MATLAB® Test Report
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Timestamp: |
25-Sep-2025 14:38:39 |
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Host: |
runnervm3ublj |
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Platform: |
glnxa64 |
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MATLAB Version: |
25.1.0.2973910 (R2025a) Update 1 |
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Number of Tests: |
24 |
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Testing Time: |
72.7998 seconds |
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Overall Result: |
PASSED |
Overview
/home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/
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40.9836 seconds |
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31.8162 seconds |
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Details
/home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/
SmokeTests
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=BalancingChemicalEquations.mlx
The test passed. Duration: 3.2461 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=IdentifyDigits.mlx
The test passed. Duration: 12.1055 seconds
Event:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:37:32 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_fa46dd4a-b25a-45cd-8b90-ab4dd3682580.png
Event Location: SmokeTests[Project=matlab.project.Project]/SmokeRun(File=IdentifyDigits.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SmokeTests.m (SmokeTests.SmokeRun) at 94 |
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=MarkovModeling.mlx
The test passed. Duration: 0.7991 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Moments.mlx
The test passed. Duration: 0.3540 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=ReadMyWriting.mlx
The test passed. Duration: 11.9110 seconds
Events:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:37:45 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_a2b2bb70-9d62-4f08-bca3-147c4c9a69db.png
Event Location: SmokeTests[Project=matlab.project.Project]/SmokeRun(File=ReadMyWriting.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SmokeTests.m (SmokeTests.SmokeRun) at 94 |
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:37:49 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_71bed6dd-0c72-491c-a6e8-f9ceebb53776.png
Event Location: SmokeTests[Project=matlab.project.Project]/SmokeRun(File=ReadMyWriting.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SmokeTests.m (SmokeTests.SmokeRun) at 94 |
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Robotics.mlx
The test passed. Duration: 7.4818 seconds
Events:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:37:51 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_ec56417e-5ca2-4475-a600-8f6c4e2438ac.png
Event Location: SmokeTests[Project=matlab.project.Project]/SmokeRun(File=Robotics.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SmokeTests.m (SmokeTests.SmokeRun) at 94 |
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:37:56 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_273cecac-7a75-4d4b-95b5-8546b210c1a1.png
Event Location: SmokeTests[Project=matlab.project.Project]/SmokeRun(File=Robotics.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SmokeTests.m (SmokeTests.SmokeRun) at 94 |
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=StaticForces.mlx
The test passed. Duration: 0.3814 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Steganography.mlx
The test passed. Duration: 4.7048 seconds
