def func():
state = STATE_SPEC_NAME
for line in open(getfile.get_from_strawlab("week1/nanodrop-spectra.tsv")):
if state == STATE_SPEC_NAME:
spectrum_names.append(line.strip())
elif state == STATE_DATA:
wavelength, absorbance = line.strip().split()
yield absorbance
if int(wavelength) == (FREQ_TO - 1):
state = STATE_SKIP
continue
state += 1
#!/usr/bin/env python
import sys
import argparse
import Image
import getfile
parser = argparse.ArgumentParser()
parser.add_argument(
"images",
metavar="N",
type=str,
nargs="*",
help="images (default:lena)",
default=[getfile.get_from_strawlab("week1/lena-color.png")],
)
parser.add_argument("-t", "--threshold", type=int, default=80)
args = parser.parse_args()
for fn in args.images:
print "Thresholding %s at %d" % (fn, args.threshold)
im = Image.open(fn)
im = im.convert("L")
thr = im.point(lambda x: (x > args.threshold) * 255)
thr.save("binary_" + fn)
import cv
import time
import getfile
movie = cv.CaptureFromFile( getfile.get_from_strawlab("week1/flies.avi") )
nframes, rows, cols = map(lambda x: int(cv.GetCaptureProperty(movie, x)),
[cv.CV_CAP_PROP_FRAME_COUNT, cv.CV_CAP_PROP_FRAME_HEIGHT, cv.CV_CAP_PROP_FRAME_WIDTH])
background = cv.CreateMat(rows, cols, cv.CV_8UC3)
for i in range(nframes):
cv.Max(cv.QueryFrame(movie), background, background)
cv.ShowImage("background", background)
cv.SetCaptureProperty(movie, cv.CV_CAP_PROP_POS_FRAMES, 0)
for i in range(nframes):
frame = cv.QueryFrame(movie)
cv.ShowImage("before", frame)
cv.Sub(background, frame, frame)
cv.Smooth(frame, frame, param1=5)
cv.Threshold(frame, frame, 70, 255, cv.CV_THRESH_BINARY)
cv.ShowImage("after", frame)
if cv.WaitKey(20) % 256 == ord('q'):
break
import cv
import sys
import getfile
lena = "lena-gray.png"
img = cv.LoadImageM(getfile.get_from_strawlab("week1/"+lena))
cv.Smooth(img, img, smoothtype=cv.CV_GAUSSIAN, param1=11)
cv.SaveImage("smoothed-"+lena, img)
import scipy.misc
import matplotlib.pyplot as plt
import getfile
im = scipy.misc.imread(getfile.get_from_strawlab("week1/lena-gray.png"))
plt.imshow(im)
plt.colorbar()
plt.show()
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import pylsm.lsmreader as lsm
import getfile
lsmfile = lsm.Lsmimage(getfile.get_from_strawlab("week1/DB331-brain.bin"))
lsmfile.open()
Z = lsmfile.header['CZ LSM info']['Dimension Z']
fig = plt.figure()
layer = lsmfile.get_image(stack=0, channel=0)
im = plt.imshow(layer, cmap=plt.cm.hot)
def updatefig(frame, i, Z, lsmfile):
i[0] = i[0] + 1 if i[0] < Z - 1 else 0
im.set_array(lsmfile.get_image(stack=i[0], channel=0))
return im,
ani = anim.FuncAnimation(fig, updatefig,
fargs=([0], Z, lsmfile), interval=50, blit=True)
plt.show()
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import wavfile
from getfile import get_from_strawlab
rate,data = wavfile.read(get_from_strawlab("week1/sirentone.wav"))
left = data[:,1]
nsamps = len(left)
t = np.arange(nsamps, dtype=float) / rate
plt.plot(t, left) #plot in time domain
xfreq = np.fft.fft(left)
fft_freqs = np.fft.fftfreq(nsamps, d=1./rate)
plt.figure() #plot in freq domain
plt.loglog(fft_freqs[0:nsamps/2], np.abs(xfreq)[0:nsamps/2])
plt.figure()
plt.specgram(data[:,1])
plt.show()
import csv
import sqlite3 as sqlite
import numpy as np
import matplotlib.pyplot as plt
import getfile
csvfile = open(getfile.get_from_strawlab("week1/CTS.csv"),'rb')
con = sqlite.connect(':memory:')
with con and csvfile:
csv = csv.reader(csvfile)
cur = con.cursor()
cur.execute("CREATE TABLE CTS(date INTEGER PRIMARY KEY, co2 FLOAT, temp FLOAT);")
header = csv.next() #save the csv header row
idx_date = header.index("yr_mn")
idx_co2 = header.index("CO2")
idx_temp = header.index("GISS")
for row in csv:
cur.execute("INSERT INTO CTS VALUES (?,?,?)", (row[idx_date],row[idx_co2],row[idx_temp]) )
cur.execute("SELECT date, co2 FROM cts WHERE co2 != 'NA'")
data = np.array(cur.fetchall())
plt.plot(data[:,0],data[:,1])
plt.xlabel("date"); plt.ylabel("CO2 (ppm)")
plt.show()
#!/usr/bin/env python
from gi.repository import Gtk
import getfile
getfile.get_from_strawlab("week1/lena-color.png")
getfile.get_from_strawlab("week1/lena-gray.png")
class App(Gtk.Builder):
def __init__(self):
super(App, self).__init__()
self.add_from_file("gui.ui")
self.connect_signals(self)
self._label = self.get_object("label1")
self._image = self.get_object('image1')
self._on_button_clicked()
window = self.get_object('window1')
window.connect('destroy', lambda x: Gtk.main_quit())
window.show_all()
def _on_button_clicked(self, *args):
lena = "lena-color.png" if self._label.get_text() == "lena-gray.png" else "lena-gray.png"
self._image.set_from_file(lena)
self._label.set_text(lena)
app = App()
Gtk.main()
