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Hot fix - tud fng issue #290

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Jun 5, 2024
Merged

Hot fix - tud fng issue #290

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42b4464
fixed issue #287
dodu94 May 13, 2024
28787ba
fixes issue #289
dodu94 May 22, 2024
778638b
fix multirun inputs
dodu94 May 23, 2024
55989e8
solve typing error
dodu94 May 23, 2024
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182 changes: 86 additions & 96 deletions jade/expoutput.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
# You should have received a copy of the GNU General Public License
# along with JADE. If not, see <http://www.gnu.org/licenses/>.

from __future__ import annotations
import math
import os
import re
Expand Down Expand Up @@ -168,89 +169,84 @@ def build_atlas(self):
# Remove tmp images
shutil.rmtree(tmp_path)

def _extract_outputs(self):
def _extract_single_output(
self, results_path: os.PathLike, folder: str, lib: str
) -> tuple[pd.DataFrame, str]:
mfile, ofile = self._get_output_files(results_path)
# Parse output
output = MCNPoutput(mfile, ofile)

# need to extract the input in case of multi
if self.multiplerun:
pieces = folder.split("_")
input = pieces[-1]
if input not in self.inputs:
self.inputs.append(input)
self.outputs[input, lib] = output
# Get the meaningful results
self.results[input, lib] = self._processMCNPdata(output)
else:
# just treat it as a special case of multiple run
self.outputs[self.testname, lib] = output
# Get the meaningful results
self.results[self.testname, lib] = self._processMCNPdata(output)
input = self.testname

return output.tallydata, input

def _extract_outputs(self) -> None:
"""
Extract, organize and store the results coming from the MCNP runs
Extract, organize and store the results coming from the different codes
runs

Returns
-------
None.
"""
outputs = {}
results = {}
inputs = []
self.outputs = {}
self.results = {}

# Each output object is processing only one code at the time at the moment
if self.mcnp:
code_tag = "mcnp"
if self.openmc:
print("Experimental comparison not implemented for OpenMC")
return
if self.serpent:
print("Experimental comparison not implemented for Serpent")
return
if self.d1s:
code_tag = "d1s"

# only multiple runs have multiple inputs
if self.multiplerun:
self.inputs = []
else:
self.inputs = [self.testname]

# Iterate on the different libraries results except 'Exp'
for lib, test_path in self.test_path.items():
if lib != EXP_TAG:
if self.multiplerun:
# Results are organized by folder and lib
code_raw_data = {}
for folder in os.listdir(test_path):
# FIX MCNP HARD CODED PATH HERE
if self.mcnp:
results_path = os.path.join(test_path, folder, "mcnp")
pieces = folder.split("_")
# Get zaid
input = pieces[-1]
mfile, ofile = self._get_output_files(results_path)
# Parse output
output = MCNPoutput(mfile, ofile)
outputs[input, lib] = output
code_raw_data[input, lib] = output.tallydata
# self.raw_data[input, lib] = output.tallydata

# Get the meaningful results
results[input, lib] = self._processMCNPdata(output)
if input not in inputs:
inputs.append(input)
if self.openmc:
print(
"Experimental comparison not implemented \
for OpenMC"
)
break
if self.serpent:
print(
"Experimental comparison not implemented \
for Serpent"
)
break
if self.d1s:
results_path = os.path.join(test_path, folder, "d1s")
pieces = folder.split("_")
# Get zaid
input = pieces[-1]
mfile, ofile = self._get_output_files(results_path)
# Parse output
output = MCNPoutput(mfile, ofile)
outputs[input, lib] = output
code_raw_data[input, lib] = output.tallydata
# self.raw_data[input, lib] = output.tallydata

# Get the meaningful results
results[input, lib] = self._processMCNPdata(output)
if input not in inputs:
inputs.append(input)
if self.mcnp:
self.raw_data["mcnp"].update(code_raw_data)
if self.d1s:
self.raw_data["d1s"].update(code_raw_data)
results_path = os.path.join(test_path, folder, code_tag)
tallydata, input = self._extract_single_output(
results_path, folder, lib
)
code_raw_data[input, lib] = tallydata

