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434f09f410
| Author | SHA1 | Date | |
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434f09f410 | ||
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9630edac10 |
5 changed files with 242 additions and 150 deletions
100
CHAOSa.py
100
CHAOSa.py
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@ -30,27 +30,27 @@ parser.add_argument("-res", type=str, nargs='+', help = "multiplies resolution w
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parser.add_argument("-equal", action='store_true', help = "puts temperature correction to BGO data") # on/off flag
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parser.add_argument("-cut",type=str, nargs='+',help=("Choose cut definitions for specific detectors and apply corresponding conditions:\n"
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"- D: Applies a condition on D1H and D2H that D2H lies within 15% of D1H, with a tolerance of ±30 units.\n"
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"- B: Ensures B channel is inside the range [106.38, 366.46].\n"
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"- nB: Ensures B channel is outside the range [106.38, 366.46].\n"
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"- As: For detector A, requires either A1H or A2H to be above threshold.\n"
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"- Ah: For detector A, requires one of A1H or A2H to be above threshold, while the other is below.\n"
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"- Cs: For detector C, requires either C1H or C2H to be above threshold.\n"
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"- Ch: For detector C, requires one of C1H or C2H to be above threshold, while the other is below.\n"
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"- E123s: For detector group E123, requires at least one of E1, E2, or E3 to be above threshold.\n"
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"- E123h: For detector group E123, requires one of E1, E2, or E3 to be above threshold, while the others are below.\n"
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"- B: Ensures B channel is above 35.\n"
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"- nB: Ensures B channel is lower 35.\n"
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"- A: For detector A\n"
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"- C: For detector C\n"
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"- E123: For detector group E123, requires at least one of E1, E2, or E3 to be above threshold.\n"
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"- E123_two: For detector group E123, requires at least two of E1, E2, or E3 to be above threshold."
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)
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)
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parser.add_argument("-mask",type=str, nargs='+',help=("Choose mask definitions and apply corresponding conditions:\n"
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"- HeA: Applies He-mask using A/E123 vs D (fishplot).\n"
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"- HeC: Applies He-mask using C/E123 vs D (fishplot).\n"))
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"- HeC: Applies He-mask using C/E123 vs D (fishplot).\n"
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"- He1: Applies He-mask for min(A,C)-D plot"))
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parser.add_argument("-deltaT", action='store_true', help = "saves deltatimes between events")
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parser.add_argument("-nameadd", type=str, nargs='+', help = "custom nameadd to add to filename")
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parser.add_argument("-Denergy", action='store_true', help = ' ')
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parser.add_argument("-Denergy", action='store_true', help = 'Histogramm of Detector D in MeV ')
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parser.add_argument("-Denergylog", action='store_true', help = 'Histogramm of Detector D in MeV and log scale')
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args = parser.parse_args()
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@ -74,6 +74,8 @@ from histframe import get_T
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from histframe import CmV
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from histframe import CmV_v
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from histframe import isCut
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from histframe import isMask
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from histframe import isMask_other
