<commit_before>import numpy as _np

class BeamParams(object):
	def __repr__(self):
		return '<{} at {}; beta={}, alpha={}>'.format(self.__class__.__module__,hex(id(self)),self.beta,self.alpha)

	def __init__(self,
			beta=None,alpha=None,emit=None,emit_n=None,gamma=None,
			spotsize=None,divergence=None,r=None,correlation=None):
		# If not enough info for Twiss
		emit_norm_insufficient = (emit_n==None or gamma==None)
		emit_geom_insufficient = emit==None
		emit_insufficient = (emit_geom_insufficient and emit_norm_insufficient)
		shape_insufficient = (beta==None or alpha==None)
		twiss_insufficient = (shape_insufficient or emit_insufficient)
		moments_insufficient = (spotsize==None or divergence==None or (r==None and correlation==None))

		# Validation that there's enough info to construct everything
		if twiss_insufficient and moments_insufficient:
			raise ValueError('Not enough information to construct Twiss values')

		if twiss_insufficient:
			if correlation!=None:
				emit = _np.sqrt(spotsize**2 * divergence**2 - correlation**2)
				corr_sign = _np.sign(correlation)
			elif r!=None:
				emit = spotsize * divergence * _np.sqrt(1-r**2)
				corr_sign = _np.sign(r)
			else:
				raise ValueError('Missing correlation/r term')
			beta = spotsize**2/emit
			gamma = divergence**2/emit
			alpha = -corr_sign * _np.sqrt(gamma*beta-1)
		else:
			def _get_geom_emit(emit=None,emit_n=None,gamma=None):
				if emit==None and emit_n==None:
					raise ValueError('Did not specify an emittance!')
				if emit!=None and emit_n!=None:
					raise ValueError('Specified too many emittance values!')
				if emit_n!=None:
					# print emit_n
					emit = _np.float64(emit_n)/_np.float64(gamma)
				else:
					emit = _np.float64(emit)
				return emit
			emit=_get_geom_emit(emit=emit,emit_n=emit_n,gamma=gamma)

		self.beta=_np.float64(beta)
		self.alpha=_np.float64(alpha)
		self.emit=_np.float64(emit)

	def set_emit_n(self,emit_n,gamma):
		self.emit=_np.float64(emit_n/gamma)

	# Definte beta property
	# Validate beta > 0
	def _set_beta(self,value):
		if not (value > 0):
			raise ValueError('Beta must be greater than zero: requested beta={}.'.format(value))
		self._beta=value
	def _get_beta(self):
		return self._beta
	beta = property(_get_beta,_set_beta)
	
	def _get_betastar(self):
		return 1/self.gamma
	betastar=property(_get_betastar)

	def _get_sstar(self):
		return self.alpha/self.gamma
	sstar=property(_get_sstar)

	# Define gamma property
	# Derived from beta and alpha
	def _get_gamma(self):
		return (1+_np.power(self.alpha,2))/self.beta
	gamma=property(_get_gamma)

	# Define T matrix<commit_msg>Updates<commit_after>import numpy as _np

class BeamParams(object):
	def __repr__(self):
		return '<{} at {}; beta={}, alpha={}>'.format(self.__class__.__module__,hex(id(self)),self.beta,self.alpha)

	def __init__(self,
			beta=None,alpha=None,emit=None,emit_n=None,gamma=None,
			spotsize=None,divergence=None,r=None,correlation=None):
		# If not enough info for Twiss
		emit_norm_insufficient = (emit_n==None or gamma==None)
		emit_geom_insufficient = emit==None
		emit_insufficient = (emit_geom_insufficient and emit_norm_insufficient)
		shape_insufficient = (beta==None or alpha==None)
		twiss_insufficient = (shape_insufficient or emit_insufficient)
		moments_insufficient = (spotsize==None or divergence==None or (r==None and correlation==None))

		# Validation that there's enough info to construct everything
		if twiss_insufficient and moments_insufficient:
			raise ValueError('Not enough information to construct Twiss values')

		if twiss_insufficient:
			if correlation!=None:
				emit = _np.sqrt(spotsize**2 * divergence**2 - correlation**2)
				corr_sign = _np.sign(correlation)
			elif r!=None:
				emit = spotsize * divergence * _np.sqrt(1-r**2)
				corr_sign = _np.sign(r)
			else:
				raise ValueError('Missing correlation/r term')
			beta = spotsize**2/emit
			gamma = divergence**2/emit
			alpha = -corr_sign * _np.sqrt(gamma*beta-1)
		else:
			def _get_geom_emit(emit=None,emit_n=None,gamma=None):
				if emit==None and emit_n==None:
					raise ValueError('Did not specify an emittance!')
				if emit!=None and emit_n!=None:
					raise ValueError('Specified too many emittance values!')
				if emit_n!=None:
					# print emit_n
					emit = _np.float64(emit_n)/_np.float64(gamma)
				else:
					emit = _np.float64(emit)
				return emit
			emit=_get_geom_emit(emit=emit,emit_n=emit_n,gamma=gamma)

		self.beta=_np.float64(beta)
		self.alpha=_np.float64(alpha)
		self.emit=_np.float64(emit)

	def set_emit_n(self,emit_n,gamma):
		self.emit=_np.float64(emit_n/gamma)

	# Definte beta property
	# Validate beta > 0
	def _get_beta(self):
		return self._beta
	def _set_beta(self,value):
		if not (value > 0):
			raise ValueError('Beta must be greater than zero: requested beta={}.'.format(value))
		self._beta=value
	beta = property(_get_beta,_set_beta)
	
	def _get_betastar(self):
		return 1/self.gamma
	betastar=property(_get_betastar)

	def _get_sstar(self):
		return self.alpha/self.gamma
	sstar=property(_get_sstar)

	# Define gamma property
	# Derived from beta and alpha
	def _get_gamma(self):
		return (1+_np.power(self.alpha,2))/self.beta
	gamma=property(_get_gamma)

	# Define T matrix
{'fraction_non_alphanumeric': 0.11902028319938768, 'fraction_numerical': 0.010332950631458095, 'mean_word_length': 4.9062146892655365, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '6054166', 'n_tokens_mistral': 2064, 'n_tokens_neox': 1847, 'n_words': 385}