weiji14 / deepbedmap

Going beyond BEDMAP2 using a super resolution deep neural network. Also a convenient flat file data repository for high resolution bed elevation datasets around Antarctica.

Kia Ora 👋

I am a Geospatial Data Scientist from Malaysia 🇲🇾 working remotely and thinking about where to go next! My background is in Geography, with a particular interest in Earth Observation using satellites 🛰️, having done cool research on Antarctic ice dynamics during my PhD in Aotearoa/New Zealand 🥝. Specifically, I work on applying Deep Learning methods to Remote Sensing datasets, keeping busy on the leading edge of data-driven research in the Earth Sciences.

These are some of the hats I wear:

• ☁️ Machine Learning Engineer in the GeoAI team at Development Seed
• 🌏 Core Developer of PyGMT: A Pythonic Interface to the Generic Mapping Tools

I'm currently:

• 🦀 Learning Rust, and trying to get into the GeoRust ecosystem
• ☯️ Developing a Python package called zen3geo for building Earth Observation and geospatial data pipelines
• 🔭 Making open source contributions to the Pytorch ecosystem and Pangeo community, all in the PyData world!

Want to connect?

• 💻 I'm open to building partnerships with folks working on open geospatial tools, specifically with a Remote Sensing focus, so reach out!
• 📫 Track me on Mastodon as @weiji14, or find some other links on my website
• 👀 Be sure to check out my cool Computer Vision projects:
  • DeepBedMap - Super Resolution Generative Adversarial Network to resolve the bed topography of Antarctica
  • DeepIceDrain - Finding subglacial lakes using unsupervised DBSCAN clustering
  • DeepSlide - Self-supervised learning on SAR data for change detection, for the FDL2022 NASA Earth Science challenge
  • Crevasse detection and navigation - Done using Image Segmentation + Reinforcement Learning
  • S2S2Net - Sentinel-2 Super-Resolution Segmentation Network using a Vision Transformer model (SegFormer)

⚡ Fun fact: I was brought up trilingual, and am fluent in English, 中文 & Bahasa Melayu.

deepbedmap's Issues

Dependabot can't resolve your Python dependency files

Dependabot can't resolve your Python dependency files.

As a result, Dependabot couldn't update your dependencies.

The error Dependabot encountered was:

