def blogs_search(content, page_num):
if not is_int(page_num):
abort(404)
page_num = int(page_num)
if request.method == 'GET':
all_blogs = Blog.query.order_by(-Blog.id).all()
blogs = []
content = content.strip()
words = content.split(' ')
for rb in all_blogs:
for word in words:
word_low = word.lower()
if word_low in rb.title.lower(
) or word_low in rb.content.lower():
blogs.append(rb)
break
split = page_spliter(blogs, 5)
min_page = 1
max_page = len(split)
if max_page == 0:
max_page = 1
split = [[]]
if page_num < min_page or page_num > max_page:
abort(404)
blogs = split[page_num - 1]
return render_template('Blog/searchBlogs.html',
blogs=blogs,
this_page=page_num,
min_page=min_page,
if_login=if_login(),
max_page=max_page,
search=content)
def get_edit_blog(blog_id):
if not is_int(blog_id):
abort(404)
blog_id = int(blog_id)
if request.method == 'GET':
blog = Blog.query.filter_by(id=blog_id).first_or_404()
return render_template('Blog/editBlog.html', blog=blog)
def get_blocks_indices_comments_values(self):
"""
This function contains knowledge about what an slhafile from slhalib looks like
It returns a dictionary: {(block_name,indices,comment): value, ...}
NB: atm ignoring BLOCK SPINFO and DECAY's
"""
s = str(self)
data = OrderedDict()
block_name = None
for line in s.split('\n'):
if line.startswith('B'):
# is a block
block_name = line.split()[1]
if 'Q=' in line:
data[(block_name,tuple([]),'Qscale')]= float(line.split('=')[1].split()[0])
elif line.startswith('D'):
#FIXME: we may want to change this
print("WARNING: DECAY's are ignored in SLHA.get_blocks_indices_comments_values() ")
block_name=None
elif block_name and (not block_name == 'SPINFO') :
#FIXME: possibly want to have the SPINFO as well at some point
items = line.split()
if len(items):
first_non_index = next(x for x in items if not is_int(x))
indices_end = items.index(first_non_index)
comment_pos = items.index('#') if '#' in items else 0
if comment_pos >0: indices_end=comment_pos-1
indices = tuple([int(x) for x in items[:indices_end]])
values = tuple([float(x) for x in
items[indices_end:comment_pos]])
if len(values) == 1:
values = values[0]
comment = ' '.join(items[comment_pos:]).lstrip('#').lstrip()
data[(block_name,indices,comment)] = values
return data
def process(self):
s = str(self)
data = OrderedDict()
block_name = None
for line in s.split('\n'):
if line.startswith('B'):
# is a block
block_name = line.split()[1]
data[block_name] = OrderedDict()
#pass
else:
items = line.split()
if len(items):
first_non_index = next(x for x in items if not is_int(x))
indices_end = items.index(first_non_index)
comment_pos = items.index('#') if '#' in items else 0
indices = tuple([int(x) for x in items[:indices_end]])
values = tuple([float(x) for x in
items[indices_end:comment_pos]])
if len(values) == 1:
values = values[0]
comment = ' '.join(items[comment_pos:]).lstrip('#').lstrip()
#data[block_name][indices] = (values, comment)
data[block_name][comment] = values
return data
def delete_blog(blog_id):
if not is_int(blog_id):
abort(404)
blog_id = int(blog_id)
if request.method == 'GET':
blog = Blog.query.filter_by(id=blog_id).first_or_404()
blog.delete_with_save()
return redirect(url_for('blog.index'))
def api_set_current_question(data):
if 'question_id' not in data or not tools.is_int(data['question_id']) \
or int(data['question_id']) < -1 or \
int(data['question_id']) >= len(app.questions):
return tools.gen_result_failure('Invalid question ID.')
else:
app.show_answer = False
app.current_question = int(data['question_id'])
return tools.gen_result_success(message='Success.')
