def toggleValue(self, event):
df = self.nmrproblem.df
patoms = self.nmrproblem.protonAtoms
catoms = self.nmrproblem.carbonAtoms
if ipysheet.to_dataframe(self.sheet1).shape == (0, 0):
return
if event.name == 'value':
self.old = event.old
self.new = event.new
# update backend dataframe
# i
if event.old == 'All':
df.loc[:, :] = ipysheet.to_dataframe(self.sheet1).loc[:, :]
elif event.old == 'COSY':
rr = ['ppm'] + patoms
cc = ['ppm'] + patoms
df.loc[rr, cc] = ipysheet.to_dataframe(self.sheet1).loc[rr, cc]
elif event.old == 'HSQC-HMBC':
rr = ['ppm'] + catoms
cc = ['ppm'] + patoms
df.loc[rr, cc] = ipysheet.to_dataframe(self.sheet1).loc[rr, cc]
elif event.old == 'integrals-ppm':
rr = ['ppm', 'integral']
cc = patoms + catoms
df.loc[rr, cc] = ipysheet.to_dataframe(self.sheet1).loc[rr, cc]
df.loc[cc, 'ppm'] = df.loc['ppm', cc]
# update sheet1 display of dataframe
if event.new == 'All':
self.sheet1 = ipysheet.from_dataframe(df)
elif event.new == 'COSY':
rr = ['ppm'] + patoms[::-1]
cc = ['ppm'] + patoms
self.sheet1 = ipysheet.from_dataframe(df.loc[rr, cc])
elif event.new == 'HSQC-HMBC':
rr = ['ppm'] + catoms[::-1]
cc = ['ppm'] + patoms
self.sheet1 = ipysheet.from_dataframe(df.loc[rr, cc])
elif event.new == 'integrals-ppm':
rr = ['ppm', 'integral']
cc = patoms + catoms
self.sheet1 = ipysheet.from_dataframe(df.loc[rr, cc])
self.dfLayout.children = [
self.toggleDF, self.dfWarningTextW, self.sheet1,
self.dfButtonsLayout
]
def options_sheet_to_df(options_sheet):
options_df = ipysheet.to_dataframe(options_sheet)
options_df.columns = options_df.iloc[0]
options_df = options_df[1:]
for col in ['C', 'K', 'P']:
options_df[col] = pd.to_numeric(options_df[col])
options_df = options_df[options_df.K != 0]
return options_df
def _sheet_to_df(sheet: sh.Sheet) -> pd.DataFrame:
"""
Transforms a ipysheet Sheet into a pandas DataFrame.
:param sheet: the ipysheet Sheet to be converted
:return the equivalent pandas DataFrame
"""
df = sh.to_dataframe(sheet)
return df
def load_data(X):
df = ipysheet.to_dataframe(X['sheet'])
B = np.array(df['Field [mT]'])
B = B[~np.isnan(B)]
M = np.array(df['Magnetization'])
M = M[~np.isnan(M)]
X['B'] = B
X['M'] = M
return X
def button_clicked(self, _):
# "linking function with output"
with out:
self.view.display_output(
self.model.runningHeader,
ipysheet.to_dataframe(self.model.sheets[self.view.menu.value]),
)
# runs the model
enriched_label, labelled_data = self.mlmodel.run(
self.model.datas[self.view.menu.value][['content'
]].copy(deep=True),
ipysheet.to_dataframe(self.model.sheets[self.view.menu.value]))
with out:
self.view.display_output(
self.model.datas[self.view.menu.value],
self.model.recommendationHeader,
self.model.recommendations[self.view.menu.value],
self.model.labelHeader,
self.model.sheets[self.view.menu.value],
self.model.enrichedHeader, enriched_label,
self.model.labelledHeader, labelled_data)
return
def test_from_to_dataframe():
df = pd.DataFrame({
'A': 1.,
'B': pd.Timestamp('20130102'),
'C': pd.Series(1, index=list(range(4)), dtype='float32'),
'D': np.array([False, True, False, False], dtype='bool'),