ERROR: ERROR: Could not find a version that matches matplotlib!=3.0.0,==3.1.1,>=2.0.0,>=3.3
Tried: 0.86, 0.86.1, 0.86.2, 0.91.0, 0.91.1, 1.0.1, 1.1.0, 1.1.1, 1.2.0, 1.2.1, 1.3.0, 1.3.1, 1.3.1, 1.3.1, 1.3.1, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2
Skipped pre-versions: 1.4.1rc1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3
There are incompatible versions in the resolved dependencies.
[pipenv.exceptions.ResolutionFailure]:   File "/usr/local/.pyenv/versions/3.7.10/lib/python3.7/site-packages/pipenv/utils.py", line 726, in resolve_deps
[pipenv.exceptions.ResolutionFailure]:       req_dir=req_dir,
[pipenv.exceptions.ResolutionFailure]:   File "/usr/local/.pyenv/versions/3.7.10/lib/python3.7/site-packages/pipenv/utils.py", line 480, in actually_resolve_deps
[pipenv.exceptions.ResolutionFailure]:       resolved_tree = resolver.resolve()
[pipenv.exceptions.ResolutionFailure]:   File "/usr/local/.pyenv/versions/3.7.10/lib/python3.7/site-packages/pipenv/utils.py", line 395, in resolve
[pipenv.exceptions.ResolutionFailure]:       raise ResolutionFailure(message=str(e))
[pipenv.exceptions.ResolutionFailure]:       pipenv.exceptions.ResolutionFailure: ERROR: ERROR: Could not find a version that matches matplotlib!=3.0.0,==3.1.1,>=2.0.0,>=3.3
[pipenv.exceptions.ResolutionFailure]:       Tried: 0.86, 0.86.1, 0.86.2, 0.91.0, 0.91.1, 1.0.1, 1.1.0, 1.1.1, 1.2.0, 1.2.1, 1.3.0, 1.3.1, 1.3.1, 1.3.1, 1.3.1, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2
[pipenv.exceptions.ResolutionFailure]:       Skipped pre-versions: 1.4.1rc1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3
[pipenv.exceptions.ResolutionFailure]: Warning: Your dependencies could not be resolved. You likely have a mismatch in your sub-dependencies.
  First try clearing your dependency cache with $ pipenv lock --clear, then try the original command again.
 Alternatively, you can use $ pipenv install --skip-lock to bypass this mechanism, then run $ pipenv graph to inspect the situation.
  Hint: try $ pipenv lock --pre if it is a pre-release dependency.
ERROR: ERROR: Could not find a version that matches matplotlib!=3.0.0,==3.1.1,>=2.0.0,>=3.3
Tried: 0.86, 0.86.1, 0.86.2, 0.91.0, 0.91.1, 1.0.1, 1.1.0, 1.1.1, 1.2.0, 1.2.1, 1.3.0, 1.3.1, 1.3.1, 1.3.1, 1.3.1, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.0, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.1, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.2, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.4.3, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.0, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.1, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.2, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 1.5.3, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.0, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.1, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.0.2, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.0, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.1, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.1.2, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.0, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.2, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.3, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.4, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 2.2.5, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.0, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.1, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.2, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.0.3, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.0, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.1, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.2, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.1.3, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.0, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.1, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.2.2, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.0, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.1, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.2, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.3, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.3.4, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.0, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.1, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2, 3.4.2
Skipped pre-versions: 1.4.1rc1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b1, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b2, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b3, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0b4, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc1, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.0.0rc2, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.1.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 2.2.0rc1, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.0.0rc2, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc1, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.1.0rc2, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc1, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.2.0rc3, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.3.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc1, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc2, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3, 3.4.0rc3
There are incompatible versions in the resolved dependencies.

['Traceback (most recent call last):\n', '  File "/usr/local/.pyenv/versions/3.7.10/lib/python3.7/site-packages/pipenv/utils.py", line 501, in create_spinner\n    yield sp\n', '  File "/usr/local/.pyenv/versions/3.7.10/lib/python3.7/site-packages/pipenv/utils.py", line 649, in venv_resolve_deps\n    c = resolve(cmd, sp)\n', '  File "/usr/local/.pyenv/versions/3.7.10/lib/python3.7/site-packages/pipenv/utils.py", line 539, in resolve\n    sys.exit(c.return_code)\n', 'SystemExit: 1\n']

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where to get istarxx.txt and 2007tx.txt files?

where to get the following files? there is no url provided

citekey: Bingham2018PIG
  folder: highres
  location: Pine Island Glacier
  resolution: nan
  doi:
    dataset: nan
    literature: "https://doi.org/10.1038/s41467-017-01597-y"
  files:
    -
      filename: 2007t1.txt
      url: nan
      sha256: 04bdbd3c8e814cbc8f0d324277e339a46cc90a8dc23434d11815a8966951e766
    -
      filename: 2007tr.txt
      url: nan
      sha256: 3858a1e58e17b2816920e1b309534cee0391f72a6a0aa68d57777b030e70e9a3
    -
      filename: 2010tr.txt
      url: nan
      sha256: 751ea56acc5271b3fb54893ed59e05ff485187a6fc5daaedf75946d730805b80
    -
      filename: istar08.txt
      url: nan
      sha256: ed03c64332e8d406371c74a66f3cd21fb3f78ee498ae8408c355879bb89eb13d
    -
      filename: istar18.txt
      url: nan
      sha256: 3e69d86f28e26810d29b0b9309090684dcb295c0dd39007fe9ee0d1285c57804
    -
      filename: istar15.txt
      url: nan
      sha256: 59c981e8c96f73f3a5bd98be6570e101848b4f67a12d98a577292e7bcf776b17
    -
      filename: istar13.txt
      url: nan
      sha256: f5bcf80c7ea5095e2eabf72b69a264bf36ed56af5cb67976f9428f560e5702a2
    -
      filename: istar17.txt
      url: nan
      sha256: f51a674dc27d6e0b99d199949a706ecf96ea807883c1901fea186efc799a36e8
    -
      filename: istar07.txt
      url: nan
      sha256: c81ec04290433f598ce4368e4aae088adeeabb546913edc44c54a5a5d7593e93

