skgstat_uncertainty.chapters.data_manage#

The data manager chapter can be used to manage the data in the connected database. It includes a sub-application, that can sample existing datasets marked as ‘field’, to derive new ‘sample’ datasets. SciKit-GStat Uncertainty defines a number of dataset types:

  • ‘field’ - this is considered to be an exhaustive (random) field, with covering quantities.

  • ‘sample’ - a sample of a field. This is used throughout the application for geostatistics.

  • ‘auxiliary’ - covering, additional information associated to a ‘sample’; used for external drift kriging.

Note

This chapter can be run standalone, or as a part of another streamlit application. Note that the chapter may terminte or restart the current run on user interaction.

In the demo application Uncertain geostatistics (https://geostat.hydrocode.de/uncertain) it is used to let registered users upload new data and mutate existing. In the standalone chapter Learning Geostatistics (https://geostat.hydrocode.de/learn) you can see several rendering functions in action to provide a nice data selection experience for the user, without the ability to upload or change data.

Warning

Any user entering the Data Manager with all action (including edit, upload and sample) are able to mutate the data in the connected database.

Module Contents#

Functions#

dataset_grid(→ None)

Create a grid of all existing datasets. When clicked, the dataset is loaded

button_panel(→ None)

Creates a panel for various buttons to manage datasets. Actions are not

action_view(→ None)

Page for viewing all details about a dataset. This page is based on streamlit

upload_view(→ None)

Page for uploading new datasets. The page uses the upload handler component.

edit_view(→ None)

Page for editing an existing dataset. This page relies on the streamlit session

delete_view(→ None)

Page for handling dataset deletions. This page relies on the streamlit session

sample_view(→ None)

Page for resample field data. This page relies on the streamlit session state,

auxiliary_upload_view(→ None)

Page view to upload auxiliary data for exsiting field or sample data.

sample_dense_data(dataset, api)

Streamlit component for re-sampling field data and store the result as a new

list_datasets(api[, container])

Dropdown component for all datasets found in the database. On selection,

edit_dataset(→ None)

Wrapper to integrate the edit_dataset component. This wrapper adds controls

main_app(api)

Data management chapter.

run([data_path, db_name])

Attributes#

ACT

skgstat_uncertainty.chapters.data_manage.ACT#
skgstat_uncertainty.chapters.data_manage.dataset_grid(api: skgstat_uncertainty.api.API) → None#

Create a grid of all existing datasets. When clicked, the dataset is loaded for viewing. In viewing mode, the dataset can be edited or deleted. The grid does also include a button for creating new datasets

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

Note

This comonent terminates the streamlit application until the user has selected a dataset. State manangement is done using a state variable called action, which is set to view. Then a data_id is available for the selected dataset.

skgstat_uncertainty.chapters.data_manage.button_panel(can_resample: bool = False, can_upload: bool = False, container=st) → None#

Creates a panel for various buttons to manage datasets. Actions are not applied, but indicated in the streamlit session. This compnent does restart the streamlit application, in case the user took action. The selected action is stored in the action state variable.

Parameters:

  • can_resample (bool) – If False (default), the resampling tool for field data types is disabled and the user can’t resample datasets.

  • can_upload (bool) – If ``False``(default), the upload dialog is disabled. This will prevent users from uploading new datasets into the database.

skgstat_uncertainty.chapters.data_manage.action_view(api: skgstat_uncertainty.api.API) → None#

Page for viewing all details about a dataset. This page is based on streamlit session state as the data_id has to be present in the state in order to load the corresponding dataset from the database. The view page includes a button panel for manipulating the dataset, along with license, origin information, a description and a preview of the dataset.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.upload_view(api: skgstat_uncertainty.api.API) → None#

Page for uploading new datasets. The page uses the upload handler component.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

Note

This component uses the streamlit session state to refer to the newly uploaded dataset and restarts the streamlit application on user interaction

skgstat_uncertainty.chapters.data_manage.edit_view(api: skgstat_uncertainty.api.API) → None#

Page for editing an existing dataset. This page relies on the streamlit session state, as the data_id has to be present in order to load the corresponding dataset from the database.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.delete_view(api: skgstat_uncertainty.api.API) → None#

Page for handling dataset deletions. This page relies on the streamlit session state, as the data_id has to be present in oder to laod the corresponding dataset from the database. The deletion process has to be acknowlegded by the user at least once.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.sample_view(api: skgstat_uncertainty.api.API) → None#

Page for resample field data. This page relies on the streamlit session state, as it needs the data_id to be present in order to load the corresponding field from the database. It uses the sample_dense_data component to load the actual user interactions.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.auxiliary_upload_view(api: skgstat_uncertainty.api.API) → None#

Page view to upload auxiliary data for exsiting field or sample data. Auxiliary data has to be of field type and can be used for external drift kriging. This page relies on the streamlit session state, as a data_id has to be present in order to load the corresponding dataset from the database.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.sample_dense_data(dataset: skgstat_uncertainty.models.DataUpload, api: skgstat_uncertainty.api.API)#

Streamlit component for re-sampling field data and store the result as a new sample data type to the database. The component can terminate or restart the the streamlit application due to user interaction. The component can re-sample the field on a regular grid by specifying the grid resolution, grid cell size or the number of desired sampling points. Alternatively, a specified number of sampling points can be selected randomly from the domain. The component also includes a preview and a dataset creation dialog.

Parameters:

  • dataset (DataUpload) – The base dataset, which should be used for resampling

  • api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.list_datasets(api: skgstat_uncertainty.api.API, container=st)#

Dropdown component for all datasets found in the database. On selection, the component will preview some basic information about the dataset.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.edit_dataset(dataset: skgstat_uncertainty.models.DataUpload, api: skgstat_uncertainty.api.API, container=st) → None#

Wrapper to integrate the edit_dataset component. This wrapper adds controls and manages the state management to indicate the user interaction to other components of the application.

Parameters:

Note

This wrapper terminates and restarts the streamlit application on user interaction.

skgstat_uncertainty.chapters.data_manage.main_app(api: skgstat_uncertainty.api.API)#

Data management chapter. This streamlit application can be run on its own or embedded into another application. It will preview all datasets in the connected database as a default action and then manage all operations like view, edit or delete on user interaction. Please note that this application does not include access management. If the application is loaded, the user will be allowed to operate the underlying database. To manage user interactions, the application shares several streamlit session state variables with all child components. action is used to indicate the user interaction and data_id the affected dataset.

Parameters:

api (skgstat_uncertainty.api.API) – Connected instance of the SciKit-GStat Python API to interact with the backend.

skgstat_uncertainty.chapters.data_manage.run(data_path=None, db_name='data.db')#