fix(test): update LAMMPS spin test expected values for PT model

Copilot · OutisLi · Copilot · commit 17e6adf243d2 · 2026-02-25T06:56:31.000Z
Co-authored-by: OutisLi &lt;137472077+OutisLi@users.noreply.github.com&gt;
diff --git a/source/lmp/tests/test_lammps_spin_nopbc_pt.py b/source/lmp/tests/test_lammps_spin_nopbc_pt.py
@@ -32,21 +32,21 @@
 md_file = Path(__file__).parent / "md.out"
 
 expected_ae = np.array(
-    [-5.452114789070532, -5.480146653237549, -5.196470063744647, -5.196470063744647]
+    [-2.337313880002, -2.339828637443377, -2.358478126000974, -2.358478126000974]
 )
 expected_e = np.sum(expected_ae)
 expected_f = np.array(
     [
-        [0.1005891161568464, -0.0421386837954357, -0.1035159238420185],
-        [-0.1005891161568464, 0.0421386837954357, 0.1035159238420185],
-        [-0.0874023630887424, -0.0816522076223778, 0.1196032337003844],
-        [0.0874023630887424, 0.0816522076223778, -0.1196032337003844],
+        [0.036908169450058, -0.0154615304452946, -0.0277072310206975],
+        [-0.036908169450058, 0.0154615304452946, 0.0277072310206975],
+        [-0.001114392839443, -0.0010410775210586, 0.0015249586223957],
+        [0.001114392839443, 0.0010410775210586, -0.0015249586223957],
     ]
 )
 expected_fm = np.array(
     [
-        [0.0248296941890119, -0.0104016286467482, 0.0166496777995534],
-        [-0.0407454346265244, 0.0170690334246251, 0.0337262181162752],
+        [0.0075469514215227, -0.0031615607306379, 0.0204654183352036],
+        [-0.0074172317569893, 0.003107218709009, 0.020927678503653],
         [0.0000000000000000, 0.00000000000000000, 0.00000000000000000],
         [0.0000000000000000, 0.00000000000000000, 0.00000000000000000],
     ]
diff --git a/source/lmp/tests/test_lammps_spin_pt.py b/source/lmp/tests/test_lammps_spin_pt.py
@@ -33,21 +33,21 @@
 md_file = Path(__file__).parent / "md.out"
 
 expected_ae = np.array(
-    [-5.449480235829702, -5.477427268428831, -5.123857693399778, -5.177090216511519]
+    [-2.33730603846356, -2.339828637443377, -2.3584765990764933, -2.358478126000974]
 )
 expected_e = np.sum(expected_ae)
 expected_f = np.array(
     [
-        [0.0009801138704236, -0.0463347604851765, -0.0971306357815108],
-        [-0.1470821855808306, 0.0437825717490265, 0.1068452488480858],
-        [0.0227539242796509, -0.0733473535079378, 0.1021096625763913],
-        [0.123348147430756, 0.0758995422440877, -0.1118242756429664],
+        [0.036819000183374, -0.0154603124989284, -0.0277136918031471],
+        [-0.0369115932121166, 0.0154614940830129, 0.0277067438704936],
+        [-0.0010240778189108, -0.0010425850123752, 0.0015323196618039],
+        [0.0011166708476534, 0.0010414034282908, -0.0015253717291505],
     ]
 )
 expected_fm = np.array(
     [
-        [0.0072488655758703, -0.0111496506342658, 0.018024837587741],
-        [-0.0469100751121456, 0.0170834549641258, 0.0338904617477562],
+        [0.007540380021158, -0.0031615447712641, 0.0204706018052022],
+        [-0.0074177167392878, 0.0031072528813168, 0.0209277147341756],
         [0.0000000000000000, 0.00000000000000000, 0.00000000000000000],
         [0.0000000000000000, 0.00000000000000000, 0.00000000000000000],
     ]
@@ -73,62 +73,44 @@
 
