def diff(master_screens_path, current_screens_path, test_name, master_hash,
current_hash):
doc = dominate.document(title=test_name)
master_screens = sorted(master_screens_path.iterdir())
current_screens = sorted(current_screens_path.iterdir())
with doc:
h1(test_name)
p("This UI test differs from master.",
style="color: grey; font-weight: bold;")
with table():
with tr():
td("Master:")
td(master_hash, style="color: red;")
with tr():
td("Current:")
td(current_hash, style="color: green;")
hr()
with table(border=1, width=600):
with tr():
th("Master")
th("Current branch")
html.diff_table(master_screens, current_screens)
return html.write(REPORTS_PATH / "diff", doc, test_name + ".html")
def generateStatsHTML(graph,statsFilePath = "stats.html",postStatsFilePath = "postStats.html"): #Generates the Stats HTML section
firstLevel = checkFirstLevel(graph)
softwareLabelNum = queryVersionNum(graph)
softwareLabelNumList = addQueryToList(softwareLabelNum)
stats = document(title="FSL Viewer") #Creates initial html page (stats)
stats += h1("Sample FSL Viewer")
stats += ul(li(a("Stats", href="stats.html")), li("-"),li(a("Post Stats", href = "postStats.html")))
stats += h2("Stats")
stats += hr()
stats += h3("Analysis Methods")
if askSpm(graph) == True: #Checks if SPM was used
stats += p("FMRI data processing was carried out using SPM Version %s (SPM, http://www.fil.ion.ucl.ac.uk/spm/)." % softwareLabelNumList[1])
elif askFsl(graph) == True: #Checks if FSL was used
fslFeatVersion = queryFslFeatVersion(graph)
stats += p("FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version %s, part of FSL %s (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl)." % (fslFeatVersion[0], softwareLabelNumList[1]))
stats += hr()
stats += h3("Design Matrix")
designMatrixLocation = queryDesignMatrixLocation(graph)
stats += a(img(src = designMatrixLocation[1], style = "border:5px solid black", border = 0), href = designMatrixLocation[0]) #Adds design matrix image (as a link) to html page
statsFile = open(statsFilePath, "x")
print(stats, file = statsFile) #Prints html page to a file
statsFile.close()
def formatWeek(week):
hr()
for day in week.days:
formatDay(day)
hr()
# week number
number = u"Week {}".format(week.number)
div(number, cls="week-number")
def generateHtml():
with open(path.join(current_dir, '../changelog/', 'storage.json'),
'r') as f:
data = json.load(f)[::-1]
doc = document(title='Changelog - lkellar.org')
articles = []
with doc.head:
tags.link(rel='stylesheet', href='style.css')
tags.meta(charset="UTF-8")
tags.meta(name="description",
content="A log of all changes made on lkellar.org")
tags.meta(name="viewport",
content="width=device-width, initial-scale=1")
tags.link(rel="alternate",
title="Changelog Feed",
type="application/json",
href="https://lkellar.org/changelog/feed.json")
with doc:
with tags.nav().add(tags.ol()):
with tags.li():
tags.a("Home", href="../")
tags.li("Changelog")
with tags.main():
tags.h1('Changelog')
for entry in data:
tags.hr()
article_content = tags.article()
with article_content:
tags.h2(
f'{entry["title"]} - {entry["date"].split("T")[0]}',
id=f'{entry["title"]} - {entry["date"]}'.replace(
' ', ''.lower()))
list_content = tags.ul()
with list_content:
for line in entry['items']:
line = urls.sub(r'<a href="\2">\1</a>', line)
tags.li(raw(line))
articles.append((f'{entry["title"]} - {entry["date"]}'.replace(
' ', ''.lower()), list_content.render(), entry["date"],
entry['title']))
with open(path.join(current_dir, '../changelog/', 'index.html'), 'w') as f:
f.write(doc.render())
generateFeed(articles)
def _render_exchanges(exchanges, trashcan):
# The ``hr`` elements really help readability in w3m.
H.hr()
for exch in exchanges:
div = H.div(_class=u'exchange')
with div:
if exch.request:
_render_request(exch.request)
H.hr()
for resp in exch.responses:
_render_response(resp)
H.hr()
if exch.complaints:
_render_complaints(exch)
H.hr()
