Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Add results attribute for DeltaDelta and MiniMetaDelta to return attributes in a DataFrame format #150

Open
wants to merge 9 commits into
base: vnbdev
Choose a base branch
from
Open

Add results attribute for DeltaDelta and MiniMetaDelta to return attributes in a DataFrame format #150

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
9 commits
Select commit Hold shift + click to select a range
b82ba4b
Add files via upload
junyangliao Nov 11, 2023
6a38de4
'Add results attribute for DeltaDelta and MiniMetaDelta to return att…
junyangliao Nov 21, 2023
cce561f
Merge branch 'vnbdev' into master
junyangliao Nov 28, 2023
99ddd93
fix .results api for retrieval of DeltaDelta results
sunroofgod Dec 1, 2023
240a753
fix .results api for retrieval of DeltaDelta results
sunroofgod Dec 1, 2023
72b7fdd
Merge pull request #1 from sunroofgod-testing/master
junyangliao Dec 2, 2023
f270b80
Added .results api for retrieval in dataframe format
junyang00 Dec 2, 2023
485f3c5
Fixed bug within deltadelta class as well as updating metadata
junyang00 Dec 2, 2023
b8cd55a
Fixed bug causing results attribute to not be compatible with python
junyang00 Dec 5, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
38 changes: 34 additions & 4 deletions dabest/_classes.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -739,6 +739,7 @@ def __init__(self, effectsizedataframe, permutation_count,bootstraps_delta_delta
self.__bootstraps = np.array(self.__effsizedf["bootstraps"])
self.__control = self.__dabest_obj.experiment_label[0]
self.__test = self.__dabest_obj.experiment_label[1]
self.__results = pd.DataFrame({})


# Compute the bootstrap delta-delta or deltas' g and the true dela-delta based on the raw data
Expand Down Expand Up @@ -809,9 +810,8 @@ def __init__(self, effectsizedataframe, permutation_count,bootstraps_delta_delta
self.__pct_interval_idx = (pct_idx_low, pct_idx_high)
self.__pct_low = sorted_delta_delta[pct_idx_low]
self.__pct_high = sorted_delta_delta[pct_idx_high]




def __permutation_test(self):
"""
Perform a permutation test and obtain the permutation p-value
Expand Down Expand Up @@ -897,7 +897,10 @@ def to_dict(self):
for a in attrs:
out[a] = getattr(self, a)
return out


def configure_results(self, __results: pd.DataFrame, column_names):
self.__results = __results
self.__results.columns = column_names

@property
def ci(self):
Expand Down Expand Up @@ -1057,6 +1060,15 @@ def permutations_delta_delta(self):
return self.__permutations_delta_delta


@property
def results(self):
"""
Returns the attributes of the DeltaDelta object as a
Dataframe.
"""
return self.__results



# %% ../nbs/API/class.ipynb 32
class MiniMetaDelta(object):
Expand Down Expand Up @@ -1091,6 +1103,7 @@ def __init__(self, effectsizedataframe, permutation_count,
self.__test = np.array(self.__effsizedf["test"])
self.__control_N = np.array(self.__effsizedf["control_N"])
self.__test_N = np.array(self.__effsizedf["test_N"])
self.__results = pd.DataFrame({})


idx = self.__dabest_obj.idx
Expand Down Expand Up @@ -1298,6 +1311,11 @@ def to_dict(self):
for a in attrs:
out[a] = getattr(self, a)
return out

def configure_results(self, __results: pd.DataFrame, column_names):
self.__results = __results
self.__results.columns = column_names



@property
Expand Down Expand Up @@ -1519,7 +1537,13 @@ def permutations_weighted_delta(self):
self.__permutation_test()
return self.__permutations_weighted_delta


@property
def results(self):
"""
Returns the attributes of the MiniMetaDelta object as a
Dataframe.
"""
return self.__results

# %% ../nbs/API/class.ipynb 37
class TwoGroupsEffectSize(object):
Expand Down Expand Up @@ -2374,6 +2398,9 @@ def __pre_calc(self):
self.__permutation_count,
bootstraps_delta_delta,
self.__ci)
delta_delta_results_dict = self.__delta_delta.to_dict()
delta_delta_results_df = pd.DataFrame.from_dict(delta_delta_results_dict, orient='index').reset_index()
self.__delta_delta.configure_results(delta_delta_results_df, ['Attribute', 'Value'])
reprs.append(self.__delta_delta.__repr__(header=False))
elif self.__delta2 is True and self.__effect_size not in ["mean_diff", "delta_g"]:
self.__delta_delta = "Delta-delta is not supported for {}.".format(self.__effect_size)
Expand All @@ -2385,6 +2412,9 @@ def __pre_calc(self):
self.__mini_meta_delta = MiniMetaDelta(self,
self.__permutation_count,
self.__ci)
mini_meta_results_dict = self.__mini_meta_delta.to_dict()
mini_meta_results_df = pd.DataFrame.from_dict(mini_meta_results_dict, orient='index').reset_index()
self.__mini_meta_delta.configure_results(mini_meta_results_df, ['Attribute', 'Value'])
reprs.append(self.__mini_meta_delta.__repr__(header=False))
elif self.__mini_meta is True and self.__effect_size != "mean_diff":
self.__mini_meta_delta = "Weighted delta is not supported for {}.".format(self.__effect_size)
Expand Down