def build_comments(url):
if url[-1] != '/':
url += '/'
page = requests.get(url)
content_type = page.headers['Content-Type']
if 'application/rss' in content_type:
from rss import rss
return rss(page)
return walk(page)
def plantreg(X, y, num):
"""
Input:
X - macierz z przykladami budujacymi drzewo
y - wektor z decyzjami
num - liczba cech, sposrod ktorych gini wybiera wartosc podzialu
Rekurencyjna funkcja budujaca drzewo. Wybiera wartosc podzialu na podstawie
wartosci RSS.
"""
rss_tup = rss.rss(X,y,num)
set1, set2, y1, y2 = Tree.divideset(X, rss_tup[0], rss_tup[1], y)
if rss_tup[2] == 100000000000000000:
if len(y1) == 0:
y1 = y2
if len(y2) == 0:
y2 = y1
y1avg = float(sum(y1))/len(y1)
y2avg = float(sum(y2))/len(y2)
return node.Node(tb = leaf.Leaf(y1avg), fb = leaf.Leaf(y2avg), value = rss_tup[1], index=rss_tup[0], gn = rss_tup[2])
if len(set1) > 3 and len(set2) > 3:
trueBranch = Tree.plantreg(set1, y1, num)
falseBranch = Tree.plantreg(set2, y2, num)
return node.Node(tb=trueBranch, fb=falseBranch, value=rss_tup[1], index=rss_tup[0], gn = rss_tup[2])
elif len(set1) > 3 and len(set2) <= 3:
trueBranch = Tree.plantreg(set1, y1, num)
y2avg = float(sum(y2))/len(y2)
falseBranch = leaf.Leaf(y2avg)
return node.Node(tb=trueBranch, fb=falseBranch, value=rss_tup[1], index=rss_tup[0], gn = rss_tup[2])
elif len(set2) > 3 and len(set1) <= 3:
y1avg = float(sum(y1))/len(y1)
trueBranch = leaf.Leaf(y1avg)
falseBranch = Tree.plantreg(set2, y2, num)
return node.Node(tb=trueBranch, fb=falseBranch, value=rss_tup[1], index=rss_tup[0], gn = rss_tup[2])
else:
if len(y1) == 0:
y1 = y2
if len(y2) == 0:
y2 = y1
y1avg = float(sum(y1))/len(y1)
y2avg = float(sum(y2))/len(y2)
return node.Node(tb = leaf.Leaf(y1avg), fb = leaf.Leaf(y2avg), value = rss_tup[1], index=rss_tup[0], gn = rss_tup[2])
async def _():
none.logger.info("Running scheduled Job")
loadConfig()
bot = none.get_bot()
tmp = rss("db").query(URLS)
for i, post in enumerate(tmp):
text = []
text.append({"type": "text", "data": {"text": f'{post.title}\n'}})
text.append({"type": "text", "data": {"text": f'发布于 {post.author}\n'}})
text.append({"type": "text", "data": {"text": f'{post.link}'}})
none.logger.info(text)
try:
for num in QQGroup:
await bot.send_group_msg(group_id=num, message=text)
except CQHttpError:
pass
def test_rss(self):
X_list = []
f = open("regd.txt", "r")
for i in f:
X_list.append(i.strip().split("\t"))
f.close()
y_list = []
g = open("regkl.txt", "r")
for j in g:
y_list.append(float(j.strip()))
g.close()
rss_val = 1926.0449999999996
rss_test = rss.rss(X_list,y_list,4)[2]
self.assertEqual(rss_val, rss_test)
def do_rss(self):
from rss import rss
return rss()
def do_rss(self): from rss import rss return rss()
from rss import rss
"""
Simple tester for the rss module which connects to rasdproc.
Data is read and output in the rtl_power format.
"""
r = rss()
print('rasdproc state:')
keys = r.parameters.keys()
values = [str(value) for value in r.parameters.values()]
print(' '.join(keys))
print(' '.join(values))
while True:
rtl_power_lines = r.read_data()
for line in rtl_power_lines:
print(line)
def convert_localfile_to_jpg(local_image_file,local_jpg_file):
debug('converting to jpeg')
debug(" "+local_image_file)
debug(" "+local_jpg_file)
im=Image.open(local_image_file)
if im.mode != "RGB":
im = im.convert("RGB")
im.save(local_jpg_file)
frameconfig=yaml.load(open('/home/matt/framer/frameconfig.yaml','r').read())
feed=frameconfig['feedinfo']
resources=frameconfig['resources']
local_dir=feed['localdir']+"/"
rss=rss.rss(feed['localdir']+"/"+feed['filename'],feed['title'],feed['description'])
#download each image, convert it to jpg if nessesary, move to folder and build rss
for item in resources:
# use a hash for the file name as some urls are horrendous looking filenames
md5= hashlib.sha224(item['uri']).hexdigest()
localfsp=local_dir+md5
# type can be file or web
if item['type']=='file':
debug('file')
debug('copying '+item['uri']+' to '+localfsp)
copyfile(item['uri'], localfsp)
else:
debug('web')
download_web_image(item['uri'],localfsp)
def plantreg(X, y, num):
"""
Input:
X - macierz z przykladami budujacymi drzewo
y - wektor z decyzjami
num - liczba cech, sposrod ktorych gini wybiera wartosc podzialu
Rekurencyjna funkcja budujaca drzewo. Wybiera wartosc podzialu na podstawie
wartosci RSS.
"""
rss_tup = rss.rss(X, y, num)
set1, set2, y1, y2 = Tree.divideset(X, rss_tup[0], rss_tup[1], y)
if rss_tup[2] == 100000000000000000:
if len(y1) == 0:
y1 = y2
if len(y2) == 0:
y2 = y1
y1avg = float(sum(y1)) / len(y1)
y2avg = float(sum(y2)) / len(y2)
return node.Node(tb=leaf.Leaf(y1avg),
fb=leaf.Leaf(y2avg),
value=rss_tup[1],
index=rss_tup[0],
gn=rss_tup[2])
if len(set1) > 3 and len(set2) > 3:
trueBranch = Tree.plantreg(set1, y1, num)
falseBranch = Tree.plantreg(set2, y2, num)
return node.Node(tb=trueBranch,
fb=falseBranch,
value=rss_tup[1],
index=rss_tup[0],
gn=rss_tup[2])
elif len(set1) > 3 and len(set2) <= 3:
trueBranch = Tree.plantreg(set1, y1, num)
y2avg = float(sum(y2)) / len(y2)
falseBranch = leaf.Leaf(y2avg)
return node.Node(tb=trueBranch,
fb=falseBranch,
value=rss_tup[1],
index=rss_tup[0],
gn=rss_tup[2])
elif len(set2) > 3 and len(set1) <= 3:
y1avg = float(sum(y1)) / len(y1)
trueBranch = leaf.Leaf(y1avg)
falseBranch = Tree.plantreg(set2, y2, num)
return node.Node(tb=trueBranch,
fb=falseBranch,
value=rss_tup[1],
index=rss_tup[0],
gn=rss_tup[2])
else:
if len(y1) == 0:
y1 = y2
if len(y2) == 0:
y2 = y1
y1avg = float(sum(y1)) / len(y1)
y2avg = float(sum(y2)) / len(y2)
return node.Node(tb=leaf.Leaf(y1avg),
fb=leaf.Leaf(y2avg),
value=rss_tup[1],
index=rss_tup[0],
gn=rss_tup[2])
