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src/README src/cent_adjust.c src/find_connected.c src/flock1.c |
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| diff -r 7eab80f86779 -r 311a4f16c483 src/README --- a/src/README Mon Feb 27 13:26:09 2017 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| @@ -1,139 +0,0 @@ -This package contains R code for converting and transforming a binary -FCS file, using the FCSTrans software, and the C code for running the -flock1 and flock2 population identification software. - -src - contains the C code for flock1, flock2 and cent_adjust -bin - contains the compiled C code for flock1, flock2 and cent_adjust, - plus the R code for using the FCSTrans algorithm for file - conversion and data transformation. -doc - documentation for FCSTrans and FLOCK algorithms -example - sample data and output from FCSTrans and FLOCK - -To run this software sucessfully the code assumes the software was installed -in the /usr/local/flock directory and that R, plus the Bioconductor flowCore -module has been installed. If you use the ipconvert.sh shell script, you -may need to adjust the location of the RScript executable and the location -of the FCSTrans.R code by editing the shell script. - -############################################################################# -# Overview -############################################################################# -ImmPort-FLOCK - -FLOCK (FLOw Clustering without K), an automated population discovery tool for -multidimensional FCM data was designed to specifically take into account the -unique feature of FCM data and produce objective segregation of cell -populations. - -FLOCK parameter settings can be customized by defining Bins and Density -Threshold. The number of bins is an integer specifying the number of -equal-sized regions the data will be partitioned into on each axis. Increasing -the number of bins increases the sensitivity to detect rare populations but -may also result in single populations being divided. Density Threshold is the -cut-off value to separate the dense regions from background. It is a floating -point number that helps define population centers; increasing the threshold -may help separate major populations but could cause the algorithm to overlook -rare populations. - -############################################################################# -# Compiling C code -############################################################################# -cd bin -cc -o flock1 ../src/flock1.c ../src/find_connected.c -lm -cc -o flock2 ../src/flock2.c -lm -cc -o cent_adjust ../src/cent_adjust.c -lm - -############################################################################# -# FCSTrans -############################################################################# -A shell script named ipconvert.sh is included that runs the FCSTrans R -code for converting and transforming a binary FCS file. The output consists -of one text file containing the transformed channel intensity values and -another file containing a list of the FCS parameters. - -cd bin -/usr/local/flock/bin/ipconvert.sh ../example/data/FCS2.fcs -/usr/local/flock/bin/ipconvert.sh ../example/data/FCS3.fcs - -############################################################################# -# Running flock1 or flock2 -############################################################################# -Running the FLOCK1 and FLOCK2 algorithms generate 8 output files that have -generic file