Numpy Interpolate

For image processing with SciPy and NumPy, you will need the libraries for this tutorial. A simple approach is to use reverse interpolation. This is an example of an area where quaternions are preferred to rotation matrices as smooth interpolation is not possible with the latter. The following are code examples for showing how to use scipy. The sinc function is used in various signal processing applications, including in anti-aliasing, in the construction of a Lanczos resampling filter, and in interpolation. For the Agg, ps and pdf backends, interpolation = 'none' works well when a big image is scaled down, while interpolation = 'nearest' works well when a small image is scaled up. 3, matplotlib provides a griddata function that behaves similarly to the matlab version. Introduction to Numerical computation using numpy and scipy: (a) Introduction to the python numpy module. ) For a 2-D array, this is the usual matrix transpose. Interpolation methods Written by Paul Bourke December 1999 Discussed here are a number of interpolation methods, this is by no means an exhaustive list but the methods shown tend to be those in common use in computer graphics. fftpack) Signal Processing (scipy. linear_1d) The linear_1d class in scipy. Before looking at the sub-packages individually, we will rst look at some of these common functions. sin(x_table) # linearly interpolate x = np. The 2013 edition will take place in Brussels, Aug. interp¶ numpy. If you have scipy installed, you can set pass the name of a 1-d interpolation routine to method. See the summary exercise on Maximum wind speed prediction at the Sprogø station for a more advanced spline interpolation example. More speciflcally, one has found a point in a graph one is interested in, and now wants. Another advantage of using scipy. interpolate. Given 1,000 points and no fancy indexing algorithms, this means calculating 1,000,000 distances (or 999,000 – we don’t care about distance to self). piecewise polynomial interpolation exploit the systematic "migration" of the evaluation point as it moves left to right across the subintervals. If the number of entries is an even number i. In this article I will be describing what it means to apply an affine transformation to an image and how to do it in Python. Interpolation methods Written by Paul Bourke December 1999 Discussed here are a number of interpolation methods, this is by no means an exhaustive list but the methods shown tend to be those in common use in computer graphics. stats) Multi-dimensional image processing (scipy. You can vote up the examples you like or vote down the ones you don't like. The result is comparable to a regular polynomial interpolation, but is less susceptible to heavy oscillation between data points for high degrees. Once a FITS file has been read, the header its accessible as a Python dictionary of the data contents, and the image data are in a NumPy array. Note that for the interp family, the interpolation points must stay within the range of given data points. common` jimbo1qaz referenced this issue Aug 11, 2019 Downgrade dependencies to fix Windows exe builds #307. iPython Notebook, using numpy and scipy interpolation, integration, and curve fitting functions. percentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=False) [source] ¶ Compute the qth percentile of the data along the specified axis. If you have scipy installed, you can pass the name of a 1-d interpolation routine to method. Returns the one-dimensional piecewise linear interpolant to a function with given values at discrete data-points. Notes-----Transformations. Learn Lagrangian interpolation formula. First we load the necessary packages and generate some data:. Interpolation (scipy. x branch, and on adding new features on the master branch. You must type the reference to the step value in cell B1 as an absolute reference (with dollar signs). This article is contributed by Mohit Gupta_OMG 😀. See Also¶ ["Cookbook/FiltFilt"] which can be used to smooth the data by low-pass filtering and does not delay the signal (as this smoother does). Linear transformations in Numpy jun 11, 2016 geometry geometric-transformations python numpy matplotlib. Interpolation of an image Given a random-sampled selection of pixels from an image, scipy. This NumPy stack has similar users to other applications such as MATLAB , GNU Octave , and Scilab. Peak Detection in the Python World 01 Nov 2015 Yoan Tournade Digital signal processing As I was working on a signal processing project for Equisense , I’ve come to need an equivalent of the MatLab findpeaks function in the Python world. Interpolation methods Written by Paul Bourke December 1999 Discussed here are a number of interpolation methods, this is by no means an exhaustive list but the methods shown tend to be those in common use in computer graphics. NumPy provides standard trigonometric functions, functions for arithmetic operations, handling complex numbers, etc. Example of underfitted, well-fitted and overfitted…. py: a two-dimensional lattice-Boltzmann "wind tunnel" simulation # Uses numpy to speed up all array handling. 