ModSim: Added graph for fibonnaci assignment.

modsim/ass2/plot.py → modsim/ass2/bisec.py

@@ -15,4 +15,5 @@ plt.xscale('log')
 plt.xlabel('epsilon')
 plt.ylabel('steps')
 plt.grid(True)
-plt.savefig('plot.pdf')
+plt.savefig('bisec.pdf')
+

modsim/ass2/q7.c

@@ -2,22 +2,37 @@
 #include <stdio.h>
 
 void sequence(int n, int max_age) {
-    int i, mature = 0,
-        died = 0;
+    int i;
+
+    long long mature = 0,
+         died = 0;
+
+    long long *new = malloc((n+1) * sizeof(long long));
+
+    printf("popu:");
 
-    int *new = malloc(n * sizeof(int));
     new[0] = 1;
-    printf("1");
+    printf(" 1");
 
     for( i = 1; i < n; i++ ) {
         died = i < max_age ? 0 : new[i - max_age];
         new[i] = mature;
         mature = mature + new[i - 1] - died;
 
-        printf(" %d", mature + new[i]);
+        printf(" %lld", mature + new[i]);
     }
+    new[i] = mature;
 
     puts("");
+
+    //printf("diff:  ");
+
+    //for( i = 1; i < n; i++ )
+    //    printf(" %lld", new[i]);
+
+    //puts("");
+
+    free(new);
 }
 
 int main(int argc, char *argv[]) {

modsim/ass2/rabbit.log

+1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
+1 1 2 2 3 4 5 7 9 12 16 21 28 37 49 65 86 114 151 200 265 351 465 616 816
+1 1 2 3 4 6 9 13 19 28 41 60 88 129 189 277 406 595 872 1278 1873 2745 4023 5896 8641
+1 1 2 3 5 7 11 17 26 40 61 94 144 221 339 520 798 1224 1878 2881 4420 6781 10403 15960 24485
+1 1 2 3 5 8 12 19 30 47 74 116 182 286 449 705 1107 1738 2729 4285 6728 10564 16587 26044 40893
+1 1 2 3 5 8 13 20 32 51 81 129 205 326 518 824 1310 2083 3312 5266 8373 13313 21168 33657 53515
+1 1 2 3 5 8 13 21 33 53 85 136 218 349 559 895 1433 2295 3675 5885 9424 15091 24166 38698 61969
+1 1 2 3 5 8 13 21 34 54 87 140 225 362 582 936 1505 2420 3891 6257 10061 16178 26014 41830 67262
+1 1 2 3 5 8 13 21 34 55 88 142 229 369 595 959 1546 2492 4017 6475 10437 16824 27119 43714 70464

modsim/ass2/rabbit.py

+import matplotlib.pyplot as plt
+import re
+data = [re.split('\s+', line)[:-1] for line in file('rabbit.log')]
+
+for i in range(len(data)):
+    data.insert(i*2, range(len(data[0])))
+
+plt.plot(*data)
+plt.yscale('log')
+plt.xlabel('generatie')
+plt.ylabel('populatie')
+plt.grid(True)
+plt.savefig('rabbit.pdf')

modsim/ass2/report.tex

@@ -78,7 +78,7 @@ gelijk aan $1.114157142 \dots$, interessanter is echter de relatie tussen de
 nauwkeurigheid en het aantal stappen van de berekening:
 
 \begin{figure}[H]
-\includegraphics[scale=.5]{plot}
+\includegraphics[width=12cm]{bisec}
 \caption{Het verband tussen de nauwkeurigheid en het aantal stappen van de
 berekening is logaritmisch.}
 \end{figure}
@@ -185,4 +185,21 @@ sin & 0 & $8\pi$ & gauss       & $-1.797258919631 \cdot 10^{-14}$ & $1.797258919
 
 % }}}
 
+\section{Instelbare accuratie} % {{{
+\label{sec:Instelbare accuratie}
+
+% }}}
+
+\section{Fibonnaci} % {{{
+\label{sec:Fibonnaci}
+
+\begin{figure}[H]
+\centering
+\includegraphics[width=12cm]{rabbit}
+\caption{Groei van konijnenpopulatie voor verschillende maximum leeftijden (2
+t/m 10 jaar).}
+\end{figure}
+
+% }}}
+
 \end{document}