diff --git a/pandapipes/test/pipeflow_internals/transient_test_tee_junction.py b/pandapipes/test/pipeflow_internals/transient_test_tee_junction.py index 05f1db17..ec26d702 100644 --- a/pandapipes/test/pipeflow_internals/transient_test_tee_junction.py +++ b/pandapipes/test/pipeflow_internals/transient_test_tee_junction.py @@ -105,17 +105,6 @@ def _output_writer(net, time_steps, ow_path=None): pipe3[1:-1, :] = np.transpose( copy.deepcopy(res_T[:, nodes + (2 * (sections - 1)):nodes + (3 * (sections - 1))])) -# datap1 = pd.read_csv(os.path.join(os.getcwd(), 'pandapipes', 'pandapipes', 'files', 'Temperature.csv'), -# sep=';', -# header=1, nrows=5, keep_default_na=False) -# datap2 = pd.read_csv(os.path.join(os.getcwd(), 'pandapipes', 'pandapipes', 'files', 'Temperature.csv'), -# sep=';', -# header=8, nrows=5, keep_default_na=False) -# datap3 = pd.read_csv(os.path.join(os.getcwd(), 'pandapipes', 'pandapipes', 'files', 'Temperature.csv'), -# sep=';', -# header=15, nrows=5, keep_default_na=False) - -from IPython.display import clear_output plt.ion() @@ -156,10 +145,20 @@ def _output_writer(net, time_steps, ow_path=None): marker="+", linestyle="dashdot") -if sections == 4: - d1 = ax.plot(np.arange(0, sections + 1, 1) * 1000 / sections, datap1["T"], color="black") - d2 = ax1.plot(np.arange(0, sections + 1, 1) * 1000 / sections, datap2["T"], color="black") - d3 = ax2.plot(np.arange(0, sections + 1, 1) * 1000 / sections, datap3["T"], color="black") +# if sections == 4: +# datap1 = pd.read_csv(os.path.join(os.getcwd(), 'pandapipes', 'pandapipes', 'files', 'Temperature.csv'), +# sep=';', +# header=1, nrows=5, keep_default_na=False) +# datap2 = pd.read_csv(os.path.join(os.getcwd(), 'pandapipes', 'pandapipes', 'files', 'Temperature.csv'), +# sep=';', +# header=8, nrows=5, keep_default_na=False) +# datap3 = pd.read_csv(os.path.join(os.getcwd(), 'pandapipes', 'pandapipes', 'files', 'Temperature.csv'), +# sep=';', +# header=15, nrows=5, keep_default_na=False) +# +# d1 = ax.plot(np.arange(0, sections + 1, 1) * 1000 / sections, datap1["T"], color="black") +# d2 = ax1.plot(np.arange(0, sections + 1, 1) * 1000 / sections, datap2["T"], color="black") +# d3 = ax2.plot(np.arange(0, sections + 1, 1) * 1000 / sections, datap3["T"], color="black") ax.set_ylim((280, 335)) ax1.set_ylim((280, 335))