def test_regulatory_graph_layout_remains() -> None:
"""
Testing if the new graph gets the correct layout of the old graph.
Returns:
None
Raises:
AssertionError: If the node coordinates of the new graph differ from expected coordinates.
"""
book = ExcelBook(PHEROMONE_XLS)
reg_graph = RegulatoryGraph(book.rxncon_system)
gml_system = XGMML(reg_graph.to_graph(), "pheromone_layout")
mapped_layout = map_layout2xgmml(gml_system.to_string(), PHEROMONE_XGMML)
xmldoc_no_layout = minidom.parseString(mapped_layout)
xmldoc_no_layout_info = _get_labels_and_coordinates_dict(xmldoc_no_layout)
xmldoc_expected_layout = minidom.parse(PHEROMONE_XGMML)
xmldoc_expected_layout_info = _get_labels_and_coordinates_dict(
xmldoc_expected_layout)
assert all(xmldoc_no_layout_info[no_layout_node] ==
xmldoc_expected_layout_info[no_layout_node]
for no_layout_node in xmldoc_no_layout_info)
assert all(xmldoc_no_layout_info[expected_layout_node] ==
xmldoc_expected_layout_info[expected_layout_node]
for expected_layout_node in xmldoc_expected_layout_info)
def write_bngl(excel_filename: str, base_name=None):
if not base_name:
base_name = os.path.splitext(os.path.basename(excel_filename))[0]
base_path = os.path.dirname(excel_filename)
bngl_model_filename = os.path.join(base_path, '{0}.bngl'.format(base_name))
print('Reading in Excel file [{}] ...'.format(excel_filename))
excel_book = ExcelBook(excel_filename)
rxncon_system = excel_book.rxncon_system
print(
'Constructed rxncon system: [{} reactions], [{} contingencies]'.format(
len(rxncon_system.reactions), len(rxncon_system.contingencies)))
print('Generating BNGL output ...')
rbm = rule_based_model_from_rxncon(rxncon_system)
print(
'Constructed rule-based model: [{} molecule types], [{} rules], [{} observables]'
.format(len(rbm.mol_defs), len(rbm.rules), len(rbm.observables)))
model_str = bngl_from_rule_based_model(rbm)
print('Writing BNGL model file [{}] ...'.format(bngl_model_filename))
with open(bngl_model_filename, mode='w') as f:
f.write(model_str)
def file_detail(request, id, compare_dict=None):
instance = File.objects.get(id=id)
slug = File.objects.filter(id=id).values("slug")
project_files = File.objects.filter(slug=slug).order_by("-updated")
# if instance.rxncon_system:
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=id, project_type="File")
# rxncon_system = pickle.loads(pickled_rxncon_system.pickled_system)
# else:
# rxncon_system = None
book = ExcelBook(instance.get_absolute_path())
rxncon_system = book.rxncon_system
context_data = {
"project_files": project_files,
"title": instance.project_name,
"instance": instance,
"loaded": instance.loaded,
}
if rxncon_system:
context_data["nr_reactions"] = len(rxncon_system.reactions)
context_data["nr_contingencies"] = len(rxncon_system.contingencies)
if compare_dict:
context_data.update(compare_dict)
return render(request, "file_detail.html", context_data)
def quick_compare(request, id):
loaded = File.objects.filter(loaded=True)
if not loaded:
# Quick
loaded = Quick.objects.filter(loaded=True)[0]
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=loaded[0].id, project_type="Quick")
book = RxnconQuick(loaded.quick_input)
else:
# File
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=loaded[0].id, project_type="File")
loaded = loaded[0]
book = ExcelBook(loaded.get_absolute_path())
# loaded_rxncon_system = pickle.loads(pickled_rxncon_system.pickled_system)
loaded_rxncon_system = book.rxncon_system
differences = compare_systems(request,
id,
loaded_rxncon_system,
called_from="Quick")
compare_dict = {
"compare_nr_reactions": len(loaded_rxncon_system.reactions),
"compare_nr_contingencies": len(loaded_rxncon_system.contingencies),
"nr_different_reactions": differences["rxns"],
"nr_different_contingencies": differences["cnts"],
}
return quick_detail(request, id, compare_dict)
def test_shuffled_columns() -> None:
rxncon_system = ExcelBook(SHUFFLED_COLUMNS_XLS).rxncon_system
expected_reactions = ['A_[x]_ppi+_B_[y]', 'A_[x]_ppi-_B_[y]', 'C_p+_A_[(z)]']
for rxn in expected_reactions:
assert reaction_from_str(rxn) in rxncon_system.reactions
def test_missing_unnecessary_sheet() -> None:
rxncon_system = ExcelBook(MISSING_UNNECESSARY_SHEET_XLS).rxncon_system
expected_reactions = ['A_[x]_ppi+_B_[y]', 'A_[x]_ppi-_B_[y]', 'C_p+_A_[(z)]']
for rxn in expected_reactions:
assert reaction_from_str(rxn) in rxncon_system.reactions
def create_rxncon_system(request, system_type, system_id):
if system_type == "File":
system = File.objects.filter(id=system_id)[0]
book = ExcelBook(system.get_absolute_path())
else:
system = Quick.objects.filter(id=system_id)[0]
book = RxnconQuick(system.quick_input)
return book.rxncon_system
def write_xgmml(excel_filename: str, output=None, layout_template_file=None):
"""
creating the xgmml file from an excel input and writing it into a new file.