1 The Interpolating Polynomial. interpolation: {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’} Method to use when the desired quantile falls between two points. import numpy as np from scipy import interpolate import matplotlib. Interpolation methods in Scipy oct 28, 2015 numerical-analysis interpolation python numpy scipy. We know the derivative is 4x. signal) Linear Algebra (scipy. For the Agg, ps and pdf backends, interpolation = 'none' works well when a big image is scaled down, while interpolation = 'nearest' works well when a small image is scaled up. fftpack) Signal Processing (scipy. Among other numerical analysis modules, scipy covers some interpolation algorithms as well as a different approaches to use them to calculate an interpolation, evaluate a polynomial with the representation of the interpolation, calculate derivatives, integrals or roots with functional and class. NumPy("넘파이"라 읽는다)는 행렬이나 일반적으로 대규모 다차원 배열을 쉽게 처리 할 수 있도록 지원하는 파이썬의 라이브러리이다. How to interpolate a set of points The purpose of this example is to show how to interpolate a set of points (x,y) using the funtion interp1 provided by scipy. 6/dist-packages/matplotlib/mpl-data/matplotlibrc. iPython Notebook, using numpy and scipy interpolation, integration, and curve fitting functions. interpolate (func, deg, domain=None, args=()) [source] ¶ Interpolate a function at the Chebyshev points of the first kind. The fundamental object of NumPy is its ndarray (or numpy. It's from Continuum (a company founded by some of NumPy's core developers), and comes included with a purchase of Anaconda Accelerate. Both Numpy and Scipy provide black box methods to fit one-dimensional data using linear least squares, in the first case, and non-linear least squares, in the latter. One is ‘interp’ in numpy. delete - This function returns a new array with the specified subarray deleted from the input array. 1D Spline Interpolation # demo/interpolate/spline. The name sinc is short for "sine cardinal" or "sinus cardinalis". 7] Now I need to apply an interpolation function using the variables in m, however based on the index in the index-matrix I need to choose from different values. Take the Near Analysis. This is an archival dump of old wiki content --- see scipy. My very basic need it to re-sample/shift 1D spectral data. However, the changes seems not to be working. # import scipy as sc import numpy as np def resample (x, k. Discrete Sibson (Natural Neighbor) Interpolation. linalg over numpy. NumPy is based on two earlier Python modules dealing with arrays. The attachment cookb_signalsmooth. Griddata takes the value of a function at arbitrary input points, and interpolates it to a grid of output points. Images in scikit-image are represented by NumPy ndarrays. The 2013 edition will take place in Brussels, Aug. transpose(*axes) Returns a view of the array with axes transposed. This series will help you understand different statistical tests and how to perform them in python using only Numpy. Arrays differ from plain Python lists in the way they are stored and handled. the scipy namespace to ease their use in interactive sessions and programs. I would like to create a 2-d array (surface) from this data, each cell in the array being an interpolated value based on the nearby z values. This is a brief overview with a few examples drawn primarily from the excellent but short introductory book SciPy and NumPy by Eli Bressert (O'Reilly 2012). py from scipy. Returns the one-dimensional piecewise linear interpolant to a function with given values at discrete data-points. The spline algorithm, on the other hand, performs cubic interpolation to produce piecewise polynomials with continuous second-order derivatives (C2). zeros() & numpy. yi = y1 + (y2-y1) * (xi-x1) / (x2-x1) With some vectorized Numpy expressions we can select the relevant points from the dataset and apply the above function:. Frequently Asked Questions. Project Management. It refers to constant-speed motion along a unit-radius great circle arc, given the ends and an interpolation parameter between 0 and 1. import numpy as np from scipy. sin(x_table) # linearly interpolate x = np. NumPy or Numeric Python is a package for computation on homogenous n-dimensional arrays. When it comes to scientific computing, NumPy is on the top of the list. interpolate class method adds support for interpolation over arbitrary intervals using the scaled and shifted Chebyshev points of the first kind. The values and distances of the two nearest neighbors as well as the interpolation parameter will determine the percentile if the normalized ranking does not match the location of q exactly. Although popular statistics libraries like SciPy and PyMC3 have pre-defined functions to compute different tests, to understand the maths behind the process, it is imperative to understand whats going on in the background. 