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

Fixing minor issues with plots and design #98

Merged
merged 1 commit into from
Nov 24, 2021
Merged

Fixing minor issues with plots and design #98

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
54 changes: 28 additions & 26 deletions QtBrainChartGUI/plugins/harmonization/harmonization.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -68,7 +68,7 @@ def __init__(self):
self.plotCanvas.axes1 = self.plotCanvas.fig.add_subplot(121)
self.plotCanvas.axes2 = self.plotCanvas.fig.add_subplot(122)
self.ui.verticalLayout.addWidget(self.plotCanvas)
self.ui.horizontalLayout_3.addWidget(self.comboBoxROI)
self.ui.horizontalLayout_3.insertWidget(0,self.comboBoxROI)
self.MUSE = None

self.ui.stackedWidget.setCurrentIndex(0)
Expand Down Expand Up @@ -107,8 +107,8 @@ def OnLoadHarmonizationModelBtnClicked(self):
self.ui.Harmonized_Data_Information_Lbl.setObjectName('Missing_label')
self.ui.Harmonized_Data_Information_Lbl.setStyleSheet('QLabel#Missing_label {color: red}')
else:
self.model = pd.read_pickle(filename)
if not (isinstance(self.model,dict) and 'SITE_labels' in self.model):
self.datamodel.harmonization_model = pd.read_pickle(filename)
if not (isinstance(self.datamodel.harmonization_model,dict) and 'SITE_labels' in self.datamodel.harmonization_model):
text_2=('Selected file is not a viable harmonization model')
self.ui.Harmonized_Data_Information_Lbl.setText(text_2)
self.ui.Harmonized_Data_Information_Lbl.setObjectName('Error_label')
Expand All @@ -121,11 +121,11 @@ def OnLoadHarmonizationModelBtnClicked(self):
self.ui.Harmonized_Data_Information_Lbl.setObjectName('correct_label')
self.ui.Harmonized_Data_Information_Lbl.setStyleSheet('QLabel#correct_label {color: black}')
model_text1 = (os.path.basename(filename) +' loaded')
model_text2 = ('SITES in training set: '+ ' '.join([str(elem) for elem in list(self.model['SITE_labels'])]))
model_text2 = ('SITES in training set: '+ ' '.join([str(elem) for elem in list(self.datamodel.harmonization_model['SITE_labels'])]))
model_text2 = wrap_by_word(model_text2,4)
model_text1 += '\n\n'+model_text2
age_max = self.model['smooth_model']['bsplines_constructor'].knot_kwds[0]['upper_bound']
age_min = self.model['smooth_model']['bsplines_constructor'].knot_kwds[0]['lower_bound']
age_max = self.datamodel.harmonization_model['smooth_model']['bsplines_constructor'].knot_kwds[0]['upper_bound']
age_min = self.datamodel.harmonization_model['smooth_model']['bsplines_constructor'].knot_kwds[0]['lower_bound']
model_text3 = ('Valid Age Range: [' + str(age_min) + ', ' + str(age_max) + ']')
model_text1 += '\n'+model_text3
self.ui.Harmonized_Data_Information_Lbl.setText(model_text1)
Expand Down Expand Up @@ -221,8 +221,8 @@ def plotMUSE(self,plotOptions):
self.MUSE.dropna(subset=[raw_res],inplace=True)
cSite=sns.color_palette("hls", len(list(self.MUSE.SITE.unique())))

data['SITE'] = pd.Categorical(data['SITE'])
data['SITE'] = data.SITE.cat.remove_unused_categories()
data.loc[:,'SITE'] = pd.Categorical(data['SITE'])
data.loc[:,'SITE'] = data.SITE.cat.remove_unused_categories()

sd_raw = data[raw_res].std()
sd_h = data[h_res].std()
Expand All @@ -247,7 +247,7 @@ def plotMUSE(self,plotOptions):
nobs1 = data['SITE'].value_counts().sort_index(ascending=True).values
nobs1 = [str(x) for x in nobs1.tolist()]
nobs1 = [i for i in nobs1]
labels = [x + ' (N=' for x in self.model['SITE_labels']]
labels = [x + ' (N=' for x in self.datamodel.harmonization_model['SITE_labels']]
labels = [''.join(i) for i in zip(labels, nobs1)]
labels = [x + ')' for x in labels]
self.plotCanvas.axes1.axvline(ci_plus_raw,color='grey',ls='--')
Expand Down Expand Up @@ -282,10 +282,12 @@ def plotMUSE(self,plotOptions):

