void run ()
{
Image::Buffer<float> dir_buf (argument[0]);
Image::Buffer<float>::voxel_type dir_vox (dir_buf);
Image::Header header (argument[0]);
header.dim(3) = header.dim(3)/3;
Image::Buffer<float> amp_buf (argument[1], header);
Image::Buffer<float>::voxel_type amp_vox (amp_buf);
Image::LoopInOrder loop (dir_vox, "converting directions to amplitudes...", 0, 3);
for (loop.start (dir_vox, amp_vox); loop.ok(); loop.next (dir_vox, amp_vox)) {
Math::Vector<float> dir (3);
dir_vox[3] = 0;
amp_vox[3] = 0;
while (dir_vox[3] < dir_vox.dim(3)) {
dir[0] = dir_vox.value(); ++dir_vox[3];
dir[1] = dir_vox.value(); ++dir_vox[3];
dir[2] = dir_vox.value(); ++dir_vox[3];
float amplitude = 0.0;
if (std::isfinite (dir[0]) && std::isfinite (dir[1]) && std::isfinite (dir[2]))
amplitude = Math::norm (dir);
amp_vox.value() = amplitude;
++amp_vox[3];
}
}
}
void run ()
{
Image::Buffer<node_t> nodes_data (argument[0]);
Image::Buffer<node_t>::voxel_type nodes (nodes_data);
Node_map node_map;
load_lookup_table (node_map);
Options opt = get_options ("config");
if (opt.size()) {
if (node_map.empty())
throw Exception ("Cannot properly interpret connectome config file if no lookup table is provided");
ConfigInvLookup config;
load_config (opt[0][0], config);
// Now that we know the configuration, can convert the lookup table to reflect the new indices
// If no corresponding entry exists in the config file, then the node doesn't get coloured
Node_map new_node_map;
for (Node_map::iterator i = node_map.begin(); i != node_map.end(); ++i) {
ConfigInvLookup::const_iterator existing = config.find (i->second.get_name());
if (existing != config.end())
new_node_map.insert (std::make_pair (existing->second, i->second));
}
if (new_node_map.empty())
throw Exception ("Config file and parcellation lookup table do not appear to belong to one another");
new_node_map.insert (std::make_pair (0, Node_info ("Unknown", Point<uint8_t> (0, 0, 0), 0)));
node_map = new_node_map;
}
if (node_map.empty()) {
INFO ("No lookup table provided; colouring nodes randomly");
node_t max_index = 0;
Image::LoopInOrder loop (nodes);
for (loop.start (nodes); loop.ok(); loop.next (nodes)) {
const node_t index = nodes.value();
if (index > max_index)
max_index = index;
}
node_map.insert (std::make_pair (0, Node_info ("None", 0, 0, 0, 0)));
Math::RNG rng;
for (node_t i = 1; i <= max_index; ++i) {
Point<uint8_t> colour;
do {
colour[0] = rng.uniform_int (255);
colour[1] = rng.uniform_int (255);
colour[2] = rng.uniform_int (255);
} while (int(colour[0]) + int(colour[1]) + int(colour[2]) < 100);
node_map.insert (std::make_pair (i, Node_info (str(i), colour)));
}
}
Image::Header H;
H.info() = nodes_data.info();
H.set_ndim (4);
H.dim(3) = 3;
H.datatype() = DataType::UInt8;
H.comments().push_back ("Coloured parcellation image generated by label2colour");
Image::Buffer<uint8_t> out_data (argument[1], H);
Image::Buffer<uint8_t>::voxel_type out (out_data);
Image::LoopInOrder loop (nodes, "Colourizing parcellated node image... ");
for (loop.start (nodes, out); loop.ok(); loop.next (nodes, out)) {
const node_t index = nodes.value();
Node_map::const_iterator i = node_map.find (index);
if (i == node_map.end()) {
out[3] = 0; out.value() = 0;
out[3] = 1; out.value() = 0;
out[3] = 2; out.value() = 0;
} else {
const Point<uint8_t>& colour (i->second.get_colour());
out[3] = 0; out.value() = colour[0];
out[3] = 1; out.value() = colour[1];
out[3] = 2; out.value() = colour[2];
}
}
}
void check_and_update (Image::Header& H, const conv_t conversion)
{
const size_t lmax = Math::SH::LforN (H.dim(3));
// Flag which volumes are m==0 and which are not
const ssize_t N = H.dim(3);
BitSet mzero_terms (N, false);
for (size_t l = 2; l <= lmax; l += 2)
mzero_terms[Math::SH::index (l, 0)] = true;
// Open in read-write mode if there's a chance of modification
typename Image::Buffer<value_type> buffer (H, (conversion != NONE));
typename Image::Buffer<value_type>::voxel_type v (buffer);
// Need to mask out voxels where the DC term is zero
Image::Info info_mask (H);
info_mask.set_ndim (3);
info_mask.datatype() = DataType::Bit;
Image::BufferScratch<bool> mask (info_mask);
Image::BufferScratch<bool>::voxel_type v_mask (mask);
size_t voxel_count = 0;
{
Image::LoopInOrder loop (v, "Masking image based on DC term...", 0, 3);
for (loop.start (v, v_mask); loop.ok(); loop.next (v, v_mask)) {
const value_type value = v.value();
if (value && std::isfinite (value)) {
v_mask.value() = true;
++voxel_count;
} else {
v_mask.value() = false;
}
}
}
// Get sums independently for each l
// Each order has a different power, and a different number of m!=0 volumes.
