Classes
class	TTCluster
	CLASS OF TT AND HPT EVENTS ######################################################. More...

Functions
	cm_to_channel (locpos, sipm_map=sipm_map, gaps_map=gaps_map, pitch=pitch, charr=charr, reverse=False, ch_max_num=ch_max_num, n_solid_sipms=n_solid_sipms)
	FUNCTIONS FOR TTCLASS #####################################################.

	channel_to_cm (channelpos, sipm_map=sipm_map, reverse=False, pitch=pitch)

	GetMatType (DetID)

	GetMatNum (DetID)

	GetMatLength (DetID)

	GetMatQty (DetID)

	GetStationNum (DetID)

	global_to_local (DetID, globalpos)

	local_to_global (DetID, localpos)

	ly_loss_mean (distance, params=ly_loss_params)

	ly_attenuation (distance)

	cluster_width_mean (distance, params=cluster_width_mean_params)

	cluster_width_sigma (distance, params=cluster_width_sigma_params)

	cluster_width_random (distance, ly, persent=random_width_persent, cluster_width_min=cluster_width_min, cluster_width_max=cluster_width_max)

	approx_function (var, approx_data)

	edep_to_ly (energy, CDF_integral=CDF_integral, energy_range=energy_range, ly_linear_params=ly_linear_params, k_cdfs_corr=k_cdfs_corr, sigma_in_percent=sigma_in_percent, ly_CDF_params=ly_CDF_params, CDF_ly_params=CDF_ly_params, ly_CDF_landau_params=ly_CDF_landau_params)

	cluster_generator (amplitude, width, wmp, cluster_width_max=cluster_width_max, chpos_min=chpos_min, chpos_max=chpos_max)

	is_realistic (cluster, width)

	create_cluster (amplitude, width, wmp)

	weigthed_mean_pos (cluster)

Variables
int	sipm_hor_pos = +1
	GLOBAL VALUES AND PARAMETERS ############.

int	sipm_vert_pos = -1

bool	is_sipm_hor_reversed = True

bool	is_sipm_vert_reversed = True

float	hw = 13.06 / 2.

float	pitch = 0.025

float	charr = 1.6

float	edge = 0.017

float	gap = 0.025

float	array = gap + 2.*charr

float	biggap = 0.042

int	ch_max_num = 511

int	n_solid_sipms = 8

tuple	sipm_map

dict	gaps_map

float	ly_loss_params = 20.78, -0.26, 7.89, -3.06

float	ly_loss_sigma_params = 6.8482, -0.5757, 3.4458

float	cluster_width_mean_params = 0.6661, -0.006955, 2.163

float	cluster_width_sigma_params = 1.103, -0.0005751

float	random_width_persent = 0.01

float	ly_min = 4.5

int	ly_max = 104

float	chpos_min = -0.5

float	chpos_max = 511.5

int	cluster_width_min = 1

int	cluster_width_max = 10

float	energy_range = 0.18, 0.477

float	CDF_integral = 0.0185640424

float	ly_linear_params = 332.882, -58.7085

float	k_cdfs_corr = 0.993076766938

float	sigma_in_percent = 0.01

int	sigma_from_width = 1 / 4.

dict	ly_CDF_params

dict	ly_CDF_landau_params

dict	CDF_ly_params

dict	design2018 = {'dy': 10.,'dv': 6,'ds': 9,'nud': 3,'caloDesign': 3,'strawDesign': 10}
	LOAD THE TARGET TRACKER GEOMETRY #########.

dict	dy = design2018['dy']

dict	dv = design2018['dv']

dict	ds = design2018['ds']

dict	nud = design2018['nud']

dict	caloDesign = design2018['caloDesign']

dict	strawDesign = design2018['strawDesign']

	geofile = None

	ship_geo

	n_hor_planes = ship_geo.NuTauTT.n_hor_planes

	n_vert_planes = ship_geo.NuTauTT.n_vert_planes

	scifimat_hor = ship_geo.NuTauTT.scifimat_hor

	scifimat_vert = ship_geo.NuTauTT.scifimat_vert

	scifimat_width = ship_geo.NuTauTT.scifimat_width

	scifimat_z = ship_geo.NuTauTT.scifimat_z

	n_tt_stations = ship_geo.NuTauTT.n

list	tt_points = []
	EXAMPLE OF USING THE CLASS #######.

