secured push against cache

RIVLower.h

@@ -7,6 +7,7 @@
 #include <unistd.h>
 #include <sys/stat.h>
 #include "RIVaccessories.h"
+#include "assert.h"
 /* RIVSIZE macro defines the dimensionality off the RIVs we will use
  * 25000 is the standard, but can be redefined specifically
  */
@@ -14,8 +15,8 @@
 #define RIVSIZE 25000
 #endif
 
-#if RIVSIZE<0
-#error "RIVSIZE must be a positive number (preferably a large positive)"
+#if RIVSIZE<4
+#error "RIVSIZE must be a positive number, greater than 4 (preferably a large positive)"
 #endif
 
 /* NONZeros macro defines the number of non-zero values that will be generated
@@ -36,7 +37,7 @@
  * that do not use lexpull/push
  */
 #ifndef CACHESIZE
-#define CACHESIZE 5000
+#define CACHESIZE 10000
 #endif
 
 #if CACHESIZE<0
@@ -57,10 +58,10 @@ typedef struct{
 	char name[100];
 	int *values;
 	int *locations;
-	size_t count;
-	float magnitude;
-	int contextSize;
+	int count;
 	int frequency;
+	int contextSize;
+	float magnitude;
 }sparseRIV;
 /* the denseRIV is a RIV form optimized for overwhelmingly non-0 vectors
  * this is rarely the case, but its primary use is for performing vector
@@ -68,11 +69,11 @@ typedef struct{
  * performed between sparse and dense (hetero-arithmetic)
  */
 typedef struct{
-	int cached;
 	char name[100];
+	int cached;
 	int frequency;
-	float magnitude;
 	int contextSize;
+	float magnitude;
 	int values[RIVSIZE];
 }denseRIV;
 
@@ -99,13 +100,13 @@ sparseRIV consolidateD2S(int *denseInput);  //#TODO fix int*/denseRIV confusion
  * this produces an "implicit" RIV which can be used with the mapI2D function
  * to create a denseRIV.
  */
-void makeSparseLocations(char* word,  int *seeds, size_t seedCount);
+void makeSparseLocations(char* word,  int *seeds, int seedCount);
 
 /* mapI2D maps an "implicit RIV" that is, an array of index values, 
  * arranged by chronological order of generation (as per makesparseLocations)
  * it assigns, in the process of mapping, values according to ordering
  */
-int* mapI2D(int *locations, size_t seedCount);
+int* mapI2D(int *locations, int seedCount);
 
 /* highly optimized method for adding vectors.  there is no method 
  * included for adding D2D or S2S, as this system is faster-enough
@@ -121,7 +122,7 @@ int cacheDump();
 /* adds all elements of an implicit RIV (a sparseRIV represented without values)
  * to a denseRIV.  used by the file2L2 functions in aggregating a document vector
  */
-int* addI2D(int* destination, int* locations, size_t seedCount);
+int* addI2D(int* destination, int* locations, int seedCount);
 
 /*subtracts a words vector from its own context.  regularly used in lex building
  */
@@ -136,6 +137,7 @@ int* addS2D(int* destination, sparseRIV input){// #TODO fix destination paramete
 	
 	/* apply values at an index based on locations */
 	while(locations_slider<locations_stop){
+		
 		destination[*locations_slider] += *values_slider;
 		locations_slider++;
 		values_slider++;
@@ -144,7 +146,7 @@ int* addS2D(int* destination, sparseRIV input){// #TODO fix destination paramete
 	return destination;
 }
 
-int* mapI2D(int *locations, size_t valueCount){// #TODO fix destination parameter vs calloc of destination
+int* mapI2D(int *locations, int valueCount){// #TODO fix destination parameter vs calloc of destination
 	int *destination = (int*)calloc(RIVSIZE,sizeof(int));
 	int *locations_slider = locations;
 	int *locations_stop = locations_slider+valueCount;
@@ -160,7 +162,7 @@ int* mapI2D(int *locations, size_t valueCount){// #TODO fix destination paramete
 
 	return destination;
 }
-int* addI2D(int* destination, int *locations, size_t valueCount){// #TODO fix destination parameter vs calloc of destination
+int* addI2D(int* destination, int *locations, int valueCount){// #TODO fix destination parameter vs calloc of destination
 	int *locations_slider = locations;
 	int *locations_stop = locations_slider+valueCount;
 
@@ -203,6 +205,7 @@ sparseRIV consolidateD2S(int *denseInput){
 		}
 	}
 	/* a slot is opened for the locations/values pair */
+	
 	output.locations = (int*) malloc(output.count*2*sizeof(int));
 	if(!output.locations){
 		printf("memory allocation failed"); //*TODO enable fail point knowledge and security
@@ -220,7 +223,7 @@ sparseRIV consolidateD2S(int *denseInput){
 
