def process(self, tides):
#print datetime.datetime.now(), "\t>>> update called",
df = None
if id(tides) != self._tides_id or tides is None:
logger.debug('clearing genCurveNodeCtrlWidget_v2 (Tide Components Section) on_process()')
#print 'setting tides components'
self._tides_id = id(tides)
if hasattr(self, '_ctrlWidget'):
self._ctrlWidget.clearTideComponents()
if tides is None:
#print '\t > returning None'
return {'sig': None}
self._ctrlWidget.on_tides_received(tides)
kwargs = self._ctrlWidget.prepareInputArguments()
# now prepare the amplitudes
kwargs['tides'] = {}
for i in xrange(len(tides)):
if not np.isnan(tides.iloc[i][kwargs['df_A']]) and np.isnan(tides.iloc[i][kwargs['df_omega']]):
continue #skipping 0-frequency amplitude
kwargs['tides'][str(i)] = {}
kwargs['tides'][str(i)]['A'] = tides.iloc[i][kwargs['df_A']]
kwargs['tides'][str(i)]['omega'] = tides.iloc[i][kwargs['df_omega']]
kwargs['tides'][str(i)]['phi'] = tides.iloc[i][kwargs['df_phi']]
# finally do the calculations
with BusyCursor():
#print '\t > doing the calculations'
if kwargs['eq'] == 'tide':
df = generate_tide(kwargs['t0'], kwargs['dt'], kwargs['tend'], components=kwargs['tides'], W=kwargs['W'], F=kwargs['F'], label=kwargs['label'], equation=kwargs['eq'])
elif kwargs['eq'] == 'ferris':
df = generate_tide(kwargs['t0'], kwargs['dt'], kwargs['tend'], components=kwargs['tides'], W=kwargs['W'], F=kwargs['F'], label=kwargs['label'], equation=kwargs['eq'],
D=kwargs['ferris']['D'], x=kwargs['x'])
elif kwargs['eq'] == 'xia':
df = generate_tide(kwargs['t0'], kwargs['dt'], kwargs['tend'], components=kwargs['tides'], W=kwargs['W'], F=kwargs['F'], label=kwargs['label'], equation=kwargs['eq'],
x=kwargs['x'],
alpha=kwargs['xia']['alpha'], beta=kwargs['xia']['beta'], theta=kwargs['xia']['theta'],
L=kwargs['xia']['L'], K1=kwargs['xia']['K1'], b1=kwargs['xia']['b1'],
K=kwargs['xia']['K'], b=kwargs['xia']['b'],
K_cap=kwargs['xia']['K_cap'], b_cap=kwargs['xia']['b_cap'])
elif kwargs['eq'] == 'song':
df = generate_tide(kwargs['t0'], kwargs['dt'], kwargs['tend'], components=kwargs['tides'], W=kwargs['W'], F=kwargs['F'], label=kwargs['label'], equation=kwargs['eq'],
x=kwargs['x'],
order=kwargs['song']['order'], b=kwargs['song']['b'], n_e=kwargs['song']['n_e'],
kf=kwargs['song']['K'],
b2msl=kwargs['song']['b2msl'])
else:
df = None
return {'sig': df}
def process(self, tides):
if tides is None:
return
if self._df_id != id(tides):
#print 'df new'
self._df_id = id(tides)
self.CW().param('tides_grp', 'n_sig').setValue(len(tides)-1)
self.CW().disconnect_valueChanged2upd(self.CW().param('tides_grp', 'A'))
self.CW().disconnect_valueChanged2upd(self.CW().param('tides_grp', 'omega'))
self.CW().disconnect_valueChanged2upd(self.CW().param('tides_grp', 'phi'))
colname = [col for col in tides.columns if isNumpyNumeric(tides[col].dtype)]
self.CW().param('tides_grp', 'A').setLimits(colname)
self.CW().param('tides_grp', 'omega').setLimits(colname)
self.CW().param('tides_grp', 'phi').setLimits(colname)
self.CW().param('tides_grp', 'A').setValue(colname[0])
self.CW().param('tides_grp', 'omega').setValue(colname[1])
self.CW().param('tides_grp', 'phi').setValue(colname[2])
self.CW().connect_valueChanged2upd(self.CW().param('tides_grp', 'A'))
self.CW().connect_valueChanged2upd(self.CW().param('tides_grp', 'omega'))
self.CW().connect_valueChanged2upd(self.CW().param('tides_grp', 'phi'))
self.CW().disconnect_valueChanged2upd(self.CW().param('W'))
W = tides[self.CW().p['tides_grp', 'A']][0] # 1st value from column `A`
