def visualizeGFSName(gfsFileName,
outFileBase,
imgFormat='png',
cMap=ColorMap.BlackBodyMap(),
mapRange=1.0,
mapLimits=None,
sitesName=None,
obstacles=None):
'''Visualizes a grid file sequence with the given color map.
@param gfsFileName A string. The name of the GridFileSequence to visualize.
@param outFileBase A string. The basic name of the images to be output.
For each grid in the sequence, it outputs outFileBase_###.imgFormat.
The path must already exist.
@param imgFormat A string. The output image format (png, jpg, or bmp )
@param cMap An instance of ColorMap. Indicates how the visualization works.
@param mapRange A float. Determines what fraction of the data range maps to the color
range. For example, if mapRange is 0.75, then the value that is
75% of the way between the min and max value achieves the maximum
color value. Ignored if mapLimits is not None.
@param mapLimits A tuple which defines the map range independent of the real values in
the data (minVal, maxVal). If the tuple has two values, that defines the range.
If either is None, then the corresponding value from the data is used.
@param sitesName A string. The path to a set of trajectory sites
@param obstacles An instance of ObstacleSet (optional). If obstacle are provided,
Then they will be drawn over the top of the data.
'''
reader = GFS.GridFileSequenceReader(gfsFileName)
reader.setNext(0)
try:
sites = loadTrajectory(sitesName)
except:
sites = None
visualizeGFS(reader, cMap, outFileBase, imgFormat, mapRange, mapLimits,
sites, obstacles)
def main():
import optparse
import ColorMap
import sys, os
import obstacles
from trajectory import loadTrajectory
parser = optparse.OptionParser()
parser.add_option( '-i', '--input', help='A path to a grid file sequence - the data to visualize',
action='store', dest='input', default='' )
parser.add_option( '-t', '--trajectory', help='(Optional) The path to the pedestrian data which produced the voronoi diagrams.',
action='store', dest='trajName', default=None )
parser.add_option( '-o', '--output', help='The path and base filename for the output images (Default is "vis").',
action='store', dest='output', default='./vis' )
parser.add_option( '-c', '--colorMap', help='Specify the color map to use. Valid values are: %s. Defaults to "black_body".' % ColorMap.getValidColorMaps(),
action='store', dest='cmapName', default='black_body' )
parser.add_option( '-e', '--extension', help='Image format: [png, jpg, bmp] (default is png)',
action='store', dest='ext', default='png' )
parser.add_option( '-b', '--obstacles', help='Path to an obstacle xml file',
action='store', dest='obstXML', default=None )
options, args = parser.parse_args()
if ( options.input == '' ):
print '\n *** You must specify an input file'
parser.print_help()
sys.exit(1)
try:
colorMap = ColorMap.getColorMapByName( options.cmapName )
except KeyError:
print '\n *** You have selected an invalid color map: %s' % ( options.cmapName )
parser.print_help()
sys.exit(1)
if ( not options.ext.lower() in ( 'png', 'jpg', 'bmp' ) ):
print '\n *** You have selected an invalid file format: %s' % ( options.ext )
parser.print_help()
sys.exit(1)
trajData = None
if ( not options.trajName is None ):
try:
trajData = loadTrajectory( options.trajName )
except ValueError:
print "Unable to recognize the data in the file: %s" % ( options.trajName )
folder, baseName = os.path.split( options.output )
if ( folder ):
if ( not os.path.exists( folder ) ):
os.makedirs( folder )
reader = GFS.GridFileSequenceReader( options.input )
reader.setNext( 0 )
obstacles = None
if ( options.obstXML ):
obstacles, bb = obstacles.readObstacles( options.obstXML )
visualizeGFS( reader, colorMap, options.output, options.ext, 1.0, trajData, obstacles )
def getcolormap(**kwargs):
colors = kwargs.pop('colors', None)
issingle = False
if colors is None:
colors = kwargs.pop('color', None)
issingle = True
if not colors is None:
if issingle or isinstance(colors, str):
c = getcolor(colors)
cmap = ColorMap(c)
else:
cs = []
for cc in colors:
c = getcolor(cc)
cs.append(c)
cmap = ColorMap(cs)
else:
cmapstr = kwargs.pop('cmap', 'matlab_jet')
if cmapstr is None:
cmapstr = 'matlab_jet'
fn = cmapstr + '.rgb'
fn = os.path.join(migl.get_cmap_folder(), fn)
if not os.path.exists(fn):
raise IOError('cmap file not exists: %s' % fn)
alpha = kwargs.pop('alpha', None)
if alpha is None:
cmap = ColorUtil.loadColorMap(fn)
else:
alpha = (int)(alpha * 255)
cmap = ColorUtil.loadColorMap(fn, alpha)
reverse = kwargs.pop('cmapreverse', False)
if reverse:
cmap.reverse()
return cmap
def getcolormap(**kwargs):
colors = kwargs.pop('colors', None)
issingle = False
if colors is None:
colors = kwargs.pop('color', None)
issingle = True
if not colors is None:
if issingle or isinstance(colors, str):
c = getcolor(colors)
cmap = ColorMap(c)
else:
cs = []
for cc in colors:
c = getcolor(cc)
cs.append(c)
cmap = ColorMap(cs)
else:
cmapstr = kwargs.pop('cmap', 'matlab_jet')
if cmapstr is None:
cmapstr = 'matlab_jet'
alpha = kwargs.pop('alpha', None)
if alpha is None:
cmap = ColorUtil.getColorMap(cmapstr)
else:
alpha = (int)(alpha * 255)
cmap = ColorUtil.getColorMap(cmapstr, alpha)
reverse = kwargs.pop('cmapreverse', False)
if reverse:
cmap.reverse()
return cmap
def plot(self, width_in=400, height_in=400):
import ColorMap
import Tkinter
cmax = max(self.values())
cmin = min(self.values())
offset = 0.05 * min(width_in, height_in)
xmin, ymin, xmax, ymax = 0, 0, self.size()[0], self.size()[1]
scale = min(0.9 * width_in, 0.9 * height_in) / max(
xmax - xmin, ymax - ymin)
root = Tkinter.Tk()
frame = Tkinter.Frame(root)
frame.pack()
text = Tkinter.Label(width=20, height=10, text='matrix sparsity')
text.pack()
canvas = Tkinter.Canvas(bg="black", width=width_in, height=height_in)
canvas.pack()
button = Tkinter.Button(frame,
text="OK?",
fg="red",
command=frame.quit)
button.pack()
for index in self.keys():
ix, iy = index[0], ymax - index[1] - 1
ya, xa = offset + scale * (ix), height_in - offset - scale * (iy)
yb, xb = offset + scale * (ix +
1), height_in - offset - scale * (iy)
yc, xc = offset + scale * (ix + 1), height_in - offset - scale * (
iy + 1)
yd, xd = offset + scale * (ix), height_in - offset - scale * (iy +
1)
color = ColorMap.strRgb(self[index], cmin, cmax)
canvas.create_polygon(xa, ya, xb, yb, xc, yc, xd, yd, fill=color)
root.mainloop()
def plot(self, width_in=400, height_in=400):
import ColorMap
import Tkinter
cmax = max(self.values())
cmin = min(self.values())
offset = 0.05*min(width_in, height_in)
xmin, ymin, xmax, ymax = 0, 0, self.size()[0], self.size()[1]
scale = min(0.9*width_in, 0.9*height_in)/max(xmax-xmin, ymax-ymin)
root = Tkinter.Tk()
frame = Tkinter.Frame(root)
frame.pack()
text = Tkinter.Label(width=20, height=10, text='matrix sparsity')
text.pack()
canvas = Tkinter.Canvas(bg="black", width=width_in, height=height_in)
canvas.pack()
button = Tkinter.Button(frame, text="OK?", fg="red",
command=frame.quit)
button.pack()
for index in self.keys():
ix, iy = index[0], ymax-index[1]-1
ya, xa = offset+scale*(ix), height_in -offset-scale*(iy)
yb, xb = offset+scale*(ix+1), height_in -offset-scale*(iy)
yc, xc = offset+scale*(ix+1), height_in -offset-scale*(iy+1)
yd, xd = offset+scale*(ix), height_in -offset-scale*(iy+1)
color = ColorMap.strRgb(self[index], cmin, cmax)
canvas.create_polygon(xa, ya, xb, yb, xc, yc, xd, yd, fill=color)
root.mainloop()
else:
# middle, connect with -256, +256, -1, +1
g.add_edge(i, i - 256)
g.add_edge(i, i + 256)
g.add_edge(i, i - 1)
g.add_edge(i, i + 1)
printStats(g)
s = (256, 256)
p1 = np.zeros(s, dtype=np.float64)
p2 = np.zeros(s, dtype=np.float64)
p3 = np.zeros(s, dtype=np.float64)
for i in range(0, GRAPH_SIZE / 256):
for j in range(0, GRAPH_SIZE / 256):
payload = g_payload[g.vertex(i + j)]
p1[i,j] = payload.susceptible + payload.immune
p2[i,j] = payload.incubation1 + payload.incubation2 + payload.incubation3 + payload.incubation4
p3[i,j] = payload.contagious1a + payload.contagious2a
import ColorMap
img1 = Image.fromarray(ColorMap.colorMap(p1))
# img1.save("/Users/paul.warren/Documents/ebola/images/mapped.png")
img1.show()