def _export(self):
if tools.is_int(self._url): # linkid needs to be converted for export
L = MYGLOBALS.g_db.getLink(self._url)
if L and L in self.links:
print L
self._url = L._url
else:
print "fixing unknown dest linkid for", self.name
self._url = "list"
return ("list %s " % self.name) + Link._export(self)
def post_edit_blog(blog_id):
if not is_int(blog_id):
abort(404)
blog_id = int(blog_id)
if request.method == 'POST':
form = BlogForm(formdata=request.form)
blog = Blog.query.filter_by(id=blog_id).first_or_404()
errors = blog.edit_with_save(form.title.data, form.content.data)
if not errors:
return redirect(url_for('blog.get_blog', blog_id=blog_id))
else:
return render_template('Blog/errorList.html', errors=errors)
def post_comment(blog_id):
if not is_int(blog_id):
abort(404)
blog_id = int(blog_id)
if request.method == 'POST':
form = CommentForm(formdata=request.form)
user = User.query.filter_by(username=get_username()).first()
comment = Comment(sender=user.username,
content=form.content.data,
blog_id=blog_id)
errors = comment.add_with_save()
if not errors:
return redirect(url_for('blog.get_blog', blog_id=blog_id))
else:
return render_template('Blog/errorList.html', errors=errors)
def get_blog(blog_id):
if not is_int(blog_id):
abort(404)
blog_id = int(blog_id)
if request.method == 'GET':
blog = Blog.query.filter_by(id=blog_id).first_or_404()
m_content = markdown(blog.content)
if '<p>' in m_content:
m_content = m_content.replace('<p>', '')
if '</p>' in m_content:
m_content = m_content.replace('</p>', '')
comments = Comment.query.filter_by(
blog_id=blog_id).order_by(-Comment.id).all()
blog.add_read()
return render_template('Blog/blog.html',
blog=blog,
if_login=if_login(),
m_content=m_content,
comments=comments)
def blogs_page(page_num):
if not is_int(page_num):
abort(404)
page_num = int(page_num)
if request.method == 'GET':
all_blogs = Blog.query.order_by(-Blog.id).all()
split = page_spliter(all_blogs, 5)
min_page = 1
max_page = len(split)
if max_page == 0:
max_page = 1
split = [[]]
if page_num < min_page or page_num > max_page:
abort(404)
blogs = split[page_num - 1]
return render_template('Blog/blogs.html',
if_login=if_login(),
blogs=blogs,
username=get_username(),
is_owner=is_owner(),
this_page=page_num,
min_page=min_page,
max_page=max_page)
def _show_res(hs, res, figtitle='', max_nCols=5, topN_cxs=None, gt_cxs=None,
show_query=False, all_kpts=False, annote=True, query_cfg=None,
split_plots=False, interact=True, **kwargs):
''' Displays query chip, groundtruth matches, and top 5 matches'''
#printDBG('[viz._show_res()] %s ' % helpers.printableVal(locals()))
fnum = kwargs.pop('fnum', 3)
#print('========================')
#print('[viz] Show chip matches:')
if topN_cxs is None:
topN_cxs = []
if gt_cxs is None:
gt_cxs = []
qcx = res.qcx
all_gts = hs.get_other_indexed_cxs(qcx)
#print('[viz._show_res()]----------------')
print('[viz._show_res()] #topN=%r #missed_gts=%r/%r' % (len(topN_cxs),
len(gt_cxs),
len(all_gts)))
#printDBG('[viz._show_res()] * max_nCols=%r' % (max_nCols,))
#printDBG('[viz._show_res()] * show_query=%r' % (show_query,))
ranked_cxs = res.topN_cxs(hs, N='all')
# Build a subplot grid
nQuerySubplts = 1 if show_query else 0
nGtSubplts = nQuerySubplts + (0 if gt_cxs is None else len(gt_cxs))
nTopNSubplts = 0 if topN_cxs is None else len(topN_cxs)
nTopNCols = min(max_nCols, nTopNSubplts)
nGTCols = min(max_nCols, nGtSubplts)
if not split_plots:
nGTCols = max(nGTCols, nTopNCols)
nTopNCols = nGTCols
nGtRows = 0 if nGTCols == 0 else int(np.ceil(nGtSubplts / nGTCols))
nTopNRows = 0 if nTopNCols == 0 else int(np.ceil(nTopNSubplts / nTopNCols))
nGtCells = nGtRows * nGTCols
if split_plots:
nRows = nGtRows
else:
nRows = nTopNRows + nGtRows
# Helper function for drawing matches to one cx
def _show_matches_fn(cx, orank, pnum):
'helper for viz._show_res'
aug = 'rank=%r\n' % orank
#printDBG('[viz._show_res()] plotting: %r' % (pnum,))
kwshow = dict(draw_ell=annote, draw_pts=annote, draw_lines=annote,
ell_alpha=.5, all_kpts=all_kpts, **kwargs)
show_matches_annote_res(res, hs, cx, title_aug=aug, fnum=fnum, pnum=pnum, **kwshow)
def _show_query_fn(plotx_shift, rowcols):
