Compare commits

...

1 Commits
main ... v2

Author SHA1 Message Date
FunctionsAPI
0f5f57eb91 Automatic push from FunctionsAPI 2025-06-10 16:29:15 +00:00
5 changed files with 3641 additions and 1 deletions

3424
Cargo.lock generated Normal file

File diff suppressed because it is too large Load Diff

12
Cargo.toml Normal file
View File

@ -0,0 +1,12 @@
[package]
edition = "2024"
name = "web"
version = "0.1.0"
[dependencies]
fathom-function = { git = "ssh://git@github.com/fathom-io/pipeline-calculations.git", branch = "main" }
pipeline-application = { git = "ssh://git@github.com/fathom-io/pipeline-calculations.git", branch = "main" }
serde = { version = "1.0.219", features = ["derive"] }
tokio = { version = "1.43.0", features = ["macros", "rt-multi-thread"] }
uom = { version = "0.36" }
uuid = { version = "1" }

View File

@ -1,2 +1,84 @@
# 911ad7c406284ad7ab4af65a7af4a46a # Dynamic segmentation function
The ILI Comparison module is a valuable tool designed to compare anomalies found in two
separate ILIs of the same pipeline. This module operates on an intelligent method that
incorporates user-defined criteria to ensure precision in the comparison process. The workflow
of this module begins with a girth-weld alignment step, which is crucial for identifying and
aligning the correct girth welds from the two in-line inspection reports. In this case, the
girth-weld alignment is applied to ILI reports conducted on 2011-06-01 and 2015-12-21, ensuring
accurate alignment between the inspections. Both ILIs were performed by Rosen using the MFL
(Magnetic Flux Leakage) technology.
Subsequently, the module matches metal loss corrosion anomalies based on the user's specified
criteria. This matching process evaluates the evolution of anomalies over a 5.5-year interval,
the time gap between the two ILIs. The output includes detailed reports that categorize the
results into matched features, matched anomalies, unmatched features, and unmatched anomalies.
In its final output, the module generates a comprehensive KPI Dashboard that showcases the
percentage of matched anomalies, providing users with an overview of the comparison results.
Furthermore, six charts visually illustrate the growth of matched anomalies over the 5.5-year
time interval between the two inspections. These visualizations provide valuable insights into
how anomalies have evolved and help users track changes in pipeline integrity over time.
In addition, the validated results from this module are used in the Local Growth Rate Module
for calculating the Final ACR and conducting future integrity assessments. The ILI Comparison
module, through the integration of historical and recent inspection data, offers an essential
framework for monitoring pipeline conditions and supporting maintenance decisions.
## Input
### Arguments
- `org_id`: as string which should be a valid `uuid` for the organization
- `project_id`: the id of the data project where the pipeline data is found
- `pipeline_id`: a `array` of string values representing a valid `uuid` for a pipeline
- `older_ili_id`: a `array` of string values representing a valid `uuid` for an ili report sequence
- `newer_ili_id`: a `array` of string values representing a valid `uuid` for an ili report sequence
- `weld_location_threshold`: a `float` value
- `feature_location_threshold`: a `float` value
- `upstream_girth_threshold`: a `float` value
- `orientation_threshold`: a `float` value
- `minimum_depth_growth_threshold`: a `float` value
- `minimum_length_growth_threshold`: a `float` value
- `surface_location_criteria`: an array of `string` each value should be one of
- `matching`
- `any`
- `target_minimum_match_rate`: a `float` value
## Creating the function on the platform
To create this function on the platform using the `cli` set up the port forwarding as shown in README.
Then run the following command to create the function.
```bash
cargo run functions create \
-f functions/ili_comparison \
-d "Compare two ILI reports" \
-i org_id=string \
-i project_id=string \
-i pipeline_id=array \
-i older_ili_id=array \
-i newer_ili_id=array \
-i weld_location_threshold=float \
-i upstream_girth_threshold=float \
-i feature_location_threshold=float \
-i orientation_threshold=float \
-i minimum_depth_growth_threshold=float \
-i minimum_length_growth_threshold=float \
-i surface_location_criteria=string \
-i target_minimum_match_rate=float
```
## Testing the function locally
You can run and test the function locally by running
```bash
cargo run
```
Then you can check it work with `curl` as follows
```bash
curl localhost:8080 -d $(jq '. | tojson' functions/ili_comparison/example_input.json)
```

