notebooks/Slippery Future Citations & References.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Github workspace  [Table of Sanity](https://github.com/Freshwater-Initiative/SkagitLandslideHazards/issues/8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Citation management location"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [Slippery Future Zotero Group Library](https://www.zotero.org/groups/2324777/slippery_future) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Netcdf file format attribute template for the project. This must sync with references in Zotero. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def netcdf_set_SlipperyFuture_attributes(data):\n",
    "    \n",
    "    data.attrs['institution']='University of Washington; Seattle City Light'\n",
    "    data.attrs['title']='Skagit DHSVM Model (2019)'\n",
    "    data.attrs['subtitle']='historic'\n",
    "    data.attrs['summary']='Abstract'\n",
    "    data.attrs['references']=''\n",
    "    data.attrs['license']=''\n",
    "    data.attrs['comment']='Slippery Future'\n",
    "    data.attrs['source']='https://www.hydroshare.org/resource/01b486f301864828ba2cd9ab7ac77c4e/data/contents/DHSVM/output_SCLlandslide_historic/Map.Soil.TableDepth.asc'\n",
    "    #keywords (ACDD)\n",
    "    #missing_value (CF)\n",
    "    return data\n",
    "\n",
    "def netcdf_set_SCL_attributes(data):\n",
    "    \n",
    "    data.attrs['time_coverage_start']=''\n",
    "    data.attrs['time_coverage_end']=''\n",
    "    data.attrs['geospatial_lat_max']=''\n",
    "    data.attrs['geospatial_lat_min']=''\n",
    "    data.attrs['geospatial_lon_max']=''\n",
    "    data.attrs['geospatial_lon_min']=''\n",
    "    #grid_mapping_name (CF)  Spatial Reference: coordinate reference system\n",
    "    #Spatial Reference: Coordinate String, Coordinate String Type, Datum\n",
    "    #attributes for grid mapping variable (CF)\n",
    "    return data\n",
    "\n",
    "def netcdf_set_GoodellCreek_attributes(data):\n",
    "    \n",
    "    data.attrs['time_coverage_start']=''\n",
    "    data.attrs['time_coverage_end']=''\n",
    "    data.attrs['geospatial_lat_max']=''\n",
    "    data.attrs['geospatial_lat_min']=''\n",
    "    data.attrs['geospatial_lon_max']=''\n",
    "    data.attrs['geospatial_lon_min']=''\n",
    "    #grid_mapping_name (CF)  Spatial Reference: coordinate reference system\n",
    "    #Spatial Reference: Coordinate String, Coordinate String Type, Datum\n",
    "    #attributes for grid mapping variable (CF)\n",
    "    return data\n",
    "\n",
    "def netcdf_set_modelvar_attributes(data):\n",
    "    \n",
    "    data.attrs['subtitle']='historic'\n",
    "    data.attrs['units']='m'\n",
    "    data.attrs['standard_name'] = 'depth' # this is a CF standard name 'Depth is the vertical distance below the surface.'\n",
    "    data.attrs['long_name']='depth to water table from surface elevation'\n",
    "    data.attrs['creator_name']=''\n",
    "    data.attrs['creator_url']=''\n",
    "    data.attrs['creator_email']=''\n",
