Started working on pointprocesses

statistics/lecture/Makefile

@@ -1,22 +1,29 @@
 BASENAME=statistics
+
 PYFILES=$(wildcard *.py)
 PYPDFFILES=$(PYFILES:.py=.pdf)
 
-pdf : $(BASENAME)-chapter.pdf $(PYPDFFILES)
+all : pdf 
 
-$(BASENAME)-chapter.pdf : $(BASENAME)-chapter.tex $(BASENAME).tex
+# script:
+pdf : $(BASENAME)-chapter.pdf
+
+$(BASENAME)-chapter.pdf : $(BASENAME)-chapter.tex $(BASENAME).tex $(PYPDFFILES)
 	pdflatex -interaction=scrollmode $< | tee /dev/stderr | fgrep -q "Rerun to get cross-references right" && pdflatex -interaction=scrollmode $< || true
 
 $(PYPDFFILES) : %.pdf : %.py
 	python $<
 
 clean :
-	rm -f *~ $(BASENAME)-chapter.aux $(BASENAME)-chapter.log $(BASENAME)-chapter.out $(BASENAME).aux $(BASENAME).log
+	rm -f *~ 
+	rm -f $(BASENAME).aux $(BASENAME).log
+	rm -f $(BASENAME)-chapter.aux $(BASENAME)-chapter.log $(BASENAME)-chapter.out
+	rm -f $(PYPDFFILES) $(GPTTEXFILES)
 
 cleanall : clean
 	rm -f $(BASENAME)-chapter.pdf
 
-watch :
+watchpdf :
 	while true; do ! make -q pdf && make pdf; sleep 0.5; done
 
 

statistics/lecture/boxwhisker.py

@@ -43,5 +43,5 @@ ax.annotate('maximum',
 ax.boxplot( x, whis=100.0 )
 plt.tight_layout()
 plt.savefig('boxwhisker.pdf')
-plt.show()
+#plt.show()
 

statistics/lecture/correlation.py

@@ -5,7 +5,6 @@ plt.xkcd()
 fig = plt.figure( figsize=(6,5) )
 n = 200
 for k, r  in enumerate( [ 1.0, 0.6, 0.0, -0.9 ] ) :
-    print r
     x = np.random.randn( n )
     y = r*x + np.sqrt(1.0-r*r)*np.random.randn( n )
     ax = fig.add_subplot( 2, 2, k+1 )
@@ -30,5 +29,4 @@ for k, r  in enumerate( [ 1.0, 0.6, 0.0, -0.9 ] ) :
 
 plt.tight_layout()
 plt.savefig('correlation.pdf')
-plt.show()
-
+#plt.show()

statistics/lecture/diehistograms.py

@@ -28,5 +28,4 @@ ax.set_ylabel( 'Probability' )
 ax.hist([x2, x1], bins, normed=True, color=['#FFCC00', '#FFFF66' ])
 plt.tight_layout()
 fig.savefig( 'diehistograms.pdf' )
-plt.show()
-
+#plt.show()

statistics/lecture/median.py

@@ -29,5 +29,4 @@ ax.plot(x,g, 'b', lw=4)
 ax.plot([0.0, 0.0], [0.0, 0.45], 'k', lw=2 )
 plt.tight_layout()
 fig.savefig( 'median.pdf' )
-plt.show()
-
+#plt.show()

statistics/lecture/nonlincorrelation.py

@@ -39,4 +39,4 @@ ax.scatter( x, z )
 
 plt.tight_layout()
 plt.savefig('nonlincorrelation.pdf')
-plt.show()
+#plt.show()

statistics/lecture/pdfhistogram.py

@@ -35,5 +35,5 @@ ax.hist(r, 20, normed=True, color='#FFCC00')
 
 plt.tight_layout()
 fig.savefig( 'pdfhistogram.pdf' )
-plt.show()
+#plt.show()
 

statistics/lecture/pdfprobabilities.py

@@ -32,5 +32,4 @@ ax.fill_between( x[(x>x1)&(x<x2)], 0.0, g[(x>x1)&(x<x2)], color='#cc0000' )
 ax.plot(x,g, 'b', lw=4)
 plt.tight_layout()
 fig.savefig( 'pdfprobabilities.pdf' )
-plt.show()
-
+#plt.show()

statistics/lecture/quartile.py

@@ -46,5 +46,4 @@ ax.plot([q[0], q[0]], [0.0, 0.4], 'k', lw=2 )
 ax.plot([q[2], q[2]], [0.0, 0.4], 'k', lw=2 )
 plt.tight_layout()
 fig.savefig( 'quartile.pdf' )
-plt.show()
-
+#plt.show()