names. For this reason, it is recommended that one output -directory be created for one input file to the program. - -cd example/output/FCS2 -/usr/local/flock/bin/flock1 ../../data/FCS2.txt - -cd example/output/FCS3 -/usr/local/flock/bin/flock2 ../../data/FCS3.txt - -Files created: MFI.txt, percentage.txt, population_id.txt, profile.txt, - flock_results.txt, coordinates.txt, population_center.txt - and percentage.txt - -Usage Information for FLOCK1 ----------------------------------------------------------------------------- -basic mode: flock1 fcs.txt -advanced_ mode: flock1 fcs.txt num_bin density_index max_num_pop - -Usage Information for FLOCK2 ----------------------------------------------------------------------------- -basic mode: flock data_file -advanced mode 0 (specify maximum # of pops): flock data_file max_num_pop -advanced mode 1 (without # of pops): flock data_file num_bin density_index -advanced mode 2 (specify # of pops): flock data_file num_bin density_index - number_of_pop -advanced mode 3 (specify both # of pops): flock data_file num_bin density_index - number_of_pop max_num_pop - -FLOCK Output Files ----------------------------------------------------------------------------- -coordinates.txt: - Output is the intensity values for each marker and event - -flock_results.txt: - A combination of the input file, event identifiers and population - identifiers. - -MFI.txt: - Provides the mean fluorescence intensity for each population for each - marker/parameter - -population_id.txt: - Contains population identifiers (i.e, values from [1 to n] where n is - the population assigned to the corresponding events in the input data - file, one identifier per row.) - -population_center.txt: - Contains the centroid coordinates for each identified population - -percentage.txt: - Includes the population identifiers and percentage of events within that - population (relative to the whole data file) - -profile.txt: - Displays an expression profile, where the approximate expression level - for each marker is assigned a numeric value from 1-4, for each identified - population - -fcs_properties.txt: - Contains the number of events, number of populations, and number of - markers, as well as the algorithm parameters used in the analysis - -############################################################################# -# Running cent_adjust -############################################################################# -Running the cent_adjust algorithm generates 4 output files that have -generic file names. For this reason, it is recommened that one output -directory be created for one input file to the program. - -mkdir example/output/FCS2/cent_adjust -cd example/output/FCS2/cent_adjust -/usr/local/flock/bin/cent_adjust ../population_center.txt ../coordinates.txt - -Files created: MFI.txt, percentage.txt, population_id.txt and profile.txt - -Usage Information for cent_adjust ----------------------------------------------------------------------------- -basic mode: cent_adjust input_center input_data_file |