Event:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:37:58 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_b509b9e3-1d2e-431c-ac5f-60fd8b2bf904.png
Event Location: SmokeTests[Project=matlab.project.Project]/SmokeRun(File=Steganography.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SmokeTests.m (SmokeTests.SmokeRun) at 94 |
(Overview)
SolnSmokeTests
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=BalancingChemicalEquations.mlx
The test passed. Duration: 0.0836 seconds
(Overview)
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=IdentifyDigits.mlx
The test passed. Duration: 0.0064 seconds
(Overview)
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=MarkovModeling.mlx
The test passed. Duration: 0.0058 seconds
(Overview)
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Moments.mlx
The test passed. Duration: 0.0056 seconds
(Overview)
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=ReadMyWriting.mlx
The test passed. Duration: 0.0077 seconds
(Overview)
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Robotics.mlx
The test passed. Duration: 0.0055 seconds
(Overview)
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=StaticForces.mlx
The test passed. Duration: 0.0053 seconds
(Overview)
ExistSolns
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Steganography.mlx
The test passed. Duration: 0.0051 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=BalancingChemicalEquations.mlx
The test passed. Duration: 0.6060 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=IdentifyDigits.mlx
The test passed. Duration: 6.7430 seconds
Event:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:38:07 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_e100acd2-8de1-43d5-b2c1-1e1f451e67bc.png
Event Location: SolnSmokeTests[Project=matlab.project.Project]/SmokeRun(File=IdentifyDigits.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SolnSmokeTests.m (SolnSmokeTests.SmokeRun) at 110 |
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=MarkovModeling.mlx
The test passed. Duration: 4.5719 seconds
Event:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:38:11 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_06402040-7364-45c6-8e3f-0f9ebe38de59.png
Event Location: SolnSmokeTests[Project=matlab.project.Project]/SmokeRun(File=MarkovModeling.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SolnSmokeTests.m (SolnSmokeTests.SmokeRun) at 110 |
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Moments.mlx
The test passed. Duration: 0.3696 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=ReadMyWriting.mlx
The test passed. Duration: 8.8790 seconds
Events:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:38:20 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_0d0b0942-ed05-4f7a-8eb5-3dc6d16cad12.png
Event Location: SolnSmokeTests[Project=matlab.project.Project]/SmokeRun(File=ReadMyWriting.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SolnSmokeTests.m (SolnSmokeTests.SmokeRun) at 110 |
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:38:23 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_50940eb8-7b92-4bee-885d-07e69e4c48e0.png
Event Location: SolnSmokeTests[Project=matlab.project.Project]/SmokeRun(File=ReadMyWriting.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SolnSmokeTests.m (SolnSmokeTests.SmokeRun) at 110 |
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Robotics.mlx
The test passed. Duration: 6.5908 seconds
Events:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:38:24 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_9134a952-9b3d-469e-82d8-14eac7f4eb7f.png
