You're reading the documentation for a development version. For the latest released version, please have a look at v0.5.

cwepr.report module

Report facilities for cw-EPR data.

Being able to automatically create well-formatted reports using pre-defined templates opens an entirely new dimension in terms of comparing different datasets and workflows, besides presenting the results of the research.

This module provides functionality to create reports based on templates provided either by the user or by the package as such.

“Batteries included”: Templates contained in the package

The “batteries included” approach of Python itself is probably responsible to a great deal for the success of Python as a language. Similarly, the cwepr package tries to provide you with a sensible set of tools you need for your routine data analysis. Reports are no exception to that rule.

Thanks to being based on the ASpecD framework, the cwepr package comes bundled with a (growing) series of templates allowing you to create reports of datasets and alike. Thus, getting access to all information stored in a single dataset is as simple as calling a single reporter, and in context of recipe-driven data analysis, it is even simpler:

- kind: report
  type: LaTeXReporter
  properties:
    template: dataset.tex
    filename: report.tex
  compile: true

This would create a report of a dataset that is then stored in the file report.tex, using the template dataset.tex bundled with the cwepr (and ASpecD) package. As you even set compile to true, it would even compile the LaTeX report, including all figures generated during cooking the recipe and referenced from within the report. Hence, you end up in your current directory with both, a LaTeX file report.tex and a PDF file report.pdf.

For more details, including how to customise reports, have a look at the documentation of the aspecd.report module of the ASpecD framework.

Notes for developers

Note

The dataset can be given either as dataset in the properties of a recipe, or via the apply_to parameter. In the first case, the dataset can be accessed in the here implemented reporter class via self.dataset (and as an object), in the latter case indirectly via operating on the context-object self.context['dataset'] (and as a dict). The dataset has to be given explicitly while the dataset-context is applied implicitly. Therefore, here is applied the usage of the context that is a bit more complicated in operating but more intuitive to write in recipes.

Note

Still in active development and not fail-safe and easy to use.

Module documentation

class cwepr.report.ExperimentalDatasetLaTeXReporter(template='', filename='')

Bases: LaTeXReporter

Report implementation for cwepr module.

create(): Perform all methods to generate a report.

class cwepr.report.PowerSweepAnalysisReporter(template='', filename='')

Bases: LaTeXReporter

Create report for power sweep analysis.

create(): Perform all methods to generate a report.

Todo

Do not rely on dataset from recipe properties but use the dataset from apply_to that is imported into the context. Further deal with (meta)data in the context thus that those are easily usable in a template.

class cwepr.report.DokuwikiCaptionsReporter(template='', filename='')

Bases: Reporter

Write DokuWiki captions.

This reporter generates captions containing selected metadata of the measurement, that can be directly used in an DokuWiki used e.g. as an electronic lab notebook. Only the filename of the uploaded figure still has to be inserted.

create(): Perform all methods to create captions.

class cwepr.report.InfofileReporter

Bases: DokuwikiCaptionsReporter

Write infofile with metadata of the dataset.

As infofiles are written manually by humans, they are inherently sensitive to wrong content and incorrect data especially in the spectrometer’s parameters. As these parameters usually get also reported in the respective data file, they are also read from there and take precedence in the dataset’s metadata.

Therefore, to correct an infofile, it can be recreated after the dataset has been loaded and the metadata sanitised, using this very reporter.

Please note: In order to not write wrong parameters to the infofile this way, the InfofileReporter needs to be called immediately after the datasets have been imported, and before any other processing takes place that may alter the datasets’ metadata.

Examples

- kind: report
  type: InfofileReporter
  properties:
    filename: NewInfofile.info