 expected_v = -np.array(
     [
-        0.0070639867264982,
-        -0.0005923577001662,
-        -0.0015491268442953,
-        -0.0005741900039506,
-        0.0004072991754844,
-        0.0005919446476345,
-        -0.0013659665914274,
-        0.0005245686552392,
-        0.0011288634277803,
-        0.0074611996305919,
-        -0.0015158254500315,
-        -0.0030704181444311,
-        -0.0015503527871207,
-        0.0006417155838534,
-        0.0010901024672963,
-        -0.0032762727340245,
-        0.0011481000769186,
-        0.0022122852076016,
-        -0.0049637269273085,
-        -0.0033079530214069,
-        0.0048850199723435,
-        -0.0032277537906931,
-        -0.0030526361938397,
-        0.0044721003136312,
-        0.0053457625015160,
-        0.0044600355962439,
-        -0.0065441506206723,
-        -0.0044231868209291,
-        -0.0033953486551904,
-        0.0050014995082810,
-        -0.0035584060948890,
-        -0.0032308004485022,
-        0.0047399657455500,
-        0.0056902937417672,
-        0.0047696802946761,
-        -0.0070004831270587,
-        0.0034978220789713,
-        -0.0044217265408896,
-        -0.0075771507215158,
-        -0.0043265981217727,
-        0.0016344211766637,
-        0.0031438764476946,
-        -0.0069613658908443,
-        0.0032277030414985,
-        0.0055466693735168,
-        -0.0182670501038624,
-        -0.0030197903610554,
-        0.0012333318415169,
-        -0.0030157009303137,
-        0.0006787737562374,
-        0.0017594542103399,
-        0.0025814653441594,
-        0.0020137939338955,
-        0.0014966802677115,
+        0.0138536891649799,
+        -0.0057815832940349,
+        -0.0104366273910430,
+        -0.0057802135977019,
+        0.0024216972469495,
+        0.0043747666241247,
+        -0.0120159787305366,
+        0.0050342035124280,
+        0.0090942101965059,
+        0.0135151396517160,
+        -0.0056617476919350,
+        -0.0102276732499471,
+        -0.0056606594176084,
+        0.0023713573235927,
+        0.0042837422619739,
+        -0.0084858208754591,
+        0.0035548709072868,
+        0.0064217022841311,
+        0.0007099617850315,
+        0.0003917168967788,
+        -0.0005467867622337,
+        0.0003906286224523,
+        0.0003696501943719,
+        -0.0005419287758774,
+        -0.0005551067425154,
+        -0.0005416915274450,
+        0.0007957607021995,
+        0.0004252005652282,
+        0.0003972268438316,
+        -0.0005818534050492,
+        0.0003958571474987,
+        0.0003698139141107,
+        -0.0005416992544720,
+        -0.0005797982376440,
+        -0.0005416536167464,
+        0.0007934081146707,
     ]
-).reshape(6, 9)
+).reshape(4, 9)
 
 expected_v2 = -np.array(
     [
@@ -168,26 +150,8 @@
         0.0010319090966831,
         0.0009955172109546,
         -0.0014553634659113,
-        0.0027303678059308,
-        -0.0017755948961346,
-        -0.0030761923779883,
-        -0.0017183308924552,
-        0.0006816964863724,
-        0.0012957090028794,
-        -0.0042486220709583,
-        0.0018539755349361,
-        0.0032531905210736,
-        -0.0053263906035893,
-        -0.0013059666848022,
-        -0.0000753225555805,
-        -0.0013078437276500,
-        0.0003423965327707,
-        0.0008080454760442,
-        0.0003139988733780,
-        0.0008955147923178,
-        0.0008788489971600,
     ]
-).reshape(6, 9)
+).reshape(4, 9)
 
 box = np.array([0, 13, 0, 13, 0, 13, 0, 0, 0])
 coord = np.array(

Original file line number	Diff line number	Diff line change
`@@ -32,21 +32,21 @@`
`32`	`32`	`md_file = Path(__file__).parent / "md.out"`
`33`	`33`
`34`	`34`	`expected_ae = np.array(`
`35`		`- [-5.452114789070532, -5.480146653237549, -5.196470063744647, -5.196470063744647]`
	`35`	`+ [-2.337313880002, -2.339828637443377, -2.358478126000974, -2.358478126000974]`
`36`	`36`	`)`
`37`	`37`	`expected_e = np.sum(expected_ae)`
`38`	`38`	`expected_f = np.array(`
`39`	`39`	`[`
`40`		`- [0.1005891161568464, -0.0421386837954357, -0.1035159238420185],`
`41`		`- [-0.1005891161568464, 0.0421386837954357, 0.1035159238420185],`
`42`		`- [-0.0874023630887424, -0.0816522076223778, 0.1196032337003844],`
`43`		`- [0.0874023630887424, 0.0816522076223778, -0.1196032337003844],`
	`40`	`+ [0.036908169450058, -0.0154615304452946, -0.0277072310206975],`
	`41`	`+ [-0.036908169450058, 0.0154615304452946, 0.0277072310206975],`
	`42`	`+ [-0.001114392839443, -0.0010410775210586, 0.0015249586223957],`
	`43`	`+ [0.001114392839443, 0.0010410775210586, -0.0015249586223957],`
`44`	`44`	`]`
`45`	`45`	`)`
`46`	`46`	`expected_fm = np.array(`
`47`	`47`	`[`
`48`		`- [0.0248296941890119, -0.0104016286467482, 0.0166496777995534],`
`49`		`- [-0.0407454346265244, 0.0170690334246251, 0.0337262181162752],`
	`48`	`+ [0.0075469514215227, -0.0031615607306379, 0.0204654183352036],`
	`49`	`+ [-0.0074172317569893, 0.003107218709009, 0.020927678503653],`
`50`	`50`	`[0.0000000000000000, 0.00000000000000000, 0.00000000000000000],`
`51`	`51`	`[0.0000000000000000, 0.00000000000000000, 0.00000000000000000],`
`52`	`52`	`]`