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from histframe import isMask_1D
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from histframe import get_MeV_mean
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from histframe import get_MeV
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@ -100,7 +102,7 @@ if args.tdhist and not args.res:
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if args.tdhistlog and not args.res:
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resV = 60*resV
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if args.res != None:
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resV=resV*int(args.res[0])
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resV=resV*float(args.res[0])
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if args.lim:
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minV = int(args.lim[0])
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@ -127,11 +129,14 @@ if args.notrig:
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for t in args.notrig:
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notrig.append(t)
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mask=[]
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if args.cut:
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nameadd += "_cut-" + "".join(args.cut)
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if args.mask:
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nameadd += "_mask-" + "".join(args.mask)
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for m in args.mask:
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mask.append(m)
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if args.lim:
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@ -222,6 +227,9 @@ def main():
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if args.Denergy:
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generate_hist_D_MeV()
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if args.Denergylog:
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generate_hist_D_MeV_log()
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if args.hist:
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generate_hist()
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@ -330,10 +338,10 @@ def generate_hist():
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if l[0] == 'H':
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timestamp = int(l[1])
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T = get_T(float(l[8]))
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if l[0] == 'EI' and len(l)>3*18 and conditions(l,args) and isFloat(args,timestamp):
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if l[0] == 'EI' and len(l)>3*18 and conditions(l,args) and isMask_other(l,T,mask) and isFloat(args,timestamp):
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for i,chan in enumerate(chans):
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b = value_HL(l,chan,u)
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b = value
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#b = value
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if minV <= b <= maxV:
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xb = int((b-minV)/resV)
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hist[xb,i+1] += 1
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@ -344,11 +352,11 @@ def generate_hist():
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################ 1D HISTOGRAM D in MeV ############################################################
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def generate_hist_D_MeV():
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#minV = 0
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#maxV = 50
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#resV = 0.1
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minV = 0
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maxV = 1000
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maxV = 100
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resV = 0.5
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#minV = 0
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#maxV = 1000
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bin = int((maxV-minV)/resV)
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hist = np.zeros((bin+1,2))
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@ -370,19 +378,59 @@ def generate_hist_D_MeV():
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if l[0] == 'EI' and len(l)>3*18 and conditions(l,args) and isFloat(args,timestamp):
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#T=15
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b = value_HL(l,'D1',u)+value_HL(l,'D2',u)
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bx = b #get_MeV(b,T)
