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david-cattermoledavid-cattermole
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mmAnimCurveDiffStatistics - Rename internal variables.
1 parent 99d7fe4 commit f15c231

2 files changed

Lines changed: 68 additions & 62 deletions

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‎src/mmSolver/cmd/MMAnimCurveDiffStatisticsCmd.cpp‎

Lines changed: 20 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -64,8 +64,8 @@
6464
#define MEAN_ABSOLUTE_DIFF_FLAG_SHORT "-mad"
6565
#define MEAN_ABSOLUTE_DIFF_FLAG_LONG "-meanAbsoluteDifference"
6666

67-
#define RMS_DIFF_FLAG_SHORT "-rsd"
68-
#define RMS_DIFF_FLAG_LONG "-rootMeanSquareDifference"
67+
#define ROOT_MEAN_SQUARE_DIFF_FLAG_SHORT "-rsd"
68+
#define ROOT_MEAN_SQUARE_DIFF_FLAG_LONG "-rootMeanSquareDifference"
6969

7070
#define MEAN_DIFF_FLAG_SHORT "-mnf"
7171
#define MEAN_DIFF_FLAG_LONG "-meanDifference"
@@ -91,8 +91,9 @@
9191
#define ROOT_MEAN_SQUARE_ERROR_FLAG_SHORT "-rme"
9292
#define ROOT_MEAN_SQUARE_ERROR_FLAG_LONG "-rootMeanSquareError"
9393

94-
#define NORMALIZED_RMSE_FLAG_SHORT "-nse"
95-
#define NORMALIZED_RMSE_FLAG_LONG "-normalizedRootMeanSquareError"
94+
#define NORMALIZED_ROOT_MEAN_SQUARE_ERROR_FLAG_SHORT "-nse"
95+
#define NORMALIZED_ROOT_MEAN_SQUARE_ERROR_FLAG_LONG \
96+
"-normalizedRootMeanSquareError"
9697

9798
#define R_SQUARED_FLAG_SHORT "-r2"
9899
#define R_SQUARED_FLAG_LONG "-rSquared"
@@ -110,7 +111,7 @@
110111

111112
// Statistic type identifiers for output
112113
#define STAT_TYPE_MEAN_ABSOLUTE_DIFF 0.0
113-
#define STAT_TYPE_RMS_DIFF 1.0
114+
#define STAT_TYPE_ROOT_MEAN_SQUARE_DIFF 1.0
114115
#define STAT_TYPE_POPULATION_STD_DEV 2.0
115116
#define STAT_TYPE_PEAK_TO_PEAK_DIFF 3.0
116117
#define STAT_TYPE_SIGNAL_TO_NOISE_RATIO 4.0
@@ -119,7 +120,7 @@
119120
#define STAT_TYPE_MEDIAN_DIFF 7.0
120121
#define STAT_TYPE_MEAN_ABSOLUTE_ERROR 8.0
121122
#define STAT_TYPE_ROOT_MEAN_SQUARE_ERROR 9.0
122-
#define STAT_TYPE_NORMALIZED_RMSE 10.0
123+
#define STAT_TYPE_NORMALIZED_ROOT_MEAN_SQUARE_ERROR 10.0
123124
#define STAT_TYPE_R_SQUARED 11.0
124125