1 The Interpolating Polynomial. transpose(*axes) Returns a view of the array with axes transposed. The method argument gives access to fancier interpolation methods. set_printoptions(suppress=True) # Suppress insignificant values for clarity >>> v = numpy. hconcat() to concatenate (combine) images vertically and horizontally with Python, OpenCV. "Piecewise Cubic Hermite Interpolating Polynomial" in python Recently, I had a need for a monotonic piece-wise cubic Hermite interpolator. Interpolation and Extrapolation in 1D in Python/v3 Learn how to interpolation and extrapolate data in one dimension Note: this page is part of the documentation for version 3 of Plotly. NumPy is based on two earlier Python modules dealing with arrays. NumPy for Numeric/numarray users. mathforcollege. Returns the one-dimensional piecewise linear interpolant to a function with given discrete data points ( xp , fp ), evaluated at x. of the form 2n, then, first quartile (Q1) is equal to the median of the n smallest entries and the third quartile (Q3) is equal to the median of the n largest entries. ,201) # here we create linear interpolation function linear = interp1d(x_table,y_table,'linear') # apply and create new array. My very basic need it to re-sample/shift 1D spectral data. I am accessing the z dimension and perform interpolation. The actual use I have is neural networks and mapping one concept to another. For each official release of NumPy and SciPy, we provide source code (tarball) as well as binary wheels for several major platforms (Windows, OSX, Linux). Read the Docs. py from scipy. integrate) 関数や数列から数値積分を行う. 補間. interp will be 0. interpolate import. percentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=False) [source] ¶ Compute the qth percentile of the data along the specified axis. The interpolated surface is smoother than corresponding surfaces obtained by bilinear interpolation or nearest-neighbor interpolation. The results always pass through the original sampling of the function. Discrete Sibson (Natural Neighbor) Interpolation. Numpy & Scipy / Linear Algebra 14. signal) Linear Algebra (scipy. 1-D interpolation (interp1d) ¶ The interp1d class in scipy. Python Numpy : Select elements or indices by conditions from Numpy Array; Create Numpy Array of different shapes & initialize with identical values using numpy. derivative(der)` returns a callable object representing the derivative of `p`. py, which is not the most recent version. For each official release of NumPy and SciPy, we provide source code (tarball) as well as binary wheels for several major platforms (Windows, OSX, Linux). Returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x. Rbf does radial basis functions, and has all the interpolation types listed on p. Try this first: http://www. SciPy Cookbook¶. Near Analysis: ArcPy vs. Griddata takes the value of a function at arbitrary input points, and interpolates it to a grid of output points. interpolate. Least squares fitting with Numpy and Scipy nov 11, 2015 numerical-analysis optimization python numpy scipy. nanpercentile()function used to compute the nth precentile of the given data (array elements) along the specified axis ang ignores nan values. This example shows the original image, the noisy image, the denoised one (with the median filter) and the difference between the two. The method argument gives access to fancier interpolation methods. Array elements stay together in memory, so they can be quickly accessed. An instance of this class is created by passing the 1-d vectors comprising the data. vstack([numpy. fftpack) Signal Processing (scipy. Returns the series that interpolates func at the Chebyshev points of the first kind scaled and shifted to the domain. NET Numerics aims to provide methods and algorithms for numerical computations in science, engineering and every day use. They are extracted from open source Python projects. This NumPy stack has similar users to other applications such as MATLAB , GNU Octave , and Scilab. – Alex Martelli Jul 29 '09 at 15:30 With these particular values, all of the results from numpy. Reading and Writing a FITS File in Python. Project Management Content Management System (CMS) Task Management Project Portfolio Management Time Tracking PDF. Pchip interpolation implementation in pure Numpy (no scipy dependency, suitable for Android. This is the "SciPy Cookbook" — a collection of various user-contributed recipes, which once lived under wiki. You may have domain knowledge to help choose how values are to be interpolated. x, y and z are arrays of values used to approximate some function f: z = f(x, y). This class returns a function whose call method uses spline interpolation to find the value of new points. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. My very basic need it to re-sample/shift 1D spectral data. Hence, many common operations can be achieved using standard NumPy methods for manipulating arrays:. When it comes to scientific computing, NumPy is on the top of the list. linear_1d) The linear_1d class in scipy. ndarray, float) – values x and PDF values y at which interpolator is fit • threshold (float, optional) – minimum value to use outside interpolation range Returnskludge_interpolator – evaluates linear interpolant based on input points Return type function. ing Numpy/Scipy. A linear transformation of the plane \(\mathbb R^2\) is a geometric transformation of the form. For another example, consider the function f(x) = exp(- 1/x²) , defined to be 0 at 0. 2018-01-14 16:05 Regina Obe * [r16295] HOWTO_RELEASE, Version. G omez26NumPy, matplotlib and SciPy. The interpolation function, or interpolant, should exactly coincide with the given data points, and it can also be evaluated for other intermediate input values within the sampled range. I then have a 2D array, and the indices. From *Cvib*, which is a matrix with *Cvib(T,V)* as from the harmonic calculations determines the *Cv* at each temperature by linear interpolation between the values at the two volumes closest to Vmin(T). Perfect sinc interpolation in Matlab and Python. It must be of the correct shape (the same shape as arr, excluding axis). interp¶ numpy. interpolate. interp pointed out in gh-7279 is nice. A new Chebyshev. arange(11) y_table = np. Interpolation and Extrapolation in 2D in Python/v3 Learn how to interpolation and extrapolate data in two dimensions Note: this page is part of the documentation for version 3 of Plotly. You can also provide an integer number, in which case the function will use a polynomial of that order to interpolate between points. Quartiles are calculated by the help of the median. Interpolation of an N-D curve¶ The scipy. Although the data is evenly spaced in this example, it need not be so to use this routine. MATLAB/Octave Python Description; doc help -i % browse with Info: help() Interpolation and regression. If you have scipy installed, you can set pass the name of a 1-d interpolation routine to method. With Python using NumPy and SciPy you can read, extract information, modify, display, create and save image data. Potapov_interpolation import Roots import Potapov import Time_Delay_Network import Time_Sims import functions import tests import numpy as np import numpy. One option suited for fast numerical operations is NumPy, which deservedly bills itself as the fundamental package for scientific computing with Python. SciPy Cookbook¶. Recommend:python - Apply numpy interpolation function with index array m = [0. Most popular Pandas, Pandas. G omez26NumPy, matplotlib and SciPy. Indexing can be done in numpy by using an array as an index. Unclaimed Prizes. Instead the goal of this post is to try and understand the fundamentals of a few simple image processing techniques. As part of the Python Tools for Visual Studio project the well-known NumPy and SciPy libraries were ported to. Take mean along specified dimension. By passing an x value to the function the function returns the interpolated y value. Vq = interp2(X,Y,V,Xq,Yq) returns interpolated values of a function of two variables at specific query points using linear interpolation. From *Cvib*, which is a matrix with *Cvib(T,V)* as from the harmonic calculations determines the *Cv* at each temperature by linear interpolation between the values at the two volumes closest to Vmin(T). # Uses matplotlib to plot and animate the curl of the macroscopic velocity field. sinc(0) is the limit value 1. Kite is a free autocomplete for Python developers. Returns the one-dimensional piecewise linear interpolant to a function with given discrete data points ( xp , fp ), evaluated at x. 0 release contains a large number of fixes and improvements, but few that stand out above all others. For another example, consider the function f(x) = exp(- 1/x²) , defined to be 0 at 0. """ Demonstration module for quadratic interpolation. Denoising an image with the median filter¶. CubicSpline(). # LatticeBoltzmannDemo. py contains a version of this script with some stylistic cleanup. Science with Python: NumPy, SciPy and Matplotlib Interpolate The SciPy interpolate module has a import numpy as np import scipy. Mathematical tasks: NumPy is quite useful to perform various mathematical tasks like numerical integration, differentiation, interpolation, extrapolation, and many others. Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. Images in scikit-image are represented by NumPy ndarrays. This webinar will review the interpolation modules available in SciPy and in the larger Python community and provide instruction on their use via example. They are extracted from open source Python projects. You'll want to consult the full scipy interpolation documentation and reference guide for details. interp¶ numpy. uk/projects/raspberrypi/tutorials/robot/downloads/ If that does not. Numeric is like NumPy a Python module for high-performance, numeric computing, but it is obsolete nowadays. Read the Docs. "Piecewise Cubic Hermite Interpolating Polynomial" in python Recently, I had a need for a monotonic piece-wise cubic Hermite interpolator. SciPy - Basic Functionality - By default, all the NumPy functions have been available through the SciPy namespace. interp2d¶ class scipy. Numpy & Scipy / Matplotlib 15. Denoising an image with the median filter¶. While these libraries are frequently used in regression analysis, it is often the case that a user might choose different libraries depending on the data in question, among other considerations. NumPy Array Object Exercises, Practice and Solution: Write a NumPy program to find the closest value (to a given scalar) in an array. They are extracted from open source Python projects. linalg as la import matplotlib. You can vote up the examples you like or vote down the ones you don't like. From *Cvib*, which is a matrix with *Cvib(T,V)* as from the harmonic calculations determines the *Cv* at each temperature by linear interpolation between the values at the two volumes closest to Vmin(T). Upcasting to float64 always seems simpler though, and the consistency with PPoly and np. Although the data is evenly spaced in this example, it need not be so to use this routine. Take mean along specified dimension. Once a FITS file has been read, the header its accessible as a Python dictionary of the data contents, and the image data are in a NumPy array. The code below does this, when fed the name of an image file on the command line. This is a brief overview with a few examples drawn primarily from the excellent but short introductory book SciPy and NumPy by Eli Bressert (O'Reilly 2012). Python Numpy Tutorial. stats) Multi-dimensional image processing (scipy. derivative(der)` returns a callable object representing the derivative of `p`. 흑백 이미지를 2D 배열로 표현하는 방법을 살펴보자. Parameters: field3d (xarray. Hence, many common operations can be achieved using standard NumPy methods for manipulating arrays:. Images in scikit-image are represented by NumPy ndarrays. The graph shows the data contained in the array price_index and shows the tangent of the curve for the years 1991 and 1998. You may have domain knowledge to help choose how values are to be interpolated. More generally, let be an arbitrary distribution on the interval , the associated orthogonal polynomials , and , , the fundamental polynomials corresponding to the set of zeros of a polynomial. 64, which is the 11th data point. In this tutorial we'll learn how to handle missing data in pandas using fillna, interpolate and dropna methods. slerp_vectorized for a vectorized version of this function, and quaternion. Code faster with the Kite plugin for your code editor, featuring Line-of-Code Completions and cloudless processing. This chapter includes discussion and examples on integration, optimization, interpolation, and more. T) The default method for both MATLAB and scipy is linear interpolation, and this can be changed with the method argument. interp for 1-dimensional linear interpolation. The spline algorithm, on the other hand, performs cubic interpolation to produce piecewise polynomials with continuous second-order derivatives (C2). reshape ( 8 , 8 ). txt) or read online for free. interpolate. If the number of entries is an even number i. NumbaPro is a GPU-accelerated version of Numba (which is an LLVM-enhanced version of NumPy). The answer is, first you interpolate it to a regular grid. linalg over numpy. Although the data is evenly spaced in this example, it need not be so to use this routine. interpolate is a convenient method to create a function based on fixed data points, which can be evaluated anywhere within the domain defined by the given data using linear interpolation. I am accessing the z dimension and perform interpolation. They are extracted from open source Python projects. 2000 "Interpolation Revisited") that interpolation using a Cardinal spline is equivalent to interpolating-B-spline interpolation. interpolate. arr :input array. As most parts of linear algebra deals with matrices only. Returns the one-dimensional piecewise linear interpolant to a function with given values at discrete data-points. #! /usr/bin/python # # Author: Gaute Hope (gaute. But since it's so large (3e6 doubles), doing it in Python is not feasible/sensible. interp(x, xp, fp, left=None, right=None) [source] ¶ One-dimensional linear interpolation. 