a", "b", "c", "d", "e"]
+ str_input_values = ["a", "b", "c", "d", "e"]
str_arr = StringArrayProperty("letters", str_input_values, validator, direc)
# Test
- self.assertEquals(float_arr.dtype(), "double")
- self.assertEquals(str_arr.dtype(), "string")
+ self.assertEquals(float_arr.dtype(), "float64")
+ self.assertEquals(str_arr.dtype(), "string_")
# Implementation of IntArrayProperty is based on long
# (which is itself implementation defined, so a special case is needed here)
if sys.platform == 'win32' or sys.platform == 'darwin':
- # Windows and macOS should return "long"
- self.assertEquals(int_arr.dtype(), "long")
+ # Windows and macOS should return "int_"
+ self.assertEquals(int_arr.dtype(), "int_")
else:
# Linux based systems should return "int64"
self.assertEquals(int_arr.dtype(), "int64")
+ def test_construct_numpy_array_with_given_dtype_float(self):
+ # Set up
+ direc = Direction.Output
+ validator = NullValidator()
+
+ # Create float array
+ float_input_values = [1.1, 2.5, 5.6, 4.6, 9.0, 6.0]
+ float_arr = FloatArrayProperty("floats", float_input_values, validator, direc)
+
+ # Use the returned dtype() to check it works with numpy arrays
+ x = np.arange(1, 10, dtype=float_arr.dtype())
+ self.assertIsInstance(x, np.ndarray)
+ self.assertEquals(x.dtype, float_arr.dtype())
+
+ def test_construct_numpy_array_with_given_dtype_int(self):
+ # Set up
+ direc = Direction.Output
+ validator = NullValidator()
+
+ # Create int array
+ int_input_values = [1, 2, 5, 4, 9, 6]
+ int_arr = IntArrayProperty("integers", int_input_values, validator, direc)
+
+ # Use the returned dtype() to check it works with numpy arrays
+ x = np.arange(1, 10, dtype=int_arr.dtype())
+ self.assertIsInstance(x, np.ndarray)
+ self.assertEquals(x.dtype, int_arr.dtype())
+
+ def test_construct_numpy_array_with_given_dtype_string(self):
+ # Set up
+ direc = Direction.Output
+ validator = NullValidator()
+
+ # Create string array
+ str_input_values = ["hello", "testing", "word", "another word", "word"]
+ str_arr = StringArrayProperty("letters", str_input_values, validator, direc)
+
+ # Use the returned dtype() to check it works with numpy arrays
+ x = np.array(str_input_values, dtype=str_arr.dtype())
+ self.assertIsInstance(x, np.ndarray)
+ # Expect longest string to be returned
+ self.assertEquals(x.dtype, "S12")
def test_PythonAlgorithm_setProperty_With_Ranges_String(self):
"""
diff --git a/Framework/PythonInterface/test/python/mantid/kernel/TimeSeriesPropertyTest.py b/Framework/PythonInterface/test/python/mantid/kernel/TimeSeriesPropertyTest.py
index ca07e433b75..d162fc3f5b4 100644
--- a/Framework/PythonInterface/test/python/mantid/kernel/TimeSeriesPropertyTest.py
+++ b/Framework/PythonInterface/test/python/mantid/kernel/TimeSeriesPropertyTest.py
@@ -61,7 +61,7 @@ class TimeSeriesPropertyTest(unittest.TestCase):
self.assertEquals(log_series.size(), self._ntemp)
self.assertAlmostEqual(log_series.nthValue(0), -0.00161)
# Check the dtype return value
- self.assertEquals(log_series.dtype(), "double")
+ self.assertEquals(log_series.dtype(), "float64")
def test_time_series_int_can_be_extracted(self):
log_series = self._test_ws.getRun()["raw_frames"]
@@ -77,14 +77,14 @@ class TimeSeriesPropertyTest(unittest.TestCase):
self.assertEquals(log_series.size(), 4)
self.assertEquals(log_series.nthValue(0).strip(), 'CHANGE_PERIOD 1')
# Check the dtype return value
- self.assertEquals(log_series.dtype(), "string")
+ self.assertEquals(log_series.dtype(), "string_")
def test_time_series_bool_can_be_extracted(self):
log_series = self._test_ws.getRun()["period 1"]
self._check_has_time_series_attributes(log_series)
self.assertEquals(log_series.size(), 1)
# Check the dtype return value
- self.assertEquals(log_series.dtype(), "boolean")
+ self.assertEquals(log_series.dtype(), "bool_")
def _check_has_time_series_attributes(self, log, values_type=np.ndarray):
self.assertTrue(hasattr(log, "value"))
--
GitLab