    "    data.attrs['contributor_name']=''\n",
    "    data.attrs['time_coverage_start']=''\n",
    "    data.attrs['time_coverage_end']=''\n",
    "    data.attrs['geospatial_lat_max']=''\n",
    "    data.attrs['geospatial_lat_min']=''\n",
    "    data.attrs['geospatial_lon_max']=''\n",
    "    data.attrs['geospatial_lon_min']=''\n",
    "    data.attrs['summary']='Abstract'\n",
    "    data.attrs['references']=''\n",
    "    data.attrs['license']=''\n",
    "    data.attrs['comment']='Slippery Future'\n",
    "    data.attrs['source']='https://www.hydroshare.org/resource/01b486f301864828ba2cd9ab7ac77c4e/data/contents/DHSVM/output_SCLlandslide_historic/Map.Soil.TableDepth.asc'\n",
    "    #keywords (ACDD)\n",
    "    #missing_value (CF)\n",
    "    #grid_mapping_name (CF)  Spatial Reference: coordinate reference system\n",
    "    #Spatial Reference: Coordinate String, Coordinate String Type, Datum\n",
    "    #attributes for grid mapping variable (CF)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Goodell Creek subset coordinates on the SCL grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "min_lon = 1150\n",
    "min_lat = 1125\n",
    "max_lon = 1450\n",
    "max_lat = 1475"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Citations for software and versions used\n",
    "\n",
    "Notebook 1. observedlandslides_data+landlab+netcdf_20200806.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# xarray\n",
    "\n",
    "[How should I cite xarray?](http://xarray.pydata.org/en/stable/faq.html)\n",
    "If you are using xarray and would like to cite it in academic publication, we would certainly appreciate it. We recommend two citations.\n",
    "\n",
    "At a minimum, we recommend citing the xarray overview journal article, published in the Journal of Open Research Software.\n",
    "\n",
    "Hoyer, S. & Hamman, J., (2017). xarray: N-D labeled Arrays and Datasets in Python. Journal of Open Research Software. 5(1), p.10. DOI: http://doi.org/10.5334/jors.148\n",
    "\n",
    "Here’s an example of a BibTeX entry:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "@article{hoyer2017xarray,\n",
    "  title     = {xarray: {N-D} labeled arrays and datasets in {Python}},\n",
    "  author    = {Hoyer, S. and J. Hamman},\n",
    "  journal   = {Journal of Open Research Software},\n",
    "  volume    = {5},\n",
    "  number    = {1},\n",
    "  year      = {2017},\n",
    "  publisher = {Ubiquity Press},\n",
    "  doi       = {10.5334/jors.148},\n",
    "  url       = {http://doi.org/10.5334/jors.148}\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.16.0'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xarray\n",
    "xarray.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the badge for pydata/xarray: v0.16.0\n",
    "    \n",
    "[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3940662.svg)](https://doi.org/10.5281/zenodo.3940662)\n",
    "\n",
    "Stephan Hoyer, Joe Hamman, Maximilian Roos, Deepak Cherian, Clark Fitzgerald, Keisuke Fujii, … johnomotani. (2020, July 11). pydata/xarray: v0.16.0 (Version v0.16.0). Zenodo. http://doi.org/10.5281/zenodo.3940662"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Software used \n",
