# BraggIntegrationSettings

Settings for Bragg spot integration

## Properties

Name | Type | Description | Notes
------------ | ------------- | ------------- | -------------
**integration_model** | [**IntegrationModel**](IntegrationModel.md) |  | [default to IntegrationModel.PROFILEGAUSSIAN]
**max_hkl** | **int** | How far the Bragg predictor walks the lattice: reflections with |h|,|k|,|l| above this are never predicted. An axis is truncated once a/d_min exceeds it, so a long axis - or a short one taken to high resolution - loses its outermost reflections. The cost grows as the cube (2n+1)^3 of candidates per image, which is why online keeps a fixed, predictable value instead of taking it from whichever crystal is mounted.  Omitting the field selects the default above; it is never interpreted as \"choose per crystal\". The offline tools (rugnux, viewer) do derive it from the refined cell when it is left unset there, but that is their own default and is not reachable through this API.  | [optional] [default to 100]

## Example

```python
from jfjoch_client.models.bragg_integration_settings import BraggIntegrationSettings

# TODO update the JSON string below
json = "{}"
# create an instance of BraggIntegrationSettings from a JSON string
bragg_integration_settings_instance = BraggIntegrationSettings.from_json(json)
# print the JSON string representation of the object
print(BraggIntegrationSettings.to_json())

# convert the object into a dict
bragg_integration_settings_dict = bragg_integration_settings_instance.to_dict()
# create an instance of BraggIntegrationSettings from a dict
bragg_integration_settings_from_dict = BraggIntegrationSettings.from_dict(bragg_integration_settings_dict)
```
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