add --version and -V

7 files changed, 36 insertions, 9 deletions

diff --git a/src/c/Makefile b/src/c/Makefile
index 152121a..35bc645 100644
--- a/src/c/Makefile
+++ b/src/c/Makefile
@@ -1,11 +1,14 @@
+VERSION=\"v1.0.3\"
 UNAME := $(shell uname)
 CC = gcc
-QUIKR_TRAIN_CFLAGS = -O3 -s -mtune=native -Wall -lm -lz -D$(UNAME)
-QUIKR_CFLAGS = -O3 -s -mtune=native -Wextra -Wall -lm -pthread -L../ -I../ -std=gnu99 -fopenmp -D$(UNAME) -lz
+QUIKR_TRAIN_CFLAGS = -O3 -s -mtune=native -Wall -lm -lz -D$(UNAME) -DVERSION=$(VERSION)
+MULTIFASTA_CFLAGS = -O3 -s -mtune=native -Wextra -Wall -lm -lz -pthread -L../ -I../ -std=gnu99 -fopenmp -D$(UNAME) -DVERSION=$(VERSION)
+QUIKR_CFLAGS= -O3 -s -mtune=native -Wextra -Wall -lm -lz -std=gnu99 -D$(UNAME) -DVERSION=$(VERSION)
+
 all: quikr_train_ quikr_ multifasta_to_otu_
 
 multifasta_to_otu_:
-	$(CC) multifasta_to_otu.c quikr_functions.c nnls.c -o multifasta_to_otu $(QUIKR_CFLAGS)
+	$(CC) multifasta_to_otu.c quikr_functions.c nnls.c -o multifasta_to_otu $(MULTIFASTA_CFLAGS)
 quikr_train_:
 	$(CC) quikr_train.c quikr_functions.c -o quikr_train $(QUIKR_TRAIN_CFLAGS)
 quikr_:
diff --git a/src/c/multifasta_to_otu.1 b/src/c/multifasta_to_otu.1
index 2a00d5c..7e1fb83 100644
--- a/src/c/multifasta_to_otu.1
+++ b/src/c/multifasta_to_otu.1
@@ -51,6 +51,9 @@ the OTU table, with NUM_READS_PRESENT for each sample which is compatible with Q
 .TP
 .B \-v, --verbose
 verbose mode.
+.TP
+.B \-V, --version
+print version.
 .SH USAGE
 This program will use a large amount of memory, and CPU time. 
 You can reduce the number of cores used, and thus memory, by specifying the -j flag with aspecified number of jobs. Otherwise multifasta_to_otu will run one job per cpu core.
diff --git a/src/c/multifasta_to_otu.c b/src/c/multifasta_to_otu.c
index 01a4f0e..6d704dd 100644
--- a/src/c/multifasta_to_otu.c
+++ b/src/c/multifasta_to_otu.c
@@ -13,7 +13,7 @@
 
 #define sensing_matrix(i,j) (sensing_matrix[width*i + j])
 #define solutions(i,j) (solutions[sequences*i+ j])
-#define USAGE "Usage:\n\tmultifasta_to_otu [OPTION...] - create a QIIME OTU table based on Quikr results. \n\nOptions:\n\n-i, --input-directory\n\tthe directory containing the samples' fasta files of reads (note each file should correspond to a separate sample)\n\n-f, --sensing-fasta\n\tlocation of the fasta file database used to create the sensing matrix (fasta format)\n\n-s, --sensing-matrix\n\t location of the sensing matrix. (sensing from quikr_train)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-l, --lambda\n\tlambda value to use. (default value is 10000)\n\n-j, --jobs\n\t specifies how many jobs to run at once. (default value is the number of CPUs)\n\n-o, --output\n\tthe OTU table, with NUM_READS_PRESENT for each sample which is compatible with QIIME's convert_biom.py (or a sequence table if not OTU's)\n\n-v, --verbose\n\tverbose mode."
+#define USAGE "Usage:\n\tmultifasta_to_otu [OPTION...] - create a QIIME OTU table based on Quikr results. \n\nOptions:\n\n-i, --input-directory\n\tthe directory containing the samples' fasta files of reads (note each file should correspond to a separate sample)\n\n-f, --sensing-fasta\n\tlocation of the fasta file database used to create the sensing matrix (fasta format)\n\n-s, --sensing-matrix\n\t location of the sensing matrix. (sensing from quikr_train)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-l, --lambda\n\tlambda value to use. (default value is 10000)\n\n-j, --jobs\n\t specifies how many jobs to run at once. (default value is the number of CPUs)\n\n-o, --output\n\tthe OTU table, with NUM_READS_PRESENT for each sample which is compatible with QIIME's convert_biom.py (or a sequence table if not OTU's)\n\n-v, --verbose\n\tverbose mode.\n\n-V, --version\n\tprint version."
 