# Some exchanges are "complaint boxes", carrying only a complaint.
# If the user silences that complaint, we end up with an empty box.
# To avoid adding it to our document, we preemptively add it
# to a dummy "trash can" element, per Dominate docs:
#
# When the context is closed, any nodes that were not already
# added to something get added to the current context.
#
if len(div) == 0:
trashcan.add(div)
def _header(test_name, expected_hash, actual_hash):
h1(test_name)
with div():
if actual_hash == expected_hash:
p(
"This test succeeded on UI comparison.",
style="color: green; font-weight: bold;",
)
else:
p(
"This test failed on UI comparison.",
style="color: red; font-weight: bold;",
)
p("Expected: ", expected_hash)
p("Actual: ", actual_hash)
hr()
def gen_goal(self, goal, toggle=None):
"""Serialize a goal to HTML."""
with tags.blockquote(cls="alectryon-goal"):
if goal.hypotheses:
# Chrome doesn't support the ‘gap’ property in flex containers,
# so properly spacing hypotheses requires giving them margins
# and giving negative margins to their container. This breaks
# when the container is empty, so just omit the hypotheses if
# there are none.
self.gen_hyps(goal.hypotheses)
toggle = goal.hypotheses and toggle
cls = "goal-separator" + (" alectryon-extra-goal-label"
if toggle else "")
with self.gen_label(toggle, cls):
tags.hr()
if goal.name:
tags.span(goal.name, cls="goal-name")
tags.div(self.highlight(goal.conclusion), cls="goal-conclusion")
def added(screens_path, test_name):
doc = dominate.document(title=test_name)
screens = sorted(screens_path.iterdir())
with doc:
h1(test_name)
p(
"This UI test has been added to fixtures.json.",
style="color: green; font-weight: bold;",
)
hr()
with table(border=1):
with tr():
th("Added files")
for screen in screens:
with tr():
html.image(screen)
return html.write(REPORTS_PATH / "added", doc, test_name + ".html")
def add_summary(self, dict_):
""" Add a summary with key value pairs from the dictionary """
self.doc += br()
self.doc += hr()
self.doc += br()
self.add_header("Test Summary")
self.doc += br()
for k, v in dict_.items():
self.doc += p(b(k), ' = ', str(v))
self.doc += br()
def index():
removed = list((REPORTS_PATH / "removed").iterdir())
added = list((REPORTS_PATH / "added").iterdir())
diff = list((REPORTS_PATH / "diff").iterdir())
title = "UI changes from master"
doc = dominate.document(title=title)
with doc:
h1("UI changes from master")
hr()
h2("Removed:", style="color: red;")
i("UI fixtures that have been removed:")
html.report_links(removed, REPORTS_PATH)
br()
hr()
h2("Added:", style="color: green;")
i("UI fixtures that have been added:")
html.report_links(added, REPORTS_PATH)
br()
hr()
h2("Differs:", style="color: grey;")
i("UI fixtures that have been modified:")
html.report_links(diff, REPORTS_PATH)
return html.write(REPORTS_PATH, doc, "index.html")
def index() -> Path:
passed_tests = list((REPORTS_PATH / "passed").iterdir())
failed_tests = list((REPORTS_PATH / "failed").iterdir())
title = "UI Test report " + datetime.now().strftime("%Y-%m-%d %H:%M:%S")
doc = document(title=title, index=True)
with doc:
h1("UI Test report")
if not failed_tests:
p("All tests succeeded!", style="color: green; font-weight: bold;")
else:
p("Some tests failed!", style="color: red; font-weight: bold;")
hr()
h2("Failed", style="color: red;")
with p(id="file-hint"):
strong("Tip:")
text(" use ")
t.span("./tests/show_results.sh", style="font-family: monospace")
text(" to enable smart features.")