    "\n",
    "Landlab kernel on CyberGIS for Water"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Today's date: 2020-07-24\n"
     ]
    }
   ],
   "source": [
    "from datetime import date\n",
    "today = date.today()\n",
    "print(\"Today's date:\", today)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "environ({'CPU_GUARANTEE': '0.1', 'MINICONDA_VERSION': '4.7.10', 'LANGUAGE': 'en_US.UTF-8', 'HOSTNAME': '7c78693c5fda', 'JUPYTERHUB_HOST': '', 'JUPYTERHUB_USER': 'christinabandaragoda', 'SHLVL': '0', 'XDG_CACHE_HOME': '/home/jovyan/.cache/', 'HS_AUTH_SOURCE': 'spawner', 'HOME': '/home/jovyan', 'CONDA_VERSION': '4.7.12', 'JUPYTERHUB_API_URL': 'http://5f6c39602f3f:8081/hub/api', 'JUPYTERHUB_OAUTH_CALLBACK_URL': '/user/christinabandaragoda/oauth_callback', 'FC': 'gfortran', 'NB_USER': 'jovyan', 'XSEDE_KEY_PATH': '/home/cybergis/.xsede-gateway-attributes-apikey-cjw', 'JUPYTERHUB_CLIENT_ID': 'jupyterhub-user-christinabandaragoda', 'FC_EXE': 'gfortran', 'PATH': '/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin', 'JUPYTERHUB_ACTIVITY_URL': 'http://5f6c39602f3f:8081/hub/api/users/christinabandaragoda/activity', 'MEM_LIMIT': '8589934592', 'NB_GID': '100', 'LANG': 'en_US.UTF-8', 'FC_ENV': 'gfortran-6-docker', 'DEBIAN_FRONTEND': 'noninteractive', 'CPU_LIMIT': '2.0', 'SHELL': '/bin/bash', 'F_MASTER': '/tmp/summa', 'JUPYTERHUB_ADMIN_ACCESS': '1', 'CONDA_DIR': '/opt/conda', 'JUPYTERHUB_SERVICE_PREFIX': '/user/christinabandaragoda/', 'HS_AUTH': '[{\"access_token\": \"ed0v3gqY7rANZuqfXaTfvhZrPTl0Wk\", \"refresh_token\": \"rXRXhOn4HGqKf8djGgfcQBXm0YJKzI\", \"oauth_user\": {\"username\": \"ChristinaBandaragoda\", \"email\": \"cband@uw.edu\", \"first_name\": \"Christina\", \"id\": 259, \"last_name\": \"Bandaragoda\", \"title\": \"Senior Research Scientist\", \"organization\": \"University of Washington\"}, \"scope\": \"read write\", \"expires_in\": 2592000, \"token_type\": \"Bearer\"}, \"gTxS2TgfSpOFfwzkB38Gg6KNWwb35HNbTh04RwK2\"]', 'LC_ALL': 'en_US.UTF-8', 'PROJ_LIB': '/opt/conda/share/proj', 'PWD': '/home/jovyan', 'JUPYTERHUB_API_TOKEN': 'a1ba1c0fe6174161acf40b8a7becf3f8', 'JUPYTERHUB_BASE_URL': '/', 'JUPYTERHUB_SERVER_NAME': '', 'MEM_GUARANTEE': '268435456', 'NB_UID': '1000', 'JPY_API_TOKEN': 'a1ba1c0fe6174161acf40b8a7becf3f8', 'GDAL_DATA': '/opt/conda/share/gdal', 'MINICONDA_MD5': '1c945f2b3335c7b2b15130b1b2dc5cf4', 'KERNEL_LAUNCH_TIMEOUT': '40', 'JPY_PARENT_PID': '6', 'TERM': 'xterm-color', 'CLICOLOR': '1', 'PAGER': 'cat', 'GIT_PAGER': 'cat', 'MPLBACKEND': 'module://ipykernel.pylab.backend_inline'})\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "print(os.environ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "affine==2.3.0\r\n",
      "alembic==1.3.0\r\n",
      "appdirs==1.4.4\r\n",
      "async-generator==1.10\r\n",
      "attrs==19.3.0\r\n",
      "backcall==0.1.0\r\n",
      "beautifulsoup4==4.8.1\r\n",
      "bleach==3.1.0\r\n",
      "blinker==1.4\r\n",
      "bokeh==1.3.4\r\n",
      "certifi==2020.4.5.1\r\n",
