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| 1 | +"""The ants visualisation module provides basic functions based on ITK. |
| 2 | + Change directory to provide relative paths for doctests |
| 3 | + >>> import os |
| 4 | + >>> filepath = os.path.dirname( os.path.realpath( __file__ ) ) |
| 5 | + >>> datadir = os.path.realpath(os.path.join(filepath, '../../testing/data')) |
| 6 | + >>> os.chdir(datadir) |
| 7 | +""" |
| 8 | + |
| 9 | +from ..base import (TraitedSpec, File, traits) |
| 10 | +from .base import ANTSCommand, ANTSCommandInputSpec |
| 11 | +from nipype.utils.filemanip import split_filename |
| 12 | +from nipype.interfaces.base import InputMultiPath |
| 13 | +from nipype.interfaces.traits_extension import isdefined |
| 14 | +import numpy as np |
| 15 | +import os |
| 16 | + |
| 17 | +class ConvertScalarImageToRGBInputSpec(ANTSCommandInputSpec): |
| 18 | + dimension=traits.Enum(3, 2, argstr= '%d', usedefault=True, |
| 19 | + desc='image dimension (2 or 3)', mandatory=True, |
| 20 | + position = 0) |
| 21 | + input_image=File(argstr='%s', exists=True, |
| 22 | + desc='Main input is a 3-D grayscale image.', mandatory=True, |
| 23 | + position = 1) |
| 24 | + output_image=traits.Str('rgb.nii.gz', argstr='%s', usedefault=True, |
| 25 | + desc=('rgb output image'), position = 2) |
| 26 | + mask_image=File('none', argstr='%s', exists=True, |
| 27 | + desc = 'mask image', position = 3, usedefault = True) |
| 28 | + colormap=traits.Str(argstr='%s', usedefault=True, |
| 29 | + desc=('Possible colormaps: grey, red, green, ' |
| 30 | + 'blue, copper, jet, hsv, spring, summer, ' |
| 31 | + 'autumn, winter, hot, cool, overunder, custom ' |
| 32 | + ), mandatory = True, position = 4) |
| 33 | + custom_color_map_file=traits.Str('none', argstr='%s', usedefault=True, |
| 34 | + desc = 'custom color map file', position = 5) |
| 35 | + minimum_input = traits.Int(argstr='%d', desc='minimum input', |
| 36 | + mandatory = True, position = 6) |
| 37 | + maximum_input = traits.Int(argstr='%d', desc='maximum input', |
| 38 | + mandatory = True, position = 7) |
| 39 | + minimum_RGB_output = traits.Int(0, usedefault=True, |
| 40 | + argstr='%d', desc = '', position = 8) |
| 41 | + maximum_RGB_output = traits.Int(255, usedefault=True, |
| 42 | + argstr='%d', desc = '', position = 9) |
| 43 | + |
| 44 | +class ConvertScalarImageToRGBOutputSpec(TraitedSpec): |
| 45 | + output_image= File(exists=True, desc='converted RGB image') |
| 46 | + |
| 47 | +class ConvertScalarImageToRGB(ANTSCommand): |
| 48 | + """ |
| 49 | + Examples |
| 50 | + -------- |
| 51 | + >>> from nipype.interfaces.ants.visualization import ConvertScalarImageToRGB |
| 52 | + >>> converter = ConvertScalarImageToRGB() |
| 53 | + >>> converter.inputs.dimension = 3 |
| 54 | + >>> converter.inputs.input_image = 'T1.nii.gz' |
| 55 | + >>> converter.inputs.colormap = 'jet' |
| 56 | + >>> converter.inputs.minimum_input = 0 |
| 57 | + >>> converter.inputs.maximum_input = 6 |
| 58 | + >>> converter.cmdline |
| 59 | + 'ConvertScalarImageToRGB 3 T1.nii.gz rgb.nii.gz none jet none 0 6 0 255' |
| 60 | + """ |
| 61 | + _cmd = 'ConvertScalarImageToRGB' |
| 62 | + input_spec = ConvertScalarImageToRGBInputSpec |
| 63 | + output_spec = ConvertScalarImageToRGBOutputSpec |
| 64 | + |
| 65 | + def _format_arg(self, opt, spec, val): |
| 66 | + return super(ConvertScalarImageToRGB, self)._format_arg(opt, spec, val) |
| 67 | + |
| 68 | + def _list_outputs(self): |
| 69 | + outputs = self._outputs().get() |
| 70 | + outputs['output_image'] = os.path.join(os.getcwd(), |
| 71 | + self.inputs.output_image) |
| 72 | + return outputs |
| 73 | + |
| 74 | + |
| 75 | +class CreateTiledMosaicInputSpec(ANTSCommandInputSpec): |
| 76 | + input_image = File(argstr='-i %s', exists=True, |
| 77 | + desc = 'Main input is a 3-D grayscale image.', |
| 78 | + mandatory = True) |
| 79 | + rgb_image= File(argstr='-r %s', exists = True, |
| 80 | + desc = ('An optional Rgb image can be added as an overlay.' |
| 81 | + 'It must have the same image' |
| 82 | + 'geometry as the input grayscale image.'), |
