bumpy min numpy version, redoing transscription velocity fixture 2

.github/environment-minimal.yml

@@ -4,7 +4,7 @@ channels:
   - defaults
 dependencies:
   - pip
-  - numpy ==1.7.0
+  - numpy ==1.14.0
   - scipy ==1.0.0
   - matplotlib==2.1.0
   - pytest

.github/environment.yml

@@ -4,7 +4,7 @@ channels:
   - defaults
 dependencies:
   - pip
-  - numpy >=1.7.0
+  - numpy >=1.14.0
   - scipy >=1.0.0
   - matplotlib>=2.1.0
   - pytest

mir_eval/transcription_velocity.py

@@ -210,6 +210,7 @@ def match_notes(
     slope, intercept = np.linalg.lstsq(
         np.vstack([est_matched_velocities, np.ones(len(est_matched_velocities))]).T,
         ref_matched_velocities,
+        rcond=None
     )[0]
     # Re-scale est velocities to match ref
     est_matched_velocities = slope * est_matched_velocities + intercept

setup.cfg

@@ -46,7 +46,7 @@ classifiers =
 packages = find:
 keywords = audio music mir dsp
 install_requires =
-    numpy >= 1.7.0
+    numpy >= 1.14.0
     scipy >= 1.0.0
 
 [options.extras_require]

tests/data/transcription_velocity/output2.json

@@ -1 +1 @@
-{"Precision": 0.1761055081458495, "Recall": 0.15655172413793103, "F-measure": 0.16575392479006937, "Average_Overlap_Ratio": 0.6339212298653343, "Precision_no_offset": 0.5865011636927852, "Recall_no_offset": 0.5213793103448275, "F-measure_no_offset": 0.552026286966046, "Average_Overlap_Ratio_no_offset": 0.4720752936805029}
+{"Precision": 0.17532971295577968, "Recall": 0.15586206896551724, "F-measure": 0.16502373128879153, "Average_Overlap_Ratio": 0.6346439422322657, "Precision_no_offset": 0.5865011636927852, "Recall_no_offset": 0.5213793103448275, "F-measure_no_offset": 0.552026286966046, "Average_Overlap_Ratio_no_offset": 0.4720752936805029}

tests/test_transcription_velocity.py

@@ -91,6 +91,8 @@ def test_precision_recall_f1_overlap():
     assert np.allclose((p, r, f, o), (1.0, 1.0, 1.0, 1.0))
 
 
+# Suppressing this warning. We know the notes are empty, that's not the point.
+@pytest.mark.filterwarnings("ignore:.*notes are empty")
 def test_precision_recall_f1_overlap_empty():
     good_i, good_p, good_v = np.array([[0, 1]]), np.array([100]), np.array([1])
     bad_i, bad_p, bad_v = np.empty((0, 2)), np.array([]), np.array([])