Event Location: SolnSmokeTests[Project=matlab.project.Project]/SmokeRun(File=Robotics.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SolnSmokeTests.m (SolnSmokeTests.SmokeRun) at 110 |
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:38:30 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_f99c75fe-0bf4-49ec-b986-0f154df12464.png
Event Location: SolnSmokeTests[Project=matlab.project.Project]/SmokeRun(File=Robotics.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SolnSmokeTests.m (SolnSmokeTests.SmokeRun) at 110 |
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=StaticForces.mlx
The test passed. Duration: 0.2147 seconds
(Overview)
SmokeRun
Class Setup Parameters: Project=matlab.project.Project
Test Parameters: File=Steganography.mlx
The test passed. Duration: 3.7161 seconds
Event:
Diagnostic logged.
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Timestamp: 25-Sep-2025 14:38:31 Verbosity: Terse Logged Diagnostic: Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_fd84ba64-b09d-4c15-9fd7-4342a6590f94.png
Event Location: SolnSmokeTests[Project=matlab.project.Project]/SmokeRun(File=Steganography.mlx) Stack: In /home/runner/work/Applied-Linear-Algebra/Applied-Linear-Algebra/SoftwareTests/SolnSmokeTests.m (SolnSmokeTests.SmokeRun) at 110 |
(Overview)
Command Window Text
Running SmokeTests >> Running BalancingChemicalEquations.mlx A = [2, -1, 0] [5, -2, -2] B = 0 0 matrix([[2, -1, 0], [5, -2, -2]])*matrix([[N_2*O_5], [NO_2], [O_2]]) == matrix([[0], [0]]) ans = 2 M = 1.0000 2.0000 0.5000 1.0000 ans = 1 ans = -0.8944 0.4472 x = 2 4 1 2 N_2 O_5`→`4NO_2+ O_2 matrix([[2, 0, 0, -2, 0], [0, 4, 2, -12, -1], [0, 1, 0, -3, 0], [0, 2, 0, 0, -2]])*matrix([[x_1], [x_2], [x_3], [x_4], [x_5]]) == matrix([[0], [0], [0], [0]]) x = 1/3 1 1/2 1/3 1 x = 1/3 1 1/2 1/3 1 1/3Fe_2+ H_2SO_4+1/2 O_2`→`1/3Fe_2(SO_4)_3+ H_2 O .>> Running IdentifyDigits.mlx Name Size Bytes Class Attributes Img 784x60000 47040000 uint8 ans = 784 1 ans = 28×28 uint8 matrix Columns 1 through 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 65 76 7 0 0 0 0 0 0 0 0 0 21 170 206 46 0 0 0 0 0 0 0 0 0 39 217 251 170 2 0 0 0 0 0 0 0 2 82 233 254 215 4 0 0 0 0 0 0 0 11 141 250 254 203 4 0 0 0 0 0 0 0 91 221 254 246 127 0 0 0 0 0 0 0 22 232 254 254 202 34 0 0 0 0 0 0 7 95 251 254 251 95 7 0 0 0 0 0 0 37 215 254 254 227 46 33 17 21 0 0 0 0 37 217 254 254 249 217 205 162 173 0 0 0 0 18 122 247 254 254 255 254 254 254 0 0 0 0 0 12 190 222 245 253 253 254 252 0 0 0 0 0 0 4 9 34 102 95 115 82 0 0 0 0 0 0 0 0 0 3 3 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 33 0 0 0 0 0 0 0 0 0 0 0 9 139 0 0 0 0 0 0 0 0 0 0 0 46 208 0 0 0 0 0 0 0 0 0 0 2 170 251 0 0 0 0 0 0 0 0 0 0 4 215 254 0 0 0 0 0 0 0 0 0 0 4 203 253 0 0 0 0 0 0 0 0 0 0 0 121 213 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 Columns 14 through 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 10 91 200 90 7 0 0 0 0 0 0 0 8 127 221 253 200 32 0 0 0 0 0 0 8 126 253 254 251 95 7 0 0 0 0 0 0 34 204 254 254 232 22 0 0 0 0 0 0 0 127 246 254 234 95 0 0 0 0 0 0 0 4 203 254 254 204 34 0 0 0 0 0 0 0 5 217 254 245 115 4 0 0 0 0 0 0 1 36 234 254 220 50 0 0 0 0 0 39 82 129 189 254 254 140 9 0 0 0 0 0 217 233 246 242 254 254 125 4 0 0 0 0 0 254 254 254 254 254 246 46 0 0 0 0 0 0 233 211 242 254 254 208 8 0 0 0 0 0 0 22 41 249 254 250 129 0 0 0 0 0 0 0 0 39 250 254 245 114 0 0 0 0 0 0 0 4 115 254 254 159 22 0 0 0 0 0 0 0 34 177 254 250 52 1 0 0 0 0 0 0 0 139 250 254 232 21 0 0 0 0 0 0 