"""grd2xyz - Convert grid to data table"""importwarningsimportpandasaspdimportxarrayasxrfrompygmt.clibimportSessionfrompygmt.exceptionsimportGMTInvalidInputfrompygmt.helpersimport(GMTTempFile,build_arg_string,fmt_docstring,kwargs_to_strings,use_alias,)
[docs]@fmt_docstring@use_alias(C="cstyle",R="region",V="verbose",W="weight",Z="convention",b="binary",d="nodata",f="coltypes",h="header",o="outcols",s="skiprows",)@kwargs_to_strings(R="sequence",o="sequence_comma")defgrd2xyz(grid,output_type="pandas",outfile=None,**kwargs):r""" Convert grid to data table. Read a grid and output xyz-triplets as a :class:`numpy.ndarray`, :class:`pandas.DataFrame`, or ASCII file. Full option list at :gmt-docs:`grd2xyz.html` {aliases} Parameters ---------- grid : str or xarray.DataArray The file name of the input grid or the grid loaded as a :class:`xarray.DataArray`. This is the only required parameter. output_type : str Determine the format the xyz data will be returned in [Default is ``pandas``]: - ``numpy`` - :class:`numpy.ndarray` - ``pandas``- :class:`pandas.DataFrame` - ``file`` - ASCII file (requires ``outfile``) outfile : str The file name for the output ASCII file. cstyle : str [**f**\|\ **i**]. Replace the x- and y-coordinates on output with the corresponding column and row numbers. These start at 0 (C-style counting); append **f** to start at 1 (Fortran-style counting). Alternatively, append **i** to write just the two columns *index* and *z*, where *index* is the 1-D indexing that GMT uses when referring to grid nodes. {R} Adding ``region`` will select a subsection of the grid. If this subsection exceeds the boundaries of the grid, only the common region will be output. weight : str [**a**\ [**+u**\ *unit*]\|\ *weight*]. Write out *x,y,z,w*\ , where *w* is the supplied *weight* (or 1 if not supplied) [Default writes *x,y,z* only]. Choose **a** to compute weights equal to the area each node represents. For Cartesian grids this is simply the product of the *x* and *y* increments (except for gridline-registered grids at all sides [half] and corners [quarter]). For geographic grids we default to a length unit of **k**. Change this by appending **+u**\ *unit*. For such grids, the area varies with latitude and also sees special cases for gridline-registered layouts at sides, corners, and poles. {V} convention : str [*flags*]. Write a 1-column ASCII [or binary] table. Output will be organized according to the specified ordering convention contained in *flags*. If data should be written by rows, make *flags* start with **T** (op) if first row is y = ymax or **B** (ottom) if first row is y = ymin. Then, append **L** or **R** to indicate that first element should start at left or right end of row. Likewise for column formats: start with **L** or **R** to position first column, and then append **T** or **B** to position first element in a row. For gridline registered grids: If grid is periodic in x but the written data should not contain the (redundant) column at x = xmax, append **x**. For grid periodic in y, skip writing the redundant row at y = ymax by appending **y**. If the byte-order needs to be swapped, append **w**. Select one of several data types (all binary except **a**): * **a** ASCII representation of a single item per record * **c** int8_t, signed 1-byte character * **u** uint8_t, unsigned 1-byte character * **h** int16_t, short 2-byte integer * **H** uint16_t, unsigned short 2-byte integer * **i** int32_t, 4-byte integer * **I** uint32_t, unsigned 4-byte integer * **l** int64_t, long (8-byte) integer * **L** uint64_t, unsigned long (8-byte) integer * **f** 4-byte floating point single precision * **d** 8-byte floating point double precision Default format is scanline orientation of ASCII numbers: **TLa**. {b} {d} {f} {h} {o} {s} Returns ------- ret : pandas.DataFrame or numpy.ndarray or None Return type depends on ``outfile`` and ``output_type``: - None if ``outfile`` is set (output will be stored in file set by ``outfile``) - :class:`pandas.DataFrame` or :class:`numpy.ndarray` if ``outfile`` is not set (depends on ``output_type``) """ifoutput_typenotin["numpy","pandas","file"]:raiseGMTInvalidInput("Must specify 'output_type' either as 'numpy', 'pandas' or 'file'.")ifoutfileisnotNoneandoutput_type!="file":msg=(f"Changing 'output_type' of grd2xyz from '{output_type}' to 'file' ""since 'outfile' parameter is set. Please use output_type='file' ""to silence this warning.")warnings.warn(message=msg,category=RuntimeWarning,stacklevel=2)output_type="file"elifoutfileisNoneandoutput_type=="file":raiseGMTInvalidInput("Must specify 'outfile' for ASCII output.")if"o"inkwargsandoutput_type=="pandas":raiseGMTInvalidInput("If 'outcols' is specified, 'output_type' must be either 'numpy'""or 'file'.")# Set the default column names for the pandas dataframe headerdataframe_header=["x","y","z"]# Let output pandas column names match input DataArray dimension namesifisinstance(grid,xr.DataArray)andoutput_type=="pandas":# Reverse the dims because it is rows, columns ordered.dataframe_header=[grid.dims[1],grid.dims[0],grid.name]withGMTTempFile()astmpfile:withSession()aslib:file_context=lib.virtualfile_from_data(check_kind="raster",data=grid)withfile_contextasinfile:ifoutfileisNone:outfile=tmpfile.namearg_str=" ".join([infile,build_arg_string(kwargs),"->"+outfile])lib.call_module("grd2xyz",arg_str)# Read temporary csv output to a pandas tableifoutfile==tmpfile.name:# if user did not set outfile, return pd.DataFrameresult=pd.read_csv(tmpfile.name,sep="\t",names=dataframe_header,comment=">")elifoutfile!=tmpfile.name:# return None if outfile set, output in outfileresult=Noneifoutput_type=="numpy":result=result.to_numpy()returnresult