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regutils.py
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regutils.py
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# -*- coding: utf-8 -*-
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""The regutils module provides classes for interfacing with the `niftyreg
<http://niftyreg.sourceforge.net>`_ utility command line tools.
The interfaces were written to work with niftyreg version 1.5.10
"""
import os
from ..base import TraitedSpec, File, traits, isdefined
from .base import get_custom_path, NiftyRegCommand, NiftyRegCommandInputSpec
from ...utils.filemanip import split_filename
class RegResampleInputSpec(NiftyRegCommandInputSpec):
""" Input Spec for RegResample. """
# Input reference file
ref_file = File(
exists=True,
desc="The input reference/target image",
argstr="-ref %s",
mandatory=True,
)
# Input floating file
flo_file = File(
exists=True,
desc="The input floating/source image",
argstr="-flo %s",
mandatory=True,
)
# Input deformation field
trans_file = File(
exists=True, desc="The input transformation file", argstr="-trans %s"
)
type = traits.Enum(
"res",
"blank",
argstr="-%s",
position=-2,
usedefault=True,
desc="Type of output",
)
# Output file name
out_file = File(
name_source=["flo_file"],
name_template="%s",
argstr="%s",
position=-1,
desc="The output filename of the transformed image",
)
# Interpolation type
inter_val = traits.Enum(
"NN", "LIN", "CUB", "SINC", desc="Interpolation type", argstr="-inter %d"
)
# Padding value
pad_val = traits.Float(desc="Padding value", argstr="-pad %f")
# Tensor flag
tensor_flag = traits.Bool(desc="Resample Tensor Map", argstr="-tensor ")
# Verbosity off
verbosity_off_flag = traits.Bool(argstr="-voff", desc="Turn off verbose output")
# PSF flag
desc = "Perform the resampling in two steps to resample an image to a \
lower resolution"
psf_flag = traits.Bool(argstr="-psf", desc=desc)
desc = "Minimise the matrix metric (0) or the determinant (1) when \
estimating the PSF [0]"
psf_alg = traits.Enum(0, 1, argstr="-psf_alg %d", desc=desc)
class RegResampleOutputSpec(TraitedSpec):
""" Output Spec for RegResample. """
out_file = File(desc="The output filename of the transformed image")
class RegResample(NiftyRegCommand):
"""Interface for executable reg_resample from NiftyReg platform.
Tool to resample floating image in the space of a defined reference image
given a transformation parametrisation generated by reg_aladin, reg_f3d or
reg_transform
`Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
Examples
--------
>>> from nipype.interfaces import niftyreg
>>> node = niftyreg.RegResample()
>>> node.inputs.ref_file = 'im1.nii'
>>> node.inputs.flo_file = 'im2.nii'
>>> node.inputs.trans_file = 'warpfield.nii'
>>> node.inputs.inter_val = 'LIN'
>>> node.inputs.omp_core_val = 4
>>> node.cmdline
'reg_resample -flo im2.nii -inter 1 -omp 4 -ref im1.nii -trans \
warpfield.nii -res im2_res.nii.gz'
"""
_cmd = get_custom_path("reg_resample")
input_spec = RegResampleInputSpec
output_spec = RegResampleOutputSpec
# Need this overload to properly constraint the interpolation type input
def _format_arg(self, name, spec, value):
if name == "inter_val":
inter_val = {"NN": 0, "LIN": 1, "CUB": 3, "SINC": 4}
return spec.argstr % inter_val[value]
else:
return super(RegResample, self)._format_arg(name, spec, value)
def _overload_extension(self, value, name=None):
path, base, _ = split_filename(value)
suffix = self.inputs.type
return os.path.join(path, "{0}_{1}.nii.gz".format(base, suffix))
class RegJacobianInputSpec(NiftyRegCommandInputSpec):
""" Input Spec for RegJacobian. """
# Reference file name
desc = "Reference/target file (required if specifying CPP transformations."
ref_file = File(exists=True, desc=desc, argstr="-ref %s")
# Input transformation file
trans_file = File(
exists=True,
desc="The input non-rigid transformation",
argstr="-trans %s",
mandatory=True,
)
type = traits.Enum(
"jac",
"jacL",
"jacM",
usedefault=True,
argstr="-%s",
position=-2,
desc="Type of jacobian outcome",
)
out_file = File(
name_source=["trans_file"],
name_template="%s",
desc="The output jacobian determinant file name",
argstr="%s",
position=-1,
)
class RegJacobianOutputSpec(TraitedSpec):
""" Output Spec for RegJacobian. """
out_file = File(desc="The output file")
class RegJacobian(NiftyRegCommand):
"""Interface for executable reg_resample from NiftyReg platform.
