diff --git a/Core/Scan/UnitConverter1D.cpp b/Core/Scan/UnitConverter1D.cpp
index 9b28bd67ec22cf031a82358b136c1333c23ff58f..cd328dc92bdc9ddbd79827a8e7946bca8dcf2000 100644
--- a/Core/Scan/UnitConverter1D.cpp
+++ b/Core/Scan/UnitConverter1D.cpp
@@ -82,7 +82,7 @@ std::unique_ptr<IAxis> UnitConverter1D::createConvertedAxis(size_t i_axis, Axes:
std::unique_ptr<OutputData<double>>
UnitConverter1D::createConvertedData(const OutputData<double>& data, Axes::Units units) const
{
- if (data.getRank() != 1)
+ if (data.rank() != 1)
throw std::runtime_error("Error in UnitConverter1D::createConvertedData: unexpected "
"dimensions of the input data");
diff --git a/Core/Simulation/ISimulation.cpp b/Core/Simulation/ISimulation.cpp
index 614e82cef1c388ca2c6943e99c4f150d0224ebe0..e6c63e258e18a5c4acc2e9dc499661173f3ab8d7 100644
--- a/Core/Simulation/ISimulation.cpp
+++ b/Core/Simulation/ISimulation.cpp
@@ -32,7 +32,7 @@ namespace
bool detHasSameDimensions(const IDetector& detector, const OutputData<double>& data)
{
- if (data.getRank() != detector.dimension())
+ if (data.rank() != detector.dimension())
return false;
for (size_t i = 0; i < detector.dimension(); ++i)
diff --git a/Device/Data/LLData.h b/Device/Data/LLData.h
index ec311b771541aff7e92459e152c5cd4b25443e6e..f4bc08d73eefd27b0b4cced4f2b3b0cdc41369a9 100644
--- a/Device/Data/LLData.h
+++ b/Device/Data/LLData.h
@@ -53,7 +53,7 @@ public:
// retrieve basic info
size_t getTotalSize() const;
- inline size_t getRank() const { return m_rank; }
+ inline size_t rank() const { return m_rank; }
const int* getDimensions() const { return m_dims; }
T getTotalSum() const;
@@ -91,7 +91,7 @@ inline LLData<T>::LLData(size_t rank, const int* dimensions) : m_rank(0), m_dims
template <class T> LLData<T>::LLData(const LLData<T>& right) : m_rank(0), m_dims(0), m_data_array(0)
{
- allocate(right.getRank(), right.getDimensions());
+ allocate(right.rank(), right.getDimensions());
for (size_t i = 0; i < getTotalSize(); ++i) {
m_data_array[i] = right[i];
}
@@ -295,11 +295,11 @@ template <class T> LLData<T> operator/(const LLData<T>& left, const LLData<T>& r
template <class T> bool HaveSameDimensions(const LLData<T>& left, const LLData<T>& right)
{
- if (left.getRank() != right.getRank())
+ if (left.rank() != right.rank())
return false;
const int* ldims = left.getDimensions();
const int* rdims = right.getDimensions();
- for (size_t i = 0; i < left.getRank(); ++i) {
+ for (size_t i = 0; i < left.rank(); ++i) {
if (ldims[i] != rdims[i])
return false;
}
diff --git a/Device/Data/OutputData.cpp b/Device/Data/OutputData.cpp
index 88b623df6e00aa3e24ed198fb83025012e6879e9..25d9aaf6665f4969270413c0b5baf4528b3ad29c 100644
--- a/Device/Data/OutputData.cpp
+++ b/Device/Data/OutputData.cpp
@@ -22,7 +22,7 @@
template <> PyObject* OutputData<double>::getArray() const
{
std::vector<size_t> dimensions;
- for (size_t i = 0; i < getRank(); i++)
+ for (size_t i = 0; i < rank(); i++)
dimensions.push_back(axis(i).size());
// for rot90 of 2-dim arrays to conform with numpy
@@ -45,7 +45,7 @@ template <> PyObject* OutputData<double>::getArray() const
double* array_buffer = (double*)PyArray_DATA((PyArrayObject*)pyarray);
// filling numpy array with output_data
- if (getRank() == 2) {
+ if (rank() == 2) {
for (size_t index = 0; index < getAllocatedSize(); ++index) {
std::vector<int> axes_indices = getAxesBinIndices(index);
size_t offset =
diff --git a/Device/Data/OutputData.h b/Device/Data/OutputData.h
index 1bd07d28c39991dad42372e390aa641afa30616e..0e4cbe630d7c4bf202781450e8feb846dbad682b 100644
--- a/Device/Data/OutputData.h
+++ b/Device/Data/OutputData.h
@@ -56,7 +56,7 @@ public:
// retrieve basic info
//! Returns number of dimensions.
- size_t getRank() const { return m_value_axes.size(); }
+ size_t rank() const { return m_value_axes.size(); }
//! Returns total size of data buffer (product of bin number in every dimension).
size_t getAllocatedSize() const
@@ -271,7 +271,7 @@ template <class T> void OutputData<T>::copyFrom(const OutputData<T>& other)
template <class T> template <class U> void OutputData<T>::copyShapeFrom(const OutputData<U>& other)
{
clear();
- size_t rank = other.getRank();
+ size_t rank = other.rank();
for (size_t i = 0; i < rank; ++i)
addAxis(other.axis(i));
}
@@ -325,7 +325,7 @@ template <class T> inline std::vector<size_t> OutputData<T>::getAllSizes() const
{
ASSERT(m_ll_data);
std::vector<size_t> result;
- for (size_t i = 0; i < getRank(); ++i) {
+ for (size_t i = 0; i < rank(); ++i) {
int dim = m_ll_data->getDimensions()[i];
result.push_back(dim);
}
@@ -358,11 +358,11 @@ template <class T> std::vector<int> OutputData<T>::getAxesBinIndices(size_t glob
ASSERT(m_ll_data);
size_t remainder = global_index;
std::vector<int> result;
- result.resize(m_ll_data->getRank());
- for (size_t i = 0; i < m_ll_data->getRank(); ++i) {
- result[m_ll_data->getRank() - 1 - i] =
- (int)(remainder % m_value_axes[m_ll_data->getRank() - 1 - i]->size());
- remainder /= m_value_axes[m_ll_data->getRank() - 1 - i]->size();
+ result.resize(m_ll_data->rank());
+ for (size_t i = 0; i < m_ll_data->rank(); ++i) {
+ result[m_ll_data->rank() - 1 - i] =
+ (int)(remainder % m_value_axes[m_ll_data->rank() - 1 - i]->size());
+ remainder /= m_value_axes[m_ll_data->rank() - 1 - i]->size();
}
return result;
}
@@ -372,8 +372,8 @@ size_t OutputData<T>::getAxisBinIndex(size_t global_index, size_t i_selected_axi
{
ASSERT(m_ll_data);
size_t remainder(global_index);
- for (size_t i = 0; i < m_ll_data->getRank(); ++i) {
- size_t i_axis = m_ll_data->getRank() - 1 - i;
+ for (size_t i = 0; i < m_ll_data->rank(); ++i) {
+ size_t i_axis = m_ll_data->rank() - 1 - i;
size_t result = remainder % m_value_axes[i_axis]->size();
if (i_selected_axis == i_axis)
return result;
@@ -393,13 +393,13 @@ template <class T>
size_t OutputData<T>::toGlobalIndex(const std::vector<unsigned>& axes_indices) const
{
ASSERT(m_ll_data);
- if (axes_indices.size() != m_ll_data->getRank())
+ if (axes_indices.size() != m_ll_data->rank())
throw Exceptions::LogicErrorException(
"size_t OutputData<T>::toGlobalIndex() -> "
"Error! Number of coordinates must match rank of data structure");
size_t result = 0;
size_t step_size = 1;
- for (size_t i = m_ll_data->getRank(); i > 0; --i) {
+ for (size_t i = m_ll_data->rank(); i > 0; --i) {
if (axes_indices[i - 1] >= m_value_axes[i - 1]->size()) {
std::ostringstream message;
message << "size_t OutputData<T>::toGlobalIndex() -> Error. Index ";
@@ -418,13 +418,13 @@ template <class T>
size_t OutputData<T>::findGlobalIndex(const std::vector<double>& coordinates) const
{
ASSERT(m_ll_data);
- if (coordinates.size() != m_ll_data->getRank())
+ if (coordinates.size() != m_ll_data->rank())