with div("Test colors", _class="script-hidden"):
with t.ul():
with t.li():
t.span("new", style="color: blue")
t.button("clear all", onclick="resetState('all')")
with t.li():
t.span("marked OK", style="color: grey")
t.button("clear", onclick="resetState('ok')")
with t.li():
t.span("marked BAD", style="color: darkred")
t.button("clear", onclick="resetState('bad')")
html.report_links(failed_tests, REPORTS_PATH, ACTUAL_HASHES)
h2("Passed", style="color: green;")
html.report_links(passed_tests, REPORTS_PATH)
return html.write(REPORTS_PATH, doc, "index.html")
def _render_exchanges(exchanges):
H.hr()
for exch in exchanges:
with H.div(_class=u'exchange'):
# The ``hr`` elements really help readability in w3m.
if exch.request:
_render_request(exch.request)
H.hr()
for resp in exch.responses:
_render_response(resp)
H.hr()
if exch.complaints:
_render_complaints(exch)
H.hr()
def _render_exchanges(exchanges):
# The ``hr`` elements really help readability in w3m.
H.hr()
for exch in exchanges:
with H.div(_class=u'exchange'):
if exch.request:
_render_request(exch.request)
H.hr()
for resp in exch.responses:
_render_response(resp)
H.hr()
if exch.complaints:
_render_complaints(exch)
H.hr()
def index():
passed_tests = list((REPORTS_PATH / "passed").iterdir())
failed_tests = list((REPORTS_PATH / "failed").iterdir())
title = "UI Test report " + datetime.now().strftime("%Y-%m-%d %H:%M:%S")
doc = dominate.document(title=title)
with doc:
h1("UI Test report")
if not failed_tests:
p("All tests succeeded!", style="color: green; font-weight: bold;")
else:
p("Some tests failed!", style="color: red; font-weight: bold;")
hr()
h2("Failed", style="color: red;")
html.report_links(failed_tests, REPORTS_PATH)
h2("Passed", style="color: green;")
html.report_links(passed_tests, REPORTS_PATH)
return html.write(REPORTS_PATH, doc, "index.html")
def html_report(exchanges, buf):
"""Generate an HTML report with check results.
:param exchanges:
An iterable of :class:`~httpolice.Exchange` objects.
They must be already processed by :func:`~httpolice.check_exchange`.
:param buf:
The file (or file-like object) to which the report will be written.
It must be opened in binary mode (not text).
"""
# We don't want to hold the entire report in memory before printing it,
# because that would mean unbounded memory growth with more input.
# But Dominate obviously doesn't have a streaming mode, so we do this
# manually. We create our document, but instead of the actual exchanges,
# we insert a separator string that allows us to split it into a prologue
# and an epilogue.
separator = u'---- CUT HERE ----'
title = u'HTTPolice report'
document = dominate.document(title=title)
_common_meta(document)
with document.head:
H.script(type=u'text/javascript').add_raw_string(js_code)
with document.body:
H.attr(_class=u'report')
with document:
H.h1(title)
H.hr()
text_node(separator)
(prologue, epilogue) = document.render().split(separator)
buf.write(prologue.encode('utf-8'))
for div in _generate_exchange_divs(exchanges):
buf.write(div.render().encode('utf-8'))
buf.write(epilogue.encode('utf-8'))
def html_report(exchanges, buf):
"""Generate an HTML report with check results.
:param exchanges:
An iterable of :class:`~httpolice.Exchange` objects.
They must be already processed by :func:`~httpolice.check_exchange`.
:param buf:
The file (or file-like object) to which the report will be written.
It must be opened in binary mode (not text).
"""
# We don't want to hold the entire report in memory before printing it,
# because that would mean unbounded memory growth with more input.
# But Dominate obviously doesn't have a streaming mode, so we do this
# manually. We create our document, but instead of the actual exchanges,
# we insert a separator string that allows us to split it into a prologue
# and an epilogue.
separator = u'---- CUT HERE ----'
title = u'HTTPolice report'
document = dominate.document(title=title)
_common_meta(document)
with document.head:
H.script(type=u'text/javascript').add_raw_string(js_code)
with document.body:
H.attr(_class=u'report')
with document:
H.h1(title)
H.hr()
text_node(separator)
(prologue, epilogue) = document.render().split(separator)
buf.write(prologue.encode('utf-8'))
for div in _generate_exchange_divs(exchanges):
buf.write(div.render().encode('utf-8'))
buf.write(epilogue.encode('utf-8'))
def get_html(self):
"""overrides the base class function"""
html_string = super(GenericFileMetaDataMixin, self).get_html()
if not self.has_metadata:
no_metadata_message = div(id="#fb-metadata-default", cls="text-center text-muted",
role="alert")
with no_metadata_message:
div("No file level metadata exists for the selected file.")