 int main(int argc, char **argv) {
 
@@ -58,11 +58,12 @@ int main(int argc, char **argv) {
       {"sensing-fasta",  required_argument, 0, 'f'},
       {"sensing-matrix", required_argument, 0, 's'},
       {"verbose", no_argument, 0, 'v'},
+      {"version", no_argument, 0, 'V'},
       {0, 0, 0, 0}
     };
     int option_index = 0;
 
-    c = getopt_long (argc, argv, "k:l:f:s:i:o:j:hv", long_options, &option_index);
+    c = getopt_long (argc, argv, "k:l:f:s:i:o:j:hvV", long_options, &option_index);
 
     if (c == -1)
       break;
@@ -92,6 +93,10 @@ int main(int argc, char **argv) {
       case 'v':
         verbose = 1;
         break;
+      case 'V':
+        printf("%s\n", VERSION);
+        exit(EXIT_SUCCESS);
+        break;
       case 'h':
         puts(USAGE);
         exit(EXIT_SUCCESS);
diff --git a/src/c/quikr.1 b/src/c/quikr.1
index 9b32667..4afb52e 100644
--- a/src/c/quikr.1
+++ b/src/c/quikr.1
@@ -47,6 +47,9 @@ OTU_FRACTION_PRESENT a vector representing the percentage of database sequence's
 .B \-v, --verbose
 verbose mode.
 .TP
+.B \-V, --version
+print version.
+.TP
 .B \-d, --debug
 debug mode, this will save our sensing matrix and sample matrix (A and B matricies) in files called 'sensing.matrix' and 'count.matrix' for debugging purposes
 .SH EXAMPLES
diff --git a/src/c/quikr.c b/src/c/quikr.c
index f588c5f..9946a30 100644
--- a/src/c/quikr.c
+++ b/src/c/quikr.c
@@ -12,7 +12,7 @@
 #include "quikr_functions.h"
 
 #define sensing_matrix(i,j) (sensing_matrix[width*i + j])
-#define USAGE "Usage:\n\tquikr [OPTION...] - Calculate estimated frequencies of bacteria in a sample.\n\nOptions:\n\n-i, --input\n\tthe sample's fasta file of NGS READS (fasta format)\n\n-f, --sensing-fasta\n\tlocation of the fasta file database used to create the sensing matrix (fasta format)\n\n-s, --sensing-matrix\n\t location of the sensing matrix. (trained from quikr_train)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-l, --lambda\n\tlambda value to use. (default value is 10000)\n\n-o, --output\n\tOTU_FRACTION_PRESENT a vector representing the percentage of database sequence's presence in sample. (csv output)\n\n-v, --verbose\n\tverbose mode.\n\n-d, --debug\n\tdebug mode, read manpage for more details"
+#define USAGE "Usage:\n\tquikr [OPTION...] - Calculate estimated frequencies of bacteria in a sample.\n\nOptions:\n\n-i, --input\n\tthe sample's fasta file of NGS READS (fasta format)\n\n-f, --sensing-fasta\n\tlocation of the fasta file database used to create the sensing matrix (fasta format)\n\n-s, --sensing-matrix\n\t location of the sensing matrix. (trained from quikr_train)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-l, --lambda\n\tlambda value to use. (default value is 10000)\n\n-o, --output\n\tOTU_FRACTION_PRESENT a vector representing the percentage of database sequence's presence in sample. (csv output)\n\n-v, --verbose\n\tverbose mode.\n\n-V, --version\n\tprint version.\n\n-d, --debug\n\tdebug mode, read manpage for more details"
 
