How to Create Panoply-Like NetCDF Plots Using C++ for Earth Science Applications

NetCDF (Network Common Data Form) is a set of libraries and data formats used to store and manipulate scientific data. It is widely used in the Earth science community to store and share data such as atmospheric and oceanographic data. Panoply is a popular software tool for visualizing and analyzing NetCDF data. In this article, we will explore how to create NetCDF plots like Panoply using C++.

What is NetCDF?

NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. It was developed by the Unidata Program Center, a community of researchers and educators dedicated to sharing geoscience data. NetCDF is used by a wide variety of scientific disciplines, including earth science, atmospheric science, oceanography, and more.

NetCDF is a binary file format that is self-describing, meaning that it contains information about the data it contains. This makes it easy to exchange data between different software programs and operating systems. NetCDF files contain metadata that describes the data, as well as the data itself. Metadata includes information such as units of measurement, variable names, and dimensions of the data.

What is Panoply?

Panoply is a software tool developed by NASA’s Goddard Space Flight Center for visualizing and analyzing NetCDF data. It is a cross-platform application available for Windows, Mac, and Linux operating systems. Panoply can be used to create a variety of visualizations, including contour plots, vector plots, and 3D surface plots. It also includes tools for filtering, smoothing, and manipulating data.

One of the benefits of using Panoply is its easy-to-use interface. It allows users to easily import NetCDF files, select variables and dimensions, and create visualizations with just a few clicks. However, if you are working with large datasets or need to create custom visualizations, it may be more efficient to use a programming language such as C++.

Creating NetCDF plots in C++

To create NetCDF plots in C++, you must use a library that supports NetCDF, such as the NetCDF C++ API. The NetCDF C++ API is a set of C++ classes that provide a high-level interface to the NetCDF library. It allows you to create, read, write, and manipulate NetCDF files in C++.

Here is a simple example of how to create a NetCDF file in C++ using the NetCDF C++ API:
#include <netcdf>

using the netCDF namespace;

int main()

);

// Write data to file

double data1010 = ,

,

,

,

,

,

,

,

,

};

dataVar.putVar(data);

// Add metadata

file.putAtt(“units”, “meters”)

file.putAtt(“long_name”, “example_data”)

return 0;

}

This code creates a new NetCDF file named “example.nc” with two dimensions (“x” and “y”) and one variable (“data”). The data in the “data” variable is a 10×10 array of doubles. The code also adds metadata to the file, including the units and long name of the data. This is just a simple example, and in a real-world application you would likely be working with much larger data sets and more complex variables.

Once you have created a NetCDF file in C++, you can use the NetCDF C++ API to read the data and create visualizations. There are several C++ libraries that can be used to visualize NetCDF data, including the Boost C++ libraries and the VTK (Visualization Toolkit) library.

Creating NetCDF Plots Like Panoply

To create NetCDF plots like those in Panoply, you need to use a combination of the NetCDF libraries and a plotting library such as Gnuplot or Matplotlib. These libraries provide tools for creating a variety of plot types, including contour plots, line plots, and surface plots.

One approach to creating NetCDF plots in C++ is to use the NetCDF C++ API to read the data from the NetCDF file and then use Gnuplot or Matplotlib to create the plot. Here is an example of how to create a contour plot of NetCDF data using the NetCDF C++ API and Gnuplot:

#include <netcdf>

#include <gnuplot-iostream.h>

using the netCDF namespace;

int main()

}

// Plot the data as a contour plot

gp.splot(GnuplotMatrix(matrix));

return 0;

}

This code reads the “data” variable from the “example.nc” NetCDF file using the NetCDF C++ API. It then creates a Gnuplot object and sets the plot properties, such as the x-axis label, y-axis label and plot title. Next, it creates a matrix from the data and plots it as a contour plot using the Gnuplot object’s plot() function.

Matplotlib is another popular plotting library that can be used to create NetCDF plots in C++. Matplotlib is a Python library, but can be called from C++ using the Python/C API. Here is an example of how to create a contour plot of NetCDF data using the NetCDF C++ API and Matplotlib:
#include <netcdf>

#include <Python.h>

using the netCDF namespace;

int main()

{

// Initialize the Python interpreter

Py_Initialize();

// Import the Matplotlib library

PyObject* matplotlib = PyImport_ImportModule(“matplotlib.pyplot”)

// Open the NetCDF file

NcFile file(“example.nc”, NcFile::read);

// Get the data variable

NcVar dataVar = file.getVar(“data”);

// get the data dimensions

NcDim xDim = file.getDim(“x”)

NcDim yDim = file.getDim(“y”);

// Read the data into a vector

std::vector<double> data(xDim.getSize() * yDim.getSize());

dataVar.getVar(data.data());

// create a NumPy array from

FAQs

What is NetCDF?

NetCDF is a set of libraries and data formats used to store and manipulate scientific data, commonly used in the Earth science community to store and share data such as atmospheric and oceanographic data.

What is Panoply?

Panoply is a software tool developed by NASA’s Goddard Space Flight Center for visualizing and analyzing NetCDF data. It is a cross-platform application that is available for Windows, Mac, and Linux operating systems.

How can you create NetCDF plots in C++?

To create NetCDF plots in C++, you can use a library that supports NetCDF, such as the NetCDF C++ API, and a plotting library such as Gnuplot or Matplotlib.

How can you create a NetCDF file in C++ using the NetCDF C++ API?

You can create a NetCDF file in C++ using the NetCDF C++ API by defining the dimensions and variables, writing data to the variables, and adding metadata to the file. Here is an example:

NcFile file("example.nc", NcFile::replace);
NcDim xDim = file.addDim("x", 10);
NcDim yDim = file.addDim("y", 10);
NcVar dataVar = file.addVar("data", ncDouble, {xDim, yDim});
double data1010 = {{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
                       {2, 4, 6, 8, 10, 12, 14, 16, 18, 20},
                       {3, 6, 9, 12, 15, 18, 21, 24, 27, 30},
                       {4, 8, 12, 16, 20, 24, 28, 32, 36, 40},
                       {5, 10, 15, 20, 25, 30, 35, 40, 45, 50},
                       {6, 12, 18, 24, 30, 36, 42, 48, 54, 60},
                       {7, 14, 21, 28, 35, 42, 49, 56, 63, 70},
                       {8, 16, 24, 32, 40, 48, 56, 64, 72, 80},
                       {9, 18, 27, 36, 45, 54, 63, 72, 81, 90},
{10, 20, 30, 40, 50, 60, 70, 80, 90, 100}};
dataVar.putVar(data);
file.putAtt("units", "meters");
file.putAtt("long_name", "example data");

What are some advantages of using C++ to create NetCDF plots?

Using C++ to create NetCDF plots allows for more flexibility and customization than using a tool like Panoply. C++ provides access to a wide range of libraries and tools for data manipulation and visualization, and allows for more fine-grained control over the plotting process.

What are some popular C++ libraries for creating NetCDF plots?

Some popular C++ libraries for creating NetCDF plots include the NetCDF C++ API, the Boost C++ libraries, and the VTK (Visualization Toolkit) library. These libraries provide a range of tools for working with NetCDF data and creating visualizations.

What are some common plot types that can be created using C++ and NetCDF?

Some common plot types that can be created using C++ and NetCDF include contour plots, line plots, surface plots, and vector plots. These plots can be used to visualize a wide range of scientific data, including atmospheric and oceanographic data.