 
 
-void makeSparseLocations(char* word,  int *locations, size_t count){
+void makeSparseLocations(char* word,  int *locations, int count){
 	locations+=count;
 	srand(wordtoSeed(word));
 	int *locations_stop = locations+NONZEROS;

RIVclasses.c

+#include <stdio.h>
+#define CACHESIZE 0
+#define CACHEEXCLUSIVE 1
+#define RIVSIZE 50000
+#include "RIVtools.h"
+char* stem(char* word);
+int main(){
+	lexOpen("consolidatedLexicon50-8");
+	FILE* text = fopen("../books/pg56902.txt", "r");
+	if(!text){
+		puts("no file");
+		return 1;
+	}
+	denseRIV accumulate = {0};
+	sparseRIV temp;
+	char word[100];
+	while(fscanf(text, "%99s", word)){
+		if(feof(text)) break;
+		if(!*word) break;
+		
+		
+		if(stem(word)){
+			denseRIV* wordRIV = lexPull(word);
+			if(!wordRIV){
+				printf("%s, not in lexicon\n", word);
+				continue;
+			}else{
+				temp = consolidateD2S(wordRIV->values);
+				addS2D(accumulate.values, temp);
+				
+				
+				free(temp.locations);
+				free(wordRIV);
+				
+				
+				
+				
+			}
+		}else{
+			printf("%s, not in wordNet\n", word);
+		
+		}
+		
+	}
+	
+	
+	
+	return 0;
+	
+}
+
+
+char* stem(char* word){
+	
+	char pathString[200];
+	int WNdata;
+	sprintf(pathString, "WN/%s", word);
+	FILE* WNfile = fopen(pathString, "r");
+	
+	if(!WNfile) return NULL;
+	
+	fscanf(WNfile, "%d", &WNdata);
+	
+	if(!WNdata) return NULL;
+	
+	if(WNdata == 1) return word;
+	
+	if(WNdata == 2){
+		fscanf(WNfile, "%s", word);
+		fclose(WNfile);
+		sprintf(pathString, "WN/%s", word);
+		WNfile = fopen(pathString, "r");
+		if(!WNfile) return NULL;
+		
+		fscanf(WNfile, "%*d%s", word);
+		return word;
+	}
+	return NULL;
+}
+		
+		
+		
+		
+		
+		 
+	
+	
+	
+	
+

RIVconsolidate.c

+#include <stdio.h>
+#define RIVSIZE 50000
+#define CACHESIZE 0
+#include "RIVtools.h"
+#include <dirent.h>
+
+int main(int argc, char* argv[]){
+	lexOpen(argv[1]);
+	denseRIV* intake;
+	sparseRIV examine;
+	static denseRIV *output[60000] = {0};
+	DIR *directory;
+    struct dirent *files = 0;
+
+	if(!(directory = opendir(argv[1]))){
+		printf("location not found, %s\n", argv[1]);
+		return 1;
+	}
+	int i=0;
+	int j=0;
+	while((files=readdir(directory))){
+		if(*(files->d_name) == '.') continue;
+
+		if(files->d_type == DT_DIR){
+			/* the lexicon should not have valid sub-directories */
+			continue;
+		}
+		j++;
+		intake = lexPull(files->d_name);
+		/* if the vector has been encountered more than MINSIZE times
+		 * then it should be statistically significant, and useful */
+		if(intake->contextSize<7000){
+			free(intake);
+			continue;
+		}
+		examine = normalize(*intake, 10000);
+		strcpy(examine.name, files->d_name);
+		printf("%d,%d,%lf,%d,%d\n", examine.frequency, examine.contextSize, examine.magnitude, i, j);
+		output[i] = calloc(1, sizeof(denseRIV));
+		addS2D(output[i]->values, examine);
+		output[i]->magnitude = examine.magnitude;
+		strcpy(output[i]->name, files->d_name);
+		output[i]->frequency = intake->frequency;
+		output[i]->contextSize = intake->contextSize;
+		free(intake);
+		free(examine.locations);
+		i++;
+	}
+	lexClose();
+	lexOpen("consolidatedLexicon50-8");
+	for(int j=0; j<i; j++){
+		
+		lexPush(output[j]);
+		
+		
+	}
+	lexClose();
+	return 0;
+}

