def orders():
if request.method == 'GET':
return render_template('searchorders.html')
else:
# build the skiplist
orderskiplist = helpers.makePresidentialOrderlist()
if request.form['title_cont'] != '':
app.vars['title_cont'] = request.form['title_cont']
if request.form['category'] != '':
app.vars['category'] = request.form['category']
if len(app.vars) == 1:
searchtype = app.vars.keys()[0]
filters.filter(orderskiplist, app.vars, searchtype, 'title', 2)
# resets the request dictionary
app.vars = {}
return render_template('download.html')
else:
app.vars = {}
return render_template('error.html')
def grants():
if request.method == 'GET':
# build the skiplist and pass in as argument
grantskiplist = helpers.makeGrantlist()
return render_template('searchgrants.html')
else:
# for post request do the searching and redirect
# build the skiplist
grantskiplist = helpers.makeGrantlist()
if request.form['name_cont'] != '':
app.vars['name_cont'] = request.form['name_cont']
if request.form['category'] != '':
app.vars['category'] = request.form['category']
if len(app.vars) == 1:
searchtype = app.vars.keys()[0]
filters.filter(grantskiplist, app.vars, searchtype, 'Awardee', 3)
# resets the request dictionary
app.vars = {}
return render_template('download.html')
else:
app.vars = {}
return render_template('error.html')
def population():
if request.method == 'GET':
return render_template('searchpopulation.html')
else:
# build the skiplist and pass in as argument
populationskiplist = helpers.makePopulationlist()
# for post request do the searching and redirect
# to the download page and pass in file as arg
#request was a POST
if request.form['initial'] != '':
app.vars['initial'] = request.form['initial']
if request.form['popgreater'] != '':
app.vars['popgreater'] = request.form['popgreater']
if request.form['poplesser'] != '':
app.vars['poplesser'] = request.form['poplesser']
if len(app.vars) == 1:
# checks for errors in the post request
searchtype = app.vars.keys()[0]
filters.filter(populationskiplist, app.vars, searchtype, 'NAME', 1)
# resets the request dictionary
app.vars = {}
return render_template('download.html')
else:
app.vars = {}
return render_template('error.html')
def plot_tau(x_test, y_test, y_predict, plot_folder, filter_type, y_predict2=None):
"""Plot Reynolds stresses tau fields and pdf."""
dimension = len(y_test[0]['u'].shape)
k = filters.filter_size(filter_type, dimension)
if len(y_test[0]['u'].shape) == 3:
logging.info('Plot tau')
for test_example in range(3):
tau = dict()
tau2 = dict()
tau_true = dict()
for u_i in ['u', 'v', 'w']:
for u_j in ['u', 'v', 'w']:
tmp = y_predict[test_example][u_i]*y_predict[test_example][u_j]
tmp = filters.filter(tmp, filter_type, k=k[test_example])
tau[u_i+u_j] = x_test[test_example][u_i]*x_test[test_example][u_j] - tmp
tmp = y_test[test_example][u_i]*y_test[test_example][u_j]
tmp = filters.filter(tmp, filter_type, k=k[test_example])
tau_true[u_i + u_j] = x_test[test_example][u_i] * x_test[test_example][u_j] - tmp
if y_predict2:
tmp = y_predict2[test_example][u_i]*y_predict2[test_example][u_j]
tmp = filters.filter(tmp, filter_type, k=k[test_example])
tau2[u_i + u_j] = x_test[test_example][u_i] * x_test[test_example][u_j] - tmp
imagesc([tau_true['uu'][:, :, 32], tau_true['uv'][:, :, 32], tau_true['uw'][:, :, 32]],
titles=[r'$\tau^{true}_{11}$', r'$\tau^{true}_{12}$', r'$\tau^{true}_{13}$'],
name=os.path.join(plot_folder, 'tau_true{}'.format(test_example)), limits=[-0.07, 0.07])
