def gabor(im, W, angles):
(x, y) = im.size
im_load = im.load()
ymage = np.asarray(im.getdata(), dtype=np.float64).reshape(im.size[0],(im.size[1]))
freqs = frequency.freq(im, W, angles)
print "computing local ridge frequency done"
gauss = utils.gauss_kernel(3)
# utils.apply_kernel(freqs, gauss)
for i in range(1, x / W - 1):
for j in range(1, y / W - 1):
kernel = gabor_kernel(W, angles[i][j], freqs[i][j])
for k in range(0, W):
for l in range(0, W):
val = utils.apply_kernel_at(
lambda x, y: im_load[x, y],
kernel,
i * W + k,
j * W + l)
ymage[i * W + k][j * W + l] = val
# im.putpixel((i * W + k, j * W + l),val )
return Image.fromarray(ymage,mode='L')
def load(self, file):
f = open(data_path + file, 'rb')
arr = marshal.load(f)
for i in arr:
self.ask[i] = freq()
self.ask[i].__dict__ = arr[i]
self.total += arr[i]['total']
f.close()
def today():
text = ''
home_url = 'https://panorama.pub'
page = requests.get(home_url)
unpretty_text = page.text
soup = BeautifulSoup(unpretty_text, 'html.parser')
for link in soup.find_all('a', rel='bookmark'):
new_page_text = requests.get(link['href']).text
new_soup = BeautifulSoup(new_page_text, 'html.parser')
article = list(map(str, new_soup.findAll('p')))[2:-1]
article = '\n'.join([i[3:-4] for i in article])
text += ' ' + article
return frequency.freq(text.split())
def simulate_drift(N,p):
population = init_pop.with_a_bang(N, p)
fixation = False
num_generations = 0
while fixation == False:
distribution = frequency.freq(population)
if distribution['AA'] == N or distribution['aa'] == N:
print "An allele has gone to fixation in ", num_generations
print "The genotype counts are: ", distribution
fixation = True
num_generations += 1
population = new_pop.generation(population)
#simulate_drift(1000, 0.60)
def rosalin(k, m, n):
population = []
total = 0
for i in range(k):
population.append( "AA" )
i += 1
for j in range(m):
population.append( "Aa" )
j += 1
for Q in range(n):
population.append( "aa" )
Q += 1
for i in range(1000000):
newpop = new_pop.generation(population)
distribution = frequency.freq(newpop)
freqaa = distribution["aa"] / float(len(newpop))
total += freqaa
return total/1000000
def gabor(im, W, angles):
(x, y) = im.size
im_load = im.load()
freqs = frequency.freq(im, W, angles)
print "computing local ridge frequency done"
gauss = utils.gauss_kernel(3)
utils.apply_kernel(freqs, gauss)
for i in range(1, x / W - 1):
for j in range(1, y / W - 1):
kernel = gabor_kernel(W, angles[i][j], freqs[i][j])
for k in range(0, W):
for l in range(0, W):
im_load[i * W + k, j * W + l] = utils.apply_kernel_at(
lambda x, y: im_load[x, y], kernel, i * W + k,
j * W + l)
return im
def gabor(im, W, angles):
(x, y) = im.size
im_load = im.load()
freqs = frequency.freq(im, W, angles)
print "computing local ridge frequency done"
gauss = utils.gauss_kernel(3)
utils.apply_kernel(freqs, gauss)
for i in range(1, x / W - 1):
for j in range(1, y / W - 1):
kernel = gabor_kernel(W, angles[i][j], freqs[i][j])
for k in range(0, W):
for l in range(0, W):
im_load[i * W + k, j * W + l] = utils.apply_kernel_at(
lambda x, y: im_load[x, y],
kernel,
i * W + k,
j * W + l)
return im
def convert_freq(h, count):
freq = []
for t in h:
freq.append((t[0], frequency.freq(h, t[0], count)))
return freq
def freqamp2(self):
flag = 2
frequency.freq(self.filepath2, flag)
self.fnalabel2.setScaledContents(True)
self.fnalabel2.setPixmap(QPixmap("freq&2.png"))
def freqamp1(self):
flag = 1
frequency.freq(self.filepath1, flag)
self.fnalabel1.setScaledContents(True)
self.fnalabel1.setPixmap(QPixmap("freq&1.png"))
def freqamp2(self):
flag=2
frequency.freq(self.filepath2,flag)
self.fnalabel2.setScaledContents(True)
self.fnalabel2.setPixmap(QPixmap("freq&2.png"))
def freqamp1(self):
flag=1
frequency.freq(self.filepath1,flag)
self.fnalabel1.setScaledContents(True)
self.fnalabel1.setPixmap(QPixmap("freq&1.png"))
