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spacetelescope/synphot_refactor
synphot/observation.py
Observation.plot
def plot(self, binned=True, wavelengths=None, flux_unit=None, area=None, vegaspec=None, **kwargs): # pragma: no cover """Plot the observation. .. note:: Uses ``matplotlib``. Parameters ---------- binned : bool Plot data in native wavelengths if `False`. Else, plot binned data (default). wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` or `binset` is used, depending on ``binned``. flux_unit : str or `~astropy.units.core.Unit` or `None` Flux is converted to this unit for plotting. If not given, internal unit is used. area, vegaspec See :func:`~synphot.units.convert_flux`. kwargs : dict See :func:`synphot.spectrum.BaseSpectrum.plot`. Raises ------ synphot.exceptions.SynphotError Invalid inputs. """ if binned: w, y = self._get_binned_arrays(wavelengths, flux_unit, area=area, vegaspec=vegaspec) else: w, y = self._get_arrays(wavelengths, flux_unit=flux_unit, area=area, vegaspec=vegaspec) self._do_plot(w, y, **kwargs)
python
def plot(self, binned=True, wavelengths=None, flux_unit=None, area=None, vegaspec=None, **kwargs): # pragma: no cover """Plot the observation. .. note:: Uses ``matplotlib``. Parameters ---------- binned : bool Plot data in native wavelengths if `False`. Else, plot binned data (default). wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` or `binset` is used, depending on ``binned``. flux_unit : str or `~astropy.units.core.Unit` or `None` Flux is converted to this unit for plotting. If not given, internal unit is used. area, vegaspec See :func:`~synphot.units.convert_flux`. kwargs : dict See :func:`synphot.spectrum.BaseSpectrum.plot`. Raises ------ synphot.exceptions.SynphotError Invalid inputs. """ if binned: w, y = self._get_binned_arrays(wavelengths, flux_unit, area=area, vegaspec=vegaspec) else: w, y = self._get_arrays(wavelengths, flux_unit=flux_unit, area=area, vegaspec=vegaspec) self._do_plot(w, y, **kwargs)
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spacetelescope/synphot_refactor
synphot/observation.py
Observation.as_spectrum
def as_spectrum(self, binned=True, wavelengths=None): """Reduce the observation to an empirical source spectrum. An observation is a complex object with some restrictions on its capabilities. At times, it would be useful to work with the observation as a simple object that is easier to manipulate and takes up less memory. This is also useful for writing an observation as sampled spectrum out to a FITS file. Parameters ---------- binned : bool Write out data in native wavelengths if `False`. Else, write binned data (default). wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` or `binset` is used, depending on ``binned``. Returns ------- sp : `~synphot.spectrum.SourceSpectrum` Empirical source spectrum. """ if binned: w, y = self._get_binned_arrays( wavelengths, self._internal_flux_unit) else: w, y = self._get_arrays( wavelengths, flux_unit=self._internal_flux_unit) header = {'observation': str(self), 'binned': binned} return SourceSpectrum(Empirical1D, points=w, lookup_table=y, meta={'header': header})
python
def as_spectrum(self, binned=True, wavelengths=None): """Reduce the observation to an empirical source spectrum. An observation is a complex object with some restrictions on its capabilities. At times, it would be useful to work with the observation as a simple object that is easier to manipulate and takes up less memory. This is also useful for writing an observation as sampled spectrum out to a FITS file. Parameters ---------- binned : bool Write out data in native wavelengths if `False`. Else, write binned data (default). wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` or `binset` is used, depending on ``binned``. Returns ------- sp : `~synphot.spectrum.SourceSpectrum` Empirical source spectrum. """ if binned: w, y = self._get_binned_arrays( wavelengths, self._internal_flux_unit) else: w, y = self._get_arrays( wavelengths, flux_unit=self._internal_flux_unit) header = {'observation': str(self), 'binned': binned} return SourceSpectrum(Empirical1D, points=w, lookup_table=y, meta={'header': header})
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Julius2342/pyvlx
pyvlx/set_node_name.py
SetNodeName.handle_frame
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameSetNodeNameConfirmation): return False self.success = frame.status == SetNodeNameConfirmationStatus.OK return True
python
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameSetNodeNameConfirmation): return False self.success = frame.status == SetNodeNameConfirmationStatus.OK return True
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Julius2342/pyvlx
pyvlx/api_event.py
ApiEvent.do_api_call
async def do_api_call(self): """Start. Sending and waiting for answer.""" self.pyvlx.connection.register_frame_received_cb( self.response_rec_callback) await self.send_frame() await self.start_timeout() await self.response_received_or_timeout.wait() await self.stop_timeout() self.pyvlx.connection.unregister_frame_received_cb(self.response_rec_callback)
python
async def do_api_call(self): """Start. Sending and waiting for answer.""" self.pyvlx.connection.register_frame_received_cb( self.response_rec_callback) await self.send_frame() await self.start_timeout() await self.response_received_or_timeout.wait() await self.stop_timeout() self.pyvlx.connection.unregister_frame_received_cb(self.response_rec_callback)
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Julius2342/pyvlx
pyvlx/api_event.py
ApiEvent.start_timeout
async def start_timeout(self): """Start timeout.""" self.timeout_handle = self.pyvlx.connection.loop.call_later( self.timeout_in_seconds, self.timeout)
python
async def start_timeout(self): """Start timeout.""" self.timeout_handle = self.pyvlx.connection.loop.call_later( self.timeout_in_seconds, self.timeout)
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Julius2342/pyvlx
old_api/examples/example.py
main
async def main(): """Load devices and scenes, run first scene.""" pyvlx = PyVLX('pyvlx.yaml') # Alternative: # pyvlx = PyVLX(host="192.168.2.127", password="velux123", timeout=60) await pyvlx.load_devices() print(pyvlx.devices[1]) print(pyvlx.devices['Fenster 4']) await pyvlx.load_scenes() print(pyvlx.scenes[0]) print(pyvlx.scenes['Bath Closed']) # opening/ closing windows by running scenes, yay! await pyvlx.scenes[1].run() await pyvlx.disconnect()
python
async def main(): """Load devices and scenes, run first scene.""" pyvlx = PyVLX('pyvlx.yaml') # Alternative: # pyvlx = PyVLX(host="192.168.2.127", password="velux123", timeout=60) await pyvlx.load_devices() print(pyvlx.devices[1]) print(pyvlx.devices['Fenster 4']) await pyvlx.load_scenes() print(pyvlx.scenes[0]) print(pyvlx.scenes['Bath Closed']) # opening/ closing windows by running scenes, yay! await pyvlx.scenes[1].run() await pyvlx.disconnect()
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Julius2342/pyvlx
pyvlx/on_off_switch.py
OnOffSwitch.set_state
async def set_state(self, parameter): """Set switch to desired state.""" command_send = CommandSend(pyvlx=self.pyvlx, node_id=self.node_id, parameter=parameter) await command_send.do_api_call() if not command_send.success: raise PyVLXException("Unable to send command") self.parameter = parameter await self.after_update()
python
async def set_state(self, parameter): """Set switch to desired state.""" command_send = CommandSend(pyvlx=self.pyvlx, node_id=self.node_id, parameter=parameter) await command_send.do_api_call() if not command_send.success: raise PyVLXException("Unable to send command") self.parameter = parameter await self.after_update()
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spacetelescope/synphot_refactor
synphot/reddening.py
etau_madau
def etau_madau(wave, z, **kwargs): """Madau 1995 extinction for a galaxy at given redshift. This is the Lyman-alpha prescription from the photo-z code BPZ. The Lyman-alpha forest approximately has an effective "throughput" which is a function of redshift and rest-frame wavelength. One would multiply the SEDs by this factor before passing it through an instrument filter. This approximation is from Footnote 3 of :ref:`Madau et al. (1995) <synphot-ref-madau1995>`. This is claimed accurate to 5%. The scatter in this factor (due to different lines of sight) is huge, as shown in Madau's Fig. 3 (top panel); The figure's bottom panel shows a redshifted version of the "exact" prescription. Parameters ---------- wave : array-like or `~astropy.units.quantity.Quantity` Redshifted wavelength values. Non-redshifted wavelength is ``wave / (1 + z)``. z : number Redshift. kwargs : dict Equivalencies for unit conversion, see :func:`~synphot.units.validate_quantity`. Returns ------- extcurve : `ExtinctionCurve` Extinction curve to apply to the redshifted spectrum. """ if not isinstance(z, numbers.Real): raise exceptions.SynphotError( 'Redshift must be a real scalar number.') if np.isscalar(wave) or len(wave) <= 1: raise exceptions.SynphotError('Wavelength has too few data points') wave = units.validate_quantity(wave, u.AA, **kwargs).value ll = 912.0 c = np.array([3.6e-3, 1.7e-3, 1.2e-3, 9.3e-4]) el = np.array([1216, 1026, 973, 950], dtype=np.float) # noqa tau = np.zeros_like(wave, dtype=np.float) xe = 1.0 + z # Lyman series for i in range(len(el)): tau = np.where(wave <= el[i] * xe, tau + c[i] * (wave / el[i]) ** 3.46, tau) # Photoelectric absorption xc = wave / ll xc3 = xc ** 3 tau = np.where(wave <= ll * xe, (tau + 0.25 * xc3 * (xe ** 0.46 - xc ** 0.46) + 9.4 * xc ** 1.5 * (xe ** 0.18 - xc ** 0.18) - 0.7 * xc3 * (xc ** (-1.32) - xe ** (-1.32)) - 0.023 * (xe ** 1.68 - xc ** 1.68)), tau) thru = np.where(tau > 700., 0., np.exp(-tau)) meta = {'descrip': 'Madau 1995 extinction for z={0}'.format(z)} return ExtinctionCurve(ExtinctionModel1D, points=wave, lookup_table=thru, meta=meta)
python
def etau_madau(wave, z, **kwargs): """Madau 1995 extinction for a galaxy at given redshift. This is the Lyman-alpha prescription from the photo-z code BPZ. The Lyman-alpha forest approximately has an effective "throughput" which is a function of redshift and rest-frame wavelength. One would multiply the SEDs by this factor before passing it through an instrument filter. This approximation is from Footnote 3 of :ref:`Madau et al. (1995) <synphot-ref-madau1995>`. This is claimed accurate to 5%. The scatter in this factor (due to different lines of sight) is huge, as shown in Madau's Fig. 3 (top panel); The figure's bottom panel shows a redshifted version of the "exact" prescription. Parameters ---------- wave : array-like or `~astropy.units.quantity.Quantity` Redshifted wavelength values. Non-redshifted wavelength is ``wave / (1 + z)``. z : number Redshift. kwargs : dict Equivalencies for unit conversion, see :func:`~synphot.units.validate_quantity`. Returns ------- extcurve : `ExtinctionCurve` Extinction curve to apply to the redshifted spectrum. """ if not isinstance(z, numbers.Real): raise exceptions.SynphotError( 'Redshift must be a real scalar number.') if np.isscalar(wave) or len(wave) <= 1: raise exceptions.SynphotError('Wavelength has too few data points') wave = units.validate_quantity(wave, u.AA, **kwargs).value ll = 912.0 c = np.array([3.6e-3, 1.7e-3, 1.2e-3, 9.3e-4]) el = np.array([1216, 1026, 973, 950], dtype=np.float) # noqa tau = np.zeros_like(wave, dtype=np.float) xe = 1.0 + z # Lyman series for i in range(len(el)): tau = np.where(wave <= el[i] * xe, tau + c[i] * (wave / el[i]) ** 3.46, tau) # Photoelectric absorption xc = wave / ll xc3 = xc ** 3 tau = np.where(wave <= ll * xe, (tau + 0.25 * xc3 * (xe ** 0.46 - xc ** 0.46) + 9.4 * xc ** 1.5 * (xe ** 0.18 - xc ** 0.18) - 0.7 * xc3 * (xc ** (-1.32) - xe ** (-1.32)) - 0.023 * (xe ** 1.68 - xc ** 1.68)), tau) thru = np.where(tau > 700., 0., np.exp(-tau)) meta = {'descrip': 'Madau 1995 extinction for z={0}'.format(z)} return ExtinctionCurve(ExtinctionModel1D, points=wave, lookup_table=thru, meta=meta)
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Madau 1995 extinction for a galaxy at given redshift. This is the Lyman-alpha prescription from the photo-z code BPZ. The Lyman-alpha forest approximately has an effective "throughput" which is a function of redshift and rest-frame wavelength. One would multiply the SEDs by this factor before passing it through an instrument filter. This approximation is from Footnote 3 of :ref:`Madau et al. (1995) <synphot-ref-madau1995>`. This is claimed accurate to 5%. The scatter in this factor (due to different lines of sight) is huge, as shown in Madau's Fig. 3 (top panel); The figure's bottom panel shows a redshifted version of the "exact" prescription. Parameters ---------- wave : array-like or `~astropy.units.quantity.Quantity` Redshifted wavelength values. Non-redshifted wavelength is ``wave / (1 + z)``. z : number Redshift. kwargs : dict Equivalencies for unit conversion, see :func:`~synphot.units.validate_quantity`. Returns ------- extcurve : `ExtinctionCurve` Extinction curve to apply to the redshifted spectrum.
