def cumulative_df(df, full_cum=False):
"""Index by band, """
bands = df.index
assert all(bands == ["Z", "Y", "J", "H", "K"]), bands
if full_cum:
cum_bands = [
"Z", "ZY", "ZYJ", "ZYJH", "ZYJHK", "YJHK", "JHK", "HK", "K"
]
cum_dict = {
"Band": cum_bands,
"Cond. 1": rv_cumulative_full(df["Cond. 1"]),
"Cond. 2": rv_cumulative_full(df["Cond. 2"]),
"Cond. 3": rv_cumulative_full(df["Cond. 3"]),
}
else:
cum_bands = ["Z", "ZY", "ZYJ", "ZYJH", "ZYJHK"]
cum_dict = {
"Band": cum_bands,
"Cond. 1": rv_cumulative(df["Cond. 1"], single=True),
"Cond. 2": rv_cumulative(df["Cond. 2"], single=True),
"Cond. 3": rv_cumulative(df["Cond. 3"], single=True),
}
cum_df = pd.DataFrame(cum_dict)
cum_df = cum_df.set_index("Band")
cum_df = cum_df.reindex(cum_bands)
return cum_df
def test_rv_cumulative(input_, flag):
"""Test it works on well formed input."""
result = rv_cumulative(input_, single=flag)
assert result[-2] == weighted_error(input_[:-1])
assert result[-1] == weighted_error(input_)
if flag:
assert result[0] == input_[0]
def cumulative_df(df, full_cum=False):
"""Calculated cumulative RV precision across bands.
The precision of "Z", "ZY", "ZYJ", "ZYJH", "ZYJHK" bands.
Parameters
----------
df: pandas.DataFrame
DataFrame.
full_cum: bool
Include "YJHK", "JHK", "HK", "K" grouping also. Default is False.
"""
bands = df.index
assert all(bands == ["Z", "Y", "J", "H", "K"]), bands
if full_cum:
cum_bands = [
"Z", "ZY", "ZYJ", "ZYJH", "ZYJHK", "YJHK", "JHK", "HK", "K"
]
cum_dict = {
"Band": cum_bands,
"Cond. 1": rv_cumulative_full(df["Cond. 1"]),
"Cond. 2": rv_cumulative_full(df["Cond. 2"]),
"Cond. 3": rv_cumulative_full(df["Cond. 3"]),
}
else:
cum_bands = ["Z", "ZY", "ZYJ", "ZYJH", "ZYJHK"]
cum_dict = {
"Band": cum_bands,
"Cond. 1": rv_cumulative(df["Cond. 1"], single=True),
"Cond. 2": rv_cumulative(df["Cond. 2"], single=True),
"Cond. 3": rv_cumulative(df["Cond. 3"], single=True),
}
cum_df = pd.DataFrame(cum_dict)
cum_df = cum_df.set_index("Band")
cum_df = cum_df.reindex(cum_bands)
return cum_df