def update(Q,qT,angle,height):
params=gen_params()
params['T_t']=qT
params['Q']=Q
_zh=np.linspace(0.1,1,50)
_xb=np.linspace(0.1,1,50)
xb,zh=np.meshgrid(_xb, _zh)
params['x_bj']=xb
params['z_h']=zh
yh=evaluate(rat.get_yh,params)
camera = dict(
up=dict(x=0, y=0, z=1),
center=dict(x=0, y=0, z=0),
eye=dict(x=2.5*np.cos(angle*np.pi/180), y=2.5*np.sin(angle*np.pi/180), z=height))
trace= go.Surface(y=tuple(xb),x=tuple(zh),z=tuple(yh),)
layout = go.Layout(
title="" ,
autosize=False,
width=700,
height=700,
scene=dict(
aspectmode='cube',
camera=camera,
yaxis=dict(title='x<sub>Bj</sub>'),
xaxis=dict(title='z<sub>h</sub>'),
zaxis=dict(title='y<sub>h</sub>' ),))
data=[trace]
fig = go.Figure(data=data, layout=layout)
return fig
def update(Ri, Q, qT, xi, zeta, Mki, Mkf, dkT, kiT, angle, height):
params = gen_params()
params['xi'] = xi
params['zeta'] = zeta
params['M_ki'] = Mki
params['M_kf'] = Mkf
params['T_t'] = qT
params['delta_k_t'] = dkT
params['k_i_t'] = kiT
params['Q'] = Q
_xb = np.linspace(xi, 1, 50)
_zh = np.linspace(zeta, 1, 50)
xb, zh = np.meshgrid(_xb, _zh)
params['x_bj'] = xb
params['z_h'] = zh
if Ri == 'R1': R = evaluate(rat.get_R1, params)
if Ri == 'R2': R = evaluate(rat.get_R2, params)
if Ri == 'R3': R = evaluate(rat.get_R3, params)
if Ri == 'R1prime': R = evaluate(rat.get_R4, params)
R = np.abs(R)
R[R > 1] = 1
camera = dict(up=dict(x=0, y=0, z=1),
center=dict(x=0, y=0, z=0),
eye=dict(x=2.5 * np.cos(angle * np.pi / 180),
y=2.5 * np.sin(angle * np.pi / 180),
z=height))
trace = go.Surface(
y=tuple(xb),
x=tuple(zh),
z=tuple(R),
)
layout = go.Layout(title="",
autosize=False,
width=700,
height=700,
scene=dict(
aspectmode='cube',
camera=camera,
yaxis=dict(title='x<sub>Bj</sub>', range=(0, 1)),
xaxis=dict(title='z<sub>h</sub>', range=(0, 1)),
zaxis=dict(title=Ri, range=(0, 1)),
))
data = [trace]
fig = go.Figure(data=data, layout=layout)
return fig
def update(Ri,qT,xbjmin,xbjmax,zh,xi,zeta,M,Mki,Mkf,dkT,kiT):
params=gen_params()
params['M']=M
params['z_h']=zh
params['xi']=xi
params['zeta']=zeta
params['T_t']=qT
params['delta_k_t']=dkT
params['M_ki']=Mki
params['M_kf']=Mkf
params['k_i_t']=kiT
_xb=np.linspace(xbjmin,xbjmax,100)
_Q =np.linspace(0.8,2.0,100)
xb,Q=np.meshgrid(_xb,_Q)
params['Q']=Q
params['x_bj']=xb
if Ri=='R1': R=evaluate(rat.get_R1,params)
if Ri=='R2': R=evaluate(rat.get_R2,params)
if Ri=='R3': R=evaluate(rat.get_R3,params)
if Ri=='R1prime': R=evaluate(rat.get_R4,params)
R=np.abs(R)
R[R>1]=1
data = [go.Heatmap(x=_xb,y=_Q,z=R,colorscale='Jet'),]
layout = go.Layout(
width = 800,
height = 500,
xaxis = dict(
#nticks = 10,
#domain = [0, 0.45],
title = 'x<sub>Bj'
),
yaxis = dict(
#scaleanchor = "x",
#domain = [0, 0.45],
title = "Q [GeV]"
),
showlegend= False
)
fig = go.Figure(data=data, layout=layout)
return fig
def update(zh, qT, W2max):
params = gen_params()
params['T_t'] = qT
params['z_h'] = zh
_Q = np.linspace(0.5, 2.5, 100)