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spacetelescope/synphot_refactor
synphot/reddening.py
ReddeningLaw.extinction_curve
def extinction_curve(self, ebv, wavelengths=None): """Generate extinction curve. .. math:: A(V) = R(V) \\; \\times \\; E(B-V) THRU = 10^{-0.4 \\; A(V)} Parameters ---------- ebv : float or `~astropy.units.quantity.Quantity` :math:`E(B-V)` value in magnitude. wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` is used. Returns ------- extcurve : `ExtinctionCurve` Empirical extinction curve. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if isinstance(ebv, u.Quantity) and ebv.unit.decompose() == u.mag: ebv = ebv.value elif not isinstance(ebv, numbers.Real): raise exceptions.SynphotError('E(B-V)={0} is invalid.'.format(ebv)) x = self._validate_wavelengths(wavelengths).value y = 10 ** (-0.4 * self(x).value * ebv) header = { 'E(B-V)': ebv, 'ReddeningLaw': self.meta.get('expr', 'unknown')} return ExtinctionCurve(ExtinctionModel1D, points=x, lookup_table=y, meta={'header': header})
python
def extinction_curve(self, ebv, wavelengths=None): """Generate extinction curve. .. math:: A(V) = R(V) \\; \\times \\; E(B-V) THRU = 10^{-0.4 \\; A(V)} Parameters ---------- ebv : float or `~astropy.units.quantity.Quantity` :math:`E(B-V)` value in magnitude. wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` is used. Returns ------- extcurve : `ExtinctionCurve` Empirical extinction curve. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if isinstance(ebv, u.Quantity) and ebv.unit.decompose() == u.mag: ebv = ebv.value elif not isinstance(ebv, numbers.Real): raise exceptions.SynphotError('E(B-V)={0} is invalid.'.format(ebv)) x = self._validate_wavelengths(wavelengths).value y = 10 ** (-0.4 * self(x).value * ebv) header = { 'E(B-V)': ebv, 'ReddeningLaw': self.meta.get('expr', 'unknown')} return ExtinctionCurve(ExtinctionModel1D, points=x, lookup_table=y, meta={'header': header})
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Generate extinction curve. .. math:: A(V) = R(V) \\; \\times \\; E(B-V) THRU = 10^{-0.4 \\; A(V)} Parameters ---------- ebv : float or `~astropy.units.quantity.Quantity` :math:`E(B-V)` value in magnitude. wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` is used. Returns ------- extcurve : `ExtinctionCurve` Empirical extinction curve. Raises ------ synphot.exceptions.SynphotError Invalid input.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/reddening.py#L42-L84
spacetelescope/synphot_refactor
synphot/reddening.py
ReddeningLaw.to_fits
def to_fits(self, filename, wavelengths=None, **kwargs): """Write the reddening law to a FITS file. :math:`R(V)` column is automatically named 'Av/E(B-V)'. Parameters ---------- filename : str Output filename. wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` is used. kwargs : dict Keywords accepted by :func:`~synphot.specio.write_fits_spec`. """ w, y = self._get_arrays(wavelengths) kwargs['flux_col'] = 'Av/E(B-V)' kwargs['flux_unit'] = self._internal_flux_unit # No need to trim/pad zeroes, unless user chooses to do so. if 'pad_zero_ends' not in kwargs: kwargs['pad_zero_ends'] = False if 'trim_zero' not in kwargs: kwargs['trim_zero'] = False # There are some standard keywords that should be added # to the extension header. bkeys = {'tdisp1': 'G15.7', 'tdisp2': 'G15.7'} if 'expr' in self.meta: bkeys['expr'] = (self.meta['expr'], 'synphot expression') if 'ext_header' in kwargs: kwargs['ext_header'].update(bkeys) else: kwargs['ext_header'] = bkeys specio.write_fits_spec(filename, w, y, **kwargs)
python
def to_fits(self, filename, wavelengths=None, **kwargs): """Write the reddening law to a FITS file. :math:`R(V)` column is automatically named 'Av/E(B-V)'. Parameters ---------- filename : str Output filename. wavelengths : array-like, `~astropy.units.quantity.Quantity`, or `None` Wavelength values for sampling. If not a Quantity, assumed to be in Angstrom. If `None`, ``self.waveset`` is used. kwargs : dict Keywords accepted by :func:`~synphot.specio.write_fits_spec`. """ w, y = self._get_arrays(wavelengths) kwargs['flux_col'] = 'Av/E(B-V)' kwargs['flux_unit'] = self._internal_flux_unit # No need to trim/pad zeroes, unless user chooses to do so. if 'pad_zero_ends' not in kwargs: kwargs['pad_zero_ends'] = False if 'trim_zero' not in kwargs: kwargs['trim_zero'] = False # There are some standard keywords that should be added # to the extension header. bkeys = {'tdisp1': 'G15.7', 'tdisp2': 'G15.7'} if 'expr' in self.meta: bkeys['expr'] = (self.meta['expr'], 'synphot expression') if 'ext_header' in kwargs: kwargs['ext_header'].update(bkeys) else: kwargs['ext_header'] = bkeys specio.write_fits_spec(filename, w, y, **kwargs)
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/reddening.py#L86-L128
spacetelescope/synphot_refactor
synphot/reddening.py
ReddeningLaw.from_file
def from_file(cls, filename, **kwargs): """Create a reddening law from file. If filename has 'fits' or 'fit' suffix, it is read as FITS. Otherwise, it is read as ASCII. Parameters ---------- filename : str Reddening law filename. kwargs : dict Keywords acceptable by :func:`~synphot.specio.read_fits_spec` (if FITS) or :func:`~synphot.specio.read_ascii_spec` (if ASCII). Returns ------- redlaw : `ReddeningLaw` Empirical reddening law. """ if 'flux_unit' not in kwargs: kwargs['flux_unit'] = cls._internal_flux_unit if ((filename.endswith('fits') or filename.endswith('fit')) and 'flux_col' not in kwargs): kwargs['flux_col'] = 'Av/E(B-V)' header, wavelengths, rvs = specio.read_spec(filename, **kwargs) return cls(Empirical1D, points=wavelengths, lookup_table=rvs, meta={'header': header})
python
def from_file(cls, filename, **kwargs): """Create a reddening law from file. If filename has 'fits' or 'fit' suffix, it is read as FITS. Otherwise, it is read as ASCII. Parameters ---------- filename : str Reddening law filename. kwargs : dict Keywords acceptable by :func:`~synphot.specio.read_fits_spec` (if FITS) or :func:`~synphot.specio.read_ascii_spec` (if ASCII). Returns ------- redlaw : `ReddeningLaw` Empirical reddening law. """ if 'flux_unit' not in kwargs: kwargs['flux_unit'] = cls._internal_flux_unit if ((filename.endswith('fits') or filename.endswith('fit')) and 'flux_col' not in kwargs): kwargs['flux_col'] = 'Av/E(B-V)' header, wavelengths, rvs = specio.read_spec(filename, **kwargs) return cls(Empirical1D, points=wavelengths, lookup_table=rvs, meta={'header': header})
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/reddening.py#L131-L163
spacetelescope/synphot_refactor
synphot/reddening.py
ReddeningLaw.from_extinction_model
def from_extinction_model(cls, modelname, **kwargs): """Load :ref:`pre-defined extinction model <synphot_reddening>`. Parameters ---------- modelname : str Extinction model name. Choose from 'lmc30dor', 'lmcavg', 'mwavg', 'mwdense', 'mwrv21', 'mwrv40', 'smcbar', or 'xgalsb'. kwargs : dict Keywords acceptable by :func:`~synphot.specio.read_remote_spec`. Returns ------- redlaw : `ReddeningLaw` Empirical reddening law. Raises ------ synphot.exceptions.SynphotError Invalid extinction model name. """ modelname = modelname.lower() # Select filename based on model name if modelname == 'lmc30dor': cfgitem = Conf.lmc30dor_file elif modelname == 'lmcavg': cfgitem = Conf.lmcavg_file elif modelname == 'mwavg': cfgitem = Conf.mwavg_file elif modelname == 'mwdense': cfgitem = Conf.mwdense_file elif modelname == 'mwrv21': cfgitem = Conf.mwrv21_file elif modelname == 'mwrv40': cfgitem = Conf.mwrv40_file elif modelname == 'smcbar': cfgitem = Conf.smcbar_file elif modelname == 'xgalsb': cfgitem = Conf.xgal_file else: raise exceptions.SynphotError( 'Extinction model {0} is invalid.'.format(modelname)) filename = cfgitem() if 'flux_unit' not in kwargs: kwargs['flux_unit'] = cls._internal_flux_unit if ((filename.endswith('fits') or filename.endswith('fit')) and 'flux_col' not in kwargs): kwargs['flux_col'] = 'Av/E(B-V)' header, wavelengths, rvs = specio.read_remote_spec(filename, **kwargs) header['filename'] = filename header['descrip'] = cfgitem.description meta = {'header': header, 'expr': modelname} return cls(Empirical1D, points=wavelengths, lookup_table=rvs, meta=meta)
python
def from_extinction_model(cls, modelname, **kwargs): """Load :ref:`pre-defined extinction model <synphot_reddening>`. Parameters ---------- modelname : str Extinction model name. Choose from 'lmc30dor', 'lmcavg', 'mwavg', 'mwdense', 'mwrv21', 'mwrv40', 'smcbar', or 'xgalsb'. kwargs : dict Keywords acceptable by :func:`~synphot.specio.read_remote_spec`. Returns ------- redlaw : `ReddeningLaw` Empirical reddening law. Raises ------ synphot.exceptions.SynphotError Invalid extinction model name. """ modelname = modelname.lower() # Select filename based on model name if modelname == 'lmc30dor': cfgitem = Conf.lmc30dor_file elif modelname == 'lmcavg': cfgitem = Conf.lmcavg_file elif modelname == 'mwavg': cfgitem = Conf.mwavg_file elif modelname == 'mwdense': cfgitem = Conf.mwdense_file elif modelname == 'mwrv21': cfgitem = Conf.mwrv21_file elif modelname == 'mwrv40': cfgitem = Conf.mwrv40_file elif modelname == 'smcbar': cfgitem = Conf.smcbar_file elif modelname == 'xgalsb': cfgitem = Conf.xgal_file else: raise exceptions.SynphotError( 'Extinction model {0} is invalid.'.format(modelname)) filename = cfgitem() if 'flux_unit' not in kwargs: kwargs['flux_unit'] = cls._internal_flux_unit if ((filename.endswith('fits') or filename.endswith('fit')) and 'flux_col' not in kwargs): kwargs['flux_col'] = 'Av/E(B-V)' header, wavelengths, rvs = specio.read_remote_spec(filename, **kwargs) header['filename'] = filename header['descrip'] = cfgitem.description meta = {'header': header, 'expr': modelname} return cls(Empirical1D, points=wavelengths, lookup_table=rvs, meta=meta)
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train
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Julius2342/pyvlx
pyvlx/get_version.py
GetVersion.handle_frame
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameGetVersionConfirmation): return False self.version = frame.version self.success = True return True
python
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameGetVersionConfirmation): return False self.version = frame.version self.success = True return True
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Handle incoming API frame, return True if this was the expected frame.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/get_version.py#L15-L21
Julius2342/pyvlx
pyvlx/frames/frame.py
FrameBase.validate_payload_len
def validate_payload_len(self, payload): """Validate payload len.""" if not hasattr(self, "PAYLOAD_LEN"): # No fixed payload len, e.g. within FrameGetSceneListNotification return # pylint: disable=no-member if len(payload) != self.PAYLOAD_LEN: raise PyVLXException("Invalid payload len", expected_len=self.PAYLOAD_LEN, current_len=len(payload), frame_type=type(self).__name__)
python
def validate_payload_len(self, payload): """Validate payload len.""" if not hasattr(self, "PAYLOAD_LEN"): # No fixed payload len, e.g. within FrameGetSceneListNotification return # pylint: disable=no-member if len(payload) != self.PAYLOAD_LEN: raise PyVLXException("Invalid payload len", expected_len=self.PAYLOAD_LEN, current_len=len(payload), frame_type=type(self).__name__)
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame.py#L22-L29
Julius2342/pyvlx
pyvlx/frames/frame.py
FrameBase.build_frame
def build_frame(command, payload): """Build raw bytes from command and payload.""" packet_length = 2 + len(payload) + 1 ret = struct.pack("BB", 0, packet_length) ret += struct.pack(">H", command.value) ret += payload ret += struct.pack("B", calc_crc(ret)) return ret
python
def build_frame(command, payload): """Build raw bytes from command and payload.""" packet_length = 2 + len(payload) + 1 ret = struct.pack("BB", 0, packet_length) ret += struct.pack(">H", command.value) ret += payload ret += struct.pack("B", calc_crc(ret)) return ret
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame.py#L45-L52
Julius2342/pyvlx
pyvlx/scene.py
Scene.run
async def run(self, wait_for_completion=True): """Run scene. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ activate_scene = ActivateScene( pyvlx=self.pyvlx, wait_for_completion=wait_for_completion, scene_id=self.scene_id) await activate_scene.do_api_call() if not activate_scene.success: raise PyVLXException("Unable to activate scene")
python
async def run(self, wait_for_completion=True): """Run scene. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ activate_scene = ActivateScene( pyvlx=self.pyvlx, wait_for_completion=wait_for_completion, scene_id=self.scene_id) await activate_scene.do_api_call() if not activate_scene.success: raise PyVLXException("Unable to activate scene")
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Run scene. Parameters: * wait_for_completion: If set, function will return after device has reached target position.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/scene.py#L23-L37
Julius2342/pyvlx
old_api/pyvlx/scenes.py
Scenes.add
def add(self, scene): """Add scene.""" if not isinstance(scene, Scene): raise TypeError() self.__scenes.append(scene)
python
def add(self, scene): """Add scene.""" if not isinstance(scene, Scene): raise TypeError() self.__scenes.append(scene)
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/old_api/pyvlx/scenes.py#L33-L37
Julius2342/pyvlx
old_api/pyvlx/scenes.py
Scenes.load
async def load(self): """Load scenes from KLF 200.""" json_response = await self.pyvlx.interface.api_call('scenes', 'get') self.data_import(json_response)
python
async def load(self): """Load scenes from KLF 200.""" json_response = await self.pyvlx.interface.api_call('scenes', 'get') self.data_import(json_response)
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Julius2342/pyvlx
old_api/pyvlx/scenes.py
Scenes.data_import
def data_import(self, json_response): """Import scenes from JSON response.""" if 'data' not in json_response: raise PyVLXException('no element data found: {0}'.format( json.dumps(json_response))) data = json_response['data'] for item in data: self.load_scene(item)
python
def data_import(self, json_response): """Import scenes from JSON response.""" if 'data' not in json_response: raise PyVLXException('no element data found: {0}'.format( json.dumps(json_response))) data = json_response['data'] for item in data: self.load_scene(item)
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Import scenes from JSON response.
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train
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Julius2342/pyvlx
old_api/pyvlx/scenes.py
Scenes.load_scene
def load_scene(self, item): """Load scene from json.""" scene = Scene.from_config(self.pyvlx, item) self.add(scene)
python
def load_scene(self, item): """Load scene from json.""" scene = Scene.from_config(self.pyvlx, item) self.add(scene)
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train
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Julius2342/pyvlx
pyvlx/get_state.py
GetState.handle_frame
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameGetStateConfirmation): return False self.success = True self.gateway_state = frame.gateway_state self.gateway_sub_state = frame.gateway_sub_state return True
python
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameGetStateConfirmation): return False self.success = True self.gateway_state = frame.gateway_state self.gateway_sub_state = frame.gateway_sub_state return True
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Handle incoming API frame, return True if this was the expected frame.
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train
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Julius2342/pyvlx
pyvlx/alias_array.py
AliasArray.parse_raw
def parse_raw(self, raw): """Parse alias array from raw bytes.""" if not isinstance(raw, bytes): raise PyVLXException("AliasArray::invalid_type_if_raw", type_raw=type(raw)) if len(raw) != 21: raise PyVLXException("AliasArray::invalid_size", size=len(raw)) nbr_of_alias = raw[0] if nbr_of_alias > 5: raise PyVLXException("AliasArray::invalid_nbr_of_alias", nbr_of_alias=nbr_of_alias) for i in range(0, nbr_of_alias): self.alias_array_.append((raw[i*4+1:i*4+3], raw[i*4+3:i*4+5]))
python
def parse_raw(self, raw): """Parse alias array from raw bytes.""" if not isinstance(raw, bytes): raise PyVLXException("AliasArray::invalid_type_if_raw", type_raw=type(raw)) if len(raw) != 21: raise PyVLXException("AliasArray::invalid_size", size=len(raw)) nbr_of_alias = raw[0] if nbr_of_alias > 5: raise PyVLXException("AliasArray::invalid_nbr_of_alias", nbr_of_alias=nbr_of_alias) for i in range(0, nbr_of_alias): self.alias_array_.append((raw[i*4+1:i*4+3], raw[i*4+3:i*4+5]))
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train
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Julius2342/pyvlx
pyvlx/slip.py
decode
def decode(raw): """Decode SLIP message.""" return raw \ .replace(bytes([SLIP_ESC, SLIP_ESC_END]), bytes([SLIP_END])) \ .replace(bytes([SLIP_ESC, SLIP_ESC_ESC]), bytes([SLIP_ESC]))
python
def decode(raw): """Decode SLIP message.""" return raw \ .replace(bytes([SLIP_ESC, SLIP_ESC_END]), bytes([SLIP_END])) \ .replace(bytes([SLIP_ESC, SLIP_ESC_ESC]), bytes([SLIP_ESC]))
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Decode SLIP message.
