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fixed optimize test

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fixed first our values for optimize test
This commit is contained in:
Normann 2024-10-06 15:10:14 +02:00 committed by Andreas
parent 40341d9aef
commit d8a46eb5d3
1 changed files with 18 additions and 18 deletions
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36
tests/test_class_optimize.py
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@ -107,7 +107,7 @@ EXPECTED_RESULT = {
], ],
"result": { "result": {
"Last_Wh_pro_Stunde": [ "Last_Wh_pro_Stunde": [
None, 0.0,
1063.91, 1063.91,
1320.56, 1320.56,
1132.03, 1132.03,
@ -147,7 +147,7 @@ EXPECTED_RESULT = {
592.97, 592.97,
], ],
"Netzeinspeisung_Wh_pro_Stunde": [ "Netzeinspeisung_Wh_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -187,7 +187,7 @@ EXPECTED_RESULT = {
0.0, 0.0,
], ],
"Netzbezug_Wh_pro_Stunde": [ "Netzbezug_Wh_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -227,7 +227,7 @@ EXPECTED_RESULT = {
0.0, 0.0,
], ],
"Kosten_Euro_pro_Stunde": [ "Kosten_Euro_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -267,7 +267,7 @@ EXPECTED_RESULT = {
0.0, 0.0,
], ],
"akku_soc_pro_stunde": [ "akku_soc_pro_stunde": [
None, 80.0,
79.91107093663912, 79.91107093663912,
78.99070247933885, 78.99070247933885,
79.08956914600552, 79.08956914600552,
@ -307,7 +307,7 @@ EXPECTED_RESULT = {
86.4914772727273, 86.4914772727273,
], ],
"Einnahmen_Euro_pro_Stunde": [ "Einnahmen_Euro_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -348,7 +348,7 @@ EXPECTED_RESULT = {
], ],
"Gesamtbilanz_Euro": np.float64(-0.7150588584710738), "Gesamtbilanz_Euro": np.float64(-0.7150588584710738),
"E-Auto_SoC_pro_Stunde": [ "E-Auto_SoC_pro_Stunde": [
None, 54.0,
54.0, 54.0,
54.0, 54.0,
54.0, 54.0,
@ -390,7 +390,7 @@ EXPECTED_RESULT = {
"Gesamteinnahmen_Euro": np.float64(0.7150588584710738), "Gesamteinnahmen_Euro": np.float64(0.7150588584710738),
"Gesamtkosten_Euro": np.float64(0.0), "Gesamtkosten_Euro": np.float64(0.0),
"Verluste_Pro_Stunde": [ "Verluste_Pro_Stunde": [
None, 0.0,
2.817272727272737, 2.817272727272737,
29.157272727272726, 29.157272727272726,
3.5592000000000112, 3.5592000000000112,
@ -431,7 +431,7 @@ EXPECTED_RESULT = {
], ],
"Gesamt_Verluste": np.float64(4041.523450413223), "Gesamt_Verluste": np.float64(4041.523450413223),
"Haushaltsgeraet_wh_pro_stunde": [ "Haushaltsgeraet_wh_pro_stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -681,7 +681,7 @@ EXPECTED_RESULT = {
"spuelstart": None, "spuelstart": None,
"simulation_data": { "simulation_data": {
"Last_Wh_pro_Stunde": [ "Last_Wh_pro_Stunde": [
None, 0.0,
1063.91, 1063.91,
1320.56, 1320.56,
1132.03, 1132.03,
@ -721,7 +721,7 @@ EXPECTED_RESULT = {
592.97, 592.97,
], ],
"Netzeinspeisung_Wh_pro_Stunde": [ "Netzeinspeisung_Wh_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -761,7 +761,7 @@ EXPECTED_RESULT = {
0.0, 0.0,
], ],
"Netzbezug_Wh_pro_Stunde": [ "Netzbezug_Wh_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -801,7 +801,7 @@ EXPECTED_RESULT = {
0.0, 0.0,
], ],
"Kosten_Euro_pro_Stunde": [ "Kosten_Euro_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -841,7 +841,7 @@ EXPECTED_RESULT = {
0.0, 0.0,
], ],
"akku_soc_pro_stunde": [ "akku_soc_pro_stunde": [
None, 80.0,
79.91107093663912, 79.91107093663912,
78.99070247933885, 78.99070247933885,
79.08956914600552, 79.08956914600552,
@ -881,7 +881,7 @@ EXPECTED_RESULT = {
86.4914772727273, 86.4914772727273,
], ],
"Einnahmen_Euro_pro_Stunde": [ "Einnahmen_Euro_pro_Stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,
@ -922,7 +922,7 @@ EXPECTED_RESULT = {
], ],
"Gesamtbilanz_Euro": np.float64(-0.7150588584710738), "Gesamtbilanz_Euro": np.float64(-0.7150588584710738),
"E-Auto_SoC_pro_Stunde": [ "E-Auto_SoC_pro_Stunde": [
None, 54.0,
54.0, 54.0,
54.0, 54.0,
54.0, 54.0,
@ -964,7 +964,7 @@ EXPECTED_RESULT = {
"Gesamteinnahmen_Euro": np.float64(0.7150588584710738), "Gesamteinnahmen_Euro": np.float64(0.7150588584710738),
"Gesamtkosten_Euro": np.float64(0.0), "Gesamtkosten_Euro": np.float64(0.0),
"Verluste_Pro_Stunde": [ "Verluste_Pro_Stunde": [
None, 0.0,
2.817272727272737, 2.817272727272737,
29.157272727272726, 29.157272727272726,
3.5592000000000112, 3.5592000000000112,
@ -1005,7 +1005,7 @@ EXPECTED_RESULT = {
], ],
"Gesamt_Verluste": np.float64(4041.523450413223), "Gesamt_Verluste": np.float64(4041.523450413223),
"Haushaltsgeraet_wh_pro_stunde": [ "Haushaltsgeraet_wh_pro_stunde": [
None, 0.0,
0.0, 0.0,
0.0, 0.0,
0.0, 0.0,