125126
namespace mmsg = mmscenegraph;
@@ -154,7 +155,8 @@ MSyntax MMAnimCurveDiffStatisticsCmd::newSyntax() {
154155
// Statistics flags
155156
syntax.addFlag(MEAN_ABSOLUTE_DIFF_FLAG_SHORT, MEAN_ABSOLUTE_DIFF_FLAG_LONG,
156157
MSyntax::kBoolean);
157-
syntax.addFlag(RMS_DIFF_FLAG_SHORT, RMS_DIFF_FLAG_LONG, MSyntax::kBoolean);
158+
syntax.addFlag(ROOT_MEAN_SQUARE_DIFF_FLAG_SHORT,
159+
ROOT_MEAN_SQUARE_DIFF_FLAG_LONG, MSyntax::kBoolean);
158160
syntax.addFlag(MEAN_DIFF_FLAG_SHORT, MEAN_DIFF_FLAG_LONG,
159161
MSyntax::kBoolean);
160162
syntax.addFlag(MEDIAN_DIFF_FLAG_SHORT, MEDIAN_DIFF_FLAG_LONG,
@@ -171,7 +173,8 @@ MSyntax MMAnimCurveDiffStatisticsCmd::newSyntax() {
171173
MEAN_ABSOLUTE_ERROR_FLAG_LONG, MSyntax::kBoolean);
172174
syntax.addFlag(ROOT_MEAN_SQUARE_ERROR_FLAG_SHORT,
173175
ROOT_MEAN_SQUARE_ERROR_FLAG_LONG, MSyntax::kBoolean);
174-
syntax.addFlag(NORMALIZED_RMSE_FLAG_SHORT, NORMALIZED_RMSE_FLAG_LONG,
176+
syntax.addFlag(NORMALIZED_ROOT_MEAN_SQUARE_ERROR_FLAG_SHORT,
177+
NORMALIZED_ROOT_MEAN_SQUARE_ERROR_FLAG_LONG,
175178
MSyntax::kBoolean);
176179
syntax.addFlag(R_SQUARED_FLAG_SHORT, R_SQUARED_FLAG_LONG,
177180
MSyntax::kBoolean);
@@ -334,9 +337,9 @@ MStatus MMAnimCurveDiffStatisticsCmd::parseArgs(const MArgList &args) {
334337
m_calculateMeanAbsDiff);
335338
MMSOLVER_CHECK_MSTATUS_AND_RETURN_IT(status);
336339
}
337-
if (argData.isFlagSet(RMS_DIFF_FLAG_SHORT)) {
338-
status =
339-
argData.getFlagArgument(RMS_DIFF_FLAG_SHORT, 0, m_calculateRmsDiff);
340+
if (argData.isFlagSet(ROOT_MEAN_SQUARE_DIFF_FLAG_SHORT)) {
341+
status = argData.getFlagArgument(ROOT_MEAN_SQUARE_DIFF_FLAG_SHORT, 0,
342+
m_calculateRmsDiff);
340343
MMSOLVER_CHECK_MSTATUS_AND_RETURN_IT(status);
341344
}
342345
if (argData.isFlagSet(MEAN_DIFF_FLAG_SHORT)) {
@@ -379,9 +382,9 @@ MStatus MMAnimCurveDiffStatisticsCmd::parseArgs(const MArgList &args) {
379382
m_calculateRMSE);
380383
MMSOLVER_CHECK_MSTATUS_AND_RETURN_IT(status);
381384
}
382-
if (argData.isFlagSet(NORMALIZED_RMSE_FLAG_SHORT)) {
383-
status = argData.getFlagArgument(NORMALIZED_RMSE_FLAG_SHORT, 0,
384-
m_calculateNRMSE);
385+
if (argData.isFlagSet(NORMALIZED_ROOT_MEAN_SQUARE_ERROR_FLAG_SHORT)) {
386+
status = argData.getFlagArgument(
387+
NORMALIZED_ROOT_MEAN_SQUARE_ERROR_FLAG_SHORT, 0, m_calculateNRMSE);
385388
MMSOLVER_CHECK_MSTATUS_AND_RETURN_IT(status);
386389
}
387390
if (argData.isFlagSet(R_SQUARED_FLAG_SHORT)) {
@@ -674,7 +677,7 @@ MStatus MMAnimCurveDiffStatisticsCmd::doIt(const MArgList &args) {
674677
if (mmsg::calc_population_variance(squared_diff_slice, mean_squared,
675678
variance_squared)) {
676679
rms_diff = std::sqrt(mean_squared);
677-
statsResults.push_back({STAT_TYPE_RMS_DIFF, rms_diff});
680+
statsResults.push_back({STAT_TYPE_ROOT_MEAN_SQUARE_DIFF, rms_diff});
678681
MMSOLVER_MAYA_VRB(CMD_NAME << ": rms_diff=" << rms_diff);
679682
} else {
680683
MGlobal::displayWarning(CMD_NAME
@@ -756,7 +759,8 @@ MStatus MMAnimCurveDiffStatisticsCmd::doIt(const MArgList &args) {
756759
mmsg::Real nrmse = 0.0;
757760
if (mmsg::calc_normalized_root_mean_square_error(
758761
values_y2_slice, values_y1_slice, nrmse)) {
759-
statsResults.push_back({STAT_TYPE_NORMALIZED_RMSE, nrmse});
762+
statsResults.push_back(
763+
{STAT_TYPE_NORMALIZED_ROOT_MEAN_SQUARE_ERROR, nrmse});
760764
MMSOLVER_MAYA_VRB(CMD_NAME << ": normalized_root_mean_square_error="
761765
<< nrmse);
762766
} else {