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bx = get_MeV(b, T)
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if minV <= bx <= maxV:
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xb = int((bx-minV)/resV)
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hist[xb,1] += 1
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frame = pd.DataFrame(hist, columns = ['keV'] + ['D'])
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frame.to_csv(f'histograms/{filename}_D_keV.1dhist', sep = ' ', index = False)
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print(f'histograms/{filename}_D_keV.1dhist was created')
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frame = pd.DataFrame(hist, columns = ['MeV'] + ['D'])
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frame.to_csv(f'histograms/{filename}{nameadd}_D_MeV.1dhist', sep = ' ', index = False)
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print(f'histograms/{filename}{nameadd}_D_MeV.1dhist was created')
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def generate_hist_D_MeV_log():
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minX = 1
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maxX = 10000
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resX = 190*resV
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#minV = 0
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bin_x = int((maxX-minX)/resX)
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edges_x = np.logspace(np.log10(minX), np.log10(maxX), bin_x)
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hist = np.zeros((bin_x,2))
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for i, edge in enumerate(edges_x):
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hist[i][0] = edge
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with fileinput.input(files=(file), encoding="utf-8", errors='ignore') as f:
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timestamp = 0
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T=None
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for line in f:
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if not line.strip() or len(line.split()) < 9:
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continue
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l = line.split()
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if not any(x in l for x in ['EOF', 'X', 'xF']):
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if l[0] == 'H':
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timestamp = int(l[1])
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T = get_T(float(l[8]))
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if l[0] == 'EI' and len(l)>3*18 and conditions(l,args):
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#T=15
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b = value_HL(l,'D1',u)+value_HL(l,'D2',u)
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bx = get_MeV(b, T)
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if minX <= bx <= maxX:
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xb = np.digitize(bx, edges_x)-1
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hist[xb,1] += 1
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frame = pd.DataFrame(hist, columns = ['MeV'] + ['D'])
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frame.to_csv(f'histograms/{filename}{nameadd}_D_MeV.1dhistlog', sep = ' ', index = False)
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print(f'histograms/{filename}{nameadd}_D_MeV.1dhistlog was created')
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##########################################################################################
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def generate_hist_xlog():
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minX = 0.01
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maxX = 100
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resX = resV
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minX = 1
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maxX = 3500
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resX = 100*resV
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bin_x = int((maxX-minX)/resX)
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edges_x = np.logspace(np.log10(minX), np.log10(maxX), bin_x)
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@ -403,13 +451,13 @@ def generate_hist_xlog():
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if l[0] == 'H':
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timestamp = int(l[1])
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T = get_T(float(l[8]))
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if l[0] == 'EI' and len(l)>3*18 and conditions(l,args):
