def exec_plot_output_sed_doc(omex_file_path, base_out_path):
archive = CombineArchiveReader().run(in_file=omex_file_path,
out_dir=tmp_dir,
try_reading_as_plain_zip_archive=True)
# determine files to execute
sedml_contents = get_sedml_contents(archive)
report_results = ReportResults()
for i_content, content in enumerate(sedml_contents):
content_filename = os.path.join(tmp_dir, content.location)
for report_filename in glob.glob(
os.path.join(base_out_path, content.location, '*.csv')):
if report_filename.find('__plot__') != -1:
report_id = os.path.splitext(
os.path.basename(report_filename))[0]
# read report from CSV file produced by tellurium
# data_set_df = pd.read_csv(report_filename).transpose()
data_set_df = pd.read_csv(report_filename, header=None).T
data_set_df.columns = data_set_df.iloc[0]
data_set_df.drop(0, inplace=True)
data_set_df.reset_index(inplace=True)
data_set_df.drop('index', axis=1, inplace=True)
# create pseudo-report for ReportWriter
datasets = []
for col in list(data_set_df.columns):
datasets.append(DataSet(id=col, label=col, name=col))
#report.data_sets = datasets
report = Report(id=report_id,
name=report_id,
data_sets=datasets)
data_set_results = DataSetResults()
for col in list(data_set_df.columns):
data_set_results[col] = data_set_df[col].values
# append to data structure of report results
# save file in desired BioSimulators format(s)
export_id = report_id.replace('__plot__', '')
report.id = export_id
rel_path = os.path.join(content.location, report.id)
if len(rel_path.split("./")) > 1:
rel_path = rel_path.split("./")[1]
ReportWriter().run(report,
data_set_results,
base_out_path,
rel_path,
format='h5')
os.rename(report_filename,
report_filename.replace('__plot__', ''))
def exec_plot_output_sed_doc(omex_file_path, base_out_path):
config = Config(VALIDATE_OMEX_MANIFESTS=False)
archive = CombineArchiveReader().run(in_file=omex_file_path,
out_dir=tmp_dir,
config=config)
# determine files to execute
sedml_contents = get_sedml_contents(archive)
report_results = ReportResults()
for i_content, content in enumerate(sedml_contents):
content_filename = os.path.join(tmp_dir, content.location)
for report_filename in glob.glob(
os.path.join(base_out_path, content.location, '*.csv')):
if report_filename.find('__plot__') != -1:
report_id = os.path.splitext(
os.path.basename(report_filename))[0]
# read report from CSV file produced by tellurium
# data_set_df = pd.read_csv(report_filename).transpose()
data_set_df = pd.read_csv(report_filename, header=None).T
datasets = []
for col in data_set_df.columns:
datasets.append(
DataSet(id=data_set_df.loc[0, col],
label=data_set_df.loc[1, col],
name=data_set_df.loc[2, col]))
report = Report(id=report_id,
name=report_id,
data_sets=datasets)
data_set_df.columns = data_set_df.iloc[0]
data_set_df.drop(0, inplace=True)
data_set_df.drop(1, inplace=True)
data_set_df.drop(2, inplace=True)
data_set_df.reset_index(inplace=True)
data_set_df.drop('index', axis=1, inplace=True)
# create pseudo-report for ReportWriter
data_set_results = DataSetResults()
for col in list(data_set_df.columns):
data_set_results[col] = data_set_df[col].to_numpy(
dtype='float64')
# append to data structure of report results
# save file in desired BioSimulators format(s)
export_id = report_id.replace('__plot__', '')
report.id = export_id
rel_path = os.path.join(content.location, report.id)
if len(rel_path.split("./")) > 1:
rel_path = rel_path.split("./")[1]
# print("base: ", base_out_path, file=sys.stdout)
# print("rel: ", rel_path, file=sys.stdout)
ReportWriter().run(report,
data_set_results,
base_out_path,
rel_path,
format='h5',
type=Plot2D)
os.rename(report_filename,
report_filename.replace('__plot__', ''))
else:
print("report : ", report_filename, file=sys.stdout)
report_id = os.path.splitext(
os.path.basename(report_filename))[0]
data_set_df = pd.read_csv(report_filename, header=None).T
datasets = []
for col in data_set_df.columns:
datasets.append(
DataSet(id=data_set_df.loc[0, col],
label=data_set_df.loc[1, col],
name=""))
report = Report(id=report_id,
name=report_id,
data_sets=datasets)
data_set_df.columns = data_set_df.iloc[0] # use ids
data_set_df.drop(0, inplace=True)
data_set_df.drop(1, inplace=True)
data_set_df.drop(2, inplace=True)
data_set_df.reset_index(inplace=True)
data_set_df.drop('index', axis=1, inplace=True)
data_set_results = DataSetResults()
for col in list(data_set_df.columns):
data_set_results[col] = data_set_df[col].to_numpy(
dtype='float64')
rel_path = os.path.join(content.location, report.id)
if len(rel_path.split("./")) > 1:
rel_path = rel_path.split("./")[1]
ReportWriter().run(report,
data_set_results,
base_out_path,
rel_path,
format='h5',
type=Report)