# Copyright (c) TorchGeo Contributors. All rights reserved.
# Licensed under the MIT License.
"""Dataset for the Global Biodiversity Information Facility."""
import functools
import glob
import os
import geopandas as gpd
import matplotlib.pyplot as plt
import pandas as pd
import rasterio
import torch
from geopandas import GeoDataFrame
from matplotlib.figure import Figure
from .errors import DatasetNotFoundError
from .geo import GeoDataset
from .utils import GeoSlice, Path, Sample, disambiguate_timestamp
[docs]
class GBIF(GeoDataset):
"""Dataset for the Global Biodiversity Information Facility.
`GBIF <https://www.gbif.org/>`__, the Global Biodiversity Information Facility,
is an international network and data infrastructure funded by the world's
governments and aimed at providing anyone, anywhere, open access to data about
all types of life on Earth.
This dataset is intended for use with GBIF's
`occurrence records <https://www.gbif.org/occurrence/search>`_. It may or may not
work for other GBIF `datasets <https://www.gbif.org/dataset/search>`_. Data for a
particular species or region of interest can be downloaded from the above link.
If you use a GBIF dataset in your research, please cite it according to:
* https://www.gbif.org/citation-guidelines
.. versionadded:: 0.3
"""
[docs]
def __init__(self, root: Path = 'data') -> None:
"""Initialize a new Dataset instance.
Args:
root: root directory where dataset can be found
Raises:
DatasetNotFoundError: If dataset is not found.
"""
super().__init__()
self.root = root
files = glob.glob(os.path.join(root, '**.csv'))
if not files:
raise DatasetNotFoundError(self)
# Read tab-delimited CSV file
usecols = ['decimalLatitude', 'decimalLongitude', 'day', 'month', 'year']
dtype = {'day': str, 'month': str, 'year': str}
df = pd.read_table(files[0], usecols=usecols, dtype=dtype) # type: ignore[arg-type]
df = df[df['decimalLatitude'].notna()]
df = df[df['decimalLongitude'].notna()]
df['day'] = df['day'].str.zfill(2)
df['month'] = df['month'].str.zfill(2)
date = df['day'] + ' ' + df['month'] + ' ' + df['year']
# Convert from pandas DataFrame to geopandas GeoDataFrame
func = functools.partial(disambiguate_timestamp, format='%d %m %Y')
index = pd.IntervalIndex.from_tuples(
date.apply(func).to_list(), closed='both', name='datetime'
)
geometry = gpd.points_from_xy(df['decimalLongitude'], df['decimalLatitude'])
self.index = GeoDataFrame(index=index, geometry=geometry, crs='EPSG:4326')
[docs]
def __getitem__(self, index: GeoSlice) -> Sample:
"""Retrieve input, target, and/or metadata indexed by spatiotemporal slice.
Args:
index: [xmin:xmax:xres, ymin:ymax:yres, tmin:tmax:tres] coordinates to index.
Returns:
Sample of input, target, and/or metadata at that index.
Raises:
IndexError: If *index* is not found in the dataset.
"""
x, y, t = self._disambiguate_slice(index)
interval = pd.Interval(t.start, t.stop)
df = self.index.iloc[self.index.index.overlaps(interval)]
df = df.iloc[:: t.step]
df = df.cx[x.start : x.stop, y.start : y.stop]
if df.empty:
raise IndexError(
f'index: {index} not found in dataset with bounds: {self.bounds}'
)
keypoints = torch.tensor(df.get_coordinates().values, dtype=torch.float32)
transform = rasterio.transform.from_origin(x.start, y.stop, x.step, y.step)
sample = {
'bounds': self._slice_to_tensor(index),
'keypoints': keypoints,
'transform': torch.tensor(transform),
}
return sample
[docs]
def plot(
self, sample: Sample, show_titles: bool = True, suptitle: str | None = None
) -> Figure:
"""Plot a sample from the dataset.
Args:
sample: a sample return by :meth:`__getitem__`
show_titles: flag indicating whether to show titles above each panel
suptitle: optional suptitle to use for Figure
Returns:
a matplotlib Figure with the rendered sample
.. versionadded:: 0.8
"""
# Create figure and axis - using regular matplotlib axes
fig, ax = plt.subplots(figsize=(10, 8))
ax.grid(ls='--')
# Extract coordinates
keypoints = sample['keypoints']
x = keypoints[:, 0]
y = keypoints[:, 1]
# Plot the points
ax.scatter(x, y)
# Set labels
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
# Add titles if requested
if show_titles:
ax.set_title('GBIF Occurrence Locations by Date')
if suptitle is not None:
fig.suptitle(suptitle)
fig.tight_layout()
return fig