Args:
excel_filename: Name of the excel input file.
output: Name of the new output.
layout_template_file: Name of the layout template file.
Returns:
None
"""
if not output:
output = os.path.splitext(os.path.basename(excel_filename))[0]
base_path = os.path.dirname(excel_filename)
suffix = '_srg'
if not output.endswith('.xgmml'):
output = '{0}{1}.xgmml'.format(output, suffix)
else:
base_name = output.split('.xgmml')[0]
output = "{0}{1}.{2}".format(base_name, suffix, 'xgmml')
graph_filename = os.path.join(base_path, '{0}'.format(output))
print('graph_filename: ', graph_filename)
_file_path_existence(graph_filename)
print('Reading in Excel file [{}] ...'.format(excel_filename))
excel_book = ExcelBook(excel_filename)
rxncon_system = excel_book.rxncon_system
print(
'Constructed rxncon system: [{} reactions], [{} contingencies]'.format(
len(rxncon_system.reactions), len(rxncon_system.contingencies)))
print('Generating reaction species graph output...')
reg_system = SpeciesReactionGraph(rxncon_system)
graph = reg_system.to_graph()
if layout_template_file:
print('Writing layout information from [{0}] to graph file [{1}] ...'.
format(layout_template_file, graph_filename))
gml_system = XGMML(graph, "{}".format(output))
graph = map_layout2xgmml(gml_system.to_string(), layout_template_file)
print('Writing reaction species graph file [{}] ...'.format(
graph_filename))
with open(graph_filename, "w") as graph_handle:
graph_handle.write(graph)
else:
print('Writing reaction species graph file [{}] ...'.format(
graph_filename))
gml_system = XGMML(graph, "{}".format(output))
gml_system.to_file(graph_filename)
def test_additional_modifiers() -> None:
with pytest.raises(ValueError):
state_from_str('A_[(x)]-{bladiebla}')
rxncon_system = ExcelBook(ADDITIONAL_MODIFIERS_XLS).rxncon_system
assert str(state_from_str('A_[(x)]-{bladiebla}')) == 'A_[(x)]-{bladiebla}'
initialize_state_modifiers()
with pytest.raises(ValueError):
state_from_str('A_[(x)]-{bladiebla}')
def post(self, request, system_id=None):
self.system_id = system_id
self.request = request
self.form = RuleForm(self.request.POST or None)
if self.form.is_valid():
media_url = settings.MEDIA_URL
media_root = settings.MEDIA_ROOT
loaded = File.objects.filter(loaded=True)
if not loaded:
system_type = "Quick"
system = Quick.objects.filter(id=system_id)[0]
project_name = system.name
book = RxnconQuick(system.quick_input)
else:
system_type = "File"
system = File.objects.filter(id=system_id)[0]
project_name = system.project_name
book = ExcelBook(system.get_absolute_path())
bngl_model_filename = system.slug + "_model.bngl"
model_path = os.path.join(media_root, system.slug, "rule_based", bngl_model_filename)
if not check_filepath(request, model_path, system, media_root):
if system_type == "Quick":
return quick_detail(request, system_id)
else:
return file_detail(request, system_id)
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=system_id, project_type=system_type)
# rxncon_system = pickle.loads(pickled_rxncon_system.pickled_system)
rxncon_system = book.rxncon_system
rbm = rule_based_model_from_rxncon(rxncon_system)
model_str = bngl_from_rule_based_model(rbm)
if not os.path.exists(os.path.join(media_root, system.slug, "rule_based")):
os.mkdir(os.path.join(media_root, system.slug, "rule_based"))
with open(model_path, mode='w') as f:
f.write(model_str)
r = Rule_based_from_rxnconsys(project_name=project_name, model_path=model_path,
comment=request.POST.get('comment'))
r.save()
messages.info(request, "BoolNet files for project '" + r.project_name + "' successfully created.")
