def draw_single_pages() :
def make_lines(ndata,fullpage_metric) :
# make horizontal data sets for metric and mean
fullpage = np.ones_like(ndata) * fullpage_metric
m = np.ones_like(ndata) * np.mean(ndata)
print "mean=",np.mean(ndata)
return np.column_stack((ndata,fullpage,m))
base = "300_winder_rast/imagesAndgTruth/"
# draw a few results from single pages
outfilename = "winder_full_rast_double_2col300_1.png"
if not os.path.exists(outfilename):
ndata = datfile.load(base+"Double_Column/300dpi/2col300_1/2col300_1.dat")
plotit( make_lines(ndata,1.0),
outfilename, title="Winder RAST DoubleColumn 2col300_1", fmt="-" )
outfilename = "winder_full_rast_double_pic_2col300_2.png"
if not os.path.exists(outfilename):
ndata = datfile.load(base+"Double_Column_Pictures/300dpi/2colpic300_2/2colpic300_2.dat")
plotit( make_lines(ndata,.78), outfilename,
title="Winder RAST Double Column Picture 2col300_2",
fmt="-" )
outfilename = "winder_full_rast_double_sci_2col300_3.png"
if not os.path.exists(outfilename):
ndata = datfile.load(base+"Double_Column_Pictures_Scientific/300dpi/2colpic300_3/2colpic300_3.dat")
plotit( make_lines(ndata,.56), outfilename,
title="Winder RAST Double Column Scientific Picture 2col300_3",
fmt="-" )
def get_winder_class_results(class_dir) :
# load all .dat files corresponding to each class of image in the Winder
# data set
# gather all the datafiles from the fullpage winder
fullpage_winder = datfile.find_all(class_dir)
class_data = []
class_names = []
for datfilename in fullpage_winder :
ndata = datfile.load(datfilename)
basename = get_basename(datfilename)
class_data.append( np.mean(ndata) )
class_names.append( basename.replace( "_"," ") )
return (class_data,class_names)
def load_all_datfiles( dirname ) :
metrics = None
for root,dirs,files in os.walk(dirname) :
# print "root=",root
# print "dirs=",dirs
# print "files=",files
for f in files :
path=os.path.join(root,f)
if path.endswith(".dat") :
# print "path=",os.path.join(root,f)
ndata = datfile.load( path )
# print ndata
if metrics is None :
metrics = ndata
ndata = None
else :
metrics = np.append( metrics, ndata )
return metrics
def main() :
if len(sys.argv) < 2 :
usage()
return
metrics = None
for datfile_name in sys.argv[1:] :
print datfile_name
ndata = datfile.load( datfile_name )
# print ndata
if metrics is None :
metrics = ndata
ndata = None
else :
metrics = np.append( metrics, ndata )
print metrics
print metrics.shape
np.save('metrics.npy',metrics)
make_histogram( metrics, "out.png" )