0 0 221 254 251 171 3 0 0 0 0 0 0 0 0 254 255 222 51 0 0 0 0 0 0 0 0 0 254 254 215 37 0 0 0 0 0 0 0 0 0 254 247 91 7 0 0 0 0 0 0 0 0 0 254 220 11 0 0 0 0 0 0 0 0 0 0 250 139 0 0 0 0 0 0 0 0 0 0 0 201 77 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Columns 27 through 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 The success rate is 709 out of 1000 which is 70.9%. The following images are identified as 6, but are actually 0. True Distance Predicted Distance _____________ __________________ 2016.3 2001.7 2065.6 1783.2 2132.8 2052.2 2155.2 1938.7 2014 1953.3 2423.3 1844.7 2318.1 2148.6 2217.2 1868.5 The success rate is 5 out of 10 which is 50%. [Terse] Diagnostic logged (2025-09-25 14:37:32): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_fa46dd4a-b25a-45cd-8b90-ab4dd3682580.png .>> Running MarkovModeling.mlx T = 1 0 0 0 1 0 0 0 1 This is the identity matrix. In this system, nothing changes. That is not correct for this system. TransitionMatrix = [1, 0, 0] [0, 1, 0] [0, 0, 1] Susceptible Infected Zombies ___________ ________ _______ 100 steps 999999 1 0 V = [1, 0, 0] [0, 1, 0] [0, 0, 1] D = [1, 0, 0] [0, 1, 0] [0, 0, 1] TransitionMatrix2 = [1 - alpha_SI, 0, 0] [ 0, 1, 0] [ 0, 0, 1] Vs = [0, 0, 1] [1, 0, 0] [0, 1, 0] Ds = [1, 0, 0] [0, 1, 0] [0, 0, 1 - alpha_SI] MySoln = struct with fields: beta_IS: [0×1 sym] parameters: [1×0 sym] conditions: [0×1 sym] TransitionMatrix3 = Empty sym: 0-by-1 .>> Running Moments.mlx M_AC = -16.5000 0 0 Yes, it is in the x-direction, and it is in the negative direction, away from us. This is will cause clockwise rotation around the x-axis. M_BC = 0 0 0 The force at C is (-16.5,0,0). This indicates clockwise rotation around C. That is not a static equilibrium. Please try again. These are the default values for A, B, and C. Please complete the exercise. F_R = NaN MR = NaN Mx = NaN My = NaN NaN is the default value. Please solve the problem and resubmit. M_axis = NaN Please complete Exercise 1 before attempting Exercise 2. TAB = 0 TAC = 0 TAD = 0 This is the default value. Please solve this problem and resubmit. .>> Running ReadMyWriting.mlx In order, these are identified as: 3 [Terse] Diagnostic logged (2025-09-25 14:37:45): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_a2b2bb70-9d62-4f08-bca3-147c4c9a69db.png [Terse] Diagnostic logged (2025-09-25 14:37:49): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_71bed6dd-0c72-491c-a6e8-f9ceebb53776.png .>> Running Robotics.mlx MaxPaths = 170 You have chosen the point (-0.93684, 0.31412). [Warning: Hardware-accelerated graphics is unavailable. Displaying fewer markers to preserve interactivity.] [> In matlab.ui.internal.controller/FigureController/exportToPngBase64 (line 351) In matlab.ui.internal.FigureImageCaptureService.exportToPngBase64 (line 91) In matlab.graphics.internal.getframeWithDecorations>getWebFigureWithDecorations (line 46) In matlab.graphics.internal.getframeWithDecorations (line 27) In exportapp In matlab.unittest.diagnostics.FigureDiagnostic>figureToArtifact (line 229) In matlab.unittest.diagnostics.FigureDiagnostic>@(format)figureToArtifact(diag.Figure,fileNameWithoutExt,format,diagData.ArtifactsDisplayFolder) (line 167) In matlab.unittest.diagnostics/FigureDiagnostic/diagnoseWith (line 167) In matlab.unittest.internal.diagnostics.DiagnosticResultCache>safelyDiagnoseWith (line 47) In matlab.unittest.internal.diagnostics.DiagnosticResultCache>captureFormattableResult (line 38) In matlab.unittest.internal.diagnostics/DiagnosticResultCache/getFormattableResultFor (line 28) In matlab.unittest.diagnostics.DiagnosticResultsStore>@(cache)cache.getFormattableResultFor(diagData) (line 24) In matlab.unittest.diagnostics/DiagnosticResultsStore/getFormattableResults (line 24) In matlab.unittest.internal.eventrecords.LoggedDiagnosticEventRecord.fromEventData (line 62) In matlab.unittest.internal.plugins/EventRecordProducer/produceLoggedDiagnosticEventRecord (line 161) In matlab.unittest.internal.plugins.EventRecordProducer>@(~,eventData)producer.produceLoggedDiagnosticEventRecord(eventData,eventScope,eventLocation,locationProvider) (line 120) In SmokeTests/SmokeRun (line 94)] [Terse] Diagnostic logged (2025-09-25 14:37:51): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_ec56417e-5ca2-4475-a600-8f6c4e2438ac.png [Terse] Diagnostic logged (2025-09-25 14:37:56): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_273cecac-7a75-4d4b-95b5-8546b210c1a1.png .>> Running StaticForces.mlx F_AB = 0 -268.3282 -536.6563 F_AC = 242.5356 363.8034 -242.5356 F_R = 242.5356 95.4753 -779.1919 u_FR = 0.2952 0.1162 -0.9483 The default value is nan. Please enter real numbers. The default value is nan. Please enter real numbers. The default value is nan. Please enter real numbers. The default value is nan. Please enter real numbers. You must compute the correct cartesian coordinates for B, A, C, and O before continuing. These are default values. Please complete the problem. .>> Running Steganography.mlx SizeOfMouse = 192 500 SizeOfTurkeys = 562 1963 3 RotateMe = 0 1 0 0 0 1 1 0 0 channels = 1 2 3 channelSelect = 2 3 1 A = 1 2 3 4 copySideways = 1 1 0 0 0 0 1 1 ans = 1 1 2 2 3 3 4 4 ans = 2×1 uint8 column vector 0 1 cutValue = 0 [Terse] Diagnostic logged (2025-09-25 14:37:58): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_b509b9e3-1d2e-431c-ac5f-60fd8b2bf904.png . Done SmokeTests __________ Running SolnSmokeTests ........>> Running BalancingChemicalEquationsSoln.mlx A = [2, -1, 0] [5, -2, -2] B = 0 0 matrix([[2, -1, 0], [5, -2, -2]])*matrix([[N_2*O_5], [NO_2], [O_2]]) == matrix([[0], [0]]) [Warning: Solution is not unique because the system is rank-deficient.] [> In mupadengine/evalin2sym In mupadengine/feval2sym In sym/privBinaryOp (line 1079) In \ (line 427) In BalancingChemicalEquationsSoln (line 7) In run (line 112) In SolnSmokeTests/SmokeRun (line 94) In matlab.unittest/TestRunner/evaluateMethodCore (line 1089) In matlab.unittest/TestRunner/evaluateMethodsOnTestContent (line 1020) In matlab.unittest/TestRunner/runTestMethodCore (line 1199) In matlab.unittest/TestRunner/runTestCore (line 1171) In matlab.unittest/TestRunner/repeatTest (line 615) In matlab.unittest/TestRunner/runSharedTestCase (line 556) In matlab.unittest/TestRunner/runTestClass (line 1465) In matlab.unittest.plugins/TestRunnerPlugin/runTestClass (line 430) In matlab.unittest.plugins.testrunprogress/ConciseProgressPlugin/runTestClass (line 68) In matlab.unittest/TestRunner/runTestSuite (line 1390) In matlab.unittest.plugins/TestRunnerPlugin/runTestSuite (line 265) In matlab.unittest.plugins/DiagnosticsOutputPlugin/runTestSuite (line 161) In matlab.unittest.plugins/TestRunnerPlugin/runTestSuite (line 265) In matlab.unittest.plugins/TestReportPlugin/runTestSuite (line 296) In matlab.unittest/TestRunner/evaluateMethodOnPlugins (line 473) In matlab.unittest.internal/SerialTestRunStrategy/runTestSuite (line 36) In matlab.unittest.internal/SerialTestRunStrategy/runSession (line 16) In matlab.unittest/TestRunner/runSession (line 1346) In matlab.unittest.plugins/TestRunnerPlugin/runSession (line 