throw Exceptions::LogicErrorException(
"OutputData<T>::findClosestIndex() -> "
"Error! Number of coordinates must match rank of data structure");
std::vector<unsigned> axes_indexes;
- axes_indexes.resize(m_ll_data->getRank());
- for (size_t i = 0; i < m_ll_data->getRank(); ++i)
+ axes_indexes.resize(m_ll_data->rank());
+ for (size_t i = 0; i < m_ll_data->rank(); ++i)
axes_indexes[i] = static_cast<unsigned>(m_value_axes[i]->findClosestIndex(coordinates[i]));
return toGlobalIndex(axes_indexes);
}
@@ -528,9 +528,9 @@ template <class T> bool OutputData<T>::isInitialized() const
{
if (!m_ll_data)
return false;
- if (getRank() != m_ll_data->getRank())
+ if (rank() != m_ll_data->rank())
return false;
- if (!getRank())
+ if (!rank())
return false;
return true;
}
@@ -581,9 +581,9 @@ inline bool OutputData<T>::hasSameDimensions(const OutputData<U>& right) const
return false;
if (!right.isInitialized())
return false;
- if (getRank() != right.getRank())
+ if (rank() != right.rank())
return false;
- for (size_t i_axis = 0; i_axis < getRank(); ++i_axis)
+ for (size_t i_axis = 0; i_axis < rank(); ++i_axis)
if (axis(i_axis).size() != right.axis(i_axis).size())
return false;
return true;
diff --git a/Device/Detector/DetectorMask.cpp b/Device/Detector/DetectorMask.cpp
index aa3644a5cc1212ba77511de146f51f2c40cb0dfe..6841513b130b61799216be1275feda6583568bcd 100644
--- a/Device/Detector/DetectorMask.cpp
+++ b/Device/Detector/DetectorMask.cpp
@@ -68,7 +68,7 @@ void DetectorMask::initMaskData(const OutputData<double>& data)
ASSERT(m_shapes.size() == m_mask_of_shape.size());
m_mask_data.clear();
- for (size_t dim = 0; dim < data.getRank(); ++dim)
+ for (size_t dim = 0; dim < data.rank(); ++dim)
m_mask_data.addAxis(data.axis(dim));
process_masks();
diff --git a/Device/Detector/RegionOfInterest.cpp b/Device/Detector/RegionOfInterest.cpp
index bd4241f84741493307b8762df5d7b819861e0f21..3503d1fc47740071678b570bf05c5993882a0887 100644
--- a/Device/Detector/RegionOfInterest.cpp
+++ b/Device/Detector/RegionOfInterest.cpp
@@ -27,7 +27,7 @@ RegionOfInterest::RegionOfInterest(const OutputData<double>& data, double xlow,
double xup, double yup)
: RegionOfInterest(xlow, ylow, xup, yup)
{
- if (data.getRank() != 2)
+ if (data.rank() != 2)
throw Exceptions::RuntimeErrorException("RegionOfInterest::RegionOfInterest() -> Error. "
"Data is not two-dimensional.");
diff --git a/Device/Histo/Histogram1D.h b/Device/Histo/Histogram1D.h
index 229508b5c2c6319eee491aa13c09334c7adb8a97..ee5a83029cd463b728de0d8e8636a99f5607305d 100644
--- a/Device/Histo/Histogram1D.h
+++ b/Device/Histo/Histogram1D.h
@@ -45,7 +45,7 @@ public:
Histogram1D* clone() const;
//! Returns the number of histogram dimensions
- size_t getRank() const { return 1; }
+ size_t rank() const { return 1; }
//! Increment bin with abscissa x with a weight.
int fill(double x, double weight = 1.0);
diff --git a/Device/Histo/Histogram2D.h b/Device/Histo/Histogram2D.h
index f3db774f0259c8e87080fb609071883911484b78..2ca08ab08f9f2cfbd96b4c979a27634e467bd3f4 100644
--- a/Device/Histo/Histogram2D.h
+++ b/Device/Histo/Histogram2D.h
@@ -56,7 +56,7 @@ public:
Histogram2D* clone() const;
//! Returns the number of histogram dimensions
- size_t getRank() const { return 2; }
+ size_t rank() const { return 2; }
//! Increment bin with abscissa x and ordinate y with a weight.
int fill(double x, double y, double weight = 1.0);
diff --git a/Device/Histo/IHistogram.cpp b/Device/Histo/IHistogram.cpp
index c8509382a7df1ad6645c6ca757d0b1ff0253f01e..b4083b18885a77586b06d47c12cff01ad86e0f30 100644
--- a/Device/Histo/IHistogram.cpp
+++ b/Device/Histo/IHistogram.cpp
@@ -87,7 +87,7 @@ size_t IHistogram::getGlobalBin(size_t binx, size_t biny) const
{
std::vector<unsigned> axes_indices;
axes_indices.push_back(static_cast<unsigned>(binx));
- if (getRank() == 2)
+ if (rank() == 2)
axes_indices.push_back(static_cast<unsigned>(biny));
return m_data.toGlobalIndex(axes_indices);
}
@@ -96,7 +96,7 @@ size_t IHistogram::findGlobalBin(double x, double y) const
{
std::vector<double> coordinates;
coordinates.push_back(x);
- if (getRank() == 2)
+ if (rank() == 2)
coordinates.push_back(y);
return m_data.findGlobalIndex(coordinates);
}
@@ -242,14 +242,14 @@ void IHistogram::reset()
IHistogram* IHistogram::createHistogram(const OutputData<double>& source)
{
- if (source.getRank() == 1) {
+ if (source.rank() == 1) {
return new Histogram1D(source);
- } else if (source.getRank() == 2) {
+ } else if (source.rank() == 2) {
return new Histogram2D(source);
} else {
std::ostringstream message;
message << "IHistogram::createHistogram(const OutputData<double>& source) -> Error. ";
- message << "The rank of source " << source.getRank() << " ";
+ message << "The rank of source " << source.rank() << " ";
message << "is not suitable for creation neither 1-dim nor 2-dim histograms.";
throw Exceptions::LogicErrorException(message.str());
}
@@ -267,31 +267,31 @@ IHistogram* IHistogram::createFrom(const std::vector<std::vector<double>>& data)
void IHistogram::check_x_axis() const
{
- if (getRank() < 1) {
+ if (rank() < 1) {
std::ostringstream message;
message << "IHistogram::check_x_axis() -> Error. X-xis does not exist. ";
- message << "Rank of histogram " << getRank() << "." << std::endl;
+ message << "Rank of histogram " << rank() << "." << std::endl;
throw Exceptions::LogicErrorException(message.str());
}
}
void IHistogram::check_y_axis() const
{
- if (getRank() < 2) {
+ if (rank() < 2) {
std::ostringstream message;
message << "IHistogram::check_y_axis() -> Error. Y-axis does not exist. ";
- message << "Rank of histogram " << getRank() << "." << std::endl;
+ message << "Rank of histogram " << rank() << "." << std::endl;
throw Exceptions::LogicErrorException(message.str());
}
}
void IHistogram::init_from_data(const OutputData<double>& source)
{
- if (getRank() != source.getRank()) {
+ if (rank() != source.rank()) {
std::ostringstream message;
message << "IHistogram::IHistogram(const OutputData<double>& data) -> Error. ";
- message << "The dimension of this histogram " << getRank() << " ";
- message << "is differ from the dimension of source " << m_data.getRank() << std::endl;
+ message << "The dimension of this histogram " << rank() << " ";
+ message << "is differ from the dimension of source " << m_data.rank() << std::endl;
throw Exceptions::LogicErrorException(message.str());
}
diff --git a/Device/Histo/IHistogram.h b/Device/Histo/IHistogram.h
index 7d87c6109b2f2d9305e6e8f0a4dc8698a2db4607..c31589a9d103c9766c0228b69ec79a80a20cad37 100644
--- a/Device/Histo/IHistogram.h
+++ b/Device/Histo/IHistogram.h
@@ -38,7 +38,7 @@ public:
virtual IHistogram* clone() const = 0;
//! Returns number of histogram dimensions.