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if l[0] == 'EI' and len(l)>3*18 and conditions(l,args) and isMask_other(l,T,mask):
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for i,chan in enumerate(chans):
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#b = value_HL(l,chan,u)
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x_expr, x_op, x_next_op, x_next_channel = parse_channel_expression(chan)
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try: b = get_channel_value(l, u,x_expr, x_op, x_next_op, x_next_channel,T)
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except: b = 0
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if minV <= b <= maxX and isMask_1D(l,args.mask,T):
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if minV <= b <= maxX:
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xb = np.digitize(b, edges_x)-1
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hist[xb,i+1] += 1
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197
CHAOScustom.py
197
CHAOScustom.py
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@ -13,6 +13,7 @@ from histframe import get_T
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from histframe import get_MeV
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from histframe import CmV
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from histframe import isCut
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from histframe import isMask
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name = hf.names
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@ -27,15 +28,16 @@ resV = hf.resV
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pol = hf.pol
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#file = "2024-10-02-flight-2.EI"
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file = "chaos_sd_float.EI"
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#file = "data_sim/proton.EI"
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#file = "data_sim/e-.EI"
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#file = "data_sim/mu.EI"
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#file = "data_sim/he.EI"
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file = "2024-10-02-flight-2.EI"
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# file = "chaos_sd_float.EI"
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# file = "data_sim/proton.EI"
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# file = "data_sim/e-.EI"
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# file = "data_sim/mu.EI"file = "data_sim/he.EI"
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def main():
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def do_hist(cuts,val):
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print('do ' + val)
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print('with cuts: ' +str(cuts))
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bin_x = int((maxX-minX)/resX)
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bin_y = bin_x+1
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edges_x = np.logspace(np.log10(minX), np.log10(maxX), bin_x)
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@ -60,8 +62,13 @@ def main():
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T = get_T(float(l[8]))
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if l[0] == 'EI' and len(l)>3*18 and isCut(l,cuts) and T != None:
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if int(int(l[4].split(':')[0])/3) > deltacut:
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bx,by = get_values(l,T)
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if minX <= bx <= maxX and minY <= by <= maxY:
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if val=='fish':
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bx,by = get_values_fish(l,T)
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elif val =='other':
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bx,by = get_values_other(l,T)
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else:
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bx,by = get_values(l,T)
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if minX <= bx <= maxX and minY <= by <= maxY and isMask(bx,by,masks):
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bxx = np.digitize(bx, edges_x) - 1
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#bxx = int((bx-minX)/resX)
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byy = np.digitize(by, edges_y)
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@ -70,106 +77,112 @@ def main():
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frame = pd.DataFrame(hist, columns = ['MeV']+edges_y.astype(str).tolist())
