def dataframe_from_rpt(rpt_path, section):
"""
create a dataframe from a section of an RPT file
:param rpt_path:
:param section:
:return: pd.DataFrame
"""
# get list of all section headers in rpt to use as section ending flags
headers = get_rpt_sections_details(rpt_path)
if section not in headers:
warnings.warn(f'{section} section not found in {rpt_path}')
return pd.DataFrame()
# and get the list of columns to use for parsing this section
end_strings = list(headers.keys())
end_strings.append('***********')
start_strings = [section, '-' * 20, '-' * 20]
cols = headers[section]['columns']
# extract the string and read into a dataframe
s = extract_section_of_file(rpt_path, start_strings, end_strings)
df = pd.read_csv(StringIO(s),
header=None,
delim_whitespace=True,
skiprows=[0],
index_col=0,
names=cols)
return df
def headers(self):
"""
Return all section headers and associated column names found in the RPT file.
"""
if self._rpt_section_details is None:
self._rpt_section_details = get_rpt_sections_details(self.path)
return self._rpt_section_details
def test_complete_headers_rpt(test_model_02):
headers = get_rpt_sections_details(test_model_02.rpt.path)
sections_in_rpt = [
'Link Flow Summary', 'Link Flow Summary', 'Subcatchment Summary',
'Cross Section Summary', 'Link Summary'
]
assert (all(section in headers for section in sections_in_rpt))
assert headers['Link Summary']['columns'] == [
'Name', 'FromNode', 'ToNode', 'Type', 'Length', 'SlopePerc',
'Roughness'
]
def dataframe_from_rpt(rpt_path, section, element_id=None):
"""
create a dataframe from a section of an RPT file
:param rpt_path: path to rep file
:param section: title of section to extract
:param element_id: type of element when extracting time series data
:return: pd.DataFrame
"""
# get list of all section headers in rpt to use as section ending flags
headers = get_rpt_sections_details(rpt_path)
if section not in headers:
warnings.warn(f'{section} section not found in {rpt_path}')
return pd.DataFrame()
# handle case for extracting timeseries results
if element_id is not None:
end_strings = ['<<< ']
start_strings = [
section,
f"<<< {section.replace(' Results', '')} {element_id} >>>",
'-' * 20, '-' * 20
]
else:
# and get the list of columns to use for parsing this section
end_strings = list(headers.keys())
end_strings.append('***********')
start_strings = [section, '-'*20, '-'*20]
cols = headers[section]['columns']
# extract the string and read into a dataframe
s = extract_section_of_file(rpt_path, start_strings, end_strings)
df = pd.read_csv(StringIO(s), header=None, delim_whitespace=True, skiprows=[0],
index_col=0, names=cols)
# confirm index name is string
df = df.rename(index=str)
return df