if system_type == "Quick":
Quick.objects.filter(id=system_id).update(rule_based_model=r)
return quick_detail(request, system_id)
else:
File.objects.filter(id=system_id).update(rule_based_model=r)
return file_detail(request, system_id)
def test_additional_reactions() -> None:
with pytest.raises(SyntaxError):
reaction_from_str('A_smurf+_B_[(r)]')
rxncon_system = ExcelBook(ADDITIONAL_REACTIONS_XLS).rxncon_system
rxn = reaction_from_str('A_smurf+_B_[(r)]')
assert rxn.produced_states == [state_from_str('B_[(r)]-{smurf}')]
assert rxn.consumed_states == [state_from_str('B_[(r)]-{0}')]
initialize_reaction_defs()
with pytest.raises(SyntaxError):
reaction_from_str('A_smurf+_B_[(r)]')
def write_boolnet(excel_filename: str,
smoothing_strategy: SmoothingStrategy,
knockout_strategy: KnockoutStrategy,
overexpression_strategy: OverexpressionStrategy,
k_plus_strategy: QuantitativeContingencyStrategy,
k_minus_strategy: QuantitativeContingencyStrategy,
base_name: Optional[str] = None):
if not base_name:
base_name = os.path.splitext(os.path.basename(excel_filename))[0]
base_path = os.path.dirname(excel_filename)
boolnet_model_filename = os.path.join(base_path,
'{0}.boolnet'.format(base_name))
boolnet_symbol_filename = os.path.join(base_path,
'{0}_symbols.csv'.format(base_name))
boolnet_initial_val_filename = os.path.join(
base_path, '{0}_initial_vals.csv'.format(base_name))
print('Reading in Excel file [{}] ...'.format(excel_filename))
excel_book = ExcelBook(excel_filename)
rxncon_system = excel_book.rxncon_system
print(
'Constructed rxncon system: [{} reactions], [{} contingencies]'.format(
len(rxncon_system.reactions), len(rxncon_system.contingencies)))
print('Generating BoolNet output using smoothing strategy [{}] ...'.format(
smoothing_strategy.name))
model_str, symbol_str, initial_val_str = boolnet_strs_from_rxncon(
rxncon_system, smoothing_strategy, knockout_strategy,
overexpression_strategy, k_plus_strategy, k_minus_strategy)
print('Writing BoolNet model file [{}] ...'.format(boolnet_model_filename))
with open(boolnet_model_filename, mode='w') as f:
f.write(model_str)
print(
'Writing BoolNet symbol file [{}] ...'.format(boolnet_symbol_filename))
with open(boolnet_symbol_filename, mode='w') as f:
f.write(symbol_str)
print('Writing BoolNet initial value file [{}] ...'.format(
boolnet_initial_val_filename))
with open(boolnet_initial_val_filename, mode='w') as f:
f.write(initial_val_str)
def regGraphFile(request, system_id=None):
form = regGraphFileForm(request.POST or None)
if form.is_valid():
media_url = settings.MEDIA_URL
media_root = settings.MEDIA_ROOT
system = File.objects.get(id=system_id)
graph_file_name = system.slug + "_" + system.get_filename().split(
".")[0] + "_regGraph.xgmml"
graph_file_path = os.path.join(media_root, system.slug, "graphs",
graph_file_name)
if not check_filepath(request, graph_file_path, system, media_root):
return file_detail(request, system_id)
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=system_id, project_type="File")
# rxncon_system = pickle.loads(pickled_rxncon_system.pickled_system)
book = ExcelBook(system.get_absolute_path())
rxncon_system = book.rxncon_system
graph = regulatory_graph.RegulatoryGraph(rxncon_system).to_graph()
xgmml_graph = graphML.XGMML(graph, system.slug)
graph_file = xgmml_graph.to_file(graph_file_path)
graph_string = xgmml_graph.to_string()
if request.FILES.get('template'):
graph_string = apply_template_layout(request, graph_file_path,
graph_string)
g = Graph_from_File(project_name=system.project_name,
graph_file=graph_file_path,
graph_string=graph_string,
comment=request.POST.get('comment'))
g.save()
File.objects.filter(id=system_id).update(reg_graph=g)
messages.info(
request, "Regulatory graph for project '" + g.project_name +
"' successfully created.")
