Writing An Algorithm


Mantid’s plugin architecture has been engineered so that it is easy for a developer, or intrepid user, to write an algorithm. This page is a primer for the user about to write their first algorithm and assumes no great knowledge of C++. It covers the basics, with links to more advanced options where appropriate. There is special description for the case when you are looking to add a custom MD conversion plugin.

Alternatively, you can implement your algorithm in Python. See Python Vs C++ Algorithms for a comparison of Mantid’s two programming languages.

All algorithms in Mantid inherit from a base Algorithm class, which provides the support and services required for running a specific algorithm and greatly simplifies the process of writing a new one.

Getting Started

Creating a new algorithm is simplified using class_maker.py

$ python buildconfig/class_maker.py --alg Algorithms MyAlg

which will give an amount of information about all that it did. The intentionally failing unit test, MyAlgTest.h, and user docs, MyAlg-v1.rst, will not be described here, but need to be updated before contributing. The excerpts below are the files created and formatted using the pre-commit hooks configured for c++ files. The exact contents of the generated code may change, the methods required do not.

Header file MyAlg_initial.h from class_maker.py

 1#pragma once
 3#include "MantidAPI/Algorithm.h"
 4#include "MantidAlgorithms/DllConfig.h"
 6namespace Mantid {
 7namespace Algorithms {
10 */
11class MANTID_ALGORITHMS_DLL MyAlg : public API::Algorithm {
13  const std::string name() const override;
14  int version() const override;
15  const std::string category() const override;
16  const std::string summary() const override;
19  void init() override;
20  void exec() override;
23} // namespace Algorithms
24} // namespace Mantid

Source file MyAlg_initial.cpp from class_maker.py

 8#include "MantidAlgorithms/MyAlg.h"
10namespace Mantid {
11namespace Algorithms {
12using Mantid::API::WorkspaceProperty;
13using Mantid::Kernel::Direction;
15// Register the algorithm into the AlgorithmFactory
20/// Algorithms name for identification. @see Algorithm::name
21const std::string MyAlg::name() const { return "MyAlg"; }
23/// Algorithm's version for identification. @see Algorithm::version
24int MyAlg::version() const { return 1; }
26/// Algorithm's category for identification. @see Algorithm::category
27const std::string MyAlg::category() const { return "TODO: FILL IN A CATEGORY"; }
29/// Algorithm's summary for use in the GUI and help. @see Algorithm::summary
30const std::string MyAlg::summary() const { return "TODO: FILL IN A SUMMARY"; }
33/** Initialize the algorithm's properties.
34 */
35void MyAlg::init() {
36  declareProperty(std::make_unique<WorkspaceProperty<API::Workspace>>("InputWorkspace", "", Direction::Input),
37                  "An input workspace.");
38  declareProperty(std::make_unique<WorkspaceProperty<API::Workspace>>("OutputWorkspace", "", Direction::Output),
39                  "An output workspace.");
43/** Execute the algorithm.
44 */
45void MyAlg::exec() {
46  // TODO Auto-generated execute stub
49} // namespace Algorithms
50} // namespace Mantid

At this point you will already have something that will compile and run. If you then start MantidWorkbench your algorithm will appear in the list of available algorithms and could be run. Of course, it won’t do anything of interest until you have written some algorithm code.

Coding the Algorithm

You will see that the algorithm has a variety of methods that need to be filled in. The example linked here is used throughout the majority of this document. The first few do not normally change very often

The full files described below are MyAlg.h and MyAlg.cpp. Only MyAlg.cpp will be shown in detail, but both are functional code that can be viewed as “simple” examples.

28/// Algorithms name for identification. @see Algorithm::name
29const std::string MyAlg::name() const { return "MyAlg"; }
31/// Algorithm's version for identification. @see Algorithm::version
32int MyAlg::version() const { return 1; }
34/// Algorithm's category for identification. @see Algorithm::category
35const std::string MyAlg::category() const { return "Examples"; }
37/// Algorithm's summary for use in the GUI and help. @see Algorithm::summary
38const std::string MyAlg::summary() const { return "Multiplies a workspace by a constant. There are some modes"; }

The name() method should not be verified.

The version() method normally returns 1. Mantid allows for having multiple versions of an algorithm registered which is facilitated by this method. The most common use cases for multiple versions are when the signature or underly assumptions are radically changed. Overall, few algorithms have more than one “version.”