‎tests/test/test_tools/test_animcurve_diff_statistics.py‎

Lines changed: 48 additions & 46 deletions
Original file line numberDiff line numberDiff line change
@@ -34,7 +34,7 @@
3434

3535
# Statistic type identifiers from the C++ code.
3636
STAT_TYPE_MEAN_ABSOLUTE_DIFF = 0
37-
STAT_TYPE_RMS_DIFF = 1
37+
STAT_TYPE_ROOT_MEAN_SQUARE_DIFF = 1
3838
STAT_TYPE_POPULATION_STD_DEV = 2
3939
STAT_TYPE_PEAK_TO_PEAK_DIFF = 3
4040
STAT_TYPE_SIGNAL_TO_NOISE_RATIO = 4
@@ -43,37 +43,37 @@
4343
STAT_TYPE_MEDIAN_DIFF = 7
4444
STAT_TYPE_MEAN_ABSOLUTE_ERROR = 8
4545
STAT_TYPE_ROOT_MEAN_SQUARE_ERROR = 9
46-
STAT_TYPE_NORMALIZED_RMSE = 10
46+
STAT_TYPE_NORMALIZED_ROOT_MEAN_SQUARE_ERROR = 10
4747
STAT_TYPE_R_SQUARED = 11
4848

4949

5050
# Names for each statistic identifier defined in this module.
51-
STAT_NAME_MEAN_ABS_DIFF = "mean_absolute_diff"
52-
STAT_NAME_RMS_DIFF = "root_mean_square_diff"
53-
STAT_NAME_STD_POPULATION_DEV = "population_std_dev"
54-
STAT_NAME_POPULATION_VARIANCE = "population_variance"
55-
STAT_NAME_PEAK_TO_PEAK_DIFF = "peak_to_peak_diff"
56-
STAT_NAME_SIGNAL_TO_NOISE_RATIO = "signal_to_noise_ratio"
51+
STAT_NAME_MEAN_ABSOLUTE_DIFF = "mean_absolute_diff"
52+
STAT_NAME_MEAN_ABSOLUTE_ERROR = "mean_absolute_error"
5753
STAT_NAME_MEAN_DIFF = "mean_diff"
5854
STAT_NAME_MEDIAN_DIFF = "median_diff"
59-
STAT_NAME_MEAN_ABSOLUTE_ERROR = "mean_absolute_error"
55+
STAT_NAME_NORMALIZED_ROOT_MEAN_SQUARE_ERROR = "normalized_root_mean_square_error"
56+
STAT_NAME_PEAK_TO_PEAK_DIFF = "peak_to_peak_diff"
57+
STAT_NAME_POPULATION_STD_DEV = "population_std_dev"
58+
STAT_NAME_POPULATION_VARIANCE = "population_variance"
59+
STAT_NAME_ROOT_MEAN_SQUARE_DIFF = "root_mean_square_diff"
6060
STAT_NAME_ROOT_MEAN_SQUARE_ERROR = "root_mean_square_error"
61-
STAT_NAME_NORMALIZED_RMSE = "normalized_rmse"
6261
STAT_NAME_R_SQUARED = "r_squared"
62+
STAT_NAME_SIGNAL_TO_NOISE_RATIO = "signal_to_noise_ratio"
6363

6464
STAT_NAME_LIST = [
65-
STAT_NAME_MEAN_ABS_DIFF,
66-
STAT_NAME_RMS_DIFF,
67-
STAT_NAME_STD_POPULATION_DEV,
68-
STAT_NAME_POPULATION_VARIANCE,
69-
STAT_NAME_PEAK_TO_PEAK_DIFF,
70-
STAT_NAME_SIGNAL_TO_NOISE_RATIO,
65+
STAT_NAME_MEAN_ABSOLUTE_DIFF,
66+
STAT_NAME_MEAN_ABSOLUTE_ERROR,
7167
STAT_NAME_MEAN_DIFF,
7268
STAT_NAME_MEDIAN_DIFF,
73-
STAT_NAME_MEAN_ABSOLUTE_ERROR,
69+
STAT_NAME_NORMALIZED_ROOT_MEAN_SQUARE_ERROR,
70+
STAT_NAME_PEAK_TO_PEAK_DIFF,
71+
STAT_NAME_POPULATION_STD_DEV,
72+
STAT_NAME_POPULATION_VARIANCE,
73+
STAT_NAME_ROOT_MEAN_SQUARE_DIFF,
7474
STAT_NAME_ROOT_MEAN_SQUARE_ERROR,
75-
STAT_NAME_NORMALIZED_RMSE,
7675
STAT_NAME_R_SQUARED,
76+
STAT_NAME_SIGNAL_TO_NOISE_RATIO,
7777
]
7878