_xb = np.linspace(0.1, 0.8, 100)
xb, Q = np.meshgrid(_xb, _Q)
params['Q'] = Q
params['x_bj'] = xb
W2 = evaluate(rat.get_W2, params)
W2[W2 < 0] = np.nan
W2[W2 > W2max] = np.nan
data = [
go.Heatmap(x=_xb, y=_Q, z=W2, colorscale='Jet'),
]
layout = go.Layout(
width=800,
height=500,
xaxis=dict(
#nticks = 10,
#domain = [0, 0.45],
title="x<sub>Bj"),
yaxis=dict(
#scaleanchor = "x",
#domain = [0, 0.45],
title="Q [GeV]"),
showlegend=False)
fig = go.Figure(data=data, layout=layout)
return fig
def update(had, qua, M, x, Q, yHmin, yHmax, xi, zeta, Mki, Mkf, dkT, kiT):
params = gen_params()
params['M'] = M
params['xi'] = xi
params['zeta'] = zeta
#params['T_t']=qT
params['delta_k_t'] = dkT
params['M_ki'] = Mki
params['M_kf'] = Mkf
params['k_i_t'] = kiT
params['Q'] = Q
params['x_bj'] = x
if had == 'pion': params['M_h'] = 0.139
elif had == 'kaon': params['M_h'] = 0.497
Mh = params['M_h']
xN = evaluate(rat.get_xN, params)
#etamin=evaluate(rat.get_etamin,params)
#etamax=evaluate(rat.get_etamax,params)
#yP=np.log(Q/xN/M)
#yH=np.linspace(etamin,etamax,100)
#dy=yP-yH
#Htmax=[]
#for eta in yH:
# params['eta']=eta
# Htmax.append(evaluate(rat.get_Htmax,params))
#Htmax=np.array(Htmax)
#zh=(xN*np.sqrt(Mh**2+Htmax**2)*M/(Q**2-xN**2*M**2))*2*np.cosh(dy)
#qtmax=Htmax/zh
#line1 = go.Scatter(
# x = yH,
# y = np.zeros(yH.size),
# name = '',
# line = dict(
# color = ('rgb(22, 96, 167)'),
# width = 4,
# dash = 'solid'))
#line2 = go.Scatter(
# x = yH,
# y = qtmax/Q,
# name = 'High Q',
# line = dict(
# color = ('rgb(22, 96, 167)'),
# width = 4,
# dash = 'dot'),
# fill='tonexty')
_yH = np.linspace(yHmin, yHmax, 50)
_qT = np.linspace(0, 2, 50)
yH, qT = np.meshgrid(_yH, _qT)
yP = np.log(Q / xN / M)
pf = xN * M / (Q**2 - xN**2 * M**2) * 2 * np.cosh(yP - yH)
zh = np.sqrt(pf**2 * Mh**2 / (1 - pf**2 * qT**2))
params['z_h'] = zh
if qua == 'R1': R = np.abs(evaluate(rat.get_R1, params))
elif qua == 'R2': R = np.abs(evaluate(rat.get_R2, params))
elif qua == 'R3': R = np.abs(evaluate(rat.get_R3, params))
elif qua == 'R1prime': R = np.abs(evaluate(rat.get_R4, params))
R[R > 1] = np.nan
data = [go.Heatmap(x=_yH, y=_qT, z=R, colorscale='Jet')] #[line1,line2,R1]
layout = go.Layout(width=800,
height=500,
xaxis=dict(title="y<sub>h</sub>", range=(None, yP)),
yaxis=dict(title="q<sub>T</sub>/Q", range=(0, 2)),
showlegend=True)
fig = go.Figure(data=data, layout=layout)
return fig
def update(exp, had, qua, M, W2cut, xmax, qT, zh, xi, zeta, Mki, Mkf, dkT,
kiT):
#return exp#'%f'%M
params = gen_params()
params['M'] = M
params['z_h'] = zh
params['xi'] = xi
params['zeta'] = zeta
params['T_t'] = qT
params['delta_k_t'] = dkT
params['M_ki'] = Mki
params['M_kf'] = Mkf
params['k_i_t'] = kiT
if exp == 'JLab': s = M**2 + 2 * 11 * M
elif exp == 'HERMES': s = M**2 + 2 * 27.6 * M
elif exp == 'COMPASS': s = M**2 + 2 * 160 * M
if had == 'pion': params['M_h'] = 0.139
elif had == 'kaon': params['M_h'] = 0.497
Q2min = 1.