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| diff -r 7eab80f86779 -r 311a4f16c483 src/cent_adjust.c --- a/src/cent_adjust.c Mon Feb 27 13:26:09 2017 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| b'@@ -1,1009 +0,0 @@\n-/////////////////////////////////////////////////////////\n-// Cent_adjust version number and modification history\n-// ImmPort BISC project\n-// Author: Yu "Max" Qian\n-// v1.01: Oct 16, 2009\n-// Line 899 of the main function:\n-// Changed kmean_term=1 to kmean_term=2\n-//////////////////////////////////////////////////////////\n-\n-\n-#include <time.h>\n-#include <stdio.h>\n-#include <stdlib.h>\n-#include <math.h>\n-#include <string.h>\n-\n-#define DEBUG 0\n-#define LINE_LEN 1024\n-#define FILE_NAME_LEN 128\n-#define PARA_NAME_LEN 64\n-#define MAX_VALUE 1000000000\n-#define CUBE 0\n-\n-\n-void getctrfileinfo(FILE *f_src_ctr, long *num_clust)\n-{\n-\tint ch=\'\\n\';\n-\tint prev=\'\\n\';\n-\tlong num_rows=0;\n-\n-\twhile ((ch = fgetc(f_src_ctr))!= EOF )\n- {\n-\t\tif (ch == \'\\n\')\n- {\n-\t\t\t++num_rows;\n- }\n-\t\tprev = ch;\n- }\n-\tif (prev!=\'\\n\')\n-\t\t++num_rows;\n-\t\n-\t*num_clust=num_rows;\n-\t//printf("center file has %ld rows\\n", *num_clust);\n-}\n-\n-/************************************* Read basic info of the source file **************************************/\n-void getfileinfo(FILE *f_src, long *file_Len, long *num_dm, char *name_string, int *time_ID)\n-{\n-\tchar src[LINE_LEN];\n-\tchar current_name[64];\n-\tchar prv;\n-\n-\tlong num_rows=0;\n-\tlong num_columns=0;\n-\tint ch=\'\\n\';\n-\tint prev=\'\\n\';\n-\tlong time_pos=0;\n-\tlong i=0;\n-\tlong j=0;\n-\n-\t\n-\n-\tsrc[0]=\'\\0\';\n-\tfgets(src, LINE_LEN, f_src);\n-\n-\tname_string[0]=\'\\0\';\n-\tcurrent_name[0]=\'\\0\';\n-\tprv=\'\\n\';\n-\n-\twhile ((src[i]==\' \') || (src[i]==\'\\t\')) //skip space and tab characters\n-\t\ti++;\n-\n-\twhile ((src[i]!=\'\\r\') && (src[i]!=\'\\n\')) //repeat until the end of the line\n-\t{\n-\t\tcurrent_name[j]=src[i];\n-\t\t\n-\t\tif ((src[i]==\'\\t\') && (prv!=\'\\t\')) //a complete word\n-\t\t{\n-\t\t\tcurrent_name[j]=\'\\0\';\n-\t\t\t\n- /* \n- * Commented out John Campbell, June 10 2010\n- * We no longer want to automatically remove Time column.\n- * This column should have been removed by column selection\n- if (0!=strcmp(current_name,"Time"))\n- {\n- num_columns++; //num_columns does not inlcude the column of Time\n- time_pos++;\n- strcat(name_string,current_name); \n- strcat(name_string,"\\t");\n- }\n- else\n- {\n- *time_ID=time_pos;\n- }\n- */\n-\n- num_columns++;\n- strcat(name_string,current_name);\n- strcat(name_string,"\\t");\n-\n-\t\t current_name[0]=\'\\0\';\n-\t\t j=0;\t\t\t\n-\t\t}\t\t\n-\t\t\n-\t\tif ((src[i]==\'\\t\') && (prv==\'\\t\')) //a duplicate tab or space\n-\t\t{\n-\t\t\tcurrent_name[0]=\'\\0\';\n-\t\t\tj=0;\n-\t\t}\n-\t\t\n- if (src[i]!=\'\\t\')\n-\t j++;\n-\n-\t\t\n-\t\tprv=src[i];\n-\t\ti++;\n-\t}\n-\t\n-\tif (prv!=\'\\t\') //the last one hasn\'t been retrieved\n-\t{\n-\t\tcurrent_name[j]=\'\\0\';\n- /* \n- * Commented out John Campbell, June 10 2010\n- * We no longer want to automatically remove Time column.\n- * This column should have been removed by column selection\n- if (0!=strcmp(current_name,"Time"))\n- {\n- num_columns++;\n- strcat(name_string,current_name);\n- time_pos++;\n- }\n- else\n- {\n- *time_ID=time_pos;\n- }\n- */\n-\n- num_columns++;\n- strcat(name_string,current_name);\n-\t}\n-\n-\tif (DEBUG==1)\n-\t{\n-\t\tprintf("time_ID is %d\\n",*time_ID);\n-\t\tprintf("name_string is %s\\n",name_string);\n-\t}\n-\n-\t// # of rows\n-\n-\twhile ((ch = fgetc(f_src))!= EOF )\n- {\n-\t\tif (ch == \'\\n\')\n- {\n-\t\t\t++num_rows;\n- }\n-\t\tprev = ch;\n- }\n-\tif (prev!