- virtual size_t getRank() const = 0;
+ virtual size_t rank() const = 0;
//! Returns total number of histogram bins. For 2D histograms the result will be the product
//! of bin numbers along X and Y axes.
diff --git a/Device/Histo/SimulationResult.cpp b/Device/Histo/SimulationResult.cpp
index 0a2fc836d4bf4e5ad88457dd203e4a8aecb443a6..f14b7cf82916bd42ea95587e819e825be97ddaca 100644
--- a/Device/Histo/SimulationResult.cpp
+++ b/Device/Histo/SimulationResult.cpp
@@ -64,7 +64,7 @@ std::unique_ptr<OutputData<double>> SimulationResult::data(Axes::Units units) co
Histogram2D* SimulationResult::histogram2d(Axes::Units units) const
{
- if (m_data->getRank() != 2 || m_unit_converter->dimension() != 2)
+ if (m_data->rank() != 2 || m_unit_converter->dimension() != 2)
throw std::runtime_error("Error in SimulationResult::histogram2d: "
"dimension of data is not 2. Please use axis(), array() and "
"data() functions for 1D data.");
@@ -146,7 +146,7 @@ std::vector<double> SimulationResult::axis(size_t i_axis, Axes::Units units) con
void SimulationResult::checkDimensions() const
{
- if (m_data->getRank() != m_unit_converter->dimension())
+ if (m_data->rank() != m_unit_converter->dimension())
throw std::runtime_error("Error in SimulationResults::checkDimensions(): "
"dimensions of data and unit converter don't match");
}
diff --git a/Device/InputOutput/OutputDataWriteStrategy.cpp b/Device/InputOutput/OutputDataWriteStrategy.cpp
index 4820f77f4cd9d0643ae0604ecaf776f6af072dce..2cca13d9b31e7a05eed9f9b0df503dac345bd055 100644
--- a/Device/InputOutput/OutputDataWriteStrategy.cpp
+++ b/Device/InputOutput/OutputDataWriteStrategy.cpp
@@ -91,7 +91,7 @@ void OutputDataWriteINTStrategy::writeOutputData(const OutputData<double>& data,
{
output_stream << "# BornAgain Intensity Data\n\n";
- for (size_t i = 0; i < data.getRank(); ++i) {
+ for (size_t i = 0; i < data.rank(); ++i) {
std::string axis_name = std::string("axis") + std::to_string(i);
std::unique_ptr<IAxis> P_axis(data.axis(i).clone());
P_axis->setName(axis_name);
@@ -99,7 +99,7 @@ void OutputDataWriteINTStrategy::writeOutputData(const OutputData<double>& data,
output_stream << "# axis-" << i << "\n";
output_stream << (*P_axis) << "\n";
}
- size_t n_columns = data.axis(data.getRank() - 1).size();
+ size_t n_columns = data.axis(data.rank() - 1).size();
output_stream << "\n# data\n";
WriteOutputDataDoubles(data, output_stream, n_columns);
@@ -116,7 +116,7 @@ void OutputDataWriteNumpyTXTStrategy::writeOutputData(const OutputData<double>&
output_stream << "# BornAgain Intensity Data" << std::endl;
output_stream << "# Simple array suitable for numpy, matlab etc." << std::endl;
- const size_t dim = data.getRank();
+ const size_t dim = data.rank();
switch (dim) {
case 1:
Write1DRepresentation(data, output_stream);
diff --git a/Device/InputOutput/TiffHandler.cpp b/Device/InputOutput/TiffHandler.cpp
index d1d96361c811fd05356409c18ab8aa6c39caa3eb..e7d2f1eab860e1563dd10082833a67668a7de022 100644
--- a/Device/InputOutput/TiffHandler.cpp
+++ b/Device/InputOutput/TiffHandler.cpp
@@ -48,7 +48,7 @@ const OutputData<double>* TiffHandler::getOutputData() const
void TiffHandler::write(const OutputData<double>& data, std::ostream& output_stream)
{
m_data.reset(data.clone());
- if (m_data->getRank() != 2)
+ if (m_data->rank() != 2)
throw Exceptions::LogicErrorException("TiffHandler::write -> Error. "
"Only 2-dim arrays supported");
m_tiff = TIFFStreamOpen("MemTIFF", &output_stream);
diff --git a/Device/Instrument/IntensityDataFunctions.cpp b/Device/Instrument/IntensityDataFunctions.cpp
index 02474934e0111ba162fd853636a2727e38203109..79192d80037feef59a0bf711339d5ab24c54ff02 100644
--- a/Device/Instrument/IntensityDataFunctions.cpp
+++ b/Device/Instrument/IntensityDataFunctions.cpp
@@ -101,7 +101,7 @@ IntensityDataFunctions::createRelativeDifferenceData(const OutputData<double>& d
std::unique_ptr<OutputData<double>>
IntensityDataFunctions::createRearrangedDataSet(const OutputData<double>& data, int n)
{
- if (data.getRank() != 2)
+ if (data.rank() != 2)
throw Exceptions::LogicErrorException("IntensityDataFunctions::rotateDataByN90Deg()"
" -> Error! Works only on two-dimensional data");
n = (4 + n % 4) % 4;
@@ -148,12 +148,12 @@ std::unique_ptr<OutputData<double>>
IntensityDataFunctions::createClippedDataSet(const OutputData<double>& origin, double x1, double y1,
double x2, double y2)
{
- if (origin.getRank() != 2)
+ if (origin.rank() != 2)
throw Exceptions::LogicErrorException("IntensityDataFunctions::createClippedData()"
" -> Error! Works only on two-dimensional data");
std::unique_ptr<OutputData<double>> result(new OutputData<double>);
- for (size_t i_axis = 0; i_axis < origin.getRank(); i_axis++) {
+ for (size_t i_axis = 0; i_axis < origin.rank(); i_axis++) {
const IAxis& axis = origin.axis(i_axis);
IAxis* new_axis;
if (i_axis == 0)
@@ -229,7 +229,7 @@ void IntensityDataFunctions::coordinateFromBinf(double& x, double& y,
std::vector<std::vector<double>>
IntensityDataFunctions::create2DArrayfromOutputData(const OutputData<double>& data)
{
- if (data.getRank() != 2)
+ if (data.rank() != 2)
throw Exceptions::LogicErrorException(
"IntensityDataFunctions::create2DArrayfromOutputData() -> "
"Error! Works only on two-dimensional data");
diff --git a/Device/Intensity/ArrayUtils.h b/Device/Intensity/ArrayUtils.h
index 5822aa67fa9e76cf3baf5acbf7e0dc2905adc66a..b0d77bd8e97083ca628007cc034279f6aef14992 100644
--- a/Device/Intensity/ArrayUtils.h
+++ b/Device/Intensity/ArrayUtils.h
@@ -135,7 +135,7 @@ template <class T> std::pair<size_t, size_t> ArrayUtils::getShape(const T& data)
template <class T> decltype(auto) ArrayUtils::createVector1D(const T& data)
{
- if (data.getRank() != 1)
+ if (data.rank() != 1)
throw std::runtime_error("ArrayUtils::createVector1D() -> Error. Not 1D data.");
using value_type = typename T::value_type;
diff --git a/Device/Resolution/ConvolutionDetectorResolution.cpp b/Device/Resolution/ConvolutionDetectorResolution.cpp
