ASpecD Version 0.6.0

ASpecD is a Python framework for handling spectroscopic data focussing on reproducibility. In short: Each and every processing step applied to your data will be recorded and can be traced back, and additionally, for each representation of your data (e.g., figures, tables) you can easily follow how the data shown have been processed and where they originate from.

What is even better: Actual data processing and analysis no longer requires programming skills, but is as simple as writing a text file summarising all the steps you want to have been performed on your dataset(s) in an organised way.

Released 2021-11-05

New features

• Reports

  • Templates for reporting information contained in datasets come bundled with ASpecD.
  • Context contains templates_dir allowing to include sub-templates.
  • New class TxtReporter for plain text reports

• Tasks/Recipe-driven data analysis

  • YAML representation of recipe and tasks via aspecd.tasks.Recipe.to_yaml and aspecd.tasks.Task.to_yaml
  • Figure labels can be set in plotters; otherwise a default label will be set and can be accessed from within reports.

• Utils

  • change_working_dir can be used as context manager to temporarily change the working directory.

• General

  • aspecd.utils.ToDictMixin.to_dict can optionally remove keys with empty values.
  • to_dict() method in aspecd.processing.ProcessingStep, aspecd.analysis.AnalysisStep, aspecd.annotation.Annotation, aspecd.plotting.Plotter, aspecd.table.Table, aspecd.report.Reporter, aspecd.model.Model

• Models

  • Axes quantities and units can be explicitly set on model creation.

Changes

• Dataset labels do not contain source path.
• Recipe dataset_source and output directories are no longer converted to absolute paths.
• More complete recipe history for tasks, including more of their properties
• Recipe-driven data analysis: Figures get added to recipe with default label if no label is provided.
• aspecd.processing.Noise: explicit noise amplitude can be given.
• Model can add label to created dataset.
• ModelTask adds result label as id to result.
• Plotter: Default figure size changed to (6., 4.) inch

Fixes

• aspecd.tasks.Task.to_yaml serialises numpy arrays
• Datasets from foreign packages are correctly listed in recipe history
• aspecd.utils.copy_keys_between_dicts properly traverses
• aspecd.utils.Yaml handles numpy.double
• Recipe-driven data analysis: automatically generated figure filenames get added to recipe figure record
• Models work now correctly when based on a dataset
• aspecd.model.FamilyOfCurves sets correct values for additional axis
• aspecd.processing.Differentiation works correctly for 2D datasets
• aspecd.processing.Noise: normalisation works with >1D datasets
• aspecd.plotting.SinglePlotter2DStacked: ylabel is set to third axis if offset = 0