=\'\\n\')\n-\t\t++num_rows;\n-\t\n-\t*file_Len=num_rows;\n-\t*num_dm=num_columns; \n-\n-\t//printf("original file size is %ld; number of dimensions is %ld\\n", *file_Len, *num_dm);\n-}\n-\n-\n-\n-///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////\n-/************************************* Read the source file into uncomp_data **************************************/\n-void readsource(FILE *f_src, lo'..b'0;\n-\tlong j=0;\n-\n-\tlong *cluster_id;\n-\tlong *IDmapping; //this is to keep the original populationID of the center.txt\n-\n-\tdouble kmean_term=0;\n-\t\n-\tdouble **cluster_center;\n-\tdouble **orig_data;\n-\tdouble **normalized_data;\n-\t\t\n-/*\n-\t_strtime( tmpbuf );\n- printf( "Starting time:\\t\\t\\t\\t%s\\n", tmpbuf );\n-\t_strdate( tmpbuf );\n- printf( "Starting date:\\t\\t\\t\\t%s\\n", tmpbuf );\n-*/\n-\n-\tif (argc!=3)\n-\t{\n-\t\tprintf("usage: cent_adjust input_center input_data_file\\n"); \n-\t\texit(0);\n-\t}\t\n-\t\n-\n-\tf_src_ctr=fopen(argv[1],"r");\t\n-\t\n-\t//read source data\n-\tf_src=fopen(argv[2],"r");\n-\t\n-\tgetfileinfo(f_src, &file_Len, &num_dm, name_string, &time_id); //get the filelength, number of dimensions, and num/name of parameters\n-\n-\trewind(f_src); //reset data file pointer\t\n-\n-\torig_data = (double **)malloc(sizeof(double*)*file_Len);\n-\tmemset(orig_data,0,sizeof(double*)*file_Len);\n-\tfor (i=0;i<file_Len;i++)\n-\t{\n-\t\torig_data[i]=(double *)malloc(sizeof(double)*num_dm);\n-\t\tmemset(orig_data[i],0,sizeof(double)*num_dm);\n-\t}\n-\t\n-\treadsource(f_src, file_Len, num_dm, orig_data, time_id); //read the data;\n-\t\n-\tfclose(f_src);\n-\t/////////////////////////////////////////////////////////////////////////////\n-\tgetctrfileinfo(f_src_ctr, &num_clust); //get how many populations\n-\tnorm_used=0;\n-\tdist_used=0;\n-\tkmean_term=2; //modified on Oct 16, 2009: changed kmean_term=1 to kmean_term=2\n-\n-\trewind(f_src_ctr); //reset center file pointer\n-\n-\t//read population center\n-\tcluster_center=(double **)malloc(sizeof(double*)*num_clust);\n-\tmemset(cluster_center,0,sizeof(double*)*num_clust);\n-\tfor (i=0;i<num_clust;i++)\n-\t{\n-\t\tcluster_center[i]=(double*)malloc(sizeof(double)*num_dm);\n-\t\tmemset(cluster_center[i],0,sizeof(double)*num_dm);\n-\t}\n-\tfor (i=0;i<num_clust;i++)\n-\t\tfor (j=0;j<num_dm;j++)\n-\t\t\tcluster_center[i][j]=0;\n-\n-\tIDmapping=(long *)malloc(sizeof(long)*num_clust);\n-\tmemset(IDmapping,0,sizeof(long)*num_clust);\n-\n-\treadcenter(f_src_ctr,num_clust,num_dm,cluster_center,IDmapping); //read population center\n- fclose(f_src_ctr);\n-\n-\t/////////////////////////////////////////////////////////////////////////////\n-\tnormalized_data=(double **)malloc(sizeof(double*)*file_Len);\n-\tmemset(normalized_data,0,sizeof(double*)*file_Len);\n-\tfor (i=0;i<file_Len;i++)\n-\t{\n-\t\tnormalized_data[i]=(double *)malloc(sizeof(double)*num_dm);\n-\t\tmemset(normalized_data[i],0,sizeof(double)*num_dm);\n-\t}\n-\t\n-\ttran(orig_data, file_Len, num_dm, norm_used, normalized_data);\n-\t/************************************************* Compute number of clusters *************************************************/\n-\t\n-\tcluster_id=(long*)malloc(sizeof(long)*file_Len);\n-\tmemset(cluster_id,0,sizeof(long)*file_Len);\n-\n-\tassign_event(normalized_data,num_clust,dist_used,kmean_term,file_Len,num_dm,cluster_id,cluster_center,0);\n-\n-\t\n-\t//show(orig_data,cluster_id,file_Len,num_clust,num_dm,show_data,num_disp,name_string); \n-\tshow(orig_data, cluster_id, file_Len, num_clust, num_dm, name_string, IDmapping);\n-\n-\tf_cid=fopen("population_id.txt","w");\n-\n-\tfor (i=0;i<file_Len;i++)\n-\t\tfprintf(f_cid,"%ld\\n",IDmapping[cluster_id[i]]);\n-\t\t\n-\n-\tfclose(f_cid);\n- \n-\t//added