Commit 6331e6b5 authored by Savici, Andrei T's avatar Savici, Andrei T
Browse files

Merge pull request #15027 from mantidproject/google-readability-casting

Ran clang-tidy check: google-readability-casting.
parents c165c386 15b90a72
......@@ -20,7 +20,7 @@ IDomainCreator *DomainCreatorFactoryImpl::createDomainCreator(
const unsigned int domainType) const {
auto creator = this->createUnwrapped(id);
creator->initialize(pm, workspacePropertyName,
(IDomainCreator::DomainType)domainType);
static_cast<IDomainCreator::DomainType>(domainType));
return creator;
}
......
......@@ -224,7 +224,7 @@ void LogManager::removeProperty(const std::string &name, bool delProperty) {
// Remove any cached entries for this log. Need to make this more general
for (unsigned int stat = 0; stat < 7; ++stat) {
m_singleValueCache.removeCache(
std::make_pair(name, (Math::StatisticType)stat));
std::make_pair(name, static_cast<Math::StatisticType>(stat)));
}
m_manager.removeProperty(name, delProperty);
}
......
......@@ -1250,7 +1250,7 @@ size_t MatrixWorkspace::binIndexOf(const double xValue,
}
uint64_t MatrixWorkspace::getNPoints() const {
return (uint64_t)(this->size());
return static_cast<uint64_t>(this->size());
}
//================================= FOR MDGEOMETRY
......
......@@ -44,7 +44,7 @@ ParameterTie::~ParameterTie() {
* @return pointer to added variable
*/
double *ParameterTie::AddVariable(const char *varName, void *palg) {
ParameterTie &tie = *(ParameterTie *)palg;
ParameterTie &tie = *reinterpret_cast<ParameterTie *>(palg);
ParameterReference ref(tie.m_function1,
tie.m_function1->parameterIndex(std::string(varName)));
......
......@@ -122,7 +122,7 @@ void ApplyTransmissionCorrection::exec() {
const double exp_term =
(1.0 / cos(inputWS->detectorTwoTheta(det)) + 1.0) / 2.0;
for (int j = 0; j < (int)inputWS->readY(0).size(); j++) {
for (int j = 0; j < static_cast<int>(inputWS->readY(0).size()); j++) {
if (!thetaDependent) {
YOut[j] = 1.0 / TrIn[j];
EOut[j] = std::fabs(ETrIn[j] * TrIn[j] * TrIn[j]);
......
......@@ -85,11 +85,14 @@ void BinaryOperateMasks::exec() {
unsigned int binop;
if (op == "AND") {
binop = (unsigned int)Mantid::DataObjects::BinaryOperator::AND;
binop =
static_cast<unsigned int>(Mantid::DataObjects::BinaryOperator::AND);
} else if (op == "OR") {
binop = (unsigned int)Mantid::DataObjects::BinaryOperator::OR;
binop =
static_cast<unsigned int>(Mantid::DataObjects::BinaryOperator::OR);
} else if (op == "XOR") {
binop = (unsigned int)Mantid::DataObjects::BinaryOperator::XOR;
binop =
static_cast<unsigned int>(Mantid::DataObjects::BinaryOperator::XOR);
} else {
binop = 1000;
}
......
......@@ -67,7 +67,8 @@ void CalculateEfficiency::exec() {
outputWS = WorkspaceFactory::Instance().create(rebinnedWS);
WorkspaceFactory::Instance().initializeFromParent(inputWS, outputWS, false);
for (int i = 0; i < (int)rebinnedWS->getNumberHistograms(); i++) {
for (int i = 0; i < static_cast<int>(rebinnedWS->getNumberHistograms());
i++) {
outputWS->dataX(i) = rebinnedWS->readX(i);
}
setProperty("OutputWorkspace", outputWS);
......@@ -173,7 +174,8 @@ void CalculateEfficiency::normalizeDetectors(MatrixWorkspace_sptr rebinnedWS,
for (size_t i = 0; i < numberOfSpectra; i++) {
const double currProgress =
0.4 + 0.2 * ((double)i / (double)numberOfSpectra);
0.4 +
0.2 * (static_cast<double>(i) / static_cast<double>(numberOfSpectra));
progress(currProgress, "Computing sensitivity");
// Get the detector object for this spectrum
IDetector_const_sptr det = rebinnedWS->getDetector(i);
......
......@@ -233,8 +233,8 @@ void CompareWorkspaces::processGroups(
// We should use an algorithm for each so that the output properties are
// reset properly
Algorithm_sptr checker = this->createChildAlgorithm(
this->name(), progressFraction * (double)i,
progressFraction * (double)(i + 1), false, this->version());
this->name(), progressFraction * static_cast<double>(i),
progressFraction * static_cast<double>(i + 1), false, this->version());
checker->setPropertyValue("Workspace1", namesOne[i]);
checker->setPropertyValue("Workspace2", namesTwo[i]);
for (size_t j = 0; j < numNonDefault; ++j) {
......
......@@ -48,7 +48,7 @@ void ConvertToMatrixWorkspace::exec() {
// ...but not the data, so do that here.