return file_detail(request, system_id)
def extract_modules(excel_filename: str,
output=None,
modules=[],
min_quality=0):
"""
Extracts modules from an excel input, adds any reactions necessary to satisfy said contingency,
and then writes ouput to a new file
Args:
excel_filename: Name of the excel input file.
output: Name of the new output.
modules: Comma-separated list of modules to be extracted
min_quality: Minimum quality for a line to be kept
"""
logger.debug("modules: {}".format(modules))
logger.debug("min quality: {}".format(min_quality))
if not output:
output = os.path.dirname(excel_filename) + 'modules.xlsx'
if not output.endswith('.xlsx'):
output += '.xlsx'
print('Reading in Excel file [{}] ...'.format(excel_filename))
excel_book = ExcelBook(excel_filename)
rxncon_system = excel_book.rxncon_system
print(
'Constructed rxncon system: [{} reactions], [{} contingencies]'.format(
len(rxncon_system.reactions), len(rxncon_system.contingencies)))
### STEP 1: Get all the reactions and contingencies and filter down to only those with module tag + minimum quality
# Get the sheets
con_sheet = excel_book._xlrd_book.sheet_by_name('ContingencyList')
rxn_sheet = excel_book._xlrd_book.sheet_by_name('ReactionList')
# Get module and quality column numbers for reactions
column_rxn_module = None
column_rxn_quality = None
rxn_header_row = list(rxn_sheet.get_rows())[1]
for num, header in enumerate(rxn_header_row):
if header.value == '!Module':
column_rxn_module = num
elif header.value == '!Quality':
column_rxn_quality = num
if column_rxn_module is None:
raise ValueError(
'You must define a !Module column in the ReactionList sheet.')
elif column_rxn_quality is None:
raise ValueError(
'You must define a !Quality column in the ReactionList sheet.')
# Get module and quality column numbers for contingencies
column_con_module = None
column_con_quality = None
con_header_row = list(con_sheet.get_rows())[1]
for num, header in enumerate(con_header_row):
if header.value == '!Module':
column_con_module = num
elif header.value == '!Quality':
column_con_quality = num
if column_con_module is None:
raise ValueError(
'You must define a !Module column in the ContingencyList sheet.')
elif column_con_quality is None:
raise ValueError(
'You must define a !Quality column in the ContingencyList sheet.')