7979

@@ -90,11 +90,11 @@ def _parse_diff_statistics_result(self, result):
9090
stat_value = result[i + 1]
9191

9292
if stat_type == STAT_TYPE_MEAN_ABSOLUTE_DIFF:
93-
stats[STAT_NAME_MEAN_ABS_DIFF] = stat_value
94-
elif stat_type == STAT_TYPE_RMS_DIFF:
95-
stats[STAT_NAME_RMS_DIFF] = stat_value
93+
stats[STAT_NAME_MEAN_ABSOLUTE_DIFF] = stat_value
94+
elif stat_type == STAT_TYPE_ROOT_MEAN_SQUARE_DIFF:
95+
stats[STAT_NAME_ROOT_MEAN_SQUARE_DIFF] = stat_value
9696
elif stat_type == STAT_TYPE_POPULATION_STD_DEV:
97-
stats[STAT_NAME_STD_POPULATION_DEV] = stat_value
97+
stats[STAT_NAME_POPULATION_STD_DEV] = stat_value
9898
elif stat_type == STAT_TYPE_PEAK_TO_PEAK_DIFF:
9999
stats[STAT_NAME_PEAK_TO_PEAK_DIFF] = stat_value
100100
elif stat_type == STAT_TYPE_SIGNAL_TO_NOISE_RATIO:
@@ -109,8 +109,8 @@ def _parse_diff_statistics_result(self, result):
109109
stats[STAT_NAME_MEAN_ABSOLUTE_ERROR] = stat_value
110110
elif stat_type == STAT_TYPE_ROOT_MEAN_SQUARE_ERROR:
111111
stats[STAT_NAME_ROOT_MEAN_SQUARE_ERROR] = stat_value
112-
elif stat_type == STAT_TYPE_NORMALIZED_RMSE:
113-
stats[STAT_NAME_NORMALIZED_RMSE] = stat_value
112+
elif stat_type == STAT_TYPE_NORMALIZED_ROOT_MEAN_SQUARE_ERROR:
113+
stats[STAT_NAME_NORMALIZED_ROOT_MEAN_SQUARE_ERROR] = stat_value
114114
elif stat_type == STAT_TYPE_R_SQUARED:
115115
stats[STAT_NAME_R_SQUARED] = stat_value
116116

@@ -166,14 +166,14 @@ def test_diff_statistics_basic(self):
166166
# Standard deviation should be sqrt(variance).
167167
expected_std = math.sqrt(stats[STAT_NAME_POPULATION_VARIANCE])
168168
self.assertAlmostEqual(
169-
stats[STAT_NAME_STD_POPULATION_DEV], expected_std, places=5
169+
stats[STAT_NAME_POPULATION_STD_DEV], expected_std, places=5
170170
)
171171

172172
# Mean absolute diff should be >= 0.
173-
self.assertGreaterEqual(stats[STAT_NAME_MEAN_ABS_DIFF], 0.0)
173+
self.assertGreaterEqual(stats[STAT_NAME_MEAN_ABSOLUTE_DIFF], 0.0)
174174

175175
# RMS should be >= 0.
176-
self.assertGreaterEqual(stats[STAT_NAME_RMS_DIFF], 0.0)
176+
self.assertGreaterEqual(stats[STAT_NAME_ROOT_MEAN_SQUARE_DIFF], 0.0)
177177

178178
# Peak-to-peak should be >= 0.
179179
self.assertGreaterEqual(stats[STAT_NAME_PEAK_TO_PEAK_DIFF], 0.0)
@@ -185,7 +185,7 @@ def test_diff_statistics_basic(self):
185185
self.assertGreaterEqual(stats[STAT_NAME_ROOT_MEAN_SQUARE_ERROR], 0.0)
186186

187187
# NRMSE should be >= 0.
188-
self.assertGreaterEqual(stats[STAT_NAME_NORMALIZED_RMSE], 0.0)
188+
self.assertGreaterEqual(stats[STAT_NAME_NORMALIZED_ROOT_MEAN_SQUARE_ERROR], 0.0)
189189