list	hpt_points = []

list	tt_raw = []

list	hpt_raw = []

	muonfile = ROOT.TFile("$PWD/ship.conical.PG_13-TGeant4.root")

	tree = muonfile.Get("cbmsim")

	pnt = TTCluster(hit.GetDetectorID(), hit.GetX(), hit.GetY(), hit.GetEnergyLoss())

	fig

	axs = plt.gca()

	ly_bins = np.linspace(4,104,100)

	bins

	label

	loc

int	nbins = 24

list	xz_points = []

list	yz_points = []

Function Documentation

◆ approx_function()

TTCluster.approx_function	(	var,
		approx_data
	)

    This universal function substitutes the parameters to the function. 
    The parameters and the function are in the dictionary

Definition at line 385 of file TTCluster.py.

def approx_function(var, approx_data):
 
    """
    This universal function substitutes the parameters to the function. 
    The parameters and the function are in the dictionary
    """
 
    for (left, right), (params, func) in approx_data.items():
        if left <= var <= right:
            return func(var, *params)
    return False
 

◆ channel_to_cm()

TTCluster.channel_to_cm	(	channelpos,
		sipm_map = `sipm_map`,
		reverse = `False`,
		pitch = `pitch`
	)

    It converts a particle position measured channels to a position measured 
    in cm. The SiPM map is used. The position is in the scifi modul frame.

Definition at line 228 of file TTCluster.py.

def channel_to_cm(channelpos, sipm_map=sipm_map, reverse=False, pitch=pitch):
 
    """
    It converts a particle position measured channels to a position measured 
    in cm. The SiPM map is used. The position is in the scifi modul frame.
    """
 
    if reverse is True:
        for left, _, ch_range in sipm_map:
            if not ch_range is False:
                ch_start, ch_end = ch_range
                if ch_start <= channelpos <= ch_end:
                    return -(left + (channelpos - ch_start) * pitch)
    if reverse is False:
        for left, _, ch_range in sipm_map:
            if not ch_range is False:
                ch_start, ch_end = ch_range
                if ch_start <= channelpos <= ch_end:
                    return left + (channelpos - ch_start) * pitch
 

◆ cluster_generator()

TTCluster.cluster_generator	(	amplitude,
		width,
		wmp,
		cluster_width_max = `cluster_width_max`,
		chpos_min = `chpos_min`,
		chpos_max = `chpos_max`
	)

    It generates an event cluster with given weighted mean position in channels, width and 
    amplitude. 

    If right side of the cluster can be out of range, the maximum of the right side will be 
    right channel.

    At first an array [0, 0, 0, ... ] is generated which corresponds to the channels. 
    Next the cluster generated in the array. 
    Final array will be like [0, 0, ..., 1, 2, 5, 1, 0, ...], 
    [0, 17, 0, ...] or etc.

Definition at line 432 of file TTCluster.py.

    chpos_min=chpos_min, chpos_max=chpos_max):
 
    """
    It generates an event cluster with given weighted mean position in channels, width and 
    amplitude. 
 
    If right side of the cluster can be out of range, the maximum of the right side will be 
    right channel.
 
    At first an array [0, 0, 0, ... ] is generated which corresponds to the channels. 
    Next the cluster generated in the array. 
    Final array will be like [0, 0, ..., 1, 2, 5, 1, 0, ...], 
    [0, 17, 0, ...] or etc.
    """
 
    if int(ceil(wmp + 0.5 + cluster_width_max)) < chpos_max:
        max_fired_ch = int(ceil(wmp + 0.5 + cluster_width_max))
    else:
        max_fired_ch = int(ceil(chpos_max))
    cluster = [0 for _ in range(max_fired_ch)]
    mean = wmp
    if width == 1:
        if wmp == chpos_min:    
            fired_channel = 0
        elif wmp == chpos_max: 
            fired_channel = int(chpos_max)
        else: 
            fired_channel = int(wmp + 0.5)
        cluster[fired_channel] += amplitude 
    else:
        sigma = width * sigma_from_width
        for _ in range(amplitude):
            fired_channel = int(round(random.gauss(mean, sigma)))
            while not 0 <= fired_channel < len(cluster):
                fired_channel = int(round(random.gauss(mean, sigma)))
            cluster[fired_channel] += 1
    return cluster
 

◆ cluster_width_mean()

TTCluster.cluster_width_mean	(	distance,
		params = `cluster_width_mean_params`
	)

    It return a mean cluster width depending on the distance to SiPMs

Definition at line 347 of file TTCluster.py.

def cluster_width_mean(distance, params=cluster_width_mean_params):
 
    """
    It return a mean cluster width depending on the distance to SiPMs
    """
 
    A, B, C = params
    return exp(A + B*distance) + C
 

◆ cluster_width_random()

TTCluster.cluster_width_random	(	distance,
		ly,
		persent = `random_width_persent`,
		cluster_width_min = `cluster_width_min`,
		cluster_width_max = `cluster_width_max`
	)

    It generates a cluster. The cluster have 'ly' photoelectrons. 
    The cluster width depends on the distance to SiPM

Definition at line 365 of file TTCluster.py.