# Filter rxn rows by module tag and min quality
rxn_rows = [row for row in rxn_sheet.get_rows()][2:]
rxn_filtered = []
for num, row in enumerate(rxn_rows):
row_modules = list(
map(str.strip, row[column_rxn_module].value.split(
','))) # Split modules into list and trim whitespace
if row[excel_book._column_reaction_full_name].value.strip(
) == '': # Skip empty rows
continue
if row[column_rxn_quality].value == '': # If quality missing, assume quality = 0
row_quality = 0
else:
try: # Try and parse quality to an int
row_quality = int(row[column_rxn_quality].value)
except ValueError:
raise TypeError(
'Reaction {}\'s quality must be an int.'.format(
row[excel_book._column_reaction_full_name].value))
if row_quality < min_quality: # If less than minimum quality skip row
logger.debug(
'Skipping reaction row {} (reaction quality: {}, min quality: {})'
.format(num, row_quality, min_quality))
continue
if not modules == [] and not any(
item in row_modules for item in
modules): # If row module isnt in modules list, skip row
logger.debug(
'Skipping reaction row {} (module not present)'.format(num))
continue
else:
rxn_filtered.append({
'row_num':
num,
'name':
row[excel_book._column_reaction_full_name].value
})
# Filter rxn rows by module tag and min quality
con_rows = [row for row in con_sheet.get_rows()][2:]
con_filtered = []
for num, row in enumerate(con_rows):
row_modules = list(
map(str.strip, row[column_con_module].value.split(
','))) # Split modules into list and trim whitespace
if row[excel_book._column_contingency_target].value.strip(
) == '': # Skip empty rows
continue
if row[column_con_quality].value == '': # If quality missing, assume quality = 0
row_quality = 0
else:
try: # Try and parse quality to an int
row_quality = int(row[column_con_quality].value)
except ValueError:
raise TypeError(
'Contingency {}\'s quality must be an int.'.format(num))
if row_quality < min_quality: # If less than minimum quality skip row
logger.debug(
'Skipping contingency row {} (reaction quality: {}, min quality: {})'
.format(num, row_quality, min_quality))
continue
if not modules == [] and not any(
item in row_modules for item in
modules): # If row module isnt in modules list, skip row
logger.debug(
'Skipping contingency row {} (module not present)'.format(num))
continue
else:
con_filtered.append({
'row_num':
num,
'target':
row[excel_book._column_contingency_target].value.strip(),
'modifier':
row[excel_book._column_contingency_modifier].value.strip(),
'type':
row[excel_book._column_contingency_type].value.strip()
})
### STEP 1.5: Make sure boolean contingencies have inputs; if not, raise an error
boolean_modifiers = [
con['modifier'] for con in con_filtered
if re.match(BOOLEAN_CONTINGENCY_REGEX, con['modifier'])
]
boolean_targets = [
con['modifier'] for con in con_filtered
if re.match(BOOLEAN_CONTINGENCY_REGEX, con['modifier'])
]
for modifier in boolean_modifiers:
if not modifier in boolean_targets:
raise ValueError(
'Boolean gate {} has no inputs in filtered contingencies'.
format(modifier))
### STEP 2 (New method): Map modifiers to rxncon states
required_components = []
for con in con_filtered:
con['modifier'] = re.sub('#.*', '', con['modifier'])
if re.match(BOOLEAN_CONTINGENCY_REGEX, con['modifier']
): # If contingency modifier is a boolean state, skip it
con['modifier_states'] = []
continue
orig_modifier_state = state_from_str(
con['modifier']) # Get the state based on the string
modifier_states = [
state for state in rxncon_system.states
if state.is_subset_of(orig_modifier_state)
] # Find the states in the system that state refers to
if not modifier_states:
raise ValueError(
'Could not match contingency {} to a state in the rxncon system'
.format(con['modifier']))
con['modifier_states'] = modifier_states
for state in modifier_states:
required_components.extend(state.components)
### STEP 3 (New method): For each filtered contingency (ie a state), add reaction(s) that produce(s) state to list (also add target reactions)
def unsplit_bidirectional_reaction_str(rxn_str: str) -> str:
for verb in BIDIRECTIONAL_REACTIONS:
if ('_{}+_'.format(verb).lower() in rxn_str.lower()