index 5d240d029ded4429acee243a0be1a5ea6d3b6e92..cfa51c3543f75b5483d38f8cf29539932e4c894a 100644
--- a/Device/Resolution/ConvolutionDetectorResolution.cpp
+++ b/Device/Resolution/ConvolutionDetectorResolution.cpp
@@ -54,7 +54,7 @@ std::vector<const INode*> ConvolutionDetectorResolution::getChildren() const
void ConvolutionDetectorResolution::applyDetectorResolution(
OutputData<double>* p_intensity_map) const
{
- if (p_intensity_map->getRank() != m_dimension) {
+ if (p_intensity_map->rank() != m_dimension) {
throw Exceptions::RuntimeErrorException(
"ConvolutionDetectorResolution::applyDetectorResolution() -> Error! "
"Intensity map must have same dimension as detector resolution function.");
@@ -85,7 +85,7 @@ void ConvolutionDetectorResolution::apply1dConvolution(OutputData<double>* p_int
throw Exceptions::LogicErrorException(
"ConvolutionDetectorResolution::apply1dConvolution() -> Error! "
"No 1d resolution function present for convolution of 1d data.");
- if (p_intensity_map->getRank() != 1)
+ if (p_intensity_map->rank() != 1)
throw Exceptions::LogicErrorException(
"ConvolutionDetectorResolution::apply1dConvolution() -> Error! "
"Number of axes for intensity map does not correspond to the dimension of the map.");
@@ -121,7 +121,7 @@ void ConvolutionDetectorResolution::apply2dConvolution(OutputData<double>* p_int
throw Exceptions::LogicErrorException(
"ConvolutionDetectorResolution::apply2dConvolution() -> Error! "
"No 2d resolution function present for convolution of 2d data.");
- if (p_intensity_map->getRank() != 2)
+ if (p_intensity_map->rank() != 2)
throw Exceptions::LogicErrorException(
"ConvolutionDetectorResolution::apply2dConvolution() -> Error! "
"Number of axes for intensity map does not correspond to the dimension of the map.");
diff --git a/Device/Unit/IUnitConverter.cpp b/Device/Unit/IUnitConverter.cpp
index b3dd5928ea37523370529d0faa6652aae0edf64c..f3ff32b48d9e43b660be5c75abfaaab36f1baba1 100644
--- a/Device/Unit/IUnitConverter.cpp
+++ b/Device/Unit/IUnitConverter.cpp
@@ -35,7 +35,7 @@ std::string IUnitConverter::axisName(size_t i_axis, Axes::Units units_type) cons
std::unique_ptr<OutputData<double>>
IUnitConverter::createConvertedData(const OutputData<double>& data, Axes::Units units) const
{
- const size_t dim = data.getRank();
+ const size_t dim = data.rank();
std::unique_ptr<OutputData<double>> result(new OutputData<double>);
for (size_t i = 0; i < dim; ++i)
result->addAxis(*createConvertedAxis(i, units));
diff --git a/Examples/python/utils/plot_intensity_data.py b/Examples/python/utils/plot_intensity_data.py
index 65a8376b78678aa6ac60bcf3faf0c5dd6891de3f..077bdbc2c014527463b4760296f77a0089eeadc2 100755
--- a/Examples/python/utils/plot_intensity_data.py
+++ b/Examples/python/utils/plot_intensity_data.py
@@ -18,9 +18,9 @@ def plot_intensity_data(file_name, intensity_max=None):
data = ba.IntensityDataIOFactory.readIntensityData(file_name)
if intensity_max is None:
intensity_max = data.getMaximum()
- if data.getRank() == 1:
+ if data.rank() == 1:
plot_intensity_data_1d(data, intensity_max)
- elif data.getRank() == 2:
+ elif data.rank() == 2:
plot_intensity_data_2d(data, intensity_max)
else:
exit("Error in plot_intensity_data: wrong data rank")
diff --git a/Examples/python/utils/plot_intensity_data_diff.py b/Examples/python/utils/plot_intensity_data_diff.py
index 2bd7eada7cbc0ce72baa556ea1ae7b583f0910ed..0ed169f832d62a9e343350d8ebb1d62fa037f6d8 100755
--- a/Examples/python/utils/plot_intensity_data_diff.py
+++ b/Examples/python/utils/plot_intensity_data_diff.py
@@ -17,7 +17,7 @@ def plot_intensity_data_diff(filename1, filename2):
/ (np.abs(intensity_ref.array()) + np.abs(intensity_other.array()))
if data.max() == 0:
exit("Both data sets are equal, there is nothing to plot.")
- rank = intensity_ref.getRank()
+ rank = intensity_ref.rank()
if rank == 2:
pid.plot_raw_data_2d(data,
[intensity_ref.getXmin() / ba.deg, intensity_ref.getXmax() / ba.deg,
diff --git a/GUI/coregui/Models/IntensityDataItem.cpp b/GUI/coregui/Models/IntensityDataItem.cpp
index 7677940b165fc8f55d3548417a53a091a647f39e..e8240d860d9d04f25da00e50fe8ab2fef75a7d04 100644
--- a/GUI/coregui/Models/IntensityDataItem.cpp
+++ b/GUI/coregui/Models/IntensityDataItem.cpp
@@ -85,7 +85,7 @@ IntensityDataItem::IntensityDataItem() : DataItem("IntensityData")
void IntensityDataItem::setOutputData(OutputData<double>* data)
{
ASSERT(data && "Assertion failed in IntensityDataItem::setOutputData: nullptr data passed");
- if (data->getRank() != 2)
+ if (data->rank() != 2)
throw GUIHelpers::Error(
"Error in IntensityDataItem::setOutputData: cannot handle non-2D data");
DataItem::setOutputData(data);
diff --git a/GUI/coregui/Models/RealDataItem.cpp b/GUI/coregui/Models/RealDataItem.cpp
index dbbb78f00c1aed552e18f2dc0c295a0c0c6d4922..b3e03d80e63a852b40ab4eecac17379dc29e0872 100644
--- a/GUI/coregui/Models/RealDataItem.cpp
+++ b/GUI/coregui/Models/RealDataItem.cpp
@@ -103,10 +103,10 @@ const DataItem* RealDataItem::nativeData() const
void RealDataItem::setOutputData(OutputData<double>* data)
{
ASSERT(data && "Assertion failed in RealDataItem::setOutputData: passed data is nullptr");
- ASSERT(data->getRank() < 3 && data->getRank() > 0);
+ ASSERT(data->rank() < 3 && data->rank() > 0);
const QString& target_model_type =
- data->getRank() == 2 ? "IntensityData" : data->getRank() == 1 ? "SpecularData" : "";
+ data->rank() == 2 ? "IntensityData" : data->rank() == 1 ? "SpecularData" : "";
auto data_item = getItem(T_INTENSITY_DATA);
if (data_item && data_item->modelType() != target_model_type)
throw GUIHelpers::Error("Error in RealDataItem::setOutputData: trying to set data "
diff --git a/GUI/coregui/Models/SpecularDataItem.cpp b/GUI/coregui/Models/SpecularDataItem.cpp
index 24bea0d67b505de4c096c1d29feb3144345c469b..43ee5883d4eda09ad33d5d6c89d34851bb7e4fd6 100644
--- a/GUI/coregui/Models/SpecularDataItem.cpp
+++ b/GUI/coregui/Models/SpecularDataItem.cpp
@@ -44,7 +44,7 @@ SpecularDataItem::SpecularDataItem() : DataItem("SpecularData")