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Julius2342/pyvlx
pyvlx/slip.py
encode
def encode(raw): """Encode SLIP message.""" return raw \ .replace(bytes([SLIP_ESC]), bytes([SLIP_ESC, SLIP_ESC_ESC])) \ .replace(bytes([SLIP_END]), bytes([SLIP_ESC, SLIP_ESC_END]))
python
def encode(raw): """Encode SLIP message.""" return raw \ .replace(bytes([SLIP_ESC]), bytes([SLIP_ESC, SLIP_ESC_ESC])) \ .replace(bytes([SLIP_END]), bytes([SLIP_ESC, SLIP_ESC_END]))
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Encode SLIP message.
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train
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Julius2342/pyvlx
pyvlx/slip.py
get_next_slip
def get_next_slip(raw): """ Get the next slip packet from raw data. Returns the extracted packet plus the raw data with the remaining data stream. """ if not is_slip(raw): return None, raw length = raw[1:].index(SLIP_END) slip_packet = decode(raw[1:length+1]) new_raw = raw[length+2:] return slip_packet, new_raw
python
def get_next_slip(raw): """ Get the next slip packet from raw data. Returns the extracted packet plus the raw data with the remaining data stream. """ if not is_slip(raw): return None, raw length = raw[1:].index(SLIP_END) slip_packet = decode(raw[1:length+1]) new_raw = raw[length+2:] return slip_packet, new_raw
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Get the next slip packet from raw data. Returns the extracted packet plus the raw data with the remaining data stream.
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Julius2342/pyvlx
pyvlx/set_utc.py
set_utc
async def set_utc(pyvlx): """Enable house status monitor.""" setutc = SetUTC(pyvlx=pyvlx) await setutc.do_api_call() if not setutc.success: raise PyVLXException("Unable to set utc.")
python
async def set_utc(pyvlx): """Enable house status monitor.""" setutc = SetUTC(pyvlx=pyvlx) await setutc.do_api_call() if not setutc.success: raise PyVLXException("Unable to set utc.")
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Enable house status monitor.
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Julius2342/pyvlx
pyvlx/set_utc.py
SetUTC.handle_frame
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameSetUTCConfirmation): return False self.success = True return True
python
async def handle_frame(self, frame): """Handle incoming API frame, return True if this was the expected frame.""" if not isinstance(frame, FrameSetUTCConfirmation): return False self.success = True return True
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spacetelescope/synphot_refactor
synphot/binning.py
_slow_calcbinflux
def _slow_calcbinflux(len_binwave, i_beg, i_end, avflux, deltaw): """Python implementation of ``calcbinflux``. This is only used if ``synphot.synphot_utils`` C-extension import fails. See docstrings.py """ binflux = np.empty(shape=(len_binwave, ), dtype=np.float64) intwave = np.empty(shape=(len_binwave, ), dtype=np.float64) # Note that, like all Python striding, the range over which # we integrate is [first:last). for i in range(len(i_beg)): first = i_beg[i] last = i_end[i] cur_dw = deltaw[first:last] intwave[i] = cur_dw.sum() binflux[i] = np.sum(avflux[first:last] * cur_dw) / intwave[i] return binflux, intwave
python
def _slow_calcbinflux(len_binwave, i_beg, i_end, avflux, deltaw): """Python implementation of ``calcbinflux``. This is only used if ``synphot.synphot_utils`` C-extension import fails. See docstrings.py """ binflux = np.empty(shape=(len_binwave, ), dtype=np.float64) intwave = np.empty(shape=(len_binwave, ), dtype=np.float64) # Note that, like all Python striding, the range over which # we integrate is [first:last). for i in range(len(i_beg)): first = i_beg[i] last = i_end[i] cur_dw = deltaw[first:last] intwave[i] = cur_dw.sum() binflux[i] = np.sum(avflux[first:last] * cur_dw) / intwave[i] return binflux, intwave
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spacetelescope/synphot_refactor
synphot/binning.py
calculate_bin_edges
def calculate_bin_edges(centers): """Calculate the edges of wavelength bins given the centers. The algorithm calculates bin edges as the midpoints between bin centers and treats the first and last bins as symmetric about their centers. Parameters ---------- centers : array-like or `~astropy.units.quantity.Quantity` Sequence of bin centers. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- edges : `~astropy.units.quantity.Quantity` Array of bin edges. Will be 1D, have one more value than ``centers``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if not isinstance(centers, u.Quantity): centers = centers * u.AA if centers.ndim != 1: raise exceptions.SynphotError('Bin centers must be 1D array.') if centers.size < 2: raise exceptions.SynphotError( 'Bin centers must have at least two values.') edges = np.empty(centers.size + 1, dtype=np.float64) edges[1:-1] = (centers.value[1:] + centers.value[:-1]) * 0.5 # Compute the first and last by making them symmetric edges[0] = 2.0 * centers.value[0] - edges[1] edges[-1] = 2.0 * centers.value[-1] - edges[-2] return edges * centers.unit
python
def calculate_bin_edges(centers): """Calculate the edges of wavelength bins given the centers. The algorithm calculates bin edges as the midpoints between bin centers and treats the first and last bins as symmetric about their centers. Parameters ---------- centers : array-like or `~astropy.units.quantity.Quantity` Sequence of bin centers. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- edges : `~astropy.units.quantity.Quantity` Array of bin edges. Will be 1D, have one more value than ``centers``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if not isinstance(centers, u.Quantity): centers = centers * u.AA if centers.ndim != 1: raise exceptions.SynphotError('Bin centers must be 1D array.') if centers.size < 2: raise exceptions.SynphotError( 'Bin centers must have at least two values.') edges = np.empty(centers.size + 1, dtype=np.float64) edges[1:-1] = (centers.value[1:] + centers.value[:-1]) * 0.5 # Compute the first and last by making them symmetric edges[0] = 2.0 * centers.value[0] - edges[1] edges[-1] = 2.0 * centers.value[-1] - edges[-2] return edges * centers.unit
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train
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spacetelescope/synphot_refactor
synphot/binning.py
calculate_bin_widths
def calculate_bin_widths(edges): """Calculate the widths of wavelengths bins given their edges. Parameters ---------- edges : array-like or `~astropy.units.quantity.Quantity` Sequence of bin edges. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- widths : `~astropy.units.quantity.Quantity` Array of bin widths. Will be 1D, have one less value than ``edges``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if not isinstance(edges, u.Quantity): edges = edges * u.AA if edges.ndim != 1: raise exceptions.SynphotError('Bin edges must be 1D array.') if edges.size < 2: raise exceptions.SynphotError( 'Bin edges must have at least two values.') return np.abs(edges[1:] - edges[:-1])
python
def calculate_bin_widths(edges): """Calculate the widths of wavelengths bins given their edges. Parameters ---------- edges : array-like or `~astropy.units.quantity.Quantity` Sequence of bin edges. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- widths : `~astropy.units.quantity.Quantity` Array of bin widths. Will be 1D, have one less value than ``edges``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if not isinstance(edges, u.Quantity): edges = edges * u.AA if edges.ndim != 1: raise exceptions.SynphotError('Bin edges must be 1D array.') if edges.size < 2: raise exceptions.SynphotError( 'Bin edges must have at least two values.') return np.abs(edges[1:] - edges[:-1])
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Calculate the widths of wavelengths bins given their edges. Parameters ---------- edges : array-like or `~astropy.units.quantity.Quantity` Sequence of bin edges. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- widths : `~astropy.units.quantity.Quantity` Array of bin widths. Will be 1D, have one less value than ``edges``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input.
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train
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spacetelescope/synphot_refactor
synphot/binning.py
calculate_bin_centers
def calculate_bin_centers(edges): """Calculate the centers of wavelengths bins given their edges. Parameters ---------- edges : array-like or `~astropy.units.quantity.Quantity` Sequence of bin edges. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- centers : `~astropy.units.quantity.Quantity` Array of bin centers. Will be 1D, have one less value than ``edges``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if not isinstance(edges, u.Quantity): edges = edges * u.AA if edges.ndim != 1: raise exceptions.SynphotError('Bin edges must be 1D array.') if edges.size < 2: raise exceptions.SynphotError( 'Bin edges must have at least two values.') centers = np.empty(edges.size - 1, dtype=np.float64) centers[0] = edges.value[:2].mean() for i in range(1, centers.size): centers[i] = 2.0 * edges.value[i] - centers[i - 1] return centers * edges.unit
python
def calculate_bin_centers(edges): """Calculate the centers of wavelengths bins given their edges. Parameters ---------- edges : array-like or `~astropy.units.quantity.Quantity` Sequence of bin edges. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- centers : `~astropy.units.quantity.Quantity` Array of bin centers. Will be 1D, have one less value than ``edges``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input. """ if not isinstance(edges, u.Quantity): edges = edges * u.AA if edges.ndim != 1: raise exceptions.SynphotError('Bin edges must be 1D array.') if edges.size < 2: raise exceptions.SynphotError( 'Bin edges must have at least two values.') centers = np.empty(edges.size - 1, dtype=np.float64) centers[0] = edges.value[:2].mean() for i in range(1, centers.size): centers[i] = 2.0 * edges.value[i] - centers[i - 1] return centers * edges.unit
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Calculate the centers of wavelengths bins given their edges. Parameters ---------- edges : array-like or `~astropy.units.quantity.Quantity` Sequence of bin edges. Must be 1D and have at least two values. If not a Quantity, assumed to be in Angstrom. Returns ------- centers : `~astropy.units.quantity.Quantity` Array of bin centers. Will be 1D, have one less value than ``edges``, and also the same unit. Raises ------ synphot.exceptions.SynphotError Invalid input.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/binning.py#L129-L166
spacetelescope/synphot_refactor
synphot/binning.py
wave_range
def wave_range(bins, cenwave, npix, mode='round'): """Calculate the wavelength range covered by the given number of pixels centered on the given central wavelength of the given bins. Parameters ---------- bins : array-like Wavelengths at bin centers, each centered on a pixel. Must be 1D array. cenwave : float Desired central wavelength, in the same unit as ``bins``. npix : int Desired number of pixels, centered on ``cenwave``. mode : {'round', 'min', 'max', 'none'} Determines how the pixels at the edges of the wavelength range are handled. All the options, except 'none', will return wavelength range edges that correspond to pixel edges: * 'round' - Wavelength range edges are the pixel edges and the range spans exactly ``npix`` pixels. An edge that falls in the center of a bin is rounded to the nearest pixel edge. This is the default. * 'min' - Wavelength range is shrunk such that it includes an integer number of pixels and its edges fall on pixel edges. It may not span exactly ``npix`` pixels. * 'max' - Wavelength range is expanded such that it includes an integer number of pixels and its edges fall on pixel edges. It may not span exactly ``npix`` pixels. * 'none' - Exact wavelength range is returned. The edges may not correspond to pixel edges, but it covers exactly ``npix`` pixels. Returns ------- wave1, wave2 : float Lower and upper limits of the wavelength range. Raises ------ synphot.exceptions.OverlapError Given central wavelength is not within the given bins or the wavelength range would exceed the bin limits. synphot.exceptions.SynphotError Invalid inputs or calculation failed. """ mode = mode.lower() if mode not in ('round', 'min', 'max', 'none'): raise exceptions.SynphotError( 'mode={0} is invalid, must be "round", "min", "max", ' 'or "none".'.format(mode)) if not isinstance(npix, int): raise exceptions.SynphotError('npix={0} is invalid.'.format(npix)) # Bin values must be in ascending order. if bins[0] > bins[-1]: bins = bins[::-1] # Central wavelength must be within given bins. if cenwave < bins[0] or cenwave > bins[-1]: raise exceptions.OverlapError( 'cenwave={0} is not within binset (min={1}, max={2}).'.format( cenwave, bins[0], bins[-1])) # Find the index the central wavelength among bins diff = cenwave - bins ind = np.argmin(np.abs(diff)) # Calculate fractional index frac_ind = float(ind) if diff[ind] < 0: frac_ind += diff[ind] / (bins[ind] - bins[ind - 1]) elif diff[ind] > 0: frac_ind += diff[ind] / (bins[ind + 1] - bins[ind]) # Calculate fractional indices of the edges half_npix = npix / 2.0 frac_ind1 = frac_ind - half_npix frac_ind2 = frac_ind + half_npix # Calculated edges must not exceed bin edges if frac_ind1 < -0.5: raise exceptions.OverlapError( 'Lower limit of wavelength range is out of bounds.') if frac_ind2 > (bins.size - 0.5): raise exceptions.OverlapError( 'Upper limit of wavelength range is out of bounds.') frac1, int1 = np.modf(frac_ind1) frac2, int2 = np.modf(frac_ind2) int1 = int(int1) int2 = int(int2) if mode == 'round': # Lower end of wavelength range if frac1 >= 0: # end is somewhere greater than binset[0] so we can just # interpolate between two neighboring values going with upper edge wave1 = bins[int1:int1 + 2].mean() else: # end is below the lowest binset value, but not by enough to # trigger an exception wave1 = bins[0] - (bins[0:2].mean() - bins[0]) # Upper end of wavelength range if int2 < bins.shape[0] - 1: # end is somewhere below binset[-1] so we can just interpolate # between two neighboring values, going with the upper edge. wave2 = bins[int2:int2 + 2].mean() else: # end is above highest binset value but not by enough to # trigger an exception wave2 = bins[-1] + (bins[-1] - bins[-2:].mean()) elif mode == 'min': # Lower end of wavelength range if frac1 <= 0.5 and int1 < bins.shape[0] - 1: # not at the lowest possible edge and pixel i included wave1 = bins[int1:int1 + 2].mean() elif frac1 > 0.5 and int1 < bins.shape[0] - 2: # not at the lowest possible edge and pixel i not included wave1 = bins[int1 + 1:int1 + 3].mean() elif frac1 == -0.5: # at the lowest possible edge wave1 = bins[0] - (bins[0:2].mean() - bins[0]) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac1={1}, int1={2}'.format( mode, frac1, int1)) # Upper end of wavelength range if frac2 >= 0.5 and int2 < bins.shape[0] - 1: # not out at the end and pixel i included wave2 = bins[int2:int2 + 2].mean() elif frac2 < 0.5 and int2 < bins.shape[0]: # not out at end and pixel i not included wave2 = bins[int2 - 1:int2 + 1].mean() elif frac2 == 0.5 and int2 == bins.shape[0] - 1: # at the very end wave2 = bins[-1] + (bins[-1] - bins[-2:].mean()) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac2={1}, int2={2}'.format( mode, frac2, int2)) elif mode == 'max': # Lower end of wavelength range if frac1 < 0.5 and int1 < bins.shape[0]: # not at the lowest possible edge and pixel i included wave1 = bins[int1 - 1:int1 + 1].mean() elif frac1 >= 0.5 and int1 < bins.shape[0] - 1: # not at the lowest possible edge and pixel i not included wave1 = bins[int1:int1 + 2].mean() elif frac1 == -0.5: # at the lowest possible edge wave1 = bins[0] - (bins[0:2].mean() - bins[0]) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac1={1}, int1={2}'.format( mode, frac1, int1)) # Upper end of wavelength range if frac2 > 0.5 and int2 < bins.shape[0] - 2: # not out at the end and pixel i included wave2 = bins[int2 + 1:int2 + 3].mean() elif frac2 <= 0.5 and int2 < bins.shape[0] - 1: # not out at end and pixel i not included wave2 = bins[int2:int2 + 2].mean() elif frac2 == 0.5 and int2 == bins.shape[0] - 1: # at the very end wave2 = bins[-1] + (bins[-1] - bins[-2:].mean()) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac2={1}, int2={2}'.format( mode, frac2, int2)) else: # mode == 'none' wave1 = bins[int1] + frac1 * (bins[int1 + 1] - bins[int1]) wave2 = bins[int2] + frac2 * (bins[int2 + 1] - bins[int2]) return wave1, wave2