or '_{}-_'.format(verb).lower() in rxn_str.lower()
): # If reaction is in format _verb+_ or _verb-_
new_rxn_str = re.sub('(?i)_{}._'.format(verb),
'_{}_'.format(verb),
rxn_str) # Replace with _verb_
return new_rxn_str
return rxn_str
required_components = list(set(
required_components)) # Make sure there are no duplicate components
required_reactions = []
for con in con_filtered:
con_reactions = [
] # List to store reactions producing/synthesizing contingency reactions
con_required_reactions = [
] # List to store which reactions will be added to satisfy contingency
# If target not a global state or boolean node (i.e. target is a reaction), add it to list of required reactions
if not (re.match(BOOLEAN_CONTINGENCY_REGEX, con['target'])
or re.match(GLOBAL_STATE_REGEX, con['target'])):
required_reactions.append(
unsplit_bidirectional_reaction_str(con['target']))
for state in con[
'modifier_states']: # For each state contingency modifier matched to
for reaction in rxncon_system.reactions:
if (any([
produced_state.is_subset_of(state)
for produced_state in reaction.produced_states
]) or # If a reaction produces the state
any([
synthesised_state.is_subset_of(state) for
synthesised_state in reaction.synthesised_states
])): # or synthesizes the state
con_reactions.append(
reaction
) # Add it to the list of reactions for the contingency
# Try and find if reaction producing state already in filtered reactions
for reaction in con_reactions:
rxn_name = unsplit_bidirectional_reaction_str(
reaction.name
) # Turn bidirectional reactions like ppi+ or ppi- into ppi
rxn_name_no_domains = re.sub(
r'_\[.*?\]', '',
rxn_name) # Also check name of reaction without domains
if [
filtered_reaction for filtered_reaction in rxn_filtered
if (filtered_reaction['name'] == rxn_name
or filtered_reaction['name'] == rxn_name_no_domains)
]:
con_required_reactions.append(rxn_name)
# If an already filtered reaction wasn't found, first try adding reaction involving only required components
if not con_required_reactions:
for reaction in con_reactions:
rxn_name = unsplit_bidirectional_reaction_str(
reaction.name
) # Turn bidirectional reactions like ppi+ or ppi- into ppi
if all(
component in required_components
for component in reaction.components
): # Check that all reaction components are in required_components
logger.warning(
'Adding reaction {} to satisfy contingency {} {} {}'.
format(rxn_name, con['target'], con['type'],
con['modifier']))
con_required_reactions.append(rxn_name)
# If a reaction still wasn't found, add all reactions producing the contingency modifier
if not con_required_reactions:
for reaction in con_reactions:
rxn_name = unsplit_bidirectional_reaction_str(reaction.name)
logger.warning(
'Adding reaction {} to satisfy contingency {} {} {}'.
format(rxn_name, con['target'], con['type'],
con['modifier']))
con_required_reactions.append(rxn_name)
required_reactions.extend(con_required_reactions)
### STEP 4: Check if required reactions already in rxn_filtered and add them if missing
all_rxn_names = rxn_sheet.col_values(
excel_book._column_reaction_full_name)[
2:] # Get list of all reaction names
rxn_filtered_names = [d['name'] for d in rxn_filtered]
required_reactions = list(
set(required_reactions)) # Make sure there are no duplicate reactions
added_reactions = []
for required_rxn_name in required_reactions:
# Check if reaction exists in rxn_filtered and skip it if it does
required_rxn_name_no_domains = re.sub(
r'_\[.*?\]', '',
required_rxn_name) # Also check name of reaction without domains
if required_rxn_name in rxn_filtered_names or required_rxn_name_no_domains in rxn_filtered_names:
continue
# If node not in rxn_filtered, try and find the matching reaction and add it to rxn_filtered
for num, rxn_name in enumerate(all_rxn_names):
if required_rxn_name == rxn_name or required_rxn_name_no_domains == rxn_name:
logger.warning(
'Added required reaction {} to filtered reactions.'.format(
rxn_name))
added_reactions.append({'name': rxn_name, 'row_num': num})
# If still not found, try stripping domains from both sides
for num, rxn_name in enumerate(all_rxn_names):
