U Cv fq4@sddlmZddlZddlZddlZddlmZddlm Z ddl m Z ddl m Z ddlmZddlmZe Zd ZGd d d eZd d ZdddZdS)) annotationsN) BackendArray)CachingFileManager)SerializableLock)indexing) DataArray) is_scalarz~The kind of indexing operation you are trying to do is not valid on rasterio files. Try to load your data with ds.load()first.c@sPeZdZdZdddZeddZeddd d Zd d Zd dZ ddZ dS)RasterioArrayWrapperz)A wrapper around rasterio dataset objectsNcCsddlm}||_||_|}|dk r4||f|}||_|j|j|jf|_ |j }t t ||dksrtdt |d|_dS)Nr WarpedVRTz$All bands should have the same dtype) rasterio.vrtr managerlockacquire vrt_paramscountheightwidth_shapedtypesnpallasarray ValueErrordtype_dtype)selfr rrr riodsrr=/tmp/pip-unpacked-wheel-h316xyqg/xarray/backends/rasterio_.py__init__s  zRasterioArrayWrapper.__init__cCs|jSN)rrrrrr.szRasterioArrayWrapper.dtypeztuple[int, ...])returncCs|jSr!)rr"rrrshape2szRasterioArrayWrapper.shapec Cst|dkstd|d}g}t|trN||jd\}}}t|||}t|d }t|t rx| tdg}g}t t |dd|jddD]\} \} } t| tr| | \}}}| tdd|nPt| r| d|  | }| d}n(t| t| d}}| | || ||fqt|dtjrxt|dtjrxtj|dd|dd<|t|t|t|fS)aGet indexer for rasterio array. Parameters ---------- key : tuple of int Returns ------- band_key: an indexer for the 1st dimension window: two tuples. Each consists of (start, stop). squeeze_axis: axes to be squeezed np_ind: indexer for loaded numpy array See Also -------- indexing.decompose_indexer z%rasterio datasets should always be 3DrN)lenAssertionError isinstancesliceindicesr$rarangertolistlistappend enumerateziprminmaxndarrayZix_tuple) rkeyband_keynp_indsstartstopstepwindow squeeze_axisiknrrr _get_indexer6s2  ,   $z!RasterioArrayWrapper._get_indexerc Csddlm}||\}}}}|r4tdd|Drbt|ftdd|D}tj||jd}nF|j :|j j dd} |j dk r|| f|j } | j ||d }W5QRX|rtj||d }||S) Nrr css|]\}}||kVqdSr!r.0r;r<rrr tsz0RasterioArrayWrapper._getitem..css|]\}}||VqdSr!rrDrrrrFvs)rF)Z needs_lock)r>)Zaxis)r r rCanyr)r7rzerosrrr rrreadZsqueeze) rr8r r9r>r?r:r$outrrrr_getitemos  zRasterioArrayWrapper._getitemcCst||jtjj|jSr!)rZexplicit_indexing_adapterr$ZIndexingSupportZOUTERrK)rr8rrr __getitem__s z RasterioArrayWrapper.__getitem__)N) __name__ __module__ __qualname____doc__r propertyrr$rCrKrLrrrrr s  9r cs6dd}dd||dfdd|D}|S)aParse ENVI metadata into Python data structures. See the link for information on the ENVI header file format: http://www.harrisgeospatial.com/docs/enviheaderfiles.html Parameters ---------- meta : dict Dictionary of keys and str values to parse, as returned by the rasterio tags(ns='ENVI') call. Returns ------- parsed_meta : dict Dictionary containing the original keys and the parsed values cSstj|ddddS)N{}float,)rsep)r fromstringstripsrrrparsevecsz_parse_envi..parseveccSs |dS)NrR)rWrXrrrdefaultsz_parse_envi..default)Z wavelengthZfwhmcs"i|]\}}|||qSr)get)rErAvr[parserr sz_parse_envi..)items)metarZZ parsed_metarr^r _parse_envis  rccKsRtjdtddddl}ddlm}d}t||jjr>|j }nZt||j jr|} | j j }t | j | j| j| j| j| j| j| j| j| j| j| jd }|dkrt}t|j||d|d } | } |dk r|| f|} |dkr|dk}i} | jd krtd t !| j"| d <| jj#r|dkr"d n|} | r| j| j}}| jt $|dt %|df\}}| jt %|dt $|df\}}|| d<|| d<n(|dkrdn|} | rtjdt&ddi}t'| jdd|d<t(| dr&| jr&z| j)|d<Wn$t*k r$| j|d<YnXt(| dr<| j+|d<t(| drXt ,| j-|d<t(| dr|t'dd| j.D|d<t(| dr| j/|d<t(| dr| j0|d<t(| drt1| j2r| j2|d<t(| drt1| j3r| j3|d<t4d d!d"}| j5}||kr|d#kr&||| 6}n||| j6|d$}|7D]H\}}t|t8t j9frt:|| jkrd t !|f| |<n|||<qBt;|}|r|dkrt;?|}t@|d%| |d&}|dk rBdd'lAmB}ztCjDEtCjDF|}WntGk rd}YnX||||}d(|}|jH|||d)}|I| jJ|S)*a8Open a file with rasterio. .. deprecated:: 0.20.0 Deprecated in favor of rioxarray. For information about transitioning, see: https://corteva.github.io/rioxarray/stable/getting_started/getting_started.html This should work with any file that rasterio can open (most often: geoTIFF). The x and y coordinates are generated automatically from the file's geoinformation, shifted to the center of each pixel (see `"PixelIsArea" Raster Space `_ for more information). Parameters ---------- filename : str, rasterio.DatasetReader, or rasterio.WarpedVRT Path to the file to open. Or already open rasterio dataset. parse_coordinates : bool, optional Whether to parse the x and y coordinates out of the file's ``transform`` attribute or not. The default is to automatically parse the coordinates only if they are rectilinear (1D). It can be useful to set ``parse_coordinates=False`` if your files are very large or if you don't need the coordinates. chunks : int, tuple or dict, optional Chunk sizes along each dimension, e.g., ``5``, ``(5, 5)`` or ``{'x': 5, 'y': 5}``. If chunks is provided, it used to load the new DataArray into a dask array. cache : bool, optional If True, cache data loaded from the underlying datastore in memory as NumPy arrays when accessed to avoid reading from the underlying data- store multiple times. Defaults to True unless you specify the `chunks` argument to use dask, in which case it defaults to False. lock : False, True or threading.Lock, optional If chunks is provided, this argument is passed on to :py:func:`dask.array.from_array`. By default, a global lock is used to avoid issues with concurrent access to the same file when using dask's multithreaded backend. Returns ------- data : DataArray The newly created DataArray. zopen_rasterio is Deprecated in favor of rioxarray. For information about transitioning, see: https://corteva.github.io/rioxarray/stable/getting_started/getting_started.htmlr') stacklevelrNr ) src_crscrs resampling tolerance src_nodatanodatarr src_transform transformr warp_extrasr)rmodekwargsr&z Unknown dimsbandTg?yxFzThe file coordinates' transformation isn't rectilinear: xarray won't parse the coordinates in this case. 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