hr()
i_tag = i(cls="fa fa-eye-slash fa-2x")
i_tag['aria-hidden'] = 'true'
html_string = no_metadata_message.render()
else:
if self.temporal_coverage:
html_string += self.temporal_coverage.get_html()
if self.spatial_coverage:
html_string += self.spatial_coverage.get_html()
template = Template(html_string)
context = Context({})
return template.render(context)
def get_html(self):
"""overrides the base class function"""
html_string = super(GenericFileMetaDataMixin, self).get_html()
if not self.has_metadata:
no_metadata_message = div(id="#fb-metadata-default",
cls="text-center text-muted",
role="alert")
with no_metadata_message:
div("No file level metadata exists for the selected file.")
hr()
i_tag = i(cls="fa fa-eye-slash fa-2x")
i_tag['aria-hidden'] = 'true'
html_string = no_metadata_message.render()
else:
if self.temporal_coverage:
html_string += self.temporal_coverage.get_html()
if self.spatial_coverage:
html_string += self.spatial_coverage.get_html()
template = Template(html_string)
context = Context({})
return template.render(context)
def _generate_exchange_divs(exchanges):
for exch in exchanges:
div = H.div(_class=u'exchange')
with div:
if exch.request:
_render_request(exch.request)
# The ``hr`` elements really help readability in w3m.
H.hr()
for resp in exch.responses:
_render_response(resp)
H.hr()
if exch.complaints:
_render_complaints(exch)
H.hr()
# Some exchanges are "complaint boxes", carrying only a complaint.
# If the user silences that complaint, we end up with an empty box.
if len(div) != 0: # pylint: disable=len-as-condition
yield div
def _generate_exchange_divs(exchanges):
for exch in exchanges:
div = H.div(_class=u'exchange')
with div:
if exch.request:
_render_request(exch.request)
# The ``hr`` elements really help readability in w3m.
H.hr()
for resp in exch.responses:
_render_response(resp)
H.hr()
if exch.complaints:
_render_complaints(exch)
H.hr()
# Some exchanges are "complaint boxes", carrying only a complaint.
# If the user silences that complaint, we end up with an empty box.
if len(div) != 0: # pylint: disable=len-as-condition
yield div
def add_image_with_text(self, visuals, aspect_ratio=1.0, width=256):
""" Add images along with textual metadata """
image_dir = self.get_image_dir()
visuals['image'] = visuals['image'][0]
self.add_header(visuals['image'])
pred = util.tensor2im(visuals['Predicted'])
image_name = visuals['image']
save_path = os.path.join(image_dir, 'pred_' + image_name)
util.save_image(pred, save_path, aspect_ratio=aspect_ratio)
t = table(
border=1,
style="table-layout: fixed; width: 1200px;") # Insert a table
self.doc.add(t)
with t:
with tr():
with td(style="word-wrap: break-word;",
halign="center",
valign="top"):
with p():
hr()
p(b('ImageID: '), visuals['image'])
br()
#### Add image and feature maps ####
with figure(style="display: inline-block;"):
img(style=
"border:0px;margin:0px;float:left;width:%dpx;"
% width,
src=os.path.relpath(
os.path.join(visuals['low_path'],
visuals['image']),
self.web_dir))
figcaption('Low-Light',
style="text-align: center;")
with figure(style="display: inline-block;"):
img(style=
"border:0px;margin:0px;float:left;width:%dpx;"
% width,
src=os.path.join('images',
'pred_' + visuals['image']))
figcaption('Prediction',
style="text-align: center;")
with figure(style="display: inline-block;"):
img(style=
"border:0px;margin:0px;float:left;width:%dpx;"
% width,
src=os.path.relpath(
os.path.join(visuals['target_path'],
visuals['image']),
self.web_dir))
figcaption('Ground Truth',
style="text-align: center;")
#### Add image and feature maps ####
br()
# Add a table for class probabilities
for k, v in visuals['metrics'].items():
p("{} = {}".format(k, float(v)))
br()
def render_attn_to_html(data_imgs, captions, ixtoword,
attn_maps, att_sze, lr_imgs=None,
batch_size=cfg.TRAIN.BATCH_SIZE,
max_word_num=cfg.TEXT.WORDS_NUM, info = ['Real Images'], nvis = 8, v_sigma = 20):
html_doc = dominate.document(title='Attention Visualization')
with html_doc:
T.hr()
T.h1('Attention Sample')
if type(data_imgs) is not list:
