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Merge pull request nipy#2459 from djarecka/fix_tutorials
Fix tutorials (continuation of nipy#1036)
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‎doc/devel/cmd_interface_devel.rst

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@@ -80,7 +80,7 @@ symbols. For an input defined in InputSpec to be included into the executed
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commandline ``argstr`` has to be included. Additionally inside the main
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interface class you need to specify the name of the executable by assigning it
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to the ``_cmd`` field. Also the main interface class needs to inherit from
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:class:`nipype.interfaces.base.CommandLine`:
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:class:`CommandLine <nipype.interfaces.base.core.CommandLine>`:
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.. testcode::
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‎doc/devel/matlab_example1.py

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from nipype.interfaces.matlab import MatlabCommand
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from nipype.interfaces.base import TraitedSpec, \
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BaseInterface, BaseInterfaceInputSpec, File
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import os
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from string import Template
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class ConmapTxt2MatInputSpec(BaseInterfaceInputSpec):
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in_file = File(exists=True, mandatory=True)
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out_file = File('cmatrix.mat', usedefault=True)
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class ConmapTxt2MatOutputSpec(TraitedSpec):
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out_file = File(exists=True)
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class ConmapTxt2Mat(BaseInterface):
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input_spec = ConmapTxt2MatInputSpec
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output_spec = ConmapTxt2MatOutputSpec
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def _run_interface(self, runtime):
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d = dict(in_file=self.inputs.in_file,
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out_file=self.inputs.out_file)
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# This is your MATLAB code template
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script = Template("""in_file = '$in_file';
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out_file = '$out_file';
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ConmapTxt2Mat(in_file, out_file);
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exit;
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""").substitute(d)
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# mfile = True will create an .m file with your script and executed.
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# Alternatively
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# mfile can be set to False which will cause the matlab code to be
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# passed
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# as a commandline argument to the matlab executable
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# (without creating any files).
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# This, however, is less reliable and harder to debug
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# (code will be reduced to
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# a single line and stripped of any comments).
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mlab = MatlabCommand(script=script, mfile=True)
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result = mlab.run()
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return result.runtime
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def _list_outputs(self):
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outputs = self._outputs().get()
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outputs['out_file'] = os.path.abspath(self.inputs.out_file)
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return outputs

‎doc/devel/matlab_example2.py

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from nipype.interfaces.base import traits
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from nipype.interfaces.base import TraitedSpec
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from nipype.interfaces.matlab import MatlabCommand, MatlabInputSpec
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class HelloWorldInputSpec(MatlabInputSpec):
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name = traits.Str(mandatory=True,
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desc='Name of person to say hello to')
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class HelloWorldOutputSpec(TraitedSpec):
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matlab_output = traits.Str()
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class HelloWorld(MatlabCommand):
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"""Basic Hello World that displays Hello <name> in MATLAB
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Returns
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-------
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matlab_output : capture of matlab output which may be
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parsed by user to get computation results
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Examples
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--------
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>>> hello = HelloWorld()
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>>> hello.inputs.name = 'hello_world'
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>>> out = hello.run()
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>>> print out.outputs.matlab_output
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"""
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input_spec = HelloWorldInputSpec
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output_spec = HelloWorldOutputSpec
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def _my_script(self):
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"""This is where you implement your script"""
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script = """
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disp('Hello %s Python')
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two = 1 + 1
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""" % (self.inputs.name)
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return script
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def run(self, **inputs):
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# Inject your script
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self.inputs.script = self._my_script()
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results = super(MatlabCommand, self).run(**inputs)
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stdout = results.runtime.stdout
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# Attach stdout to outputs to access matlab results
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results.outputs.matlab_output = stdout
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return results
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def _list_outputs(self):
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outputs = self._outputs().get()
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return outputs