// Therefore, calculate the mean-square intensity for the m==0 and m!=0
// volumes independently, and report ratio for each harmonic order
Ptr<ProgressBar> progress;
if (App::log_level > 0 && App::log_level < 2)
progress = new ProgressBar ("Evaluating SH basis of image \"" + H.name() + "\"...", N-1);
std::vector<float> ratios;
for (size_t l = 2; l <= lmax; l += 2) {
double mzero_sum = 0.0, mnonzero_sum = 0.0;
Image::LoopInOrder loop (v, 0, 3);
for (v[3] = ssize_t (Math::SH::NforL(l-2)); v[3] != ssize_t (Math::SH::NforL(l)); ++v[3]) {
double sum = 0.0;
for (loop.start (v, v_mask); loop.ok(); loop.next (v, v_mask)) {
if (v_mask.value())
sum += Math::pow2 (value_type(v.value()));
}
if (mzero_terms[v[3]]) {
mzero_sum += sum;
DEBUG ("Volume " + str(v[3]) + ", m==0, sum " + str(sum));
} else {
mnonzero_sum += sum;
DEBUG ("Volume " + str(v[3]) + ", m!=0, sum " + str(sum));
}
if (progress)
++*progress;
}
const double mnonzero_MSoS = mnonzero_sum / (2.0 * l);
const float power_ratio = mnonzero_MSoS/mzero_sum;
ratios.push_back (power_ratio);
INFO ("SH order " + str(l) + ", ratio of m!=0 to m==0 power: " + str(power_ratio) +
", m==0 power: " + str (mzero_sum));
}
if (progress)
progress = NULL;
// First is ratio to be used for SH basis decision, second is gradient of regression
std::pair<float, float> regression = std::make_pair (0.0f, 0.0f);
size_t l_for_decision;
float power_ratio;
// The gradient will change depending on the current basis, so the threshold needs to also
// The gradient is as a function of l, not of even orders
float grad_threshold = 0.02;
switch (lmax) {
// Lmax == 2: only one order to use
case 2:
power_ratio = ratios.front();
l_for_decision = 2;
break;
// Lmax = 4: Use l=4 order to determine SH basis, can't check gradient since l=2 is untrustworthy
case 4:
power_ratio = ratios.back();
l_for_decision = 4;
break;
// Lmax = 6: Use l=4 order to determine SH basis, but checking the gradient is not reliable:
// artificially double the threshold so the power ratio at l=6 needs to be substantially
// different to l=4 to throw a warning
case 6:
regression = std::make_pair (ratios[1] - 2*(ratios[2]-ratios[1]), 0.5*(ratios[2]-ratios[1]));
power_ratio = ratios[1];
l_for_decision = 4;
grad_threshold *= 2.0;
break;
// Lmax >= 8: Do a linear regression from l=4 to l=lmax, project back to l=0
// (this is a more reliable quantification on poor data than l=4 alone)
default:
regression = get_regression (ratios);
power_ratio = regression.first;
l_for_decision = 0;
break;
}
// If the gradient is in fact positive (i.e. power ration increases for larger l), use the
// regression to pull the power ratio from l=lmax
if (regression.second > 0.0) {
l_for_decision = lmax;
power_ratio = regression.first + (lmax * regression.second);
}
DEBUG ("Power ratio for assessing SH basis is " + str(power_ratio) + " as " + (lmax < 8 ? "derived from" : "regressed to") + " l=" + str(l_for_decision));
// Threshold to make decision on what basis the data are currently stored in
value_type multiplier = 1.0;