21
example_input.json Normal file
View File

@ -0,0 +1,21 @@
{
"feature_location_threshold": "5",
"minimum_depth_growth_threshold": "0",
"minimum_length_growth_threshold": "-2",
"newer_ili_id": [
"d0dd7c6b-6c54-4149-b46c-5e5b033fe6dd"
],
"older_ili_id": [
"514167e0-f197-4edb-a382-f8db9b048613"
],
"org_id": "2cbfe270-d195-48ad-aed1-24145924635c",
"orientation_threshold": "15",
"pipeline_id": [
"01966d47-1d4c-7751-a1f1-0617caa3a00d"
],
"project_id": "680b61b0aedd6f9e639d8699",
"surface_location_criteria": "matching",
"target_minimum_match_rate": "25",
"upstream_girth_threshold": "0.05",
"weld_location_threshold": "9"
}

101
src/main.rs Normal file
View File

@ -0,0 +1,101 @@
use fathom_function::tracing;
use pipeline_application::{
application::{Application, MatchingCriteria, SurfaceLocationCriteria as SLC},
serialization::{
serialize_meter, serialize_millimeter, serialize_orientation_min, serialize_percent,
},
};
use uom::si::f64::{Angle, Length, Ratio};
use uuid::Uuid;
#[fathom_function::function]
async fn ili_comparison(input: Input) -> Result<Output, String> {
let app = Application::new_from_compile_env(input.org_id, input.project_id).unwrap();
for ((previous_id, newer_id), pipeline_id) in input
.older_ili_id
.into_iter()
.zip(input.newer_ili_id)
.zip(input.pipeline_id)
{
app.ili_comparison(pipeline_id, previous_id, newer_id, &input.criteria)
.await
.map_err(|err| {
tracing::error!(
%pipeline_id, %newer_id, %previous_id, ?err,
"Error running comparison algorithm"
);
format!("{err:?}")
})?;
}
Ok(Output {
status: "Success".to_owned(),
})
}
#[derive(Debug, serde::Serialize)]
struct Output {
status: String,
}
#[derive(Debug, serde::Deserialize)]
struct Input {
org_id: Uuid,
project_id: String,
pipeline_id: Vec<Uuid>,
older_ili_id: Vec<Uuid>,
newer_ili_id: Vec<Uuid>,
#[serde(flatten)]
criteria: Criteria,
}
#[derive(Debug, serde::Deserialize)]
struct Criteria {
#[serde(with = "serialize_meter")]
weld_location_threshold: Length,
#[serde(with = "serialize_meter")]
feature_location_threshold: Length,
#[serde(with = "serialize_meter")]
upstream_girth_threshold: Length,
#[serde(with = "serialize_orientation_min")]
orientation_threshold: Angle,
#[serde(with = "serialize_percent")]
minimum_depth_growth_threshold: Ratio,
#[serde(with = "serialize_millimeter")]
minimum_length_growth_threshold: Length,
surface_location_criteria: SurfaceLocationCriteria,
#[serde(with = "serialize_percent")]
target_minimum_match_rate: Ratio,
}
#[derive(Debug, Clone, Copy, serde::Deserialize)]
#[serde(rename_all = "snake_case")]
enum SurfaceLocationCriteria {
Matching,
Any,
}
impl From<SurfaceLocationCriteria> for SLC {
fn from(value: SurfaceLocationCriteria) -> Self {
match value {
SurfaceLocationCriteria::Matching => Self::Matching,
SurfaceLocationCriteria::Any => Self::Any,
}
}
}
impl From<&Criteria> for MatchingCriteria {
fn from(value: &Criteria) -> Self {
MatchingCriteria::default()
.with_weld_location_threshold(value.weld_location_threshold)
.with_feature_location_threshold(value.feature_location_threshold)
.with_upstream_girth_threshold(value.upstream_girth_threshold)
.with_orientation_threshold(value.orientation_threshold)
.with_minimum_depth_growth_threshold(value.minimum_depth_growth_threshold)
.with_minimum_length_growth_threshold(value.minimum_length_growth_threshold)
.with_surface_location_criteria(value.surface_location_criteria)
.with_target_minimum_match_rate(value.target_minimum_match_rate)
}
}