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frame.to_csv(f'{folder}/{filename}', sep = ' ', index = False)
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print(f'{folder}/{filename} was created')
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# def mainZ():
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# bin_x = int((maxX-minX)/resX)
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# bin_y = bin_x+1
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# edges_x = np.logspace(np.log10(minX), np.log10(maxX), bin_x)
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# #edges_x = [minX + i*resX for i in range(bin_x+1)]
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# edges_y = np.logspace(np.log10(minY), np.log10(maxY), bin_y)
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# #hist = np.zeros((bin_x+1, bin_y+1))
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# hist = np.zeros((bin_x, bin_y+1))
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# for i, edge in enumerate(edges_x):
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# hist[i][0] = edge
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# with fileinput.input(files=("2024-10-02-flight-2.EI"), encoding="utf-8", errors='ignore') as f:
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# T=None
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# timestamp=0
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# for line in f:
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# if not line.strip():
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# continue
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# l = line.split()
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# if l[0] == 'H':
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# timestamp = int(l[1])
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# T = get_T(float(l[8]))
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# if l[0] == 'EI' and len(l)>3*18 and isCut(l,cuts) and 1727859780 < timestamp < 1727872980 and T != None:
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# if int(int(l[4].split(':')[0])/3) > deltacut:
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# bx,by,z = get_valuesZ(l,T)
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# if minX <= bx <= maxX and minY <= by <= maxY:
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# bxx = np.digitize(bx, edges_x) - 1
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# #bxx = int((bx-minX)/resX)
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# byy = np.digitize(by, edges_y) - 1
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# if 0 <= bxx < bin_x and 0 <= byy < bin_y:
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# hist[bxx, byy] = z
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# frame = pd.DataFrame(hist, columns = ['MeV']+edges_y.astype(str).tolist())
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# frame.to_csv(f'{folder}/{filename}', sep = ' ', index = False)
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# print(f'{folder}/{filename} was created')
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##################################################################################################
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def get_valuesZ(l,T):
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y = min(max(value(l,"A1H"),value(l,"A2H")),max(value(l,"C1H"),value(l,"C2H")))/max(value(l,"E1"),value(l,"E2"),value(l,"E3"))
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x = value(l,"D1H")+value(l,"D2H")
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x2 = get_MeV(x,T)
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z = value(l,"B")
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return x2,y,z
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print(f'{folder}/{filename} was created \n')
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###################################################################################################
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def get_values(l,T):
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#y = max(value(l,"C1H"),value(l,"C2H"))/value(l,"EH")q
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y = min(value_HL(l,"A",u),value_HL(l,"C",u))/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
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#y = value(l,"A",u)/1000
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#y = value(l,"C",u)/1000
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#y = min(value_HL(l,"A",u),value_HL(l,"C",u))/1000
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def get_values_fish(l,T):
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y = min(value_HL(l,"A",u),value_HL(l,"C",u))/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
