From 3d5ffa6ed49581777a6fbf385ee5c0b0cdf26f97 Mon Sep 17 00:00:00 2001
From: Lars Bilke <lars.bilke@ufz.de>
Date: Thu, 18 Jan 2024 15:29:47 +0100
Subject: [PATCH] [py] ruff fixes in Tests/Data/Parabolic/T/3D_3BHEs_array.
---
.../Parabolic/T/3D_3BHEs_array/bcs_tespy.py | 46 +++++++++---------
.../T/3D_3BHEs_array/bcs_tespy_closedloop.py | 47 +++++++++----------
2 files changed, 45 insertions(+), 48 deletions(-)
diff --git a/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy.py b/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy.py
index fb824f82b09..fe224552508 100644
--- a/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy.py
+++ b/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy.py
@@ -5,19 +5,19 @@
# http://www.opengeosys.org/project/license
###
-import sys
-
-print(sys.version)
import os
+import sys
import numpy as np
+from pandas import read_csv
+from tespy.networks import load_network
try:
import ogs.callbacks as OpenGeoSys
except ModuleNotFoundError:
import OpenGeoSys
-from pandas import read_csv
-from tespy.networks import load_network
+
+print(sys.version)
# User setting ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# parameters
@@ -148,36 +148,34 @@ class BC(OpenGeoSys.BHENetwork):
df.loc[:, "flowrate"] = 0
cur_flowrate = df["flowrate"].tolist()
return (True, True, Tout_val, cur_flowrate)
- else:
- # read Tout_val to dataframe
- for i in range(n_BHE):
- df.loc[df.index[i], "Tout_val"] = Tout_val[i]
- # TESPy solver
- cur_Tin_val, cur_flowrate = get_tespy_results(t)
- # check norm if network achieves the converge
- if_success = False
- pre_Tin_val = Tin_val
- norm = np.linalg.norm(
- abs(np.asarray(pre_Tin_val) - np.asarray(cur_Tin_val))
- )
- if norm < 10e-6:
- if_success = True
- # return to OGS
- return (True, if_success, cur_Tin_val, cur_flowrate)
+
+ # read Tout_val to dataframe
+ for i in range(n_BHE):
+ df.loc[df.index[i], "Tout_val"] = Tout_val[i]
+ # TESPy solver
+ cur_Tin_val, cur_flowrate = get_tespy_results(t)
+ # check norm if network achieves the converge
+ if_success = False
+ pre_Tin_val = Tin_val
+ norm = np.linalg.norm(abs(np.asarray(pre_Tin_val) - np.asarray(cur_Tin_val)))
+ if norm < 10e-6:
+ if_success = True
+ # return to OGS
+ return (True, if_success, cur_Tin_val, cur_flowrate)
# main
# initialize the tespy model of the bhe network
# load path of network model:
# loading the TESPy model
-if ogs_prj_directory != "":
- os.chdir(ogs_prj_directory)
+if ogs_prj_directory != "": # noqa: F821
+ os.chdir(ogs_prj_directory) # noqa: F821
nw = load_network("./pre/tespy_nw")
# set if print the network iteration info
nw.set_attr(iterinfo=False)
# create bhe dataframe of the network system from bhe_network.csv
-df = create_dataframe()
+df = create_dataframe() # noqa: PD901
n_BHE = np.size(df.iloc[:, 0])
# create local variables of the components label and connections label in
diff --git a/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy_closedloop.py b/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy_closedloop.py
index 630700f288a..56aa85fa05d 100644
--- a/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy_closedloop.py
+++ b/Tests/Data/Parabolic/T/3D_3BHEs_array/bcs_tespy_closedloop.py
@@ -6,18 +6,19 @@
###
import sys
-
-print(sys.version)
-import os
+from pathlib import Path
import numpy as np
+from pandas import read_csv
+from tespy.networks import load_network
try:
import ogs.callbacks as OpenGeoSys
except ModuleNotFoundError:
import OpenGeoSys
-from pandas import read_csv
-from tespy.networks import load_network
+
+
+print(sys.version)
# User setting ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# parameters
@@ -151,37 +152,35 @@ class BC(OpenGeoSys.BHENetwork):
df.loc[:, "flowrate"] = 0
cur_flowrate = df["flowrate"].tolist()
return (True, True, Tout_val, cur_flowrate)
- else:
- # read Tout_val to dataframe
- for i in range(n_BHE):
- df.loc[df.index[i], "Tout_val"] = Tout_val[i]
- # TESPy solver
- cur_Tin_val, cur_flowrate = get_tespy_results(t)
- # check norm if network achieves the converge
- if_success = False
- pre_Tin_val = Tin_val
- norm_dx = np.linalg.norm(
- abs(np.asarray(pre_Tin_val) - np.asarray(cur_Tin_val))
- )
- norm_x = np.linalg.norm(np.asarray(cur_Tin_val))
- if norm_dx / norm_x < 1e-6:
- if_success = True
- # return to OGS
- return (True, if_success, cur_Tin_val, cur_flowrate)
+
+ # read Tout_val to dataframe
+ for i in range(n_BHE):
+ df.loc[df.index[i], "Tout_val"] = Tout_val[i]
+ # TESPy solver
+ cur_Tin_val, cur_flowrate = get_tespy_results(t)
+ # check norm if network achieves the converge
+ if_success = False
+ pre_Tin_val = Tin_val
+ norm_dx = np.linalg.norm(abs(np.asarray(pre_Tin_val) - np.asarray(cur_Tin_val)))
+ norm_x = np.linalg.norm(np.asarray(cur_Tin_val))
+ if norm_dx / norm_x < 1e-6:
+ if_success = True
+ # return to OGS
+ return (True, if_success, cur_Tin_val, cur_flowrate)
# main
# initialize the tespy model of the bhe network
# load path of network model:
# loading the TESPy model
-project_dir = os.getcwd()
+project_dir = Path.cwd()
print("Project dir is: ", project_dir)
nw = load_network("./pre/tespy_nw_closedloop")
# set if print the network iteration info
nw.set_attr(iterinfo=False)
# create bhe dataframe of the network system from bhe_network.csv
-df = create_dataframe()
+df = create_dataframe() # noqa: PD901
n_BHE = np.size(df.iloc[:, 0])
# create local variables of the components label and connections label in
--
GitLab