Source code for

info - Get information about data tables.
import numpy as np
from pygmt.clib import Session
from pygmt.exceptions import GMTInvalidInput
from pygmt.helpers import (

[docs]@fmt_docstring @use_alias(C="per_column", I="spacing", T="nearest_multiple", V="verbose") def info(table, **kwargs): r""" Get information about data tables. Reads from files and finds the extreme values in each of the columns reported as min/max pairs. It recognizes NaNs and will print warnings if the number of columns vary from record to record. As an option, it will find the extent of the first two columns rounded up and down to the nearest multiple of the supplied increments given by ``spacing``. Such output will be in a numpy.ndarray form [*w*, *e*, *s*, *n*], which can be used directly as the ``region`` parameter for other modules (hence only *dx* and *dy* are needed). If the ``per_column`` parameter is combined with ``spacing``, then the numpy.ndarray output will be rounded up/down for as many columns as there are increments provided in ``spacing``. A similar parameter ``nearest_multiple`` option will provide a numpy.ndarray in the form of [*zmin*, *zmax*, *dz*]`` for makecpt. Full option list at :gmt-docs:`gmtinfo.html` {aliases} Parameters ---------- table : str or np.ndarray or pandas.DataFrame or xarray.Dataset Pass in either a file name to an ASCII data table, a 1D/2D numpy array, a pandas dataframe, or an xarray dataset made up of 1D xarray.DataArray data variables. per_column : bool Report the min/max values per column in separate columns. spacing : str [**b**\|\ **p**\|\ **f**\|\ **s**]\ *dx*\[/*dy*\[/*dz*...]]. Report the min/max of the first n columns to the nearest multiple of the provided increments and output results in the form ``[w, e, s, n]``. nearest_multiple : str **dz**\[\ **+c**\ *col*]. Report the min/max of the first (0'th) column to the nearest multiple of dz and output this in the form ``[zmin, zmax, dz]``. {V} Returns ------- output : np.ndarray or str Return type depends on whether any of the ``per_column``, ``spacing``, or ``nearest_multiple`` parameters are set. - np.ndarray if either of the above parameters are used. - str if none of the above parameters are used. """ kind = data_kind(table) with Session() as lib: if kind == "file": file_context = dummy_context(table) elif kind == "matrix": try: # pandas.DataFrame and xarray.Dataset types arrays = [array for _, array in table.items()] except AttributeError: # Python lists, tuples, and numpy ndarray types arrays = np.atleast_2d(np.asanyarray(table).T) file_context = lib.virtualfile_from_vectors(*arrays) else: raise GMTInvalidInput(f"Unrecognized data type: {type(table)}") with GMTTempFile() as tmpfile: with file_context as fname: arg_str = " ".join( [fname, build_arg_string(kwargs), "->" +] ) lib.call_module("info", arg_str) result = if any(arg in kwargs for arg in ["C", "I", "T"]): # Converts certain output types into a numpy array # instead of a raw string that is less useful. if result.startswith(("-R", "-T")): # e.g. -R0/1/2/3 or -T0/9/1 result = result[2:].replace("/", " ") result = np.loadtxt(result.splitlines()) return result