if required_rxn_name_no_domains == re.sub(r'_\[.*?\]', '',
rxn_name):
logger.warning(
'Added required reaction {} to filtered reactions.'.format(
rxn_name))
added_reactions.append({'name': rxn_name, 'row_num': num})
if not added_reactions:
raise ValueError(
'Unable to find reaction {}'.format(required_rxn_name))
rxn_filtered.extend(added_reactions)
### STEP 5: Write updated lists to excel file. This has to be done with openpyxl as xlrd/xlwt don't really support xlsx
# NOTE: openpyxl is 1-indexed, not 0-indexed like xlrd
wb = load_workbook(filename=excel_filename, data_only=True)
rxn_open_sheet = wb['ReactionList']
con_open_sheet = wb['ContingencyList']
# Delete the old unfiltered rows. This is more efficient than the delete_rows method
for row in rxn_open_sheet.iter_rows(min_row=3,
max_row=(3 + len(rxn_rows))):
for col in range(0, 12):
row[col].value = None
for row in con_open_sheet.iter_rows(min_row=3,
max_row=(3 + len(con_rows))):
for col in range(0, 8):
row[col].value = None
# Add the filtered rows to workbook
rxn_filtered_row_nums = [d['row_num'] for d in rxn_filtered]
for row_num, filtered_row_num in enumerate(rxn_filtered_row_nums, 3):
for col_num, val in enumerate(
rxn_sheet.row_values(filtered_row_num + 2), 1):
rxn_open_sheet.cell(row_num, col_num).value = val
con_filtered_row_nums = [d['row_num'] for d in con_filtered]
for row_num, filtered_row_num in enumerate(con_filtered_row_nums, 3):
for col_num, val in enumerate(
con_sheet.row_values(filtered_row_num + 2), 1):
con_open_sheet.cell(row_num, col_num).value = val
# Write to file
wb.save(output)
print('Wrote filtered rxncon file to {}'.format(output))
def post(self, request, system_id=None):
self.system_id = system_id
self.request = request
self.form = reaGraphFileForm(self.request.POST or None)
if self.form.is_valid():
media_url = settings.MEDIA_URL
media_root = settings.MEDIA_ROOT
loaded = File.objects.filter(loaded=True)
if not loaded:
system_type = "Quick"
system = Quick.objects.filter(id=system_id)[0]
project_name = system.name
book = RxnconQuick(system.quick_input)
else:
system_type = "File"
system = File.objects.filter(id=system_id)[0]
project_name = system.project_name
book = ExcelBook(system.get_absolute_path())
graph_file_name = system.slug + "_" + system.get_filename().split(
".")[0] + "_sReaGraph.xgmml"
graph_file_path = os.path.join(media_root, system.slug, "graphs",
graph_file_name)
if not check_filepath(request, graph_file_path, system,
media_root):
if system_type == "Quick":
return quick_detail(request, system_id)
else:
return file_detail(request, system_id)
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=system_id, project_type=system_type)
# rxncon_system = pickle.loads(pickled_rxncon_system.pickled_system)
rxncon_system = book.rxncon_system
graph = regulatory_graph.SpeciesReactionGraph(
rxncon_system=rxncon_system).to_graph()
xgmml_graph = graphML.XGMML(graph, system.slug)
graph_file = xgmml_graph.to_file(graph_file_path)
graph_string = xgmml_graph.to_string()
if request.FILES.get('template'):
graph_string = apply_template_layout(request, graph_file_path,
graph_string)
g = Graph_from_File(project_name=project_name,
graph_file=graph_file_path,
graph_string=graph_string,
comment=request.POST.get('comment'))
g.save()
messages.info(
request, "Species reaction graph for project '" +
g.project_name + "' successfully created.")
if system_type == "Quick":
Quick.objects.filter(id=system_id).update(sRea_graph=g)
return quick_detail(request, system_id)
else:
File.objects.filter(id=system_id).update(sRea_graph=g)
return file_detail(request, system_id)
def post(self, request, system_id=None):
self.system_id = system_id
self.request = request
self.form = BoolForm(self.request.POST or None)
if self.form.is_valid():
media_url = settings.MEDIA_URL
media_root = settings.MEDIA_ROOT
loaded = File.objects.filter(loaded=True)
if not loaded:
system_type = "Quick"
system = Quick.objects.filter(id=system_id)[0]
project_name = system.name
book = RxnconQuick(system.quick_input)
else:
system_type = "File"
system = File.objects.filter(id=system_id)[0]
project_name = system.project_name