      "certipy==0.1.3\r\n",
      "cffi==1.13.2\r\n",
      "chardet==3.0.4\r\n",
      "Click==7.0\r\n",
      "click-plugins==1.1.1\r\n",
      "cligj==0.5.0\r\n",
      "cloudpickle==1.2.2\r\n",
      "conda==4.7.12\r\n",
      "conda-package-handling==1.6.0\r\n",
      "cryptography==2.8\r\n",
      "cycler==0.10.0\r\n",
      "Cython==0.29.14\r\n",
      "cytoolz==0.10.1\r\n",
      "dask==2.2.0\r\n",
      "decorator==4.4.1\r\n",
      "defusedxml==0.6.0\r\n",
      "dill==0.3.1.1\r\n",
      "distributed==2.5.2\r\n",
      "entrypoints==0.3\r\n",
      "fastcache==1.1.0\r\n",
      "fsspec==0.5.2\r\n",
      "future==0.18.2\r\n",
      "GDAL==2.4.2\r\n",
      "geojson==2.5.0\r\n",
      "gmpy2==2.1.0b1\r\n",
      "h5py==2.9.0\r\n",
      "HeapDict==1.0.1\r\n",
      "hs-restclient==1.3.6\r\n",
      "html5lib==0.9999999\r\n",
      "idna==2.8\r\n",
      "imageio==2.6.1\r\n",
      "importlib-metadata==0.23\r\n",
      "ipykernel==5.1.3\r\n",
      "ipython==7.9.0\r\n",
      "ipython-genutils==0.2.0\r\n",
      "ipywidgets==7.5.1\r\n",
      "isodate==0.6.0\r\n",
      "jedi==0.15.1\r\n",
      "Jinja2==2.10.3\r\n",
      "joblib==0.14.0\r\n",
      "json5==0.8.5\r\n",
      "jsonschema==3.1.1\r\n",
      "jupyter-client==5.3.3\r\n",
      "jupyter-contrib-core==0.3.3\r\n",
      "jupyter-contrib-nbextensions==0.2.6\r\n",
      "jupyter-core==4.5.0\r\n",
      "jupyter-highlight-selected-word==0.2.0\r\n",
      "jupyter-latex-envs==1.4.6\r\n",
      "jupyter-nbextensions-configurator==0.4.1\r\n",
      "jupyterhub==1.0.0\r\n",
      "jupyterlab==1.2.1\r\n",
      "jupyterlab-server==1.0.6\r\n",
      "kiwisolver==1.1.0\r\n",
      "llvmlite==0.29.0\r\n",
      "locket==0.2.0\r\n",
      "lxml==4.5.2\r\n",
      "Mako==1.1.0\r\n",
      "MarkupSafe==1.1.1\r\n",
      "matplotlib==3.1.2\r\n",
      "mistune==0.8.4\r\n",
      "more-itertools==7.2.0\r\n",
      "mpmath==1.1.0\r\n",
      "msgpack==0.6.2\r\n",
      "nbconvert==5.6.1\r\n",
      "nbfetch==0.0.3\r\n",
      "nbformat==4.4.0\r\n",
      "networkx==2.4\r\n",
      "notebook==6.0.0\r\n",
      "numba==0.45.1\r\n",
      "numexpr==2.6.9\r\n",
      "numpy==1.17.3\r\n",
      "oauthlib==3.0.1\r\n",
      "olefile==0.46\r\n",
      "packaging==19.2\r\n",
      "pamela==1.0.0\r\n",
      "pandas==0.25.3\r\n",
      "pandocfilters==1.4.2\r\n",
      "parso==0.5.1\r\n",
      "partd==1.0.0\r\n",
      "patsy==0.5.1\r\n",
      "pexpect==4.7.0\r\n",
      "pickleshare==0.7.5\r\n",
      "Pillow==6.2.1\r\n",
      "prometheus-client==0.7.1\r\n",
      "prompt-toolkit==2.0.10\r\n",
      "protobuf==3.9.2\r\n",
      "psutil==5.6.5\r\n",
      "ptyprocess==0.6.0\r\n",
      "pycosat==0.6.3\r\n",
      "pycparser==2.19\r\n",
      "pycurl==7.43.0.3\r\n",
      "Pygments==2.4.2\r\n",
      "PyJWT==1.7.1\r\n",
      "pyOpenSSL==19.0.0\r\n",
      "pyparsing==2.4.4\r\n",
      "pyrsistent==0.15.5\r\n",
      "PySocks==1.7.1\r\n",
      "python-dateutil==2.8.1\r\n",
      "python-editor==1.0.4\r\n",
      "pytz==2019.3\r\n",
      "PyWavelets==1.1.1\r\n",
      "PyYAML==5.1.2\r\n",
      "pyzmq==18.1.0\r\n",
