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revert changes to material scan script
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Chao Peng committed Jul 23, 2023
1 parent 1878986 commit 32be753
Showing 1 changed file with 6 additions and 91 deletions.
97 changes: 6 additions & 91 deletions scripts/subdetector_tests/material_scan.py
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
# SPDX-License-Identifier: LGPL-3.0-or-later
# Copyright (C) 2023 Chao Peng
'''
A script to scan the materials thickness (X0 or Lambda) by detectors over eta
A script to scan the materials thickness (X0 or Lambda) over eta
It uses dd4hep::rec::MaterialManager::placementsBetween to check the material layers, and then uses the detector
alignment to transform world coordinates to local coordiantes, and then assigns the materials to a detector based
@@ -34,7 +34,6 @@
COLORS = ['royalblue', 'indianred', 'forestgreen', 'gold', 'darkviolet', 'orange', 'darkturquoise']
# a specified color for Others, this should not be included in COLORS
OTHERS_COLOR = 'silver'
MAX_N_MATS = 50


# FIXME: this is a work-around to an issue of dd4hep::rec::MaterialManager::placementsBetween
@@ -157,10 +156,6 @@ def material_scan(desc, start, end, epsilon, int_dets=None, thickness_corrector=
dest='compact',
help='Top-level xml file of the detector description.'
)
parser.add_argument(
'-o', default='.', dest='outdir',
help='Output directory.'
)
parser.add_argument(
'--path-r', type=float, default=400., # 120.,
help='R_xy (cm) where the scan stops.'
@@ -193,10 +188,6 @@ def material_scan(desc, start, end, epsilon, int_dets=None, thickness_corrector=
'--value-type', default='X0',
help='Choose one in {}.'.format(list(ALLOWED_VALUE_TYPES.keys()))
)
parser.add_argument(
'--groupby-materials', action='store_true',
help='Enable it to group the results by materials instead of by detectors.'
)
parser.add_argument(
'--detectors',
# default='all',
@@ -214,8 +205,6 @@ def material_scan(desc, start, end, epsilon, int_dets=None, thickness_corrector=
print('Cannot find value {}, choose one in {}'.format(args.value_type, list(ALLOWED_VALUE_TYPES.keys())))
exit(-1)

os.makedirs(args.outdir, exist_ok=True)

# scan parameters
path_r = args.path_r
phi = args.phi
@@ -257,86 +246,12 @@ def material_scan(desc, start, end, epsilon, int_dets=None, thickness_corrector=
th_corr.scan_missing_thickness(desc, start_point, np.array(start_point) + np.array([100., 50., 0.]),
dz=0.0001, epsilon=args.epsilon)

# value-type
vt = ALLOWED_VALUE_TYPES[args.value_type]

# material-based scan
if args.groupby_materials:
vals = np.zeros(shape=(len(etas), MAX_N_MATS))
mats = []
for i, eta in enumerate(etas):
if i % PROGRESS_STEP == 0:
print('Scanned {:d}/{:d} for {:.2f} <= eta <= {:.2f}'.format(i, len(etas), etas[0], etas[-1]),
end='\r', flush=True)
# scan material layers
end_x = path_r*np.cos(phi/180.*np.pi)
end_y = path_r*np.sin(phi/180.*np.pi)
end_z = path_r*np.sinh(eta)
# print('({:.2f}, {:.2f}, {:.2f})'.format(end_x, end_y, end_z))
dfr = material_scan(desc, start_point, (end_x, end_y, end_z), epsilon=args.epsilon, int_dets=dets, thickness_corrector=th_corr)

# aggregated values for detectors
x0_vals = dfr.groupby('material')[vt[0]].sum().to_dict()
# update material list
for mat in x0_vals.keys():
if mat not in mats:
mats.append(mat)
# save material scan results
for j, mat in enumerate(mats):
vals[i, j] = x0_vals.get(mat, 0.)
print('Scanned {:d}/{:d} lines for {:.2f} < eta < {:.2f}'.format(len(etas), len(etas), etas[0], etas[-1]))

# aggregated data for plots
dfa = pd.DataFrame(data=vals[:, :len(mats)], columns=mats, index=etas)
# sort by total thickness
smats = [d for d in dfa.sum().sort_values(ascending=False).index]
dfa.to_csv(os.path.join(args.outdir, 'material_scan_agg.csv'))

