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        "author": "Jess Robertson",
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            "Development Status :: 3 - Alpha",
            "Environment :: Plugins",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: Other/Proprietary License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Scientific/Engineering :: Physics",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# Read data from the Bureau of Meterology (BoM)\n\nauthor: Jess Robertson (@jesserobertson)\n\nThe BoM, in it's wisdom, have made getting their geospatial data fairly difficult. This package aims to fix that\n\nTo see this readme as an ipython notebook, check out https://github.com/jesserobertson/bomber/blob/master/examples/request_bom_data.ipynb\n\n## Example usage\n\nCheck out the measurement/observation datasets that we have available:\n\n```python\n>>> import bomber\n>>> print(bomber.measurements.DATASETS)\n```\n\n```\n{'ndvi': ['ndviave'],\n 'rainfall': ['totals'],\n 'solar': ['solarave'],\n 'temperature': ['maxave', 'minave'],\n 'vprp': ['vprp09', 'vprp15']}\n```\n\nThen we can get the bit that we want as a geotiff:\n\n```python\n>>> geotiff = bomber.get_measurements(dataset='rainfall', year=2015, month=1)\n```\n\n```\nDownloaded data to rainfall_totals_month_2015010120150131.geotiff\n```\n\nand then plot it using rasterio\n\n```python\n>>> import rasterio, numpy\n>>> import matplotlib.pyplot as plt\n>>> with rasterio.drivers():\n...     with rasterio.open(geotiff) as src:\n...         fig = plt.figure(figsize=(11, 11))\n...         data = numpy.ma.MaskedArray(\n...             data=src.read(1), \n...             mask=src.read_masks(1))\n...         ax = fig.gca()\n...         ax.imshow(data, cmap=plt.get_cmap('coolwarm'))\n...         ax.set_aspect('equal')\n...         ax.set_axis_off()\n...         ax.set_title('Rainfall, January 2015')\n```\n\n![Rainfall png](https://raw.githubusercontent.com/jesserobertson/bomber/master/examples/rainfall.png)\n\nYou can also get the climatic average datasets as well:\n\n```python\n>>> print(bomber.climate.DATASETS)\n```\n\n```\n{'decadal-rainfall': ['r'], 'decadal-temperature': ['mx', 'mn']}\n```\n\nThere's also a borked version for the climate regions but I'm too lazy to finish that one. Pull requests welcome!",
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