imagesc([tau['uu'][:, :, 32], tau['uv'][:, :, 32], tau['uw'][:, :, 32]],
titles=[r'$\tau_{11}$', r'$\tau_{12}$', r'$\tau_{13}$'],
name=os.path.join(plot_folder, 'tau{}'.format(test_example)), limits=[-0.07, 0.07])
fig, axarr = plt.subplots(nrows=1, ncols=3, sharex=True, sharey=True, figsize=(6.5, 2.4))
titles = [r'$\tau_{11}$', r'$\tau_{12}$', r'$\tau_{13}$']
for ind, key in enumerate(['uu', 'uv', 'uw']):
x, y = utils.pdf_from_array_with_x(tau_true[key], bins=100, range=[-0.1, 0.1])
axarr[ind].semilogy(x, y, 'r-', lw=2, label='true')
x, y = utils.pdf_from_array_with_x(tau[key], bins=100, range=[-0.1, 0.1])
axarr[ind].semilogy(x, y, 'b-', label='modeled')
if y_predict2:
x, y = utils.pdf_from_array_with_x(tau2[key], bins=100, range=[-0.1, 0.1])
axarr[ind].semilogy(x, y, 'g-', label='modeled 2')
axarr[ind].set_xlabel(titles[ind])
axarr[0].axis(xmin=-0.1, xmax=0.1, ymin=1e-3)
axarr[0].set_ylabel('pdf')
axarr[0].set_yscale('log')
plt.legend(loc=0)
fig.subplots_adjust(left=0.1, right=0.95, wspace=0.16, bottom=0.2, top=0.9)
fig.savefig(os.path.join(plot_folder, 'tau_pdf{}'.format(test_example)))
# print(os.path.join(plot_folder, 'tau_pdf{}'.format(test_example)))
plt.close('all')
def user_achievements(device_id, db):
f = filters.filter(bottle.request.query.filter)
return {a: handlers.dispatch(handlers=handlers.handlers.user.achievements,
config=f(c),
achievement_id=a,
db=db,
params={'device_id': device_id})
for a, c in conf.achievements.items()}
def user_achievement_by_id(device_id, achievement_id, db):
f = filters.filter(bottle.request.query.filter)
c = conf.achievements.get_or_raise(key=achievement_id,
error=errors.UnknownAchievementId(achievement_id))
return handlers.dispatch(handlers=handlers.handlers.user.achievements,
config=f(c),
achievement_id=achievement_id,
db=db,
params={'device_id': device_id})
def user_achievement_by_id(device_id, achievement_id, db):
f = filters.filter(bottle.request.query.filter)
c = conf.achievements.get_or_raise(
key=achievement_id, error=errors.UnknownAchievementId(achievement_id))
return handlers.dispatch(handlers=handlers.handlers.user.achievements,
config=f(c),
achievement_id=achievement_id,
db=db,
params={'device_id': device_id})
def test_should_return_list_with_only_bosse_items():
result = filter(["bosse", "daniel", "edvard", "bosse", "bosse"], "bosse")
length = len(result) # should be 3
for name in result:
assert_equal(name, "bosse")
assert_equal(length, 3)
def ranking_all(db):
f = filters.filter(bottle.request.query.filter)
return {a: handlers.dispatch(handlers=handlers.handlers.ranking,
config=f(c),
achievement_id=a,
db=db,
params={'from': bottle.request.query.get("from"),
'to': bottle.request.query.to})
for a, c in conf.achievements.items()}
def user_achievements(device_id, db):
f = filters.filter(bottle.request.query.filter)
return {
a: handlers.dispatch(handlers=handlers.handlers.user.achievements,
config=f(c),
achievement_id=a,
db=db,
params={'device_id': device_id})
for a, c in conf.achievements.items()
}
def test_should_return_list_with_only_bosse_items():
result = filter(["bosse", "daniel", "edvard", "bosse", "bosse"], "bosse")
length = len(result) # should be 3
for name in result:
assert_equal(name, "bosse")
assert_equal(length,3)
def ranking_by_id(achievement_id, db):
f = filters.filter(bottle.request.query.filter)
c = conf.achievements.get_or_raise(key=achievement_id,
error=errors.UnknownAchievementId(achievement_id))
return handlers.dispatch(handlers=handlers.handlers.ranking,
