static void em_1003sats(struct gps_state *gps)
{
double elv, azm;
int j, svn, nsats = INT16(&packet[WD(14)]);
gps->hdop = INT32(&packet[WD(11)]) * 1.0e-2;
for (j = 0; j < nsats; j++) {
svn = INT16(&packet[WD(15 + (3 * j))]);
elv = INT16(&packet[WD(17 + (3 * j))]) * 1.0e-4;
azm = INT16(&packet[WD(16 + (3 * j))]) * 1.0e-4;
if (elv < 0) elv = 0;
if (azm < 0) azm += 2 * M_PI;
new_sat(gps, svn, UNKNOWN_TIME, elv, azm, UNKNOWN_SNR, UNKNOWN_USED);
}
if (nsats)
gps->updated = GPS_STATE_SATS;
}
static void em_1002chsum(struct gps_state *gps)
{
int j, status, svn, snr, used, valid;
int timestamp, datestamp, time;
#define EPOCHDIFF 315532800 /* difference between GPS and UNIX time */
#define LEAP_SECONDS 13 /* hardcoded, bad me, should get it from the receiver */
datestamp = INT16(&packet[WD(10)]) * 7 * 86400 + EPOCHDIFF;
timestamp = INT32(&packet[WD(11)]) + LEAP_SECONDS;
time = datestamp + timestamp;
for (j = 0; j < 12; j++) {
status = INT16(&packet[WD(15 + (3 * j))]);
used = status & 0x1;
valid = status & 0x4;
svn = INT16(&packet[WD(16 + (3 * j))]);
snr = INT16(&packet[WD(17 + (3 * j))]) / 4; /* scaling snr to 0-16 */
new_sat(gps, svn, valid ? time : UNKNOWN_TIME, UNKNOWN_ELV, UNKNOWN_AZM,
snr, used);
}
gps->updated = GPS_STATE_SIGNALS;
}
int main()
{
long n;
GF2X a, b, c, c1, ss, ss1, tt, tt1;
double t;
long iter, i;
cout << WD(12,"n") << WD(12,"OldGCD") << WD(12,"GCD") << WD(12,"OldXGCD")
<< WD(12, "XGCD") << "\n";
cout.precision(3);
cout.setf(ios::scientific);
for (n = 32; n <= (1L << 18); n = n << 3) {
random(a, n);
random(b, n);
OldGCD(c, a, b);
GCD(c1, a, b);
OldXGCD(c, ss, tt, a, b);
XGCD(c1, ss1, tt1, a, b);
if (c1 != c || ss1 != ss || tt1 != tt) {
cerr << "**** GF2XTest FAILED!\n";
return 1;
}
cout << WD(12,n);
iter = 0;
do {
iter = iter ? (2*iter) : 1;
t = GetTime();
for (i = 0; i < iter; i++)
OldGCD(c, a, b);
t = GetTime()-t;
} while (t < 0.5);
cout << WD(12,t/iter);
iter = 0;
do {
iter = iter ? (2*iter) : 1;
t = GetTime();
for (i = 0; i < iter; i++)
GCD(c, a, b);
t = GetTime()-t;
} while (t < 0.5);
cout << WD(12,t/iter);
iter = 0;
do {
iter = iter ? (2*iter) : 1;
t = GetTime();
for (i = 0; i < iter; i++)
OldXGCD(c, ss, tt, a, b);
t = GetTime()-t;
} while (t < 0.5);
cout << WD(12,t/iter);
iter = 0;
do {
iter = iter ? (2*iter) : 1;
t = GetTime();
for (i = 0; i < iter; i++)
XGCD(c, ss, tt, a, b);
t = GetTime()-t;
} while (t < 0.5);
cout << WD(12,t/iter);
cout << "\n";
}
return 0;
}
///' Calculate the network properties
///'
///' @details
///' \subsection{Input expectations:}{
///' Note that this function expects all inputs to be sensible, as checked by
///' the R function 'checkUserInput' and processed by 'networkProperties'.