      "rasterio==1.1.5\r\n",
      "requests==2.22.0\r\n",
      "requests-oauthlib==1.3.0\r\n",
      "requests-toolbelt==0.9.1\r\n",
      "ruamel-yaml==0.15.71\r\n",
      "scikit-image==0.15.0\r\n",
      "scikit-learn==0.21.3\r\n",
      "scipy==1.3.1\r\n",
      "seaborn==0.9.0\r\n",
      "Send2Trash==1.5.0\r\n",
      "six==1.13.0\r\n",
      "snuggs==1.4.7\r\n",
      "sortedcontainers==2.1.0\r\n",
      "soupsieve==1.9.4\r\n",
      "SQLAlchemy==1.3.10\r\n",
      "statsmodels==0.10.1\r\n",
      "suds-jurko==0.6\r\n",
      "sympy==1.4\r\n",
      "tables==3.6.1\r\n",
      "tblib==1.4.0\r\n",
      "terminado==0.8.2\r\n",
      "testpath==0.4.4\r\n",
      "toolz==0.10.0\r\n",
      "tornado==6.0.3\r\n",
      "tqdm==4.37.0\r\n",
      "traitlets==4.3.3\r\n",
      "ulmo==0.8.5\r\n",
      "urllib3==1.25.6\r\n",
      "vincent==0.4.4\r\n",
      "wcwidth==0.1.7\r\n",
      "webencodings==0.5.1\r\n",
      "widgetsnbextension==3.5.1\r\n",
      "xlrd==1.2.0\r\n",
      "zict==1.0.0\r\n",
      "zipp==0.6.0\r\n"
     ]
    }
   ],
   "source": [
    "!pip freeze xarray"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# References"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gariano, S.L., Guzzetti, F., 2016. Landslides in a changing climate. Earth-Science Reviews 162, 227–252. https://doi.org/10.1016/j.earscirev.2016.08.011\n",
    "\n",
    "Hobley, D.E.J., Adams, J.M., Nudurupati, S.S., Hutton, E.W.H., Gasparini, N.M., Istanbulluoglu, E., Tucker, G.E., 2017. Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics. Earth Surface Dynamics 5, 21–46. https://doi.org/10.5194/esurf-5-21-2017\n",
    "\n",
    "Hoyer, S., Hamman, J., 2017. xarray: N-D labeled Arrays and Datasets in Python. Journal of Open Research Software 5, 10. https://doi.org/10.5334/jors.148\n",
    "IEEE Xplore Abstract Record, n.d.\n",
    "\n",
    "Stephan Hoyer, Joe Hamman, Maximilian Roos, Deepak Cherian, Clark Fitzgerald, Keisuke Fujii, Fabien Maussion, keewis, crusaderky, Alex Kleeman, Spencer Clark, Thomas Kluyver, James Munroe, Tom Nicholas, Zac Hatfield-Dodds, Mathias Hauser, Ryan Abernathey, MaximilianR, Phillip J. Wolfram, Julia Signell, Yohai Bar Sinai, Jonathan J. Helmus, Gregory Gundersen, Markel, Pete Cable, Benoit Bovy, Andrew Barna, Gerardo Rivera, Matthew Rocklin, johnomotani, 2020. pydata/xarray: v0.16.0. Zenodo. https://doi.org/10.5281/zenodo.3940662\n",
    "\n",
    "Strauch, R., Istanbulluoglu, E., Nudurupati, S.S., Bandaragoda, C., Gasparini, N.M., Tucker, G.E., 2018. A hydroclimatological approach to predicting regional landslide probability using Landlab. Earth Surface Dynamics 6, 49–75. https://doi.org/10.5194/esurf-6-49-2018\n",
    "Submitted Version, n.d.\n"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# [References - Bibtex](SlipperyFuture-ZenodoExported-20200724.bib)\n",
    "Click here and you will have the option to import to your Zotero account. \n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "LANDLAB",
   "language": "python",
   "name": "landlab"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}