                         cluster_width_min=cluster_width_min, cluster_width_max=cluster_width_max):
    
    """
    It generates a cluster. The cluster have 'ly' photoelectrons. 
    The cluster width depends on the distance to SiPM
    """
 
    mean = cluster_width_mean(distance)
    sigma = cluster_width_sigma(distance)
    if random.random() <= persent:
        return random.randint(cluster_width_min, cluster_width_max)
    random_width = int(round(random.gauss(mean - 1, sigma))) + 1
 
    # Generate again if the width < minimal width and the light yield < the width
    while random_width < 1 or ly < random_width:
        random_width = int(round(random.gauss(mean - 1, sigma))) + 1
 
    return random_width
 

◆ cluster_width_sigma()

TTCluster.cluster_width_sigma	(	distance,
		params = `cluster_width_sigma_params`
	)

    It return a standard deviation of the mean cluster width depending on the distance to SiPMs

Definition at line 356 of file TTCluster.py.

def cluster_width_sigma(distance, params=cluster_width_sigma_params):
 
    """
    It return a standard deviation of the mean cluster width depending on the distance to SiPMs
    """
 
    A, B = params
    return A + B*distance
 

◆ cm_to_channel()

TTCluster.cm_to_channel	(	locpos,
		sipm_map = `sipm_map`,
		gaps_map = `gaps_map`,
		pitch = `pitch`,
		charr = `charr`,
		reverse = `False`,
		ch_max_num = `ch_max_num`,
		n_solid_sipms = `n_solid_sipms`
	)

FUNCTIONS FOR TTCLASS #####################################################.

    It converts a particle position (an event) measured in cm to a position measured 
    in channels. The SiPM map is used. The position is in the scifi modul frame.

Definition at line 203 of file TTCluster.py.

                  reverse=False, ch_max_num=ch_max_num, n_solid_sipms=n_solid_sipms):
    
    """
    It converts a particle position (an event) measured in cm to a position measured 
    in channels. The SiPM map is used. The position is in the scifi modul frame.
    """
 
    if reverse is True:
        for left, right, ch_range in sipm_map:
            if left <= locpos <= right:
                if not ch_range is False:
                    ch_start = ch_range[0]
                    return ch_max_num - ((locpos-left) / pitch + ch_start)
                else:
                    return gaps_map.get((n_solid_sipms - (locpos + hw) // charr), False)
    elif reverse is False:
        for left, right, ch_range in sipm_map:
            if left <= locpos <= right:
                if not ch_range is False:
                    ch_start = ch_range[0]
                    return (locpos-left) / pitch + ch_start
                else:
                    return gaps_map.get((locpos + hw) // charr, False)
 

◆ create_cluster()

TTCluster.create_cluster	(	amplitude,
		width,
		wmp
	)

    The final function for creating a signal cluster

Definition at line 486 of file TTCluster.py.

def create_cluster(amplitude, width, wmp):
 
    """
    The final function for creating a signal cluster
 
    """
    if not chpos_min < wmp < chpos_max: return False
    if wmp is False: return False
    if not ly_min <= amplitude >= width: return False
    shifted_wmp = wmp + 0.5 # For right counting
    cluster = cluster_generator(amplitude, width, shifted_wmp)
 
    # Generate again if it doesn't look like real cluster
    while is_realistic(cluster, width) is False:
        cluster = cluster_generator(amplitude, width, shifted_wmp)
 
    return cluster
 

◆ edep_to_ly()

TTCluster.edep_to_ly	(	energy,
		CDF_integral = `CDF_integral`,
		energy_range = `energy_range`,
		ly_linear_params = `ly_linear_params`,
		k_cdfs_corr = `k_cdfs_corr`,
		sigma_in_percent = `sigma_in_percent`,
		ly_CDF_params = `ly_CDF_params`,
		CDF_ly_params = `CDF_ly_params`,
		ly_CDF_landau_params = `ly_CDF_landau_params`
	)

    It returns the light yield calculated from the energy deposit. The calculations are based 
    on the equality of the cumulative distribution functions (CDF) :
    energy => CDF(energy) => CDF(light yield) => ly

    The linear converting range 0.18 MeV < dE < 0.477 MeV corresponds 4.5 < LY < 104 ph.e.