self.CW().param('W').setValue(W)
self.CW().param('W').setDefault(W)
self.CW().connect_valueChanged2upd(self.CW().param('W'))
kwargs = self.CW().prepareInputArguments()
kwargs['tides'] = {}
for i in xrange(len(tides)):
if not np.isnan(tides.iloc[i][kwargs['df_A']]) and np.isnan(tides.iloc[i][kwargs['df_omega']]):
continue #skipping 0-frequency amplitude
kwargs['tides'][str(i)] = {}
kwargs['tides'][str(i)]['A'] = tides.iloc[i][kwargs['df_A']]
kwargs['tides'][str(i)]['omega'] = tides.iloc[i][kwargs['df_omega']]
kwargs['tides'][str(i)]['phi'] = tides.iloc[i][kwargs['df_phi']]
#print i, ': a={0}, omega={1}, phi={2}'.format(kwargs['tides'][str(i)]['A'], kwargs['tides'][str(i)]['omega'], kwargs['tides'][str(i)]['phi'] )
with BusyCursor():
if kwargs['eq'] == 'tide':
df = generate_tide(kwargs['t0'], kwargs['dt'], kwargs['tend'], components=kwargs['tides'], W=kwargs['W'], F=kwargs['F'], label=kwargs['label'], equation=kwargs['eq'])
elif kwargs['eq'] == 'ferris':
df = generate_tide(kwargs['t0'], kwargs['dt'], kwargs['tend'], components=kwargs['tides'], W=kwargs['W'], F=kwargs['F'], label=kwargs['label'], equation=kwargs['eq'],
D=kwargs['ferris']['D'], x=kwargs['ferris']['x'])
elif kwargs['eq'] == 'xia':
df = generate_tide(kwargs['t0'], kwargs['dt'], kwargs['tend'], components=kwargs['tides'], W=kwargs['W'], F=kwargs['F'], label=kwargs['label'], equation=kwargs['eq'],
x=kwargs['xia']['x'],
alpha=kwargs['xia']['alpha'], beta=kwargs['xia']['beta'], theta=kwargs['xia']['theta'],
L=kwargs['xia']['L'], K1=kwargs['xia']['K1'], b1=kwargs['xia']['b1'],
K=kwargs['xia']['K'], b=kwargs['xia']['b'],
K_cap=kwargs['xia']['K_cap'], b_cap=kwargs['xia']['b_cap'])
else:
df = None
return {'sig': df}
def process(self, tides):
if tides is None:
return
if self._df_id != id(tides):
# print 'df new'
self._df_id = id(tides)
self.CW().param("tides_grp", "n_sig").setValue(len(tides) - 1)
self.CW().disconnect_valueChanged2upd(self.CW().param("tides_grp", "A"))
self.CW().disconnect_valueChanged2upd(self.CW().param("tides_grp", "omega"))
self.CW().disconnect_valueChanged2upd(self.CW().param("tides_grp", "phi"))
colname = [col for col in tides.columns if isNumpyNumeric(tides[col].dtype)]
self.CW().param("tides_grp", "A").setLimits(colname)
self.CW().param("tides_grp", "omega").setLimits(colname)
self.CW().param("tides_grp", "phi").setLimits(colname)
self.CW().param("tides_grp", "A").setValue(colname[0])
self.CW().param("tides_grp", "omega").setValue(colname[1])
self.CW().param("tides_grp", "phi").setValue(colname[2])
self.CW().connect_valueChanged2upd(self.CW().param("tides_grp", "A"))
self.CW().connect_valueChanged2upd(self.CW().param("tides_grp", "omega"))
self.CW().connect_valueChanged2upd(self.CW().param("tides_grp", "phi"))
self.CW().disconnect_valueChanged2upd(self.CW().param("W"))
W = tides[self.CW().p["tides_grp", "A"]][0] # 1st value from column `A`
self.CW().param("W").setValue(W)
self.CW().param("W").setDefault(W)
self.CW().connect_valueChanged2upd(self.CW().param("W"))
kwargs = self.CW().prepareInputArguments()
kwargs["tides"] = {}
for i in xrange(len(tides)):
if not np.isnan(tides.iloc[i][kwargs["df_A"]]) and np.isnan(tides.iloc[i][kwargs["df_omega"]]):
continue # skipping 0-frequency amplitude
kwargs["tides"][str(i)] = {}
kwargs["tides"][str(i)]["A"] = tides.iloc[i][kwargs["df_A"]]
kwargs["tides"][str(i)]["omega"] = tides.iloc[i][kwargs["df_omega"]]
kwargs["tides"][str(i)]["phi"] = tides.iloc[i][kwargs["df_phi"]]
