def begin_reply_generate(item, rest_repo, readme_link, sdk_repo, pipeline_url,
assigner_repo):
global issue_object_rg
issue_object_rg = item.issue_object
link_dict = get_links(readme_link)
labels = item.labels
whether_change_readme = readme_comparison(rest_repo, link_dict, labels)
if not whether_change_readme:
reply_content, sdk_link_number = get_reply_and_sdk_number_from_readme(
rest_repo, link_dict, item)
res_run = run_pipeline(issue_link=issue_object_rg.html_url,
sdk_issue_object=sdk_repo.get_pull(
int(sdk_link_number)),
pipeline_url=pipeline_url)
if res_run:
logging.info(f'{issue_object_rg.number} run pipeline successfully')
else:
logging.info(f'{issue_object_rg.number} run pipeline fail')
assigner_issue = assigner_repo.get_issue(number=issue_object_rg.number)
reply_owner(assigner_issue, reply_content)
issue_object_rg.add_to_labels('auto-ask-check')
else:
logging.info('issue {} need config readme'.format(
issue_object_rg.number))
def begin_reply_generate(item, rest_repo, readme_link, pipeline_url):
global issue_object_rg
issue_object_rg = item.issue_object
link_dict = get_links(readme_link)
labels = item.labels
whether_change_readme = readme_comparison(rest_repo, link_dict, labels)
if not whether_change_readme:
res_run = run_pipeline(issue_link=issue_object_rg.html_url,
pipeline_url=pipeline_url,
spec_readme=readme_link
)
if res_run:
logging.info(f'{issue_object_rg.number} run pipeline successfully')
else:
logging.info(f'{issue_object_rg.number} run pipeline fail')
issue_object_rg.add_to_labels(AUTO_ASK_FOR_CHECK)
else:
logging.info('issue {} need config readme'.format(issue_object_rg.number))
if not os.path.exists(path + today):
os.makedirs(path + today)
# =============================================================================
#load model
# =============================================================================
#modelname = "../models/20200716_w_cyto_comm.txt"
modelname = "../models/const_precursors.txt"
with open(modelname, 'r') as myfile:
antimony_model = myfile.read()
# =============================================================================
# run simulations
# =============================================================================
r = te.loada(antimony_model)
cells, cytos = run_pipeline(r)
xlabel = "time post infection (d)"
ylabel = "cells"
xticks = [0, 10, 20, 30, 40, 50, 60]
# =============================================================================
# plot fahey data
# =============================================================================
plt.close("all")
path_data = "../../chronic_infection_model/data_literature/"
fahey_data = "fahey_cell_numbers.csv"
fahey_error = "fahey_error_bars.csv"
df_fahey = pd.read_csv(path_data + fahey_data)