April 16, 2009\n-\tf_mfi=fopen("MFI.txt","w");\n-\n-\tfor (i=0;i<num_clust;i++)\n-\t{\n-\t\tfprintf(f_mfi,"%ld\\t",IDmapping[i]);\n-\n-\t\tfor (j=0;j<num_dm;j++)\n-\t\t{\n-\t\t\tif (j==num_dm-1)\n-\t\t\t\tfprintf(f_mfi,"%.0f\\n",cluster_center[i][j]);\n-\t\t\telse\n-\t\t\t\tfprintf(f_mfi,"%.0f\\t",cluster_center[i][j]);\n-\t\t}\n-\t}\n-\tfclose(f_mfi);\n-\n-\t//ended April 16, 2009\n-\n-\tfor (i=0;i<num_clust;i++)\n-\t\tfree(cluster_center[i]);\n-\tfree(cluster_center);\n-\t\t\n-\n-\t/********************************************** Release memory ******************************************/\n- \n-\tfor (i=0;i<file_Len;i++)\n-\t{\n-\t\tfree(orig_data[i]);\t\t\n-\t\tfree(normalized_data[i]);\n-\t}\n-\t\n-\tfree(orig_data);\n-\tfree(normalized_data);\n-\tfree(cluster_id);\n-\tfree(IDmapping);\n-\n-/*\n-\t_strtime( tmpbuf );\n- printf( "Ending time:\\t\\t\\t\\t%s\\n", tmpbuf );\n-\t_strdate( tmpbuf );\n- printf( "Ending date:\\t\\t\\t\\t%s\\n", tmpbuf );\n-*/\n-\n-}\n' |
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| diff -r 7eab80f86779 -r 311a4f16c483 src/find_connected.c --- a/src/find_connected.c Mon Feb 27 13:26:09 2017 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| @@ -1,176 +0,0 @@ -#include <stdlib.h> -#include <stdio.h> -#include <string.h> -#include <assert.h> - -//static const char *rcsid = "$Id: find_connected.c,v 1.1 2008/09/05 21:54:40 rpl Exp $"; - -int find_connected(int **G, int num_dense_grids, int ndim, int *grid_clusterID); -void depth_first(int startnode); - -void bail(const char *); /* exits via abort */ -static void check_clusters(int *gcID, int ndense); -static void merge_cluster(int from, int into); - - -/* Vars that will not change througout the depth-first recursion. We - store them here to avoid endless replication on the stack. */ -static int **Gr=0; -static int *gcID = 0; /* grid cluster IDs */ -static int *cluster_count=0; /* count of nodes per cluster */ -static int ndense=0; -static int ndim=0; -/* cid changes between depth-first searches, but is constant within a - single search, so it goes here. */ -static int cid=0; - -/* Find connected components in the graph of neighboring grids defined in G. - * - * Output: - * - * grid_clusterID[] -- cluster to which each dense grid was assigned - * return value -- number of clusters assigned. - */ -int find_connected(int **G, int n_dense_grids, int num_dm, int *grid_clusterID) -{ - int nclust=0; /* number of clusters found */ - int i; - int *subfac; - int subval=0,nempty=0; - int clustid=0; - - size_t sz = n_dense_grids*sizeof(int); - cluster_count = malloc(sz); - if(!cluster_count) - bail("find_connected: Unable to allocate %zd bytes.\n"); - memset(cluster_count,0,sz); - - /* set up the statics that will be used in the DFS */ - Gr=G; - gcID = grid_clusterID; - ndense = n_dense_grids; - ndim = num_dm; - - - for(i=0;i<ndense;++i) - grid_clusterID[i] = -1; - - for(i=0;i<ndense;++i) { - if(grid_clusterID[i] < 0) { /* grid hasn't been assigned yet */ - cid = nclust++; - depth_first(i); - } - } - -#ifndef NDEBUG - check_clusters(gcID,ndense); -#endif - - /* At this point we probably have some clusters that are empty due to merging. - We want to compact the cluster numbering to eliminate the empty clusters. */ - - subfac = malloc(sz); - if(!subfac) - bail("find_connected: Unable to allocate %zd bytes.