sabiharustam /
voltcycle
| @@ 134-149 (lines=16) @@ | ||
| 131 | #list1, list2 = list(dict1['df_1'].items()) |
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| 132 | #list1, list2 = list(dict1.get('df_'+str(1))) |
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| 133 | ||
| 134 | def data_frame(dict_cycle, n): |
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| 135 | """Reads the dictionary of dataframes and returns dataframes for each cycle |
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| 136 | ||
| 137 | Parameters |
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| 138 | __________ |
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| 139 | dict_cycle: Dictionary of dataframes |
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| 140 | n: cycle number |
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| 141 | ||
| 142 | Returns: |
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| 143 | _______ |
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| 144 | Dataframe correcponding to the cycle number |
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| 145 | """ |
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| 146 | list1, list2 = (list(dict_cycle.get('cycle_'+str(n)).items())) |
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| 147 | zippedList = list(zip(list1[1], list2[1])) |
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| 148 | data = pd.DataFrame(zippedList, columns = ['Potential' , 'Current']) |
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| 149 | return data |
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| 150 | ||
| 151 | ||
| 152 | def plot_fig(dict_cycle, n): |
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| @@ 82-97 (lines=16) @@ | ||
| 79 | #list1, list2 = list(dict1['df_1'].items()) |
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| 80 | #list1, list2 = list(dict1.get('df_'+str(1))) |
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| 81 | ||
| 82 | def data_frame(dict_cycle, n): |
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| 83 | """Reads the dictionary of dataframes and returns dataframes for each cycle |
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| 84 | ||
| 85 | Parameters |
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| 86 | __________ |
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| 87 | dict_cycle: Dictionary of dataframes |
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| 88 | n: cycle number |
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| 89 | ||
| 90 | Returns: |
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| 91 | _______ |
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| 92 | Dataframe correcponding to the cycle number |
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| 93 | """ |
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| 94 | list1, list2 = (list(dict_cycle.get('cycle_'+str(n)).items())) |
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| 95 | zippedList = list(zip(list1[1], list2[1])) |
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| 96 | data = pd.DataFrame(zippedList, columns = ['Potential' , 'Current']) |
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| 97 | return data |
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| 98 | ||
| 99 | def plot_fig(dict_cycle, n): |
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| 100 | """For basic plotting of the cycle data |
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