python
def wave_range(bins, cenwave, npix, mode='round'): """Calculate the wavelength range covered by the given number of pixels centered on the given central wavelength of the given bins. Parameters ---------- bins : array-like Wavelengths at bin centers, each centered on a pixel. Must be 1D array. cenwave : float Desired central wavelength, in the same unit as ``bins``. npix : int Desired number of pixels, centered on ``cenwave``. mode : {'round', 'min', 'max', 'none'} Determines how the pixels at the edges of the wavelength range are handled. All the options, except 'none', will return wavelength range edges that correspond to pixel edges: * 'round' - Wavelength range edges are the pixel edges and the range spans exactly ``npix`` pixels. An edge that falls in the center of a bin is rounded to the nearest pixel edge. This is the default. * 'min' - Wavelength range is shrunk such that it includes an integer number of pixels and its edges fall on pixel edges. It may not span exactly ``npix`` pixels. * 'max' - Wavelength range is expanded such that it includes an integer number of pixels and its edges fall on pixel edges. It may not span exactly ``npix`` pixels. * 'none' - Exact wavelength range is returned. The edges may not correspond to pixel edges, but it covers exactly ``npix`` pixels. Returns ------- wave1, wave2 : float Lower and upper limits of the wavelength range. Raises ------ synphot.exceptions.OverlapError Given central wavelength is not within the given bins or the wavelength range would exceed the bin limits. synphot.exceptions.SynphotError Invalid inputs or calculation failed. """ mode = mode.lower() if mode not in ('round', 'min', 'max', 'none'): raise exceptions.SynphotError( 'mode={0} is invalid, must be "round", "min", "max", ' 'or "none".'.format(mode)) if not isinstance(npix, int): raise exceptions.SynphotError('npix={0} is invalid.'.format(npix)) # Bin values must be in ascending order. if bins[0] > bins[-1]: bins = bins[::-1] # Central wavelength must be within given bins. if cenwave < bins[0] or cenwave > bins[-1]: raise exceptions.OverlapError( 'cenwave={0} is not within binset (min={1}, max={2}).'.format( cenwave, bins[0], bins[-1])) # Find the index the central wavelength among bins diff = cenwave - bins ind = np.argmin(np.abs(diff)) # Calculate fractional index frac_ind = float(ind) if diff[ind] < 0: frac_ind += diff[ind] / (bins[ind] - bins[ind - 1]) elif diff[ind] > 0: frac_ind += diff[ind] / (bins[ind + 1] - bins[ind]) # Calculate fractional indices of the edges half_npix = npix / 2.0 frac_ind1 = frac_ind - half_npix frac_ind2 = frac_ind + half_npix # Calculated edges must not exceed bin edges if frac_ind1 < -0.5: raise exceptions.OverlapError( 'Lower limit of wavelength range is out of bounds.') if frac_ind2 > (bins.size - 0.5): raise exceptions.OverlapError( 'Upper limit of wavelength range is out of bounds.') frac1, int1 = np.modf(frac_ind1) frac2, int2 = np.modf(frac_ind2) int1 = int(int1) int2 = int(int2) if mode == 'round': # Lower end of wavelength range if frac1 >= 0: # end is somewhere greater than binset[0] so we can just # interpolate between two neighboring values going with upper edge wave1 = bins[int1:int1 + 2].mean() else: # end is below the lowest binset value, but not by enough to # trigger an exception wave1 = bins[0] - (bins[0:2].mean() - bins[0]) # Upper end of wavelength range if int2 < bins.shape[0] - 1: # end is somewhere below binset[-1] so we can just interpolate # between two neighboring values, going with the upper edge. wave2 = bins[int2:int2 + 2].mean() else: # end is above highest binset value but not by enough to # trigger an exception wave2 = bins[-1] + (bins[-1] - bins[-2:].mean()) elif mode == 'min': # Lower end of wavelength range if frac1 <= 0.5 and int1 < bins.shape[0] - 1: # not at the lowest possible edge and pixel i included wave1 = bins[int1:int1 + 2].mean() elif frac1 > 0.5 and int1 < bins.shape[0] - 2: # not at the lowest possible edge and pixel i not included wave1 = bins[int1 + 1:int1 + 3].mean() elif frac1 == -0.5: # at the lowest possible edge wave1 = bins[0] - (bins[0:2].mean() - bins[0]) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac1={1}, int1={2}'.format( mode, frac1, int1)) # Upper end of wavelength range if frac2 >= 0.5 and int2 < bins.shape[0] - 1: # not out at the end and pixel i included wave2 = bins[int2:int2 + 2].mean() elif frac2 < 0.5 and int2 < bins.shape[0]: # not out at end and pixel i not included wave2 = bins[int2 - 1:int2 + 1].mean() elif frac2 == 0.5 and int2 == bins.shape[0] - 1: # at the very end wave2 = bins[-1] + (bins[-1] - bins[-2:].mean()) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac2={1}, int2={2}'.format( mode, frac2, int2)) elif mode == 'max': # Lower end of wavelength range if frac1 < 0.5 and int1 < bins.shape[0]: # not at the lowest possible edge and pixel i included wave1 = bins[int1 - 1:int1 + 1].mean() elif frac1 >= 0.5 and int1 < bins.shape[0] - 1: # not at the lowest possible edge and pixel i not included wave1 = bins[int1:int1 + 2].mean() elif frac1 == -0.5: # at the lowest possible edge wave1 = bins[0] - (bins[0:2].mean() - bins[0]) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac1={1}, int1={2}'.format( mode, frac1, int1)) # Upper end of wavelength range if frac2 > 0.5 and int2 < bins.shape[0] - 2: # not out at the end and pixel i included wave2 = bins[int2 + 1:int2 + 3].mean() elif frac2 <= 0.5 and int2 < bins.shape[0] - 1: # not out at end and pixel i not included wave2 = bins[int2:int2 + 2].mean() elif frac2 == 0.5 and int2 == bins.shape[0] - 1: # at the very end wave2 = bins[-1] + (bins[-1] - bins[-2:].mean()) else: # pragma: no cover raise exceptions.SynphotError( 'mode={0} gets unexpected frac2={1}, int2={2}'.format( mode, frac2, int2)) else: # mode == 'none' wave1 = bins[int1] + frac1 * (bins[int1 + 1] - bins[int1]) wave2 = bins[int2] + frac2 * (bins[int2 + 1] - bins[int2]) return wave1, wave2
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Calculate the wavelength range covered by the given number of pixels centered on the given central wavelength of the given bins. Parameters ---------- bins : array-like Wavelengths at bin centers, each centered on a pixel. Must be 1D array. cenwave : float Desired central wavelength, in the same unit as ``bins``. npix : int Desired number of pixels, centered on ``cenwave``. mode : {'round', 'min', 'max', 'none'} Determines how the pixels at the edges of the wavelength range are handled. All the options, except 'none', will return wavelength range edges that correspond to pixel edges: * 'round' - Wavelength range edges are the pixel edges and the range spans exactly ``npix`` pixels. An edge that falls in the center of a bin is rounded to the nearest pixel edge. This is the default. * 'min' - Wavelength range is shrunk such that it includes an integer number of pixels and its edges fall on pixel edges. It may not span exactly ``npix`` pixels. * 'max' - Wavelength range is expanded such that it includes an integer number of pixels and its edges fall on pixel edges. It may not span exactly ``npix`` pixels. * 'none' - Exact wavelength range is returned. The edges may not correspond to pixel edges, but it covers exactly ``npix`` pixels. Returns ------- wave1, wave2 : float Lower and upper limits of the wavelength range. Raises ------ synphot.exceptions.OverlapError Given central wavelength is not within the given bins or the wavelength range would exceed the bin limits. synphot.exceptions.SynphotError Invalid inputs or calculation failed.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/binning.py#L169-L358
spacetelescope/synphot_refactor
synphot/binning.py
pixel_range
def pixel_range(bins, waverange, mode='round'): """Calculate the number of pixels within the given wavelength range and the given bins. Parameters ---------- bins : array-like Wavelengths at bin centers, each centered on a pixel. Must be 1D array. waverange : tuple of float Lower and upper limits of the desired wavelength range, in the same unit as ``bins``. mode : {'round', 'min', 'max', 'none'} Determines how the pixels at the edges of the wavelength range are handled. All the options, except 'none', will return an integer number of pixels: * 'round' - Wavelength range edges that fall in the middle of a pixel are counted if more than half of the pixel is within the given wavelength range. Edges that fall in the center of a pixel are rounded to the nearest pixel edge. This is the default. * 'min' - Only pixels wholly within the given wavelength range are counted. * 'max' - Pixels that are within the given wavelength range by any margin are counted. * 'none' - The exact number of encompassed pixels, including fractional pixels, is returned. Returns ------- npix : number Number of pixels. Raises ------ synphot.exceptions.OverlapError Given wavelength range exceeds the bounds of given bins. synphot.exceptions.SynphotError Invalid mode. """ mode = mode.lower() if mode not in ('round', 'min', 'max', 'none'): raise exceptions.SynphotError( 'mode={0} is invalid, must be "round", "min", "max", ' 'or "none".'.format(mode)) if waverange[0] < waverange[-1]: wave1 = waverange[0] wave2 = waverange[-1] else: wave1 = waverange[-1] wave2 = waverange[0] # Bin values must be in ascending order. if bins[0] > bins[-1]: bins = bins[::-1] # Wavelength range must be within bins minwave = bins[0] - (bins[0:2].mean() - bins[0]) maxwave = bins[-1] + (bins[-1] - bins[-2:].mean()) if wave1 < minwave or wave2 > maxwave: raise exceptions.OverlapError( 'Wavelength range ({0}, {1}) is out of bounds of bins ' '(min={2}, max={3}).'.format(wave1, wave2, minwave, maxwave)) if wave1 == wave2: return 0 if mode == 'round': ind1 = bins.searchsorted(wave1, side='right') ind2 = bins.searchsorted(wave2, side='right') else: ind1 = bins.searchsorted(wave1, side='left') ind2 = bins.searchsorted(wave2, side='left') if mode == 'round': npix = ind2 - ind1 elif mode == 'min': # for ind1, figure out if pixel ind1 is wholly included or not. # do this by figuring out where wave1 is between ind1 and ind1-1. frac = (bins[ind1] - wave1) / (bins[ind1] - bins[ind1 - 1]) if frac < 0.5: # ind1 is only partially included ind1 += 1 # similar but reversed procedure for ind2 frac = (wave2 - bins[ind2 - 1]) / (bins[ind2] - bins[ind2 - 1]) if frac < 0.5: # ind2 is only partially included ind2 -= 1 npix = ind2 - ind1 elif mode == 'max': # for ind1, figure out if pixel ind1-1 is partially included or not. # do this by figuring out where wave1 is between ind1 and ind1-1. frac = (wave1 - bins[ind1 - 1]) / (bins[ind1] - bins[ind1 - 1]) if frac < 0.5: # ind1 is partially included ind1 -= 1 # similar but reversed procedure for ind2 frac = (bins[ind2] - wave2) / (bins[ind2] - bins[ind2 - 1]) if frac < 0.5: # ind2 is partially included ind2 += 1 npix = ind2 - ind1 else: # mode == 'none' # calculate fractional indices frac1 = ind1 - (bins[ind1] - wave1) / (bins[ind1] - bins[ind1 - 1]) frac2 = ind2 - (bins[ind2] - wave2) / (bins[ind2] - bins[ind2 - 1]) npix = frac2 - frac1 return npix
python
def pixel_range(bins, waverange, mode='round'): """Calculate the number of pixels within the given wavelength range and the given bins. Parameters ---------- bins : array-like Wavelengths at bin centers, each centered on a pixel. Must be 1D array. waverange : tuple of float Lower and upper limits of the desired wavelength range, in the same unit as ``bins``. mode : {'round', 'min', 'max', 'none'} Determines how the pixels at the edges of the wavelength range are handled. All the options, except 'none', will return an integer number of pixels: * 'round' - Wavelength range edges that fall in the middle of a pixel are counted if more than half of the pixel is within the given wavelength range. Edges that fall in the center of a pixel are rounded to the nearest pixel edge. This is the default. * 'min' - Only pixels wholly within the given wavelength range are counted. * 'max' - Pixels that are within the given wavelength range by any margin are counted. * 'none' - The exact number of encompassed pixels, including fractional pixels, is returned. Returns ------- npix : number Number of pixels. Raises ------ synphot.exceptions.OverlapError Given wavelength range exceeds the bounds of given bins. synphot.exceptions.SynphotError Invalid mode. """ mode = mode.lower() if mode not in ('round', 'min', 'max', 'none'): raise exceptions.SynphotError( 'mode={0} is invalid, must be "round", "min", "max", ' 'or "none".'.format(mode)) if waverange[0] < waverange[-1]: wave1 = waverange[0] wave2 = waverange[-1] else: wave1 = waverange[-1] wave2 = waverange[0] # Bin values must be in ascending order. if bins[0] > bins[-1]: bins = bins[::-1] # Wavelength range must be within bins minwave = bins[0] - (bins[0:2].mean() - bins[0]) maxwave = bins[-1] + (bins[-1] - bins[-2:].mean()) if wave1 < minwave or wave2 > maxwave: raise exceptions.OverlapError( 'Wavelength range ({0}, {1}) is out of bounds of bins ' '(min={2}, max={3}).'.format(wave1, wave2, minwave, maxwave)) if wave1 == wave2: return 0 if mode == 'round': ind1 = bins.searchsorted(wave1, side='right') ind2 = bins.searchsorted(wave2, side='right') else: ind1 = bins.searchsorted(wave1, side='left') ind2 = bins.searchsorted(wave2, side='left') if mode == 'round': npix = ind2 - ind1 elif mode == 'min': # for ind1, figure out if pixel ind1 is wholly included or not. # do this by figuring out where wave1 is between ind1 and ind1-1. frac = (bins[ind1] - wave1) / (bins[ind1] - bins[ind1 - 1]) if frac < 0.5: # ind1 is only partially included ind1 += 1 # similar but reversed procedure for ind2 frac = (wave2 - bins[ind2 - 1]) / (bins[ind2] - bins[ind2 - 1]) if frac < 0.5: # ind2 is only partially included ind2 -= 1 npix = ind2 - ind1 elif mode == 'max': # for ind1, figure out if pixel ind1-1 is partially included or not. # do this by figuring out where wave1 is between ind1 and ind1-1. frac = (wave1 - bins[ind1 - 1]) / (bins[ind1] - bins[ind1 - 1]) if frac < 0.5: # ind1 is partially included ind1 -= 1 # similar but reversed procedure for ind2 frac = (bins[ind2] - wave2) / (bins[ind2] - bins[ind2 - 1]) if frac < 0.5: # ind2 is partially included ind2 += 1 npix = ind2 - ind1 else: # mode == 'none' # calculate fractional indices frac1 = ind1 - (bins[ind1] - wave1) / (bins[ind1] - bins[ind1 - 1]) frac2 = ind2 - (bins[ind2] - wave2) / (bins[ind2] - bins[ind2 - 1]) npix = frac2 - frac1 return npix