    If energy more then 0.477 MeV the light yield calculated randomly (uniformly in the range) 
    according to the distribution

    Also a little randomness is added to the CDF value with a normal distribution and 
    standard deviation with 'sigma_in_percent' (in percent of the whole range 0 - max CDF)

Definition at line 397 of file TTCluster.py.

    ly_CDF_params=ly_CDF_params, CDF_ly_params=CDF_ly_params, ly_CDF_landau_params=ly_CDF_landau_params):
    
    """
    It returns the light yield calculated from the energy deposit. The calculations are based 
    on the equality of the cumulative distribution functions (CDF) :
    energy => CDF(energy) => CDF(light yield) => ly
 
    The linear converting range 0.18 MeV < dE < 0.477 MeV corresponds 4.5 < LY < 104 ph.e.
 
    If energy more then 0.477 MeV the light yield calculated randomly (uniformly in the range) 
    according to the distribution
 
    Also a little randomness is added to the CDF value with a normal distribution and 
    standard deviation with 'sigma_in_percent' (in percent of the whole range 0 - max CDF)
    """
 
    e_min, e_max = energy_range
    A, C = ly_linear_params
    if e_min < energy < e_max:
        ly_lin = A * energy + C
        cdf_raw = approx_function(ly_lin, ly_CDF_landau_params) * k_cdfs_corr
    elif e_max <= energy:
        cdf_raw = CDF_integral * np.random.uniform(0., 1.0) 
    else:
        return 0.    
    cdf_random = random.gauss(cdf_raw, sigma_in_percent * CDF_integral)
 
    # Generate again while the CDF value is not in the range
    while cdf_random < 0 or cdf_random > CDF_integral:
        cdf_random = random.gauss(cdf_raw, sigma_in_percent * CDF_integral)
 
    return approx_function(cdf_random, CDF_ly_params)
 

◆ GetMatLength()

TTCluster.GetMatLength ( DetID )

    It returns a length of a scifi mat. The values 'scifimat_vert', 'scifimat_hor' are set 
    in the FairShip geometry file.

Definition at line 269 of file TTCluster.py.

def GetMatLength(DetID):
 
    """
    It returns a length of a scifi mat. The values 'scifimat_vert', 'scifimat_hor' are set 
    in the FairShip geometry file.
    """
 
    global scifimat_vert, scifimat_hor
 
    if GetMatType(DetID) == 1:
        return scifimat_vert 
    elif GetMatType(DetID) == 0:
        return scifimat_hor
 

◆ GetMatNum()

TTCluster.GetMatNum ( DetID )

    It returns an id (number) of a scifi module. In current version one plane have 7 vertical
    and 11 horisontal scifi assemblies.

Definition at line 260 of file TTCluster.py.

def GetMatNum(DetID):
 
    """
    It returns an id (number) of a scifi module. In current version one plane have 7 vertical
    and 11 horisontal scifi assemblies. 
    """
 
    return int(DetID % 1000 % 100)
 

◆ GetMatQty()

TTCluster.GetMatQty ( DetID )

    It returns a number of scifi mats in a plane. In current version it is 7 for vertical
    and 11 for horisontal scifi assemblies.

Definition at line 283 of file TTCluster.py.

def GetMatQty(DetID):
 
    """
    It returns a number of scifi mats in a plane. In current version it is 7 for vertical
    and 11 for horisontal scifi assemblies.
    """
 
    global n_vert_planes, n_hor_planes
 
    if GetMatType(DetID) == 1:
        return n_vert_planes 
    elif GetMatType(DetID) == 0:
        return n_hor_planes
 

◆ GetMatType()

TTCluster.GetMatType ( DetID )

    It returns a type of a scifi module.
    1 - vertical scifi assembly
    0 - horizontal scifi assembly

Definition at line 248 of file TTCluster.py.

def GetMatType(DetID):
 
    """
    It returns a type of a scifi module.
    1 - vertical scifi assembly
    0 - horizontal scifi assembly
    """
 
    if DetID < 1000: return False
    return (DetID % 1000) // 100.
 
 

◆ GetStationNum()

TTCluster.GetStationNum ( DetID )

    It returns an id of a plane. In current the detector have 19 TT stations and 5 HPT stations.

Definition at line 297 of file TTCluster.py.

def GetStationNum(DetID):
 
    """
    It returns an id of a plane. In current the detector have 19 TT stations and 5 HPT stations.
    """
 
    return int(hit.GetDetectorID() // 1000.)
 

◆ global_to_local()

TTCluster.global_to_local	(	DetID,
		globalpos
	)

    It returns the local coordinates in one scifi assembly frame from global coordinates.