The category() method aids users in finding the algorithm. The return can be a semilcolon (;) delimited string of categors/subcategories. You are highly encouraged to stay to the list of existing categories.

The summary() method is a brief description of the algorithms functionality. It is automatically re-used in the python docstring, and the generated help. The first sentence of the summary (up to the first period, .) is what appears in the generated gui for the algorithm.

You will see that the algorithm skeletons set up in the last section contain two larger methods called init and exec. These are described in sections below.


The algorithm base class defines an object, g_log. The g_log object enables access to the logging facilities of Mantid, and is an invaluable tool in understanding the running of your algorithms. When writing information to the logs, be aware of the various levels available and that the default level for users is set to notice.

The logging framework does have facility for flushing logs. However, logging std::endl will force the framework to flush at that time and developers should prever "\n" instead to not interfere with the framework.


The init() method written in your algorithm is called as part of the larger algorithm lifecycle. It is a private method that cannot be called directly, but one can call an algorithm’s inherited initialize() method for the desired effect. For details, look at the source of the API::Algorithm::initialize() .

The initialization (init) method is executed by the FrameworkManager when an algorithm is requested and must contain the declaration of the properties required by the algorithm. Atypically, it can also contain other initialization code such as the calculation of constants used by the algorithm, so long as this does not rely on the values of any of the properties.

Calls to the inherited declareProperty() method are used to add a property to this algorithm. See the properties page for more information on the types of properties supported and the example algorithms in UserAlgorithms (especially PropertyAlgorithm and WorkspaceAlgorithm) for further guidance on how to use them. There are many overloaded signatures for declareProperty() which are intended to make things easier, but can often be confusing due to the many options available.

43void MyAlg::init() {
44  auto instrumentValidator = std::make_shared<CompositeValidator>();
45  instrumentValidator->add<InstrumentValidator>();
46  declareProperty(
47      std::make_unique<WorkspaceProperty<MatrixWorkspace>>("InputWorkspace", "", Direction::Input, instrumentValidator),
48      "An input workspace.");
49  declareProperty("NumberToApply", EMPTY_DBL(), "Value to apply to workspace. This is extra information");
51  std::vector<std::string> propOptions{"X", "Y"};
52  declareProperty("WayToApply", propOptions.back(), std::make_shared<StringListValidator>(propOptions),
53                  "Which axis to apply values to");
55  declareProperty(std::make_unique<WorkspaceProperty<MatrixWorkspace>>("OutputWorkspace", "", Direction::Output),
56                  "An output workspace.");

This example shows a couple of different ways of declaring properites. They all have a couple of features in common:

  • Every property has a name. Here they are InputWorkspace, NumberToApply, WayToApply, and OutputWorkspace

  • Every property has a default value, many of which are effectively empty. Here they are empty workspace name, EMPTY_DBL() (special float value), "Y", and empty name. It is extremely unusual to specify a default workspace name

  • Every property has documentation. Most of the ones here are very uniformative, but the document on NumberToApply was written to demonstrate a particular point. Everything up to the first period (.) appears in the mouseover in the generated algorithm dialogs. The whole string appears in the user docs and python help.

An optional validator or directional argument (input, output or both) can also be appended. The syntax for other property types (WorkspaceProperty and ArrayProperty) is more complex - see the properties page.

Validation of inputs

While not part of the initialization, the optional validateInputs() method allows for cross-checking parameters. This particular example shows how one would ban a particular value, but normally a validator would be placed on the property itself for this behavior For more advanced validation, override the Algorithm::validateInputs() method. This is a method that returns a map where:

  • The key is the name of the property that is in error.

  • The value is a string describing the error.

This method allows you to provide validation that depends on several property values at once (something that cannot be done with IValidator). Its default implementation returns an empty map, signifying no errors.

It will be called in dialogs after parsing all inputs and setting the properties, but before executing. It is also called again in the execute() call, which will throw if this returns something.

This will set a “star” * label next to each property that is reporting an error. This makes it easier for users to find where they went wrong.

If your validateInputs() method validates an input workspace property, bear in mind that the user could provide a WorkspaceGroup (or an unexpected type of workspace) - when retrieving the property, check that casting it to its intended type succeeded before attempting to use it.