book = ExcelBook(system.get_absolute_path())
boolnet_model_filename = system.slug + "_model.boolnet"
boolnet_symbol_filename = system.slug + "_symbols.csv"
boolnet_initial_val_filename = system.slug + "_initial_vals.csv"
model_path = os.path.join(media_root, system.slug, "boolnet", boolnet_model_filename)
symbol_path = os.path.join(media_root, system.slug, "boolnet", boolnet_symbol_filename)
init_path = os.path.join(media_root, system.slug, "boolnet", boolnet_initial_val_filename)
for path in [model_path, symbol_path, init_path]:
if not check_filepath(request, path, system, media_root):
if system_type == "Quick":
return quick_detail(request, system_id)
else:
return file_detail(request, system_id)
# pickled_rxncon_system = Rxncon_system.objects.get(project_id=system_id, project_type=system_type)
# rxncon_system = pickle.loads(pickled_rxncon_system.pickled_system)
rxncon_system = book.rxncon_system
smoothing = SmoothingStrategy(request.POST.get('smoothing'))
knockout = KnockoutStrategy(request.POST.get('knockout'))
overexpr = OverexpressionStrategy(request.POST.get('overexpr'))
k_plus = QuantitativeContingencyStrategy(request.POST.get('k_plus'))
k_minus = QuantitativeContingencyStrategy(request.POST.get('k_minus'))
model_str, symbol_str, initial_val_str = boolnet_strs_from_rxncon(rxncon_system,
smoothing_strategy=smoothing,
knockout_strategy=knockout,
overexpression_strategy=overexpr,
k_plus_strategy=k_plus,
k_minus_strategy=k_minus)
if not os.path.exists(os.path.join(media_root, system.slug, "boolnet")):
os.mkdir(os.path.join(media_root, system.slug, "boolnet"))
with open(model_path, mode='w') as f:
f.write(model_str)
with open(symbol_path, mode='w') as f:
f.write(symbol_str)
with open(init_path, mode='w') as f:
f.write(initial_val_str)
b = Bool_from_rxnconsys(project_name=project_name, model_path=model_path, symbol_path=symbol_path,
init_path=init_path,
comment=request.POST.get('comment'))
b.save()
messages.info(request, "BoolNet files for project '" + b.project_name + "' successfully created.")
if system_type == "Quick":
Quick.objects.filter(id=system_id).update(boolean_model=b)
return quick_detail(request, system_id)
else:
File.objects.filter(id=system_id).update(boolean_model=b)
return file_detail(request, system_id)
def test_missing_necessary_sheet() -> None:
with pytest.raises(SyntaxError):
ExcelBook(MISSING_NECESSARY_SHEET_XLS)
def write_reaction_mapping(excel_filename: str, output=None):
"""
Creates reaction string to full reaction name mapping
Args:
excel_filename: Name of the excel input file.
output: Name of the new output.
Returns:
None
"""
if not output:
output = './reaction_mapping.csv'
print('Reading in Excel file [{}] ...'.format(excel_filename))
excel_book = ExcelBook(excel_filename)
sheet = excel_book._xlrd_book.sheet_by_name(
SHEET_REACTION_LIST) # type: ignore
reaction_rows = [row for row in sheet.get_rows()][DATA_ROW:]
header_row = list(sheet.get_rows())[HEADER_ROW]
rate_column = None
for num, header in enumerate(header_row):
if header.value == '!Rate':
rate_column = num
strs_to_reactions = {}
strs_to_rates = {}
for row in reaction_rows:
if not row[excel_book._column_reaction_full_name].value:
logger.debug('_load_reaction_list: Empty row')
continue
raw_str = row[excel_book._column_reaction_full_name].value
logger.debug('_load_reaction_list: {}'.format(raw_str))
# When a verb such as 'ppi' is encountered, the function 'preprocessed_reaction_strs'
# will split it into 'ppi+' and 'ppi-'.
reaction_strs = split_bidirectional_reaction_str(raw_str)
strs_to_reactions[raw_str] = [
reaction_from_str(x) for x in reaction_strs
]
rate = 1
if rate_column is not None:
rate = row[rate_column].value
if rate == "":
rate = 1
strs_to_rates[raw_str] = rate
with open(output, mode='w') as output_file:
writer = csv.writer(output_file,
delimiter=',',
quotechar='"',
quoting=csv.QUOTE_MINIMAL)
writer.writerow(['original', 'rxnconName', 'rate'])
for key in strs_to_reactions:
if isinstance(strs_to_reactions[key], list):
for x in strs_to_reactions[key]:
writer.writerow([key, x, strs_to_rates[key]])
else:
writer.writerow(
[key, strs_to_reactions[key], strs_to_rates[key]])
