# Sample data sets
These files are used as sample data in Verde and are downloaded by `verde.datasets`
functions:
* `baja-bathymetry.csv.xz`: Bathymetry data from Baja California. This is the GMT
tutorial data `@tut_ship.xyz` stored in CSV format and `xz` compressed.
* `rio-magnetic.csv.xz`: Total-field magnetic anomaly data from the northwestern part of
an airborne survey of Rio de Janeiro, Brazil, conducted in 1978. Columns are
longitude, latitude, total field anomaly (nanoTesla), observation height above the
WGS84 ellipsoid (meters), type of flight line (LINE or TIE), and flight line number.
The anomaly is calculated with respect to the IGRF field at the center of the survey
area at 500 m altitude for the year 1978.3. This dataset was cropped from the original
survey, made available by the Geological Survey of Brazil (CPRM) through their [GEOSGB
portal](http://geosgb.cprm.gov.br/). See the original data for more processing
information.
* `california-gps.csv.xz`: GPS velocities (east, north, vertical) from the United States
West coast cut from EarthScope Plate Boundary Observatory data provided by UNAVCO
through the GAGE Facility with support from the National Science Foundation (NSF) and
National Aeronautics and Space Administration (NASA) under NSF Cooperative Agreement
No. EAR-1261833. Velocities are referenced to the North American tectonic plate
(NAM08).
* `texas-wind.csv`: Average for February 26 2018 of wind speed (in knots) and air
temperature (in C) for the state of Texas, USA. The original data was downloaded from
the [Iowa State University](https://mesonet.agron.iastate.edu/request/download.phtml)
archive.
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资源分类:Python库 所属语言:Python 资源全名:verde-1.6.0.tar.gz 资源来源:官方 安装方法:https://lanzao.blog.csdn.net/article/details/101784059
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Python库 | verde-1.6.0.tar.gz (139个子文件)
paper.bib 3KB
setup.cfg 38B
.coveragerc 82B
style.css 2KB
texas-wind.csv 17KB
.flake8 216B
.gitignore 227B
breadcrumbs.html 2KB
layout.html 1KB
MANIFEST.in 248B
Makefile 2KB
Makefile 2KB
CONTRIBUTING.md 13KB
MAINTENANCE.md 9KB
paper.md 4KB
CODE_OF_CONDUCT.md 3KB
AUTHORSHIP.md 3KB
README.md 2KB
AUTHORS.md 1KB
PKG-INFO 9KB
PKG-INFO 9KB
banner.png 627KB
readme-banner.png 401KB
test_setup_baja_bathymetry.png 25KB
test_setup_texas_wind.png 23KB
test_setup_california_gps.png 16KB
test_setup_rio_magnetic.png 15KB
favicon.png 7KB
verde-logo.png 6KB
coordinates.py 49KB
model_selection.py 34KB
base_classes.py 30KB
utils.py 23KB
blockreduce.py 21KB
spline.py 21KB
vector.py 18KB
test_base.py 16KB
test_blockreduce.py 11KB
sample_data.py 11KB
weights.py 11KB
test_coordinates.py 11KB
grid_coordinates.py 10KB
vectors.py 10KB
test_utils.py 10KB
utils.py 9KB
mask.py 9KB
model_evaluation.py 9KB
trend.py 9KB
model_selection.py 8KB
projections.py 8KB
test_spline.py 7KB
overview.py 6KB
projections.py 6KB
chain.py 6KB
test_vector.py 6KB
conf.py 5KB
scipygridder.py 5KB
test_model_selection.py 5KB
chain.py 5KB
test_mask.py 5KB
distances.py 5KB
io.py 4KB
test_projections.py 4KB
blockkfold.py 4KB
test_io.py 4KB
test_datasets.py 4KB
decimation.py 4KB
train_test_split.py 4KB
blockreduce_weights_mean.py 4KB
spline_weights.py 4KB
test_scipy.py 4KB
scipygridder.py 4KB
synthetic.py 4KB
vector_uncoupled.py 4KB
vector_trend.py 3KB
spline.py 3KB
spline_cv.py 3KB
trends.py 3KB
project_grid.py 3KB
test_chain.py 3KB
trend.py 3KB
blockreduce_weights.py 3KB
license_notice.py 3KB
least_squares.py 3KB
__init__.py 3KB
test_distances.py 2KB
setup.py 2KB
test_trend.py 2KB
distance_mask.py 2KB
convex_hull_mask.py 2KB
test_minimal.py 2KB
rio_magnetic.py 2KB
california_gps.py 2KB
blockreduce.py 2KB
texas-wind.py 1KB
baja_bathymetry.py 1KB
checkerboard.py 1KB
version.py 554B
__init__.py 552B
utils.py 525B
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