Util fix #105
Util fix #105
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Sorry for the delay in writing back, but like we talked about this is looking good. The logic for handling combinations of |
web/handlers/genomics/util.py
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| keep_lineages.append(lineages_to_retain) | ||
| date_limit = dt.strptime(max_date, "%Y-%m-%d") - timedelta(days=ndays) # searches from max_date to ndays back | ||
| df = df[(df["prevalence"] >= prevalence_threshold) & (df['date'] < max_date) & (df['date'] > date_limit)] | ||
| num_unique_dates = df[df["date"] >= date_limit]["date"].unique().shape[0] |
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Since you've already filtered the df at this point, I think you can skip the [df["date"] <= date_limit] part of this line and the two similar ones above, and then just have one line that does this after the if statement.
web/handlers/genomics/util.py
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| @@ -209,48 +209,28 @@ def get_major_lineage_prevalence(df, index_col = "date", min_date = None, max_da | |||
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| df['prevalence'] = df['total_count']/df['lineage_count'] | |||
| df = df.sort_values(by="date") #Sort date values | |||
| min_date = dt.strptime(min_date, "%Y-%m-%d") | |||
| max_date = dt.strptime(max_date, "%Y-%m-%d") | |||
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| if min_date and max_date: | |||
| df = df[(df["date"].between(min_date, max_date)) & (df["prevalence"] >= prevalence_threshold)] | |||
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I think you just want to filter by date here, and not by prevalence just yet. Later, you're removing the lineages which don't have enough days above the prevalence threshold, but we still want to return data for low-prevalence days for lineages that are above the threshold.
web/handlers/genomics/util.py
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| if num_unique_dates < nday_threshold: | ||
| nday_threshold = round((nday_threshold/ndays) * num_unique_dates) | ||
| lineage_counts = df["lineage"].value_counts() #number of times lineage is found in df |
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If you put your prevalence threshold filter down here instead, you should get the same counts as your current version, but there won't be gaps in the dataframe on low prevalence days
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