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covid19-forecasts-orderly's Introduction

orderly

This is an orderly project. The directories are:

  • src: create new reports here
  • archive: versioned results of running your report
  • data: copies of data used in the reports

Each step of the analysis is an orderly task and corresponds to a directory on the src directory.

Description of tasks

  1. prepare_ecdc_data This task prepares the ECDC data in a format required by the modeling teams. Download the latest data from ECDC on Sunday evening and save it as a csv in the folder prepare_ecdc_data. Update the resources section in orderly.yml to reflect the name of the latest file. Then

    a <- orderly::orderly_run("prepare_ecdc_data")
    orderly::orderly_commit(a)
    

    This will generate two artefacts (outputs of a task are called artefacts in orderly). They are exactly the same files but one has the date in the file name - this file will be shared with the modeling groups, and the second file is called latest_model_input.rds. This is so that the downstream tasks can read the latest file without the need to manually update orderly.yml.

  2. process_individual_models By Monday afternoon, all modelling teams will produce outputs for the report in a prescribed format. These could be shared via DropBox for example i.e. the generation of model outputs is not part of the orderly workflow. Once these outputs are received, save them in a directory on your machine, and update the location in orderly_envir.yml. For example, this is the file on my machine:

    COVID19_INPUT_PATH: "/Users/sbhatia/OneDrive - Imperial College London/covid19-short-term-forecasts/model_outputs/"
    

    Note that the trailing slash in the directory name must be included. You can run the task as:

    a <- orderly::orderly_run("process_individual_models", parameter =
    list(week_ending = "2020-05-31"))
    orderly::orderly_commit(a)
    

    produce_performace_metrics Computes various performance metrics for each model.

    a <- orderly::orderly_run("produce_performace_metrics")
    orderly::orderly_commit(a)
    

    compute_model_weights Computes model weights using the metrics produced in the previous task.

  3. produce_ensemble_outputs This task creates an ensemble model.

    a <- orderly::orderly_run("produce_ensemble_outputs", parameters = list(week_ending = "2020-06-14"))
    orderly::orderly_commit(a)
    
  4. format_model_outputs Pretty formatting of model outputs for plugging into the final report.

    a <- orderly::orderly_run("format_model_outputs", use_draft = TRUE)
    orderly::orderly_commit(a)
    
  5. produce_visualisations As the name suggests, makes all the graphs needed for the report.

    a <- orderly::orderly_run("produce_visualisations")
    orderly::orderly_commit(a)
    
  6. produce_exec_summary Generates the summary that goes into the report. Run as all other tasks. It is the executive summary which is the summary of the new report. produce_summary task is redundant and can be ignored for now.

  7. produce_full_report Generate the full report.

covid19-forecasts-orderly's People

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kant avatar lvcooper avatar pnouvellet avatar sangeetabhatia03 avatar

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