Definition at line 305 of file TTCluster.py.

def global_to_local(DetID, globalpos):
 
    """
    It returns the local coordinates in one scifi assembly frame from global coordinates.
    """
 
    global scifimat_width
 
    matnum = GetMatNum(DetID)
    nmats = GetMatQty(DetID)
    return globalpos + ((nmats-1)/2. - matnum + 1) * scifimat_width
 

◆ is_realistic()

TTCluster.is_realistic	(	cluster,
		width
	)

    It returns TRUE if cluster is realistic: it doesn't have a gap between numders, like
    [..., 0, 1, 2, 0, 0, 5, 6, ...], and it doens't have the light yield less then width.

Definition at line 471 of file TTCluster.py.

def is_realistic(cluster, width):
 
    """
    It returns TRUE if cluster is realistic: it doesn't have a gap between numders, like
    [..., 0, 1, 2, 0, 0, 5, 6, ...], and it doens't have the light yield less then width.
    """
 
    cluster_only_values = [(channel, value) for channel, value in enumerate(cluster) if value > 0]
    first_channel, _ = cluster_only_values[0]
    last_channel, _ = cluster_only_values[-1]
    if len(cluster_only_values) != width or (last_channel - first_channel + 1) != width:
        return False
    else:
        return True
    

◆ local_to_global()

TTCluster.local_to_global	(	DetID,
		localpos
	)

    It returns the global coordinates from the local coordinates in one scifi assembly frame.

Definition at line 317 of file TTCluster.py.

def local_to_global(DetID, localpos):
 
    """
    It returns the global coordinates from the local coordinates in one scifi assembly frame.
    """
 
    global scifimat_width
 
    matnum = GetMatNum(DetID)
    nmats = GetMatQty(DetID)
    return localpos + (-nmats/2. + matnum - 1/2.) * scifimat_width
 

◆ ly_attenuation()

TTCluster.ly_attenuation ( distance )

    It return the light yield losses in percent depending on the distance to SiPMs

Definition at line 338 of file TTCluster.py.

def ly_attenuation(distance):
 
    """
    It return the light yield losses in percent depending on the distance to SiPMs
    """
 
    res_ly_loss = ly_loss_mean(distance) / ly_loss_mean(0.) 
    return res_ly_loss
 

◆ ly_loss_mean()

TTCluster.ly_loss_mean	(	distance,
		params = `ly_loss_params`
	)

    It return the light yield depending on the distance to SiPMs

Definition at line 329 of file TTCluster.py.

def ly_loss_mean(distance, params=ly_loss_params):
 
    """
    It return the light yield depending on the distance to SiPMs
    """
 
    A1, k1, A2, k2 = params
    return A1 * exp(k1 * distance / 100.) + A2 * exp(k2 * distance / 100.)
 

◆ weigthed_mean_pos()

TTCluster.weigthed_mean_pos ( cluster )

    Calculate the weighted mean position of the cluster

Definition at line 504 of file TTCluster.py.

def weigthed_mean_pos(cluster):
 
    """
    Calculate the weighted mean position of the cluster
    """
 
    if cluster is False:
        return False
    sumup = 0.
    sumdown = 0.
    wmp = 0.
    for channel, value in enumerate(cluster):
        if value > 0:
            sumup += value * channel
            sumdown += value
    if sumdown != 0:
        wmp = sumup / sumdown - 0.5
    return wmp
 

Variable Documentation

◆ array

float TTCluster.array = gap + 2.*charr

Definition at line 38 of file TTCluster.py.

◆ axs

TTCluster.axs = plt.gca()

Definition at line 727 of file TTCluster.py.

◆ biggap

float TTCluster.biggap = 0.042

Definition at line 39 of file TTCluster.py.

◆ bins

TTCluster.bins

Definition at line 731 of file TTCluster.py.

◆ caloDesign

dict TTCluster.caloDesign = design2018['caloDesign']

Definition at line 183 of file TTCluster.py.

◆ CDF_integral

float TTCluster.CDF_integral = 0.0185640424

Definition at line 102 of file TTCluster.py.