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Setup Continuous Integration

Perform automated builds and tests for each commit/PR to identify possible regressions. Try to replicate Binder's repo2docker build as much as possible.

TODO:

• Create a basic dockerfile (dd85dd2)
• Remove postBuild script (add to Dockerfile instead) (d11669d)
• Refactor/simplify installation related scripts (4ac7fab)
• Have a dependabot upgrade PR go through CI tests (7ba1422)
• Add badges to main README.md (4f41092)
• Setup a 'simple' unit testing framework that can work on jupyter notebooks directly (70d1eee)

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Provide bed elevation data about Pine island and bed_depth_below_WGS84_datum.csv?

Because I can't get the data from the original author. I am wondering if you could kindly send me the bed elevation data about Pine island and bed_depth_below_WGS84_datum.csv.

SCAR2020 Online DeepBedMap Poster

Hi 👋

If you've noticed my virtual poster at the SCAR2020 online conference (search for the abstract here), here's the place to find out more! There's a digital pdf copy of it below in case you need it (click on the image to download):

For more details, I recommend checking out some of these other content:

• Leong, W. J., & Horgan, H. J. (2020). DeepBedMap: Using a deep neural network to better resolve the bed topography of Antarctica. The Cryosphere Discussions, 2020, 1–27. https://doi.org/10.5194/tc-2020-74
• IGS Five Decades of Radioglaciolopy Symposium 2019 talk slides at https://gist.github.com/weiji14/dc992ce6751f7f6adf3d30f0e9c4d2e2
• EGU 2019 Poster at #133
• OBIA Research Group talk @ ZGIS, University of Salzburg, Apr 2019
• PhD Proposal talk @ Victoria University of Wellington, Dec 2018

Feel free to look around the repository, ask any questions or leave a comment below 😄

The poster itself was made Libreoffice Draw Version 6.1.5.2. The neural network figure was created using PlotNeuralNet (a personal fork actually), and the other figures/maps were created using PyGMT. Code to reproduce the figures are available at 'paper_figures.ipynb'.

Add Princess Elizabeth Land data

Add in bed elevation data at Princess Elizabeth Land, East Antarctica collected using the “Snow Eagle 601” aero geophysical platform; a BT-67 airplane operated by the Polar Research Institute of China for the Chinese National Antarctic Research Expedition (CHINARE) program

References:

• Cui, X., Jeofry, H., Greenbaum, J. S., Guo, J., Li, L., Lindzey, L. E., Habbal, F. A., Wei, W., Young, D. A., Ross, N., Morlighem, M., Jong, L. M., Roberts, J. L., Blankenship, D. D., Bo, S., & Siegert, M. J. (2020). Bed topography of Princess Elizabeth Land in East Antarctica [Preprint]. Cryosphere – Radar measurements. https://doi.org/10.5194/essd-2020-126
• ICECAP-2 consortium processed airborne ice thickness data from the Princess Elizabeth Land, East Antarctica at https://doi.org/10.5281/zenodo.3815063
• ICECAP-2 consortium bed elevation model for Princess Elizabeth Land, East Antarctica at https://doi.org/10.5281/zenodo.3666087

Feed ESRGAN with other relevant raster inputs

Aiming to train the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) with more than just bed elevation data. More bed elevation data is still helpful (see figure below), but by incorporating other relevant datasets, we might improve the results!