'helper for viz._show_res'
plotx = plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
#printDBG('[viz._show_res()] Plotting Query: pnum=%r' % (pnum,))
show_chip(hs, res=res, pnum=pnum, draw_kpts=annote, prefix='q', fnum=fnum)
# Helper to draw many cxs
def _plot_matches_cxs(cx_list, plotx_shift, rowcols):
'helper for viz._show_res'
#printDBG('[viz._show_res()] Plotting Chips %s:' % hs.cidstr(cx_list))
if cx_list is None:
return
for ox, cx in enumerate(cx_list):
plotx = ox + plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
oranks = np.where(ranked_cxs == cx)[0]
if len(oranks) == 0:
orank = -1
continue
orank = oranks[0] + 1
_show_matches_fn(cx, orank, pnum)
#query_uid = res.query_uid
#query_uid = re.sub(r'_trainID\([0-9]*,........\)', '', query_uid)
#query_uid = re.sub(r'_indxID\([0-9]*,........\)', '', query_uid)
#query_uid = re.sub(r'_dcxs\(........\)', '', query_uid)
#print('[viz._show_res()] fnum=%r' % fnum)
fig = df2.figure(fnum=fnum, pnum=(nRows, nGTCols, 1), doclf=True)
fig.clf()
df2.plt.subplot(nRows, nGTCols, 1)
# Plot Query
if show_query:
_show_query_fn(0, (nRows, nGTCols))
# Plot Ground Truth
_plot_matches_cxs(gt_cxs, nQuerySubplts, (nRows, nGTCols))
# Plot TopN in a new figure
if split_plots:
#df2.set_figtitle(figtitle + 'GT', query_uid)
nRows = nTopNRows
fig = df2.figure(fnum=fnum + 9000)
fig.clf()
df2.plt.subplot(nRows, nTopNCols, 1)
shift_topN = 0
else:
shift_topN = nGtCells
_plot_matches_cxs(topN_cxs, shift_topN, (nRows, nTopNCols))
if split_plots:
pass
#df2.set_figtitle(figtitle + 'topN', query_uid)
else:
pass
#df2.set_figtitle(figtitle, query_uid)
df2.set_figtitle(figtitle)
if interact:
#printDBG('[viz._show_res()] starting interaction')
# Create
def _on_res_click(event):
'result interaction mpl event callback slot'
print('[viz] clicked result')
if event.xdata is None:
return
_show_res(hs, res, figtitle=figtitle, max_nCols=max_nCols, topN_cxs=topN_cxs,
gt_cxs=gt_cxs, show_query=show_query, all_kpts=all_kpts,
annote=not annote, split_plots=split_plots,
interact=interact, **kwargs)
fig.canvas.draw()
df2.disconnect_callback(fig, 'button_press_event')
if interact:
df2.connect_callback(fig, 'button_press_event', _on_res_click)
#printDBG('[viz._show_res()] Finished')
return fig
# USE LAB
USE_LAB = False # True # False
import tools
from skimage import color
if USE_LAB:
isInt = tools.is_int(rchip2)
rchip2_blendA = np.zeros((h2, w2, 3), dtype=rchip2.dtype)
rchip2_blendH = np.zeros((h2, w2, 3), dtype=rchip2.dtype)
rchip2_blendA = np.rollaxis(rchip2_blendA, 2)
rchip2_blendH = np.rollaxis(rchip2_blendH, 2)
#rchip2_blendA[0] = (rchip2 / 2) + (rchip1_At / 2)
#rchip2_blendH[0] = (rchip2 / 2) + (rchip1_Ht / 2)
#rchip2_blendA[0] /= 1 + (122 * isInt)
#rchip2_blendH[0] /= 1 + (122 * isInt)
rchip2_blendA[0] += 255
rchip2_blendH[0] += 255
rchip2_blendA[1] = rchip2
rchip2_blendH[1] = rchip2
rchip2_blendA[2] = rchip1_At
rchip2_blendH[2] = rchip1_Ht
rchip2_blendA = np.rollaxis(np.rollaxis(rchip2_blendA, 2), 2)
rchip2_blendH = np.rollaxis(np.rollaxis(rchip2_blendH, 2), 2)
print('unchanged stats')
print(helpers.printable_mystats(rchip2_blendH.flatten()))
print(helpers.printable_mystats(rchip2_blendA.flatten()))
if isInt:
print('is int')
rchip2_blendA = np.array(rchip2_blendA, dtype=float)
rchip2_blendH = np.array(rchip2_blendH, dtype=float)
else:
print('is float')
print('div stats')
print(helpers.printable_mystats(rchip2_blendH.flatten()))
print(helpers.printable_mystats(rchip2_blendA.flatten()))
rchip2_blendA = color.lab2rgb(rchip2_blendA)
rchip2_blendH = color.lab2rgb(rchip2_blendH)
if isInt:
print('is int')
rchip2_blendA = np.array(np.round(rchip2_blendA * 255), dtype=np.uint8)
rchip2_blendH = np.array(np.round(rchip2_blendH * 255), dtype=np.uint8)
print('changed stats')
print(helpers.printable_mystats(rchip2_blendH.flatten()))
print(helpers.printable_mystats(rchip2_blendA.flatten()))
def api_get_question(data):
if 'question_id' not in data or not tools.is_int(data['question_id']) \
or int(data['question_id']) < 0 or \
int(data['question_id']) >= len(app.questions):
return tools.gen_result_failure('Invalid question ID.')