void SpecularDataItem::setOutputData(OutputData<double>* data)
{
ASSERT(data && "Assertion failed in SpecularDataItem::setOutputData: nullptr data passed");
- if (data->getRank() != 1)
+ if (data->rank() != 1)
throw GUIHelpers::Error(
"Error in SpecularDataItem::setOutputData: cannot handle non-1D data");
DataItem::setOutputData(data);
diff --git a/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp b/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp
index 85b4b4e76c33a85f225c052184bc866638d8c2e2..ef70e5c50017d2df9c66468d6c88e6bf0773abaf 100644
--- a/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp
+++ b/GUI/coregui/Views/ImportDataWidgets/ImportDataUtils.cpp
@@ -34,12 +34,12 @@ const QString filter_string_ba = "Intensity File (*.int *.gz *.tif *.tiff *.txt
const QString filter_string_ascii = "Intensity File (*.int *.int.gz *.txt *.csv *.dat *.ascii);;"
"Ascii column-wise data (*.*)";
-int getRank(const RealDataItem& item)
+int rank(const RealDataItem& item)
{
return static_cast<int>(item.shape().size());
}
-int getRank(const InstrumentItem& item)
+int rank(const InstrumentItem& item)
{
return static_cast<int>(item.shape().size());
}
@@ -138,13 +138,13 @@ ImportDataInfo ImportDataUtils::getFromImportAssistant(QString& fileName)
bool ImportDataUtils::Compatible(const InstrumentItem& instrumentItem,
const RealDataItem& realDataItem)
{
- return getRank(instrumentItem) == getRank(realDataItem);
+ return rank(instrumentItem) == rank(realDataItem);
}
std::unique_ptr<OutputData<double>>
ImportDataUtils::CreateSimplifiedOutputData(const OutputData<double>& data)
{
- const size_t data_rank = data.getRank();
+ const size_t data_rank = data.rank();
if (data_rank > 2 || data_rank < 1)
throw std::runtime_error("Error in ImportDataUtils::CreateSimplifiedOutputData: passed "
"array is neither 1D nor 2D");
diff --git a/GUI/coregui/utils/ImportDataInfo.cpp b/GUI/coregui/utils/ImportDataInfo.cpp
index ff4c191430d656ed768768df654bcf7a8f1bf57c..a44d6bc101aa046e7dfad25014b8a3c8f05b3979 100644
--- a/GUI/coregui/utils/ImportDataInfo.cpp
+++ b/GUI/coregui/utils/ImportDataInfo.cpp
@@ -79,7 +79,7 @@ size_t ImportDataInfo::dataRank() const
{
if (!m_data)
return 0;
- return m_data->getRank();
+ return m_data->rank();
}
QString ImportDataInfo::unitsLabel() const
@@ -92,7 +92,7 @@ QString ImportDataInfo::axisLabel(size_t axis_index) const
if (!m_data)
return "";
- const size_t rank = m_data->getRank();
+ const size_t rank = m_data->rank();
if (rank == 2)
return axis_index == 0 ? "X [nbins]" : "Y [nbins]";
else if (rank == 1) {
@@ -109,7 +109,7 @@ void ImportDataInfo::checkValidity()
{
if (!m_data)
return;
- auto iter = available_units.find(m_data->getRank());
+ auto iter = available_units.find(m_data->rank());
if (iter == available_units.end())
throw GUIHelpers::Error("Error in ImportDataInfo constructor: unsupported data type");
for (auto& value : iter->second)
diff --git a/Tests/Functional/Python/PyCore/intensitydata.py b/Tests/Functional/Python/PyCore/intensitydata.py
index dd17475dcb3f88aee80ea4cc0dcbba8d6ee86700..7a3b93636437016510e6c3164db2aea1be7487c5 100644
--- a/Tests/Functional/Python/PyCore/intensitydata.py
+++ b/Tests/Functional/Python/PyCore/intensitydata.py
@@ -13,7 +13,7 @@ class IntensityDataTest(unittest.TestCase):
def test_empty_data(self):
data = ba.IntensityData()
self.assertEqual(1, data.getAllocatedSize())
- self.assertEqual(0, data.getRank())
+ self.assertEqual(0, data.rank())
self.assertEqual(0, data.totalSum())
def test_create_1d_output_data_from_numpy(self):
@@ -38,7 +38,7 @@ class IntensityDataTest(unittest.TestCase):
data = ba.IntensityData()
data.addAxis(axis0)
self.assertEqual(20, data.getAllocatedSize())
- self.assertEqual(1, data.getRank())
+ self.assertEqual(1, data.rank())
self.assertEqual(0, data.totalSum())
def test_create_2d_object(self):
@@ -46,7 +46,7 @@ class IntensityDataTest(unittest.TestCase):
data.addAxis("axis0", 10, 0.0, 10.0)
data.addAxis("axis1", 20, 0.0, 20.0)
self.assertEqual(200, data.getAllocatedSize())
- self.assertEqual(2, data.getRank())
+ self.assertEqual(2, data.rank())
self.assertEqual(0, data.totalSum())
data.setAllTo(1.0)
self.assertEqual(200.0, data.totalSum())
@@ -59,7 +59,7 @@ class IntensityDataTest(unittest.TestCase):
simulation.setDetectorParameters(10, -1.0, 1.0, 100, 0.0, 2.0)
data = simulation.result().histogram2d()
self.assertEqual(1000, data.getTotalNumberOfBins())
- self.assertEqual(2, data.getRank())
+ self.assertEqual(2, data.rank())
self.assertEqual(0, data.integral())
self.assertEqual(10, data.xAxis().size())
diff --git a/Tests/Functional/Python/PyCore/intensitydata_io.py b/Tests/Functional/Python/PyCore/intensitydata_io.py
index 73585a7440802c9e28f2cc4fb3fd1a38fb7df09b..f764771c8484075f7d83d0eebb197507748dff93 100644
--- a/Tests/Functional/Python/PyCore/intensitydata_io.py
+++ b/Tests/Functional/Python/PyCore/intensitydata_io.py
@@ -19,9 +19,9 @@ def is_the_same_data(data1, data2):
"""
if data1.getAllocatedSize() != data2.getAllocatedSize():
return False
- if data1.getRank() != data2.getRank():
+ if data1.rank() != data2.rank():
return False
- for i in range(0, data1.getRank()):
+ for i in range(0, data1.rank()):
if data1.axis(i) != data2.axis(i):
return False
for i in range(0, data1.getAllocatedSize()):
diff --git a/Tests/Functional/Python/PyCore/intensitydata_io_tiff.py b/Tests/Functional/Python/PyCore/intensitydata_io_tiff.py
index 41140fc918fabc6c3d18fbf13766492cecf8a966..8ae1ad26bb573b3d8aa2cc250fc558bde0d78fa8 100644
--- a/Tests/Functional/Python/PyCore/intensitydata_io_tiff.py
+++ b/Tests/Functional/Python/PyCore/intensitydata_io_tiff.py
@@ -20,9 +20,9 @@ def is_the_same_data(data1, data2):
"""
if data1.getAllocatedSize() != data2.getAllocatedSize():
return False
- if data1.getRank() != data2.getRank():
+ if data1.rank() != data2.rank():
return False
- for i in range(0, data1.getRank()):
+ for i in range(0, data1.rank()):
if data1.axis(i) != data2.axis(i):
return False