◆ CDF_ly_params

dict TTCluster.CDF_ly_params

Initial value:

=  {
    (0., 0.0006): (
        (89., 4.152, 0.0001574, -1.326e+04, 4.3), 
        lambda cdf, *p: p[0] * sqrt(p[1]*(cdf+p[2])) * (1-exp(p[3]*cdf)) + p[4]
    ),
    (0.0006, 0.012): (
        (158, 1.035, 0.24, 217),
        lambda cdf, *p: p[0] * log(sqrt(cdf)+p[1]) + p[2]*exp(p[3]*cdf)
    ),
    (0.012, 0.018561405): (
        (9.36, 335.984, -18100, -400, 15),
        lambda cdf, *p: p[0] * log((p[1]-p[2]*cdf)/(p[1]+p[2]*cdf)) + p[3]*cdf + p[4]
    ),
    (0.018561405, 0.0185640424): (
        (9.36, 335.984, -18100, -400, 15),
        lambda cdf, *p: (p[0] * log((p[1]-p[2]*0.018561405)/(p[1]+p[2]*0.018561405)) 
            + p[3]*0.018561405 + p[4])
    )
}

Definition at line 154 of file TTCluster.py.

◆ ch_max_num

int TTCluster.ch_max_num = 511

Definition at line 40 of file TTCluster.py.

◆ charr

float TTCluster.charr = 1.6

Definition at line 35 of file TTCluster.py.

◆ chpos_max

float TTCluster.chpos_max = 511.5

Definition at line 93 of file TTCluster.py.

◆ chpos_min

float TTCluster.chpos_min = -0.5

Definition at line 92 of file TTCluster.py.

◆ cluster_width_max

int TTCluster.cluster_width_max = 10

Definition at line 95 of file TTCluster.py.

◆ cluster_width_mean_params

float TTCluster.cluster_width_mean_params = 0.6661, -0.006955, 2.163

Definition at line 82 of file TTCluster.py.

◆ cluster_width_min

int TTCluster.cluster_width_min = 1

Definition at line 94 of file TTCluster.py.

◆ cluster_width_sigma_params

float TTCluster.cluster_width_sigma_params = 1.103, -0.0005751

Definition at line 83 of file TTCluster.py.

◆ design2018

dict TTCluster.design2018 = {'dy': 10.,'dv': 6,'ds': 9,'nud': 3,'caloDesign': 3,'strawDesign': 10}

LOAD THE TARGET TRACKER GEOMETRY #########.

Definition at line 178 of file TTCluster.py.

◆ ds

dict TTCluster.ds = design2018['ds']

Definition at line 181 of file TTCluster.py.

◆ dv

dict TTCluster.dv = design2018['dv']

Definition at line 180 of file TTCluster.py.

◆ dy

dict TTCluster.dy = design2018['dy']

Definition at line 179 of file TTCluster.py.

◆ edge

float TTCluster.edge = 0.017

Definition at line 36 of file TTCluster.py.

◆ energy_range

float TTCluster.energy_range = 0.18, 0.477

Definition at line 99 of file TTCluster.py.

◆ fig

TTCluster.fig

Definition at line 727 of file TTCluster.py.

◆ gap

float TTCluster.gap = 0.025

Definition at line 37 of file TTCluster.py.

◆ gaps_map

dict TTCluster.gaps_map

Initial value:

=  {
: -0.5, 
: 63.5,
: 127.5, 
: 191.5,
: 255.5, 
: 319.5,
: 383.5,
: 447.5, 
: 511.5
}

Definition at line 66 of file TTCluster.py.

◆ geofile

TTCluster.geofile = None

Definition at line 185 of file TTCluster.py.

◆ hpt_points

float TTCluster.hpt_points = []

Definition at line 632 of file TTCluster.py.

◆ hpt_raw

float TTCluster.hpt_raw = []

Definition at line 634 of file TTCluster.py.

◆ hw

float TTCluster.hw = 13.06 / 2.

Definition at line 33 of file TTCluster.py.

◆ is_sipm_hor_reversed

bool TTCluster.is_sipm_hor_reversed = True

Definition at line 23 of file TTCluster.py.

◆ is_sipm_vert_reversed

bool TTCluster.is_sipm_vert_reversed = True

Definition at line 24 of file TTCluster.py.

◆ k_cdfs_corr

float TTCluster.k_cdfs_corr = 0.993076766938

Definition at line 109 of file TTCluster.py.

◆ label

TTCluster.label

Definition at line 731 of file TTCluster.py.

◆ loc

TTCluster.loc

Definition at line 734 of file TTCluster.py.

◆ ly_bins

TTCluster.ly_bins = np.linspace(4,104,100)

Definition at line 730 of file TTCluster.py.