1-D interpolation (interp1d) ¶ The interp1d class in scipy. Code faster with the Kite plugin for your code editor, featuring Line-of-Code Completions and cloudless processing. The spline algorithm, on the other hand, performs cubic interpolation to produce piecewise polynomials with continuous second-order derivatives (C2). These values are appended to a copy of arr. interp (x, xp, fp, left=None, right=None, period=None) [source] ¶ One-dimensional linear interpolation. I have a 3D array that I want to interpolate the np. The original article is no longer available. ones() | Create a numpy array of zeros or ones; Python Numpy : Create a Numpy Array from list, tuple or list of lists using numpy. SciPy (pronounced "Sigh Pie") is a Python-based ecosystem of open-source software for mathematics, science, and engineering. Interpolation of an N-D curve¶ The scipy. Python GAMMA Function Example. interpolate import interp1d # make our tabular values x_table = np. iPython Notebook, using numpy and scipy interpolation, integration, and curve fitting functions. interpolate import interp1d from pylab import plot, axis, legend from numpy import linspace # sample values x = linspace(0,2*pi,6) y = sin(x) # Create a spline class for interpolation. pyplot as pl import numpy as np from scipy. linalg) Sparse Eigenvalue Problems with ARPACK Statistics (scipy. interpolate packages wraps the netlib FITPACK routines (Dierckx) for calculating smoothing splines for various kinds of data and geometries. arange ( 0 , 256 , 4 ). Importing the NumPy module There are several ways to import NumPy. Kite is a free autocomplete for Python developers. Now, let's zoom it 10 times using each interpolation method. 2013-03-20 16:47 strk * Deprecate non-CamelCase linear referencing function (#1994) - ST_Line_Interpolate_Point renamed to ST_LineInterpolatePoint - ST_Line_Substring renamed to ST_LineSubstring - ST_Line_Locate_Point renamed to ST_LineLocatePoint Tests updated to use the new signature, docs updated to show the new signature and report. yi = y1 + (y2-y1) * (xi-x1) / (x2-x1) With some vectorized Numpy expressions we can select the relevant points from the dataset and apply the above function:. interpolate. One option suited for fast numerical operations is NumPy, which deservedly bills itself as the fundamental package for scientific computing with Python. q : percentile value. array([xi,yi,zi]). pyplot as plt Univariate interpolation In the next examples, x and y represents the known points. Here's quaternion interpolation in action: >>> import numpy >>> numpy. linalg as la import matplotlib. This example shows the original image, the noisy image, the denoised one (with the median filter) and the difference between the two. DataArray or numpy. Experienced NumPy users will have noticed some discrepancy between meshgrid and the mgrid, a function that is used just as often, for exactly the same purpose. 2+dfsg-4+b1_i386. pyplot as plt x = np. interp2d to interpolate these values onto a finer, evenly-spaced $(x,y)$ grid. The actual use I have is neural networks and mapping one concept to another. python - interpolate 3D volume with numpy and or scipy up vote 0 down vote favorite I have a DLL, written in Delphi, which should determine some values and then pass the results back to the C++ app, which called the DLL. This example demonstrates some of the different interpolation methods available in scipy. Contribute to scipy/scipy development by creating an account on GitHub. py # Copyright (c) 2007-2019, Christoph Gohlke # Copyright (c) 2007-2019, The Regents of the University of California # Produced at the. A good starting point is to use a linear interpolation. interpolate (func, deg, domain=None, args=()) [source] ¶ Interpolate a function at the Chebyshev points of the first kind. nanpercentile()function used to compute the nth precentile of the given data (array elements) along the specified axis ang ignores nan values. config, doc/release_notes. linalg) Sparse Eigenvalue Problems with ARPACK Statistics (scipy. The Series Pandas object provides an interpolate() function to interpolate missing values, and there is a nice selection of simple and more complex interpolation functions. They are extracted from open source Python projects. This chapter concentrates on two closely related interpolants: the piecewise cubic spline and the shape-preserving piecewise cubic named "pchip. nan values along the z dimension, and I just want the changes to modify my existing array. NumPy is based on two earlier Python modules dealing with arrays. You can also provide an integer number, in which case the function will use a polynomial of that order to interpolate between points. Returns the one-dimensional piecewise linear interpolant to a function with given discrete data points ( xp , fp ), evaluated at x. Returns the qth percentile of the array elements. interpolate. v means vertical and h means horizontal. The method argument gives access to fancier interpolation methods. Plotting Tools. It performs "natural neighbor interpolation" of irregularly spaced data a regular grid, which you can then plot with contour, imshow or pcolor.