# print i, ': a={0}, omega={1}, phi={2}'.format(kwargs['tides'][str(i)]['A'], kwargs['tides'][str(i)]['omega'], kwargs['tides'][str(i)]['phi'] )
with BusyCursor():
if kwargs["eq"] == "tide":
df = generate_tide(
kwargs["t0"],
kwargs["dt"],
kwargs["tend"],
components=kwargs["tides"],
W=kwargs["W"],
F=kwargs["F"],
label=kwargs["label"],
equation=kwargs["eq"],
)
elif kwargs["eq"] == "ferris":
df = generate_tide(
kwargs["t0"],
kwargs["dt"],
kwargs["tend"],
components=kwargs["tides"],
W=kwargs["W"],
F=kwargs["F"],
label=kwargs["label"],
equation=kwargs["eq"],
D=kwargs["ferris"]["D"],
x=kwargs["ferris"]["x"],
)
elif kwargs["eq"] == "xia":
df = generate_tide(
kwargs["t0"],
kwargs["dt"],
kwargs["tend"],
components=kwargs["tides"],
W=kwargs["W"],
F=kwargs["F"],
label=kwargs["label"],
equation=kwargs["eq"],
x=kwargs["xia"]["x"],
alpha=kwargs["xia"]["alpha"],
beta=kwargs["xia"]["beta"],
theta=kwargs["xia"]["theta"],
L=kwargs["xia"]["L"],
K1=kwargs["xia"]["K1"],
b1=kwargs["xia"]["b1"],
K=kwargs["xia"]["K"],
b=kwargs["xia"]["b"],
K_cap=kwargs["xia"]["K_cap"],
b_cap=kwargs["xia"]["b_cap"],
)
else:
df = None
return {"sig": df}
def process(self, tides):
#print datetime.datetime.now(), "\t>>> update called",
df = None
if id(tides) != self._tides_id or tides is None:
logger.debug(
'clearing genCurveNodeCtrlWidget_v2 (Tide Components Section) on_process()'
)
#print 'setting tides components'
self._tides_id = id(tides)
if hasattr(self, '_ctrlWidget'):
self._ctrlWidget.clearTideComponents()
if tides is None:
#print '\t > returning None'
return {'sig': None}
self._ctrlWidget.on_tides_received(tides)
kwargs = self._ctrlWidget.prepareInputArguments()
# now prepare the amplitudes
kwargs['tides'] = {}
for i in xrange(len(tides)):
if not np.isnan(tides.iloc[i][kwargs['df_A']]) and np.isnan(
tides.iloc[i][kwargs['df_omega']]):
continue #skipping 0-frequency amplitude
kwargs['tides'][str(i)] = {}
kwargs['tides'][str(i)]['A'] = tides.iloc[i][kwargs['df_A']]
kwargs['tides'][str(i)]['omega'] = tides.iloc[i][
kwargs['df_omega']]
kwargs['tides'][str(i)]['phi'] = tides.iloc[i][kwargs['df_phi']]
# finally do the calculations
with BusyCursor():
#print '\t > doing the calculations'
if kwargs['eq'] == 'tide':
df = generate_tide(kwargs['t0'],
kwargs['dt'],
kwargs['tend'],
components=kwargs['tides'],
W=kwargs['W'],
F=kwargs['F'],
label=kwargs['label'],
equation=kwargs['eq'])
elif kwargs['eq'] == 'ferris':
df = generate_tide(kwargs['t0'],
kwargs['dt'],
kwargs['tend'],
components=kwargs['tides'],
W=kwargs['W'],
F=kwargs['F'],
label=kwargs['label'],
equation=kwargs['eq'],
D=kwargs['ferris']['D'],
x=kwargs['x'])
elif kwargs['eq'] == 'xia':
df = generate_tide(kwargs['t0'],
kwargs['dt'],
kwargs['tend'],
components=kwargs['tides'],
W=kwargs['W'],
F=kwargs['F'],
label=kwargs['label'],
equation=kwargs['eq'],
x=kwargs['x'],
alpha=kwargs['xia']['alpha'],
beta=kwargs['xia']['beta'],
theta=kwargs['xia']['theta'],
L=kwargs['xia']['L'],
K1=kwargs['xia']['K1'],
b1=kwargs['xia']['b1'],
K=kwargs['xia']['K'],
b=kwargs['xia']['b'],
K_cap=kwargs['xia']['K_cap'],
b_cap=kwargs['xia']['b_cap'])
elif kwargs['eq'] == 'song':
df = generate_tide(kwargs['t0'],
kwargs['dt'],
kwargs['tend'],
components=kwargs['tides'],
W=kwargs['W'],
F=kwargs['F'],
label=kwargs['label'],
equation=kwargs['eq'],
x=kwargs['x'],
order=kwargs['song']['order'],
b=kwargs['song']['b'],
n_e=kwargs['song']['n_e'],
kf=kwargs['song']['K'],
b2msl=kwargs['song']['b2msl'])
else:
df = None
return {'sig': df}