Tool to generate Jacobian determinant maps from transformation
parametrisation generated by reg_f3d
`Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
Examples
--------
>>> from nipype.interfaces import niftyreg
>>> node = niftyreg.RegJacobian()
>>> node.inputs.ref_file = 'im1.nii'
>>> node.inputs.trans_file = 'warpfield.nii'
>>> node.inputs.omp_core_val = 4
>>> node.cmdline
'reg_jacobian -omp 4 -ref im1.nii -trans warpfield.nii -jac \
warpfield_jac.nii.gz'
"""
_cmd = get_custom_path("reg_jacobian")
input_spec = RegJacobianInputSpec
output_spec = RegJacobianOutputSpec
def _overload_extension(self, value, name=None):
path, base, _ = split_filename(value)
suffix = self.inputs.type
return os.path.join(path, "{0}_{1}.nii.gz".format(base, suffix))
class RegToolsInputSpec(NiftyRegCommandInputSpec):
""" Input Spec for RegTools. """
# Input image file
in_file = File(
exists=True, desc="The input image file path", argstr="-in %s", mandatory=True
)
# Output file path
out_file = File(
name_source=["in_file"],
name_template="%s_tools.nii.gz",
desc="The output file name",
argstr="-out %s",
)
# Make the output image isotropic
iso_flag = traits.Bool(argstr="-iso", desc="Make output image isotropic")
# Set scale, slope to 0 and 1.
noscl_flag = traits.Bool(argstr="-noscl", desc="Set scale, slope to 0 and 1")
# Values outside the mask are set to NaN
mask_file = File(
exists=True, desc="Values outside the mask are set to NaN", argstr="-nan %s"
)
# Threshold the input image
desc = "Binarise the input image with the given threshold"
thr_val = traits.Float(desc=desc, argstr="-thr %f")
# Binarise the input image
bin_flag = traits.Bool(argstr="-bin", desc="Binarise the input image")
# Compute the mean RMS between the two images
rms_val = File(
exists=True, desc="Compute the mean RMS between the images", argstr="-rms %s"
)
# Perform division by image or value
div_val = traits.Either(
traits.Float,
File(exists=True),
desc="Divide the input by image or value",
argstr="-div %s",
)
# Perform multiplication by image or value
mul_val = traits.Either(
traits.Float,
File(exists=True),
desc="Multiply the input by image or value",
argstr="-mul %s",
)
# Perform addition by image or value
add_val = traits.Either(
traits.Float,
File(exists=True),
desc="Add to the input image or value",
argstr="-add %s",
)
# Perform subtraction by image or value
sub_val = traits.Either(
traits.Float,
File(exists=True),
desc="Add to the input image or value",
argstr="-sub %s",
)
# Downsample the image by a factor of 2.
down_flag = traits.Bool(
desc="Downsample the image by a factor of 2", argstr="-down"
)
# Smoothing using spline kernel
desc = "Smooth the input image using a cubic spline kernel"
smo_s_val = traits.Tuple(
traits.Float, traits.Float, traits.Float, desc=desc, argstr="-smoS %f %f %f"
)
# Change the resolution of the input image
chg_res_val = traits.Tuple(
traits.Float,
traits.Float,
traits.Float,
desc="Change the resolution of the input image",
argstr="-chgres %f %f %f",
)
# Smoothing using Gaussian kernel
desc = "Smooth the input image using a Gaussian kernel"
smo_g_val = traits.Tuple(
traits.Float, traits.Float, traits.Float, desc=desc, argstr="-smoG %f %f %f"
)
# Interpolation type
inter_val = traits.Enum(
"NN",
"LIN",
"CUB",
"SINC",
desc="Interpolation order to use to warp the floating image",
argstr="-interp %d",
)
class RegToolsOutputSpec(TraitedSpec):
""" Output Spec for RegTools. """
out_file = File(desc="The output file", exists=True)
class RegTools(NiftyRegCommand):
"""Interface for executable reg_tools from NiftyReg platform.
Tool delivering various actions related to registration such as
resampling the input image to a chosen resolution or remove the nan and
inf in the input image by a specified value.
`Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
Examples
--------
>>> from nipype.interfaces import niftyreg
>>> node = niftyreg.RegTools()
>>> node.inputs.in_file = 'im1.nii'
>>> node.inputs.mul_val = 4
>>> node.inputs.omp_core_val = 4
>>> node.cmdline
'reg_tools -in im1.nii -mul 4.0 -omp 4 -out im1_tools.nii.gz'
"""
_cmd = get_custom_path("reg_tools")
input_spec = RegToolsInputSpec
output_spec = RegToolsOutputSpec
_suffix = "_tools"
# Need this overload to properly constraint the interpolation type input
def _format_arg(self, name, spec, value):
if name == "inter_val":
inter_val = {"NN": 0, "LIN": 1, "CUB": 3, "SINC": 4}
return spec.argstr % inter_val[value]
else:
return super(RegTools, self)._format_arg(name, spec, value)
class RegAverageInputSpec(NiftyRegCommandInputSpec):
""" Input Spec for RegAverage. """
avg_files = traits.List(
File(exist=True),
position=1,
argstr="-avg %s",
sep=" ",
xor=[
"avg_lts_files",
"avg_ref_file",
"demean1_ref_file",
"demean2_ref_file",
"demean3_ref_file",
"warp_files",
],
desc="Averaging of images/affine transformations",
)
desc = "Robust average of affine transformations"
avg_lts_files = traits.List(
File(exist=True),
position=1,
argstr="-avg_lts %s",
sep=" ",
xor=[
"avg_files",
"avg_ref_file",
"demean1_ref_file",
"demean2_ref_file",
"demean3_ref_file",
"warp_files",
],
desc=desc,
)
desc = "All input images are resampled into the space of <reference image>\
and averaged. A cubic spline interpolation scheme is used for resampling"
avg_ref_file = File(
position=1,
argstr="-avg_tran %s",
xor=[
"avg_files",
"avg_lts_files",
"demean1_ref_file",
"demean2_ref_file",
"demean3_ref_file",
],
requires=["warp_files"],
desc=desc,
)
desc = "Average images and demean average image that have affine \
transformations to a common space"
demean1_ref_file = File(
position=1,
argstr="-demean1 %s",
xor=[
"avg_files",
"avg_lts_files",
"avg_ref_file",
"demean2_ref_file",
"demean3_ref_file",
],
requires=["warp_files"],
desc=desc,
)
desc = "Average images and demean average image that have non-rigid \
transformations to a common space"
demean2_ref_file = File(
position=1,
argstr="-demean2 %s",
xor=[
"avg_files",
"avg_lts_files",
"avg_ref_file",
"demean1_ref_file",
"demean3_ref_file",
],
requires=["warp_files"],
desc=desc,
)
desc = "Average images and demean average image that have linear and \
non-rigid transformations to a common space"
demean3_ref_file = File(
position=1,
argstr="-demean3 %s",
xor=[
"avg_files",
"avg_lts_files",
"avg_ref_file",
"demean1_ref_file",
"demean2_ref_file",
],
requires=["warp_files"],
desc=desc,
)
desc = "transformation files and floating image pairs/triplets to the \
reference space"
warp_files = traits.List(
File(exist=True),
position=-1,
argstr="%s",
sep=" ",
xor=["avg_files", "avg_lts_files"],
desc=desc,
)
out_file = File(genfile=True, position=0, desc="Output file name", argstr="%s")
class RegAverageOutputSpec(TraitedSpec):
""" Output Spec for RegAverage. """
out_file = File(desc="Output file name")
class RegAverage(NiftyRegCommand):
"""Interface for executable reg_average from NiftyReg platform.
Compute average matrix or image from a list of matrices or image.
The tool can be use to resample images given input transformation
parametrisation as well as to demean transformations in Euclidean or
log-Euclidean space.
This interface is different than the others in the way that the options
will be written in a command file that is given as a parameter.
`Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
Examples
--------
>>> from nipype.interfaces import niftyreg
>>> node = niftyreg.RegAverage()
>>> one_file = 'im1.nii'
>>> two_file = 'im2.nii'
>>> three_file = 'im3.nii'
>>> node.inputs.avg_files = [one_file, two_file, three_file]
>>> node.cmdline # doctest: +ELLIPSIS
'reg_average --cmd_file .../reg_average_cmd'
"""
_cmd = get_custom_path("reg_average")
input_spec = RegAverageInputSpec
output_spec = RegAverageOutputSpec
_suffix = "avg_out"
def _gen_filename(self, name):
if name == "out_file":
if isdefined(self.inputs.avg_lts_files):
return self._gen_fname(self._suffix, ext=".txt")
elif isdefined(self.inputs.avg_files):
_, _, _ext = split_filename(self.inputs.avg_files[0])
if _ext not in [".nii", ".nii.gz", ".hdr", ".img", ".img.gz"]:
return self._gen_fname(self._suffix, ext=_ext)
return self._gen_fname(self._suffix, ext=".nii.gz")
return None
def _list_outputs(self):
outputs = self.output_spec().get()
if isdefined(self.inputs.out_file):
outputs["out_file"] = self.inputs.out_file
else:
outputs["out_file"] = self._gen_filename("out_file")
return outputs
@property
def cmdline(self):
""" Rewrite the cmdline to write options in text_file."""