if ((power_ratio > (5.0/3.0)) && (power_ratio < (7.0/3.0))) {
CONSOLE ("Image \"" + str(H.name()) + "\" appears to be in the old non-orthonormal basis");
switch (conversion) {
case NONE: break;
case OLD: break;
case NEW: multiplier = 1.0 / M_SQRT2; break;
case FORCE_OLDTONEW: multiplier = 1.0 / M_SQRT2; break;
case FORCE_NEWTOOLD: WARN ("Refusing to convert image \"" + H.name() + "\" from new to old basis, as data appear to already be in the old non-orthonormal basis"); return;
}
grad_threshold *= 2.0;
} else if ((power_ratio > (2.0/3.0)) && (power_ratio < (4.0/3.0))) {
CONSOLE ("Image \"" + str(H.name()) + "\" appears to be in the new orthonormal basis");
switch (conversion) {
case NONE: break;
case OLD: multiplier = M_SQRT2; break;
case NEW: break;
case FORCE_OLDTONEW: WARN ("Refusing to convert image \"" + H.name() + "\" from old to new basis, as data appear to already be in the new orthonormal basis"); return;
case FORCE_NEWTOOLD: multiplier = M_SQRT2; break;
}
} else {
multiplier = 0.0;
WARN ("Cannot make unambiguous decision on SH basis of image \"" + H.name()
+ "\" (power ratio " + (lmax < 8 ? "in" : "regressed to") + " " + str(l_for_decision) + " is " + str(power_ratio) + ")");
if (conversion == FORCE_OLDTONEW) {
WARN ("Forcing conversion of image \"" + H.name() + "\" from old to new SH basis on user request; however NO GUARANTEE IS PROVIDED on appropriateness of this conversion!");
multiplier = 1.0 / M_SQRT2;
} else if (conversion == FORCE_NEWTOOLD) {
WARN ("Forcing conversion of image \"" + H.name() + "\" from new to old SH basis on user request; however NO GUARANTEE IS PROVIDED on appropriateness of this conversion!");
multiplier = M_SQRT2;
}
}
// Decide whether the user needs to be warned about a poor diffusion encoding scheme
if (regression.second)
DEBUG ("Gradient of regression is " + str(regression.second) + "; threshold is " + str(grad_threshold));
if (Math::abs(regression.second) > grad_threshold) {
WARN ("Image \"" + H.name() + "\" may have been derived from poor directional encoding, or have some other underlying data problem");
WARN ("(m!=0 to m==0 power ratio changing by " + str(2.0*regression.second) + " per even order)");
}
// Adjust the image data in-place if necessary
if (multiplier && (multiplier != 1.0)) {
Image::LoopInOrder loop (v, 0, 3);
ProgressBar progress ("Modifying SH basis of image \"" + H.name() + "\"...", N-1);
for (v[3] = 1; v[3] != N; ++v[3]) {
if (!mzero_terms[v[3]]) {
for (loop.start (v); loop.ok(); loop.next (v))
v.value() *= multiplier;
}
++progress;
}
} else if (multiplier && (conversion != NONE)) {
INFO ("Image \"" + H.name() + "\" already in desired basis; nothing to do");
}
}
void run () {
Image::Header input_header (argument[0]);
const size_t filter_index = argument[1];
// Separate code path for FFT filter
if (!filter_index) {
// Gets preloaded by the FFT filter anyways, so just use a buffer
// FIXME Had to use cdouble throughout; seems to fail at compile time even trying to
// convert between cfloat and cdouble...
