def get_context_data(self, **kwargs):
context = super(BioactiveSearchFilterMixin, self).get_context_data(**kwargs)
context.update({
'compound_search': BioactiveSearchForm(),
'protein_search': ProteinSearchForm(),
})
return context
def get_context_data(self, **kwargs):
context = super(MechanismListView, self).get_context_data(**kwargs)
context.update({
'filter_form': ClassficationChoiceForm,
'is_filtered': self.is_filtered,
'compound_search': BioactiveSearchForm(),
'protein_search': ProteinSearchForm(),
})
selected_mechanisms = self.request.GET.getlist('selected_mechanisms')
if selected_mechanisms:
context.update({
'choice_form': ChemDataChoiceSubmitForm,
'data_display': 'true',
})
id_list = [int(a) for a in selected_mechanisms if a]
if self.request.GET.get('mean_data'):
averages = Activity.bioactives_data_stats(id_list)
for chem_prop, val in averages.items():
plot = self.make_plot(val, chem_prop, 'mean')
if plot:
script, div = components(plot, CDN)
context['plot_script' + '_' + chem_prop] = script
context['plot_div' + '_' + chem_prop] = div
stats_arrays = Activity.bioactives_data_stats(id_list,
std_dev=True)
sds = {}
for cp in chemical_properties_label_map.keys():
sds[cp] = [(a[0], a[1][cp].std()) for a in stats_arrays]
for chem_prop, val in sds.items():
plot = self.make_plot(val, chem_prop, 'std dev in')
if plot:
script, div = components(plot, CDN)
context['sd_plot_script' + '_' + chem_prop] = script
context['sd_plot_div' + '_' + chem_prop] = div
return context
def get_context_data(self, **kwargs):
context = super(UserCompoundSourceListView,
self).get_context_data(**kwargs)
context.update({
'form':
self.form_class(),
'upload_form':
UserSourceCsvUploadForm(),
'compound':
self.compound,
'compound_search':
OdorantSearchForm()
if isinstance(self.compound, Odorant) else BioactiveSearchForm()
})
if self.user_compound:
user_cpd_model = 'user_odorant' if isinstance(
self.compound, Odorant) else 'user_bioactive'
cs_kwargs = {
'source__isnull': False,
user_cpd_model: self.user_compound,
}
context.update({
'rel_sources_list':
CompoundSource.objects.filter(**cs_kwargs)
})
return context
def get_context_data(self, **kwargs):
context = super(CompoundSourceListView,
self).get_context_data(**kwargs)
context.update({
'form':
self.form_class(width=200),
'compound':
self.compound,
'compound_search':
OdorantSearchForm()
if isinstance(self.compound, Odorant) else BioactiveSearchForm()
})
return context
def get_context_data(self, **kwargs):
context = super(LiteratureRefsView, self).get_context_data(**kwargs)
context['body_systems'] = Activity.classified_actions_mechs()
if self.model == Activity:
self.mechanism_context(context)
else:
context.update({
'user_literature':
self.records[0],
'literature':
self.records[1],
'compound':
self.compound,
'compound_search':
OdorantSearchForm()
if self.model == Odorant else BioactiveSearchForm(),
})
return context
def mechanism_context(self, context):
mechanism = get_object_or_404(self.model, pk=self.kwargs.get('pk'))
if not mechanism.name:
raise Http404
split_name = mechanism.name.split()
query = split_name[0]
for item in split_name[1:]:
if item != 'and':
query += '%5b%5d+AND+{}'.format(item)
lit_data = self.get_mech_literature(split_name, query)
context.update({
'mechanism':
True,
'literature':
lit_data,
'compound':
'Recent literature: {}'.format(mechanism.name),
'compound_search':
BioactiveSearchForm(),
})
return context
def get_context_data(self, **kwargs):
context = super(ActivityProteinListView,
self).get_context_data(**kwargs)
if self.action_id:
mechanisms = Activity.objects.mechanisms().filter(
action_id=self.action_id)
proteins = Enzyme.objects.filter(mechanism__in=mechanisms)
context['page_header'] = 'Drug action: {}'.format(
self.kwargs['action_name'].replace('-', ' '))
if not proteins.exists():
messages.info(self.request, 'No proteins matched the query')
proteins = Enzyme.objects.exclude(notes__isnull=True)
else:
proteins = self.process_search_query(self.search_term)
context.update({
'results_label':
' {} drug targets'.format(self.results_label)
if self.results_label else None,
'page_header':
'Protein search query: {}'.format(self.search_term)
})
context.update({
'body_systems':
Activity.classified_actions_mechs(),
'drug_actions':
Activity.objects.actions().order_by('name'),
'search_form':
ProteinSearchForm(),
'compound_search':
BioactiveSearchForm(),
'proteins':
proteins.exists(),
'proteins_json':
json.dumps([{
'citation': a['citation'],
'notes': a['notes'],
'pdb_number': a['pdb_number']
} for a in proteins.values('pdb_number', 'notes', 'citation')]),
})
return context