'S': pd.Categorical(["test", "train", "test", "train"]),
'T': 'foo'
})
df.loc[[0, 2], ['B']] = np.nan
sheet = ipysheet.from_dataframe(df)
df2 = ipysheet.to_dataframe(sheet)
a = np.array(df.values)
b = np.array(df2.values)
assert ((a == b) | (pd.isna(a) & pd.isna(b))).all()
def onButtonClicked(self, bttn):
self.debugLabel.value = bttn.description
# print("bttn", bttn, type(bttn), bttn.description)
if "Start New" in bttn.description:
self.debugLabel.value = self.problemNameW.value
# remove spaces from name
probdirname = self.problemNameW.value.replace(" ", "")
tmpdir = tempfile.TemporaryDirectory()
os.mkdir(os.path.join(tmpdir.name, probdirname))
self.nmrproblem = nmrProblem.NMRproblem(
os.path.join(tmpdir.name, probdirname))
# create a temporary problem directory
elif "Directory" in bttn.description:
self.nmrproblem = nmrProblem.NMRproblem.from_guidata()
if not isinstance(self.nmrproblem, type(None)):
self.prDirW.value = self.nmrproblem.problemDirectoryPath
# update other widgets based on contents of nmrproblem
self.updateSpectraWidgetsFromNMRproblem()
self.updateMoleculeWidgetsFromNMRproblem()
# create a view of the dataframe in nmrproblem
self.sheet1 = ipysheet.from_dataframe(self.nmrproblem.df)
self.dfWarningTextW.value = "Table Messages: None"
# dfLayout.children = [dfWarningTextW, qgrid1, dfButtonsLayout]
# create 1D 1H & C13 plots widget
self.H1C131DplotsLayout.children = [
self.createH1C13interactivePlot()
]
elif "update table" in bttn.description:
print("update table")
self.toggleDF.value = 'All'
ok = self.nmrproblem.updateDFtable(
ipysheet.to_dataframe(self.sheet1))
if ok:
self.nmrproblem.convertHSQCHMBCCOSYtoLists()
self.nmrproblem.update_attachedprotons_c13hyb()
self.sheet1 = ipysheet.from_dataframe(self.nmrproblem.df)
self.dfWarningTextW.value = "Table Messages: None"
else:
self.dfWarningTextW.value = "Table Messages: problems in table, please check it"
self.dfLayout.children = [
self.toggleDF, self.dfWarningTextW, self.sheet1,
self.dfButtonsLayout
]
elif "update and run" in bttn.description:
self.toggleDF.value = 'All'
ok = self.nmrproblem.updateDFtable(
ipysheet.to_dataframe(self.sheet1))
if ok:
self.sheet1 = ipysheet.from_dataframe(self.nmrproblem.df)
self.dfWarningTextW.value = "Table Messages: None"
self.nmrproblem.dfToNumbers()
self.nmrproblem.convertHSQCHMBCCOSYtoLists()
self.nmrproblem.convertJHzToLists()
self.nmrproblem.update_attachedprotons_c13hyb()
# H1df_orig, C13df_orig = nmrProblem.readinChemShiftTables()
# H1df_orig, C13df_orig = read_in_cs_tables()
self.nmrproblem.calcProbDistFunctions(H1df_orig, C13df_orig)
self.nmrproblem.identify1HC13peaks()
self.nmrproblem.udic[0]['df'] = self.nmrproblem.H1df
self.nmrproblem.udic[1]['df'] = self.nmrproblem.C13df
# self.nmrproblem.iprobs = iprobs
self.nmrproblem.createInfoDataframes()
self.nmrproblem.calculate1H13CSpectra1D()
udic = self.nmrproblem.udic
self.nmrproblem.save1DspecInfotoUdic()
self.nmrproblem.create1H13Clabels(num_poss=3)
self.dfLayout.children = [
self.toggleDF, self.dfWarningTextW, self.sheet1,