◆ ly_CDF_landau_params

dict TTCluster.ly_CDF_landau_params

Initial value:

=  {
    (4.5, 15): (
        (0.001038, -0.000378, 3.53e-05), 
        lambda ly, *p: p[0] + p[1]*ly + p[2]*ly**2
    ),
    (15, 40): (
        (-0.001986, -0.0003014, 7.031e-05, -2.067e-06, 1.892e-08),
        lambda ly, *p: p[0] + p[1]*ly + p[2]*ly**2 + p[3]*ly**3 + p[4]*ly**4
    ),
    (40, 104): (
        (-0.007149, 0.001056, -1.779e-05, 1.41e-07, -4.29e-10),
        lambda ly, *p: p[0] + p[1]*ly + p[2]*ly**2 + p[3]*ly**3 + p[4]*ly**4
    )
}

Definition at line 138 of file TTCluster.py.

◆ ly_CDF_params

dict TTCluster.ly_CDF_params

Initial value:

=  {
    (4.5, 13): (
        (-13.2, 1.976), 
        lambda ly, *p: exp(p[0] + p[1]*sqrt(ly))
    ),
    (13, 104): (
        (0.0108183, -0.179752, -19.2, 0.00772965),
        lambda ly, *p: p[0]*(1 - exp(p[1]*(ly+p[2]))) / (1 + exp(p[1]*(ly+p[2]))) + p[3]
    )
}

Definition at line 124 of file TTCluster.py.

◆ ly_linear_params

float TTCluster.ly_linear_params = 332.882, -58.7085

Definition at line 106 of file TTCluster.py.

◆ ly_loss_params

float TTCluster.ly_loss_params = 20.78, -0.26, 7.89, -3.06

Definition at line 80 of file TTCluster.py.

◆ ly_loss_sigma_params

float TTCluster.ly_loss_sigma_params = 6.8482, -0.5757, 3.4458

Definition at line 81 of file TTCluster.py.

◆ ly_max

int TTCluster.ly_max = 104

Definition at line 91 of file TTCluster.py.

◆ ly_min

float TTCluster.ly_min = 4.5

Definition at line 90 of file TTCluster.py.

◆ muonfile

TTCluster.muonfile = ROOT.TFile("$PWD/ship.conical.PG_13-TGeant4.root")

Definition at line 637 of file TTCluster.py.

◆ n_hor_planes

TTCluster.n_hor_planes = ship_geo.NuTauTT.n_hor_planes

Definition at line 191 of file TTCluster.py.

◆ n_solid_sipms

int TTCluster.n_solid_sipms = 8

Definition at line 41 of file TTCluster.py.

◆ n_tt_stations

TTCluster.n_tt_stations = ship_geo.NuTauTT.n

Definition at line 197 of file TTCluster.py.

◆ n_vert_planes

TTCluster.n_vert_planes = ship_geo.NuTauTT.n_vert_planes

Definition at line 192 of file TTCluster.py.

◆ nbins

TTCluster.nbins = 24

Definition at line 738 of file TTCluster.py.

◆ nud

dict TTCluster.nud = design2018['nud']

Definition at line 182 of file TTCluster.py.

◆ pitch

float TTCluster.pitch = 0.025

Definition at line 34 of file TTCluster.py.

◆ pnt

TTCluster.pnt = TTCluster(hit.GetDetectorID(), hit.GetX(), hit.GetY(), hit.GetEnergyLoss())

Definition at line 643 of file TTCluster.py.

◆ random_width_persent

float TTCluster.random_width_persent = 0.01

Definition at line 87 of file TTCluster.py.

◆ scifimat_hor

TTCluster.scifimat_hor = ship_geo.NuTauTT.scifimat_hor

Definition at line 193 of file TTCluster.py.

◆ scifimat_vert

TTCluster.scifimat_vert = ship_geo.NuTauTT.scifimat_vert

Definition at line 194 of file TTCluster.py.

◆ scifimat_width

TTCluster.scifimat_width = ship_geo.NuTauTT.scifimat_width

Definition at line 195 of file TTCluster.py.

◆ scifimat_z

TTCluster.scifimat_z = ship_geo.NuTauTT.scifimat_z

Definition at line 196 of file TTCluster.py.

◆ ship_geo

TTCluster.ship_geo

Initial value:

=  ConfigRegistry.loadpy("$FAIRSHIP/geometry/geometry_config.py", Yheight=dy, 
    tankDesign=dv, muShieldDesign=ds, nuTauTargetDesign=nud, CaloDesign=caloDesign, 
    strawDesign=strawDesign, muShieldGeo=geofile)

Definition at line 187 of file TTCluster.py.

◆ sigma_from_width

int TTCluster.sigma_from_width = 1 / 4.

Definition at line 116 of file TTCluster.py.

◆ sigma_in_percent

float TTCluster.sigma_in_percent = 0.01

Definition at line 113 of file TTCluster.py.