def OnAddToDataFrame(self):
print('Saving modified data to pickle file...')
H_ROIs = ['H_'+x for x in self.model]
ROIs_ICV_Sex_Residuals = ['RES_ICV_Sex_' + x for x in self.model['ROIs']]
ROIs_Residuals = ['RES_' + x for x in self.model['ROIs']]
RAW_Residuals = ['RAW_RES_' + x for x in self.model['ROIs']]
H_ROIs = ['H_'+x for x in self.datamodel.harmonization_model['ROIs']]
ROIs_ICV_Sex_Residuals = ['RES_ICV_Sex_' + x for x in self.datamodel.harmonization_model['ROIs']]
ROIs_Residuals = ['RES_' + x for x in self.datamodel.harmonization_model['ROIs']]
RAW_Residuals = ['RAW_RES_' + x for x in self.datamodel.harmonization_model['ROIs']]
if ('H_MUSE_Volume_47' not in self.datamodel.data.keys()):
self.datamodel.data.loc[:,H_ROIs] = self.MUSE[H_ROIs]
self.datamodel.data.loc[:,ROIs_ICV_Sex_Residuals] = self.MUSE[ROIs_ICV_Sex_Residuals]
self.datamodel.data.loc[:,ROIs_Residuals] = self.MUSE[ROIs_Residuals]
self.datamodel.data.loc[:,RAW_Residuals] = self.MUSE[RAW_Residuals]
Expand All @@ -310,16 +312,16 @@ def DoHarmonization(self):
covars = self.datamodel.data[['SITE','Age','Sex','DLICV_baseline']].copy()
covars.loc[:,'Sex'] = covars['Sex'].map({'M':1,'F':0})
covars.loc[covars.Age>100, 'Age']=100
bayes_data, stand_mean = nh.harmonizationApply(self.datamodel.data[[x for x in self.model['ROIs']]].values,
bayes_data, stand_mean = nh.harmonizationApply(self.datamodel.data[[x for x in self.datamodel.harmonization_model['ROIs']]].values,
covars,
self.model,True)
self.datamodel.harmonization_model,True)

Raw_ROIs_Residuals = self.datamodel.data[self.model['ROIs']].values - stand_mean
Raw_ROIs_Residuals = self.datamodel.data[self.datamodel.harmonization_model['ROIs']].values - stand_mean

# create list of new SITEs to loop through
new_sites = set(self.datamodel.data['SITE'].value_counts().index.tolist())^set(self.model['SITE_labels'])
new_sites = set(self.datamodel.data['SITE'].value_counts().index.tolist())^set(self.datamodel.harmonization_model['SITE_labels'])

var_pooled = self.model['var_pooled']
var_pooled = self.datamodel.harmonization_model['var_pooled']

if 'UseForComBatGAMHarmonization' in self.datamodel.data.columns:
for site in new_sites:
Expand All @@ -341,17 +343,17 @@ def DoHarmonization(self):
print('Skipping out-of-sample harmonization because `UseForComBatGAMHarmonization` does not exist.')

if 'isTrainMUSEHarmonization' in self.datamodel.data.columns:
muse = pd.concat([self.datamodel.data['isTrainMUSEHarmonization'],covars, pd.DataFrame(bayes_data, columns=['H_' + s for s in self.model['ROIs']])],axis=1)
muse = pd.concat([self.datamodel.data['isTrainMUSEHarmonization'],covars, pd.DataFrame(bayes_data, columns=['H_' + s for s in self.datamodel.harmonization_model['ROIs']])],axis=1)
else:
muse = pd.concat([covars,pd.DataFrame(bayes_data, columns=['H_' + s for s in self.model['ROIs']])],axis=1)
start_index = len(self.model['SITE_labels'])
sex_icv_effect = np.dot(muse[['Sex','DLICV_baseline']],self.model['B_hat'][start_index:(start_index+2),:])
ROIs_ICV_Sex_Residuals = ['RES_ICV_Sex_' + x for x in self.model['ROIs']]
muse.loc[:,ROIs_ICV_Sex_Residuals] = muse[['H_' + x for x in self.model['ROIs']]] - sex_icv_effect
muse = pd.concat([covars,pd.DataFrame(bayes_data, columns=['H_' + s for s in self.datamodel.harmonization_model['ROIs']])],axis=1)
start_index = len(self.datamodel.harmonization_model['SITE_labels'])
sex_icv_effect = np.dot(muse[['Sex','DLICV_baseline']],self.datamodel.harmonization_model['B_hat'][start_index:(start_index+2),:])
ROIs_ICV_Sex_Residuals = ['RES_ICV_Sex_' + x for x in self.datamodel.harmonization_model['ROIs']]
muse.loc[:,ROIs_ICV_Sex_Residuals] = muse[['H_' + x for x in self.datamodel.harmonization_model['ROIs']]] - sex_icv_effect

muse.loc[:,'Sex'] = muse['Sex'].map({1:'M',0:'F'})
ROIs_Residuals = ['RES_' + x for x in self.model['ROIs']]
RAW_Residuals = ['RAW_RES_' + x for x in self.model['ROIs']]
ROIs_Residuals = ['RES_' + x for x in self.datamodel.harmonization_model['ROIs']]
RAW_Residuals = ['RAW_RES_' + x for x in self.datamodel.harmonization_model['ROIs']]
muse.loc[:,ROIs_Residuals] = bayes_data-stand_mean
muse.loc[:,RAW_Residuals] = Raw_ROIs_Residuals
print('Harmonization done.')
Expand Down