# to maintain API.
data_imgs = [data_imgs]
ndataimgs = len(data_imgs)
processed_data_imgs = []
for data_img in data_imgs:
data_img = data_img[:nvis]
if att_sze == 17:
vis_size = att_sze * 16
else:
vis_size = data_img.size(2)
data_img = nn.Upsample(size=(vis_size, vis_size), mode='bilinear')(data_img)
# [-1, 1] --> [0, 1]
data_img.add_(1).div_(2).mul_(255)
data_img = data_img.data.numpy()
# b x c x h x w --> b x h x w x c
data_img = np.transpose(data_img, (0, 2, 3, 1))
pad_sze = data_img.shape
processed_data_imgs.append(data_img)
seq_len = max_word_num
img_set = []
for i in range(nvis):
attn = attn_maps[i].cpu().view(1, -1, att_sze, att_sze)
# --> 1 x 1 x 17 x 17
attn_max = attn.max(dim=1, keepdim=True)
attn = torch.cat([attn_max[0], attn], 1)
#
attn = attn.view(-1, 1, att_sze, att_sze)
attn = attn.repeat(1, 3, 1, 1).data.numpy()
# n x c x h x w --> n x h x w x c
attn = np.transpose(attn, (0, 2, 3, 1))
num_attn = attn.shape[0]
#
imgs = [ imgs[i] for imgs in processed_data_imgs ]
row_beforeNorm = []; minVglobal, maxVglobal = 1, 0
row_merged = [ Image.fromarray(np.uint8(img)) for img in imgs ]
row_pure_attn = [ Image.fromarray(np.zeros(img.shape, dtype = np.uint8))\
for img in imgs]
for j in range(num_attn):
one_map = attn[j]
if (vis_size // att_sze) > 1:
one_map = skimage.transform.pyramid_expand(one_map, sigma=v_sigma, upscale=vis_size // att_sze)
row_beforeNorm.append(one_map)
minV = one_map.min()
maxV = one_map.max()
if minVglobal > minV:
minVglobal = minV
if maxVglobal < maxV:
maxVglobal = maxV
for j in range(num_attn):
one_map = row_beforeNorm[j]
one_map = (one_map - minVglobal) / (maxVglobal - minVglobal)
one_map *= 255
#
PIL_im = Image.fromarray(np.uint8(img))
PIL_att = Image.fromarray(np.uint8(one_map))
merged = Image.new('RGBA', (vis_size, vis_size), (0, 0, 0, 0))
mask = Image.new('L', (vis_size, vis_size), (210))
merged.paste(PIL_im, (0, 0))
merged.paste(PIL_att, (0, 0), mask)
row_pure_attn.append(PIL_att)
row_merged.append(merged)
with html_doc:
T.hr()
T.h2('%d-th Image:' % i)
for nthimg, (pil_att, pil_img) in enumerate(zip(row_pure_attn, row_merged)):
if nthimg < ndataimgs:
if len(info) == ndataimgs:
T.p(info[nthimg])
else:
T.p('Data Images')
elif nthimg == ndataimgs:
T.p("Attention map maximized across time:")
else:
cap = captions[i][nthimg - (ndataimgs + 1)].cpu().data.numpy()
cap = ' '.join([ixtoword[w] for w in cap])
cap = cap.replace('<end>','')
T.p(cap)
attn_b64 = render_PIL_image_b64(pil_att)
T.img(src="data:;base64,{0}".format(attn_b64))
image_b64 = render_PIL_image_b64(pil_img)
T.img(src="data:;base64,{0}".format(image_b64))
return html_doc
def add_hr(self):
with self.doc:
hr()
def __init__(self, config):
self.config = config
env = jinja2.Environment(
loader=jinja2.FileSystemLoader(self.config['templates_dir']),
trim_blocks=True)
self.script = env.get_template(self.config['js_file']).render(**self.config)
self.document = dominate.document(title=self.config['project_name'])
self.document['lang'] = 'en'
self.images = []
for image_file in os.listdir(self.config['images_dir']):
dir_image_file = os.path.join(self.config['images_dir'], image_file)
if os.path.isfile(dir_image_file):
src = '{}/{}'.format(self.config['images_route'], image_file)
alt = os.path.splitext(
image_file.capitalize()
.replace('-', ' ')
.replace('_', ' '))[0]
self.images.append((src, alt))
self.images.sort(key=lambda x: x[1])
with self.document.head:
tags.meta(charset='utf-8')
tags.meta(
name='viewport',
content='width=device-width, initial-scale=1, shrink-to-fit=no')