190190
# R-squared should be between -infinity and 1.
191191
self.assertLessEqual(stats[STAT_NAME_R_SQUARED], 1.0)
@@ -230,16 +230,16 @@ def test_diff_statistics_identical_curves(self):
230230

231231
# For identical curves, all differences should be zero.
232232
for stat_name in [
233-
STAT_NAME_MEAN_ABS_DIFF,
234-
STAT_NAME_RMS_DIFF,
235-
STAT_NAME_STD_POPULATION_DEV,
233+
STAT_NAME_MEAN_ABSOLUTE_DIFF,
234+
STAT_NAME_ROOT_MEAN_SQUARE_DIFF,
235+
STAT_NAME_POPULATION_STD_DEV,
236236
STAT_NAME_POPULATION_VARIANCE,
237237
STAT_NAME_PEAK_TO_PEAK_DIFF,
238238
STAT_NAME_MEAN_DIFF,
239239
STAT_NAME_MEDIAN_DIFF,
240240
STAT_NAME_MEAN_ABSOLUTE_ERROR,
241241
STAT_NAME_ROOT_MEAN_SQUARE_ERROR,
242-
STAT_NAME_NORMALIZED_RMSE,
242+
STAT_NAME_NORMALIZED_ROOT_MEAN_SQUARE_ERROR,
243243
]:
244244
self.assertAlmostEqual(stats[stat_name], 0.0, places=5)
245245

@@ -286,7 +286,9 @@ def test_diff_statistics_constant_offset(self):
286286
# - Mean diff should equal the offset.
287287
self.assertAlmostEqual(stats[STAT_NAME_MEAN_DIFF], -offset, places=5)
288288
# - Mean absolute diff should equal abs(offset).
289-
self.assertAlmostEqual(stats[STAT_NAME_MEAN_ABS_DIFF], abs(offset), places=5)
289+
self.assertAlmostEqual(
290+
stats[STAT_NAME_MEAN_ABSOLUTE_DIFF], abs(offset), places=5
291+
)
290292
# - Median diff should equal the offset.
291293
self.assertAlmostEqual(stats[STAT_NAME_MEDIAN_DIFF], -offset, places=5)
292294
# - Variance should be 0 (no variation in differences).
@@ -339,8 +341,8 @@ def test_diff_statistics_frame_range(self):
339341

340342
# Statistics should be different for different ranges.
341343
self.assertNotAlmostEqual(
342-
stats_full[STAT_NAME_MEAN_ABS_DIFF],
343-
stats_partial[STAT_NAME_MEAN_ABS_DIFF],
344+
stats_full[STAT_NAME_MEAN_ABSOLUTE_DIFF],
345+
stats_partial[STAT_NAME_MEAN_ABSOLUTE_DIFF],
344346
places=2,
345347
)
346348
self.assertNotAlmostEqual(
@@ -387,8 +389,8 @@ def test_diff_statistics_noise_detection(self):
387389
stats = self._parse_diff_statistics_result(result)
388390

389391
# Verify noise is detected.
390-
self.assertGreater(stats[STAT_NAME_STD_POPULATION_DEV], 0.1)
391-
self.assertGreater(stats[STAT_NAME_RMS_DIFF], 0.1)
392+
self.assertGreater(stats[STAT_NAME_POPULATION_STD_DEV], 0.1)
393+
self.assertGreater(stats[STAT_NAME_ROOT_MEAN_SQUARE_DIFF], 0.1)
392394
self.assertGreater(stats[STAT_NAME_MEAN_ABSOLUTE_ERROR], 0.1)
393395
self.assertGreater(stats[STAT_NAME_ROOT_MEAN_SQUARE_ERROR], 0.1)
394396
# Mean difference should be close to zero for random noise.
@@ -503,15 +505,15 @@ def test_diff_statistics_single_flag(self):
503505
)
504506
parsed = self._parse_diff_statistics_result(result)
505507
self.assertEqual(len(parsed), 1)
506-
self.assertIn(STAT_NAME_MEAN_ABS_DIFF, parsed)
508+
self.assertIn(STAT_NAME_MEAN_ABSOLUTE_DIFF, parsed)
507509

508510
# Test RMS only.
509511
result = maya.cmds.mmAnimCurveDiffStatistics(
510512
animCurve_tx, animCurve_ty, rootMeanSquareDifference=True
511513
)
512514
parsed = self._parse_diff_statistics_result(result)
513515
self.assertEqual(len(parsed), 1)
514-
self.assertIn(STAT_NAME_RMS_DIFF, parsed)
516+
self.assertIn(STAT_NAME_ROOT_MEAN_SQUARE_DIFF, parsed)
515517