for i in range(0, data1.getAllocatedSize()):
diff --git a/Tests/UnitTests/Core/Axes/Histogram1DTest.cpp b/Tests/UnitTests/Core/Axes/Histogram1DTest.cpp
index c7429c11346fa1fb71538e35ab6faf6ff982c097..4630d9179ea55180e26967c4d122842d9221acaf 100644
--- a/Tests/UnitTests/Core/Axes/Histogram1DTest.cpp
+++ b/Tests/UnitTests/Core/Axes/Histogram1DTest.cpp
@@ -10,7 +10,7 @@ TEST_F(Histogram1DTest, FixedBinConstructor)
{
Histogram1D hist(5, 0.0, 5.0);
- EXPECT_EQ(size_t(1), hist.getRank());
+ EXPECT_EQ(size_t(1), hist.rank());
EXPECT_EQ(size_t(5), hist.getTotalNumberOfBins());
EXPECT_EQ(0.0, hist.getXmin());
EXPECT_EQ(5.0, hist.getXmax());
@@ -137,7 +137,7 @@ TEST_F(Histogram1DTest, CreateHistogram)
}
std::unique_ptr<IHistogram> hist(IHistogram::createHistogram(data));
- EXPECT_EQ(size_t(1), hist->getRank());
+ EXPECT_EQ(size_t(1), hist->rank());
EXPECT_EQ(data.getAllocatedSize(), hist->getNbinsX());
EXPECT_EQ(data.axis(0).getMin(), hist->getXmin());
EXPECT_EQ(data.axis(0).getMax(), hist->getXmax());
@@ -159,7 +159,7 @@ TEST_F(Histogram1DTest, CreateOutputData)
}
std::unique_ptr<OutputData<double>> data(hist.createOutputData(IHistogram::DataType::INTEGRAL));
- EXPECT_EQ(size_t(1), data->getRank());
+ EXPECT_EQ(size_t(1), data->rank());
EXPECT_EQ(data->getAllocatedSize(), hist.getNbinsX());
EXPECT_EQ(data->axis(0).getMin(), hist.getXmin());
EXPECT_EQ(data->axis(0).getMax(), hist.getXmax());
diff --git a/Tests/UnitTests/Core/Axes/Histogram2DTest.cpp b/Tests/UnitTests/Core/Axes/Histogram2DTest.cpp
index 1e8406f40009cc4e1d9a7e847c90dabeae07c827..dddbd4e7332dcd364defa68a101a87b463c22a7a 100644
--- a/Tests/UnitTests/Core/Axes/Histogram2DTest.cpp
+++ b/Tests/UnitTests/Core/Axes/Histogram2DTest.cpp
@@ -32,7 +32,7 @@ TEST_F(Histogram2DTest, VariableHist)
// basic axes check
EXPECT_EQ(size_t(12), hist.getTotalNumberOfBins());
- EXPECT_EQ(hist.getRank(), size_t(2));
+ EXPECT_EQ(hist.rank(), size_t(2));
EXPECT_EQ(hist.xAxis().size(), size_t(4));
EXPECT_EQ(hist.getXmin(), -1.0);
EXPECT_EQ(hist.getXmax(), 2.0);
@@ -344,7 +344,7 @@ TEST_F(Histogram2DTest, CreateHistogram)
}
std::unique_ptr<IHistogram> h2(IHistogram::createHistogram(data));
- EXPECT_EQ(size_t(2), h2->getRank());
+ EXPECT_EQ(size_t(2), h2->rank());
EXPECT_EQ(data.getAllocatedSize(), h2->getTotalNumberOfBins());
EXPECT_EQ(data.axis(0).getMin(), h2->getXmin());
EXPECT_EQ(data.axis(0).getMax(), h2->getXmax());
@@ -371,7 +371,7 @@ TEST_F(Histogram2DTest, CreateOutputData)
}
std::unique_ptr<OutputData<double>> data(h2.createOutputData(IHistogram::DataType::INTEGRAL));
- EXPECT_EQ(size_t(2), data->getRank());
+ EXPECT_EQ(size_t(2), data->rank());
EXPECT_EQ(data->getAllocatedSize(), h2.getTotalNumberOfBins());
EXPECT_EQ(data->axis(0).getMin(), h2.getXmin());
EXPECT_EQ(data->axis(0).getMax(), h2.getXmax());
diff --git a/Tests/UnitTests/Core/DataStructure/ArrayUtilsTest.cpp b/Tests/UnitTests/Core/DataStructure/ArrayUtilsTest.cpp
index 9460c7b2588fd8ed357bd1303852b28ef1808522..b2ac1bc78fecb065b7613cbb762d91701fafc380 100644
--- a/Tests/UnitTests/Core/DataStructure/ArrayUtilsTest.cpp
+++ b/Tests/UnitTests/Core/DataStructure/ArrayUtilsTest.cpp
@@ -46,7 +46,7 @@ TEST_F(ArrayUtilsTest, OutputDataFromVector2D)
{0.0, 1.0, 2.0, 3.0}, {4.0, 5.0, 6.0, 7.0}, {8.0, 9.0, 10.0, 11.0}};
auto data = ArrayUtils::createData(vec_double);
- EXPECT_EQ(data->getRank(), 2u);
+ EXPECT_EQ(data->rank(), 2u);
EXPECT_EQ(data->getAllocatedSize(), 12u);
EXPECT_EQ(data->axis(0).size(), 4u);
EXPECT_EQ(data->axis(0).getMin(), 0.0);
diff --git a/Tests/UnitTests/Core/DataStructure/IOStrategyTest.cpp b/Tests/UnitTests/Core/DataStructure/IOStrategyTest.cpp
index f5ecfacbe9473ced627fd551ea9f5be5be112c8a..86fdc752d976ca36ad397c46f8f6c5d1ea42c212 100644
--- a/Tests/UnitTests/Core/DataStructure/IOStrategyTest.cpp
+++ b/Tests/UnitTests/Core/DataStructure/IOStrategyTest.cpp
@@ -35,7 +35,7 @@ TEST_F(IOStrategyTest, TestINTStrategies)
EXPECT_EQ(m_model_data.axis(index).getMax(), result->axis(index).getMax());
};
- EXPECT_EQ(m_model_data.getRank(), result->getRank());
+ EXPECT_EQ(m_model_data.rank(), result->rank());
EXPECT_EQ(m_model_data.getAllSizes(), result->getAllSizes());
compare_axis(0);
compare_axis(1);
@@ -51,7 +51,7 @@ TEST_F(IOStrategyTest, TestNumpyTXTStrategies)
OutputDataReadNumpyTXTStrategy read_txt_strategy;
auto result = std::unique_ptr<OutputData<double>>(read_txt_strategy.readOutputData(ss));
- EXPECT_EQ(m_model_data.getRank(), result->getRank());
+ EXPECT_EQ(m_model_data.rank(), result->rank());
EXPECT_EQ(m_model_data.getAllSizes(), result->getAllSizes());
for (size_t i = 0, size = m_model_data.getAllocatedSize(); i < size; ++i)
EXPECT_EQ(m_model_data[i], (*result)[i]);
@@ -67,7 +67,7 @@ TEST_F(IOStrategyTest, TestTIFFStrategies)
OutputDataReadTiffStrategy read_tiff_strategy;
auto result = std::unique_ptr<OutputData<double>>(read_tiff_strategy.readOutputData(ss));
- EXPECT_EQ(m_model_data.getRank(), result->getRank());
+ EXPECT_EQ(m_model_data.rank(), result->rank());
EXPECT_EQ(m_model_data.getAllSizes(), result->getAllSizes());
for (size_t i = 0, size = m_model_data.getAllocatedSize(); i < size; ++i)
EXPECT_EQ(m_model_data[i], (*result)[i]);
diff --git a/Tests/UnitTests/Core/DataStructure/LLDataTest.cpp b/Tests/UnitTests/Core/DataStructure/LLDataTest.cpp
index 4220132efb4e462ed9b99051155a66b7e77f0cd0..6b43e7d18fede59f964aa960d0a957f3daffb0c8 100644
--- a/Tests/UnitTests/Core/DataStructure/LLDataTest.cpp
+++ b/Tests/UnitTests/Core/DataStructure/LLDataTest.cpp
@@ -48,10 +48,10 @@ TEST_F(LLDataTest, TotalSize)
TEST_F(LLDataTest, GetRank)
{
- EXPECT_EQ(0u, int_data_0d->getRank());
- EXPECT_EQ(1u, fl_data_1d->getRank());
- EXPECT_EQ(3u, db_data_3d->getRank());
- EXPECT_EQ(2u, matrix_data_2d->getRank());
+ EXPECT_EQ(0u, int_data_0d->rank());
+ EXPECT_EQ(1u, fl_data_1d->rank());
+ EXPECT_EQ(3u, db_data_3d->rank());
+ EXPECT_EQ(2u, matrix_data_2d->rank());
}
TEST_F(LLDataTest, SetAll)