return tools.gen_result_success(data=get_question(int(data['question_id'])))
def _show_res(hs,
res,
figtitle='',
max_nCols=5,
topN_cxs=None,
gt_cxs=None,
show_query=False,
all_kpts=False,
annote=True,
query_cfg=None,
split_plots=False,
interact=True,
**kwargs):
''' Displays query chip, groundtruth matches, and top 5 matches'''
#printDBG('[viz._show_res()] %s ' % helpers.printableVal(locals()))
fnum = kwargs.pop('fnum', 3)
#print('========================')
#print('[viz] Show chip matches:')
if topN_cxs is None:
topN_cxs = []
if gt_cxs is None:
gt_cxs = []
qcx = res.qcx
all_gts = hs.get_other_indexed_cxs(qcx)
#print('[viz._show_res()]----------------')
print('[viz._show_res()] #topN=%r #missed_gts=%r/%r' %
(len(topN_cxs), len(gt_cxs), len(all_gts)))
#printDBG('[viz._show_res()] * max_nCols=%r' % (max_nCols,))
#printDBG('[viz._show_res()] * show_query=%r' % (show_query,))
ranked_cxs = res.topN_cxs(hs, N='all')
# Build a subplot grid
nQuerySubplts = 1 if show_query else 0
nGtSubplts = nQuerySubplts + (0 if gt_cxs is None else len(gt_cxs))
nTopNSubplts = 0 if topN_cxs is None else len(topN_cxs)
nTopNCols = min(max_nCols, nTopNSubplts)
nGTCols = min(max_nCols, nGtSubplts)
if not split_plots:
nGTCols = max(nGTCols, nTopNCols)
nTopNCols = nGTCols
nGtRows = 0 if nGTCols == 0 else int(np.ceil(nGtSubplts / nGTCols))
nTopNRows = 0 if nTopNCols == 0 else int(np.ceil(nTopNSubplts / nTopNCols))
nGtCells = nGtRows * nGTCols
if split_plots:
nRows = nGtRows
else:
nRows = nTopNRows + nGtRows
# Helper function for drawing matches to one cx
def _show_matches_fn(cx, orank, pnum):
'helper for viz._show_res'
aug = 'rank=%r\n' % orank
#printDBG('[viz._show_res()] plotting: %r' % (pnum,))
kwshow = dict(draw_ell=annote,
draw_pts=annote,
draw_lines=annote,
ell_alpha=.5,
all_kpts=all_kpts,
**kwargs)
show_matches_annote_res(res,
hs,
cx,
title_aug=aug,
fnum=fnum,
pnum=pnum,
**kwshow)
def _show_query_fn(plotx_shift, rowcols):
'helper for viz._show_res'
plotx = plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
#printDBG('[viz._show_res()] Plotting Query: pnum=%r' % (pnum,))
show_chip(hs,
res=res,
pnum=pnum,
draw_kpts=annote,
prefix='q',
fnum=fnum)
# Helper to draw many cxs
def _plot_matches_cxs(cx_list, plotx_shift, rowcols):
'helper for viz._show_res'
#printDBG('[viz._show_res()] Plotting Chips %s:' % hs.cidstr(cx_list))
if cx_list is None:
return
for ox, cx in enumerate(cx_list):
plotx = ox + plotx_shift + 1
pnum = (rowcols[0], rowcols[1], plotx)
oranks = np.where(ranked_cxs == cx)[0]
if len(oranks) == 0:
orank = -1
continue
orank = oranks[0] + 1
_show_matches_fn(cx, orank, pnum)
#query_uid = res.query_uid
#query_uid = re.sub(r'_trainID\([0-9]*,........\)', '', query_uid)
#query_uid = re.sub(r'_indxID\([0-9]*,........\)', '', query_uid)
#query_uid = re.sub(r'_dcxs\(........\)', '', query_uid)
#print('[viz._show_res()] fnum=%r' % fnum)