# plot material scan
fig, ax = plt.subplots(figsize=(16, 8), dpi=160,
gridspec_kw={'top': 0.9, 'bottom': 0.2, 'left': 0.08, 'right': 0.98})

# group some materials into "Others" if there're no enough colors
plot_mats = smats
if len(smats) > len(COLORS):
group_mats = smats[len(COLORS):]
dfa.loc[:, OTHERS_NAME] += dfa.loc[:, group_mats].sum(axis=1)
print('Materials {} are grouped into {} due to limited number of colors.'.format(group_mats, OTHERS_NAME))
plot_mats = sdets[:len(COLORS)]

bottom = np.zeros(len(dfa))
width = np.mean(np.diff(dfa.index))
for col, c in zip(plot_mats, COLORS):
ax.fill_between(dfa.index, bottom, dfa[col].values + bottom, label=col, step='mid', color=c)
bottom += dfa[col].values
# only plot Others if there are any
if OTHERS_NAME in dfa.columns and dfa[OTHERS_NAME].sum() > 0.:
ax.fill_between(dfa.index, bottom, dfa[OTHERS_NAME].values + bottom, label=OTHERS_NAME, step='mid', color=OTHERS_COLOR)

# formatting
ax.tick_params(which='both', direction='in', labelsize=22)
ax.set_xlabel('$\eta$', fontsize=22)
ax.set_ylabel('{} ($R_{{xy}} \leq {:.1f}$ cm)'.format(vt[1], args.path_r), fontsize=22)
ax.xaxis.set_major_locator(MultipleLocator(0.5))
ax.xaxis.set_minor_locator(MultipleLocator(0.1))
ax.yaxis.set_major_locator(MultipleLocator(vt[2]))
ax.yaxis.set_minor_locator(MultipleLocator(vt[3]))
ax.grid(ls=':', which='both')
ax.set_axisbelow(False)
ax.set_xlim(args.eta_min, args.eta_max)
ax.set_ylim(0., ax.get_ylim()[1]*1.1)
ax.legend(bbox_to_anchor=(0.0, 0.9, 1.0, 0.1), ncol=2, loc="upper center", fontsize=22,
borderpad=0.2, labelspacing=0.2, columnspacing=0.6, borderaxespad=0.05, handletextpad=0.4)
# ax.set_yscale('log')
fig.savefig(os.path.join(args.outdir, 'material_scan.png'))
exit(0)

# detector-based scan
# array for detailed data
# number of materials cannot be pre-determined, so just assign a large number to be safe
vals = np.zeros(shape=(len(etas), len(dets) + 1, MAX_N_MATS))
vals = np.zeros(shape=(len(etas), len(dets) + 1, 50))
dets2 = dets + [OTHERS_NAME]
det_mats = {d: [] for d in dets2}
vt = ALLOWED_VALUE_TYPES[args.value_type]

for i, eta in enumerate(etas):
if i % PROGRESS_STEP == 0:
@@ -371,10 +286,10 @@ def material_scan(desc, start, end, epsilon, int_dets=None, thickness_corrector=
if sort_dets:
sdets = [d for d in dfa.sum().sort_values(ascending=False).index if d != OTHERS_NAME]
dfa = dfa[sdets + [OTHERS_NAME]]
dfa.to_csv(os.path.join(args.outdir, 'material_scan_agg.csv'))
dfa.to_csv('material_scan_agg.csv')

# plots
pdf = matplotlib.backends.backend_pdf.PdfPages(os.path.join(args.outdir, 'material_scan_details.pdf'))
pdf = matplotlib.backends.backend_pdf.PdfPages('material_scan_details.pdf')
fig, ax = plt.subplots(figsize=(16, 8), dpi=160,
gridspec_kw={'top': 0.9, 'bottom': 0.2, 'left': 0.08, 'right': 0.98})

@@ -411,7 +326,7 @@ def material_scan(desc, start, end, epsilon, int_dets=None, thickness_corrector=
ax.legend(bbox_to_anchor=(0.0, 0.9, 1.0, 0.1), ncol=4, loc="upper center", fontsize=22,
borderpad=0.2, labelspacing=0.2, columnspacing=0.6, borderaxespad=0.05, handletextpad=0.4)
# ax.set_yscale('log')
fig.savefig(os.path.join(args.outdir, 'material_scan.png'))
fig.savefig('material_scan.png')
pdf.savefig(fig)
plt.close(fig)

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