///'
///' These requirements are:
///' \itemize{
///' \item{The ordering of node names across 'data' and 'net' is consistent.}
///' \item{The columns of 'data' are the nodes.}
///' \item{'net' is a square matrix, and its rownames are identical to its
///' column names.}
///' \item{'moduleAssigments' is a named character vector, where the names
///' represent node labels found in the discovery dataset. Unlike
///' 'PermutationProcedure', these may include nodes that are not
///' present in 'data' and 'net'.}
///' \item{The module labels specified in 'modules' must occur in
///' 'moduleAssignments'.}
///' }
///' }
///'
///' @param data data matrix from the dataset in which to calculate the network
///' properties.
///' @param net adjacency matrix of network edge weights between all pairs of
///' nodes in the dataset in which to calculate the network properties.
///' @param moduleAssignments a named character vector containing the module
///' each node belongs to in the discovery dataset.
///' @param modules a character vector of modules for which to calculate the
///' network properties for.
///'
///' @return a list containing the summary profile, node contribution, module
///' coherence, weighted degree, and average edge weight for each 'module'.
///'
///' @keywords internal
// [[Rcpp::export]]
Rcpp::List NetProps (
Rcpp::NumericMatrix data, Rcpp::NumericMatrix net,
Rcpp::CharacterVector moduleAssignments,
Rcpp::CharacterVector modules
) {
// First, scale the matrix data
unsigned int nSamples = data.nrow();
unsigned int nNodes = data.ncol();
arma::mat scaledData = Scale(data.begin(), nSamples, nNodes);
R_CheckUserInterrupt();
// convert the colnames / rownames to C++ equivalents
const std::vector<std::string> nodeNames (Rcpp::as<std::vector<std::string>>(colnames(net)));
const std::vector<std::string> sampleNames (Rcpp::as<std::vector<std::string>>(rownames(data)));
/* Next, we need to create two mappings:
* - From node IDs to indices in the dataset of interest
* - From modules to node IDs
* - From modules to only node IDs present in the dataset of interest
*/
const namemap nodeIdxMap = MakeIdxMap(nodeNames);
const stringmap modNodeMap = MakeModMap(moduleAssignments);
const stringmap modNodePresentMap = MakeModMap(moduleAssignments, nodeIdxMap);
// What modules do we actually want to analyse?
const std::vector<std::string> mods (Rcpp::as<std::vector<std::string>>(modules));
R_CheckUserInterrupt();
// Calculate the network properties for each module
std::string mod; // iterators
unsigned int mNodesPresent, mNodes;
arma::uvec nodeIdx, propIdx, nodeRank;
namemap propIdxMap;
std::vector<std::string> modNodeNames;
arma::vec WD, SP, NC; // results containers
double avgWeight, coherence;
Rcpp::NumericVector degree, summary, contribution; // for casting to R equivalents
Rcpp::List results; // final storage container
for (auto mi = mods.begin(); mi != mods.end(); ++mi) {
// What nodes are in this module?
mod = *mi;
modNodeNames = GetModNodeNames(mod, modNodeMap);
// initialise results containers with NA values for nodes not present in
// the dataset we're calculating the network properties in.