xmin = Q2min / (s - M)
_xb = np.linspace(xmin, xmax, 50)
Q2max = xmax * (s - M**2)
_Q = np.linspace(Q2min, Q2max, 100)**0.5
#print(Q2min,Q2max)
xb, Q = np.meshgrid(_xb, _Q)
params['Q'] = Q
params['x_bj'] = xb
if qua == 'R1': R = np.abs(evaluate(rat.get_R1, params))
elif qua == 'R2': R = np.abs(evaluate(rat.get_R2, params))
elif qua == 'R3': R = np.abs(evaluate(rat.get_R3, params))
elif qua == 'R1prime': R = np.abs(evaluate(rat.get_R4, params))
elif qua == 'xN/xb': R = evaluate(rat.get_xN, params) / xb
elif qua == 'zN/zh': R = evaluate(rat.get_zN, params) / zh
R[R > 1] = np.nan
R[Q**2 > xb * (s - M)] = np.nan
R[W2cut > (M**2 + Q**2 / xb - Q**2)] = np.nan
#print(R)
data = [
go.Heatmap(x=_xb, y=_Q, z=R, colorscale='Jet'),
]
layout = go.Layout(
width=800,
height=500,
xaxis=dict(
#nticks = 10,
#domain = [0, 0.45],
title="x<sub>Bj"),
yaxis=dict(
#scaleanchor = "x",
#domain = [0, 0.45],
title="Q [GeV]"),
showlegend=False)
fig = go.Figure(data=data, layout=layout)
return fig
def update(exp, M, W2cut, xmax, Q):
params = gen_params()
params['M'] = M
if exp == 'JLab': s = M**2 + 2 * 11 * M
elif exp == 'HERMES': s = M**2 + 2 * 27.6 * M
elif exp == 'COMPASS': s = M**2 + 2 * 160 * M
Q2min = 1.
xmin = Q2min / (s - M)
xb = np.linspace(xmin, xmax, 50)
Q2_low = xb / (1 - xb) * (W2cut - M**2)
Q2_high = xb * (s - M**2)
params['x_bj'] = xb
params['Q'] = Q2_low**0.5
xN_low = evaluate(rat.get_xN, params)
params['Q'] = Q2_high**0.5
xN_high = evaluate(rat.get_xN, params)
line1 = go.Scatter(x=xb,
y=xN_low / xb,
name='Low Q',
line=dict(color=('rgb(22, 96, 167)'),
width=4,
dash='solid'))
line2 = go.Scatter(x=xb,
y=xN_high / xb,
name='High Q',
line=dict(color=('rgb(22, 96, 167)'),
width=4,
dash='dot'),
fill='tonexty')
xmin = Q**2 / (s - M)
_xmax = Q**2 / (W2cut - M**2 + Q**2)
xb = np.linspace(xmin, min(_xmax, xmax), 50)
params['x_bj'] = xb
params['Q'] = Q
xN = evaluate(rat.get_xN, params)
line3 = go.Scatter(x=xb,
y=xN / xb,
name='Q',
line=dict(
color=('rgb(205, 12, 24)'),
width=4,
))
data = [line1, line2, line3]
layout = go.Layout(width=800,
height=500,
xaxis=dict(title="x<sub>Bj"),
yaxis=dict(title="x<sub>N</sub>/x<sub>Bj</sub>",
range=(0.9, 1)),
showlegend=True)
fig = go.Figure(data=data, layout=layout)
return fig
def update(exp,had,qT,W2cut,xmax,x,Q):
params=gen_params()
M=0.938
if exp=='JLab': s = M**2 + 2*11*M
elif exp=='HERMES': s = M**2 + 2*27.6*M
elif exp=='COMPASS': s = M**2 + 2*160*M
if had=='pion': params['M_h']=0.139
elif had=='kaon': params['M_h']=0.497
params['T_t']=qT
zh=np.linspace(0.1,0.8,50)
Q2min=1.
xmin=Q2min/(s-M)
xb=np.linspace(xmin,xmax,50)
Q2_low = xb/(1-xb)*(W2cut-M**2)
Q2_high = xb*(s-M**2)
params['x_bj']=xb
zN_up=[]
zN_do=[]
for _zh in zh:
params['z_h']=_zh
params['Q']=Q2_low**0.5
zN_vals=evaluate(rat.get_zN,params)
params['Q']=Q2_high**0.5
zN_vals=np.append(zN_vals,evaluate(rat.get_zN,params))
zN_do.append(np.amin(zN_vals))
zN_up.append(np.amax(zN_vals))
zN_up=np.array(zN_up)
zN_do=np.array(zN_do)
line1 = go.Scatter(
x = zh,
y = zN_do/zh,
name = 'Low Q',
line = dict(
color = ('rgb(22, 96, 167)'),
width = 4,
dash = 'solid'))
line2 = go.Scatter(
x = zh,
y = zN_up/zh,
name = 'High Q',
line = dict(
color = ('rgb(22, 96, 167)'),
width = 4,
dash = 'dot'),
fill='tonexty')
params['z_h']=zh
params['Q']=Q
zN=evaluate(rat.get_zN,params)
line3 = go.Scatter(
x = zh,
y = zN/zh,
name = 'Q',
line = dict(
color = ('rgb(205, 12, 24)'),
width = 4,))
data = [line1,line2,line3]
layout = go.Layout(
width = 800,
height = 500,
xaxis = dict(title = "z<sub>h"),
yaxis = dict(title = "z<sub>N</sub>/z<sub>h</sub>",range=(0.8,1)),
showlegend= True
)
fig = go.Figure(data=data, layout=layout)
return fig