MAINT: Add ".csv" to some data file names.

It is useful to encode the data file type in the name.

6 files changed, 8 insertions, 7 deletions

diff --git a/numpy/core/tests/data/umath-validation-set-README b/numpy/core/tests/data/umath-validation-set-README.txt
index 6561ca3b5..cfc9e4145 100644
--- a/numpy/core/tests/data/umath-validation-set-README
+++ b/numpy/core/tests/data/umath-validation-set-README.txt
@@ -1,5 +1,5 @@
 Steps to validate transcendental functions:
-1) Add a file 'umath-validation-set-<ufuncname>', where ufuncname is name of
+1) Add a file 'umath-validation-set-<ufuncname>.txt', where ufuncname is name of
    the function in NumPy you want to validate
 2) The file should contain 4 columns: dtype,input,expected output,ulperror
     a. dtype: one of np.float16, np.float32, np.float64
@@ -11,5 +11,5 @@ Steps to validate transcendental functions:
     d. ulperror: expected maximum ulp error of the function. This
        should be same across all rows of the same dtype. Otherwise, the function is
        tested for the maximum ulp error among all entries of that dtype.
-3) Add file umath-validation-set-<ufuncname> to the test file test_umath_accuracy.py
+3) Add file umath-validation-set-<ufuncname>.txt to the test file test_umath_accuracy.py
    which will then validate your ufunc.
diff --git a/numpy/core/tests/data/umath-validation-set-cos b/numpy/core/tests/data/umath-validation-set-cos.csv
index 2e75f044c..2e75f044c 100644
--- a/numpy/core/tests/data/umath-validation-set-cos
+++ b/numpy/core/tests/data/umath-validation-set-cos.csv
diff --git a/numpy/core/tests/data/umath-validation-set-exp b/numpy/core/tests/data/umath-validation-set-exp.csv
index 7c5ef3b33..7c5ef3b33 100644
--- a/numpy/core/tests/data/umath-validation-set-exp
+++ b/numpy/core/tests/data/umath-validation-set-exp.csv
diff --git a/numpy/core/tests/data/umath-validation-set-log b/numpy/core/tests/data/umath-validation-set-log.csv
index b8f6b0875..b8f6b0875 100644
--- a/numpy/core/tests/data/umath-validation-set-log
+++ b/numpy/core/tests/data/umath-validation-set-log.csv
diff --git a/numpy/core/tests/data/umath-validation-set-sin b/numpy/core/tests/data/umath-validation-set-sin.csv
index 64e78ae15..64e78ae15 100644
--- a/numpy/core/tests/data/umath-validation-set-sin
+++ b/numpy/core/tests/data/umath-validation-set-sin.csv
diff --git a/numpy/core/tests/test_umath_accuracy.py b/numpy/core/tests/test_umath_accuracy.py
index 33080edbb..8e04d2875 100644
--- a/numpy/core/tests/test_umath_accuracy.py
+++ b/numpy/core/tests/test_umath_accuracy.py
@@ -28,10 +28,10 @@ def convert(s, datatype="np.float32"):
     return fp.contents.value         # dereference the pointer, get the float
 
 str_to_float = np.vectorize(convert)
-files = ['umath-validation-set-exp',
-         'umath-validation-set-log',
-         'umath-validation-set-sin',
-         'umath-validation-set-cos']
+files = ['umath-validation-set-exp.csv',
+         'umath-validation-set-log.csv',
+         'umath-validation-set-sin.csv',
+         'umath-validation-set-cos.csv']
 
 class TestAccuracy:
     @platform_skip
@@ -47,7 +47,8 @@ class TestAccuracy:
                                          names=('type','input','output','ulperr'),
                                          delimiter=',',
                                          skip_header=1)
-                    npfunc = getattr(np, filename.split('-')[3])
+                    npname = path.splitext(filename)[0].split('-')[3]
+                    npfunc = getattr(np, npname)
                     for datatype in np.unique(data['type']):
                         data_subset = data[data['type'] == datatype]
                         inval  = np.array(str_to_float(data_subset['input'].astype(str), data_subset['type'].astype(str)), dtype=eval(datatype))