| 83 | + mandatory = True) |
| 84 | + mask_image = File(argstr = '-x %s', exists = True, |
| 85 | + desc = 'Specifies the ROI of the RGB voxels used.') |
| 86 | + alpha_value = traits.Float(argstr = '-a %.2f', |
| 87 | + desc = ('If an Rgb image is provided, render the overlay ' |
| 88 | + 'using the specified alpha parameter.')) |
| 89 | + output_image = traits.Str('output.png', argstr = '-o %s', |
| 90 | + desc = 'The output consists of the tiled mosaic image.', |
| 91 | + usedefault = True) |
| 92 | + tile_geometry = traits.Str(argstr = '-t %s',desc = ( |
| 93 | + 'The tile geometry specifies the number of rows and columns' |
| 94 | + 'in the output image. For example, if the user specifies "5x10", ' |
| 95 | + 'then 5 rows by 10 columns of slices are rendered. If R < 0 and C > ' |
| 96 | + '0 (or vice versa), the negative value is selected' |
| 97 | + 'based on direction.')) |
| 98 | + direction = traits.Int(argstr = '-d %d', desc = ('Specifies the direction of ' |
| 99 | + 'the slices. If no direction is specified, the ' |
| 100 | + 'direction with the coarsest spacing is chosen.')) |
| 101 | + pad_or_crop = traits.Str(argstr='-p %s', |
| 102 | + desc = 'argument passed to -p flag:' |
| 103 | + '[padVoxelWidth,<constantValue=0>]' |
| 104 | + '[lowerPadding[0]xlowerPadding[1],upperPadding[0]xupperPadding[1],' |
| 105 | + 'constantValue]' |
| 106 | + 'The user can specify whether to pad or crop a specified ' |
| 107 | + 'voxel-width boundary of each individual slice. For this ' |
| 108 | + 'program, cropping is simply padding with negative voxel-widths.' |
| 109 | + 'If one pads (+), the user can also specify a constant pad ' |
| 110 | + 'value (default = 0). If a mask is specified, the user can use ' |
| 111 | + 'the mask to define the region, by using the keyword "mask"' |
| 112 | + ' plus an offset, e.g. "-p mask+3".' |
| 113 | + ) |
| 114 | + slices = traits.Str(argstr='-s %s', |
| 115 | + desc = ('Number of slices to increment Slice1xSlice2xSlice3' |
| 116 | + '[numberOfSlicesToIncrement,<minSlice=0>,<maxSlice=lastSlice>]')) |
| 117 | + flip_slice = traits.Str(argstr = '-f %s', |
| 118 | + desc = ('flipXxflipY')) |
| 119 | + permute_axes = traits.Bool(argstr = '-g', desc = 'doPermute' |
| 120 | + ) |
| 121 | + |
| 122 | + |
| 123 | +class CreateTiledMosaicOutputSpec(TraitedSpec): |
| 124 | + output_image= File(exists=True, desc='image file') |
| 125 | + |
| 126 | +class CreateTiledMosaic(ANTSCommand): |
| 127 | + """The program CreateTiledMosaic in conjunction with ConvertScalarImageToRGB |
| 128 | + provides useful functionality for common image analysis tasks. The basic |
| 129 | + usage of CreateTiledMosaic is to tile a 3-D image volume slice-wise into |
| 130 | + a 2-D image. |
| 131 | +
|
| 132 | + Examples |
| 133 | + -------- |
| 134 | +
|
| 135 | + >>> from nipype.interfaces.ants.visualization import CreateTiledMosaic |
| 136 | + >>> mosaic_slicer = CreateTiledMosaic() |
| 137 | + >>> mosaic_slicer.inputs.input_image = 'T1.nii.gz' |
| 138 | + >>> mosaic_slicer.inputs.rgb_image = 'rgb.nii.gz' |
| 139 | + >>> mosaic_slicer.inputs.mask_image = 'mask.nii.gz' |
| 140 | + >>> mosaic_slicer.inputs.output_image = 'output.png' |
| 141 | + >>> mosaic_slicer.inputs.alpha_value = 0.5 |
| 142 | + >>> mosaic_slicer.inputs.direction = 2 |
| 143 | + >>> mosaic_slicer.inputs.pad_or_crop = '[ -15x -50 , -15x -30 ,0]' |
| 144 | + >>> mosaic_slicer.inputs.slices = '[2 ,100 ,160]' |
| 145 | + >>> mosaic_slicer.cmdline |
| 146 | + 'CreateTiledMosaic -a 0.50 -d 2 -i T1.nii.gz -x mask.nii.gz -o output.png -p [ -15x -50 , -15x -30 ,0] -r rgb.nii.gz -s [2 ,100 ,160]' |
| 147 | + """ |
| 148 | + |
| 149 | + _cmd = 'CreateTiledMosaic' |
| 150 | + input_spec = CreateTiledMosaicInputSpec |
| 151 | + output_spec = CreateTiledMosaicOutputSpec |
| 152 | + |
| 153 | + def _list_outputs(self): |
| 154 | + outputs = self._outputs().get() |
| 155 | + outputs['output_image'] = os.path.join(os.getcwd(), |
| 156 | + self.inputs.output_image) |
| 157 | + return outputs |
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