RIVcull.c

+#include <stdio.h>
+#include <stdlib.h>
+#include <dirent.h>
+#include <time.h>
+
+#include "RIVtools.h"
+#define THRESHOLD 0.70
+/* this program identifies all near-duplicates among the documents in the 
+ * chosen root directory, using RIV comparison */
+
+// fills the fileRIVs array with a vector for each file in the root directory
+void directoryToL2s(char *rootString, sparseRIV** fileRIVs, int *fileCount);
+
+int main(int argc, char *argv[]){
+	
+	int fileCount = 0;
+	
+	//initializes the fileRIVs array to be reallocced by later function
+	sparseRIV *fileRIVs = (sparseRIV*) malloc(1*sizeof(sparseRIV));
+	char rootString[2000];
+	if(argc <2){ 
+		printf("give me a directory");
+		return 1;
+	}
+	strcpy(rootString, argv[1]);
+	strcat(rootString, "/");
+
+	//gather all vectors ino the fileRIVs array and count them in fileCount
+	directoryToL2s(rootString, &fileRIVs, &fileCount);
+	printf("fileCount: %d\n", fileCount);
+	
+	//first calculate all magnitudes for later use
+	for(int i = 0; i < fileCount; i++){
+		fileRIVs[i].magnitude = getMagnitudeSparse(fileRIVs[i]);
+		
+	}
+	clock_t begintotal = clock();
+	double cosine;
+	double minmag;
+	double maxmag;
+	
+	//all cosines need a sparse-dense comparison.  so we will create a 
+	denseRIV baseDense;
+		
+	for(int i = 0; i < fileCount; i++){
+		
+		//0 out the denseVector, and map the next sparseVector to it
+		memset(&baseDense, 0, sizeof(denseRIV));
+		addS2D(baseDense.values, fileRIVs[i]);
+		
+		//pass magnitude to the to the dense vector
+		baseDense.magnitude = fileRIVs[i].magnitude;
+		
+		//if these two vectors are too different in size, we can know that they are not duplicates
+		minmag = baseDense.magnitude*.85;
+		maxmag  = baseDense.magnitude*1.15;
+		for(int j = 0; j < i; j++){
+			//if this vector is within magnitude threshold
+			if(fileRIVs[j].magnitude < maxmag 
+			&& fileRIVs[j].magnitude > minmag){
+				
+				//identify the similarity of these two vectors
+				cosine = cosCompare(baseDense, fileRIVs[j]);
+								
+		
+				//if the two are similar enough to be flagged
+				if(cosine>THRESHOLD){
+					printf("%s\t%s\n%f\n", fileRIVs[i].name , fileRIVs[j].name, cosine);
+				}	
+			}
+		}
+	}
+	printf("fileCount: %d", fileCount);
+	free(fileRIVs);
+	clock_t endtotal = clock();
+	double time_spent = (double)(endtotal - begintotal) / CLOCKS_PER_SEC;
+	printf("total time:%lf\n\n", time_spent);
+return 0;
+}
+
+//mostly a standard recursive Dirent-walk
+void directoryToL2s(char *rootString, sparseRIV** fileRIVs, int *fileCount){
+/* *** begin Dirent walk *** */
+	char pathString[2000];
+	DIR *directory;
+	struct dirent *files = 0;
+
+	if(!(directory = opendir(rootString))){
+		printf("location not found, %s\n", rootString);
+		return;
+	}
+
+	while((files=readdir(directory))){
+		
+		if(!files->d_name[0]) break;
+		while(*(files->d_name)=='.'){
+			files = readdir(directory);
+		}
+		
+		
+		
+		if(files->d_type == DT_DIR){
+			strcpy(pathString, rootString);
+
+			strcat(pathString, files->d_name);
+			strcat(pathString, "/");
+			directoryToL2s(pathString, fileRIVs, fileCount);
+			continue;
+		}
+		strcpy(pathString, rootString);
+		strcat(pathString, files->d_name);
+
+/* *** end dirent walk, begin meat of function  *** */
+
+		FILE *input = fopen(pathString, "r");
+		if(input){
+			
+			*fileRIVs = (sparseRIV*)realloc((*fileRIVs), ((*fileCount)+1)*sizeof(sparseRIV));
+			
+			(*fileRIVs)[*fileCount] = fileToL2(input);
+			strcpy((*fileRIVs)[*fileCount].name, pathString);
+			
+			fclose(input);
+			 *fileCount += 1;
+		}
+	}
+}

RIVgraphout.c

 #include <stdio.h>
-#define RIVSIZE 25000
+#define RIVSIZE 50000
 #define CACHESIZE 0
 #include "RIVtools.h"
 #include <dirent.h>
@@ -7,8 +7,6 @@
 int main(int argc, char* argv[]){
 	lexOpen(argv[1]);
 	denseRIV* intake;
-	sparseRIV examine;
-	static denseRIV *output[60000] = {0};
 	DIR *directory;
     struct dirent *files = 0;
 