◆ sipm_hor_pos

int TTCluster.sipm_hor_pos = +1

GLOBAL VALUES AND PARAMETERS ############.

Definition at line 18 of file TTCluster.py.

◆ sipm_map

tuple TTCluster.sipm_map

Initial value:

=  (
    (-hw, -hw+edge, False),
    (-hw+edge, -hw+edge+charr, (-0.5, 63.5)),
    (-hw+edge+charr, -hw+edge+charr+gap, False),
    (-hw+edge+charr+gap, -hw+edge+array, (63.5, 127.5)),
    (-hw+edge+array, -hw+edge+array+biggap, False),
    (-hw+edge+array+biggap, -hw+edge+array+biggap+charr, (127.5, 191.5)),
    (-hw+edge+array+biggap+charr, -hw+edge+array+biggap+charr+gap, False),
    (-hw+edge+array+biggap+charr+gap, -hw+edge+array+biggap+array, (191.5, 255.5)),
    (-hw+edge+array+biggap+array, biggap/2., False),
    (biggap/2., biggap/2.+charr, (255.5, 319.5)),
    (biggap/2.+charr, biggap/2.+charr+gap, False),
    (biggap/2.+charr+gap, biggap/2.+array, (319.5, 383.5)),
    (biggap/2.+array, biggap/2.+array+biggap, False),
    (biggap/2.+array+biggap, biggap/2.+array+biggap+charr, (383.5, 447.5)),
    (biggap/2.+array+biggap+charr, biggap/2.+array+biggap+charr+gap, False),
    (biggap/2.+array+biggap+charr+gap, biggap/2.+array+biggap+charr+array, (447.5, 511.5)),
    (biggap/2.+array+biggap+charr+array, biggap/2.+array+biggap+charr+array+edge, False)
)

Definition at line 45 of file TTCluster.py.

◆ sipm_vert_pos

int TTCluster.sipm_vert_pos = -1

Definition at line 19 of file TTCluster.py.

◆ strawDesign

dict TTCluster.strawDesign = design2018['strawDesign']

Definition at line 184 of file TTCluster.py.

◆ tree

TTCluster.tree = muonfile.Get("cbmsim")

Definition at line 638 of file TTCluster.py.

◆ tt_points

float TTCluster.tt_points = []

EXAMPLE OF USING THE CLASS #######.

Definition at line 631 of file TTCluster.py.

◆ tt_raw

float TTCluster.tt_raw = []

Definition at line 633 of file TTCluster.py.

◆ xz_points

float TTCluster.xz_points = []

Definition at line 746 of file TTCluster.py.

◆ yz_points

float TTCluster.yz_points = []

Definition at line 747 of file TTCluster.py.

Classes

Functions

Variables

Function Documentation

◆ approx_function()

◆ channel_to_cm()

◆ cluster_generator()

◆ cluster_width_mean()

◆ cluster_width_random()

◆ cluster_width_sigma()

◆ cm_to_channel()

◆ create_cluster()

◆ edep_to_ly()

◆ GetMatLength()

◆ GetMatNum()

◆ GetMatQty()

◆ GetMatType()

◆ GetStationNum()

◆ global_to_local()

◆ is_realistic()

◆ local_to_global()

◆ ly_attenuation()

◆ ly_loss_mean()

◆ weigthed_mean_pos()

Variable Documentation

◆ array

◆ axs

◆ biggap

◆ bins

◆ caloDesign

◆ CDF_integral

◆ CDF_ly_params

◆ ch_max_num

◆ charr

◆ chpos_max

◆ chpos_min

◆ cluster_width_max

◆ cluster_width_mean_params

◆ cluster_width_min

◆ cluster_width_sigma_params

◆ design2018

◆ ds

◆ dv

◆ dy

◆ edge

◆ energy_range

◆ fig

◆ gap

◆ gaps_map

◆ geofile

◆ hpt_points

◆ hpt_raw

◆ hw

◆ is_sipm_hor_reversed

◆ is_sipm_vert_reversed

◆ k_cdfs_corr

◆ label

◆ loc

◆ ly_bins

◆ ly_CDF_landau_params

◆ ly_CDF_params

◆ ly_linear_params

◆ ly_loss_params

◆ ly_loss_sigma_params

◆ ly_max

◆ ly_min

◆ muonfile

◆ n_hor_planes

◆ n_solid_sipms

◆ n_tt_stations

◆ n_vert_planes

◆ nbins

◆ nud

◆ pitch

◆ pnt

◆ random_width_persent

◆ scifimat_hor

◆ scifimat_vert

◆ scifimat_width

◆ scifimat_z