PARALLEL_FOR2(inputWorkspace, outputWorkspace)
for (int64_t i = 0; i < (int64_t)numHists; ++i) {
for (int64_t i = 0; i < static_cast<int64_t>(numHists); ++i) {
PARALLEL_START_INTERUPT_REGION
const ISpectrum *inSpec = inputWorkspace->getSpectrum(i);
ISpectrum *outSpec = outputWorkspace->getSpectrum(i);
......
......@@ -53,7 +53,7 @@ DiffractionEventCalibrateDetectors::~DiffractionEventCalibrateDetectors() {}
static double gsl_costFunction(const gsl_vector *v, void *params) {
double x, y, z, rotx, roty, rotz;
std::string detname, inname, outname, peakOpt, rb_param, groupWSName;
std::string *p = (std::string *)params;
std::string *p = reinterpret_cast<std::string *>(params);
detname = p[0];
inname = p[1];
outname = p[2];
......
......@@ -105,7 +105,8 @@ void EQSANSTofStructure::exec() {
frame_skipping ? tof_frame_width * 2.0 : tof_frame_width;
double frame_offset = 0.0;
if (frame_tof0 >= tmp_frame_width)
frame_offset = tmp_frame_width * ((int)(frame_tof0 / tmp_frame_width));
frame_offset =
tmp_frame_width * (static_cast<int>(frame_tof0 / tmp_frame_width));
this->execEvent(inputWS, frame_tof0, frame_offset, tof_frame_width,
tmp_frame_width, frame_skipping);
......
......@@ -131,8 +131,8 @@ void FindCenterOfMassPosition::exec() {
// Get the current spectrum
const MantidVec &YIn = inputWS->readY(i);
double y = (double)((i - n_monitors) % n_pixel_x);
double x = floor((double)(i - n_monitors) / n_pixel_y);
double y = static_cast<double>((i - n_monitors) % n_pixel_x);
double x = floor(static_cast<double>(i - n_monitors) / n_pixel_y);
if (x >= xmin && x <= xmax && y >= ymin && y <= ymax) {
if (!direct_beam) {
......
......@@ -38,7 +38,7 @@ const double BAD_OFFSET(1000.); // mark things that didn't work with this
double gsl_costFunction(const gsl_vector *v, void *params) {
// FIXME - there is no need to use vectors peakPosToFit, peakPosFitted and
// chisq
double *p = (double *)params;
double *p = reinterpret_cast<double *>(params);
size_t n = static_cast<size_t>(p[0]);
std::vector<double> peakPosToFit(n);
std::vector<double> peakPosFitted(n);
......
......@@ -678,9 +678,10 @@ void GetEi2::integrate(double &integral_val, double &integral_err,
MantidVec::size_type nx(x.size());
if (mu < ml) {
// special case of no data points in the integration range
unsigned int ilo = std::max<unsigned int>((unsigned int)ml - 1, 0);
unsigned int ihi =
std::min<unsigned int>((unsigned int)mu + 1, (unsigned int)nx);
unsigned int ilo =
std::max<unsigned int>(static_cast<unsigned int>(ml) - 1, 0);
unsigned int ihi = std::min<unsigned int>(static_cast<unsigned int>(mu) + 1,
static_cast<unsigned int>(nx));
double fraction = (xmax - xmin) / (x[ihi] - x[ilo]);
integral_val =
0.5 * fraction * (s[ihi] * ((xmax - x[ilo]) + (xmin - x[ilo])) +
......@@ -733,7 +734,7 @@ void GetEi2::integrate(double &integral_val, double &integral_err,
double err_hi = e[mu] * (x[mu - 1] - xneff);
integral_err += err_lo * err_lo + err_hi * err_hi;
} else {
for (int i = (int)ml; i < mu; ++i) {
for (int i = static_cast<int>(ml); i < mu; ++i) {
integral_val += (s[i + 1] + s[i]) * (x[i + 1] - x[i]);
if (i < mu - 1) {
double ierr = e[i + 1] * (x[i + 2] - x[i]);
......
......@@ -205,7 +205,7 @@ void MonteCarloAbsorption::doSimulation(const IDetector *const detector,
// Attenuation factor is simply the average value
attenFactor /= numDetected;
// Error is 1/sqrt(nevents)
error = 1. / sqrt((double)numDetected);
error = 1. / sqrt(static_cast<double>(numDetected));
}
/**
......
......@@ -396,7 +396,7 @@ API::MatrixWorkspace_sptr NormaliseToMonitor::getInWSMonitorSpectrum(
throw std::runtime_error("More then one spectra corresponds to the "
"requested monitor ID, which is unheard of");
}
spectra_num = (int)indexList[0];
spectra_num = static_cast<int>(indexList[0]);
} else { // monitor spectrum is specified.
spec2index_map specs;
const SpectraAxis *axis =
......@@ -410,7 +410,7 @@ API::MatrixWorkspace_sptr NormaliseToMonitor::getInWSMonitorSpectrum(
throw std::runtime_error("Input workspace does not contain spectrum "
"number given for MonitorSpectrum");
}
spectra_num = (int)specs[monitorSpec];
spectra_num = static_cast<int>(specs[monitorSpec]);
}
return this->extractMonitorSpectrum(inputWorkspace, spectra_num);
}
......