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#y = value_HL(l,"A",u)/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
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x = value_HL(l,"D1",u)+value_HL(l,"D2",u)
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x2 = get_MeV(x,T)
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return x2,y
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def get_values_other(l,T):
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y = min(value_HL(l,"A",u),value_HL(l,"C",u))/1000
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#y = value_HL(l,"A",u)/1000
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x = value_HL(l,"D1",u)+value_HL(l,"D2",u)
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x2 = get_MeV(x,T)
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return x2,y
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cuts = ['A','hB','C','AeqC','D','E123']
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def get_values(l,T):
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y = min(value_HL(l,"A",u),value_HL(l,"C",u))/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
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#y = value(l,"A",u)/1000
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#y = value(l,"C",u)/1000
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#y = min(value_HL(l,"A",u),value_HL(l,"C",u))/1000
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x = value_HL(l,"D1",u)+value_HL(l,"D2",u)
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x2 = get_MeV(x,T)
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return x2,y
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deltacut = 0
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allcuts = [['A','B','C','AeqC','D'],['A','nB','C','AeqC','D']]
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#allcuts = [['A','D'],['A','B','D'],['A','nB','D']]
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allcuts = [['A','C','AeqC','D']]
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#masks = ['He1']
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masks=[]
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allfish = True
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allother = True
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filename = "chaos20_Cut"+ "".join(cuts)+"~min(A,C)dE-D.2dhist2log"
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#filename = "chaos20_Cut"+ "".join(cuts)+"~min(A,C)-D.2dhist2log"
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folder = "hists_fish"
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#folder = "hists_sim"
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minX = 2
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maxX = 10000
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minY = 0.02
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maxY = 20
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resV = 50*80*resV
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resX = resV/0.00362/polynom(15,*pol)
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if allother:
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for cut in allcuts:
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filename = "chaos_Cut"+ "".join(cut)+"~min(A,C)-D.2dhist2log"
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#filename = "chaosB35_Cut"+ "".join(cut)+"~A-D.2dhist2log"
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#filename = "simHe-chaos_Cut"+ "".join(cut)+"~min(A,C)-D.2dhist2log"
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do_hist(cut,'other')
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if allfish:
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for cut in allcuts:
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cut.append('E123')
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filename = "chaos_Cut"+ "".join(cut)+"~min(A,C)dE-D.2dhist2log"
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#filename = "chaosB35_Cut"+ "".join(cut)+"~AdE-D.2dhist2log"
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#filename = "simHe-chaos_Cut"+ "".join(cut)+"~min(A,C)dE-D.2dhist2log"
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do_hist(cut,'fish')
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#cuts = ['A','hB','C','AeqC','D','E123']
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||||
#filename = "chaos35_Cut"+ "".join(cuts)+"~min(A,C)dE-D.2dhist2log"
|
||||
#filename = "chaos35_Cut"+ "".join(cuts)+"~min(A,C)-D.2dhist2log"
|
||||
#folder = "hists_fish"
|
||||
|
||||
# filename = "chaos-dE-cut"+ "".join(cuts)+"~A-D.2dhist2log"
|
||||
# folder = "hists_dEdx"
|
||||
|
||||
#chaos
|
||||
#resV = 50*resV
|
||||
minY = 0.05
|
||||
