1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346
|
/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkMultiTransform_hxx
#define itkMultiTransform_hxx
namespace itk
{
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
auto
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::GetTransformCategory() const -> TransformCategoryEnum
{
// If all sub-transforms are the same, return that type. Otherwise
// return Unknown.
TransformCategoryEnum result = Self::TransformCategoryEnum::UnknownTransformCategory;
for (SizeValueType tind = 0; tind < this->GetNumberOfTransforms(); ++tind)
{
const TransformCategoryEnum type = this->GetNthTransformConstPointer(tind)->GetTransformCategory();
if (tind == 0)
{
result = type;
}
else
{
if (type != result)
{
result = Self::TransformCategoryEnum::UnknownTransformCategory;
break;
}
}
}
return result;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
bool
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::IsLinear() const
{
// If all sub-transforms are linear, return true.
for (SizeValueType tind = 0; tind < this->GetNumberOfTransforms(); ++tind)
{
if (!this->GetNthTransformConstPointer(tind)->IsLinear())
{
return false;
}
}
return true;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
auto
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::GetParameters() const -> const ParametersType &
{
/* Resize destructively. But if it's already this size, nothing is done so
* it's efficient. */
this->m_Parameters.SetSize(this->GetNumberOfParameters());
NumberOfParametersType offset{};
for (const TransformType * const transform : m_TransformQueue)
{
const ParametersType & subParameters = transform->GetParameters();
/* use vnl_vector data_block() to get data ptr */
std::copy_n(subParameters.data_block(), subParameters.Size(), &(this->m_Parameters.data_block())[offset]);
offset += subParameters.Size();
}
return this->m_Parameters;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
void
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::SetParameters(const ParametersType & inputParameters)
{
/* We do not copy inputParameters into m_Parameters,
* to avoid unnecessary copying. */
/* We assume input params are concatenation of the parameters of the
sub-transforms, in order of the queue from begin() to end(). */
/* Verify proper input size. */
if (inputParameters.Size() != this->GetNumberOfParameters())
{
itkExceptionMacro("Input parameter list size is not expected size. " << inputParameters.Size() << " instead of "
<< this->GetNumberOfParameters() << '.');
}
NumberOfParametersType offset{};
for (TransformType * const transform : m_TransformQueue)
{
/* If inputParams is same object as m_Parameters, we just pass
* each sub-transforms own m_Parameters in. This is needed to
* avoid unnecessary copying of parameters in the sub-transforms,
* while still allowing SetParameters to do any operations on the
* parameters to update member variable states. A hack. */
if (&inputParameters == &this->m_Parameters)
{
transform->SetParameters(transform->GetParameters());
}
else
{
const size_t parameterSize = transform->GetParameters().Size();
transform->CopyInParameters(&(inputParameters.data_block())[offset],
&(inputParameters.data_block())[offset] + parameterSize);
offset += static_cast<NumberOfParametersType>(parameterSize);
}
}
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
auto
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::GetFixedParameters() const
-> const FixedParametersType &
{
/* Resize destructively. But if it's already this size, nothing is done so
* it's efficient. */
this->m_FixedParameters.SetSize(this->GetNumberOfFixedParameters());
NumberOfParametersType offset{};
for (const TransformType * const transform : m_TransformQueue)
{
const FixedParametersType & subFixedParameters = transform->GetFixedParameters();
/* use vnl_vector data_block() to get data ptr */
std::copy_n(
subFixedParameters.data_block(), subFixedParameters.Size(), &(this->m_FixedParameters.data_block())[offset]);
offset += subFixedParameters.Size();
}
return this->m_FixedParameters;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
void
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::SetFixedParameters(
const FixedParametersType & inputParameters)
{
/* Verify proper input size. */
if (inputParameters.Size() != this->GetNumberOfFixedParameters())
{
itkExceptionMacro("Input parameter list size is not expected size. " << inputParameters.Size() << " instead of "
<< this->GetNumberOfFixedParameters() << '.');
}
/* Assumes input params are concatenation of the parameters of the
* sub transforms. */
NumberOfParametersType offset{};
/* Why is this done? Seems unnecessary. */
this->m_FixedParameters = inputParameters;
for (TransformType * const transform : m_TransformQueue)
{
const size_t fixedParameterSize = transform->GetFixedParameters().Size();
transform->CopyInFixedParameters(&(this->m_FixedParameters.data_block())[offset],
&(this->m_FixedParameters.data_block())[offset] + fixedParameterSize);
offset += static_cast<NumberOfParametersType>(fixedParameterSize);
}
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
auto
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::GetNumberOfParameters() const
-> NumberOfParametersType
{
/* Returns to total number of params in all transforms currently
* set to be used for optimized.