The (Gardner et al., 2018) reference below cites quite a few papers/datasets that appear to be relevant for our study.

References:

• Gardner, A. S., Moholdt, G., Scambos, T., Fahnstock, M., Ligtenberg, S., van den Broeke, M., & Nilsson, J. (2018). Increased West Antarctic and unchanged East Antarctic ice discharge over the last 7 years. The Cryosphere, 12(2), 521–547. https://doi.org/10.5194/tc-12-521-2018

To add:

• Surface DEM (see also #8)
• Ice Flow Velocity (see also #20)
• Snow accumulation (see also #146)
• Ice surface elevation change

Any other suggestions? Add to the comments!

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Add Pine Island Glacier dataset

Add in high resolution Pine Island Glacier dataset from British Antarctic Survey's Ice Sheet Stability Programme (iSTAR).

• Get iSTAR DELORES DEMs from Rob Bingham
• Process 2013-2014 iSTAR raw bed pick data to DEM (be0b77c)
• Process 2010 raw bed pick data to DEM (be0b77c)
• Tile many 250m resolution DEMs (38143f3)
• Retrain FSRCNN on just Pine Island Glacier dataset (325d272)
• Use iSTARt6 and 2007 DEMs as independent test set for model verification (TODO Migrate to new issue).

References:

• Bingham et al. 2018 paper
• https://istar-gis-features.data.bas.ac.uk/glacial/delores_dems/
• WAIS workshop presentation

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RMSE_test calculation does not sample points along groundtruth grid edges properly

Commit 054e295 in #151 highlighted a bug introduced in #149. Basically, pygmt.grdtrack differs in sampling points along the edges depending on whether we use a xarray.DataArray or NetCDF file grid input. See image below showing points sampling the 2007tx.nc grid, specifically the 2007t1.txt area.

Yes we do crop the 2007tx.nc grid by one pixel on the left, bottom, right and top (to make the image shape divisible by 4), but there's still some serious discrepancies.

Number of points:

• Actual total from 2007t1.txt + 2007tr.txt = 42995 points
• pygmt.grdtrack sample on NetCDF file = 38112 points
• pygmt.grdtrack sample on xr.DataArray = 37829 points

Strangely enough, running it on an xr.DataArray captures more points on the top and bottom (y-direction) whereas running it on a NetCDF file captures more points on the left and right (x-direction).

How to fix

Adjust data_prep.xyz_to_grid to not use tight bounds from data_prep.get_region. Maybe buffer the input bounds by 250m * 3 pixels (the mask we set when running pygmt.surface) before running blockmedian and surface. This should mean we get closer to the actual total of 42995 points regardless of whether we run it on an xarray.DataArray or NetCDF file

If not, then it might be a good idea to report this upstream to whoever wrote that wrapper for pygmt.grdtrack 😅

EGU2019 DeepBedMap Poster

Hi!

If you've noticed my poster at the EGU2019 conference (see also abstract), here is a digital pdf copy of it (click on the image to download):

For more details, I've also given two talks before on the topic:

• PhD Proposal talk @ Victoria University of Wellington, Dec 2018
• OBIA Research Group talk @ ZGIS, University of Salzburg, Apr 2019

Feel free to look around the repository, ask any questions or leave a comment below 😄

The poster itself was made using a trial 'PRO' version of Gravit Designer Version 2019-1.4. The centrepiece map was composed in QGIS 3.6 Noosa. I will be slowly releasing the code/scripts used to produce the figures via Pull Request #136.

Add google colaboratory badge to main README.md

Main goal

This is a relatively easy task on my TODO list for a while now. Basically I'd like to make the jupyter notebooks in this github repository more readily accessible to others without having to spend too much time installing all the dependencies.