self.dfButtonsLayout
]
# create 1D 1H & C13 plots widget
self.H1C131DplotsLayout.children = [
self.createH1C13interactivePlot(), self.saveProblemButtonW
]
else:
self.dfWarningTextW.value = "Table Messages: problems in table, please check it"
self.dfLayout.children = [
self.toggleDF, self.dfWarningTextW, self.sheet1,
self.dfButtonsLayout
]
elif "Spectra" in bttn.description:
self.nmrproblem.createInfoDataframes()
self.nmrproblem.save1DspecInfotoUdic()
self.updateSpectralInformationWidgetChanged()
self.nmrproblem.calculate1H13CSpectra1D()
self.H1C131DplotsLayout.children = [
self.createH1C13interactivePlot(), self.saveProblemButtonW
]
elif "Molecule" in bttn.description:
print("Molecule")
self.nmrproblem.update_molecule(self.moleculeAtomsW.value,
self.pGrpsW.value,
self.cGrpsW.value)
# create a view of the dataframe in nmrproblem
self.sheet1 = ipysheet.from_dataframe(self.nmrproblem.df)
self.dfWarningTextW.value = "Table Messages: None"
self.dfLayout.children = [
self.toggleDF, self.dfWarningTextW, self.sheet1,
self.dfButtonsLayout
]
elif "Save Problem" in bttn.description:
yml_dict = self.nmrproblem.save_problem()
yml_str = yaml.dump(yml_dict, indent=4)
self.ymlText.value = yml_str
def test_to_dataframe():
sheet = ipysheet.sheet(rows=5, columns=4)
ipysheet.cell(0, 0, value=True)
ipysheet.row(1, value=[2, 34, 543, 23])
ipysheet.column(3, value=[1.2, 1.3, 1.4, 1.5, 1.6])
df = ipysheet.to_dataframe(sheet)
assert np.all(df['A'].tolist() == [True, 2, None, None, None])
assert np.all(df['B'].tolist() == [None, 34, None, None, None])
assert np.all(df['C'].tolist() == [None, 543, None, None, None])
assert np.all(df['D'].tolist() == [1.2, 1.3, 1.4, 1.5, 1.6])
sheet = ipysheet.sheet(rows=4,
columns=4,
column_headers=['c0', 'c1', 'c2', 'c3'],
row_headers=['r0', 'r1', 'r2', 'r3'])
ipysheet.cell_range([
[2, 34, 543, 23],
[1, 1, 1, 1],
[2, 2, 222, 22],
[2, 0, 111, 11],
],
row_start=0,
column_start=0,
transpose=True)
df = ipysheet.to_dataframe(sheet)
assert np.all(df['c0'].tolist() == [2, 34, 543, 23])
assert np.all(df['c1'].tolist() == [1, 1, 1, 1])
assert np.all(df['c2'].tolist() == [2, 2, 222, 22])
assert np.all(df['c3'].tolist() == [2, 0, 111, 11])
sheet = ipysheet.sheet(rows=4,
columns=4,
column_headers=['t0', 't1', 't2', 't3'])
ipysheet.cell_range([
[2, 34, 543, 23],
[1, 1, 1, 1],
[2, 2, 222, 22],
[2, 0, 111, 11],
],
row_start=0,
column_start=0,
transpose=False)
df = ipysheet.to_dataframe(sheet)
assert np.all(df['t0'].tolist() == [2, 1, 2, 2])
assert np.all(df['t1'].tolist() == [34, 1, 2, 0])
assert np.all(df['t2'].tolist() == [543, 1, 222, 111])
assert np.all(df['t3'].tolist() == [23, 1, 22, 11])
sheet = ipysheet.sheet(rows=0, columns=0)
df = ipysheet.to_dataframe(sheet)
assert np.all(df == pd.DataFrame())
sheet = ipysheet.sheet(rows=4, columns=1)
ipysheet.column(0,
['2019/02/28', '2019/02/27', '2019/02/26', '2019/02/25'],
type='date')
df = ipysheet.to_dataframe(sheet)
assert [_format_date(x) for x in df['A'].tolist()
] == ['2019/02/28', '2019/02/27', '2019/02/26', '2019/02/25']