@@ -28,27 +26,15 @@ int main(int argc, char* argv[]){
 		intake = lexPull(files->d_name);
 		/* if the vector has been encountered more than MINSIZE times
 		 * then it should be statistically significant, and useful */
-		if(intake->contextSize<10000)continue;
-		examine = normalize(*intake, 500);
-		strcpy(examine.name, files->d_name);
-		printf("%d,%d,%lf,%s\n", examine.frequency, examine.contextSize, examine.magnitude, examine.name);
-		output[i] = calloc(1, sizeof(denseRIV));
-		addS2D(output[i]->values, examine);
-		output[i]->magnitude = examine.magnitude;
-		strcpy(output[i]->name, files->d_name);
-		output[i]->frequency = intake->frequency;
+		
+		
+		printf("%d,%d,%lf,%d,%s\n", intake->frequency, intake->contextSize, intake->magnitude, i, files->d_name);
+		
 		free(intake);
-		free(examine.locations);
+		
 		i++;
 	}
 	lexClose();
-	/*lexOpen("consolidatedLexiconAggressive");
-	for(int j=0; j<i; j++){
 
-		lexPush(output[j]);
-		
-		
-	}
-	lexClose();*/
 	return 0;
 }

RIVread.c

@@ -6,6 +6,7 @@
 #include <dirent.h>
 #include <error.h>
 #include <string.h>
+#define CACHESIZE 100000
 #include "RIVtools.h"
 
 //this program reads a directory full of files, and adds all context vectors (considering file as context)
@@ -17,6 +18,7 @@ void directoryGrind(char *rootString);
 void lineGrind(char* textLine);
 
 int main(int argc, char *argv[]){
+
 	char pathString[1000];
 
 	//we open the lexicon, if it does not yet exist, it will be created
@@ -69,7 +71,7 @@ void directoryGrind(char *rootString){
 			printf("skipped: %s\n", files->d_name); 
 			continue;
 		}
-		
+		puts(files->d_name);
 		//open a file within root directory
 		FILE *input = fopen(pathString, "r");
 		if(input){
@@ -83,11 +85,11 @@ void directoryGrind(char *rootString){
 
 
 void fileGrind(FILE* textFile){
-	char textLine[5000];
+	char textLine[10000];
 	// included python script separates paragraphs into lines
-	
-	while(fgets(textLine, 4999, textFile)){
-	
+	int i=0;
+	while(fgets(textLine, 9999, textFile)){
+		printf("line: %d\n", i++);
 		if(!strlen(textLine)) continue;
 		if(feof(textFile)) break;
 	
@@ -100,6 +102,10 @@ void fileGrind(FILE* textFile){
 void lineGrind(char* textLine){
 	//extract a context vector from this text set
 	sparseRIV contextVector = textToL2(textLine);
+	if(contextVector.contextSize <= 1){
+		free(contextVector.locations);
+		return;
+	}
 		
 	denseRIV* lexiconRIV;
 	//identify stopping point in line read
@@ -110,6 +116,7 @@ void lineGrind(char* textLine){
 		sscanf(textLine, "%99s%n", word, &displacement);
 		//we ensure that each word exists, and is free of unwanted characters
 		
+		textLine += displacement+1;
 		if(!(*word))continue;
 
 		if(!isWordClean((char*)word)){
@@ -132,7 +139,7 @@ void lineGrind(char* textLine){
 		
 		//and finally we push it back to the lexicon for permanent storage
 		lexPush(lexiconRIV);
-		textLine += displacement+1;
+		
 		
 	}
 	//free the heap allocated context vector data

test.py

 import numpy as np
 import matplotlib.pyplot as plt
+import math
+def fit(x):
+    return 1*(1067+94500000/x)
 
 
-
-data = open("../code/RIVet/graphdata.txt", "r");
-frequencies = [];
-mags = [];
-i = 0;
-for line in data:
-    if(int(line.split(",")[1])>40000):
+x = 7
+range = 0.15
+while(1):
+    range = input("gimmerange");
+    data = open("graphdata.txt", "r");
+    frequencies = [];
+    mags = [];
+    fitline = [];
+    i = 0;
+    for line in data:
+        segments = line.split(",")
+        freq = int(segments[1])
+        mag = float(segments[2])
+        name = segments[4];
+        if(freq>40000):
              continue;
-    frequencies.append(int(line.split(",")[1]))
-    mags.append(float(line.split(",")[2]))
-    if(mags[i]>80 and frequencies[i]>7000 and frequencies[i]<15000):
-        print(line)
+        core = fit(freq)
+        fitmax = core*(1+range);
+        fitmin = core*(1-range);
+        if(mag >fitmax or mag < fitmin):
+            continue
+        frequencies.append(freq)
+        mags.append(mag)
+	fitline.append(fit(freq));
+	print("{} {} {}".format(name, freq, mag))
+    
+        
         i+=1
 
     
-plt.scatter(frequencies, mags)
-plt.show()
+    #plt.scatter(frequencies, mags)
+    plt.plot(frequencies, fitline, 'r^', frequencies, mags, 'bs')
+    plt.show()
+    x+=1
+