Add parsing for non 1-minute data to UO SRML parser #711
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cwhanse
reviewed
May 6, 2019
pvlib/iotools/srml.py
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| with pandas' default labeling behavior. | ||
| The time index is shifted back by one interval to account for the | ||
| daily endtime of 2400, and to avoid time parsing errors on leap | ||
| years. The returned data values should be understood to occur |
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are labeled by the left endpoint of interval, and should be understood...
cwhanse
reviewed
May 6, 2019
pvlib/iotools/srml.py
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| # subracting the length of one interval and then correcting the times | ||
| # at each former hour. interval_length is determined by taking the | ||
| # difference of the first two rows of the time column. | ||
| interval_length = int(df[df.columns[1]][:2].diff()[1]) |
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This line would be easier to read as, e.g., interval_length = df[df.columns[0]][1] - df[df.columns[0]][0]
cwhanse
approved these changes
May 6, 2019
wholmgren
reviewed
May 6, 2019
| fifty_nines = df_time % 100 == 99 | ||
| times = df_time.where(~fifty_nines, df_time - 40) | ||
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| # subracting the length of one interval and then correcting the times |
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Add comment like "e.g. the first two rows of hourly data are 100, 200, so interval length = 100"
pvlib/iotools/srml.py
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| # Hourly files do not require fixing the former hour timestamps. | ||
| times = df_time | ||
| else: | ||
| old_hours = df_time % 100 == (100 - interval_length) |
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I updated the logic for fixing the hour times. I didn't think of checking |
wholmgren
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solarfx2
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