////////////////////////////////HistVizualizer Functions//////////////////////////////////////
bool
pcl::visualization::PCLPlotter::addFeatureHistogram (
const sensor_msgs::PointCloud2 &cloud, const std::string &field_name,
const std::string &id, int win_width, int win_height)
{
// Get the field
int field_idx = pcl::getFieldIndex (cloud, field_name);
if (field_idx == -1)
{
PCL_ERROR ("[addFeatureHistogram] Invalid field (%s) given!", field_name.c_str ());
return (false);
}
int hsize = cloud.fields[field_idx].count;
std::vector<double> array_x (hsize), array_y (hsize);
// Parse the cloud data and store it in the array
for (int i = 0; i < hsize; ++i)
{
array_x[i] = i;
float data;
// TODO: replace float with the real data type
memcpy (&data, &cloud.data[cloud.fields[field_idx].offset + i * sizeof (float)], sizeof (float));
array_y[i] = data;
}
this->addPlotData(array_x, array_y, id.c_str(), vtkChart::LINE);
setWindowSize (win_width, win_height);
return (true);
}
int main() {
const float a = 100.0f;
float host_x[N];
float host_y[N];
// initialize the input data
std::default_random_engine random_gen;
std::uniform_real_distribution<float> distribution(-N, N);
std::generate_n(host_x, N, [&]() { return distribution(random_gen); });
std::generate_n(host_y, N, [&]() { return distribution(random_gen); });
// CPU implementation of saxpy
float host_result_y[N];
for (int i = 0; i < N; i++) {
host_result_y[i] = a * host_x[i] + host_y[i];
}
// allocate data buffers on the accelerator and copy the data over
hc::array<float, 1> array_x(N);
hc::completion_future future_x = hc::copy_async(host_x, host_x + N, array_x);
hc::array<float, 1> array_y(N);
hc::completion_future future_y = hc::copy_async(host_y, host_y + N, array_y);
// wait for the copy operations to complete
future_x.wait();
future_y.wait();
// launch a GPU kernel to compute the saxpy in parallel
hc::completion_future future_pfe;
future_pfe = hc::parallel_for_each(hc::extent<1>(N)
, [&](hc::index<1> i) [[hc]] {
array_y[i] = a * array_x[i] + array_y[i];
});
// wait for the kernel to complete before copying results back
// to the host
future_pfe.wait();
future_y = hc::copy_async(array_y, host_y);
future_y.wait();
// verify the results
int errors = 0;
for (int i = 0; i < N; i++) {
if (fabs(host_y[i] - host_result_y[i]) > fabs(host_result_y[i] * 0.0001f))
errors++;
}
std::cout << errors << " errors" << std::endl;
return errors;
}
template <typename PointT> bool
pcl::visualization::PCLPlotter::addFeatureHistogram (
const pcl::PointCloud<PointT> &cloud, int hsize,
const std::string &id, int win_width, int win_height)
{
std::vector<double> array_x(hsize), array_y(hsize);
// Parse the cloud data and store it in the array
for (int i = 0; i < hsize; ++i)
{
array_x[i] = i;
array_y[i] = cloud.points[0].histogram[i];
}
this->addPlotData(array_x, array_y, id.c_str(), vtkChart::LINE);
setWindowSize (win_width, win_height);
return true;
}
bool
pcl::visualization::PCLPlotter::addFeatureHistogram (
const sensor_msgs::PointCloud2 &cloud,
const std::string &field_name,
const int index,
const std::string &id, int win_width, int win_height)
{
if (index < 0 || index >= static_cast<int> (cloud.width * cloud.height))
{
PCL_ERROR ("[addFeatureHistogram] Invalid point index (%d) given!\n", index);
return (false);
}
// Get the field
int field_idx = pcl::getFieldIndex (cloud, field_name);
if (field_idx == -1)
{
PCL_ERROR ("[addFeatureHistogram] Invalid field (%s) given!", field_name.c_str ());
