VERSION: 1.0.0-rc.161
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@@ -7,7 +7,7 @@ Name | Type | Description | Notes
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------------ | ------------- | ------------- | -------------
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**polarization_corr** | **bool** | Apply polarization correction for azimuthal integration (polarization factor must be configured in dataset settings) | [default to True]
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**solid_angle_corr** | **bool** | Apply solid angle correction for azimuthal integration | [default to True]
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**high_q_recip_a** | **float** | |
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**high_q_recip_a** | **float** | Upper q limit of the azimuthal integration [1/Angstrom]. Optional: if omitted, the integration (and the adaptive spot detection that shares these q bins) extends to the highest q the detector reaches. | [optional]
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**low_q_recip_a** | **float** | |
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**q_spacing** | **float** | |
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**azimuthal_bins** | **int** | Numer of azimuthal (phi) bins; 1 = standard 1D azimuthal integration | [optional] [default to 1]
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@@ -0,0 +1,30 @@
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# BraggIntegrationSettings
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Settings for Bragg spot integration
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## Properties
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Name | Type | Description | Notes
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------------ | ------------- | ------------- | -------------
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**integration_model** | [**IntegrationModel**](IntegrationModel.md) | | [default to IntegrationModel.PROFILEGAUSSIAN]
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## Example
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```python
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from jfjoch_client.models.bragg_integration_settings import BraggIntegrationSettings
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# TODO update the JSON string below
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json = "{}"
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# create an instance of BraggIntegrationSettings from a JSON string
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bragg_integration_settings_instance = BraggIntegrationSettings.from_json(json)
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# print the JSON string representation of the object
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print(BraggIntegrationSettings.to_json())
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# convert the object into a dict
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bragg_integration_settings_dict = bragg_integration_settings_instance.to_dict()
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# create an instance of BraggIntegrationSettings from a dict
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bragg_integration_settings_from_dict = BraggIntegrationSettings.from_dict(bragg_integration_settings_dict)
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```
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[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
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@@ -1,16 +0,0 @@
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# ColorScale
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## Enum
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* `INDIGO` (value: `'Indigo'`)
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* `VIRIDIS` (value: `'Viridis'`)
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* `BLACKWHITE` (value: `'BlackWhite'`)
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* `HEAT` (value: `'Heat'`)
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[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
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@@ -1,36 +0,0 @@
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# GridScanResultImagesInner
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## Properties
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Name | Type | Description | Notes
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------------ | ------------- | ------------- | -------------
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**efficiency** | **float** | |
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**number** | **int** | Detector image number for a given cell |
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**bkg** | **float** | Background estimate | [optional]
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**spots** | **int** | Spot count | [optional]
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**index** | **int** | Indexing solution | [optional]
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**mos** | **float** | Mosaicity estimate | [optional]
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**b** | **float** | B-Factor estimate | [optional]
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**uc** | [**UnitCell**](UnitCell.md) | | [optional]
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## Example
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```python
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from jfjoch_client.models.grid_scan_result_images_inner import GridScanResultImagesInner
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# TODO update the JSON string below
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json = "{}"
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# create an instance of GridScanResultImagesInner from a JSON string
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grid_scan_result_images_inner_instance = GridScanResultImagesInner.from_json(json)
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# print the JSON string representation of the object
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print(GridScanResultImagesInner.to_json())
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# convert the object into a dict
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grid_scan_result_images_inner_dict = grid_scan_result_images_inner_instance.to_dict()
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# create an instance of GridScanResultImagesInner from a dict
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grid_scan_result_images_inner_from_dict = GridScanResultImagesInner.from_dict(grid_scan_result_images_inner_dict)
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```
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[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
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@@ -0,0 +1,15 @@
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# IntegrationModel
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Bragg spot integration model. ProfileGaussian - profile fit with a measured-width Gaussian (Kabsch-style), the default; more accurate intensities than box summation. ProfileEmpirical - profile fit with a per-resolution-shell empirical profile learned from strong spots. BoxSum - classical uniform box summation minus a ring-mean background; the simpler, faster fallback.
