def generate_displayId_from_selection(self, start_paragraph, start_offset, end_offset):
paragraphs = self.lab_experiment.paragraphs()
paragraph_text = intent_parser_utils.get_paragraph_text(paragraphs[start_paragraph])
selection = paragraph_text[start_offset:end_offset + 1]
# Remove leading/trailing space
selection = selection.strip()
return selection, self.sbh.sanitize_name_to_display_id(selection)
def update_experimental_results(self):
# For test documents, replace doc id with corresponding production doc
if self.lab_experiment.document_id() in self._test_doc_id_map:
source_doc_uri = 'https://docs.google.com/document/d/' + self._test_doc_id_map[self.lab_experiment.document_id()]
else:
source_doc_uri = 'https://docs.google.com/document/d/' + self.lab_experiment.document_id()
# Search SBH to get data
target_collection = '%s/user/%s/experiment_test/experiment_test_collection/1' % (self.sbh.get_sbh_url(), self.sbh.get_sbh_collection_user())
exp_collection = self.sbh.query_experiments(self.sbh, target_collection)
data = {}
for exp in exp_collection:
exp_uri = exp['uri']
timestamp = exp['timestamp']
title = exp['title']
request_doc = self.sbh.query_experiment_request(exp_uri)
if source_doc_uri == request_doc:
source_uri = self.sbh.query_experiment_source(exp_uri) # Get the reference to the source document with lab data
data[exp_uri] = {'timestamp' : timestamp, 'agave' : source_uri[0], 'title' : title}
exp_data = []
exp_links = []
for exp in data:
exp_data.append((data[exp]['title'], ' updated on ', data[exp]['timestamp'], ', ', 'Agave link', '\n'))
exp_links.append((exp, '', '', '', data[exp]['agave'], ''))
if exp_data == '':
exp_data = ['No currently run experiments.']
paragraphs = self.lab_experiment.paragraphs()
headerIdx = -1
contentIdx = -1
for pIdx in range(len(paragraphs)):
para_text = intent_parser_utils.get_paragraph_text(paragraphs[pIdx])
if para_text == "Experiment Results\n":
headerIdx = pIdx
elif headerIdx >= 0 and not para_text == '\n':
contentIdx = pIdx
break
if headerIdx >= 0 and contentIdx == -1:
self.logger.error('ERROR: Couldn\'t find a content paragraph index for experiment results!')
experimental_result = {}
experimental_result['action'] = 'updateExperimentResults'
experimental_result['headerIdx'] = headerIdx
experimental_result['contentIdx'] = contentIdx
experimental_result['expData'] = exp_data
experimental_result['expLinks'] = exp_links
return experimental_result
def get_currently_selected_text(testcase, ips, doc_id, doc_content):
"""
Given select start and end dicts from spelling results, retrieve the text from the test document.
"""
spelling_index = ips.client_state_map[doc_id]['spelling_index']
spelling_result = ips.client_state_map[doc_id]['spelling_results'][spelling_index]
select_start = spelling_result['select_start']
select_end = spelling_result['select_end']
if not select_start['paragraph_index'] == select_end['paragraph_index']:
testcase.fail('Selection starting and ending paragraphs differ! Not supported!')
paragraphs = ips.get_paragraphs(doc_content)
paragraph = paragraphs[select_start['paragraph_index']]
para_text = table_utils.get_paragraph_text(paragraph)
return para_text[select_start['cursor_index']:(select_end['cursor_index'] + 1)]
def detect_new_measurement_table(table):
"""
Scan the header row to see if it contains what we expect in a new-style measurements table.
"""
found_replicates = False
found_strain = False
found_measurement_type = False
found_file_type = False
rows = table['table']['tableRows']
headerRow = rows[1]
for cell in headerRow['tableCells']:
cellTxt = intent_parser_utils.get_paragraph_text(
cell['content'][0]['paragraph']).strip()
found_replicates |= cellTxt == intent_parser_constants.HEADER_REPLICATE_VALUE
found_strain |= cellTxt == intent_parser_constants.HEADER_STRAINS_VALUE
found_measurement_type |= cellTxt == intent_parser_constants.HEADER_MEASUREMENT_TYPE_VALUE
found_file_type |= cellTxt == intent_parser_constants.HEADER_FILE_TYPE_VALUE
return found_replicates and found_strain and found_measurement_type and found_file_type
def calculate_samples(self):
doc_tables = self.lab_experiment.tables()
table_ids = []
sample_indices = []
samples_values = []
for tIdx in range(len(doc_tables)):
table = doc_tables[tIdx]
is_new_measurement_table = table_utils.detect_new_measurement_table(table)
if not is_new_measurement_table:
continue
rows = table['tableRows']
headerRow = rows[0]
samples_col = -1
for cell_idx in range(len(headerRow['tableCells'])):
cellTxt = intent_parser_utils.get_paragraph_text(headerRow['tableCells'][cell_idx]['content'][0]['paragraph']).strip()
if cellTxt == intent_parser_constants.COL_HEADER_SAMPLES:
samples_col = cell_idx
samples = []
numCols = len(headerRow['tableCells'])
# Scrape data for each row
for row in rows[1:]:
comp_count = []
is_type_col = False
colIdx = 0
# Process reagents
while colIdx < numCols and not is_type_col:
paragraph_element = headerRow['tableCells'][colIdx]['content'][0]['paragraph']
headerTxt = intent_parser_utils.get_paragraph_text(paragraph_element).strip()
if headerTxt == intent_parser_constants.COL_HEADER_MEASUREMENT_TYPE:
is_type_col = True
else:
cellContent = row['tableCells'][colIdx]['content']
cellTxt = ' '.join([intent_parser_utils.get_paragraph_text(c['paragraph']).strip() for c in cellContent]).strip()
comp_count.append(len(cellTxt.split(sep=',')))
colIdx += 1
# Process the rest of the columns
while colIdx < numCols:
paragraph_element = headerRow['tableCells'][colIdx]['content'][0]['paragraph']
headerTxt = intent_parser_utils.get_paragraph_text(paragraph_element).strip()
# Certain columns don't contain info about samples
if headerTxt == intent_parser_constants.COL_HEADER_MEASUREMENT_TYPE or headerTxt == intent_parser_constants.COL_HEADER_NOTES or headerTxt == intent_parser_constants.COL_HEADER_SAMPLES:
colIdx += 1
continue
cellContent = row['tableCells'][colIdx]['content']
cellTxt = ' '.join([intent_parser_utils.get_paragraph_text(c['paragraph']).strip() for c in cellContent]).strip()
if headerTxt == intent_parser_constants.COL_HEADER_REPLICATE:
comp_count.append(int(cellTxt))
else:
comp_count.append(len(cellTxt.split(sep=',')))
colIdx += 1
samples.append(int(np.prod(comp_count)))
table_ids.append(tIdx)
sample_indices.append(samples_col)
samples_values.append(samples)
samples = {}
samples['action'] = 'calculateSamples'
samples['tableIds'] = table_ids
samples['sampleIndices'] = sample_indices
samples['sampleValues'] = samples_values
return samples