\n"); - subval=0; - nempty=0; - - /* cluster #i needs to have its ID decremented by 1 for each empty cluster with - ID < i. Precaclulate the decrements in this loop: */ - for(i=0;i<nclust;++i) { - //clustid = grid_clusterID[i]; - if(cluster_count[i] == 0) { - subval++; - nempty++; - } - subfac[i] = subval; - } - - /* Now apply the decrements to all of the dense grids */ - for(i=0;i<ndense;++i) { - clustid = grid_clusterID[i]; - grid_clusterID[i] -= subfac[clustid]; - } - -#ifndef NDEBUG - // check_clusters(gcID,ndense); -#endif - - /* correct the number of clusters found */ - nclust -= nempty; - - return nclust; -} - - -/* Do a depth-first search for a single connected component in graph - * G. Start from node, tag the nodes found with cid, and record - * the tags in grid_clusterID. Also, record the node count in - * cluster_count. If we find a node that has already been assigned to - * a cluster, that means we're merging two clusters, so zero out the - * old cid's node count. - * - * Note that our graph is constructed as a DAG, so we can be - * guaranteed to terminate without checking for cycles. - * - * Note2: this function can potentially recurse to depth = ndense. - * Plan stack size accordingly. - * - * Output: - * - * grid_clusterID[] -- array where we tag the nodes. - * cluster_count[] -- count of the number of nodes per cluster. - */ - -void depth_first(int node) -{ - int i; - - if(gcID[node] == cid) // we're guaranteed no cycles, but it is possible to reach a node - return; // through two different paths in the same cluster. This early - // return saves us some unneeded work. - - /* Check to see if we are merging a cluster */ - if(gcID[node] >= 0) { - /* We are, so zero the count for the old cluster. */ - cluster_count[ gcID[node] ] = 0; - merge_cluster(gcID[node], cid); - return; - } - - /* Update for this node */ - gcID[node] = cid; - cluster_count[cid]++; - - /* Recursively search the child nodes */ - for(i=0; i<ndim; ++i) - if(Gr[node][i] >= 0) /* This is a child node */ - depth_first(Gr[node][i]); -} - -void bail(const char *msg) -{ - fprintf(stderr,"%s",msg); - abort(); -} - - -static void check_clusters(int *gcID, int ndense) -{ - int i; - - for(i=0; i<ndense; ++i) - if(gcID[i] < 0) { - fprintf(stderr,"faulty cluster id at i= %d\n",i); - abort(); - } -} - -static void merge_cluster(int from, int into) -{ - int i; - - for(i=0; i<ndense; ++i) - if(gcID[i] == from) - gcID[i] = into; -} |
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| diff -r 7eab80f86779 -r 311a4f16c483 src/flock1.c --- a/src/flock1.c Mon Feb 27 13:26:09 2017 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| b'@@ -1,2400 +0,0 @@\n-/*****************************************************************************\n-\t\n-\tFLOCK: FLOw cytometry Clustering without K (Named by: Jamie A. Lee and Richard H. Scheuermann) \n-\t\n-\tAuthor: (Max) Yu Qian, Ph.D.\n-\t\n-\tCopyright: Scheuermann Lab, Dept. of Pathology, UTSW\n-\t\n-\tDevelopment: November 2005 ~ Forever\n-\n-\tAlgorithm Status: May 2007: Release 1.0\n-\n-\tUsage: flock data_file\n-\t\t Note: the input file format must be channel values and the delimiter between two values must be a tab.