* NOTE: Ideally we'd optimize this to store the result and
* only re-calc when the composite object has been modified.
* However, it seems that number of parameter might change for dense
* field transforms (deformation, bspline) during processing and
* we wouldn't know that in this class, so this is safest. */
NumberOfParametersType result{};
for (SizeValueType tind = 0; tind < this->GetNumberOfTransforms(); ++tind)
{
/* Use raw pointer for efficiency */
const TransformType * transform = this->GetNthTransformConstPointer(tind);
result += transform->GetNumberOfParameters();
}
return result;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
auto
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::GetNumberOfLocalParameters() const
-> NumberOfParametersType
{
if (this->GetMTime() == this->m_LocalParametersUpdateTime)
{
return this->m_NumberOfLocalParameters;
}
this->m_LocalParametersUpdateTime = this->GetMTime();
/* Note that unlike in GetNumberOfParameters(), we don't expect the
* number of local parameters to possibly change, so we can cache
* the value. */
NumberOfParametersType result{};
for (SizeValueType tind = 0; tind < this->GetNumberOfTransforms(); ++tind)
{
const TransformType * transform = this->GetNthTransformConstPointer(tind);
result += transform->GetNumberOfLocalParameters();
}
this->m_NumberOfLocalParameters = result;
return result;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
auto
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::GetNumberOfFixedParameters() const
-> NumberOfParametersType
{
NumberOfParametersType result{};
for (SizeValueType tind = 0; tind < this->GetNumberOfTransforms(); ++tind)
{
const TransformType * transform = this->GetNthTransformConstPointer(tind);
result += transform->GetFixedParameters().Size();
}
return result;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
void
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::UpdateTransformParameters(
const DerivativeType & update,
ScalarType factor)
{
/* Update parameters within the sub-transforms. */
/* NOTE: We might want to thread this over each sub-transform, if we
* find we're working with longer lists of sub-transforms that do
* not implement any threading of their own for UpdateTransformParameters.
* Since the plan is for an UpdateTransformParameters functor that is
* user-assignable, we would need a method in the
* functor to return whether or not it does threading. If all sub-transforms
* return that they don't thread, we could do each sub-transform in its
* own thread from here. */
NumberOfParametersType numberOfParameters = this->GetNumberOfParameters();
if (update.Size() != numberOfParameters)
{
itkExceptionMacro("Parameter update size, " << update.Size()
<< ", must "
" be same as transform parameter size, "
<< numberOfParameters << std::endl);
}
NumberOfParametersType offset{};
for (SizeValueType tind = 0; tind < this->GetNumberOfTransforms(); ++tind)
{
// HACK: The following line looks wrong. We should not need to const_cast
TransformType * subtransform = this->GetNthTransformModifiablePointer(tind);
/* The input values are in a monolithic block, so we have to point
* to the subregion corresponding to the individual subtransform.
* This simply creates an Array object with data pointer, no
* memory is allocated or copied.
* NOTE: the use of const_cast is used to avoid a deep copy in the underlying vnl_vector
* by using LetArrayManageMemory=false, and being very careful here we can
* ensure that casting away const-ness does not result in memory corruption. */
auto * nonConstDataRefForPerformance =
const_cast<typename DerivativeType::ValueType *>(&((update.data_block())[offset]));
const DerivativeType subUpdate(nonConstDataRefForPerformance, subtransform->GetNumberOfParameters(), false);
/* This call will also call SetParameters, so don't need to call it
* explicitly here. */
subtransform->UpdateTransformParameters(subUpdate, factor);
offset += subtransform->GetNumberOfParameters();
}
this->Modified();
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
bool
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::GetInverse(Self * inverse) const
{
// NOTE: MultiTransform delegates to
// individual transform for setting FixedParameters
// inverse->SetFixedParameters( this->GetFixedParameters() );
inverse->ClearTransformQueue();
for (const TransformType * const transform : m_TransformQueue)
{
TransformTypePointer inverseTransform = (transform->GetInverseTransform()).GetPointer();
if (!inverseTransform)
{
inverse->ClearTransformQueue();
return false;
}
else
{
/* Add to end of queue to preserve transform order */
inverse->PushBackTransform(inverseTransform);
}
}
return true;
}
template <typename TParametersValueType, unsigned int VDimension, unsigned int VSubDimensions>
void
MultiTransform<TParametersValueType, VDimension, VSubDimensions>::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "TransformQueue: " << std::endl;
for (const TransformType * const transform : m_TransformQueue)
{
os << indent << ">>>>>>>>>" << std::endl;
transform->Print(os, indent);
}
}
} // end namespace itk
#endif
|