228) In matlab.unittest.plugins/TestReportPlugin/runSession (line 290) In matlab.unittest/TestRunner/evaluateMethodOnPlugins (line 473) In matlab.unittest/TestRunner/doRunWithFcn (line 461) In matlab.unittest/TestRunner/run (line 344) In RunAllTests (line 30) In command_c0ae8956_b9b1_4233_ba8c_8d7a93b0ff19 (line 1) ] x = 0 0 0 ans = 0 0 ans = 2 ans = 1 ans = 2 M = 1.0000 2.0000 0.5000 1.0000 ans = 1 ans = -0.8944 0.4472 x = 2 4 1 2 N_2 O_5`→`4NO_2+ O_2 matrix([[2, 0, 0, -2, 0], [0, 4, 2, -12, -1], [0, 1, 0, -3, 0], [0, 2, 0, 0, -2]])*matrix([[x_1], [x_2], [x_3], [x_4], [x_5]]) == matrix([[0], [0], [0], [0]]) x = 1/3 1 1/2 1/3 1 x = 2 6 3 2 6 2Fe_2+6 H_2SO_4+3 O_2`→`2Fe_2(SO_4)_3+6 H_2 O The solution is matrix([[x_1], [x_2], [x_3]]) = matrix([[4], [3], [2]]). 4Fe+3 O_2`→`2Fe_2 O_3 The solution is matrix([[x_1], [x_2], [x_3], [x_4]]) = matrix([[1], [5], [3], [4]]). C_3 H_8+5 O_2`→`3 C O_2+4 H_2 O The solution is matrix([[x_1], [x_2], [x_3], [x_4], [x_5], [x_6], [x_7]]) = matrix([[2], [3], [5], [1], [2], [8], [10]]). 2KMnO_4+3 H_2SO_4+5 H_2 C_2 O_4`→` K_2SO_4+2MnSO_4+8 H_2 O+10CO_2 .>> Running IdentifyDigitsSoln.mlx Name Size Bytes Class Attributes Img 784x60000 47040000 uint8 ans = 784 1 ans = 28×28 uint8 matrix Columns 1 through 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 65 76 7 0 0 0 0 0 0 0 0 0 21 170 206 46 0 0 0 0 0 0 0 0 0 39 217 251 170 2 0 0 0 0 0 0 0 2 82 233 254 215 4 0 0 0 0 0 0 0 11 141 250 254 203 4 0 0 0 0 0 0 0 91 221 254 246 127 0 0 0 0 0 0 0 22 232 254 254 202 34 0 0 0 0 0 0 7 95 251 254 251 95 7 0 0 0 0 0 0 37 215 254 254 227 46 33 17 21 0 0 0 0 37 217 254 254 249 217 205 162 173 0 0 0 0 18 122 247 254 254 255 254 254 254 0 0 0 0 0 12 190 222 245 253 253 254 252 0 0 0 0 0 0 4 9 34 102 95 115 82 0 0 0 0 0 0 0 0 0 3 3 4 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 33 0 0 0 0 0 0 0 0 0 0 0 9 139 0 0 0 0 0 0 0 0 0 0 0 46 208 0 0 0 0 0 0 0 0 0 0 2 170 251 0 0 0 0 0 0 0 0 0 0 4 215 254 0 0 0 0 0 0 0 0 0 0 4 203 253 0 0 0 0 0 0 0 0 0 0 0 121 213 0 0 0 0 0 0 0 0 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 Columns 14 through 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 10 91 200 90 7 0 0 0 0 0 0 0 8 127 221 253 200 32 0 0 0 0 0 0 8 126 253 254 251 95 7 0 0 0 0 0 0 34 204 254 254 232 22 0 0 0 0 0 0 0 127 246 254 234 95 0 0 0 0 0 0 0 4 203 254 254 204 34 0 0 0 0 0 0 0 5 217 254 245 115 4 0 0 0 0 0 0 1 36 234 254 220 50 0 0 0 0 0 39 82 129 189 254 254 140 9 0 0 0 0 0 217 233 246 242 254 254 125 4 0 0 0 0 0 254 254 254 254 254 246 46 0 0 0 0 0 0 233 211 242 254 254 208 8 0 0 0 0 0 0 22 41 249 254 250 129 0 0 0 0 0 0 0 0 39 250 254 245 114 0 0 0 0 0 0 0 4 115 254 254 159 22 0 0 0 0 0 0 0 34 177 254 250 52 1 0 0 0 0 0 0 0 139 250 254 232 21 0 0 0 0 0 0 0 0 221 254 251 171 3 0 0 0 0 0 0 0 0 254 255 222 51 0 0 0 0 0 0 0 0 0 254 254 215 37 0 0 0 0 0 0 0 0 0 254 247 91 7 0 0 0 0 0 0 0 0 0 254 220 11 0 0 0 0 0 0 0 0 0 0 250 139 0 0 0 0 0 0 0 0 0 0 0 201 77 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Columns 27 through 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 digit = 5 ans = 665 The success rate is 888 out of 1000 which is 88.8%. The following images are identified as 6, but are actually 0. True Distance Predicted Distance _____________ __________________ 1710.1 1645.2 The success rate is 7 out of 10 which is 70%. [Terse] Diagnostic logged (2025-09-25 14:38:07): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_e100acd2-8de1-43d5-b2c1-1e1f451e67bc.png . >> Running MarkovModelingSoln.mlx T = [1 - alpha_SI, alpha_SI, 0] [ 0, 