diff --git a/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp b/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp
index de4b50abab3a16742027d63406f42f1ce0eed067..695fe617fbb2f9e0c75424b851afaf728cfb8559 100644
--- a/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp
+++ b/Tests/UnitTests/Core/Fresnel/DepthProbeSimulationTest.cpp
@@ -150,7 +150,7 @@ TEST_F(DepthProbeSimulationTest, ResultAquisition)
const std::unique_ptr<Histogram2D> depth_map(sim_result.histogram2d());
EXPECT_EQ(10u * 12u, depth_map->getTotalNumberOfBins());
- EXPECT_EQ(2u, depth_map->getRank());
+ EXPECT_EQ(2u, depth_map->rank());
EXPECT_EQ(0.0, depth_map->xAxis().getMin());
EXPECT_EQ(2.0, depth_map->xAxis().getMax());
EXPECT_EQ(-30.0, depth_map->yAxis().getMin());
@@ -160,7 +160,7 @@ TEST_F(DepthProbeSimulationTest, ResultAquisition)
const auto output = sim_result.data();
EXPECT_EQ(depth_map->getTotalNumberOfBins(), output->getAllocatedSize());
- EXPECT_EQ(depth_map->getRank(), output->getRank());
+ EXPECT_EQ(depth_map->rank(), output->rank());
EXPECT_EQ(depth_map->xAxis().getMin(), output->axis(0).getMin());
EXPECT_EQ(depth_map->xAxis().getMax(), output->axis(0).getMax());
diff --git a/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp b/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp
index c2034698cdbc0e10f68c368e13eaca3573f4a40e..0a46296f9da2ba9034c176f2dc291ac6ac9419cf 100644
--- a/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp
+++ b/Tests/UnitTests/Core/Fresnel/SpecularSimulationTest.cpp
@@ -172,14 +172,14 @@ TEST_F(SpecularSimulationTest, ConstructSimulation)
auto data = sim_result.data();
EXPECT_EQ(data->getAllocatedSize(), 10u);
EXPECT_EQ(data->totalSum(), 0.0);
- EXPECT_EQ(data->getRank(), 1u);
+ EXPECT_EQ(data->rank(), 1u);
sim->runSimulation();
sim_result = sim->result();
data = sim_result.data();
EXPECT_EQ(data->getAllocatedSize(), 10u);
- EXPECT_EQ(data->getRank(), 1u);
+ EXPECT_EQ(data->rank(), 1u);
EXPECT_NEAR(0.1 * Units::degree, sim_result.axis(Axes::Units::RADIANS).front(),
Units::degree * 1e-11);
diff --git a/auto/Wrap/doxygenDevice.i b/auto/Wrap/doxygenDevice.i
index 7c2c9645112a9c677e79bc15e30fc2a5b258733e..79c4e6c00f6b8831c2cb6911d744d614519a5f6b 100644
--- a/auto/Wrap/doxygenDevice.i
+++ b/auto/Wrap/doxygenDevice.i
@@ -628,7 +628,7 @@ Constructor for 1D histograms from basic OutputData object.
Returns clone of other histogram.
";
-%feature("docstring") Histogram1D::getRank "size_t Histogram1D::getRank() const
+%feature("docstring") Histogram1D::rank "size_t Histogram1D::rank() const
Returns the number of histogram dimensions.
";
@@ -742,7 +742,7 @@ Constructor for 2D histograms from numpy array (thanks to swig)
Returns clone of other histogram.
";
-%feature("docstring") Histogram2D::getRank "size_t Histogram2D::getRank() const
+%feature("docstring") Histogram2D::rank "size_t Histogram2D::rank() const
Returns the number of histogram dimensions.
";
@@ -1196,7 +1196,7 @@ C++ includes: IHistogram.h
%feature("docstring") IHistogram::clone "virtual IHistogram* IHistogram::clone() const =0
";
-%feature("docstring") IHistogram::getRank "virtual size_t IHistogram::getRank() const =0
+%feature("docstring") IHistogram::rank "virtual size_t IHistogram::rank() const =0
Returns number of histogram dimensions.
";
@@ -1832,7 +1832,7 @@ C++ includes: LLData.h
%feature("docstring") LLData::getTotalSize "size_t LLData< T >::getTotalSize() const
";
-%feature("docstring") LLData::getRank "size_t LLData< T >::getRank() const
+%feature("docstring") LLData::rank "size_t LLData< T >::rank() const
";
%feature("docstring") LLData::getDimensions "const int* LLData< T >::getDimensions() const
@@ -1914,7 +1914,7 @@ returns axis with given serial number
returns axis with given name
";
-%feature("docstring") OutputData::getRank "size_t OutputData< T >::getRank() const
+%feature("docstring") OutputData::rank "size_t OutputData< T >::rank() const
Returns number of dimensions.
";
diff --git a/auto/Wrap/libBornAgainDevice.py b/auto/Wrap/libBornAgainDevice.py
index 7e9007ad4f11d4c05ad8a13bdb58bb514d5ca4d2..919dfda0c95ee819f79e8e06a81af292d568f5eb 100644
--- a/auto/Wrap/libBornAgainDevice.py
+++ b/auto/Wrap/libBornAgainDevice.py
@@ -2279,15 +2279,15 @@ class IntensityData(object):
"""
return _libBornAgainDevice.IntensityData_axis(self, *args)
- def getRank(self):
+ def rank(self):
r"""
- getRank(IntensityData self) -> size_t
- size_t OutputData< T >::getRank() const
+ rank(IntensityData self) -> size_t
+ size_t OutputData< T >::rank() const
Returns number of dimensions.
"""
- return _libBornAgainDevice.IntensityData_getRank(self)
+ return _libBornAgainDevice.IntensityData_rank(self)
def getAllocatedSize(self):
r"""
@@ -5266,15 +5266,15 @@ class IHistogram(object):
"""
return _libBornAgainDevice.IHistogram_clone(self)
- def getRank(self):
+ def rank(self):
r"""
- getRank(IHistogram self) -> size_t
- virtual size_t IHistogram::getRank() const =0
+ rank(IHistogram self) -> size_t
+ virtual size_t IHistogram::rank() const =0
Returns number of histogram dimensions.
"""
- return _libBornAgainDevice.IHistogram_getRank(self)
+ return _libBornAgainDevice.IHistogram_rank(self)
def getTotalNumberOfBins(self):
r"""
@@ -5724,15 +5724,15 @@ class Histogram1D(IHistogram):
"""
return _libBornAgainDevice.Histogram1D_clone(self)
- def getRank(self):
+ def rank(self):
r"""
- getRank(Histogram1D self) -> size_t
- size_t Histogram1D::getRank() const
+ rank(Histogram1D self) -> size_t
+ size_t Histogram1D::rank() const
Returns the number of histogram dimensions.
"""
- return _libBornAgainDevice.Histogram1D_getRank(self)
+ return _libBornAgainDevice.Histogram1D_rank(self)
def fill(self, x, weight=1.0):
r"""
@@ -5849,15 +5849,15 @@ class Histogram2D(IHistogram):
"""
return _libBornAgainDevice.Histogram2D_clone(self)
- def getRank(self):
+ def rank(self):
r"""
- getRank(Histogram2D self) -> size_t
- size_t Histogram2D::getRank() const
+ rank(Histogram2D self) -> size_t
+ size_t Histogram2D::rank() const
Returns the number of histogram dimensions.