 int main(int argc, char **argv) {
 
@@ -45,13 +45,14 @@ int main(int argc, char **argv) {
       {"sensing-fasta",  required_argument, 0, 'f'},
       {"sensing-matrix", required_argument, 0, 's'},
       {"verbose", no_argument, 0, 'v'},
+      {"version", no_argument, 0, 'V'},
       {"debug", no_argument, 0, 'd'},
       {0, 0, 0, 0}
     };
 
     int option_index = 0;
 
-    c = getopt_long (argc, argv, "k:l:f:s:i:o:hdv", long_options, &option_index);
+    c = getopt_long (argc, argv, "k:l:f:s:i:o:hdvV", long_options, &option_index);
 
     if (c == -1)
       break;
@@ -81,6 +82,10 @@ int main(int argc, char **argv) {
       case 'v':
         verbose = 1;
         break;
+      case 'V':
+        printf("%s\n", VERSION);
+        exit(EXIT_SUCCESS);
+        break;
       case 'h':
         printf("%s\n", USAGE);
         exit(EXIT_SUCCESS);
diff --git a/src/c/quikr_train.1 b/src/c/quikr_train.1
index 6a058cd..ba6d17f 100644
--- a/src/c/quikr_train.1
+++ b/src/c/quikr_train.1
@@ -34,6 +34,9 @@ the sensing matrix. (a gzip'd text file)
 .TP
 .B \-v, --verbose
 verbose mode.
+.TP
+.B \-V, --version
+print version.
 .SH EXAMPLES
 Use quikr_train to generate a sensing matrix from rdp7.fasta. This uses 6mers by default.
 .P
diff --git a/src/c/quikr_train.c b/src/c/quikr_train.c
index b169fcc..b5b111f 100644
--- a/src/c/quikr_train.c
+++ b/src/c/quikr_train.c
@@ -10,7 +10,7 @@
 
 #include "quikr_functions.h"
 
-#define USAGE "Usage:\n\tquikr_train [OPTION...] - train a database for use with quikr.\n\nOptions:\n\n-i, --input\n\tthe database of sequences to create the sensing matrix (fasta format)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-o, --output\n\tthe sensing matrix. (a gzip'd text file)\n\n-v, --verbose\n\tverbose mode."
+#define USAGE "Usage:\n\tquikr_train [OPTION...] - train a database for use with quikr.\n\nOptions:\n\n-i, --input\n\tthe database of sequences to create the sensing matrix (fasta format)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-o, --output\n\tthe sensing matrix. (a gzip'd text file)\n\n-v, --verbose\n\tverbose mode.\n\n-V, --version\n\tprint version."
 
 int main(int argc, char **argv) {
 
@@ -36,6 +36,7 @@ int main(int argc, char **argv) {
   while (1) {
     static struct option long_options[] = {
       {"verbose", no_argument, 0, 'v'},
+      {"version", no_argument, 0, 'V'},
       {"input", required_argument, 0, 'i'},
       {"kmer",  required_argument, 0, 'k'},
       {"output", required_argument, 0, 'o'},
@@ -44,7 +45,7 @@ int main(int argc, char **argv) {
 
     int option_index = 0;
 
-    c = getopt_long (argc, argv, "i:o:k:hv", long_options, &option_index);
+    c = getopt_long (argc, argv, "i:o:k:hvV", long_options, &option_index);
 
     if (c == -1)
       break;
@@ -62,6 +63,10 @@ int main(int argc, char **argv) {
       case 'v':
         verbose = 1;
         break;
+      case 'V':
+        printf("%s\n", VERSION);
+        exit(EXIT_SUCCESS);
+        break;
       case 'h':
         printf("%s\n", USAGE);
         exit(EXIT_SUCCESS);