0, 1] [ 0, 0, 1] That looks like the correct transition matrix. TransitionMatrix = [99/100, 1/100, 0] [ 0, 0, 1] [ 0, 0, 1] Susceptible Infected Zombies ___________ ________ _______ 30 steps 739700 7472 252829 ans = [739700373388280422730015092316714942252676262352676444347001/1000000000000000000000000000000000000000000000000000000000000, 7471720943315963865959748407239544871239154165178549942899/1000000000000000000000000000000000000000000000000000000000000, 2528279056684036134040251592760455128760845834821450057101/10000000000000000000000000000000000000000000000000000000000] [ 0, 0, 1] [ 0, 0, 1] ans = [0.7397, 0.0075, 0.2528] [ 0, 0, 1.0] [ 0, 0, 1.0] ans = 1 1 1 ans = 1 1 1 V = [ 0, -99/100, 0] [-1, -1/100, 0] [ 1, 1, 1] D = [0, 0, 0] [0, 99/100, 0] [0, 0, 1] ans = [0, 0, 1] TransitionMatrix2 = [1 - alpha_SI, alpha_SI, 0] [ beta_IS, 0, 1 - beta_IS] [ 0, 0, 1] Vs = [0, - (alpha_SI/2 + (4*alpha_SI*beta_IS - 2*alpha_SI + alpha_SI^2 + 1)^(1/2)/2 - 1/2)/(beta_IS - 1) - beta_IS/(beta_IS - 1), ((4*alpha_SI*beta_IS - 2*alpha_SI + alpha_SI^2 + 1)^(1/2)/2 - alpha_SI/2 + 1/2)/(beta_IS - 1) - beta_IS/(beta_IS - 1)] [0, 1/(beta_IS - 1) + (alpha_SI/2 + (4*alpha_SI*beta_IS - 2*alpha_SI + alpha_SI^2 + 1)^(1/2)/2 - 1/2)/(beta_IS - 1), 1/(beta_IS - 1) - ((4*alpha_SI*beta_IS - 2*alpha_SI + alpha_SI^2 + 1)^(1/2)/2 - alpha_SI/2 + 1/2)/(beta_IS - 1)] [1, 1, 1] Ds = [1, 0, 0] [0, 1/2 - (4*alpha_SI*beta_IS - 2*alpha_SI + alpha_SI^2 + 1)^(1/2)/2 - alpha_SI/2, 0] [0, 0, (4*alpha_SI*beta_IS - 2*alpha_SI + alpha_SI^2 + 1)^(1/2)/2 - alpha_SI/2 + 1/2] MySoln = struct with fields: beta_IS: 1 parameters: [1×0 sym] conditions: -1 <= alpha_SI & alpha_SI ~= 0 TransitionMatrix3 = [1 - alpha_SI, alpha_SI, 0] [ 1, 0, 0] [ 0, 0, 1] Vs3 = [1/alpha_SI, 0, -1] [ 1, 0, 1] [ 0, 1, 0] Ds3 = [1, 0, 0] [0, 1, 0] [0, 0, -alpha_SI] Vfinal = [(gamma_ZI + 2*gamma_ZS)/alpha_SI, alpha_SI - gamma_ZI - gamma_ZS + (alpha_SI^2 - 2*alpha_SI*gamma_ZI - 2*alpha_SI*gamma_ZS + gamma_ZI^2 + 2*gamma_ZI*gamma_ZS + gamma_ZS^2 - 2*gamma_ZS + 1)^(1/2), alpha_SI - gamma_ZI - gamma_ZS - (alpha_SI^2 - 2*alpha_SI*gamma_ZI - 2*alpha_SI*gamma_ZS + gamma_ZI^2 + 2*gamma_ZI*gamma_ZS + gamma_ZS^2 - 2*gamma_ZS + 1)^(1/2)] [ 2*gamma_ZI + 2*gamma_ZS, gamma_ZI - alpha_SI + gamma_ZS - (alpha_SI^2 - 2*alpha_SI*gamma_ZI - 2*alpha_SI*gamma_ZS + gamma_ZI^2 + 2*gamma_ZI*gamma_ZS + gamma_ZS^2 - 2*gamma_ZS + 1)^(1/2) - 1, gamma_ZI - alpha_SI + gamma_ZS + (alpha_SI^2 - 2*alpha_SI*gamma_ZI - 2*alpha_SI*gamma_ZS + gamma_ZI^2 + 2*gamma_ZI*gamma_ZS + gamma_ZS^2 - 2*gamma_ZS + 1)^(1/2) - 1] [ 1, 1, 1] Dfinal = [1, 0, 0] [0, 1/2 - gamma_ZI/2 - gamma_ZS/2 - (alpha_SI^2 - 2*alpha_SI*gamma_ZI - 2*alpha_SI*gamma_ZS + gamma_ZI^2 + 2*gamma_ZI*gamma_ZS + gamma_ZS^2 - 2*gamma_ZS + 1)^(1/2)/2 - alpha_SI/2, 0] [0, 0, (alpha_SI^2 - 2*alpha_SI*gamma_ZI - 2*alpha_SI*gamma_ZS + gamma_ZI^2 + 2*gamma_ZI*gamma_ZS + gamma_ZS^2 - 2*gamma_ZS + 1)^(1/2)/2 - gamma_ZI/2 - gamma_ZS/2 - alpha_SI/2 + 1/2] D = 1.0000 0 0 0 -0.2000 0 0 0 -0.0000 W = 0.3642 0.7071 0.4082 0.6724 0.0000 -0.8165 0.6444 -0.7071 0.4082 ChooseAnEigenvalue = 0×1 empty double column vector Yes, T is stochastic matrix. TransitionMatrix = 0 1 0 0 0 0 1 0 0 0 0 1 1 0 0 0 D = -1.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 1.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 - 1.