516518
# Test median difference only.
517519
result = maya.cmds.mmAnimCurveDiffStatistics(
@@ -543,7 +545,7 @@ def test_diff_statistics_single_flag(self):
543545
)
544546
parsed = self._parse_diff_statistics_result(result)
545547
self.assertEqual(len(parsed), 1)
546-
self.assertIn(STAT_NAME_NORMALIZED_RMSE, parsed)
548+
self.assertIn(STAT_NAME_NORMALIZED_ROOT_MEAN_SQUARE_ERROR, parsed)
547549

548550
# Test R-squared only.
549551
result = maya.cmds.mmAnimCurveDiffStatistics(
@@ -585,12 +587,12 @@ def test_diff_statistics_combined_flags(self):
585587
parsed = self._parse_diff_statistics_result(result)
586588
self.assertEqual(len(parsed), 2)
587589
self.assertIn(STAT_NAME_POPULATION_VARIANCE, parsed)
588-
self.assertIn(STAT_NAME_STD_POPULATION_DEV, parsed)
590+
self.assertIn(STAT_NAME_POPULATION_STD_DEV, parsed)
589591

590592
# Verify stddev = sqrt(variance).
591593
expected_stddev = math.sqrt(parsed[STAT_NAME_POPULATION_VARIANCE])
592594
self.assertAlmostEqual(
593-
parsed[STAT_NAME_STD_POPULATION_DEV], expected_stddev, places=5
595+
parsed[STAT_NAME_POPULATION_STD_DEV], expected_stddev, places=5
594596
)
595597

596598
result = maya.cmds.mmAnimCurveDiffStatistics(
@@ -605,7 +607,7 @@ def test_diff_statistics_combined_flags(self):
605607
self.assertEqual(len(parsed), 4)
606608
self.assertIn(STAT_NAME_MEAN_ABSOLUTE_ERROR, parsed)
607609
self.assertIn(STAT_NAME_ROOT_MEAN_SQUARE_ERROR, parsed)
608-
self.assertIn(STAT_NAME_NORMALIZED_RMSE, parsed)
610+
self.assertIn(STAT_NAME_NORMALIZED_ROOT_MEAN_SQUARE_ERROR, parsed)
609611
self.assertIn(STAT_NAME_R_SQUARED, parsed)
610612

611613
def test_diff_statistics_with_list_inputs(self):
@@ -629,7 +631,7 @@ def test_diff_statistics_with_list_inputs(self):
629631

630632
# For constant offset of 5:
631633
self.assertAlmostEqual(stats[STAT_NAME_MEAN_DIFF], -5.0, places=5)
632-
self.assertAlmostEqual(stats[STAT_NAME_MEAN_ABS_DIFF], 5.0, places=5)
634+
self.assertAlmostEqual(stats[STAT_NAME_MEAN_ABSOLUTE_DIFF], 5.0, places=5)
633635
self.assertAlmostEqual(stats[STAT_NAME_POPULATION_VARIANCE], 0.0, places=5)
634636
self.assertAlmostEqual(stats[STAT_NAME_MEAN_ABSOLUTE_ERROR], 5.0, places=5)
635637
self.assertAlmostEqual(stats[STAT_NAME_ROOT_MEAN_SQUARE_ERROR], 5.0, places=5)
@@ -703,8 +705,8 @@ def test_diff_statistics_noise_with_lists(self):
703705
stats = self._parse_diff_statistics_result(result)
704706

705707
# Verify noise is detected
706-
self.assertGreater(stats[STAT_NAME_STD_POPULATION_DEV], 0.1)
707-
self.assertGreater(stats[STAT_NAME_RMS_DIFF], 0.1)
708+
self.assertGreater(stats[STAT_NAME_POPULATION_STD_DEV], 0.1)
709+
self.assertGreater(stats[STAT_NAME_ROOT_MEAN_SQUARE_DIFF], 0.1)
708710
self.assertGreater(stats[STAT_NAME_MEAN_ABSOLUTE_ERROR], 0.1)
709711
self.assertGreater(stats[STAT_NAME_ROOT_MEAN_SQUARE_ERROR], 0.1)
710712
# Mean difference should be close to zero for random noise

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