def testex(request, filename="wordgap/data/test.txt", pos="v", wordnet="wordnet"):
# alles in unicode strings
# [[wordsbefore, wordsafter, token, [dis]], ...]
if wordnet=='wordnet':
fast = True
else:
fast = False
filename = "wordgap/data/" + filename + ".txt"
if path.exists(filename) and path.isfile(filename) and access(filename, R_OK):
text = tools.load_text(filename)
else:
text = tools.load_text("wordgap/data/test.txt")
if (pos=='v' or pos=='n' or pos=='a'):
ex = wordex.create_ex(text, pos=pos, fast=fast)
elif pos=='p':
ex = prepex.create_prepex(text)
else:
print "invalid POS Tag"
return Http404
# reset session data
request.session.flush()
request.session["ex"]=ex
request.session["wrong"] = 0
request.session["right"] = 0
return render_to_response("templates/template_start.html")
def read_features(filename_fet, nchannels, fetdim, freq, do_process=True):
"""Read a .fet file and return the normalize features array,
as well as the spiketimes."""
try:
features = load_text(filename_fet, np.int64, skiprows=1, delimiter=' ')
except ValueError:
features = load_text(filename_fet, np.float32, skiprows=1, delimiter='\t')
if do_process:
return process_features(features, fetdim, nchannels, freq,
nfet=first_row(filename_fet))
else:
return features
def read_features(filename_fet, nchannels, fetdim, freq, do_process=True):
"""Read a .fet file and return the normalize features array,
as well as the spiketimes."""
try:
features = load_text(filename_fet, np.int64, skiprows=1, delimiter=' ')
except ValueError:
features = load_text(filename_fet, np.float32, skiprows=1, delimiter='\t')
if do_process:
return process_features(features, fetdim, nchannels, freq,
nfet=first_row(filename_fet))
else:
return features
def weather_data():
PATH = datamanager.read_path()
request_data = datamanager.read_json(PATH + "weather/", "request_data")
url = request_data["url"]
headers = request_data["headers"]
widget_selector = request_data["widget_selector"]
html_text = tools.load_html(url, headers)
html_list = bs4.BeautifulSoup(html_text.text, "html.parser")
icon_selector = widget_selector + " " + request_data["icon_selector"]
tag_name = request_data["icon_titles"]["tag_name"]
attr_title = request_data["icon_titles"]["attr_title"]
icon_title_list = tools.load_icon_titles(icon_selector, html_list,
tag_name, attr_title)
time_selector = widget_selector + " " + request_data["time_selector"]
tag_name = request_data["time"]["tag_name"]
time_list = tools.load_text(time_selector, html_list, tag_name)
warm_selector = widget_selector + " " + request_data["warm_selector"]
tag_name = request_data["warm"]["tag_name"]
warm_list = tools.load_text(warm_selector, html_list, tag_name)
time_indexes = tools.get_list_time(time_list)
icon_titles = tools.get_list_icon_titles(icon_title_list, time_indexes)
warm_intervals = tools.get_list_warm(warm_list, time_indexes)
morning = {
"icon_title": icon_titles["morning_icon_title"],
"warm": warm_intervals["morning_warm_interval"]
}
day = {
"icon_title": icon_titles["day_icon_title"],
"warm": warm_intervals["day_warm_interval"]
}
night = {
"icon_title": icon_titles["night_icon_title"],
"warm": warm_intervals["night_warm_interval"]
}
weather_data = {"morning": morning, "day": day, "night": night}
return weather_data
def testprepex(request):
text = tools.load_text("wordgap/data/test.txt")
ex = prepex.create_prepex(text)
if ex is None:
raise Http404
request.session.flush()
request.session["ex"]=ex
request.session["wrong"] = 0
request.session["right"] = 0
return render_to_response("templates/template_start.html")
def read_probe(filename_probe, fileindex):
"""fileindex is the shank index."""
if not filename_probe:
return
if os.path.exists(filename_probe):
# Try the text-flavored probe file.
try:
probe = load_text(filename_probe, np.float32)
except:
# Or try the Python-flavored probe file (SpikeDetekt, with an
# extra field 'geometry').
try:
ns = {}
execfile(filename_probe, ns)
probe = ns['geometry'][fileindex]
probe = np.array([probe[i] for i in sorted(probe.keys())],
dtype=np.float32)
except:
return None
return process_probe(probe)
def read_probe(filename_probe, fileindex):
"""fileindex is the shank index."""
if not filename_probe:
return
if os.path.exists(filename_probe):
# Try the text-flavored probe file.
try:
probe = load_text(filename_probe, np.float32)
except:
# Or try the Python-flavored probe file (SpikeDetekt, with an
# extra field 'geometry').
try:
ns = {}
execfile(filename_probe, ns)
probe = ns['geometry'][fileindex]
probe = np.array([probe[i] for i in sorted(probe.keys())],
dtype=np.float32)
except:
return None
return process_probe(probe)
def read_waveforms(filename_spk, nsamples, nchannels):
waveforms = np.array(load_binary(filename_spk), dtype=np.float32)
n = waveforms.size
if n % nsamples != 0 or n % nchannels != 0:
waveforms = load_text(filename_spk, np.float32)
return process_waveforms(waveforms, nsamples, nchannels)
def read_waveforms(filename_spk, nsamples, nchannels):
waveforms = np.array(load_binary(filename_spk), dtype=np.float32)
n = waveforms.size
if n % nsamples != 0 or n % nchannels != 0:
waveforms = load_text(filename_spk, np.float32)
return process_waveforms(waveforms, nsamples, nchannels)
def read_masks(filename_mask, fetdim):
masks_full = load_text(filename_mask, np.float32, skiprows=1)
return process_masks(masks_full, fetdim)
def read_group_info(filename_groupinfo):
# For each group (absolute indexing): color index, and name
group_info = load_text(filename_groupinfo, str, delimiter='\t')
return process_group_info(group_info)
def read_cluster_info(filename_acluinfo):
# For each cluster (absolute indexing): cluster index, color index,
# and group index
cluster_info = load_text(filename_acluinfo, np.int32)
return process_cluster_info(cluster_info)
def read_res(filename_res, freq=None):
res = load_text(filename_res, np.int32)
return process_res(res, freq)
def read_clusters(filename_clu):
clusters = load_text(filename_clu, np.int32)
return process_clusters(clusters)
def read_clusters(filename_clu):
clusters = load_text(filename_clu, np.int32)
return process_clusters(clusters)
def testjson(request):
text = tools.load_text("wordgap/data/test.txt")
#ex = wordex.create_ex(text, pos='v', fast=True)
ex = prepex.create_prepex(text)
return HttpResponse(simplejson.dumps(ex), mimetype='application/json')
def read_masks(filename_mask, fetdim):
masks_full = load_text(filename_mask, np.float32, skiprows=1)
return process_masks(masks_full, fetdim)
def read_group_info(filename_groupinfo):
# For each group (absolute indexing): color index, and name
group_info = load_text(filename_groupinfo, str, delimiter='\t')
return process_group_info(group_info)
def read_cluster_info(filename_acluinfo):
# For each cluster (absolute indexing): cluster index, color index,
# and group index
cluster_info = load_text(filename_acluinfo, np.int32)
return process_cluster_info(cluster_info)
def read_res(filename_res, freq=None):
res = load_text(filename_res, np.int32)
return process_res(res, freq)