# Results are organized just by lib
else:
mfile, ofile = self._get_output_files(test_path)
# Parse output
output = MCNPoutput(mfile, ofile)
outputs[self.testname, lib] = output
# Adjourn raw Data
self.raw_data[self.testname, lib] = output.tallydata
# Get the meaningful results
results[self.testname, lib] = self._processMCNPdata(output)

self.outputs = outputs
self.results = results
if inputs:
self.inputs = inputs
else:
self.inputs = [self.testname]
results_path = os.path.join(test_path, code_tag)
tallydata, input = self._extract_single_output(
results_path, None, lib
)
code_raw_data = {(self.testname, lib): tallydata}

# Adjourn raw Data
self.raw_data[code_tag].update(code_raw_data)

def _read_exp_results(self):
"""
Expand Down Expand Up @@ -483,9 +479,7 @@ def _pp_excel_comparison(self):
Responsible for producing excel outputs
"""
# Dump the global C/E table
ex_outpath = os.path.join(
self.excel_path, self.testname + "_CE_tables.xlsx"
)
ex_outpath = os.path.join(self.excel_path, self.testname + "_CE_tables.xlsx")
# Create a Pandas Excel writer using XlsxWriter as the engine.
with pd.ExcelWriter(ex_outpath, engine="xlsxwriter") as writer:
# --- build and dump the C/E table ---
Expand Down Expand Up @@ -673,7 +667,7 @@ def _read_exp_file(self, filepath):
filepath : str
string containing the path to the experimental file to be read
for comparison

"""
return pd.read_csv(filepath, sep=";")

Expand All @@ -684,7 +678,7 @@ def _build_atlas(self, tmp_path, atlas):
"""
Fill the atlas with the customized plots. Creation and saving of the
atlas are handled elsewhere.

Parameters
----------
tmp_path : str
Expand Down Expand Up @@ -753,7 +747,7 @@ def _get_tally_info(self, tally):
tallynum (int): Tally number of the tally being plotted
particle (str): Type of quantity being plotted on the X axis
quant + unit (str): Unit of quantity being plotted on the X axis

"""
tallynum = tally.tallyNumber
particle = tally.particleList[np.where(tally.tallyParticles == 1)[0][0]]
Expand Down Expand Up @@ -786,7 +780,7 @@ def _define_title(self, input, quantity_CE):

def _dump_ce_table(self):
"""
Generates the C/E table and dumps them as an .xlsx file
Generates the C/E table and dumps them as an .xlsx file
"""
final_table = pd.concat(self.tables)
skipcol_global = 0
Expand Down Expand Up @@ -998,7 +992,7 @@ def _parse_data_df(self, data, output, x_axis, tallynum):
x_axis : str
X axis title
tallynum : int
Tally number, used to determine behaviour for protons and
Tally number, used to determine behaviour for protons and
neutrons

Returns
Expand Down Expand Up @@ -1172,7 +1166,7 @@ def _exp_comp_case_check(self, indexes):

def _get_conv_df(self, df):
"""
Adds extra columns to the dataframe containing the maximum and
Adds extra columns to the dataframe containing the maximum and
average errors of the tallies

Parameters
Expand All @@ -1184,9 +1178,9 @@ def _get_conv_df(self, df):
Returns
-------
conv_df: Dataframe
Same as previous dataframe, but with two extra columns containing
Same as previous dataframe, but with two extra columns containing
maximum and average errors

"""
conv_df = pd.DataFrame()
for library in df.index.unique(level="Library").tolist():
Expand All @@ -1203,7 +1197,7 @@ class TiaraFCOutput(TiaraOutput):

def _pp_excel_comparison(self):
"""
Builds dataframe from computational output comparable to experimental
Builds dataframe from computational output comparable to experimental
data and generates the excel comparison
"""