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Calculate the number of pixels within the given wavelength range and the given bins. Parameters ---------- bins : array-like Wavelengths at bin centers, each centered on a pixel. Must be 1D array. waverange : tuple of float Lower and upper limits of the desired wavelength range, in the same unit as ``bins``. mode : {'round', 'min', 'max', 'none'} Determines how the pixels at the edges of the wavelength range are handled. All the options, except 'none', will return an integer number of pixels: * 'round' - Wavelength range edges that fall in the middle of a pixel are counted if more than half of the pixel is within the given wavelength range. Edges that fall in the center of a pixel are rounded to the nearest pixel edge. This is the default. * 'min' - Only pixels wholly within the given wavelength range are counted. * 'max' - Pixels that are within the given wavelength range by any margin are counted. * 'none' - The exact number of encompassed pixels, including fractional pixels, is returned. Returns ------- npix : number Number of pixels. Raises ------ synphot.exceptions.OverlapError Given wavelength range exceeds the bounds of given bins. synphot.exceptions.SynphotError Invalid mode.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/binning.py#L361-L486
Julius2342/pyvlx
pyvlx/pyvlx.py
PyVLX.connect
async def connect(self): """Connect to KLF 200.""" PYVLXLOG.warning("Connecting to KLF 200.") await self.connection.connect() login = Login(pyvlx=self, password=self.config.password) await login.do_api_call() if not login.success: raise PyVLXException("Login to KLF 200 failed, check credentials")
python
async def connect(self): """Connect to KLF 200.""" PYVLXLOG.warning("Connecting to KLF 200.") await self.connection.connect() login = Login(pyvlx=self, password=self.config.password) await login.do_api_call() if not login.success: raise PyVLXException("Login to KLF 200 failed, check credentials")
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Julius2342/pyvlx
pyvlx/pyvlx.py
PyVLX.update_version
async def update_version(self): """Retrieve version and protocol version from API.""" get_version = GetVersion(pyvlx=self) await get_version.do_api_call() if not get_version.success: raise PyVLXException("Unable to retrieve version") self.version = get_version.version get_protocol_version = GetProtocolVersion(pyvlx=self) await get_protocol_version.do_api_call() if not get_protocol_version.success: raise PyVLXException("Unable to retrieve protocol version") self.protocol_version = get_protocol_version.version PYVLXLOG.warning( "Connected to: %s, protocol version: %s", self.version, self.protocol_version)
python
async def update_version(self): """Retrieve version and protocol version from API.""" get_version = GetVersion(pyvlx=self) await get_version.do_api_call() if not get_version.success: raise PyVLXException("Unable to retrieve version") self.version = get_version.version get_protocol_version = GetProtocolVersion(pyvlx=self) await get_protocol_version.do_api_call() if not get_protocol_version.success: raise PyVLXException("Unable to retrieve protocol version") self.protocol_version = get_protocol_version.version PYVLXLOG.warning( "Connected to: %s, protocol version: %s", self.version, self.protocol_version)
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Julius2342/pyvlx
pyvlx/pyvlx.py
PyVLX.send_frame
async def send_frame(self, frame): """Send frame to API via connection.""" if not self.connection.connected: await self.connect() await self.update_version() await set_utc(pyvlx=self) await house_status_monitor_enable(pyvlx=self) self.connection.write(frame)
python
async def send_frame(self, frame): """Send frame to API via connection.""" if not self.connection.connected: await self.connect() await self.update_version() await set_utc(pyvlx=self) await house_status_monitor_enable(pyvlx=self) self.connection.write(frame)
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Julius2342/pyvlx
old_api/pyvlx/scene.py
Scene.from_config
def from_config(cls, pyvlx, item): """Read scene from configuration.""" name = item['name'] ident = item['id'] return cls(pyvlx, ident, name)
python
def from_config(cls, pyvlx, item): """Read scene from configuration.""" name = item['name'] ident = item['id'] return cls(pyvlx, ident, name)
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train
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Julius2342/pyvlx
old_api/pyvlx/interface.py
Interface.api_call
async def api_call(self, verb, action, params=None, add_authorization_token=True, retry=False): """Send api call.""" if add_authorization_token and not self.token: await self.refresh_token() try: return await self._api_call_impl(verb, action, params, add_authorization_token) except InvalidToken: if not retry and add_authorization_token: await self.refresh_token() # Recursive call of api_call return await self.api_call(verb, action, params, add_authorization_token, True) raise
python
async def api_call(self, verb, action, params=None, add_authorization_token=True, retry=False): """Send api call.""" if add_authorization_token and not self.token: await self.refresh_token() try: return await self._api_call_impl(verb, action, params, add_authorization_token) except InvalidToken: if not retry and add_authorization_token: await self.refresh_token() # Recursive call of api_call return await self.api_call(verb, action, params, add_authorization_token, True) raise
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/old_api/pyvlx/interface.py#L19-L31
Julius2342/pyvlx
old_api/pyvlx/interface.py
Interface.refresh_token
async def refresh_token(self): """Refresh API token from KLF 200.""" json_response = await self.api_call('auth', 'login', {'password': self.config.password}, add_authorization_token=False) if 'token' not in json_response: raise PyVLXException('no element token found in response: {0}'.format(json.dumps(json_response))) self.token = json_response['token']
python
async def refresh_token(self): """Refresh API token from KLF 200.""" json_response = await self.api_call('auth', 'login', {'password': self.config.password}, add_authorization_token=False) if 'token' not in json_response: raise PyVLXException('no element token found in response: {0}'.format(json.dumps(json_response))) self.token = json_response['token']
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Refresh API token from KLF 200.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/old_api/pyvlx/interface.py#L62-L67
Julius2342/pyvlx
old_api/pyvlx/interface.py
Interface.create_body
def create_body(action, params): """Create http body for rest request.""" body = {} body['action'] = action if params is not None: body['params'] = params return body
python
def create_body(action, params): """Create http body for rest request.""" body = {} body['action'] = action if params is not None: body['params'] = params return body
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Create http body for rest request.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/old_api/pyvlx/interface.py#L89-L95
Julius2342/pyvlx
old_api/pyvlx/interface.py
Interface.evaluate_response
def evaluate_response(json_response): """Evaluate rest response.""" if 'errors' in json_response and json_response['errors']: Interface.evaluate_errors(json_response) elif 'result' not in json_response: raise PyVLXException('no element result found in response: {0}'.format(json.dumps(json_response))) elif not json_response['result']: raise PyVLXException('Request failed {0}'.format(json.dumps(json_response)))
python
def evaluate_response(json_response): """Evaluate rest response.""" if 'errors' in json_response and json_response['errors']: Interface.evaluate_errors(json_response) elif 'result' not in json_response: raise PyVLXException('no element result found in response: {0}'.format(json.dumps(json_response))) elif not json_response['result']: raise PyVLXException('Request failed {0}'.format(json.dumps(json_response)))
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Evaluate rest response.
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Julius2342/pyvlx
old_api/pyvlx/interface.py
Interface.evaluate_errors
def evaluate_errors(json_response): """Evaluate rest errors.""" if 'errors' not in json_response or \ not isinstance(json_response['errors'], list) or \ not json_response['errors'] or \ not isinstance(json_response['errors'][0], int): raise PyVLXException('Could not evaluate errors {0}'.format(json.dumps(json_response))) # unclear if response may contain more errors than one. Taking the first. first_error = json_response['errors'][0] if first_error in [402, 403, 405, 406]: raise InvalidToken(first_error) raise PyVLXException('Unknown error code {0}'.format(first_error))
python
def evaluate_errors(json_response): """Evaluate rest errors.""" if 'errors' not in json_response or \ not isinstance(json_response['errors'], list) or \ not json_response['errors'] or \ not isinstance(json_response['errors'][0], int): raise PyVLXException('Could not evaluate errors {0}'.format(json.dumps(json_response))) # unclear if response may contain more errors than one. Taking the first. first_error = json_response['errors'][0] if first_error in [402, 403, 405, 406]: raise InvalidToken(first_error) raise PyVLXException('Unknown error code {0}'.format(first_error))
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Evaluate rest errors.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/old_api/pyvlx/interface.py#L108-L122
Julius2342/pyvlx
pyvlx/frames/frame_set_node_name.py
FrameSetNodeNameRequest.get_payload
def get_payload(self): """Return Payload.""" ret = bytes([self.node_id]) ret += string_to_bytes(self.name, 64) return ret
python
def get_payload(self): """Return Payload.""" ret = bytes([self.node_id]) ret += string_to_bytes(self.name, 64) return ret
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Return Payload.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_set_node_name.py#L21-L25
Julius2342/pyvlx
pyvlx/frames/frame_set_node_name.py
FrameSetNodeNameRequest.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.node_id = payload[0] self.name = bytes_to_string(payload[1:65])
python
def from_payload(self, payload): """Init frame from binary data.""" self.node_id = payload[0] self.name = bytes_to_string(payload[1:65])
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_set_node_name.py#L27-L30
Julius2342/pyvlx
pyvlx/frames/frame_set_node_name.py
FrameSetNodeNameConfirmation.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.status = SetNodeNameConfirmationStatus(payload[0]) self.node_id = payload[1]
python
def from_payload(self, payload): """Init frame from binary data.""" self.status = SetNodeNameConfirmationStatus(payload[0]) self.node_id = payload[1]
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_set_node_name.py#L60-L63
Julius2342/pyvlx
pyvlx/node_helper.py
convert_frame_to_node
def convert_frame_to_node(pyvlx, frame): """Convert FrameGet[All]Node[s]InformationNotification into Node object.""" # pylint: disable=too-many-return-statements if frame.node_type == NodeTypeWithSubtype.WINDOW_OPENER: return Window(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name, rain_sensor=False) if frame.node_type == NodeTypeWithSubtype.WINDOW_OPENER_WITH_RAIN_SENSOR: return Window(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name, rain_sensor=True) if frame.node_type == NodeTypeWithSubtype.ROLLER_SHUTTER or \ frame.node_type == NodeTypeWithSubtype.DUAL_ROLLER_SHUTTER: return RollerShutter(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) if frame.node_type == NodeTypeWithSubtype.INTERIOR_VENETIAN_BLIND or \ frame.node_type == NodeTypeWithSubtype.VERTICAL_INTERIOR_BLINDS or \ frame.node_type == NodeTypeWithSubtype.EXTERIOR_VENETIAN_BLIND or \ frame.node_type == NodeTypeWithSubtype.LOUVER_BLIND: return Blind(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) if frame.node_type == NodeTypeWithSubtype.VERTICAL_EXTERIOR_AWNING or \ frame.node_type == NodeTypeWithSubtype.HORIZONTAL_AWNING: return Awning(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) if frame.node_type == NodeTypeWithSubtype.ON_OFF_SWITCH: return OnOffSwitch(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) PYVLXLOG.warning("%s not implemented", frame.node_type) return None
python
def convert_frame_to_node(pyvlx, frame): """Convert FrameGet[All]Node[s]InformationNotification into Node object.""" # pylint: disable=too-many-return-statements if frame.node_type == NodeTypeWithSubtype.WINDOW_OPENER: return Window(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name, rain_sensor=False) if frame.node_type == NodeTypeWithSubtype.WINDOW_OPENER_WITH_RAIN_SENSOR: return Window(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name, rain_sensor=True) if frame.node_type == NodeTypeWithSubtype.ROLLER_SHUTTER or \ frame.node_type == NodeTypeWithSubtype.DUAL_ROLLER_SHUTTER: return RollerShutter(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) if frame.node_type == NodeTypeWithSubtype.INTERIOR_VENETIAN_BLIND or \ frame.node_type == NodeTypeWithSubtype.VERTICAL_INTERIOR_BLINDS or \ frame.node_type == NodeTypeWithSubtype.EXTERIOR_VENETIAN_BLIND or \ frame.node_type == NodeTypeWithSubtype.LOUVER_BLIND: return Blind(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) if frame.node_type == NodeTypeWithSubtype.VERTICAL_EXTERIOR_AWNING or \ frame.node_type == NodeTypeWithSubtype.HORIZONTAL_AWNING: return Awning(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) if frame.node_type == NodeTypeWithSubtype.ON_OFF_SWITCH: return OnOffSwitch(pyvlx=pyvlx, node_id=frame.node_id, name=frame.name) PYVLXLOG.warning("%s not implemented", frame.node_type) return None
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Convert FrameGet[All]Node[s]InformationNotification into Node object.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/node_helper.py#L8-L30
spacetelescope/synphot_refactor
synphot/thermal.py
ThermalSpectralElement.temperature
def temperature(self, what): """Set temperature.""" self._temperature = units.validate_quantity(what, u.K)
python
def temperature(self, what): """Set temperature.""" self._temperature = units.validate_quantity(what, u.K)
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Set temperature.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/thermal.py#L53-L55
spacetelescope/synphot_refactor
synphot/thermal.py
ThermalSpectralElement.thermal_source
def thermal_source(self): """Apply emissivity to an existing beam to produce a thermal source spectrum (without optical counterpart). Thermal source spectrum is calculated as follow: #. Create a blackbody spectrum in PHOTLAM per square arcsec with `temperature`. #. Multiply the blackbody with `beam_fill_factor` and ``self``. Returns ------- sp : `~synphot.spectrum.SourceSpectrum` Thermal source spectrum. """ sp = (SourceSpectrum(BlackBody1D, temperature=self.temperature) * units.SR_PER_ARCSEC2 * self.beam_fill_factor * self) sp.meta['temperature'] = self.temperature sp.meta['beam_fill_factor'] = self.beam_fill_factor return sp
python
def thermal_source(self): """Apply emissivity to an existing beam to produce a thermal source spectrum (without optical counterpart). Thermal source spectrum is calculated as follow: #. Create a blackbody spectrum in PHOTLAM per square arcsec with `temperature`. #. Multiply the blackbody with `beam_fill_factor` and ``self``. Returns ------- sp : `~synphot.spectrum.SourceSpectrum` Thermal source spectrum. """ sp = (SourceSpectrum(BlackBody1D, temperature=self.temperature) * units.SR_PER_ARCSEC2 * self.beam_fill_factor * self) sp.meta['temperature'] = self.temperature sp.meta['beam_fill_factor'] = self.beam_fill_factor return sp
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/thermal.py#L72-L92
spacetelescope/synphot_refactor
synphot/thermal.py
ThermalSpectralElement.from_file