......@@ -207,8 +207,9 @@ void Q1DWeighted::exec() {
double sub_y = pixelSizeY *
((isub % nSubPixels) - (nSubPixels - 1.0) / 2.0) /
nSubPixels;
double sub_x = pixelSizeX * (floor((double)isub / nSubPixels) -
(nSubPixels - 1.0) / 2.0) /
double sub_x = pixelSizeX *
(floor(static_cast<double>(isub) / nSubPixels) -
(nSubPixels - 1.0) / 2.0) /
nSubPixels;
// Find the position of this sub-pixel in real space and compute Q
......@@ -224,14 +225,15 @@ void Q1DWeighted::exec() {
// Bin assignment depends on whether we have log or linear bins
if (binParams.size() == 3) {
if (binParams[1] > 0.0) {
iq = (int)floor((q - binParams[0]) / binParams[1]);
iq = static_cast<int>(floor((q - binParams[0]) / binParams[1]));
} else {
iq = (int)floor(log(q / binParams[0]) / log(1.0 - binParams[1]));
iq = static_cast<int>(
floor(log(q / binParams[0]) / log(1.0 - binParams[1])));
}
// If we got a more complicated binning, find the q bin the slow way
} else {
for (int i_qbin = 0; i_qbin < (int)XOut.access().size() - 1;
i_qbin++) {
for (int i_qbin = 0;
i_qbin < static_cast<int>(XOut.access().size()) - 1; i_qbin++) {
if (q >= XOut.access()[i_qbin] && q < XOut.access()[(i_qbin + 1)]) {
iq = i_qbin;
break;
......
......@@ -116,7 +116,7 @@ void Qhelper::examineInput(API::MatrixWorkspace_const_sptr dataWS,
size_t num_histograms = dataWS->getNumberHistograms();
for (size_t i = 0; i < num_histograms; i++) {
double adj = (double)detectAdj->readY(i)[0];
double adj = static_cast<double>(detectAdj->readY(i)[0]);
if (adj <= 0.0) {
bool det_is_masked;
......
......@@ -527,8 +527,8 @@ void RadiusSum::numBinsIsReasonable() {
<< "It corresponds to a separation smaller than the image "
"resolution (detector size). "
<< "A resonable number is smaller than "
<< (int)((max_radius - min_radius) / min_bin_size)
<< std::endl;
<< static_cast<int>((max_radius - min_radius) /
min_bin_size) << std::endl;
}
double RadiusSum::getMinBinSizeForInstrument(API::MatrixWorkspace_sptr inWS) {
......@@ -570,8 +570,8 @@ double RadiusSum::getMinBinSizeForNumericImage(API::MatrixWorkspace_sptr inWS) {
std::vector<double> boundaries = getBoundariesOfNumericImage(inWS);
const MantidVec &refX = inWS->readX(inputWS->getNumberHistograms() / 2);
int nX = (int)(refX.size());
int nY = (int)(inWS->getAxis(1)->length());
int nX = static_cast<int>(refX.size());
int nY = static_cast<int>(inWS->getAxis(1)->length());
// remembering boundaries is defined as { xMin, xMax, yMin, yMax}
return std::min(((boundaries[1] - boundaries[0]) / nX),
......@@ -592,11 +592,11 @@ void RadiusSum::normalizeOutputByRadius(std::vector<double> &values,
g_log.debug() << "Calculate Output[i] = Counts[i] / (Radius[i] ^ "
<< exp_power << ") << " << std::endl;
if (exp_power > 1.00001 || exp_power < 0.99999) {
for (int i = 0; i < (int)values.size(); i++) {
for (int i = 0; i < static_cast<int>(values.size()); i++) {
values[i] = values[i] / pow(first_radius + i * bin_size, exp_power);
}
} else { // avoid calling pow because exp_power == 1 (for performance)
for (int i = 0; i < (int)values.size(); i++) {
for (int i = 0; i < static_cast<int>(values.size()); i++) {
values[i] = values[i] / (first_radius + i * bin_size);
}
}
......@@ -649,7 +649,7 @@ void RadiusSum::setUpOutputWorkspace(std::vector<double> &values) {
MantidVec &refX = outputWS->dataX(0);
double bin_size = (max_radius - min_radius) / num_bins;
for (int i = 0; i < ((int)refX.size()) - 1; i++)
for (int i = 0; i < (static_cast<int>(refX.size())) - 1; i++)
refX[i] = min_radius + i * bin_size;
refX[refX.size() - 1] = max_radius;
......
......@@ -75,7 +75,7 @@ void RebinToWorkspace::createRebinParameters(
// params vector should have the form [x_1, delta_1,x_2, ...
// ,x_n-1,delta_n-1,x_n), see Rebin.cpp
rb_params.clear();
int xsize = (int)matchXdata.size();
int xsize = static_cast<int>(matchXdata.size());
rb_params.reserve(xsize * 2);
for (int i = 0; i < xsize; ++i) {
// bin bound
......
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