58std::map<std::string, std::string> MyAlg::validateInputs() {
59  std::map<std::string, std::string> issues;
61  if (!isDefault("NumberToApply")) {
62    const double value = getProperty("NumberToApply");
63    if (value == 42.) {
64      issues["NumberToApply"] = "We do cannot answer that question";
65    }
66  }
68  return issues;


Like initialization, the exec() method you write is not directly, but can be indirectly called via the execute() method of the algorith There are other methods that will do the same thing in different modes. All of them eventually call the API::Algorithm::executeInternal() which does the following

  • log a warning message if the algorithm is marked as deprecated

  • validate all of the input parameters individually against what they are set to checking for type and any validators that were defined

  • run the validateInputs() method

  • run the exec() method

  • add history to the Workspace annotating the parameters that the algorithm was called with

Additionally, the algorithm framework also handles things like sync/async calling, exception handling, and interaction with AnalysisDataService.

Fetching properties

Before the data can be processed, the first task is likely to be to fetch the values of the input properties. This uses the getProperty() method as follows

76  API::MatrixWorkspace_sptr inputWS = getProperty("InputWorkspace");
77  API::MatrixWorkspace_sptr outputWS = getProperty("OutputWorkspace");
78  const double number = getProperty("NumberToApply");
79  const std::string axisToApply = getPropertyValue("WayToApply");

where the type in the left hand side is the type of the property (int, double, std::string, std::vector…) and must match what was defined in the init(). Note that the value of a WorkspaceProperty is a shared pointer to the workspace, which is referred to as Mantid::API::Workspace_sptr or Mantid::API::Workspace_const_sptr. The latter should be used for input workspaces that will not need to be changed in the course of the algorithm. The output workspace is retrieved here to be used to detect if the algorithm is being performed in-place which will be discussed further down in this document. This example also uses the getPropertyValue() method which returns a string representation of the requested property (e.g. the name of the workspace).

If a handle is required on the property itself, rather than just its value, then the same method is used as follows:

Mantid::Kernel::Property* myProperty = getProperty("PropertyName");

This is useful, for example, for checking whether or not an optional property has been set (using Property’s isDefault() method). However, the algorithm has a convenience method isDefault(const std::string &) as well.

Creating the output workspace

Usually, the result of an algorithm will be stored in another new workspace and the algorithm will need to create that new workspace through a call to the WorkspaceFactory. For the (common) example where the output workspace should be of the same type and size as the input one, the code would read as follows:

outputWS = Mantid::API::WorkspaceFactory::Instance().create(inputWS);

where inputWS is a shared pointer to the input workspace. However, in many instances, one can simply clone the input workspace and work on the clone directly.

81  // set up the output
82  if (outputWS != inputWS) {
83    outputWS = inputWS->clone();
84  }

It is also important to, at some point, set the output workspace property to point at this workspace. This is achieved through a call to the setProperty method as follows:

109  // pass back the output workspace
110  setProperty("OutputWorkspace", outputWS);

where outputWorkspace is a shared pointer to the created output workspace.

Using workspaces

The bulk of most algorithms will involve the manipulation of the data contained in workspaces and information on how to interact with these is given here. The more advanced user may also want to refer to the full workspace documentation.

Those familiar with C++ should make use of private methods and data members to break up the execution code into more manageable and readable sections.

Further Features

The advanced user is referred to the full documentation page for the Algorithm base class to explore the full range of methods available for use within an algorithm. A few aspects are highlighted below.

Child Algorithms

Algorithms may wish to make use of the functionality of other algorithms as part of their execution. For example, if a units change is required the ConvertUnits algorithm could be used. Mantid therefore has the concept of a child algorithm and this is accessed through a call to the createChildAlgorithm method as follows:

Mantid::API::Algorithm_sptr childAlg = createChildAlgorithm("AlgorithmName");

This call will also initialise the algorithm, so the algorithm’s properties can then be set and it can be executed:

childAlg->setPropertyValue("number", 0);

Because Property is generic to input and output, the workspace pointers cannot be const when shared with a child algorithm.

Enhancing asynchronous running

Any algorithm can be run asynchronously without modification. However, some features are only enabled if code is added within the exec() method. Algorithm::interruption_point() should be called at appropriate intervals so that the algorithm’s execution can be interrupted. Algorithm::progress(double p) reports the progress of the algorithm. p must be between 0 (start) and 1 (finish).


It is fine to throw exceptions in your algorithms in the event of an unrecoverable failure. These will be caught in the base Algorithm class, which will report the failure of the algorithm.