Image::Buffer<cdouble> input_data (input_header);
Image::Buffer<cdouble>::voxel_type input_voxel (input_data);
Image::Filter::FFT* filter = (dynamic_cast<Image::Filter::FFT*> (create_fft_filter (input_voxel)));
Image::Header header;
header.info() = filter->info();
set_strides (header);
filter->set_message (std::string("applying FFT filter to image " + std::string(argument[0]) + "..."));
if (get_options ("magnitude").size()) {
Image::BufferScratch<cdouble> temp_data (header, "complex FFT result");
Image::BufferScratch<cdouble>::voxel_type temp_voxel (temp_data);
(*filter) (input_voxel, temp_voxel);
header.datatype() = DataType::Float32;
Image::Buffer<float> output_data (argument[2], header);
Image::Buffer<float>::voxel_type output_voxel (output_data);
Image::LoopInOrder loop (output_voxel);
for (loop.start (temp_voxel, output_voxel); loop.ok(); loop.next (temp_voxel, output_voxel))
output_voxel.value() = std::abs (cdouble(temp_voxel.value()));
} else {
Image::Buffer<cdouble> output_data (argument[2], header);
Image::Buffer<cdouble>::voxel_type output_voxel (output_data);
(*filter) (input_voxel, output_voxel);
}
delete filter;
return;
}
Image::BufferPreload<float> input_data (input_header);
Image::BufferPreload<float>::voxel_type input_voxel (input_data);
Image::Filter::Base* filter = NULL;
switch (filter_index) {
case 0: assert (0); break;
case 1: filter = create_gradient_filter (input_voxel); break;
case 2: filter = create_median_filter (input_voxel); break;
case 3: filter = create_smooth_filter (input_voxel); break;
default: assert (0);
}
Image::Header header;
header.info() = filter->info();
set_strides (header);
Image::Buffer<float> output_data (argument[2], header);
Image::Buffer<float>::voxel_type output_voxel (output_data);
filter->set_message (std::string("applying ") + std::string(argument[1]) + " filter to image " + std::string(argument[0]) + "...");
switch (filter_index) {
case 0: assert (0); break;
case 1: (*dynamic_cast<Image::Filter::Gradient*> (filter)) (input_voxel, output_voxel); break;
case 2: (*dynamic_cast<Image::Filter::Median*> (filter)) (input_voxel, output_voxel); break;
case 3: (*dynamic_cast<Image::Filter::Smooth*> (filter)) (input_voxel, output_voxel); break;
}
delete filter;
}
void run () {
Point<> p[3];
for (size_t arg = 0; arg < 3; ++arg) {
std::vector<float> V = argument[arg];
if (V.size() != 3)
throw Exception ("coordinates must contain 3 elements");
p[arg][0] = V[0];
p[arg][1] = V[1];
p[arg][2] = V[2];
}
Image::Header header (argument[3]);
float vox = Math::pow (header.vox(0)*header.vox(1)*header.vox(2), 1.0f/3.0f);
Options opt = get_options ("vox");
if (opt.size())
vox = opt[0][0];
Point<> d1 = p[1] - p[0];
Point<> d2 = p[2] - p[0];
d1.normalise();
d2.normalise();
d2 = d2 - d1 * d1.dot(d2);
d2.normalise();
Point<> d3 = d1.cross(d2);
float min1 = std::numeric_limits<float>::infinity();
float min2 = std::numeric_limits<float>::infinity();
float max1 = -std::numeric_limits<float>::infinity();
float max2 = -std::numeric_limits<float>::infinity();
update_bounds (min1, min2, max1, max2, header, Point<int>(0,0,0), 0, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(0,0,0), 1, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(0,0,0), 2, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(1,0,0), 1, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(1,0,0), 2, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(0,1,0), 0, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(0,1,0), 2, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(0,0,1), 0, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(0,0,1), 1, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(1,1,0), 2, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(1,0,1), 1, p[0], d1, d2);
update_bounds (min1, min2, max1, max2, header, Point<int>(0,1,1), 0, p[0], d1, d2);
Point<> translation (p[0] + min1*d1 + min2*d2);
header.transform()(0,0) = d1[0];
header.transform()(1,0) = d1[1];
header.transform()(2,0) = d1[2];
header.transform()(0,1) = d2[0];
header.transform()(1,1) = d2[1];
header.transform()(2,1) = d2[2];
header.transform()(0,2) = d3[0];
header.transform()(1,2) = d3[1];
header.transform()(2,2) = d3[2];
header.transform()(0,3) = translation[0];
header.transform()(1,3) = translation[1];
header.transform()(2,3) = translation[2];
header.set_ndim (3);
header.dim (0) = (max1-min1) / vox;
header.dim (1) = (max2-min2) / vox;
header.dim (2) = 1;
header.vox(0) = header.vox(1) = header.vox(2) = vox;
header.datatype() = DataType::Bit;
header.DW_scheme().clear();
Image::Buffer<bool> roi_buffer (argument[4], header);
Image::Buffer<bool>::voxel_type roi (roi_buffer);
Image::LoopInOrder loop (roi);
for (loop.start (roi); loop.ok(); loop.next (roi))
roi.value() = true;
}