return (false);
}
// Compute the total size of the fields
unsigned int fsize = 0;
for (size_t i = 0; i < cloud.fields.size (); ++i)
fsize += cloud.fields[i].count * pcl::getFieldSize (cloud.fields[i].datatype);
int hsize = cloud.fields[field_idx].count;
std::vector<double> array_x (hsize), array_y (hsize);
// Parse the cloud data and store it in the array
for (int i = 0; i < hsize; ++i)
{
array_x[i] = i;
float data;
// TODO: replace float with the real data type
memcpy (&data, &cloud.data[index * fsize + cloud.fields[field_idx].offset + i * sizeof (float)], sizeof (float));
array_y[i] = data;
}
this->addPlotData(array_x, array_y, id.c_str(), vtkChart::LINE);
setWindowSize (win_width, win_height);
return (true);
}
void
pcl::visualization::PCLPlotter::addPlotData (
PolynomialFunction const & p_function,
double x_min, double y_min,
char const *name,
int num_points,
std::vector<char> const &color)
{
std::vector<double> array_x(num_points), array_y(num_points);
double incr = (y_min - x_min)/num_points;
for (int i = 0; i < num_points; i++)
{
double xval = i*incr + x_min;
array_x[i] = xval;
array_y[i] = compute(p_function, xval);
}
this->addPlotData (array_x, array_y, name, vtkChart::LINE, color);
}
// an SAXPY example which uses hc::array
int main() {
const float a = 100.0f;
float x[N];
float y[N];
// initialize the input data
std::default_random_engine random_gen;
std::uniform_real_distribution<float> distribution(-N, N);
std::generate_n(x, N, [&]() { return distribution(random_gen); });
std::generate_n(y, N, [&]() { return distribution(random_gen); });
// make a copy of for the GPU implementation
float y_gpu[N];
std::copy_n(y, N, y_gpu);
// CPU implementation of saxpy
for (int i = 0; i < N; i++) {
y[i] = a * x[i] + y[i];
}
try {
hc::array<float, 1> array_x(N);
hc::completion_future future_x = hc::copy_async(x, x + N, array_x);
hc::array<float, 1> array_y(N);
hc::completion_future future_y = hc::copy_async(y_gpu, y_gpu + N, array_y);
future_x.wait();
future_y.wait();
// launch a GPU kernel to compute the saxpy in parallel
hc::completion_future future_kernel = hc::parallel_for_each(hc::extent<1>(N)
, [&](hc::index<1> i) __attribute((hc)) {
array_y[i] = a * array_x[i] + array_y[i];
});
future_kernel.wait();
hc::copy_async(array_y, y_gpu).wait();
} catch (std::exception& e) {
template <typename PointT> bool
pcl::visualization::PCLPlotter::addFeatureHistogram (
const pcl::PointCloud<PointT> &cloud,
const std::string &field_name,
const int index,
const std::string &id, int win_width, int win_height)
{
if (index < 0 || index >= cloud.points.size ())
{
PCL_ERROR ("[addFeatureHistogram] Invalid point index (%d) given!\n", index);
return (false);
}
// Get the fields present in this cloud
std::vector<sensor_msgs::PointField> fields;
// Check if our field exists
int field_idx = pcl::getFieldIndex<PointT> (cloud, field_name, fields);
if (field_idx == -1)
{
PCL_ERROR ("[addFeatureHistogram] The specified field <%s> does not exist!\n", field_name.c_str ());
return (false);
}
int hsize = fields[field_idx].count;
std::vector<double> array_x (hsize), array_y (hsize);
for (int i = 0; i < hsize; ++i)
{
array_x[i] = i;
float data;
// TODO: replace float with the real data type
memcpy (&data, reinterpret_cast<const char*> (&cloud.points[index]) + fields[field_idx].offset + i * sizeof (float), sizeof (float));
array_y[i] = data;
}
this->addPlotData(array_x, array_y, id.c_str(), vtkChart::LINE);
setWindowSize (win_width, win_height);
return (true);
}