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 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"))