# Bootstrap CSS.
tags.link(
rel='stylesheet',
href='https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/css/bootstrap.min.css',
integrity='sha384-ggOyR0iXCbMQv3Xipma34MD+dH/1fQ784/j6cY/iJTQUOhcWr7x9JvoRxT2MZw1T',
crossorigin='anonymous')
# Fonts.
tags.link(
rel='stylesheet',
href='https://fonts.googleapis.com/css?family=Dancing+Script&display=swap')
with self.document:
self.noscript()
with tags.script():
util.text(self.script, escape=False)
with tags.div(id='root'):
with tags.div(cls='container'):
with tags.div(cls='row mb-3 mt-3'):
with tags.div(cls='col'):
with tags.div(cls='card'):
with tags.div(cls='card-body'):
with tags.h1(cls='display-5', style="font-family: 'Dancing Script', cursive;"):
with tags.span(cls='text-capitalize'):
util.text(self.config['project_name'])
with tags.p(cls='lead'):
util.text('Use machine learning to classify flowers! The ')
tags.a('fast.ai library', href='https://docs.fast.ai')
util.text(' was used to ')
tags.a('train', href='https://github.com/nkaretnikov/resnet-flowers')
util.text(' a ')
tags.a('residual', href='https://arxiv.org/pdf/1512.03385.pdf')
util.text(' ')
tags.a('neural network', href='http://cs231n.github.io/convolutional-networks')
util.text(' on the ')
tags.a('Flower Color Images', href='https://www.kaggle.com/olgabelitskaya/flower-color-images')
util.text(' dataset to recognize the classes below.')
tags.hr(cls='my-4')
with tags.div(cls='container'):
with tags.div(cls='row mb-1'):
for src, alt in self.images:
with tags.div(cls='col-6 col-sm-4 col-md-3 col-lg-2'):
self.image(src=src, alt=alt)
with tags.div(cls='row mb-1'):
with tags.div(cls='col-md-9 col-lg-7 col-xl-6'):
self.upload_form()
with tags.div(cls='row mb-3'):
with tags.div(cls='col-md-9 col-lg-7 col-xl-6'):
self.url_form()
# Optional JavaScript for Bootstrap.
tags.script(
src='https://code.jquery.com/jquery-3.3.1.slim.min.js',
integrity='sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo',
crossorigin='anonymous')
tags.script(
src='https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.14.7/umd/popper.min.js',
integrity='sha384-UO2eT0CpHqdSJQ6hJty5KVphtPhzWj9WO1clHTMGa3JDZwrnQq4sF86dIHNDz0W1',
crossorigin='anonymous')
tags.script(
src='https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/js/bootstrap.min.js',
integrity='sha384-JjSmVgyd0p3pXB1rRibZUAYoIIy6OrQ6VrjIEaFf/nJGzIxFDsf4x0xIM+B07jRM',
crossorigin='anonymous')