def from_file(cls, filename, temperature_key='DEFT', beamfill_key='BEAMFILL', **kwargs): """Creates a thermal spectral element from file. .. note:: Only FITS format is supported. Parameters ---------- filename : str Thermal spectral element filename. temperature_key, beamfill_key : str Keywords in FITS *table extension* that store temperature (in Kelvin) and beam filling factor values. Beam filling factor is set to 1 if its keyword is missing. kwargs : dict Keywords acceptable by :func:`~synphot.specio.read_fits_spec`. Returns ------- th : `ThermalSpectralElement` Empirical thermal spectral element. Raises ------ synphot.exceptions.SynphotError Invalid inputs. """ if not (filename.endswith('fits') or filename.endswith('fit')): raise exceptions.SynphotError('Only FITS format is supported.') # Extra info from table header ext = kwargs.get('ext', 1) tab_hdr = fits.getheader(filename, ext=ext) temperature = tab_hdr.get(temperature_key) if temperature is None: raise exceptions.SynphotError( 'Missing {0} keyword.'.format(temperature_key)) beam_fill_factor = tab_hdr.get('BEAMFILL', 1) if 'flux_unit' not in kwargs: kwargs['flux_unit'] = cls._internal_flux_unit if 'flux_col' not in kwargs: kwargs['flux_col'] = 'EMISSIVITY' header, wavelengths, em = specio.read_spec(filename, **kwargs) return cls( Empirical1D, temperature, beam_fill_factor=beam_fill_factor, points=wavelengths, lookup_table=em, meta={'header': header})
python
def from_file(cls, filename, temperature_key='DEFT', beamfill_key='BEAMFILL', **kwargs): """Creates a thermal spectral element from file. .. note:: Only FITS format is supported. Parameters ---------- filename : str Thermal spectral element filename. temperature_key, beamfill_key : str Keywords in FITS *table extension* that store temperature (in Kelvin) and beam filling factor values. Beam filling factor is set to 1 if its keyword is missing. kwargs : dict Keywords acceptable by :func:`~synphot.specio.read_fits_spec`. Returns ------- th : `ThermalSpectralElement` Empirical thermal spectral element. Raises ------ synphot.exceptions.SynphotError Invalid inputs. """ if not (filename.endswith('fits') or filename.endswith('fit')): raise exceptions.SynphotError('Only FITS format is supported.') # Extra info from table header ext = kwargs.get('ext', 1) tab_hdr = fits.getheader(filename, ext=ext) temperature = tab_hdr.get(temperature_key) if temperature is None: raise exceptions.SynphotError( 'Missing {0} keyword.'.format(temperature_key)) beam_fill_factor = tab_hdr.get('BEAMFILL', 1) if 'flux_unit' not in kwargs: kwargs['flux_unit'] = cls._internal_flux_unit if 'flux_col' not in kwargs: kwargs['flux_col'] = 'EMISSIVITY' header, wavelengths, em = specio.read_spec(filename, **kwargs) return cls( Empirical1D, temperature, beam_fill_factor=beam_fill_factor, points=wavelengths, lookup_table=em, meta={'header': header})
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/thermal.py#L95-L150
Julius2342/pyvlx
pyvlx/frames/frame_get_all_nodes_information.py
FrameGetAllNodesInformationConfirmation.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.status = AllNodesInformationStatus(payload[0]) self.number_of_nodes = payload[1]
python
def from_payload(self, payload): """Init frame from binary data.""" self.status = AllNodesInformationStatus(payload[0]) self.number_of_nodes = payload[1]
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_get_all_nodes_information.py#L46-L49
Julius2342/pyvlx
pyvlx/frames/frame_get_all_nodes_information.py
FrameGetAllNodesInformationNotification.get_payload
def get_payload(self): """Return Payload.""" payload = bytes() payload += bytes([self.node_id]) payload += bytes([self.order >> 8 & 255, self.order & 255]) payload += bytes([self.placement]) payload += bytes(string_to_bytes(self.name, 64)) payload += bytes([self.velocity.value]) payload += bytes([self.node_type.value >> 8 & 255, self.node_type.value & 255]) payload += bytes([self.product_group]) payload += bytes([self.product_type]) payload += bytes([self.node_variation.value]) payload += bytes([self.power_mode]) payload += bytes([self.build_number]) payload += bytes(self._serial_number) payload += bytes([self.state]) payload += bytes(self.current_position.raw) payload += bytes(self.target.raw) payload += bytes(self.current_position_fp1.raw) payload += bytes(self.current_position_fp2.raw) payload += bytes(self.current_position_fp3.raw) payload += bytes(self.current_position_fp4.raw) payload += bytes([self.remaining_time >> 8 & 255, self.remaining_time & 255]) payload += struct.pack(">I", self.timestamp) payload += bytes(self.alias_array) return payload
python
def get_payload(self): """Return Payload.""" payload = bytes() payload += bytes([self.node_id]) payload += bytes([self.order >> 8 & 255, self.order & 255]) payload += bytes([self.placement]) payload += bytes(string_to_bytes(self.name, 64)) payload += bytes([self.velocity.value]) payload += bytes([self.node_type.value >> 8 & 255, self.node_type.value & 255]) payload += bytes([self.product_group]) payload += bytes([self.product_type]) payload += bytes([self.node_variation.value]) payload += bytes([self.power_mode]) payload += bytes([self.build_number]) payload += bytes(self._serial_number) payload += bytes([self.state]) payload += bytes(self.current_position.raw) payload += bytes(self.target.raw) payload += bytes(self.current_position_fp1.raw) payload += bytes(self.current_position_fp2.raw) payload += bytes(self.current_position_fp3.raw) payload += bytes(self.current_position_fp4.raw) payload += bytes([self.remaining_time >> 8 & 255, self.remaining_time & 255]) payload += struct.pack(">I", self.timestamp) payload += bytes(self.alias_array) return payload
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Return Payload.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_get_all_nodes_information.py#L92-L118
Julius2342/pyvlx
pyvlx/frames/frame_get_all_nodes_information.py
FrameGetAllNodesInformationNotification.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.node_id = payload[0] self.order = payload[1] * 256 + payload[2] self.placement = payload[3] self.name = bytes_to_string(payload[4:68]) self.velocity = Velocity(payload[68]) self.node_type = NodeTypeWithSubtype(payload[69] * 256 + payload[70]) self.product_group = payload[71] self.product_type = payload[72] self.node_variation = NodeVariation(payload[73]) self.power_mode = payload[74] self.build_number = payload[75] self._serial_number = payload[76:84] self.state = payload[84] self.current_position = Parameter(payload[85:87]) self.target = Parameter(payload[87:89]) self.current_position_fp1 = Parameter(payload[89:91]) self.current_position_fp2 = Parameter(payload[91:93]) self.current_position_fp3 = Parameter(payload[93:95]) self.current_position_fp4 = Parameter(payload[95:97]) self.remaining_time = payload[97] * 256 + payload[98] self.timestamp = struct.unpack(">I", payload[99:103])[0] self.alias_array = AliasArray(payload[103:125])
python
def from_payload(self, payload): """Init frame from binary data.""" self.node_id = payload[0] self.order = payload[1] * 256 + payload[2] self.placement = payload[3] self.name = bytes_to_string(payload[4:68]) self.velocity = Velocity(payload[68]) self.node_type = NodeTypeWithSubtype(payload[69] * 256 + payload[70]) self.product_group = payload[71] self.product_type = payload[72] self.node_variation = NodeVariation(payload[73]) self.power_mode = payload[74] self.build_number = payload[75] self._serial_number = payload[76:84] self.state = payload[84] self.current_position = Parameter(payload[85:87]) self.target = Parameter(payload[87:89]) self.current_position_fp1 = Parameter(payload[89:91]) self.current_position_fp2 = Parameter(payload[91:93]) self.current_position_fp3 = Parameter(payload[93:95]) self.current_position_fp4 = Parameter(payload[95:97]) self.remaining_time = payload[97] * 256 + payload[98] self.timestamp = struct.unpack(">I", payload[99:103])[0] self.alias_array = AliasArray(payload[103:125])
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_get_all_nodes_information.py#L120-L143
Julius2342/pyvlx
pyvlx/parameter.py
Parameter.from_parameter
def from_parameter(self, parameter): """Set internal raw state from parameter.""" if not isinstance(parameter, Parameter): raise Exception("parameter::from_parameter_wrong_object") self.raw = parameter.raw
python
def from_parameter(self, parameter): """Set internal raw state from parameter.""" if not isinstance(parameter, Parameter): raise Exception("parameter::from_parameter_wrong_object") self.raw = parameter.raw
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Set internal raw state from parameter.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/parameter.py#L21-L25
Julius2342/pyvlx
pyvlx/parameter.py
Parameter.from_int
def from_int(value): """Create raw out of position vlaue.""" if not isinstance(value, int): raise PyVLXException("value_has_to_be_int") if not Parameter.is_valid_int(value): raise PyVLXException("value_out_of_range") return bytes([value >> 8 & 255, value & 255])
python
def from_int(value): """Create raw out of position vlaue.""" if not isinstance(value, int): raise PyVLXException("value_has_to_be_int") if not Parameter.is_valid_int(value): raise PyVLXException("value_out_of_range") return bytes([value >> 8 & 255, value & 255])
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Create raw out of position vlaue.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/parameter.py#L28-L34
Julius2342/pyvlx
pyvlx/parameter.py
Parameter.is_valid_int
def is_valid_int(value): """Test if value can be rendered out of int.""" if 0 <= value <= Parameter.MAX: # This includes ON and OFF return True if value == Parameter.UNKNOWN_VALUE: return True if value == Parameter.CURRENT_POSITION: return True return False
python
def is_valid_int(value): """Test if value can be rendered out of int.""" if 0 <= value <= Parameter.MAX: # This includes ON and OFF return True if value == Parameter.UNKNOWN_VALUE: return True if value == Parameter.CURRENT_POSITION: return True return False
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Test if value can be rendered out of int.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/parameter.py#L37-L45
Julius2342/pyvlx
pyvlx/parameter.py
Parameter.from_raw
def from_raw(raw): """Test if raw packets are valid for initialization of Position.""" if not isinstance(raw, bytes): raise PyVLXException("Position::raw_must_be_bytes") if len(raw) != 2: raise PyVLXException("Position::raw_must_be_two_bytes") if raw != Position.from_int(Position.CURRENT_POSITION) and \ raw != Position.from_int(Position.UNKNOWN_VALUE) and \ Position.to_int(raw) > Position.MAX: raise PyVLXException("position::raw_exceed_limit", raw=raw) return raw
python
def from_raw(raw): """Test if raw packets are valid for initialization of Position.""" if not isinstance(raw, bytes): raise PyVLXException("Position::raw_must_be_bytes") if len(raw) != 2: raise PyVLXException("Position::raw_must_be_two_bytes") if raw != Position.from_int(Position.CURRENT_POSITION) and \ raw != Position.from_int(Position.UNKNOWN_VALUE) and \ Position.to_int(raw) > Position.MAX: raise PyVLXException("position::raw_exceed_limit", raw=raw) return raw
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Test if raw packets are valid for initialization of Position.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/parameter.py#L48-L58
Julius2342/pyvlx
pyvlx/parameter.py
Position.from_percent
def from_percent(position_percent): """Create raw value out of percent position.""" if not isinstance(position_percent, int): raise PyVLXException("Position::position_percent_has_to_be_int") if position_percent < 0: raise PyVLXException("Position::position_percent_has_to_be_positive") if position_percent > 100: raise PyVLXException("Position::position_percent_out_of_range") return bytes([position_percent*2, 0])
python
def from_percent(position_percent): """Create raw value out of percent position.""" if not isinstance(position_percent, int): raise PyVLXException("Position::position_percent_has_to_be_int") if position_percent < 0: raise PyVLXException("Position::position_percent_has_to_be_positive") if position_percent > 100: raise PyVLXException("Position::position_percent_out_of_range") return bytes([position_percent*2, 0])
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Create raw value out of percent position.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/parameter.py#L172-L180
Julius2342/pyvlx
pyvlx/frames/frame_get_version.py
FrameGetVersionConfirmation.product
def product(self): """Return product as human readable string.""" if self.product_group == 14 and self.product_type == 3: return "KLF 200" return "Unknown Product: {}:{}".format(self.product_group, self.product_type)
python
def product(self): """Return product as human readable string.""" if self.product_group == 14 and self.product_type == 3: return "KLF 200" return "Unknown Product: {}:{}".format(self.product_group, self.product_type)
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Return product as human readable string.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_get_version.py#L44-L48
Julius2342/pyvlx
pyvlx/frames/frame_get_version.py
FrameGetVersionConfirmation.get_payload
def get_payload(self): """Return Payload.""" ret = self._software_version ret += bytes([self.hardware_version, self.product_group, self.product_type]) return ret
python
def get_payload(self): """Return Payload.""" ret = self._software_version ret += bytes([self.hardware_version, self.product_group, self.product_type]) return ret
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Return Payload.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_get_version.py#L50-L54
Julius2342/pyvlx
pyvlx/frames/frame_get_version.py
FrameGetVersionConfirmation.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self._software_version = payload[0:6] self.hardware_version = payload[6] self.product_group = payload[7] self.product_type = payload[8]
python
def from_payload(self, payload): """Init frame from binary data.""" self._software_version = payload[0:6] self.hardware_version = payload[6] self.product_group = payload[7] self.product_type = payload[8]
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_get_version.py#L56-L61
Julius2342/pyvlx
pyvlx/frames/frame_activate_scene.py
FrameActivateSceneRequest.get_payload
def get_payload(self): """Return Payload.""" ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.originator.value]) ret += bytes([self.priority.value]) ret += bytes([self.scene_id]) ret += bytes([self.velocity.value]) return ret
python
def get_payload(self): """Return Payload.""" ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.originator.value]) ret += bytes([self.priority.value]) ret += bytes([self.scene_id]) ret += bytes([self.velocity.value]) return ret
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Return Payload.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_activate_scene.py#L23-L30
Julius2342/pyvlx
pyvlx/frames/frame_activate_scene.py
FrameActivateSceneRequest.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.originator = Originator(payload[2]) self.priority = Priority(payload[3]) self.scene_id = payload[4] self.velocity = Velocity(payload[5])
python
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.originator = Originator(payload[2]) self.priority = Priority(payload[3]) self.scene_id = payload[4] self.velocity = Velocity(payload[5])
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_activate_scene.py#L32-L38
Julius2342/pyvlx
pyvlx/frames/frame_activate_scene.py
FrameActivateSceneConfirmation.get_payload
def get_payload(self): """Return Payload.""" ret = bytes([self.status.value]) ret += bytes([self.session_id >> 8 & 255, self.session_id & 255]) return ret
python
def get_payload(self): """Return Payload.""" ret = bytes([self.status.value]) ret += bytes([self.session_id >> 8 & 255, self.session_id & 255]) return ret
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Return Payload.
