Continuous distribution
Preview API
This endpoint is marked as a preview API. Preview APIs may be unstable within the preview period: they may change without notice. You must set the header API-Preview: opt-in to opt into using this endpoint.It's good to know how your data is distributed. One way to look at that is by creating a cumulative distribution function (CDF) of the data. This task makes a non-parametric-continuous-cumulative-distribution object from your dataset.
Parameters
composites(geoscience object reference)- A geoscience object reference that points to a one-dimensional continuous attribute inside a pointset or downhole-intervals object. This is your input data.
weights(geoscience object reference)- A geoscience object reference that points to a one-dimensional continuous attribute inside a pointset or downhole-intervals object. These are optional weights you can use to make a weighted distribution. If you don't want to use them, just omit the parameter.
tail_extrapolations(object, optional)- Optional tail extrapolations to put inside the distribution. If you don't want to use tail extrapolations, just omit the parameter.
-
{
"upper": {
"power_model": {
"power": 0.9, // A number between 0 and 1.
"min": 0, // Minimum extent of the tail. It must be less than the smallest value in your data.
},
},
"lower": {
"power_model": {
"power": 1.2, // A number greater than or equal to 1.
"max": 99, // Maximum extent of the tail. It must be greater than the biggest value in your data.
},
},
}
target(geoscience object reference)- A geoscience object reference that tells the task where to save the result. It makes a non-parametric-continuous-cumulative-distribution object here.
replace(boolean, optional)- If this is turned on, the task will overwrite the target, if it already exists. If this is turned off, the task will fail if the target already exists. Defaults to
false.
- If this is turned on, the task will overwrite the target, if it already exists. If this is turned off, the task will fail if the target already exists. Defaults to
Example
Request
requests.post(
"https://{hub}.api.seequent.com/compute/orgs/{org_id}/geostat/continuous-distribution",
headers={"Authorization": "Bearer {token}"},
json={
"parameters": {
"composites": {
"type": "geoscience-object-reference",
"object_reference": "https://{hub}.api.seequent.com/geoscience-object/orgs/{org_id}/workspaces/{workspace_id}/objects/path/my-pointset.json",
"object_element": [
{
"type": "element",
"path": "/locations/attributes/@name=my-data",
},
],
},
"weights": {
"type": "geoscience-object-reference",
"object_reference": "https://{hub}.api.seequent.com/geoscience-object/orgs/{org_id}/workspaces/{workspace_id}/objects/path/my-pointset.json",
"object_element": [
{
"type": "element",
"path": "/locations/attributes/@name=my-weights",
},
],
},
"target": {
"type": "geoscience-object-reference",
"object_reference": "https://{hub}.api.seequent.com/geoscience-object/orgs/{org_id}/workspaces/{workspace_id}/objects/path/my-distribution.json",
},
"tail_extrapolations": {
"upper": {
"power_model": {
"power": 1.1,
"min": 0,
},
},
"lower": {
"power_model": {
"power": 1.2,
"max": 99,
},
},
},
"replace": True,
},
},
)
Result
{
"message": "Success.",
"object_modified": {
"type": "geoscience-object-reference",
"object_reference": "https://{hub}.api.seequent.com/geoscience-object/orgs/{org_id}/workspaces/{workspace_id}/objects/path/my-distribution.json",
},
}
Tips
- The composites and weights can use the same object, but they don't have to.