\n-\n- Changes made July 23, 2010: made errors to STDERR\n-\tChanges made Nov 4, 2010: added one more error (select_num_bin<min_grid) || (select_num_bin>max_grid) to STDERR;\n-\t MAX_GRID changed to 50 as larger than 50 seems not useful for any file we have got\n-\t\n-******************************************************************************/\n-#include <time.h>\n-#include <stdio.h>\n-#include <stdlib.h>\n-#include <math.h>\n-#include <string.h>\n-#include <sys/stat.h>\n-#include <unistd.h>\n-#include <assert.h>\n-\n-\n-#define DEBUG 0\n-#define LINE_LEN 1024\n-#define FILE_NAME_LEN 128\n-#define PARA_NAME_LEN 64\n-#define MAX_VALUE 1000000000\n-#define MIN_GRID 6\n-#define MAX_GRID 50\n-\n-#define NORM_METHOD 2 //2 if z-score; 0 if no normalization; 1 if min-max \n-#define KMEANS_TERM 100\n-//#define MAX_NUM_POP 30\n-\n-\n-int find_connected(int **G, int num_dense_grids, int ndim, int *grid_clusterID);\n-\n-/************* Read basic info of the source file ****************************/\n-void getfileinfo(FILE *f_src, int *file_Len, int *num_dm, char *name_string, int *time_ID)\n-{\n- char src[LINE_LEN];\n- char current_name[64];\n- char prv;\n-\n- int num_rows=0;\n- int num_columns=0;\n- int ch=\'\\n\';\n- int prev=\'\\n\';\n- int time_pos=0;\n- int i=0;\n- int j=0;\n- int sw=0;\n-\n- src[0]=\'\\0\';\n- fgets(src, LINE_LEN, f_src);\n-\n- if ((src[0]==\'F\') && (src[1]==\'C\') && (src[2]==\'S\'))\n-\t{\n-\t\tfprintf(stderr,"the correct input format is a tab-delimited txt file, instead of FCS file.\\n");\n-\t\tabort();\n-\t}\n-\n- name_string[0]=\'\\0\';\n- current_name[0]=\'\\0\';\n- prv=\'\\n\';\n-\n- // skip space and tab characters\n- while ((src[i]==\' \') || (src[i]==\'\\t\'))\n- i++;\n-\n- // repeat until the end of line is reached\n- while ((src[i]!=\'\\0\') && (src[i]!=\'\\n\') && (src[i]!=\'\\r\'))\n- {\n- current_name[j]=src[i];\n-\t\t\n- if ((src[i]==\'\\t\') && (prv!=\'\\t\')) //a complete word\n- {\n- current_name[j]=\'\\0\';\n-\t\t\t\n- if (0!=strcmp(current_name,"Time"))\n- {\n- num_columns++; //num_columns does not inlcude the column of Time\n- time_pos++;\n- if (sw) {\n- strcat(name_string,"\\t");\n- }\n- strcat(name_string,current_name); \n- sw = 1;\n- }\n- else\n- {\n- *time_ID=time_pos;\n- }\n- \n- \n- current_name[0]=\'\\0\';\n- j=0;\t\t\t\n- }\t\t\n-\t\t\n- if ((src[i]==\'\\t\') && (prv==\'\\t\')) //a duplicate tab or space\n- {\n- current_name[0]=\'\\0\';\n- j=0;\n- }\n-\t\t\n- if (src[i]!=\'\\t\')\n- j++;\n-\t\t\n- prv=src[i];\n- i++;\n- }\n-\t\n- if (prv!=\'\\t\') //the last one hasn\'t been retrieved\n- {\n- current_name[j]=\'\\0\';\n- \n- if (0!=strcmp(current_name,"Time"))\n- {\n- num_columns++;\n- strcat(name_string,"\\t");\n- strcat(name_string,current_name);\n- time_pos++;\n- }\n- else\n- {\n- *time_ID=time_pos;\n- }\n- \n- \n- }\n- if (DEBUG==1)\n- {\n- printf("time_ID is %d\\n",*time_ID);\n- printf("name_string is %s\\n",name_string);\n- }\n-\n- //start computing # of rows\n-\n- while ((ch = fgetc(f_src))!= EOF )\n- {\n- if (ch == \'\\n\')\n- {\n- ++num_rows;\n- }\n- prev = ch;\n- }\n- if (prev!=\'\\n\')\n- ++num_rows;\n-\n- //added on July 23, 2010\n- if (num_rows<50)\n- {\n- fprintf(stderr,"Number of events '..b'lation_ID=(int*)malloc(sizeof(int)*file_Len);\n- memset(all_population_ID,0,sizeof(int)*file_Len);\n-\n- kmeans(normalized_data, num_population, KMEANS_TERM, file_Len, num_dm, all_population_ID, population_center);\n- show(input_data, all_population_ID, file_Len, num_population, num_dm, para_name_string);\n-\n- ID2Center_all(input_data,file_Len,num_dm,num_population,all_population_ID,population_center);\n- \n-\n- f_cid=fopen("population_id.txt","w");\n- f_ctr=fopen("population_center.txt","w");\n- f_out=fopen("coordinates.txt","w");\n- f_results=fopen("flock_results.txt","w");\n-\n-/*\n- f_parameters=fopen("parameters.txt","w");\n- fprintf(f_parameters,"Number_of_Bins\\t%d\\n",num_bin);\n- fprintf(f_parameters,"Density\\t%f\\n",aver_index);\n- fclose(f_parameters);\n-*/\n-\n- for (i=0;i<file_Len;i++)\n-\tfprintf(f_cid,"%d\\n",all_population_ID[i]+1); //all_population_ID[i] changed to all_population_ID[i]+1 to start from 1 instead of 0: April 16, 2009\n-\n- /*\n- * New to check for min/max to add to parameters.txt\n- *\n- */\n- \n- fprintf(f_out,"%s\\n",para_name_string);\n- //fprintf(f_results,"%s\\tEvent\\tPopulation\\n",para_name_string);\n- fprintf(f_results,"%s\\tPopulation\\n",para_name_string);\n- for (i=0;i<file_Len;i++)\n- {\n-\tfor (j=0;j<num_dm;j++)\n-\t{\n-\t\tif (input_data[i][j] < min) {\n-\t\t\tmin = (int)input_data[i][j];\n-\t\t}\n-\t\tif (input_data[i][j] > max) {\n-\t\t\tmax = (int)input_data[i][j];\n-\t\t}\n-\t\tif (j==num_dm-1)\n-\t\t{\n-\t\t\tfprintf(f_out,"%d\\n",(int)input_data[i][j]);\n-\t\t\tfprintf(f_results,"%d\\t",(int)input_data[i][j]);\n-\t\t}\n-\t\telse\n-\t\t{\n-\t\t\tfprintf(f_out,"%d\\t",(int)input_data[i][j]);\n-\t\t\tfprintf(f_results,"%d\\t",(int)input_data[i][j]);\n-\t\t}\n-\t}\n-\t//fprintf(f_results,"%d\\t",i + 1);\n-\tfprintf(f_results,"%d\\n",all_population_ID[i]+1); //all_population_ID[i] changed to all_population_ID[i]+1 to start from 1 instead of 0: April 16, 2009\n- }\n-\n-/*\n- f_parameters=fopen("parameters.txt","w");\n- fprintf(f_parameters,"Number_of_Bins\\t%d\\n",num_bin);\n- fprintf(f_parameters,"Density\\t%d\\n",den_t_event);\n- fprintf(f_parameters,"Min\\t%d\\n",min);\n- fprintf(f_parameters,"Max\\t%d\\n",max);\n- fclose(f_parameters);\n-*/\n-\n- f_properties=fopen("fcs.properties","w");\n- fprintf(f_properties,"Bins=%d\\n",num_bin);\n- fprintf(f_properties,"Density=%d\\n",den_t_event);\n- fprintf(f_properties,"Min=%d\\n",min);\n- fprintf(f_properties,"Max=%d\\n",max);\n- fprintf(f_properties,"Populations=%d\\n",num_population);\n- fprintf(f_properties,"Events=%d\\n",file_Len);\n- fprintf(f_properties,"Markers=%d\\n",num_dm);\n- fclose(f_properties);\n-\n-\n- for (i=0;i<num_population;i++) {\n-\t/* Add if we want to include population id in the output\n-\t*/\n-\tfprintf(f_ctr,"%d\\t",i+1); //i changed to i+1 to start from 1 instead of 0: April 16, 2009\n-\n-\tfor (j=0;j<num_dm;j++) {\n-\t\tif (j==num_dm-1)\n-\t\t\tfprintf(f_ctr,"%.0f\\n",population_center[i][j]);\n-\t\telse\n-\t\t\tfprintf(f_ctr,"%.0f\\t",population_center[i][j]);\n-\t}\n- }\n-\n- \t//added April 16, 2009\n-\tf_mfi=fopen("MFI.txt","w");\n-\n-\tfor (i=0;i<num_population;i++)\n-\t{\n-\t\tfprintf(f_mfi,"%d\\t",i+1);\n-\n-\t\tfor (j=0;j<num_dm;j++)\n-\t\t{\n-\t\t\tif (j==num_dm-1)\n-\t\t\t\tfprintf(f_mfi,"%.0f\\n",population_center[i][j]);\n-\t\t\telse\n-\t\t\t\tfprintf(f_mfi,"%.0f\\t",population_center[i][j]);\n-\t\t}\n-\t}\n-\tfclose(f_mfi);\n-\n-\t//ended April 16, 2009\n-\t\t\t\n- fclose(f_cid);\n- fclose(f_ctr);\n- fclose(f_out);\n- fclose(f_results);\n-\n-\n- for (i=0;i<num_population;i++)\n- {\n-\tfree(population_center[i]);\n- }\n- free(population_center);\n- \n-\n- for (i=0;i<file_Len;i++)\n- free(normalized_data[i]);\n- free(normalized_data);\t\n-\t\n- free(grid_populationID);\n-\n- free(cluster_populationID);\n- free(grid_clusterID);\n- free(cluster_ID);\n-\n- for (i=0;i<file_Len;i++)\n- free(input_data[i]);\n- free(input_data);\n-\n- free(grid_ID);\n- free(population_ID);\n- free(all_population_ID);\n- free(eventID_To_denseventID);\n-\t\t\n- ///////////////////////////////////////////////////////////\n- printf("Ending time:\\t\\t\\t\\t");\n- fflush(stdout);\n- system("/bin/date");\n-\n- return 0;\n-\n-}\n' |