[ "Return", "Payload", "." ]
train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_activate_scene.py#L65-L69
Julius2342/pyvlx
pyvlx/frames/frame_activate_scene.py
FrameActivateSceneConfirmation.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.status = ActivateSceneConfirmationStatus(payload[0]) self.session_id = payload[1]*256 + payload[2]
python
def from_payload(self, payload): """Init frame from binary data.""" self.status = ActivateSceneConfirmationStatus(payload[0]) self.session_id = payload[1]*256 + payload[2]
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_activate_scene.py#L71-L74
Julius2342/pyvlx
pyvlx/frames/frame_command_send.py
FrameCommandSendRequest.get_payload
def get_payload(self): """Return Payload.""" # Session id ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.originator.value]) ret += bytes([self.priority.value]) ret += bytes([0]) # ParameterActive pointing to main parameter (MP) # FPI 1+2 ret += bytes([0]) ret += bytes([0]) # Main parameter + functional parameter ret += bytes(self.parameter) ret += bytes(32) # Nodes array: Number of nodes + node array + padding ret += bytes([len(self.node_ids)]) # index array count ret += bytes(self.node_ids) + bytes(20-len(self.node_ids)) # Priority Level Lock ret += bytes([0]) # Priority Level information 1+2 ret += bytes([0, 0]) # Locktime ret += bytes([0]) return ret
python
def get_payload(self): """Return Payload.""" # Session id ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.originator.value]) ret += bytes([self.priority.value]) ret += bytes([0]) # ParameterActive pointing to main parameter (MP) # FPI 1+2 ret += bytes([0]) ret += bytes([0]) # Main parameter + functional parameter ret += bytes(self.parameter) ret += bytes(32) # Nodes array: Number of nodes + node array + padding ret += bytes([len(self.node_ids)]) # index array count ret += bytes(self.node_ids) + bytes(20-len(self.node_ids)) # Priority Level Lock ret += bytes([0]) # Priority Level information 1+2 ret += bytes([0, 0]) # Locktime ret += bytes([0]) return ret
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Return Payload.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_command_send.py#L25-L50
Julius2342/pyvlx
pyvlx/frames/frame_command_send.py
FrameCommandSendRequest.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.originator = Originator(payload[2]) self.priority = Priority(payload[3]) len_node_ids = payload[41] if len_node_ids > 20: raise PyVLXException("command_send_request_wrong_node_length") self.node_ids = [] for i in range(len_node_ids): self.node_ids.append(payload[42] + i) self.parameter = Parameter(payload[7:9])
python
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.originator = Originator(payload[2]) self.priority = Priority(payload[3]) len_node_ids = payload[41] if len_node_ids > 20: raise PyVLXException("command_send_request_wrong_node_length") self.node_ids = [] for i in range(len_node_ids): self.node_ids.append(payload[42] + i) self.parameter = Parameter(payload[7:9])
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train
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Julius2342/pyvlx
pyvlx/frames/frame_command_send.py
FrameCommandSendConfirmation.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.status = CommandSendConfirmationStatus(payload[2])
python
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.status = CommandSendConfirmationStatus(payload[2])
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_command_send.py#L98-L101
Julius2342/pyvlx
pyvlx/frames/frame_command_send.py
FrameCommandRunStatusNotification.get_payload
def get_payload(self): """Return Payload.""" ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.status_id]) ret += bytes([self.index_id]) ret += bytes([self.node_parameter]) ret += bytes([self.parameter_value >> 8 & 255, self.parameter_value & 255]) # XXX: Missing implementation of run_status, status_reply and information_code ret += bytes(6) return ret
python
def get_payload(self): """Return Payload.""" ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.status_id]) ret += bytes([self.index_id]) ret += bytes([self.node_parameter]) ret += bytes([self.parameter_value >> 8 & 255, self.parameter_value & 255]) # XXX: Missing implementation of run_status, status_reply and information_code ret += bytes(6) return ret
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Return Payload.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_command_send.py#L122-L132
Julius2342/pyvlx
pyvlx/frames/frame_command_send.py
FrameCommandRunStatusNotification.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.status_id = payload[2] self.index_id = payload[3] self.node_parameter = payload[4] self.parameter_value = payload[5]*256 + payload[6]
python
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.status_id = payload[2] self.index_id = payload[3] self.node_parameter = payload[4] self.parameter_value = payload[5]*256 + payload[6]
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_command_send.py#L134-L140
Julius2342/pyvlx
pyvlx/frames/frame_command_send.py
FrameCommandRemainingTimeNotification.get_payload
def get_payload(self): """Return Payload.""" ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.index_id]) ret += bytes([self.node_parameter]) ret += bytes([self.seconds >> 8 & 255, self.seconds & 255]) return ret
python
def get_payload(self): """Return Payload.""" ret = bytes([self.session_id >> 8 & 255, self.session_id & 255]) ret += bytes([self.index_id]) ret += bytes([self.node_parameter]) ret += bytes([self.seconds >> 8 & 255, self.seconds & 255]) return ret
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Return Payload.
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train
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Julius2342/pyvlx
pyvlx/frames/frame_command_send.py
FrameCommandRemainingTimeNotification.from_payload
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.index_id = payload[2] self.node_parameter = payload[3] self.seconds = payload[4]*256 + payload[5]
python
def from_payload(self, payload): """Init frame from binary data.""" self.session_id = payload[0]*256 + payload[1] self.index_id = payload[2] self.node_parameter = payload[3] self.seconds = payload[4]*256 + payload[5]
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Init frame from binary data.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/frames/frame_command_send.py#L172-L177
Julius2342/pyvlx
examples/monitor.py
main
async def main(loop): """Log packets from Bus.""" # Setting debug PYVLXLOG.setLevel(logging.DEBUG) stream_handler = logging.StreamHandler() stream_handler.setLevel(logging.DEBUG) PYVLXLOG.addHandler(stream_handler) # Connecting to KLF 200 pyvlx = PyVLX('pyvlx.yaml', loop=loop) await pyvlx.load_scenes() await pyvlx.load_nodes() # and wait, increase this timeout if you want to # log for a longer time.:) await asyncio.sleep(90) # Cleanup, KLF 200 is terrible in handling lost connections await pyvlx.disconnect()
python
async def main(loop): """Log packets from Bus.""" # Setting debug PYVLXLOG.setLevel(logging.DEBUG) stream_handler = logging.StreamHandler() stream_handler.setLevel(logging.DEBUG) PYVLXLOG.addHandler(stream_handler) # Connecting to KLF 200 pyvlx = PyVLX('pyvlx.yaml', loop=loop) await pyvlx.load_scenes() await pyvlx.load_nodes() # and wait, increase this timeout if you want to # log for a longer time.:) await asyncio.sleep(90) # Cleanup, KLF 200 is terrible in handling lost connections await pyvlx.disconnect()
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Log packets from Bus.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/examples/monitor.py#L9-L27
Julius2342/pyvlx
pyvlx/node.py
Node.rename
async def rename(self, name): """Change name of node.""" set_node_name = SetNodeName(pyvlx=self.pyvlx, node_id=self.node_id, name=name) await set_node_name.do_api_call() if not set_node_name.success: raise PyVLXException("Unable to rename node") self.name = name
python
async def rename(self, name): """Change name of node.""" set_node_name = SetNodeName(pyvlx=self.pyvlx, node_id=self.node_id, name=name) await set_node_name.do_api_call() if not set_node_name.success: raise PyVLXException("Unable to rename node") self.name = name
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Change name of node.
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train
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Julius2342/pyvlx
pyvlx/opening_device.py
OpeningDevice.set_position
async def set_position(self, position, wait_for_completion=True): """Set window to desired position. Parameters: * position: Position object containing the target position. * wait_for_completion: If set, function will return after device has reached target position. """ command_send = CommandSend( pyvlx=self.pyvlx, wait_for_completion=wait_for_completion, node_id=self.node_id, parameter=position) await command_send.do_api_call() if not command_send.success: raise PyVLXException("Unable to send command") await self.after_update()
python
async def set_position(self, position, wait_for_completion=True): """Set window to desired position. Parameters: * position: Position object containing the target position. * wait_for_completion: If set, function will return after device has reached target position. """ command_send = CommandSend( pyvlx=self.pyvlx, wait_for_completion=wait_for_completion, node_id=self.node_id, parameter=position) await command_send.do_api_call() if not command_send.success: raise PyVLXException("Unable to send command") await self.after_update()
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/opening_device.py#L24-L41
Julius2342/pyvlx
pyvlx/opening_device.py
OpeningDevice.open
async def open(self, wait_for_completion=True): """Open window. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ await self.set_position( position=Position(position_percent=0), wait_for_completion=wait_for_completion)
python
async def open(self, wait_for_completion=True): """Open window. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ await self.set_position( position=Position(position_percent=0), wait_for_completion=wait_for_completion)
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Open window. Parameters: * wait_for_completion: If set, function will return after device has reached target position.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/opening_device.py#L43-L53
Julius2342/pyvlx
pyvlx/opening_device.py
OpeningDevice.close
async def close(self, wait_for_completion=True): """Close window. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ await self.set_position( position=Position(position_percent=100), wait_for_completion=wait_for_completion)
python
async def close(self, wait_for_completion=True): """Close window. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ await self.set_position( position=Position(position_percent=100), wait_for_completion=wait_for_completion)
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Close window. Parameters: * wait_for_completion: If set, function will return after device has reached target position.
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/opening_device.py#L55-L65
Julius2342/pyvlx
pyvlx/opening_device.py
OpeningDevice.stop
async def stop(self, wait_for_completion=True): """Stop window. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ await self.set_position( position=CurrentPosition(), wait_for_completion=wait_for_completion)
python
async def stop(self, wait_for_completion=True): """Stop window. Parameters: * wait_for_completion: If set, function will return after device has reached target position. """ await self.set_position( position=CurrentPosition(), wait_for_completion=wait_for_completion)
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train
https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/opening_device.py#L67-L77
spacetelescope/synphot_refactor
synphot/models.py
_get_sampleset
def _get_sampleset(model): """Return sampleset of a model or `None` if undefined. Model could be a real model or evaluated sampleset.""" if isinstance(model, Model): if hasattr(model, 'sampleset'): w = model.sampleset() else: w = None else: w = model # Already a sampleset return w
python
def _get_sampleset(model): """Return sampleset of a model or `None` if undefined. Model could be a real model or evaluated sampleset.""" if isinstance(model, Model): if hasattr(model, 'sampleset'): w = model.sampleset() else: w = None else: w = model # Already a sampleset return w
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Return sampleset of a model or `None` if undefined. Model could be a real model or evaluated sampleset.
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https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L654-L664
spacetelescope/synphot_refactor
synphot/models.py
_merge_sampleset
def _merge_sampleset(model1, model2): """Simple merge of samplesets.""" w1 = _get_sampleset(model1) w2 = _get_sampleset(model2) return merge_wavelengths(w1, w2)
python
def _merge_sampleset(model1, model2): """Simple merge of samplesets.""" w1 = _get_sampleset(model1) w2 = _get_sampleset(model2) return merge_wavelengths(w1, w2)
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Simple merge of samplesets.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L667-L671
spacetelescope/synphot_refactor
synphot/models.py
_shift_wavelengths
def _shift_wavelengths(model1, model2): """One of the models is either ``RedshiftScaleFactor`` or ``Scale``. Possible combos:: RedshiftScaleFactor | Model Scale | Model Model | Scale """ if isinstance(model1, _models.RedshiftScaleFactor): val = _get_sampleset(model2) if val is None: w = val else: w = model1.inverse(val) elif isinstance(model1, _models.Scale): w = _get_sampleset(model2) else: w = _get_sampleset(model1) return w
python
def _shift_wavelengths(model1, model2): """One of the models is either ``RedshiftScaleFactor`` or ``Scale``. Possible combos:: RedshiftScaleFactor | Model Scale | Model Model | Scale """ if isinstance(model1, _models.RedshiftScaleFactor): val = _get_sampleset(model2) if val is None: w = val else: w = model1.inverse(val) elif isinstance(model1, _models.Scale): w = _get_sampleset(model2) else: w = _get_sampleset(model1) return w
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One of the models is either ``RedshiftScaleFactor`` or ``Scale``. Possible combos:: RedshiftScaleFactor | Model Scale | Model Model | Scale
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L674-L694
spacetelescope/synphot_refactor
synphot/models.py
get_waveset
def get_waveset(model): """Get optimal wavelengths for sampling a given model. Parameters ---------- model : `~astropy.modeling.Model` Model. Returns ------- waveset : array-like or `None` Optimal wavelengths. `None` if undefined. Raises ------ synphot.exceptions.SynphotError Invalid model. """ if not isinstance(model, Model): raise SynphotError('{0} is not a model.'.format(model)) if isinstance(model, _CompoundModel): waveset = model._tree.evaluate(WAVESET_OPERATORS, getter=None) else: waveset = _get_sampleset(model) return waveset
python
def get_waveset(model): """Get optimal wavelengths for sampling a given model. Parameters ---------- model : `~astropy.modeling.Model` Model. Returns ------- waveset : array-like or `None` Optimal wavelengths. `None` if undefined. Raises ------ synphot.exceptions.SynphotError Invalid model. """ if not isinstance(model, Model): raise SynphotError('{0} is not a model.'.format(model)) if isinstance(model, _CompoundModel): waveset = model._tree.evaluate(WAVESET_OPERATORS, getter=None) else: waveset = _get_sampleset(model) return waveset
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L708-L735
spacetelescope/synphot_refactor
synphot/models.py
_get_meta
def _get_meta(model): """Return metadata of a model. Model could be a real model or evaluated metadata.""" if isinstance(model, Model): w = model.meta else: w = model # Already metadata return w
python
def _get_meta(model): """Return metadata of a model. Model could be a real model or evaluated metadata.""" if isinstance(model, Model): w = model.meta else: w = model # Already metadata return w
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Return metadata of a model. Model could be a real model or evaluated metadata.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L744-L751
spacetelescope/synphot_refactor
synphot/models.py
_merge_meta
def _merge_meta(model1, model2): """Simple merge of samplesets.""" w1 = _get_meta(model1) w2 = _get_meta(model2) return metadata.merge(w1, w2, metadata_conflicts='silent')
python
def _merge_meta(model1, model2): """Simple merge of samplesets.""" w1 = _get_meta(model1) w2 = _get_meta(model2) return metadata.merge(w1, w2, metadata_conflicts='silent')
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https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L754-L758
spacetelescope/synphot_refactor
synphot/models.py
get_metadata
def get_metadata(model): """Get metadata for a given model. Parameters ---------- model : `~astropy.modeling.Model` Model. Returns ------- metadata : dict Metadata for the model. Raises ------ synphot.exceptions.SynphotError Invalid model. """ if not isinstance(model, Model): raise SynphotError('{0} is not a model.'.format(model)) if isinstance(model, _CompoundModel): metadata = model._tree.evaluate(METADATA_OPERATORS, getter=None) else: metadata = deepcopy(model.meta) return metadata
python
def get_metadata(model): """Get metadata for a given model. Parameters ---------- model : `~astropy.modeling.Model` Model. Returns ------- metadata : dict Metadata for the model. Raises ------ synphot.exceptions.SynphotError Invalid model. """ if not isinstance(model, Model): raise SynphotError('{0} is not a model.'.format(model)) if isinstance(model, _CompoundModel): metadata = model._tree.evaluate(METADATA_OPERATORS, getter=None) else: metadata = deepcopy(model.meta) return metadata
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Get metadata for a given model. Parameters ---------- model : `~astropy.modeling.Model` Model. Returns ------- metadata : dict Metadata for the model. Raises ------ synphot.exceptions.SynphotError Invalid model.
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https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L761-L788
spacetelescope/synphot_refactor
synphot/models.py
BlackBody1D.lambda_max
def lambda_max(self): """Peak wavelength in Angstrom when the curve is expressed as power density.""" return ((const.b_wien.value / self.temperature) * u.m).to(u.AA).value
python
def lambda_max(self): """Peak wavelength in Angstrom when the curve is expressed as power density.""" return ((const.b_wien.value / self.temperature) * u.m).to(u.AA).value
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Peak wavelength in Angstrom when the curve is expressed as power density.