argv = super(RegAverage, self).cmdline
reg_average_cmd = os.path.join(os.getcwd(), "reg_average_cmd")
with open(reg_average_cmd, "w") as f:
f.write(argv)
return "%s --cmd_file %s" % (self.cmd, reg_average_cmd)
class RegTransformInputSpec(NiftyRegCommandInputSpec):
""" Input Spec for RegTransform. """
ref1_file = File(
exists=True,
desc="The input reference/target image",
argstr="-ref %s",
position=0,
)
ref2_file = File(
exists=True,
desc="The input second reference/target image",
argstr="-ref2 %s",
position=1,
requires=["ref1_file"],
)
def_input = File(
exists=True,
argstr="-def %s",
position=-2,
desc="Compute deformation field from transformation",
xor=[
"disp_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
)
disp_input = File(
exists=True,
argstr="-disp %s",
position=-2,
desc="Compute displacement field from transformation",
xor=[
"def_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
)
flow_input = File(
exists=True,
argstr="-flow %s",
position=-2,
desc="Compute flow field from spline SVF",
xor=[
"def_input",
"disp_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
)
comp_input = File(
exists=True,
argstr="-comp %s",
position=-3,
desc="compose two transformations",
xor=[
"def_input",
"disp_input",
"flow_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
requires=["comp_input2"],
)
comp_input2 = File(
exists=True, argstr="%s", position=-2, desc="compose two transformations"
)
desc = "Update s-form using the affine transformation"
upd_s_form_input = File(
exists=True,
argstr="-updSform %s",
position=-3,
desc=desc,
xor=[
"def_input",
"disp_input",
"flow_input",
"comp_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
requires=["upd_s_form_input2"],
)
desc = "Update s-form using the affine transformation"
upd_s_form_input2 = File(
exists=True, argstr="%s", position=-2, desc=desc, requires=["upd_s_form_input"]
)
inv_aff_input = File(
exists=True,
argstr="-invAff %s",
position=-2,
desc="Invert an affine transformation",
xor=[
"def_input",
"disp_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
)
inv_nrr_input = traits.Tuple(
File(exists=True),
File(exists=True),
desc="Invert a non-linear transformation",
argstr="-invNrr %s %s",
position=-2,
xor=[
"def_input",
"disp_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
)
half_input = File(
exists=True,
argstr="-half %s",
position=-2,
desc="Half way to the input transformation",
xor=[
"def_input",
"disp_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"make_aff_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
)
argstr_tmp = "-makeAff %f %f %f %f %f %f %f %f %f %f %f %f"
make_aff_input = traits.Tuple(
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
traits.Float,
argstr=argstr_tmp,
position=-2,
desc="Make an affine transformation matrix",
xor=[
"def_input",
"disp_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"aff_2_rig_input",
"flirt_2_nr_input",
],
)
desc = "Extract the rigid component from affine transformation"
aff_2_rig_input = File(
exists=True,
argstr="-aff2rig %s",
position=-2,
desc=desc,
xor=[
"def_input",
"disp_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"flirt_2_nr_input",
],
)
desc = "Convert a FLIRT affine transformation to niftyreg affine \
transformation"
flirt_2_nr_input = traits.Tuple(
File(exists=True),
File(exists=True),
File(exists=True),
argstr="-flirtAff2NR %s %s %s",
position=-2,
desc=desc,
xor=[
"def_input",
"disp_input",
"flow_input",
"comp_input",
"upd_s_form_input",
"inv_aff_input",
"inv_nrr_input",
"half_input",
"make_aff_input",
"aff_2_rig_input",
],
)
out_file = File(
genfile=True, position=-1, argstr="%s", desc="transformation file to write"
)
class RegTransformOutputSpec(TraitedSpec):
""" Output Spec for RegTransform. """
out_file = File(desc="Output File (transformation in any format)")
class RegTransform(NiftyRegCommand):
"""Interface for executable reg_transform from NiftyReg platform.
Tools to convert transformation parametrisation from one type to another
as well as to compose, inverse or half transformations.
`Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
Examples
--------
>>> from nipype.interfaces import niftyreg
>>> node = niftyreg.RegTransform()
>>> node.inputs.def_input = 'warpfield.nii'
>>> node.inputs.omp_core_val = 4
>>> node.cmdline # doctest: +ELLIPSIS
'reg_transform -omp 4 -def warpfield.nii .../warpfield_trans.nii.gz'
"""
_cmd = get_custom_path("reg_transform")
input_spec = RegTransformInputSpec
output_spec = RegTransformOutputSpec
_suffix = "_trans"
def _find_input(self):
inputs = [
self.inputs.def_input,
self.inputs.disp_input,
self.inputs.flow_input,
self.inputs.comp_input,
self.inputs.comp_input2,
self.inputs.upd_s_form_input,
self.inputs.inv_aff_input,
self.inputs.inv_nrr_input,
self.inputs.half_input,
self.inputs.make_aff_input,
self.inputs.aff_2_rig_input,
self.inputs.flirt_2_nr_input,
]
entries = []
for entry in inputs:
if isdefined(entry):
entries.append(entry)
_, _, ext = split_filename(entry)
if ext == ".nii" or ext == ".nii.gz" or ext == ".hdr":
return entry
if len(entries):
return entries[0]
return None
def _gen_filename(self, name):
if name == "out_file":
if isdefined(self.inputs.make_aff_input):
return self._gen_fname("matrix", suffix=self._suffix, ext=".txt")
if isdefined(self.inputs.comp_input) and isdefined(self.inputs.comp_input2):
_, bn1, ext1 = split_filename(self.inputs.comp_input)
_, _, ext2 = split_filename(self.inputs.comp_input2)
if ext1 in [".nii", ".nii.gz", ".hdr", ".img", ".img.gz"] or ext2 in [
".nii",
".nii.gz",
".hdr",
".img",
".img.gz",
]:
return self._gen_fname(bn1, suffix=self._suffix, ext=".nii.gz")
else:
return self._gen_fname(bn1, suffix=self._suffix, ext=ext1)
if isdefined(self.inputs.flirt_2_nr_input):
return self._gen_fname(
self.inputs.flirt_2_nr_input[0], suffix=self._suffix, ext=".txt"
)
input_to_use = self._find_input()
_, _, ext = split_filename(input_to_use)
if ext not in [".nii", ".nii.gz", ".hdr", ".img", ".img.gz"]:
return self._gen_fname(input_to_use, suffix=self._suffix, ext=ext)
else:
return self._gen_fname(input_to_use, suffix=self._suffix, ext=".nii.gz")
return None
def _list_outputs(self):
outputs = self.output_spec().get()
if isdefined(self.inputs.out_file):
outputs["out_file"] = self.inputs.out_file
else:
outputs["out_file"] = self._gen_filename("out_file")
return outputs
class RegMeasureInputSpec(NiftyRegCommandInputSpec):
""" Input Spec for RegMeasure. """
# Input reference file
ref_file = File(
exists=True,
desc="The input reference/target image",
argstr="-ref %s",
mandatory=True,
)
# Input floating file
flo_file = File(
exists=True,
desc="The input floating/source image",
argstr="-flo %s",
mandatory=True,
)
measure_type = traits.Enum(
"ncc",
"lncc",
"nmi",
"ssd",
mandatory=True,
argstr="-%s",
desc="Measure of similarity to compute",
)
out_file = File(
name_source=["flo_file"],
name_template="%s",
argstr="-out %s",
desc="The output text file containing the measure",
)
class RegMeasureOutputSpec(TraitedSpec):
""" Output Spec for RegMeasure. """
out_file = File(desc="The output text file containing the measure")
class RegMeasure(NiftyRegCommand):
"""Interface for executable reg_measure from NiftyReg platform.
Given two input images, compute the specified measure(s) of similarity
`Source code <https://cmiclab.cs.ucl.ac.uk/mmodat/niftyreg>`_
Examples
--------
>>> from nipype.interfaces import niftyreg
>>> node = niftyreg.RegMeasure()
>>> node.inputs.ref_file = 'im1.nii'
>>> node.inputs.flo_file = 'im2.nii'
>>> node.inputs.measure_type = 'lncc'
>>> node.inputs.omp_core_val = 4
>>> node.cmdline
'reg_measure -flo im2.nii -lncc -omp 4 -out im2_lncc.txt -ref im1.nii'
"""
_cmd = get_custom_path("reg_measure")
input_spec = RegMeasureInputSpec
output_spec = RegMeasureOutputSpec
def _overload_extension(self, value, name=None):
path, base, _ = split_filename(value)
suffix = self.inputs.measure_type
return os.path.join(path, "{0}_{1}.txt".format(base, suffix))