Technically, there is a "Launch in Binder" badge on the main README.md that looks like (as of #91) but it can be a bit slow to load ...

A similar alternative is an "Open in Colab" badge, which allows people with a google account to open launch one of the public jupyter notebooks here directly on Google's servers. What I'd like is a badge that like next to the current Binder badge.

The markdown code to insert into the README.md file will look something like this:

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/weiji14/deepbedmap/]

References:

• https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb#scrollTo=Rmai0dD30XzL

Stretch goals

If you're really keen, I also need to make sure that the python libraries can actually run in Google Colaboratory! This is slightly more complicated, and will involve adapting the conda/pipenv installation instructions for Colaboratory. You'll need to add a jupyter notebook cell to the top of the data_prep.ipynb or srgan_train.ipynb notebooks and include the installation code.

One way to do it is to mimic what Chainer does in this repository, which is to use an install script:

!curl https://colab.chainer.org/install | sh -

Note that Google Colaboratory doesn't come with conda, so the GMT and CUDA binaries might be hard to install. You might only need to worry about GMT though, since CUDA should already on the servers.

Pip will be available in Google Colab, but there is no pipenv. You could maybe try running in a cell:

!pip install pipenv==2018.11.26

and then have pipenv install the libraries from the Pipfile/Pipfile.lock file. Alternatively, have it create a requirements.txt file and use pip to install the python libraries.

Update:

With #105 IPython 7.3.0 merged in, it might be easier to install some pip and conda dependencies with the new %pip and %conda magics. You'll need to have a look at the documentation, see ipython/ipython#11524.

References:

• https://pipenv.readthedocs.io/en/latest/advanced/
• https://chainer-colab-notebook.readthedocs.io/en/latest/

How do I start?

Create a fork of this repository (click on fork button on the top right), and make the relevant changes to the README.md. Feel free to leave a comment below saying you're tackling this. Mention what works and/or what doesn't, and I'll try to help you out. Once you're done, submit a pull request and I'll review it and merge it into the project!

References:

• https://opensource.guide/how-to-contribute/

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Switch to Super Resolution Generative Adversarial Network (SRGAN) architecture

Get more perceptually realistic bed elevations by going from a relatively basic Fast Super Resolution Convolutional Neural Network (FSRCNN) to a Super Resolution Generative Adversarial Network (SRGAN) architecture.

Rationale is that using a Generative Adversarial Network(GAN) backbone will drive the reconstruction towards a more 'natural' image manifold compared to a standard Convolutional Neural Network (CNN) that simply reduces the Mean Squared Error (MSE) loss.

References:

• Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

TODO:

• Build Generator Network (Deconvolutional) (9272ecc)
  • Several Residual blocks of Conv2D-BatchNorm-PReLU-Conv2D-BatchNorm-PReLU-Add
  • Upsampling using Pytorch-PixelShuffle/Tensorflow-depth_to_space
• Build Discriminator Network (Convolutional) (4828f8e)
  • Several Convolutional blocks of Conv2D-LeakyReLU-BatchNorm
  • Fully Connected/Dense Layers in the final few output layers
• Combine Generator and Discriminator together (bc60818)
  • Implement Perceptual Loss = Content Loss + Adversarial Loss
• Train the SRGAN! (fdb0464)
  • Figure out way to plot losses and metrics via tensorboard and/or livelossplot using pandas instead

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关于数据集

您好，bedmap3的数据更新了，请问您是否有增加数据集的想法呢

Add CReSIS Radar Depth Sounder (RDS) L2 data 2009-2017

Add in Radar Depth Sounder (RDS) data from the Center for
the Remote Sensing of Ice Sheets (CReSIS) team based at the University of Kansas and other places (see here).

Acknowledgements:

We acknowledge the use of data and/or data products from CReSIS generated with support from the University of Kansas, NASA Operation IceBridge grant NNX16AH54G, and NSF grant ACI-1443054.

