Links

Observation Create

https://api.sigopt.com/v1/experiments/EXPERIMENT_ID/observations
Creates a new Observation. Every observation reports on a set of parameters which can come from a Suggestion or manually specified Assignments.
Request Method: POST

Parameters

Name
Type
Required?
Description
assignments
N
Manually specify values that the parameters held during this trial. You must specify exactly one value for each parameter in the experiment. Prefer using suggestion.
failed
boolean
N
A boolean indicating whether this observation failed for some reason. SigOpt takes this into consideration when optimizing. It is invalid for both failed to be true, and any of value, value_stddev, or values to be present. The default value is false.
metadata
Metadata
N
Optional user-provided object. See Using Metadata for more information.
suggestion
string
N
The id of the Suggestion you are reporting on. Preferred over assignments.
values
N
An array of Metric Evaluation objects. For experiments with more than one Metric, you must use this instead of value and value_stddev.

Deprecated Parameters

These parameters should no longer be used because there are better alternatives.
Name
Type
Required?
Description
value
float
N
The observed metric value from this trial.
value_stddev
float
N
The standard deviation in value that was observed in this trial.

Response

Observation object.

Examples

Create an Observation

Python
Bash
Java
observation = conn.experiments(EXPERIMENT_ID).observations().create(
suggestion="1",
values=[
dict(
name="accuracy",
value=0.95
),
dict(
name="loss",
value=123.45
)
]
)
accuracy=0.95
loss=123.45
OBSERVATION=`curl -s -X POST https://api.sigopt.com/v1/experiments/EXPERIMENT_ID/observations -u "$SIGOPT_API_TOKEN": \
-H 'Content-Type: application/json' \
-d "{\"suggestion\":\"1\",\"values\":[{\"name\":\"accuracy\",\"value\":$accuracy},{\"name\":\"loss\",\"value\":$loss}]}"`
Observation observation = new Experiment(EXPERIMENT_ID).observations().create()
.data(
new Observation.Builder()
.suggestion("1")
.values(java.util.Arrays.asList(
new Value.Builder()
.name("accuracy")
.value(0.95)
.build(),
new Value.Builder()
.name("loss")
.value(123.45)
.build()
))
.build()
)
.call();
Response

Create an Observation with custom Assignments

Python
Bash
Java
observation = conn.experiments(EXPERIMENT_ID).observations().create(
assignments=dict(
degree=2,
gamma=3.6,
kernel="rbf"
),
values=[
dict(
name="Accuracy",
value=1
)
]
)
OBSERVATION=`curl -s -X POST https://api.sigopt.com/v1/experiments/EXPERIMENT_ID/observations -u "$SIGOPT_API_TOKEN": \
-H 'Content-Type: application/json' \
-d "{\"assignments\":{\"degree\":2,\"gamma"\:3.6,\"kernel\":\"rbf\"},\"values\":[{\"name\":\"Accuracy\",\"value\":1}]}"`
Observation observation = new Experiment(EXPERIMENT_ID).observations().create()
.data(
new Observation.Builder()
.assignments(new Assignments.Builder()
.set("degree", 2)
.set("gamma", 3.6)
.set("kernel", "rbf")
.build())
.values(java.util.Arrays.asList(
new MetricEvaluation.Builder()
.name("Accuracy")
.value(1)
.build()
))
.build()
)
.call();
Response

Create a Failed Observation

Python
Bash
Java
observation = conn.experiments(EXPERIMENT_ID).observations().create(
failed=True,
suggestion="2"
)
OBSERVATION=`curl -s -X POST https://api.sigopt.com/v1/experiments/EXPERIMENT_ID/observations -u "$SIGOPT_API_TOKEN": \
-H 'Content-Type: application/json' \
-d "{\"suggestion\":\"2\",\"failed\":true}"`
Observation observation = new Experiment(EXPERIMENT_ID).observations().create()
.data(
new Observation.Builder()
.failed(true)
.suggestion("2")
.build()
)
.call();
Response

Create an Observation with Metadata

Python
Bash
Java
observation = conn.experiments(EXPERIMENT_ID).observations().create(
metadata=dict(
estimated_training_time_s=302
),
suggestion="1",
values=[
dict(
name="Accuracy",
value=1,
value_stddev=0.1
)
]
)
OBSERVATION=`curl -s -X POST https://api.sigopt.com/v1/experiments/EXPERIMENT_ID/observations -u "$SIGOPT_API_TOKEN": \
-H 'Content-Type: application/json' \
-d "{\"suggestion\":\"1\",\"values\":[{\"name\":\"Accuracy\",\"value\":1,\"value_stddev\":0.1}],\"metadata\":{\"estimated_training_time_s\":302}}"`
Observation observation = new Experiment(EXPERIMENT_ID).observations().create()
.data(
new Observation.Builder()
.metadata(new Metadata.Builder()
.set("estimated_training_time_s", 302)
.build())
.suggestion("1")
.values(java.util.Arrays.asList(
new MetricEvaluation.Builder()
.name("Accuracy")
.value(1)
.valueStddev(0.1)
.build()
))
.build()
)
.call();
Response