degree = Rcpp::NumericVector(modNodeNames.size(), NA_REAL);
contribution = Rcpp::NumericVector(modNodeNames.size(), NA_REAL);
summary = Rcpp::NumericVector(nSamples, NA_REAL);
avgWeight = NA_REAL;
coherence = NA_REAL;
degree.names() = modNodeNames;
contribution.names() = modNodeNames;
// Create a mapping between node names and the result vectors
propIdxMap = MakeIdxMap(modNodeNames);
// Get just the indices of nodes that are present in the requested dataset
nodeIdx = GetNodeIdx(mod, modNodePresentMap, nodeIdxMap);
mNodesPresent = nodeIdx.n_elem;
// And a mapping of those nodes to the initialised vectors
propIdx = GetNodeIdx(mod, modNodePresentMap, propIdxMap);
mNodes = propIdx.n_elem;
// Calculate the properties if the module has nodes in the test dataset
if (nodeIdx.n_elem > 0) {
// sort the node indices for sequential memory access
nodeRank = SortNodes(nodeIdx.memptr(), mNodesPresent);
WD = WeightedDegree(net.begin(), nNodes, nodeIdx.memptr(), mNodesPresent);
WD = WD(nodeRank); // reorder results
avgWeight = AverageEdgeWeight(WD.memptr(), WD.n_elem);
R_CheckUserInterrupt();
SP = SummaryProfile(scaledData.memptr(), nSamples, nNodes,
nodeIdx.memptr(), mNodesPresent);
R_CheckUserInterrupt();
NC = NodeContribution(scaledData.memptr(), nSamples, nNodes,
nodeIdx.memptr(), mNodesPresent, SP.memptr());
NC = NC(nodeRank); // reorder results
coherence = ModuleCoherence(NC.memptr(), mNodesPresent);
R_CheckUserInterrupt();
// Convert NaNs to NAs
SP.elem(arma::find_nonfinite(SP)).fill(NA_REAL);
NC.elem(arma::find_nonfinite(NC)).fill(NA_REAL);
if (!arma::is_finite(coherence)) {
coherence = NA_REAL;
}
// Fill results vectors
Fill(degree, WD.memptr(), mNodesPresent, propIdx.memptr(), mNodes);
Fill(contribution, NC.memptr(), mNodesPresent, propIdx.memptr(), mNodes);
summary = Rcpp::NumericVector(SP.begin(), SP.end());
}
summary.names() = sampleNames;
results.push_back(
Rcpp::List::create(
Rcpp::Named("summary") = summary,
Rcpp::Named("contribution") = contribution,
Rcpp::Named("coherence") = coherence,
Rcpp::Named("degree") = degree,
Rcpp::Named("avgWeight") = avgWeight
)
);
}
results.names() = mods;
return(results);
}
///' Calculate the network properties, data matrix not provided
///'
///' @details
///' \subsection{Input expectations:}{
///' Note that this function expects all inputs to be sensible, as checked by
///' the R function 'checkUserInput' and processed by 'networkProperties'.
///'
///' These requirements are:
///' \itemize{
///' \item{'net' is a square matrix, and its rownames are identical to its
///' column names.}
///' \item{'moduleAssigments' is a named character vector, where the names
///' represent node labels found in the discovery dataset. Unlike
///' 'PermutationProcedure', these may include nodes that are not
///' present in 'data' and 'net'.}
///' \item{The module labels specified in 'modules' must occur in
///' 'moduleAssignments'.}
///' }
///' }
///'
///' @param net adjacency matrix of network edge weights between all pairs of
///' nodes in the dataset in which to calculate the network properties.
///' @param moduleAssignments a named character vector containing the module
///' each node belongs to in the discovery dataset.
///' @param modules a character vector of modules for which to calculate the
///' network properties for.
///'
///' @return a list containing the summary profile, node contribution, module
///' coherence, weighted degree, and average edge weight for each 'module'.
///'
///' @keywords internal
// [[Rcpp::export]]
Rcpp::List NetPropsNoData (
Rcpp::NumericMatrix net,
Rcpp::CharacterVector moduleAssignments,
Rcpp::CharacterVector modules
) {
// convert the colnames / rownames to C++ equivalents
const std::vector<std::string> nodeNames (Rcpp::as<std::vector<std::string>>(colnames(net)));
unsigned int nNodes = net.ncol();
R_CheckUserInterrupt();
/* Next, we need to create two mappings:
* - From node IDs to indices in the dataset of interest
* - From modules to node IDs
* - From modules to only node IDs present in the dataset of interest
*/
const namemap nodeIdxMap = MakeIdxMap(nodeNames);
const stringmap modNodeMap = MakeModMap(moduleAssignments);
const stringmap modNodePresentMap = MakeModMap(moduleAssignments, nodeIdxMap);
// What modules do we actually want to analyse?
const std::vector<std::string> mods (Rcpp::as<std::vector<std::string>>(modules));
R_CheckUserInterrupt();
// Calculate the network properties for each module
std::string mod; // iterators
unsigned int mNodesPresent, mNodes;
arma::uvec nodeIdx, propIdx, nodeRank;
namemap propIdxMap;
std::vector<std::string> modNodeNames;
arma::vec WD; // results containers
double avgWeight;
Rcpp::NumericVector degree; // for casting to R equivalents
Rcpp::List results; // final storage container
for (auto mi = mods.begin(); mi != mods.end(); ++mi) {
// What nodes are in this module?
