void PropertyManager::parseBlock(BlockProperties& properties)
{
parseMethods(properties);
if (!properties.luaRef["perBlock"].isNil())
parsePerBlockProperties(properties);
if (!properties.luaRef["events"].isNil())
parseEvents(properties);
}
QDBusMetaObjectGenerator::QDBusMetaObjectGenerator(const QString &interfaceName,
const QDBusIntrospection::Interface *parsedData)
: data(parsedData), interface(interfaceName)
{
if (data) {
parseProperties();
parseSignals(); // call parseSignals first so that slots override signals
parseMethods();
}
}
void parseInterface( JSON::Entity const &interfaceObject, Interface &interface )
{
JSON::ObjectDecoder interfaceObjectDecoder( interfaceObject );
JSON::Entity keyString, valueEntity;
while ( interfaceObjectDecoder.getNext( keyString, valueEntity ) )
{
try
{
if ( keyString.stringIs( "methods", 7 ) )
{
valueEntity.requireArray();
parseMethods( valueEntity, interface.methods );
}
}
catch ( Exception e )
{
interfaceObjectDecoder.rethrow( e );
}
}
}
/**
* The function to call when running the 'similarity' command.
*/
RunSimilarity::RunSimilarity(int argc, char *argv[]) {
// Initialize some of the program parameters.
min_obs = 30;
// Defaults for mutual information B-spline estimate.
mi_bins = 10;
mi_degree = 3;
// Set the default threshold for expression values.
threshold = -INFINITY;
// Initialize the array of method names. We set it to 10 as max. We'll
// most likely never have this many of similarity methods available.
method = (char **) malloc(sizeof(char *) * 10);
// The concatenated method.
char * cmethod = NULL;
// loop through the incoming arguments until the
// getopt_long function returns -1. Then we break out of the loop
// The value returned by getopt_long.
int c;
while(1) {
int option_index = 0;
// specify the long options. The values returned are specified to be the
// short options which are then handled by the case statement below
static struct option long_options[] = {
{"help", no_argument, 0, 'h' },
{"method", required_argument, 0, 'm' },
{"min_obs", required_argument, 0, 'o' },
{"th", required_argument, 0, 's' },
// Filtering options.
{"set1", required_argument, 0, '1' },
{"set2", required_argument, 0, '2' },
// Mutual information options.
{"mi_bins", required_argument, 0, 'b' },
{"mi_degree", required_argument, 0, 'd' },
// Expression matrix options.
{"rows", required_argument, 0, 'r' },
{"cols", required_argument, 0, 'c' },
{"headers", no_argument, &headers, 1 },
{"omit_na", no_argument, &omit_na, 1 },
{"func", required_argument, 0, 'f' },
{"na_val", required_argument, 0, 'n' },
{"ematrix", required_argument, 0, 'e' },
// Last element required to be all zeros.
{0, 0, 0, 0 }
};
// get the next option
c = getopt_long(argc, argv, "m:o:b:d:j:i:t:a:l:r:c:f:n:e:s:h", long_options, &option_index);
// if the index is -1 then we have reached the end of the options list
// and we break out of the while loop
if (c == -1) {
break;
}
// handle the options
switch (c) {
case 0:
break;
case 'm':
cmethod = optarg;
break;
case 'o':
min_obs = atoi(optarg);
break;
case 's':
threshold = atof(optarg);
break;
// Mutual information options.
case 'b':
mi_bins = atoi(optarg);
break;
case 'd':
mi_degree = atoi(optarg);
break;
// Expression matrix options.
case 'e':
infilename = optarg;
break;
case 'r':
rows = atoi(optarg);
break;
case 'c':
cols = atoi(optarg);
break;
case 'n':
na_val = optarg;
break;
case 'f':
strcpy(func, optarg);
break;
// Help and catch-all options.
case 'h':
printUsage();
exit(-1);
break;
case '?':
exit(-1);
break;
case ':':
printUsage();
exit(-1);
break;
default:
printUsage();
exit(-1);
}
}
// Make sure the similarity method is valid.
if (!cmethod) {
fprintf(stderr,"Please provide the method (--method option).\n");
exit(-1);
}
parseMethods(cmethod);
// make sure the required arguments are set and appropriate
if (!infilename) {
fprintf(stderr,"Please provide an expression matrix (--ematrix option).\n");
exit(-1);
}
// make sure we have a positive integer for the rows and columns of the matrix
if (rows < 0 || rows == 0) {
fprintf(stderr, "Please provide a positive integer value for the number of rows in the \n");
fprintf(stderr, "expression matrix (--rows option).\n");
exit(-1);
}
if (cols < 0 || cols == 0) {
fprintf(stderr, "Please provide a positive integer value for the number of columns in\n");
fprintf(stderr, "the expression matrix (--cols option).\n");
exit(-1);
}
if (omit_na && !na_val) {
fprintf(stderr, "Error: The missing value string should be provided (--na_val option).\n");
exit(-1);
}
// make sure the input file exists
if (access(infilename, F_OK) == -1) {
fprintf(stderr,"The input file does not exists or is not readable.\n");
exit(-1);
}
// Create and initialize the histogram for the distribution of coefficients.
histogram = (int *) malloc(sizeof(int) * HIST_BINS + 1);
for (int m = 0; m < HIST_BINS + 1; m++) {
histogram[m] = 0;
}
if (headers == 1) {
printf(" Reading header line\n");
}
printf(" Performing transformation: %s \n", func);
if (omit_na) {
printf(" Missing values are: '%s'\n", na_val);
}
printf(" Required observations: %d\n", min_obs);
for(int i = 0; i < this->num_methods; i++) {
printf(" Using similarity method: '%s'\n", method[i]);
if (strcmp(method[i], "mi") ==0) {
printf(" Bins for B-Spline estimate of MI: %d\n", mi_bins);
printf(" Degree for B-Spline estimate of MI: %d\n", mi_degree);
}
}
printf(" Minimal observed value: %f\n", threshold);
// Retrieve the data from the EMatrix file.
printf(" Reading expression matrix...\n");
ematrix = new EMatrix(infilename, rows, cols, headers, omit_na, na_val, func);
}
