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Panoply netCDF, HDF and GRIB Data Viewer
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Panoply plots geo-referenced and other arrays fromnetCDF,HDF,GRIB,and other datasets.
Panoply is a cross-platform application that runs on Macintosh, Windows, Linux and other desktop computers.
The current version of Panoply is 4.12.1, released 2020-11-30.
With Panoply 4 you can:
- Slice and plot geo-referenced latitude-longitude, latitude-vertical, longitude-vertical, time-latitude or time-vertical arrays from larger multidimensional variables.
- Slice and plot 'generic' 2D arrays from larger multidimensional variables.
- Slice 1D arrays from larger multidimensional variables and create line plots.
- Combine two geo-referenced arrays in one plot by differencing, summing or averaging.
- Plot lon-lat data on a global or regional map using any of over 100 map projections or make a zonal average line plot.
- Overlay continent outlines or masks on lon-lat map plots.
- Use any of numerous color tables for the scale colorbar, or apply your own custom ACT, CPT, or RGB color table.
- Save plots to disk GIF, JPEG, PNG or TIFF bitmap images or as PDF or PostScript graphics files.
- Export lon-lat map plots in KMZ format.
- Export animations as MP4 video or as a collection of invididual frame images.
- Explore remote THREDDS and OpenDAP catalogs and open datasets served from them.
Get Panoply
Panoply requires that your computer have Java 9 (or later version) installed.
Color Tables and Map Overlays
Beginning with version 4.0, Panoply's 'standard' selection of color tables and map overlays is built into the application. Additional color tables and map overlays may be opened for a single session or added to your favorites library for continued use.
For even more scale color tables, J.J. Green'scpt-city websiteincludes many CPT format files that are compatible with Panoply.
Documentation and Credits
Contact
Please send bug reports, feature requests, etc., to Dr. Robert Schmunk [email protected] note that requests for assistance opening a dataset or interpreting the gridding of thedata within will probably require that you provide a copy of the dataset or instructions onwhere it might be downloaded.
Tip: For information on the current CDF version, enter the following at the IDL prompt:
The Common Data Format (CDF) is a file format that facilitates the storage and retrieval of multi-dimensional scientific data. CDF is a product of the National Space Science Data Center (NSSDC).
IDL’s CDF routines all begin with the prefix “CDF_”.
Programming Model
Creating CDF Files
The following table lists the basic IDL commands needed to create a new CDF file:
CDF_CREATE | Call this procedure to begin creating a new file. CDF_CREATE contains a number of keywords which affect the internal format of the new CDF file. |
CDF_VARCREATE | Define the variables to be used in the file. |
CDF_ATTPUT | Optionally, use attributes to describe the data. |
CDF_VARPUT | Write the appropriate data to the CDF file. |
CDF_CLOSE | Close the file. |
Reading CDF Files
The following table lists the basic commands needed to read data from a CDF file:
CDF_OPEN | Open an existing CDF file. |
CDF_INQUIRE | Call this function to find the general information about the contents of the CDF file. |
CDF_CONTROL | Call this function to obtain further information about the CDF file |
CDF_VARINQ | Retrieve the names, types, sizes, and other information about the variables in the CDF file. |
CDF_VARGET | Retrieve the variable values. |
CDF_ATTINQ | Optionally, retrieve the names, scope, and other information about the CDF file's attributes. |
CDF_ATTGET | Optionally, retrieve the attributes. |
CDF_CLOSE | Close the file. |
If the structure of the CDF file is already known, you do not need to call the inquiry routines—only CDF_OPEN, CDF_ATTGET, CDF_VARGET, and CDF_CLOSE are needed.
Type Conversion
Values are converted to the appropriate type before being written to a CDF file. For example, in this code snippet IDL converts the string “12” to a floating-point 12.0 before writing it:
Code Examples
Creating a CDF File
The following example demonstrates the basic procedure for creating a CDF file.
Variables and Attributes
Information in a CDF file consists of attributes (metadata) and collections of data records (variables).
Variables
IDL can create CDF files representing any data that can be stored in a zero- to eight-dimensional array. CDF supports two distinct types of variables, rVariables and zVariables. For reasons of efficiency, CDF uses variances to indicate whether data is unique between records and dimensions. For example, consider a data set of simultaneous surface temperatures at a variety of locations, the IDL code for creating the CDF file is included at the end of this section. A variable representing “GMT time” will vary from record to record, but not dimension to dimension (since all data are taken simultaneously). On the other hand, a variable such as longitude may not vary from record to record, but will vary from dimension to dimension. Record variance is set using the REC_VARY and REC_NOVARY keywords to CDF_VARCREATE, while dimensional variance is set through the DimVary argument to CDF_VARCREATE. In both cases, the default is varying data.
rVariables
rVariables (or regular variables) are multidimensional arrays of values, each having the same dimensions. That is, all rVariables in a CDF must have the same number of dimensions and dimension sizes. In IDL, the rVariable dimension sizes are declared when the CDF file is first created with CDF_CREATE. In the example at the end of this section, all variables except time are rVariables.
zVariables
zVariables (The z doesn’t stand for anything—the CDF people just like the letter z) are multidimensional arrays of values of the same data type. zVariables can have different dimensionality from other zVariables and rVariables. In general, zVariables are much more flexible, and therefore easier to use, than rVariables.
Attributes
Attributes can contain auxiliary information about an entire CDF file (global scope attributes or gAttributes), or about particular CDF variables (variable scope attributes or rAttributes/zAttributes depending on variable type). CDF attributes can be scalar or vector in nature, and of any valid datatype. In the case of vector, or multiple entry, attributes the user must keep track of the entry numbers (in CDF terms these are the gEntry, rEntry, or zEntry numbers depending on attribute type). For example, every rVariable in a CDF file might have an rAttribute named “Date”. A vector zVariable might have a zAttribute named “Location” with values such as [“Melbourne Beach”, “Crowley”,...]. A global attribute “MODS” might be used to keep track of the modification history of a CDF file (see CDF_ATTPUT). Note however, that variables cannot have multiple attributes with the same names. In IDL, CDF attributes are created with CDF_ATTPUT and retrieved with CDF_ATTGET.
Specifying Attributes and Variables
Variables and attributes can be referred to either by name or by their ID numbers in most CDF routines. For example, in the CDF_VARCREATE command shown in the example Type Conversion, the following command would have been equivalent:
CDF File Options
File Type
The SINGLE_FILE and MULTI_FILE keywords to CDF_CREATE allow CDFs to be written as either:
- all data in a single file, or
- a separate file for each variable, plus a master file for global information.
Data Encodings/Decodings
Cdf File Format
Keywords to CDF_CREATE allow files to be written in a variety of data encoding and decoding options. (For example, the /SUN_ENCODING keyword creates a file in the SUN native encoding scheme). The default encoding/decoding is network (XDR). All CDF encodings and decodings can be written or read on all platforms, but matching the encoding with the architecture used provides the best performance. If you work in a single-platform environment most of the time, select HOST_ENCODING for maximum performance. If you know that the CDF file will be transported to a computer using another architecture, specify the encoding for the target architecture or specify NETWORK_ENCODING (the default). Specifying the target architecture provides maximum performance on that architecture; specifying NETWORK_ENCODING provides maximum flexibility.