maxY = 10
|
||||
# minY = 0.05
|
||||
# maxY = 10
|
||||
|
||||
minX = 10
|
||||
maxX = 170
|
||||
# minX = 10
|
||||
# maxX = 170
|
||||
|
||||
minX = 7
|
||||
maxX = 10000
|
||||
# minX = 7
|
||||
# maxX = 10000
|
||||
|
||||
#fish
|
||||
resV = 80*resV
|
||||
minY = 0.01
|
||||
maxY = 100
|
||||
minX = 5
|
||||
maxX = 500
|
||||
maxX = 10000
|
||||
resV = 50*resV
|
||||
# #fish
|
||||
# resV = 80*resV
|
||||
# minY = 0.01
|
||||
# maxY = 100
|
||||
# minX = 5
|
||||
# maxX = 500
|
||||
# maxX = 10000
|
||||
# resV = 50*resV
|
||||
|
||||
# minY = 0.02
|
||||
# maxY = 20
|
||||
# # minY = 0.02
|
||||
# # maxY = 20
|
||||
|
||||
mask_He = False
|
||||
if mask_He:
|
||||
minX,minY,maxX,maxY= 64,0.6,102, 1.5
|
||||
# mask_He = False
|
||||
# if mask_He:
|
||||
# minX,minY,maxX,maxY= 64,0.6,102, 1.5
|
||||
|
||||
#kontur
|
||||
# resV=3*resV
|
||||
|
|
@ -182,15 +195,9 @@ if mask_He:
|
|||
# minX = 1
|
||||
# maxX = 1000
|
||||
|
||||
|
||||
resX = resV/0.00362/polynom(15,*pol)
|
||||
#resX = resV/0.00362/polynom(15,*pol)
|
||||
#resX = resV/0.00362
|
||||
|
||||
deltacut = 0
|
||||
|
||||
###############################################
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
||||
#mainZ()
|
||||
71
histframe.py
71
histframe.py
|
|
@ -35,17 +35,17 @@ names[15] = "E1"; ch[15] = 8; thr[15] = 8; s[15] = 2.2; u[15] = 11.32
|
|||
names[16] = "E2"; ch[16] = 5; thr[16] = 8; s[16] = 2.2; u[16] = 11.32
|
||||
names[17] = "E3"; ch[17] = 2; thr[17] = 8; s[17] = 2.2; u[17] = 11.32
|
||||
|
||||
thr[9]=60
|
||||
thr[11]=60
|
||||
thr[9]=18
|
||||
thr[11]=18
|
||||
|
||||
thr[0] = 8
|
||||
thr[2] = 14
|
||||
thr[5] = 7
|
||||
thr[7] = 13
|
||||
|
||||
thr[13] = 14.73
|
||||
thr[13] = 13.19
|
||||
|
||||
thr[15] = 6.64; thr[16] = 6.54; thr[17] = 6.54
|
||||
thr[15] = 5.92; thr[16] = 5.92; thr[17] = 5.92
|
||||
|
||||
names_a = ["A1", "A2", "B", "C1", "C2", "D1", "D2", "E", "E1", "E2", "E3"]
|
||||
boundary = 2500 #mV
|
||||
|
|
@ -55,7 +55,7 @@ boundary = 2500 #mV
|
|||
|
||||
|
||||
mV = 14000
|
||||
minV = 0
|
||||
minV = -100
|
||||
maxV = 3500
|
||||
resV = 0.838214/2
|
||||
|
||||
|
|
@ -83,7 +83,7 @@ def get_MeV(keV,T):
|
|||
return keV/0.00362/polynom(T,*pol)
|
||||
|
||||
def get_MeV_mean(keV):
|
||||
return keV/0.00362/polynom(15,*pol)
|
||||
return keV/0.00362/polynom(14.92,*pol)
|
||||
|
||||
def get_MeV_H(keV,T):
|
||||
return keV/0.00362/line_H(T)
|
||||
|
|
@ -136,7 +136,7 @@ def valAC(l,channame,u):
|
|||
def isCut(l, cut):
|
||||
if not cut:
|
||||
return True
|
||||
|
||||
|
||||
u = 18*[1.0]
|
||||
|
||||
# Cut für D
|
||||
|
|
@ -148,22 +148,24 @@ def isCut(l, cut):
|
|||
if d1 < thresholds['D1H'] or d2 < thresholds['D2H']: return False
|
||||
if not (0.85 * (d1 - 30) < d2 < d1/0.85 + 30): return False
|
||||
|
||||
# Cut für B oder nB
|
||||
# if "B" in cut:
|
||||
# b = value(l,"B",u)
|
||||
# if not (106.38 < b < 366.46): return False
|
||||
# elif "nB" in cut:
|
||||
# b = value(l,"B",u)
|
||||
# if 106.38 < b < 366.46: return False
|
||||
elif "nB" or "lB" in cut:
|
||||
elif "nD" in cut:
|
||||
d1 = value_HL(l,'D1',u)
|
||||
d2 = value_HL(l,'D2',u)
|
||||
if d1 > thresholds['D1H'] and d2 > thresholds['D2H']: return False
|
||||
if (0.85 * (d1 - 30) < d2 < d1/0.85 + 30): return False
|
||||
|
||||
if "B" in cut or "hB" in cut:
|
||||
b = value(l,"B",u)
|
||||
if b > 35: return False
|
||||
if b < 17: return False
|
||||
#if b > 106.38: return False
|
||||
elif "B" or "hB" in cut:
|
||||
|
||||
elif "nB" in cut or "lB" in cut:
|
||||
b = value(l,"B",u)
|
||||
#if b < 366.46:
|
||||
#if b < 106.38: return False
|
||||
if b < 35: return False
|
||||
if b > 17: return False
|
||||
|
||||
elif "rB" in cut or "lB" in cut:
|
||||
b = value(l,"B",u)
|
||||
if b < 17 or b > 43: return False
|
||||
|
||||
if "A" in cut:
|
||||
a1 = value_HL(l,"A1",u)
|
||||
|
|
@ -205,6 +207,35 @@ def isCut(l, cut):
|
|||
if not (e1 > thres or e2 > thres or e3 > thres): return False
|
||||
|
||||
return True
|
||||
|
||||
###########################################################################################
|
||||
|
||||
def get_values_fish(l,T):
|
||||
y = min(value_HL(l,"A",u),value_HL(l,"C",u))/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
|
||||
#y = value_HL(l,"A",u)/max(value(l,"E1",u),value(l,"E2",u),value(l,"E3",u))
|
||||
x = value_HL(l,"D1",u)+value_HL(l,"D2",u)
|
||||
x2 = get_MeV(x,T)
|
||||
return x2,y
|
||||
|
||||
def get_values_other(l,T):
|
||||
y = min(value_HL(l,"A",u),value_HL(l,"C",u))/1000
|
||||
#y = value_HL(l,"A",u)/1000
|
||||
x = value_HL(l,"D1",u)+value_HL(l,"D2",u)
|
||||
x2 = get_MeV(x,T)
|
||||
return x2,y
|
||||
|
||||
def isMask(x,y,mask):
|
||||
if 'He1' in mask:
|
||||
if x<60 or x>100: return False
|
||||
if y<0.26 or y>0.61:return False
|
||||
return True
|
||||
|
||||
def isMask_other(l,T,mask):