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spacetelescope/synphot_refactor
synphot/models.py
BlackBody1D.bounding_box
def bounding_box(self, factor=10.0): """Tuple defining the default ``bounding_box`` limits, ``(x_low, x_high)``. .. math:: x_{\\textnormal{low}} = 0 x_{\\textnormal{high}} = \\log(\\lambda_{\\textnormal{max}} \\;\ (1 + \\textnormal{factor})) Parameters ---------- factor : float Used to calculate ``x_high``. """ w0 = self.lambda_max return (w0 * 0, np.log10(w0 + factor * w0))
python
def bounding_box(self, factor=10.0): """Tuple defining the default ``bounding_box`` limits, ``(x_low, x_high)``. .. math:: x_{\\textnormal{low}} = 0 x_{\\textnormal{high}} = \\log(\\lambda_{\\textnormal{max}} \\;\ (1 + \\textnormal{factor})) Parameters ---------- factor : float Used to calculate ``x_high``. """ w0 = self.lambda_max return (w0 * 0, np.log10(w0 + factor * w0))
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Tuple defining the default ``bounding_box`` limits, ``(x_low, x_high)``. .. math:: x_{\\textnormal{low}} = 0 x_{\\textnormal{high}} = \\log(\\lambda_{\\textnormal{max}} \\;\ (1 + \\textnormal{factor})) Parameters ---------- factor : float Used to calculate ``x_high``.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L58-L76
spacetelescope/synphot_refactor
synphot/models.py
BlackBody1D.sampleset
def sampleset(self, factor_bbox=10.0, num=1000): """Return ``x`` array that samples the feature. Parameters ---------- factor_bbox : float Factor for ``bounding_box`` calculations. num : int Number of points to generate. """ w1, w2 = self.bounding_box(factor=factor_bbox) if self._n_models == 1: w = np.logspace(w1, w2, num) else: w = list(map(partial(np.logspace, num=num), w1, w2)) return np.asarray(w)
python
def sampleset(self, factor_bbox=10.0, num=1000): """Return ``x`` array that samples the feature. Parameters ---------- factor_bbox : float Factor for ``bounding_box`` calculations. num : int Number of points to generate. """ w1, w2 = self.bounding_box(factor=factor_bbox) if self._n_models == 1: w = np.logspace(w1, w2, num) else: w = list(map(partial(np.logspace, num=num), w1, w2)) return np.asarray(w)
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Return ``x`` array that samples the feature. Parameters ---------- factor_bbox : float Factor for ``bounding_box`` calculations. num : int Number of points to generate.
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spacetelescope/synphot_refactor
synphot/models.py
BlackBody1D.evaluate
def evaluate(x, temperature): """Evaluate the model. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. temperature : number Temperature in Kelvin. Returns ------- y : number or ndarray Blackbody radiation in PHOTLAM per steradian. """ if ASTROPY_LT_2_0: from astropy.analytic_functions.blackbody import blackbody_nu else: from astropy.modeling.blackbody import blackbody_nu # Silence Numpy old_np_err_cfg = np.seterr(all='ignore') wave = np.ascontiguousarray(x) * u.AA bbnu_flux = blackbody_nu(wave, temperature) bbflux = (bbnu_flux * u.sr).to( units.PHOTLAM, u.spectral_density(wave)) / u.sr # PHOTLAM/sr # Restore Numpy settings np.seterr(**old_np_err_cfg) return bbflux.value
python
def evaluate(x, temperature): """Evaluate the model. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. temperature : number Temperature in Kelvin. Returns ------- y : number or ndarray Blackbody radiation in PHOTLAM per steradian. """ if ASTROPY_LT_2_0: from astropy.analytic_functions.blackbody import blackbody_nu else: from astropy.modeling.blackbody import blackbody_nu # Silence Numpy old_np_err_cfg = np.seterr(all='ignore') wave = np.ascontiguousarray(x) * u.AA bbnu_flux = blackbody_nu(wave, temperature) bbflux = (bbnu_flux * u.sr).to( units.PHOTLAM, u.spectral_density(wave)) / u.sr # PHOTLAM/sr # Restore Numpy settings np.seterr(**old_np_err_cfg) return bbflux.value
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spacetelescope/synphot_refactor
synphot/models.py
BlackBodyNorm1D.evaluate
def evaluate(self, x, temperature): """Evaluate the model. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. temperature : number Temperature in Kelvin. Returns ------- y : number or ndarray Blackbody radiation in PHOTLAM. """ bbflux = super(BlackBodyNorm1D, self).evaluate(x, temperature) return bbflux * self._omega
python
def evaluate(self, x, temperature): """Evaluate the model. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. temperature : number Temperature in Kelvin. Returns ------- y : number or ndarray Blackbody radiation in PHOTLAM. """ bbflux = super(BlackBodyNorm1D, self).evaluate(x, temperature) return bbflux * self._omega
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Evaluate the model. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. temperature : number Temperature in Kelvin. Returns ------- y : number or ndarray Blackbody radiation in PHOTLAM.
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spacetelescope/synphot_refactor
synphot/models.py
Box1D._calc_sampleset
def _calc_sampleset(w1, w2, step, minimal): """Calculate sampleset for each model.""" if minimal: arr = [w1 - step, w1, w2, w2 + step] else: arr = np.arange(w1 - step, w2 + step + step, step) return arr
python
def _calc_sampleset(w1, w2, step, minimal): """Calculate sampleset for each model.""" if minimal: arr = [w1 - step, w1, w2, w2 + step] else: arr = np.arange(w1 - step, w2 + step + step, step) return arr
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spacetelescope/synphot_refactor
synphot/models.py
Box1D.sampleset
def sampleset(self, step=0.01, minimal=False): """Return ``x`` array that samples the feature. Parameters ---------- step : float Distance of first and last points w.r.t. bounding box. minimal : bool Only return the minimal points needed to define the box; i.e., box edges and a point outside on each side. """ w1, w2 = self.bounding_box if self._n_models == 1: w = self._calc_sampleset(w1, w2, step, minimal) else: w = list(map(partial( self._calc_sampleset, step=step, minimal=minimal), w1, w2)) return np.asarray(w)
python
def sampleset(self, step=0.01, minimal=False): """Return ``x`` array that samples the feature. Parameters ---------- step : float Distance of first and last points w.r.t. bounding box. minimal : bool Only return the minimal points needed to define the box; i.e., box edges and a point outside on each side. """ w1, w2 = self.bounding_box if self._n_models == 1: w = self._calc_sampleset(w1, w2, step, minimal) else: w = list(map(partial( self._calc_sampleset, step=step, minimal=minimal), w1, w2)) return np.asarray(w)
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Return ``x`` array that samples the feature. Parameters ---------- step : float Distance of first and last points w.r.t. bounding box. minimal : bool Only return the minimal points needed to define the box; i.e., box edges and a point outside on each side.
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spacetelescope/synphot_refactor
synphot/models.py
ConstFlux1D.evaluate
def evaluate(self, x, *args): """One dimensional constant flux model function. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. Returns ------- y : number or ndarray Flux in PHOTLAM. """ a = (self.amplitude * np.ones_like(x)) * self._flux_unit y = units.convert_flux(x, a, units.PHOTLAM) return y.value
python
def evaluate(self, x, *args): """One dimensional constant flux model function. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. Returns ------- y : number or ndarray Flux in PHOTLAM. """ a = (self.amplitude * np.ones_like(x)) * self._flux_unit y = units.convert_flux(x, a, units.PHOTLAM) return y.value
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One dimensional constant flux model function. Parameters ---------- x : number or ndarray Wavelengths in Angstrom. Returns ------- y : number or ndarray Flux in PHOTLAM.
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spacetelescope/synphot_refactor
synphot/models.py
Empirical1D._process_neg_flux
def _process_neg_flux(self, x, y): """Remove negative flux.""" if self._keep_neg: # Nothing to do return y old_y = None if np.isscalar(y): # pragma: no cover if y < 0: n_neg = 1 old_x = x old_y = y y = 0 else: x = np.asarray(x) # In case input is just pure list y = np.asarray(y) i = np.where(y < 0) n_neg = len(i[0]) if n_neg > 0: old_x = x[i] old_y = y[i] y[i] = 0 if old_y is not None: warn_str = ('{0} bin(s) contained negative flux or throughput' '; it/they will be set to zero.'.format(n_neg)) warn_str += '\n points: {0}\n lookup_table: {1}'.format( old_x, old_y) # Extra info self.meta['warnings'].update({'NegativeFlux': warn_str}) warnings.warn(warn_str, AstropyUserWarning) return y
python
def _process_neg_flux(self, x, y): """Remove negative flux.""" if self._keep_neg: # Nothing to do return y old_y = None if np.isscalar(y): # pragma: no cover if y < 0: n_neg = 1 old_x = x old_y = y y = 0 else: x = np.asarray(x) # In case input is just pure list y = np.asarray(y) i = np.where(y < 0) n_neg = len(i[0]) if n_neg > 0: old_x = x[i] old_y = y[i] y[i] = 0 if old_y is not None: warn_str = ('{0} bin(s) contained negative flux or throughput' '; it/they will be set to zero.'.format(n_neg)) warn_str += '\n points: {0}\n lookup_table: {1}'.format( old_x, old_y) # Extra info self.meta['warnings'].update({'NegativeFlux': warn_str}) warnings.warn(warn_str, AstropyUserWarning) return y
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spacetelescope/synphot_refactor
synphot/models.py
Empirical1D.evaluate
def evaluate(self, inputs): """Evaluate the model. Parameters ---------- inputs : number or ndarray Wavelengths in same unit as ``points``. Returns ------- y : number or ndarray Flux or throughput in same unit as ``lookup_table``. """ y = super(Empirical1D, self).evaluate(inputs) # Assume NaN at both ends need to be extrapolated based on # nearest end point. if self.fill_value is np.nan: # Cannot use sampleset() due to ExtinctionModel1D x = np.squeeze(self.points) if np.isscalar(y): # pragma: no cover if inputs < x[0]: y = self.lookup_table[0] elif inputs > x[-1]: y = self.lookup_table[-1] else: y[inputs < x[0]] = self.lookup_table[0] y[inputs > x[-1]] = self.lookup_table[-1] return self._process_neg_flux(inputs, y)
python
def evaluate(self, inputs): """Evaluate the model. Parameters ---------- inputs : number or ndarray Wavelengths in same unit as ``points``. Returns ------- y : number or ndarray Flux or throughput in same unit as ``lookup_table``. """ y = super(Empirical1D, self).evaluate(inputs) # Assume NaN at both ends need to be extrapolated based on # nearest end point. if self.fill_value is np.nan: # Cannot use sampleset() due to ExtinctionModel1D x = np.squeeze(self.points) if np.isscalar(y): # pragma: no cover if inputs < x[0]: y = self.lookup_table[0] elif inputs > x[-1]: y = self.lookup_table[-1] else: y[inputs < x[0]] = self.lookup_table[0] y[inputs > x[-1]] = self.lookup_table[-1] return self._process_neg_flux(inputs, y)
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Evaluate the model. Parameters ---------- inputs : number or ndarray Wavelengths in same unit as ``points``. Returns ------- y : number or ndarray Flux or throughput in same unit as ``lookup_table``.
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train
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spacetelescope/synphot_refactor
synphot/models.py
GaussianAbsorption1D.evaluate
def evaluate(x, amplitude, mean, stddev): """ GaussianAbsorption1D model function. """ return 1.0 - Gaussian1D.evaluate(x, amplitude, mean, stddev)
python
def evaluate(x, amplitude, mean, stddev): """ GaussianAbsorption1D model function. """ return 1.0 - Gaussian1D.evaluate(x, amplitude, mean, stddev)
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spacetelescope/synphot_refactor
synphot/models.py
GaussianAbsorption1D.fit_deriv
def fit_deriv(x, amplitude, mean, stddev): """ GaussianAbsorption1D model function derivatives. """ import operator return list(map( operator.neg, Gaussian1D.fit_deriv(x, amplitude, mean, stddev)))
python
def fit_deriv(x, amplitude, mean, stddev): """ GaussianAbsorption1D model function derivatives. """ import operator return list(map( operator.neg, Gaussian1D.fit_deriv(x, amplitude, mean, stddev)))
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GaussianAbsorption1D model function derivatives.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L459-L465
spacetelescope/synphot_refactor
synphot/models.py
Lorentz1D.sampleset
def sampleset(self, factor_step=0.05, **kwargs): """Return ``x`` array that samples the feature. Parameters ---------- factor_step : float Factor for sample step calculation. The step is calculated using ``factor_step * self.fwhm``. kwargs : dict Keyword(s) for ``bounding_box`` calculation. """ w1, w2 = self.bounding_box(**kwargs) dw = factor_step * self.fwhm if self._n_models == 1: w = np.arange(w1, w2, dw) else: w = list(map(np.arange, w1, w2, dw)) return np.asarray(w)
python
def sampleset(self, factor_step=0.05, **kwargs): """Return ``x`` array that samples the feature. Parameters ---------- factor_step : float Factor for sample step calculation. The step is calculated using ``factor_step * self.fwhm``. kwargs : dict Keyword(s) for ``bounding_box`` calculation. """ w1, w2 = self.bounding_box(**kwargs) dw = factor_step * self.fwhm if self._n_models == 1: w = np.arange(w1, w2, dw) else: w = list(map(np.arange, w1, w2, dw)) return np.asarray(w)
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Return ``x`` array that samples the feature. Parameters ---------- factor_step : float Factor for sample step calculation. The step is calculated using ``factor_step * self.fwhm``. kwargs : dict Keyword(s) for ``bounding_box`` calculation.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L530-L551
spacetelescope/synphot_refactor
synphot/models.py
PowerLawFlux1D.evaluate
def evaluate(self, x, *args): """Return flux in PHOTLAM. Assume input wavelength is in Angstrom.""" xx = x / self.x_0 y = (self.amplitude * xx ** (-self.alpha)) * self._flux_unit flux = units.convert_flux(x, y, units.PHOTLAM) return flux.value
python
def evaluate(self, x, *args): """Return flux in PHOTLAM. Assume input wavelength is in Angstrom.""" xx = x / self.x_0 y = (self.amplitude * xx ** (-self.alpha)) * self._flux_unit flux = units.convert_flux(x, y, units.PHOTLAM) return flux.value
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Return flux in PHOTLAM. Assume input wavelength is in Angstrom.
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L624-L629
spacetelescope/synphot_refactor
synphot/models.py
Trapezoid1D.sampleset
def sampleset(self): """Return ``x`` array that samples the feature.""" x1, x4 = self.bounding_box dw = self.width * 0.5 x2 = self.x_0 - dw x3 = self.x_0 + dw if self._n_models == 1: w = [x1, x2, x3, x4] else: w = list(zip(x1, x2, x3, x4)) return np.asarray(w)
python
def sampleset(self): """Return ``x`` array that samples the feature.""" x1, x4 = self.bounding_box dw = self.width * 0.5 x2 = self.x_0 - dw x3 = self.x_0 + dw if self._n_models == 1: w = [x1, x2, x3, x4] else: w = list(zip(x1, x2, x3, x4)) return np.asarray(w)
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train
https://github.com/spacetelescope/synphot_refactor/blob/9c064f3cff0c41dd8acadc0f67c6350931275b9f/synphot/models.py#L637-L649
awesto/djangoshop-stripe
shop_stripe/payment.py
StripePayment.get_payment_request
def get_payment_request(self, cart, request): """ From the given request, add a snippet to the page. """ try: self.charge(cart, request) thank_you_url = OrderModel.objects.get_latest_url() js_expression = 'window.location.href="{}";'.format(thank_you_url) return js_expression except (KeyError, stripe.error.StripeError) as err: raise ValidationError(err)
python
def get_payment_request(self, cart, request): """ From the given request, add a snippet to the page. """ try: self.charge(cart, request) thank_you_url = OrderModel.objects.get_latest_url() js_expression = 'window.location.href="{}";'.format(thank_you_url) return js_expression except (KeyError, stripe.error.StripeError) as err: raise ValidationError(err)
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From the given request, add a snippet to the page.
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train
https://github.com/awesto/djangoshop-stripe/blob/010d4642f971961cfeb415520ad819b3751281cb/shop_stripe/payment.py#L28-L38