science-research

Is your feature request related to a problem? Please describe.
I have some very large files (100s of GB) that compress pretty well, and JLD2 supports compression, but I can't use this package's wonderful saving features together with that.

Describe the solution you'd like
It would be nice to be able to pass through the compress=true option to whatever function is used to actually

Describe the bug
LocalOtsuThreshold should return a binary mask as np.ndarray, like its "sibling" OtsuThreshold

1. We should not apply np_to_pil before returning, but threshold_to_mask (like OtsuThreshold)
2. The docstrings of LocalOtsuThreshold and local_otsu_threshold are different, while they should be the same.
3. Type hints need to be fixed as well to reflect the new

Objective

Provide a German translation of the strings defined in headers/text.h.

Rationale

Users, especially in educative contexts, might want to use the software in their native language.

Is your feature request related to a problem? Please describe.
It can be necessary to pull out the instrument sampling rate from data. In principle this should be easy but data gaps, instrument turn on/off, etc. can potentially frustrate this determination.

Describe the solution you'd like
It may be necessary for calc_res in utils.time to support different averaging methods for da

This request is to make $(OUTPUT_PATH) behave more like the other labels and variables such that it is accessible without the timestamped sub directories appended to it when the spec is run. Making the timestamped sub directories accessible in another token in the workflow spec and meta files would be a useful side effect of this change.

Release v22.04.01 changed the default model spec and the glossy term on models compared to previous FPSci releases. See the release notes for snippets to fix the issue.

Contributions are welcome, let's fill this list with awesome open science resources, books, courses, events, research data, etc ... 📚 🔬 🔓 🔍 🎉

The instructions and configurations listed in hn2016_falwa/examples/ to run the sample codes are specific to conda users. It would be great to include instructions for pip/virtualenv users as well, as many scientists are actually using that.