# Show the filename when using 'custom-file'.
tags.script(
src='https://cdn.jsdelivr.net/npm/bs-custom-file-input/dist/bs-custom-file-input.min.js',
integrity='sha384-wbycNUwFmhRaoqw8zOxtEdIA5kWW1MUAV4bXEfNNOk0e5HmG3AaNRvOHFjWNAAQb',
crossorigin='anonymous')
with tags.script():
util.text('$(document).ready(function () { bsCustomFileInput.init() })')
def visit_Separator(self, node):
return tags.hr(_class='separator')
def generatePostStatsHTML(graph,statsFilePath = "stats.html",postStatsFilePath = "postStats.html"): #Generates Post-Stats page
voxelWise = checkHeightThreshold(graph)
clusterWise = checkExtentThreshold(graph)
softwareLabelNum = queryVersionNum(graph)
softwareLabelNumList = addQueryToList(softwareLabelNum)
statisticType = queryStatisticType(graph)
statisticType = statisticImage(statisticType[0])
statisticTypeString = statisticImageString(statisticType)
contrastName = queryContrastName(graph)
statisticMapImage = queryExcursionSetMap(graph)
postStats = document(title="FSL Viewer") #Creates initial HTML page (Post Stats)
postStats += h1("Sample FSL Viewer")
postStats += ul(li(a("Stats", href="stats.html")), li("-"),li(a("Post Stats", href = "postStats.html")))
postStats += h2("Post-stats")
postStats += hr()
postStats += h3("Analysis Methods")
if voxelWise == True: #If main threshold is Height Threshold
mainThreshValue = queryHeightThresholdValue(graph)
if askSpm(graph) == True:
postStats += p("FMRI data processing was carried out using SPM Version %s (SPM, http://www.fil.ion.ucl.ac.uk/spm/). %s statistic images were thresholded at P = %s (corrected)" % (softwareLabelNumList[1], statisticTypeString, mainThreshValue[0]))
elif askFsl(graph) == True:
fslFeatVersion = queryFslFeatVersion(graph)
postStats += p("FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version %s, part of FSL %s (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl)."
"%s statistic images were thresholded at P = %s (corrected)"
%(fslFeatVersion[0], softwareLabelNumList[1], statisticTypeString, mainThreshValue[0]))
elif clusterWise == True: #If main threshold is extent threshold
mainThreshValue = queryClusterThresholdValue(graph)
heightThreshValue = queryUHeightThresholdValue(graph)
clusterThreshType = clusterFormingThreshType(graph, statisticType)
if askSpm(graph) == True:
postStats += p("FMRI data processing was carried out using SPM Version %s (SPM, http://www.fil.ion.ucl.ac.uk/spm/). %s statistic images were thresholded using clusters determined by %s > %s and a (corrected) "
"cluster significance of P = %s "
% (softwareLabelNumList[1], statisticTypeString, clusterThreshType, heightThreshValue[0], mainThreshValue[0]))
elif askFsl(graph) == True:
fslFeatVersion = queryFslFeatVersion(graph)
postStats += p("FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version %s, part of FSL %s (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl). %s statistic images were thresholded "
"using clusters determined by %s > %s and a (corrected) cluster significance of P = %s"
%(fslFeatVersion[0], softwareLabelNumList[1], statisticTypeString, clusterThreshType, heightThreshValue[0], mainThreshValue[0]))
else: #If there is no corrected threshold - assume voxel wise
mainThreshValue = queryUHeightThresholdValue(graph)
if askSpm(graph) == True and askIfPValueUncorrected(graph) == True: #SPM used and threshold type is nidm_PValueUncorrected
postStats += p("FMRI data processing was carried out using SPM Version %s (SPM, http://www.fil.ion.ucl.ac.uk/spm/). %s statistic images were thresholded at P = %s (uncorrected)" % (softwareLabelNumList[1], statisticTypeString, mainThreshValue[0]))
elif askSpm(graph) == True and askIfOboStatistic(graph) == True: #SPM used and threshold type is obo_statistic
postStats += p("FMRI data processing was carried out using SPM Version %s (SPM, http://www.fil.ion.ucl.ac.uk/spm/). %s statistic images were thresholded at %s = %s (uncorrected)" % (softwareLabelNumList[1], statisticTypeString, statisticType, mainThreshValue[0]))
elif askFsl(graph) == True and askIfPValueUncorrected(graph) == True:
fslFeatVersion = queryFslFeatVersion(graph)
postStats += p("FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version %s, part of FSL %s (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl)."
"%s statistic images were thresholded at P = %s (uncorrected)." % (fslFeatVersion[0], softwareLabelNumList[1], statisticTypeString, mainThreshValue[0]))
elif askFsl(graph) == True and askIfOboStatistic(graph) == True:
fslFeatVersion = queryFslFeatVersion(graph)
postStats += p("FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version %s, part of FSL %s (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl)."
