def GeneratePlot(outfile, Filename, xpixel, ypixel, nyanFlag=0, nyanAudio=0):
video = imageio.get_reader(Filename, 'ffmpeg')
colorArr = []
maxLen = int(len(video))
gradient = np.linspace(0,1,256)
gradient = np.vstack((gradient, gradient))
index = range(maxLen)
RGB = [[],[],[]] #0 - Red, 1 - Green, 2 - Blue
progress = ""
if(nyanAudio):
progress = NyanBar(audiofile="./NyanCat.mp3")
elif(nyanFlag):
progress = NyanBar()
try:
print "Starting Collection"
for i in index:
try:
frame = video.get_data(i)
pass
except KeyboardInterrupt:
print "\nEnding Collection"
break
tempArr = frame[ypixel,xpixel] #Get the Frame at X=xpixel and Y=ypixel
for j in range(3):
RGB[j].append(float(tempArr[j])/256.0) #Normalizing the RGB values to 256 to get RGB value less than 1 for Matplotlib cmap
colorArr.append([x[i] for x in RGB]) #Get the RGB values of the most recent entry and appent to colorArr
if(nyanFlag):
progress.update(int(float(i)/float(maxLen) * 100))
#sys.stdout.write("\rFrame %i of %i" % (i, maxLen))
#sys.stdout.flush()
if(nyanFlag):
progress.finish()
#RGB Plots for Rates
plt.plot(RGB[0], 'r')
plt.plot(RGB[1], 'g')
plt.plot(RGB[2], 'b')
plt.savefig(AppendTitleToFilename(outfile, "RGB"))
plt.clf()
#Making Colorbar
cmap1 = LinearSegmentedColormap.from_list("cmap", colorArr, N=256, gamma=1.0) #Need normalized RGB to 256 therefore from 0 to 1
gradient = np.linspace(0,1,256)
gradient = np.vstack((gradient, gradient))
plt.imshow(gradient, aspect='auto', cmap=cmap1)
plt.savefig(outfile)
plt.clf()
return
except KeyboardInterrupt:
print "\nEnding Plot"
else:
print "The test filename must either contain word *spam* or *ham* indicating its class!"
print "The filter won't be tested on `%s` file." % os.path.join(
e, d)
if show_progress and progress_bar == "nyan":
print "Test [%d/%d]" % (ei + 1, len(emails_dir))
progress = NyanBar(tasks=100)
tp, tn, fp, fn = 0, 0, 0, 0
evaluation_start_time = time.time()
for ii, i in enumerate(emails):
if show_progress and progress_bar == "classic":
print "[%d/%d] %.2d%% (%s)" % (ei + 1, len(emails_dir),
100. * ii / len(emails), i)
elif show_progress and progress_bar == "nyan":
progress.update(100. * ii / len(emails))
current_email = execute % os.path.abspath(i)
if "spam" in os.path.split(i)[1]:
ground_truth = "spam"
elif "ham" in os.path.split(i)[1]:
ground_truth = "ham"
else:
sys.exit(
"File %s has neither *ham* nor *spam* keyword in its name!" %
i)
exe = subprocess.Popen(current_email.split(),
cwd=path_prefix,
stdout=subprocess.PIPE)
output, error = exe.communicate()
from nyanbar import NyanBar
import time
progress = NyanBar(audiofile="NyanCat-original.mp3")
for n in range(100):
time.sleep(.3)
progress.update(n)
progress.finish()
# Sampling every x minutes
intervals = 5
nMins = nHours * 60
timer = 0
leds = 1
# Initialize the leds with the first one only
pfd.leds[0].turn_on()
pfd.leds[0].set_high()
progress = NyanBar()
while timer <= nMins:
# Update progress bar
progress.update((timer / nMins) * 100)
# Light up the transilluminator
pfd.relays[0].value = 1
# Set camera values
camera.awb_gains = 1, 0.5
camera.brightness = 55
camera.saturation = 30
camera.exposure_compensation = 25
camera.contrast = 50
camera.shutter_speed = 220000
# Let camera stabilize
time.sleep(10)
# Take the gfp image