// modNodeNames = names(moduleAssignments[moduleAssignments == mod])
mod = *mi;
modNodeNames = GetModNodeNames(mod, modNodeMap);
// initialise results containers with NA values for nodes not present in
// the dataset we're calculating the network properties in.
degree = Rcpp::NumericVector(modNodeNames.size(), NA_REAL);
avgWeight = NA_REAL;
degree.names() = modNodeNames;
// Create a mapping between node names and the result vectors
propIdxMap = MakeIdxMap(modNodeNames);
// Get just the indices of nodes that are present in the requested dataset
nodeIdx = GetNodeIdx(mod, modNodePresentMap, nodeIdxMap);
mNodesPresent = nodeIdx.n_elem;
// And a mapping of those nodes to the initialised vectors
propIdx = GetNodeIdx(mod, modNodePresentMap, propIdxMap);
mNodes = propIdx.n_elem;
// Calculate the properties if the module has nodes in the test dataset
if (nodeIdx.n_elem > 0) {
// sort the node indices for sequential memory access
nodeRank = SortNodes(nodeIdx.memptr(), mNodesPresent);
WD = WeightedDegree(net.begin(), nNodes, nodeIdx.memptr(), mNodesPresent);
WD = WD(nodeRank); // reorder results
avgWeight = AverageEdgeWeight(WD.memptr(), WD.n_elem);
R_CheckUserInterrupt();
// Fill the results vectors appropriately
Fill(degree, WD.memptr(), mNodesPresent, propIdx.memptr(), mNodes);
}
results.push_back(
Rcpp::List::create(
Rcpp::Named("degree") = degree,
Rcpp::Named("avgWeight") = avgWeight
)
);
}
results.names() = mods;
return(results);
}
static void em_1000geodpos(struct gps_state *gps)
{
double speed;
int bearing, solinv;
solinv = INT16(&packet[WD(10)]) & 0x5;
if (solinv) gps->fix &= ~0x3; /* do we know whether it is a 2D or 3D fix? */
else gps->fix |= 0x3;
gps->lat = INT32(&packet[WD(27)]) * 1.0e-8;
gps->lon = INT32(&packet[WD(29)]) * 1.0e-8;
gps->alt = INT32(&packet[WD(31)]) * 1.0e-2;
speed = ((unsigned int)INT32(&packet[WD(34)])) * 1.0e-2;
bearing = radtodeg(INT16(&packet[WD(36)]) * 1.0e-3);
if (bearing < 0) bearing += 2 * M_PI;
gps->bearing = radtodeg(bearing);
gps->spd_up = 0.0;
gps->spd_east = sin(bearing) * speed;
gps->spd_north = cos(bearing) * speed;
gps->time = conv_date(INT16(&packet[WD(21)]),
INT16(&packet[WD(20)]), INT16(&packet[WD(19)])) +
INT16(&packet[WD(24)])+(60*INT16(&packet[WD(23)])) +
(3600*INT16(&packet[WD(22)]));
gps->updated |= GPS_STATE_FIX | GPS_STATE_COORD | GPS_STATE_BEARING | GPS_STATE_SPEED;
}
void bwrite(Complx *buffer, size_t num) {
// Write num Complx numbers to the buffer, increment the pointer
WriteDirect WD(ramdisk, diskbuffer);
int sizebytes = num*sizeof(Complx);
WD.BlockingAppend(filename, (char*)buffer, sizebytes);
}