"%s statistic images were thresholded at %s = %s (uncorrected)." % (fslFeatVersion[0], softwareLabelNumList[1], statisticTypeString, statisticType, mainThreshValue[0]))
postStats += hr()
postStats += h3("Thresholded Activation Images")
postStats += hr()
i = 0
if askFsl(graph) == True:
while i < len(contrastName):
postStats += p("%s" % contrastName[i])
postStats += img(src = statisticMapImage[i])
i = i + 1
postStatsFile = open(postStatsFilePath, "x")
print(postStats, file = postStatsFile)
postStatsFile.close()
def visit_Separator(self, node):
return tags.hr(_class='separator')
def formatDays(days): with div(cls="days"): hr() for day in days: formatDay(day) hr()
def hr():
"""horizontal rule"""
return HTML(str(dt.hr()))
def _generate_html_email_body(title: str, new_songs: Iterable[Track],
playlist: PlayList) -> str:
link_style = 'color: #373737;'
# Generate links to the artists
artists_spans = []
for track in new_songs:
artists = []
for artist in track['track']['artists']:
name = artist['name']
url = '#'
if ('external_urls' in artist
and 'spotify' in artist['external_urls']):
url = artist['external_urls']['spotify']
artists.append(a(name, href=url, style=link_style))
else:
artists.append(name)
first = True
artists_span = span()
for artist_entry in artists:
if not first:
artists_span += ', '
artists_span += artist_entry
first = False
artists_spans.append(artists_span)
# Generate document
doc = dominate.document(title=title)
with doc:
with div(style=('font-family: arial, serif;border: 1px solid #99ff99; '
'padding: 3px; width: 600px; margin: auto; '
'background-color: #99ff99;')):
with table():
with tr():
with td():
with a(href=playlist['external_urls']['spotify']):
img(src=playlist['images'][0]['url'],
width='200px',
height='200px')
with td(style=('vertical-align: text-top; '
'padding-left: 10px;')):
div('New music was added to',
style='text-align: center;')
with h2():
a(playlist['name'],
href=playlist['external_urls']['spotify'],
style=link_style)
h3(playlist['description'],
style='text-align: center;')
hr(size='1', color='black', width='90%')
div('The following tracks where added:',
style='margin-top: 10px; margin-bottom: 10px;')
for track, artists_span in zip(new_songs, artists_spans):
with table(style=('border: 1px solid black; width:100%; '
'margin-bottom: 10px; font-size: 14px;')):
with td(width='100px;', style='width: 100px;'):
a(img(src=track['track']['album']['images'][2]['url']),
href=track['track']['external_urls']['spotify'])
with td():
with table():
with tr():
td('Artist(s):',
style=('text-align: right; '
'padding-right: 5px;'))
td(artists_span)
with tr():
td('Title:',
style='text-align: right; '
'padding-right: 5px;')
td(
a(track['track']['name'],
href=track['track']['external_urls']
['spotify'],
style=link_style))
with tr():
td('Album:',
style='text-align: right; '
'padding-right: 5px;')
td(
a(track['track']['album']['name'],
href=track['track']['album']
['external_urls']['spotify'],
style=link_style))
return doc.render(pretty=False)
def process():
# doc = dominate.document(DOCNAME)
h = html(name=DOCNAME)
with h:
# _head = head()
_head = head()
with _head:
s = style()
s.add("\nh3, h4 {text-align:center;}")
s.add("\nth {background-color:yellow;}")
s.add("\ntr, td, th {text-align:center;}")
s.add("\ntd.left {text-align:left;}")
s.add("\n")
b = body()
b.add(h3(DOCNAME))
b.add(h4(asctime()))
b.add(hr())
t = table(border="1", cellpadding="3", cellspacing="3")
b.add(t)
r = tr()
t.add(r)
r.add(th("Code"))
r.add(th("Waypoint"))
r.add(th("Image"))
r.add(th("Note"))
f = open(FILENAME, "r")
for index, line in enumerate(f.readlines()):
if index == 0:
continue
code, waypoint_name, url = line.split('\t')
r = tr()
t.add(r)
r.add(td(code))
r.add(td(a(waypoint_name, href=url)))
if code in IMAGES:
link = IMAGES[code]
if isinstance(link, type([])):
images = table()
for link in link:
r2 = tr()
r2.add(td(a(link, href=link)))
images.add(r2)
else:
images = a(link, href=link)
else:
images = ""
r.add(td(images))
if code in NOTES:
note = NOTES[code]
else:
note = "TBD"
r.add(td(note, cls="left"))
outfile = open(OUTFILE, "wb")
print >> outfile, h
outfile.close()
print "Output is in %s" % OUTFILE