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 1.0000 + 0.0000i W = 0.5000 + 0.0000i 0.5000 + 0.0000i 0.5000 + 0.0000i 0.5000 + 0.0000i -0.5000 + 0.0000i 0.0000 + 0.5000i 0.0000 - 0.5000i 0.5000 + 0.0000i 0.5000 + 0.0000i -0.5000 + 0.0000i -0.5000 - 0.0000i 0.5000 + 0.0000i -0.5000 + 0.0000i 0.0000 - 0.5000i 0.0000 + 0.5000i 0.5000 + 0.0000i P0 = 3000 0 0 0 ans = 0 3000 0 0 ans = 0 0 3000 0 ans = 0 0 0 3000 ans = 3000 0 0 0 ans = 1.0e+05 * 0.0144 0.0020 0.0005 0.0001 0.0562 0.0078 0.0018 0.0003 0.2442 0.0337 0.0078 0.0014 1.3257 0.1831 0.0422 0.0078 ans = 1.0000 0.1497 0.0373 0.0074 3.3487 0.5011 0.1250 0.0249 13.4254 2.0092 0.5011 0.1000 67.2812 10.0691 2.5115 0.5011 StillAlive = 0.6620 0.6447 0.6335 0.5544 [Terse] Diagnostic logged (2025-09-25 14:38:11): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_06402040-7364-45c6-8e3f-0f9ebe38de59.png .>> Running MomentsSoln.mlx M_AC = -16.5000 0 0 Yes, it is in the x-direction, and it is in the negative direction, away from us. This is will cause clockwise rotation around the x-axis. M_BC = 16.5000 0 0 That is correct. Yes, A = (0,0,6) is correct. Yes, B = (0,2.5,0) is correct. Yes, C = (2,-3,0) is correct. F_R = 132 132 -1188 MR = -792 792 0 Mx = -792 My = 792 You are correct. u_axis = 0.7071 0.7071 0 M_axis = 0 That is correct. TAB = (209^(1/2)*w)/24 TAC = 0 TAD = (209^(1/2)*w)/24 w1 = (360*209^(1/2))/209 w2 = (360*209^(1/2))/209 w3 = Empty sym: 0-by-1 MinWt = (360*209^(1/2))/209 mass = (4000000*209^(1/2))/22781 ans = 2538.4*[kg] That is correct. .>> Running ReadMyWritingSoln.mlx In order, these are identified as: 3 [Terse] Diagnostic logged (2025-09-25 14:38:20): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_0d0b0942-ed05-4f7a-8eb5-3dc6d16cad12.png [Terse] Diagnostic logged (2025-09-25 14:38:23): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_50940eb8-7b92-4bee-885d-07e69e4c48e0.png .>> Running RoboticsSoln.mlx MaxPaths = 5 You have chosen the point (-0.36973, -0.63947). [Terse] Diagnostic logged (2025-09-25 14:38:24): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_9134a952-9b3d-469e-82d8-14eac7f4eb7f.png [Terse] Diagnostic logged (2025-09-25 14:38:30): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_f99c75fe-0bf4-49ec-b986-0f154df12464.png .>> Running StaticForcesSoln.mlx F_AB = 0 -268.3282 -536.6563 F_AC = 242.5356 363.8034 -242.5356 F_R = 242.5356 95.4753 -779.1919 u_FR = 0.2952 0.1162 -0.9483 Correct. Please continue with the problem. What are the units of the argument to cos(theta) in MATLAB? Do you know the cosd() function? What are the units of the argument to sin(theta) in MATLAB? Do you know the sind() function? Correct. Please continue with the problem. Correct. Please continue with the problem. Correct. Please continue with the problem. Yes, the cartesian force vector from A to O is (-60.7428,279.3,-91.11421) Yes, the cartesian force vector from C to B is (107.8135,99.14693,-32.34405) Fweight = 47.0707 378.4470 -123.4583 That is correct. F_AC = 276.32*[lbf] F_AB = 127.3*[lbf] F_AD = 331.58*[lbf] .>> Running SteganographySoln.mlx SizeOfMouse = 192 500 SizeOfTurkeys = 562 1963 3 RotateMe = 0 1 0 0 0 1 1 0 0 channels = 1 2 3 channelSelect = 2 3 1 A = 1 2 3 4 copySideways = 1 1 0 0 0 0 1 1 ans = 1 1 2 2 3 3 4 4 copyDown = 1 0 1 0 0 1 0 1 ans = 1 2 1 2 3 4 3 4 ans = 1 1 2 2 1 1 2 2 3 3 4 4 3 3 4 4 ans = 2.9271 3.9260 ans = 2×1 uint8 column vector 0 1 This will work! This will not work in rows. oM = 900 oN = 1600 oC = 3 mdM = 384 mdN = 1536 mdC = 3 This will work in columns! Embedded a color image. This message can be embedded. CutValue = 258 [Terse] Diagnostic logged (2025-09-25 14:38:31): Figure saved to: --> /tmp/3ce3dd61-d12d-493b-8e6f-4eb133f98820/Figure_fd84ba64-b09d-4c15-9fd7-4342a6590f94.png . Done SolnSmokeTests __________