Expand Down Expand Up @@ -1247,9 +1241,7 @@ def _pp_excel_comparison(self):
self._exp_comp_case_check(indexes=indexes)
self.case_tree_df.sort_values(indexes, axis=0, inplace=True)
# Build ExcelWriter object
filepath = os.path.join(
self.excel_path, "Tiara_Fission_Cells_CE_tables.xlsx"
)
filepath = os.path.join(self.excel_path, "Tiara_Fission_Cells_CE_tables.xlsx")
with pd.ExcelWriter(filepath, engine="xlsxwriter") as writer:

# Create 1 worksheet for each energy/material combination
Expand Down Expand Up @@ -1391,7 +1383,7 @@ def _build_atlas(self, tmp_path, atlas):
"""
Fill the atlas with the customized plots. Creation and saving of the
atlas are handled elsewhere.

Parameters
----------
tmp_path : str
Expand Down Expand Up @@ -1549,9 +1541,7 @@ def _pp_excel_comparison(self):
indexes = ["Library", "Shield Material", "Energy", "Shield Thickness"]
self._exp_comp_case_check(indexes=indexes)
# Create ExcelWriter object
filepath = os.path.join(
self.excel_path, "Tiara_Bonner_Spheres_CE_tables.xlsx"
)
filepath = os.path.join(self.excel_path, "Tiara_Bonner_Spheres_CE_tables.xlsx")
with pd.ExcelWriter(filepath, engine="xlsxwriter") as writer:
# Loop over shield material/energy combinations
mat_list = self.case_tree_df.index.unique(level="Shield Material").tolist()
Expand Down Expand Up @@ -1662,7 +1652,7 @@ def _build_atlas(self, tmp_path, atlas):
"""
Fill the atlas with the customized plots. Creation and saving of the
atlas are handled elsewhere.

Parameters
----------
tmp_path : str
Expand Down Expand Up @@ -1822,7 +1812,7 @@ def _build_atlas(self, tmp_path, atlas):
"""
Fill the atlas with the customized plots. Creation and saving of the
atlas are handled elsewhere.

Parameters
----------
tmp_path : str
Expand Down Expand Up @@ -1922,7 +1912,7 @@ def _build_atlas(self, tmp_path, atlas):
"""
Fill the atlas with the customized plots. Creation and saving of the
atlas are handled elsewhere.

Parameters
----------
tmp_path : str
Expand All @@ -1944,14 +1934,14 @@ def _build_atlas(self, tmp_path, atlas):
return atlas

def _plot_tally_group(self, group, tmp_path, atlas):
"""
Plots tallies for a given group of outputs and add to Atlas object
"""
Plots tallies for a given group of outputs and add to Atlas object

Parameters
----------
group : list
list of groups in the experimental benchmark object, outputs are
grouped by material, several tallies for each material/group
list of groups in the experimental benchmark object, outputs are
grouped by material, several tallies for each material/group
tmp_path : str
path to temporary atlas plot folder
atlas : JADE Atlas
Expand All @@ -1960,7 +1950,7 @@ def _plot_tally_group(self, group, tmp_path, atlas):
Returns
-------
atlas : JADE Atlas
adjusted Atlas object
adjusted Atlas object
"""
# Extract 'Tally' and 'Input' values for the current 'Group'
group_data = self.groups.xs(group, level="Group", drop_level=False)
Expand Down
6 changes: 6 additions & 0 deletions jade/output.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -329,8 +329,14 @@ def single_postprocess(self):
except KeyError:
# this means that the column is only one and we have
# two distinct DFs for values and errors
# depending on pandas version, these may be series or
# directly arrays
values = vals_df["Value"]
error = err_df["Error"]
if isinstance(values, pd.Series) or isinstance(values, pd.DataFrame):
values = values.values
if isinstance(error, pd.Series) or isinstance(error, pd.DataFrame):
error = error.values

lib_name = self.session.conf.get_lib_name(self.lib)
lib = {"x": x, "y": values, "err": error, "ylabel": lib_name}
Expand Down