"""
- return _libBornAgainDevice.Histogram2D_getRank(self)
+ return _libBornAgainDevice.Histogram2D_rank(self)
def fill(self, x, y, weight=1.0):
r"""
diff --git a/auto/Wrap/libBornAgainDevice_wrap.cpp b/auto/Wrap/libBornAgainDevice_wrap.cpp
index a5fd64c7ba0ea4a65e88f12e2a2cef3961cf2a3f..e6ce71b12e2ea583ac31bb1f56d3a17962df65af 100644
--- a/auto/Wrap/libBornAgainDevice_wrap.cpp
+++ b/auto/Wrap/libBornAgainDevice_wrap.cpp
@@ -29257,7 +29257,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_IntensityData_getRank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+SWIGINTERN PyObject *_wrap_IntensityData_rank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
PyObject *resultobj = 0;
OutputData< double > *arg1 = (OutputData< double > *) 0 ;
void *argp1 = 0 ;
@@ -29269,10 +29269,10 @@ SWIGINTERN PyObject *_wrap_IntensityData_getRank(PyObject *SWIGUNUSEDPARM(self),
swig_obj[0] = args;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_OutputDataT_double_t, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IntensityData_getRank" "', argument " "1"" of type '" "OutputData< double > const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IntensityData_rank" "', argument " "1"" of type '" "OutputData< double > const *""'");
}
arg1 = reinterpret_cast< OutputData< double > * >(argp1);
- result = ((OutputData< double > const *)arg1)->getRank();
+ result = ((OutputData< double > const *)arg1)->rank();
resultobj = SWIG_From_size_t(static_cast< size_t >(result));
return resultobj;
fail:
@@ -40926,7 +40926,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_IHistogram_getRank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+SWIGINTERN PyObject *_wrap_IHistogram_rank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
PyObject *resultobj = 0;
IHistogram *arg1 = (IHistogram *) 0 ;
void *argp1 = 0 ;
@@ -40938,10 +40938,10 @@ SWIGINTERN PyObject *_wrap_IHistogram_getRank(PyObject *SWIGUNUSEDPARM(self), Py
swig_obj[0] = args;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_IHistogram, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IHistogram_getRank" "', argument " "1"" of type '" "IHistogram const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "IHistogram_rank" "', argument " "1"" of type '" "IHistogram const *""'");
}
arg1 = reinterpret_cast< IHistogram * >(argp1);
- result = ((IHistogram const *)arg1)->getRank();
+ result = ((IHistogram const *)arg1)->rank();
resultobj = SWIG_From_size_t(static_cast< size_t >(result));
return resultobj;
fail:
@@ -43051,7 +43051,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_Histogram1D_getRank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+SWIGINTERN PyObject *_wrap_Histogram1D_rank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
PyObject *resultobj = 0;
Histogram1D *arg1 = (Histogram1D *) 0 ;
void *argp1 = 0 ;
@@ -43063,10 +43063,10 @@ SWIGINTERN PyObject *_wrap_Histogram1D_getRank(PyObject *SWIGUNUSEDPARM(self), P
swig_obj[0] = args;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_Histogram1D, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "Histogram1D_getRank" "', argument " "1"" of type '" "Histogram1D const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "Histogram1D_rank" "', argument " "1"" of type '" "Histogram1D const *""'");
}
arg1 = reinterpret_cast< Histogram1D * >(argp1);
- result = ((Histogram1D const *)arg1)->getRank();
+ result = ((Histogram1D const *)arg1)->rank();
resultobj = SWIG_From_size_t(static_cast< size_t >(result));
return resultobj;
fail:
@@ -43741,7 +43741,7 @@ fail:
}
-SWIGINTERN PyObject *_wrap_Histogram2D_getRank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
+SWIGINTERN PyObject *_wrap_Histogram2D_rank(PyObject *SWIGUNUSEDPARM(self), PyObject *args) {
PyObject *resultobj = 0;
Histogram2D *arg1 = (Histogram2D *) 0 ;
void *argp1 = 0 ;
@@ -43753,10 +43753,10 @@ SWIGINTERN PyObject *_wrap_Histogram2D_getRank(PyObject *SWIGUNUSEDPARM(self), P
swig_obj[0] = args;
res1 = SWIG_ConvertPtr(swig_obj[0], &argp1,SWIGTYPE_p_Histogram2D, 0 | 0 );
if (!SWIG_IsOK(res1)) {
- SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "Histogram2D_getRank" "', argument " "1"" of type '" "Histogram2D const *""'");
+ SWIG_exception_fail(SWIG_ArgError(res1), "in method '" "Histogram2D_rank" "', argument " "1"" of type '" "Histogram2D const *""'");
}
arg1 = reinterpret_cast< Histogram2D * >(argp1);
- result = ((Histogram2D const *)arg1)->getRank();
+ result = ((Histogram2D const *)arg1)->rank();
resultobj = SWIG_From_size_t(static_cast< size_t >(result));
return resultobj;
fail:
@@ -46450,9 +46450,9 @@ static PyMethodDef SwigMethods[] = {
"returns axis with given name \n"
"\n"
""},
- { "IntensityData_getRank", _wrap_IntensityData_getRank, METH_O, "\n"
- "IntensityData_getRank(IntensityData self) -> size_t\n"
- "size_t OutputData< T >::getRank() const\n"
+ { "IntensityData_rank", _wrap_IntensityData_rank, METH_O, "\n"
+ "IntensityData_rank(IntensityData self) -> size_t\n"
+ "size_t OutputData< T >::rank() const\n"
"\n"
"Returns number of dimensions. \n"
"\n"
@@ -48193,9 +48193,9 @@ static PyMethodDef SwigMethods[] = {
"virtual IHistogram* IHistogram::clone() const =0\n"
"\n"
""},
- { "IHistogram_getRank", _wrap_IHistogram_getRank, METH_O, "\n"
- "IHistogram_getRank(IHistogram self) -> size_t\n"
- "virtual size_t IHistogram::getRank() const =0\n"
+ { "IHistogram_rank", _wrap_IHistogram_rank, METH_O, "\n"
+ "IHistogram_rank(IHistogram self) -> size_t\n"
+ "virtual size_t IHistogram::rank() const =0\n"
"\n"
"Returns number of histogram dimensions. \n"
"\n"
@@ -48489,9 +48489,9 @@ static PyMethodDef SwigMethods[] = {
"Returns clone of other histogram. \n"
"\n"
""},
- { "Histogram1D_getRank", _wrap_Histogram1D_getRank, METH_O, "\n"
- "Histogram1D_getRank(Histogram1D self) -> size_t\n"
- "size_t Histogram1D::getRank() const\n"
+ { "Histogram1D_rank", _wrap_Histogram1D_rank, METH_O, "\n"
+ "Histogram1D_rank(Histogram1D self) -> size_t\n"
+ "size_t Histogram1D::rank() const\n"
"\n"
"Returns the number of histogram dimensions. \n"
"\n"
@@ -48567,9 +48567,9 @@ static PyMethodDef SwigMethods[] = {
"Returns clone of other histogram. \n"
"\n"
""},
- { "Histogram2D_getRank", _wrap_Histogram2D_getRank, METH_O, "\n"
- "Histogram2D_getRank(Histogram2D self) -> size_t\n"
- "size_t Histogram2D::getRank() const\n"
+ { "Histogram2D_rank", _wrap_Histogram2D_rank, METH_O, "\n"
+ "Histogram2D_rank(Histogram2D self) -> size_t\n"
+ "size_t Histogram2D::rank() const\n"
"\n"
"Returns the number of histogram dimensions. \n"
"\n"