‎doc/devel/matlab_interface_devel.rst

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How to wrap a MATLAB script
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===========================
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This is minimal script for wrapping MATLAB code. You should replace the MATLAB
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code template, and define approriate inputs and outputs.
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Example 1
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+++++++++
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.. testcode::
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from nipype.interfaces.matlab import MatlabCommand
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from nipype.interfaces.base import TraitedSpec, BaseInterface, BaseInterfaceInputSpec, File
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import os
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from string import Template
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class ConmapTxt2MatInputSpec(BaseInterfaceInputSpec):
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in_file = File(exists=True, mandatory=True)
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out_file = File('cmatrix.mat', usedefault=True)
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class ConmapTxt2MatOutputSpec(TraitedSpec):
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out_file = File(exists=True)
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class ConmapTxt2Mat(BaseInterface):
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input_spec = ConmapTxt2MatInputSpec
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output_spec = ConmapTxt2MatOutputSpec
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def _run_interface(self, runtime):
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d = dict(in_file=self.inputs.in_file,
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out_file=self.inputs.out_file)
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#this is your MATLAB code template
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script = Template("""in_file = ‘$in_file';
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out_file = ‘$out_file';
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ConmapTxt2Mat(in_file, out_file);
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exit;
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""").substitute(d)
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# mfile = True will create an .m file with your script and executed.
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# Alternatively
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# mfile can be set to False which will cause the matlab code to be
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# passed
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# as a commandline argument to the matlab executable
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# (without creating any files).
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# This, however, is less reliable and harder to debug
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# (code will be reduced to
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# a single line and stripped of any comments).
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This is a minimal script for wrapping MATLAB code. You should replace the MATLAB
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code template, and define approriate inputs and outputs.
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mlab = MatlabCommand(script=script, mfile=True)
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result = mlab.run()
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return result.runtime
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.. literalinclude:: matlab_example1.py
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def _list_outputs(self):
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outputs = self._outputs().get()
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outputs['out_file'] = os.path.abspath(self.inputs.out_file)
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return outputs
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.. admonition:: Example source code
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You can download :download:`the source code of this example <matlab_example1.py>`.
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Example 2
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By subclassing **MatlabCommand** for your main class, and **MatlabInputSpec** for your input and output spec, you gain access to some useful MATLAB hooks
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.. testcode::
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import os
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from nipype.interfaces.base import File, traits
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from nipype.interfaces.matlab import MatlabCommand, MatlabInputSpec
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class HelloWorldInputSpec( MatlabInputSpec):
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name = traits.Str( mandatory = True,
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desc = 'Name of person to say hello to')
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class HelloWorldOutputSpec( MatlabInputSpec):
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matlab_output = traits.Str( )
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class HelloWorld( MatlabCommand):
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""" Basic Hello World that displays Hello <name> in MATLAB
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Returns
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-------
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matlab_output : capture of matlab output which may be
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parsed by user to get computation results
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Examples
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--------
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>>> hello = HelloWorld()
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>>> hello.inputs.name = 'hello_world'
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>>> out = hello.run()
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>>> print(out.outputs.matlab_output)
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"""
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input_spec = HelloWorldInputSpec
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output_spec = HelloWorldOutputSpec
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def _my_script(self):
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"""This is where you implement your script"""
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script = """
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disp('Hello %s Python')
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two = 1 + 1
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"""%(self.inputs.name)
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return script
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def run(self, **inputs):
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## inject your script
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self.inputs.script = self._my_script()
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results = super(MatlabCommand, self).run( **inputs)
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stdout = results.runtime.stdout
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# attach stdout to outputs to access matlab results
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results.outputs.matlab_output = stdout
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return results
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def _list_outputs(self):
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outputs = self._outputs().get()
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return outputs
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By subclassing :class:`nipype.interfaces.matlab.MatlabCommand` for your main
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class, and :class:`nipype.interfaces.matlab.MatlabInputSpec` for your input and
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output spec, you gain access to some useful MATLAB hooks
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.. literalinclude:: matlab_example2.py
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.. admonition:: Example source code
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You can download :download:`the source code of this example <matlab_example2.py>`.
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.. include:: ../links_names.txt

‎doc/index.rst

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* - .. image:: images/nipype_architecture_overview2.png
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:width: 100 %
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- .. container::
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Current neuroimaging software offer users an incredible opportunity to

‎doc/users/function_interface.rst

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Unlike when using a function object, this input can be set like any other,
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meaning that you could write a function that outputs different function
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strings depending on some run-time contingencies, and connect that output
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the the ``function_str`` input of a downstream Function interface.
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the ``function_str`` input of a downstream Function interface.
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.. include:: ../links_names.txt

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