fig = df2.figure(fnum=fnum, pnum=(nRows, nGTCols, 1), doclf=True)
fig.clf()
df2.plt.subplot(nRows, nGTCols, 1)
# Plot Query
if show_query:
_show_query_fn(0, (nRows, nGTCols))
# Plot Ground Truth
_plot_matches_cxs(gt_cxs, nQuerySubplts, (nRows, nGTCols))
# Plot TopN in a new figure
if split_plots:
#df2.set_figtitle(figtitle + 'GT', query_uid)
nRows = nTopNRows
fig = df2.figure(fnum=fnum + 9000)
fig.clf()
df2.plt.subplot(nRows, nTopNCols, 1)
shift_topN = 0
else:
shift_topN = nGtCells
_plot_matches_cxs(topN_cxs, shift_topN, (nRows, nTopNCols))
if split_plots:
pass
#df2.set_figtitle(figtitle + 'topN', query_uid)
else:
pass
#df2.set_figtitle(figtitle, query_uid)
df2.set_figtitle(figtitle)
if interact:
#printDBG('[viz._show_res()] starting interaction')
# Create
def _on_res_click(event):
'result interaction mpl event callback slot'
print('[viz] clicked result')
if event.xdata is None:
return
_show_res(hs,
res,
figtitle=figtitle,
max_nCols=max_nCols,
topN_cxs=topN_cxs,
gt_cxs=gt_cxs,
show_query=show_query,
all_kpts=all_kpts,
annote=not annote,
split_plots=split_plots,
interact=interact,
**kwargs)
fig.canvas.draw()
df2.disconnect_callback(fig, 'button_press_event')
if interact:
df2.connect_callback(fig, 'button_press_event', _on_res_click)
#printDBG('[viz._show_res()] Finished')
return fig
# USE LAB
USE_LAB = False # True # False
import tools
from skimage import color
if USE_LAB:
isInt = tools.is_int(rchip2)
rchip2_blendA = np.zeros((h2, w2, 3), dtype=rchip2.dtype)
rchip2_blendH = np.zeros((h2, w2, 3), dtype=rchip2.dtype)
rchip2_blendA = np.rollaxis(rchip2_blendA, 2)
rchip2_blendH = np.rollaxis(rchip2_blendH, 2)
#rchip2_blendA[0] = (rchip2 / 2) + (rchip1_At / 2)
#rchip2_blendH[0] = (rchip2 / 2) + (rchip1_Ht / 2)
#rchip2_blendA[0] /= 1 + (122 * isInt)
#rchip2_blendH[0] /= 1 + (122 * isInt)
rchip2_blendA[0] += 255
rchip2_blendH[0] += 255
rchip2_blendA[1] = rchip2
rchip2_blendH[1] = rchip2
rchip2_blendA[2] = rchip1_At
rchip2_blendH[2] = rchip1_Ht
rchip2_blendA = np.rollaxis(np.rollaxis(rchip2_blendA, 2), 2)
rchip2_blendH = np.rollaxis(np.rollaxis(rchip2_blendH, 2), 2)
print('unchanged stats')
print(helpers.printable_mystats(rchip2_blendH.flatten()))
print(helpers.printable_mystats(rchip2_blendA.flatten()))
if isInt:
print('is int')
rchip2_blendA = np.array(rchip2_blendA, dtype=float)
rchip2_blendH = np.array(rchip2_blendH, dtype=float)
else:
print('is float')
print('div stats')
print(helpers.printable_mystats(rchip2_blendH.flatten()))
print(helpers.printable_mystats(rchip2_blendA.flatten()))
rchip2_blendA = color.lab2rgb(rchip2_blendA)
rchip2_blendH = color.lab2rgb(rchip2_blendH)
if isInt:
print('is int')
rchip2_blendA = np.array(np.round(rchip2_blendA * 255),
dtype=np.uint8)
rchip2_blendH = np.array(np.round(rchip2_blendH * 255),
dtype=np.uint8)
print('changed stats')
print(helpers.printable_mystats(rchip2_blendH.flatten()))
print(helpers.printable_mystats(rchip2_blendA.flatten()))