config=f(c),
achievement_id=achievement_id,
db=db,
params={'from': bottle.request.query.get("from"),
'to': bottle.request.query.to})
def ranking_by_id(achievement_id, db):
f = filters.filter(bottle.request.query.filter)
c = conf.achievements.get_or_raise(
key=achievement_id, error=errors.UnknownAchievementId(achievement_id))
return handlers.dispatch(handlers=handlers.handlers.ranking,
config=f(c),
achievement_id=achievement_id,
db=db,
params={
'from': bottle.request.query.get("from"),
'to': bottle.request.query.to
})
def ranking_all(db):
f = filters.filter(bottle.request.query.filter)
return {
a: handlers.dispatch(handlers=handlers.handlers.ranking,
config=f(c),
achievement_id=a,
db=db,
params={
'from': bottle.request.query.get("from"),
'to': bottle.request.query.to
})
for a, c in conf.achievements.items()
}
def make_filter(filter_type=['none','snp', 'outgroup_other','outgroup', 'all_pops'],
outgroup_name='', covariance_pipeline=[]):
filter_type=initor(filter_type)
#taking care of special cases
if 23 in covariance_pipeline and filter_type=='snp':
filter_type='none'
if 6 in covariance_pipeline and (7 in covariance_pipeline or 8 in covariance_pipeline) and filter_type=='snp':
filter_type='none'
if filter_type=='outgroup':
return outgroup_filter(outgroup_name)
elif filter_type=='outgroup_other':
return outgroup_other_filter(outgroup_name)
elif filter_type=='snp':
return snp_filter()
elif filter_type=='none':
return filter()
elif filter_type=='all_pops':
return all_pops()
else:
assert False, 'Unexpected behaviour of make_filter because filter type is: '+str(filter_type)
#Average
#img1=cv2.imread('./image_1.jpg',0)
#img=filters.padding(img1,15)
#img=filters.filter(img,15,0)
#img=filters.removepadd(img,15)
#blur=cv2.blur(img1,(15,15))
#blur=filters.sub(img,blur)
#blur=blur*5
#cv2.imshow("Average filter",blur)
##Median
img1=cv2.imread('./image_2.png',0)
img1=filters.addnoise(img1,10)
img=filters.padding(img1,15)
img=filters.filter(img,15,1)
img=filters.removepadd(img,15)
print(img)
img=img.astype(np.uint8)
blur=cv2.medianBlur(img1,15)
blur=filters.sub(img,blur)
blur=blur*5
cv2.imshow("Median filter",blur)
###Gaussian
#img1=cv2.imread('./image_3.png',0)
#img=filters.padding(img1,15)
#img=filters.filter(img,15,2)
#img=filters.removepadd(img,15)
#print(img)
def test_takes_a_list_and_object_as_argument():
filter(1337, 45)
filter()
filter("kjkj")
filter([1, 2, 3])
def test_takes_a_list_and_object_as_argument():
filter(1337, 45)
filter()
filter("kjkj")
filter([1, 2, 3])
def test_should_return_list():
result = filter([1, 2, 3], 4)
# result should be a list
assert_true(isinstance(result, list))
def test_should_return_list():
result = filter([1, 2, 3], 4)
# result should be a list
assert_true(isinstance(result, list))
#cv2.imshow("Average filter",img)
#
##5x5 Gaussian filter
#img2=cv2.imread('./image_3.png',0)
#img2=filters.padding(img2,5)
#img2=filters.filter(img2,5,2)
#img2=filters.removepadd(img2,5)
#print(img2[98])
#img2=img2.astype(np.uint8)
#
#cv2.imshow("Average filter",img2)
#11x11 Gaussian filter
img = cv2.imread('./image_3.png', 0)
img = filters.padding(img, 11)
img = filters.filter(img, 11, 2)
img = filters.removepadd(img, 11)
img = img.astype(np.uint8)
cv2.imshow("Average filter", img)
##15x15 Gaussian filter
#img=cv2.imread('./image_3.png',0)
#img=filters.padding(img,15)
#img=filters.filter(img,15,2)
#img=filters.removepadd(img,15)
#img=img.astype(np.uint8)
#cv2.imshow("Average filter",img)
#Question4
##Laplacian level 1