Metadata-Version: 1.1
Name: bomber
Version: 0.0.5
Summary: Get data from the BoM in Python
Home-page: https://stash.csiro.au/projects/POH/repos/bomber
Author: Jess Robertson
Author-email: jesse.robertson@csiro.au
License: UNKNOWN
Description: # Read data from the Bureau of Meterology (BoM)
        
        author: Jess Robertson (@jesserobertson)
        
        The BoM, in it's wisdom, have made getting their geospatial data fairly difficult. This package aims to fix that
        
        To see this readme as an ipython notebook, check out https://github.com/jesserobertson/bomber/blob/master/examples/request_bom_data.ipynb
        
        ## Example usage
        
        Check out the measurement/observation datasets that we have available:
        
        ```python
        >>> import bomber
        >>> print(bomber.measurements.DATASETS)
        ```
        
        ```
        {'ndvi': ['ndviave'],
         'rainfall': ['totals'],
         'solar': ['solarave'],
         'temperature': ['maxave', 'minave'],
         'vprp': ['vprp09', 'vprp15']}
        ```
        
        Then we can get the bit that we want as a geotiff:
        
        ```python
        >>> geotiff = bomber.get_measurements(dataset='rainfall', year=2015, month=1)
        ```
        
        ```
        Downloaded data to rainfall_totals_month_2015010120150131.geotiff
        ```
        
        and then plot it using rasterio
        
        ```python
        >>> import rasterio, numpy
        >>> import matplotlib.pyplot as plt
        >>> with rasterio.drivers():
        ...     with rasterio.open(geotiff) as src:
        ...         fig = plt.figure(figsize=(11, 11))
        ...         data = numpy.ma.MaskedArray(
        ...             data=src.read(1), 
        ...             mask=src.read_masks(1))
        ...         ax = fig.gca()
        ...         ax.imshow(data, cmap=plt.get_cmap('coolwarm'))
        ...         ax.set_aspect('equal')
        ...         ax.set_axis_off()
        ...         ax.set_title('Rainfall, January 2015')
        ```
        
        ![Rainfall png](https://raw.githubusercontent.com/jesserobertson/bomber/master/examples/rainfall.png)
        
        You can also get the climatic average datasets as well:
        
        ```python
        >>> print(bomber.climate.DATASETS)
        ```
        
        ```
        {'decadal-rainfall': ['r'], 'decadal-temperature': ['mx', 'mn']}
        ```
        
        There's also a borked version for the climate regions but I'm too lazy to finish that one. Pull requests welcome!
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Plugins
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
