pygmt.grd2xyz
- pygmt.grd2xyz(grid, output_type='pandas', outfile=None, *, cstyle=None, region=None, verbose=None, weight=None, convention=None, binary=None, nodata=None, coltypes=None, header=None, outcols=None, skiprows=None, **kwargs)[source]
Convert grid to data table.
Read a grid and output xyz-triplets as a
numpy.ndarray,pandas.DataFrame, or ASCII file.Full option list at https://docs.generic-mapping-tools.org/latest/grd2xyz.html
Aliases:
C = cstyle
R = region
V = verbose
W = weight
Z = convention
b = binary
d = nodata
f = coltypes
h = header
o = outcols
s = skiprows
- Parameters
grid (str or xarray.DataArray) – The file name of the input grid or the grid loaded as a
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-numpy.ndarraypandas-pandas.DataFramefile- ASCII file (requiresoutfile)
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.
region (str or list) – xmin/xmax/ymin/ymax[+r][+uunit]. Specify the region of interest. Adding
regionwill 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[+uunit]|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 +uunit. For such grids, the area varies with latitude and also sees special cases for gridline-registered layouts at sides, corners, and poles.
Select verbosity level [Default is w], which modulates the messages written to stderr. Choose among 7 levels of verbosity:
q - Quiet, not even fatal error messages are produced
e - Error messages only
w - Warnings [Default]
t - Timings (report runtimes for time-intensive algorithms);
i - Informational messages (same as
verbose=True)c - Compatibility warnings
d - Debugging messages
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.
i|o[ncols][type][w][+l|b]. Select native binary input (using
binary="i") or output (usingbinary="o"), where ncols is the number of data columns of type, which must be one of:c - int8_t (1-byte signed char)
u - uint8_t (1-byte unsigned char)
h - int16_t (2-byte signed int)
H - uint16_t (2-byte unsigned int)
i - int32_t (4-byte signed int)
I - uint32_t (4-byte unsigned int)
l - int64_t (8-byte signed int)
L - uint64_t (8-byte unsigned int)
f - 4-byte single-precision float
d - 8-byte double-precision float
x - use to skip ncols anywhere in the record
For records with mixed types, append additional comma-separated combinations of ncols type (no space). The following modifiers are supported:
w after any item to force byte-swapping.
+l|b to indicate that the entire data file should be read as little- or big-endian, respectively.
Full documentation is at https://docs.generic-mapping-tools.org/latest/gmt.html#bi-full.
nodata (str) – i|onodata. Substitute specific values with NaN (for tabular data). For example,
d="-9999"will replace all values equal to -9999 with NaN during input and all NaN values with -9999 during output. Prepend i to the nodata value for input columns only. Prepend o to the nodata value for output columns only.coltypes (str) – [i|o]colinfo. Specify data types of input and/or output columns (time or geographical data). Full documentation is at https://docs.generic-mapping-tools.org/latest/gmt.html#f-full.
header (str) –
[i|o][n][+c][+d][+msegheader][+rremark][+ttitle]. Specify that input and/or output file(s) have n header records [Default is 0]. Prepend i if only the primary input should have header records. Prepend o to control the writing of header records, with the following modifiers supported:
+d to remove existing header records.
+c to add a header comment with column names to the output [Default is no column names].
+m to add a segment header segheader to the output after the header block [Default is no segment header].
+r to add a remark comment to the output [Default is no comment]. The remark string may contain \n to indicate line-breaks.
+t to add a title comment to the output [Default is no title]. The title string may contain \n to indicate line-breaks.
Blank lines and lines starting with # are always skipped.
outcols (str or 1d array) –
cols[,…][,t[word]]. Specify data columns for primary output in arbitrary order. Columns can be repeated and columns not listed will be skipped [Default writes all columns in order, starting with the first (i.e., column 0)].
For 1d array: specify individual columns in output order (e.g.,
outcols=[1,0]for the 2nd column followed by the 1st column).For
str: specify individual columns or column ranges in the format start[:inc]:stop, where inc defaults to 1 if not specified, with columns and/or column ranges separated by commas (e.g.,outcols="0:2,4"to output the first three columns followed by the 5th column). To write from a given column until the end of the record, leave off stop when specifying the column range. To write trailing text, add the column t. Append the word number to t to write only a single word from the trailing text. Instead of specifying columns, useoutcols="n"to simply read numerical input and skip trailing text. Note: ifincolsis also used then the columns given tooutcolscorrespond to the order after theincolsselection has taken place.
[cols][+a][+r]. Suppress output for records whose z-value equals NaN [Default outputs all records]. Optionally, supply a comma-separated list of all columns or column ranges to consider for this NaN test [Default only considers the third data column (i.e., cols = 2)]. Column ranges must be given in the format start[:inc]:stop, where inc defaults to 1 if not specified. The following modifiers are supported:
+r to reverse the suppression, i.e., only output the records whose z-value equals NaN.
+a to suppress the output of the record if just one or more of the columns equal NaN [Default skips record only if values in all specified cols equal NaN].
- Returns
ret (pandas.DataFrame or numpy.ndarray or None) – Return type depends on
outfileandoutput_type:None if
outfileis set (output will be stored in file set byoutfile)pandas.DataFrameornumpy.ndarrayifoutfileis not set (depends onoutput_type)
Example
>>> import pygmt >>> # Load a grid of @earth_relief_30m data, with an x-range of 10 to 30, >>> # and a y-range of 15 to 25 >>> grid = pygmt.datasets.load_earth_relief( ... resolution="30m", region=[10, 30, 15, 25] ... ) >>> # Create a pandas DataFrame with the xyz data from an input grid >>> xyz_dataframe = pygmt.grd2xyz(grid=grid, output_type="pandas") >>> xyz_dataframe.head(n=2) lon lat elevation 0 10.25 24.75 903.5 1 10.75 24.75 820.0
