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UsageJourney

Params

name

A human readable description of the object.

uj_steps

A list of UsageJourneySteps.

Calculated attributes

duration

ExplainableQuantity in minute, representing the Duration of user journey.

Example value: 20 min

Depends directly on:

through the following calculations:

You can also visit the link to Duration of user journey’s full calculation graph.

nb_usage_journeys_in_parallel_per_usage_pattern

Dictionary with UsagePattern as keys and Usage pattern hourly nb of user journeys in parallel as values, in concurrent.

Example value: {
UsagePattern usage pattern (c14c3c): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [2, 1.33, 3, 0.333, 0.333, 1.33, 1, 2.33, 1.33, 2],
last 10 vals [3, 3, 2.67, 1, 2, 2, 1, 1.33, 2.33, 0.667],
}

Depends directly on:

through the following calculations:

You can also visit the link to usage pattern hourly nb of user journeys in parallel’s full calculation graph.

fabrication_impact_repartition_weights

Dictionary with UsagePattern as keys and Usage pattern fabrication weight in user journey impact repartition as values, in concurrent.

Example value: {
UsagePattern usage pattern (c14c3c): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [2, 1.33, 3, 0.333, 0.333, 1.33, 1, 2.33, 1.33, 2],
last 10 vals [3, 3, 2.67, 1, 2, 2, 1, 1.33, 2.33, 0.667],
}

Depends directly on:

through the following calculations:

You can also visit the link to usage pattern fabrication weight in user journey impact repartition’s full calculation graph.

fabrication_impact_repartition_weight_sum

Sum of user journey fabrication impact repartition weights in concurrent.

Example value: 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [2, 1.33, 3, 0.333, 0.333, 1.33, 1, 2.33, 1.33, 2],
last 10 vals [3, 3, 2.67, 1, 2, 2, 1, 1.33, 2.33, 0.667]

Depends directly on:

through the following calculations:

You can also visit the link to Sum of user journey fabrication impact repartition weights’s full calculation graph.

fabrication_impact_repartition

Dictionary with UsagePattern as keys and User journey fabrication impact attribution to usage pattern as values, in concurrent.

Example value: {
UsagePattern usage pattern (c14c3c): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
}

Depends directly on:

through the following calculations:

You can also visit the link to user journey fabrication impact attribution to usage pattern’s full calculation graph.

usage_impact_repartition_weights

Dictionary with UsagePattern as keys and Usage pattern usage weight in user journey impact repartition as values, in concurrent * gram / kilowatt_hour.

Example value: {
UsagePattern usage pattern (c14c3c): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in ·g/kWh:
first 10 vals [170, 113, 255, 28.3, 28.3, 113, 85, 198, 113, 170],
last 10 vals [255, 255, 227, 85, 170, 170, 85, 113, 198, 56.7],
}

Depends directly on:

through the following calculations:

You can also visit the link to usage pattern usage weight in user journey impact repartition’s full calculation graph.

usage_impact_repartition_weight_sum

Sum of user journey usage impact repartition weights in concurrent * gram / kilowatt_hour.

Example value: 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in ·g/kWh:
first 10 vals [170, 113, 255, 28.3, 28.3, 113, 85, 198, 113, 170],
last 10 vals [255, 255, 227, 85, 170, 170, 85, 113, 198, 56.7]

Depends directly on:

through the following calculations:

You can also visit the link to Sum of user journey usage impact repartition weights’s full calculation graph.

usage_impact_repartition

Dictionary with UsagePattern as keys and User journey usage impact attribution to usage pattern as values, in concurrent.

Example value: {
UsagePattern usage pattern (c14c3c): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
}

Depends directly on:

through the following calculations:

You can also visit the link to user journey usage impact attribution to usage pattern’s full calculation graph.