See also:

• CReSIS OpenPolarServer (OPS) GeoPortal (click on Antarctic tab on top)
• Radar Depth Sounder data README
• IceBridge MCoRDS L2 Ice Thickness, Version 1
• High-Altitude Radar Measurements of Ice Thickness Over the Antarctic and Greenland Ice Sheets as a Part of Operation IceBridge

TODO:

• Get 2009-2017 Antarctic RDS data from https://data.cresis.ku.edu/data/rds/ (061242a)
• Process RDS data from csv to a gridded bed DEM (061242a, ebcb85a)
  • Note that only three (Basler, DC8, TO) were processed into DEM tiles
  • One of the datasets (P3) was only downloaded but not processed into a DEM
• Retrain Super Resolution model with this extra CReSIS RDS data (607557d)

WIP Building Community Guidelines

Inviting you to participate in DeepBedMap! It might seem intimidating, so I'll start by saying your help is not just more than welcome, it is essential for this project to work! This issue aims to establish community guidelines that will set the scene for you to contribute any data, code or even ideas to this repository.

Basics:

• Code of Conduct
• Contributing Guidelines
• Pull Request Templates
• Issue Templates
• README refresh

Create welcoming environment:

• Onboarding with Welcome and First Timers bot
• Ensure a11y/accessibility standards are followed (see e.g. jupyter-a11y)
• Automatic code quality checks (e.g. linters, code coverage, etc)
• Say Thanks to show appreciation

Resources:

• https://opensource.guide/

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Incorporate REMA surface DEM

Reference Elevation Model of Antarctica (REMA) provides the first, high resolution (8-meter) terrain map of nearly the entire continent. Adding this might help better resolve bed elevation since surface elevation does correlate with the bed elevation.

Acknowledgements:

DEMs provided by the Byrd Polar and Climate Research Center and the Polar Geospatial Center under NSF-OPP awards 1543501, 1810976, 1542736, 1559691, 1043681, 1541332, 0753663, 1548562, 1238993 and NASA award NNX10AN61G. Computer time provided through a Blue Waters Innovation Initiative. DEMs produced using data from DigitalGlobe, Inc.

See also:

• Howat, Ian; Morin, Paul; Porter, Claire; Noh, Myong-Jong, 2018, “The Reference Elevation Model of Antarctica”, https://doi.org/10.7910/DVN/SAIK8B, Harvard Dataverse, V1

TODO:

• Get full Antarctic Continent 200m mosaic in geotiff format (6a20d1c)
• Work out web-based (e.g. WMS) way to get REMA data (TODO check https://www.pgc.umn.edu/data/rema/ when ImageService is up!)
• Incorporate REMA data into the SRCNN model (f0e664a)

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Incorporate MEASURES Ice Flow Velocity

Making Earth System Data Records for Use in Research Environments (MEaSUREs) InSAR-Based Antarctica Ice Velocity Map, Version 2 provides a 450m resolution ice flow map of the Antarctic continent. Adding this would help the model determine the direction the ice is flowing be it onto bedrock bumps or away from them.

Notes:

• Will be using the whole continent version, i.e. MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2
• There are also other MEaSUREs ice flow products at https://nsidc.org/data/measures/aiv such as:
  • MEaSUREs InSAR-Based Ice Velocity Maps of Central Antarctica: 1997 and 2009, Version 1 (900m resolution)
  • MEaSUREs Annual Antarctic Ice Velocity Maps 2005-2016, Version 1 (1000m resolution)
  • MEaSUREs InSAR-Based Ice Velocity of the Amundsen Sea Embayment, Antarctica, Version 1 (450m resolution)

TODO:

• Get 450m resolution Ice Flow Velocity map in geotiff format from Quantarctica 3 (note original is in netcdf) (4be550f)
• Retrain Super Resolution model with this additional ice flow velocity map input (bb8433c)