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## Enum
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* `PROFILEGAUSSIAN` (value: `'ProfileGaussian'`)
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* `PROFILEEMPIRICAL` (value: `'ProfileEmpirical'`)
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* `BOXSUM` (value: `'BoxSum'`)
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[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
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@@ -1,77 +0,0 @@
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# jfjoch_client.JfjochBrokerApi
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All URIs are relative to *http://localhost:5232*
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Method | HTTP request | Description
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------------- | ------------- | -------------
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[**config_zeromq_metadata_put**](JfjochBrokerApi.md#config_zeromq_metadata_put) | **PUT** /config/zeromq_metadata | Set ZeroMQ metadata settings
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# **config_zeromq_metadata_put**
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> config_zeromq_metadata_put(zeromq_metadata_settings=zeromq_metadata_settings)
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Set ZeroMQ metadata settings
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Jungfraujoch can generate metadata message stream on ZeroMQ PUB socket. This stream covers all images. Here settings of the socket can be adjusted. While the data structure contains also socket_address, this cannot be changed via HTTP and is ignore in PUT request.
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### Example
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```python
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import jfjoch_client
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from jfjoch_client.models.zeromq_metadata_settings import ZeromqMetadataSettings
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from jfjoch_client.rest import ApiException
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from pprint import pprint
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# Defining the host is optional and defaults to http://localhost:5232
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# See configuration.py for a list of all supported configuration parameters.
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configuration = jfjoch_client.Configuration(
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host = "http://localhost:5232"
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)
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# Enter a context with an instance of the API client
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with jfjoch_client.ApiClient(configuration) as api_client:
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# Create an instance of the API class
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api_instance = jfjoch_client.JfjochBrokerApi(api_client)
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zeromq_metadata_settings = jfjoch_client.ZeromqMetadataSettings() # ZeromqMetadataSettings | (optional)
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try:
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# Set ZeroMQ metadata settings
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api_instance.config_zeromq_metadata_put(zeromq_metadata_settings=zeromq_metadata_settings)
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except Exception as e:
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print("Exception when calling JfjochBrokerApi->config_zeromq_metadata_put: %s\n" % e)
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```
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### Parameters
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Name | Type | Description | Notes
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------------- | ------------- | ------------- | -------------
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**zeromq_metadata_settings** | [**ZeromqMetadataSettings**](ZeromqMetadataSettings.md)| | [optional]
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### Return type
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void (empty response body)
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### Authorization
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No authorization required
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### HTTP request headers
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- **Content-Type**: application/json
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- **Accept**: text/plain, application/json
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### HTTP response details
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| Status code | Description | Response headers |
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|-------------|-------------|------------------|
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**200** | Everything OK | - |
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**400** | Input parsing or validation error | - |
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**500** | Error within Jungfraujoch code - see output message. | - |
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[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)
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@@ -11,7 +11,7 @@ Name | Type | Description | Notes
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**photon_count_threshold** | **int** | |
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**min_pix_per_spot** | **int** | |
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**max_pix_per_spot** | **int** | |
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**high_resolution_limit** | **float** | High resolution limit for spot finding [Angstrom] |
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**high_resolution_limit** | **float** | High resolution limit for spot finding [Angstrom]. Optional: if omitted, spot finding extends as far as the detector reaches, i.e. the detection is not clipped in resolution. | [optional]
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**low_resolution_limit** | **float** | Low resolution limit for spot finding [Angstrom] |
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**high_resolution_limit_for_spot_count_low_res** | **float** | High resolution threshold to consider spot \"low resolution\" [Angstrom] |
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**quick_integration** | **bool** | Quick integration of Bragg spots in diffraction images. If enabled it will likely reduce performance of Jungfraujoch for datasets with a very high indexing rate. (experimental feature) | [default to False]
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