|
||||
x,y = get_values_other(l, T)
|
||||
if 'He1' in mask:
|
||||
if x<60 or x>100: return False
|
||||
if y<0.26 or y>0.61:return False
|
||||
return True
|
||||
|
||||
|
||||
def isMask_1D(l, mask,T):
|
||||
|
|
|
|||
|
|
@ -106,7 +106,7 @@ def do_2dhist():
|
|||
y_edges = data.columns[1:].astype(float).tolist()
|
||||
|
||||
# Hauptplot: 2D-Histogramm
|
||||
cb = ax_main.pcolormesh(x_edges, y_edges, c, cmap=cmap, shading='nearest', vmin=1, norm='log')
|
||||
cb = ax_main.pcolormesh(x_edges, y_edges, c, cmap=cmap, shading='nearest', vmin=1git status, norm='log')
|
||||
ax_main.set_yscale('log') # Logarithmische Skala für y
|
||||
|
||||
# Summenberechnung
|
||||
|
|
|
|||
28
xplot.py
28
xplot.py
|
|
@ -106,10 +106,16 @@ def do_1dhist():
|
|||
#plt.axvline(x=6.5, color='k', linestyle = '--', lw=2, label = 'thr(E123) = 6.5 mV') 6.593
|
||||
#plt.axvline(x=14, color='r', linestyle = '--', lw=2, label = 'thr(E) = 14 mV')
|
||||
#plt.axvline(x=67, color='k', linestyle = '--', lw=2, label = 'thr(E123) = 67 keV')
|
||||
#plt.axvline(x=60, color='r', linestyle = '--', lw=2, label = 'thr(E) = 67 keV')
|
||||
#plt.axvline(x=60, color='r', linestyle = '--', lw=2, label = 'thr(E) = 60 keV')
|
||||
|
||||
#plt.axvline(x=20, color='blue', linestyle='--', linewidth=2, label='20 mV (flight)')
|
||||
#plt.axvline(x=60, color='black', linestyle='--', linewidth=2, label='60 mV (data analysis)')
|
||||
#plt.axvline(x=18, color='black', linestyle='--', linewidth=2, label='18 mV (2 MeV)')
|
||||
#plt.axvline(x=2, color='black', linestyle='--', linewidth=2, label='2 MeV')
|
||||
#plt.axvline(x=9, color='r', linestyle='--', linewidth=2, label='9 mV (1 MeV)')
|
||||
|
||||
plt.axvline(x=17, color='red', linestyle='--', linewidth=2, label='17 mV')
|
||||
plt.axvline(x=43, color='black', linestyle='--', linewidth=2, label='43 mV')
|
||||
|
||||
|
||||
plot_layout(title, energy, limits,None,None,None)
|
||||
|
||||
|
|
@ -182,7 +188,7 @@ def do_2dhist():
|
|||
c = np.array(data)[:,1:].T
|
||||
|
||||
Dcuts = False
|
||||
ACcuts = True
|
||||
ACcuts = False
|
||||
AeqC = False
|
||||
Ecuts = False
|
||||
Lowcal = False
|
||||
|
|
@ -192,13 +198,13 @@ def do_2dhist():
|
|||
vmin = 1
|
||||
if Dcuts:
|
||||
plt.plot(x_edges, np.multiply(np.add(x_edges,-30), 0.85), 'r-', lw=2,
|
||||
label=("Cuts: $0.85 \\cdot (D1H - 30$ mV$)< D2H < D1H/0.85 + 30$mV"))
|
||||
label=("Cuts: $0.85 \\cdot (D1 - 30$ mV$)< D2 < D1/0.85 + 30$mV"))
|
||||
#plt.plot(x_edges,np.multiply(x_edges,1.15)+30, 'r-', lw=1.5)
|
||||
plt.plot(x_edges,np.add(np.divide(x_edges,0.85),30), 'r-', lw=2)
|
||||
#plt.plot([0, 30], [30, 30], 'r--', lw=2)
|
||||
#plt.plot([30, 30], [30, 0], 'r--', lw=2)
|
||||
plt.axhline(y=60, color='r', linestyle = '--', lw=1.5,label = " $D1H, D2H > 60$ mV")
|
||||
plt.axvline(x=60, color='r', linestyle = '--', lw=1.5,)
|
||||
plt.axhline(y=25, color='r', linestyle = '--', lw=1.5,label = " $D1, D2 > 25$ mV")
|
||||
plt.axvline(x=25, color='r', linestyle = '--', lw=1.5,)
|
||||
|
||||
if ACcuts:
|
||||
plt.axhline(y=15, color='r', linestyle = '-', lw=1.5, label = "thr['C1H'] = 10 mV; thr['C2H'] = 15 mV")
|
||||
|
|
@ -217,13 +223,13 @@ def do_2dhist():
|
|||
|
||||
if Dcuts:
|
||||
plt.plot(x_edges, np.multiply(np.add(x_edges,-30), 0.85), 'r-', lw=2,
|
||||
label=("Cuts: $0.85 \\cdot (D1H - 30$ mV$)< D2H < D1H/0.85 + 30$mV"))
|
||||
label=("Cuts: $0.85 \\cdot (D1 - 30$ mV$)< D2 < D1/0.85 + 30$mV"))
|
||||
#plt.plot(x_edges,np.multiply(x_edges,1.15)+30, 'r-', lw=1.5)
|
||||
plt.plot(x_edges,np.add(np.divide(x_edges,0.85),30), 'r-', lw=2)
|
||||
#plt.plot([0, 30], [30, 30], 'r--', lw=2)
|
||||
#plt.plot([30, 30], [30, 0], 'r--', lw=2)
|
||||
plt.axhline(y=60, color='r', linestyle = '--', lw=1.5,label = " $D1H, D2H > 60$ mV")
|
||||
plt.axvline(x=60, color='r', linestyle = '--', lw=1.5,)
|
||||
plt.axhline(y=18, color='r', linestyle = '--', lw=1.5,label = " $D1, D2 > 18$ mV")
|
||||
plt.axvline(x=18, color='r', linestyle = '--', lw=1.5,)
|
||||
|
||||
|
||||
if Ecuts:
|
||||
|
|
@ -298,8 +304,8 @@ def do_2dhist():
|
|||
cbar = plt.colorbar(contour, orientation = 'vertical', shrink = 0.95, pad = 0.1)
|
||||
|
||||
else:
|
||||
cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='nearest', vmin=vmin, vmax = 2000,norm='log')
|
||||
#cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='auto', vmin=vmin, norm='log')
|
||||
#cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='nearest', vmin=vmin, vmax = 2000,norm='log')
|
||||
cb = plt.pcolormesh(x_edges, y_edges,c, cmap = cmap, shading='auto', vmin=vmin, norm='log')
|
||||
#cb = plt.pcolormesh(np.multiply(x_edges,f), y_edges,c, cmap = cmap, shading='nearest', vmin=vmin, vmax=30, norm='log')
|
||||
cbar = plt.colorbar(cb, orientation = 'vertical', shrink = 0.95, pad = 0.1)
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue