Settings¶
Here’s a list of settings specific to covid-ht, for Django settings reffer here.
DATA_PRIVACY_MODE¶
Default: True
Enables / Disables the Data Privacy Mode: data is only shown to registered users (see Data Privacy).
CHTUID¶
Default: cHT00
Covid-HT Unique IDentifier - a case-sensitive 5 characters alphanumeric string that will identify the instance in network (see Networking).
CHTUID_USE_IN_CLASSIFICATION¶
Default: True
Whether to use the CHTUID as a categorical variable in the Internal Classifier. Switching requires perfoming inference on the classifier (see Data Model).
EXAMPLE_DATA_V2¶
Default: True
Whether generate example data on migrations when creating the database and alert the existance in the HTML front-end (see Example Data).
EXAMPLE_DATA_SIZE¶
Default: 1000
Size of the dataset generated in the example data - either by migrations or the example_data django-admin command (see Example Data).
CLINICAL_FIELDS_MIN_NUM_SUBMIT¶
Default: 6
Minimum number of clinical fields (main or conversion) required for the Classification service. (see Internal Classifiers).
DATA_INPUT_FORM_FIELDS¶
Default: [ <list_of_all_fields> ]
Fields to be used in the data input form in the HTML front-end. Should be adjusted according to the output of your equipment.
DATA_CLASSIFICATION_FORM_FIELDS¶
Default: __all__
Fields to be used in the data classification form in the HTML front-end (home).
GRAPHING¶
Default: True
Enable graph generation for the classification service (see Graphing).
GRAPHING_FIELDS¶
Default: ["rbc", "wbc", "hgb", "lymp"]
Fields to be used in the graph generation.
GRAPHING_DATASET¶
Default: True
Whether to show or not the dataset in the generated graphs.
GRAPHING_COND_DEC_FUNCTION¶
Default: True
Whether to show or not the Conditional Decision Function of the internal classifier in the generated graphs.
Warning
This is computational expensive, see Graphing.
GRAPHING_MESH_STEPS¶
Default: 200
Amount of steps to be used when generating the mesh in which the Conditional Decision Function will be evaluated. Lower values will decrease the computational cost of including the Conditional Decision Function in the graphs at the expense of precision.
