Add FUNMAN test (#3482)

testing/model-extraction.md

@@ -1,36 +1,33 @@
 ## Model extraction
-Please go through __every__ steps of the test scenario. 
-When blocked, or an error, an UI/UX anomaly occurs, please report which scenario and step to [ #askem-testing](https://unchartedsoftware.slack.com/archives/C06FGLXB2CE).
-
+Please go through __every__ step of the test scenario.\
+When blocked, an error, or a UI/UX anomaly occurs, please report which scenario and step to [\#askem-testing](https://unchartedsoftware.slack.com/archives/C06FGLXB2CE).
 
 ### 1. Begin test 
-- [ ] a. login to https://app.staging.terarium.ai using the test account
-
-```
-email: [email protected]
-password: askem-quality-assurance
-```
-
-- [ ] b. Create project named `Q&A [Your Name]`
+1. Login to https://app.staging.terarium.ai using the test account
+ ```
+ email: [email protected]
+ password: askem-quality-assurance
+ ```
+2. Create, or open, project named `Q&A [Your Name] [YYMMDD]`
 
 ### 2. Upload a PDF
-- [ ] a. Upload _the Document_ [SIR](https://drive.google.com/file/d/1vN4sNR7IrRi5GsOQ9r_LgV4S5wwinXnG/view?usp=drive_link)
-- [ ] b. Wait for final notification of document extraction
-- [ ] c. Open _the Document_ and check that extractions are visible
+1. Upload _the Document_ [SIR](https://drive.google.com/file/d/1vN4sNR7IrRi5GsOQ9r_LgV4S5wwinXnG/view?usp=drive_link)
+2. Wait for final notification of document extraction
+3. Open _the Document_ and check that extractions are visible
 
 ### 3. Extract model from document
-- [ ] a. Create a new workflow named `Extract model from document`
-- [ ] b. Drag and drop _the Document_ onto the workflow
-- [ ] c. Add the operator `Create model from equations`
-- [ ] d. Link _the Document_ and open the operator
-- [ ] e. Select the equations `S`, `I` and `R` and create model
-- [ ] f. Save model and name as `SIR`
+1. Create a new workflow named `Extract model from document`
+2. Drag and drop _the Document_ onto the workflow
+3. Add the operator `Create model from equations`
+4. Link _the Document_ and open the operator
+5. Select the equations `S`, `I` and `R` and create model
+6. Save model and name as `SIR`
 
 ### 4. Check extractions from document
-- [ ] a. Open model `SIR`
-- [ ] b. Is the TA1 _model card_, extracted with `mit-tr` available?
-- [ ] c. Is the TA4 _model card_, extracted from `gollm-taskrunner` available?
-- [ ] d. Are the _variables extractions_ available in the `Other` accordion?
+1. Open model `SIR`
+2. Is the TA1 _model card_, extracted with `mit-tr` available?
+3. Is the TA4 _model card_, extracted from `gollm-taskrunner` available?
+4. Are the _variables extractions_ available in the `Other` accordion?
 
 ### 5. End test
-- [ ] a. logout of the application 
+1. logout of the application 

testing/validate-model-configuration.md

@@ -0,0 +1,64 @@
+## Validate Model Configuration
+Please go through __every__ step of the test scenario.\
+When blocked, an error, or a UI/UX anomaly occurs, please report which scenario and step to [\#askem-testing](https://unchartedsoftware.slack.com/archives/C06FGLXB2CE).
+
+### 1. Begin test
+1. Login to https://app.staging.terarium.ai using the test account
+ ```
+ email: [email protected]
+ password: askem-quality-assurance
+ ```
+2. Create, or open, project named `Q&A [Your Name] [YYMMDD]`
+
+### 2. Workflow
+1. Create a new workflow named `Validate Model Configuration`
+2. Upload _the Model_ [Configured SIR.json](https://drive.google.com/file/d/144jN19MrMYbE_nwmOgk2VD-GpNzrcf9d/view?usp=drive_link)
+3. Drag and drop _the Model_ onto the workflow
+4. Link and open a _Configure Model_ operator
+5. Verify that the model is configured correctly \
+ `β: 0.6, γ: 0.2, S: 1000, I: 2, R: 0`
+6. Save the configuration by giving it a name and clicking `Run`
+
+### 3. Operator setup
+1. Link to a _Validate configuration_ operator
+2. You should see an `additonal options` section, expand it
+3. A tolerance/threshold input should be available 
+ - set to `0.1`, this tells Funman to create smaller bounding boxes 
+4. A dropdown `parameters of interest` should be available populated with model parameters and states
+ - select `beta (β)` and `gamma (γ)`.
+
+### 4. Compartmental constraint
+It ensures non-negativity and mass conservation
+1. The `Compartmental constraint` should be on by default
+2. verify that the equation is correct `S + I + R = 1002`
+
+### 5. Successful state constraint
+1. Create a new constraint by clicking `Add constraint`
+2. Set to `State constraint` and name it `Infected`
+ - set the target to `I` from the dropdown 
+ - set the upper bound to `750`
+ - leave start/end time to `[0, 100]`
+ - leave the weight to `1.0`
+3. Run validation
+4. Verify that service returns **true** boxes as infected should not exceed 750
+
+### 6. Failed state constraint
+1. Change the upper bound of `Infected` constraint `100`
+2. Run validation
+3. Verify that service returns **false** boxes as infected should exceed 100 between time `[0, 100]`
+4. Delete the constraint
+
+### 7. Successful monotonicity constraint
+1. Create a new constraint set to `Monotonicity constraint` and name it `Suceptible`
+ - set the target to `S` from the dropdown 
+ - set the direction to `decreasing`
+2. Run validation
+3. Verify that service returns **true** boxes as susceptible should be **decreasing** over time
+
+### 8. Failed monotonicity constraint
+1. Change the direction of `Suceptible` constraint to `increasing` 
+2. Run validation
+3. Verify that service returns **false** boxes as susceptible should be **decreasing** over time
+
+### 5. End test
+1. logout of the application