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outsource reconstruction data in separate arrays

Merged outsource reconstruction data in separate arrays
add-fitinf into master
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Merged Zineb Aly requested to merge add-fitinf into master
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notebooks/OfflineReader_tutorial.ipynb
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%% Cell type:code id: tags:
``` python
# Add file to current python path
from pathlib import Path
import sys
sys.path.append(str(Path.cwd().parent))
Path.cwd()
# test samples directory - aanet test file
files_path = Path.cwd().parent / 'tests/samples'
aanet_file = files_path / 'aanet_v2.0.0.root'
```
%% Cell type:markdown id: tags:
# Read offline files (aanet)
%% Cell type:code id: tags:
``` python
import km3io as ki
r = ki.OfflineReader(aanet_file)
r
```
%% Output
<km3io.offline.OfflineReader at 0x7fa25a11fc50>
<km3io.offline.OfflineReader at 0x7fb60c2dc590>
%% Cell type:markdown id: tags:
To explore all the available branches in our offline file:
%% Cell type:code id: tags:
``` python
r.keys
```
%% Output
Events keys are:
id
det_id
mc_id
run_id
mc_run_id
frame_index
trigger_mask
trigger_counter
overlays
hits
trks
w
w2list
w3list
mc_t
mc_hits
mc_trks
comment
index
flags
t.fSec
t.fNanoSec
Hits keys are:
hits.id
hits.dom_id
hits.channel_id
hits.tdc
hits.tot
hits.trig
hits.pmt_id
hits.t
hits.a
hits.pos.x
hits.pos.y
hits.pos.z
hits.dir.x
hits.dir.y
hits.dir.z
hits.pure_t
hits.pure_a
hits.type
hits.origin
hits.pattern_flags
Tracks keys are:
trks.fUniqueID
trks.fBits
trks.id
trks.pos.x
trks.pos.y
trks.pos.z
trks.dir.x
trks.dir.y
trks.dir.z
trks.t
trks.E
trks.len
trks.lik
trks.type
trks.rec_type
trks.rec_stages
trks.status
trks.mother_id
trks.fitinf
trks.hit_ids
trks.error_matrix
trks.comment
Mc hits keys are:
mc_hits.id
mc_hits.dom_id
mc_hits.channel_id
mc_hits.tdc
mc_hits.tot
mc_hits.trig
mc_hits.pmt_id
mc_hits.t
mc_hits.a
mc_hits.pos.x
mc_hits.pos.y
mc_hits.pos.z
mc_hits.dir.x
mc_hits.dir.y
mc_hits.dir.z
mc_hits.pure_t
mc_hits.pure_a
mc_hits.type
mc_hits.origin
mc_hits.pattern_flags
Mc tracks keys are:
mc_trks.fUniqueID
mc_trks.fBits
mc_trks.id
mc_trks.pos.x
mc_trks.pos.y
mc_trks.pos.z
mc_trks.dir.x
mc_trks.dir.y
mc_trks.dir.z
mc_trks.t
mc_trks.E
mc_trks.len
mc_trks.lik
mc_trks.type
mc_trks.rec_type
mc_trks.rec_stages
mc_trks.status
mc_trks.mother_id
mc_trks.fitinf
mc_trks.hit_ids
mc_trks.error_matrix
mc_trks.comment
%% Cell type:markdown id: tags:
# read events data
%% Cell type:code id: tags:
``` python
r.events
```
%% Output
<OfflineEvents: 10 parsed events>
%% Cell type:markdown id: tags:
number of events:
%% Cell type:code id: tags:
``` python
len(r.events)
```
%% Output
10
%% Cell type:code id: tags:
``` python
r.events.id
```
%% Output
<ChunkedArray [1 2 3 ... 8 9 10] at 0x7fa25a110690>
<ChunkedArray [1 2 3 ... 8 9 10] at 0x7fb5da350b50>
%% Cell type:code id: tags:
``` python
r.events.det_id
```
%% Output
<ChunkedArray [44 44 44 ... 44 44 44] at 0x7fa25a110e90>
<ChunkedArray [44 44 44 ... 44 44 44] at 0x7fb5da3506d0>
%% Cell type:code id: tags:
``` python
r.events.frame_index
```
%% Output
<ChunkedArray [182 183 202 ... 185 185 204] at 0x7fa25a1109d0>
<ChunkedArray [182 183 202 ... 185 185 204] at 0x7fb5da350950>
%% Cell type:code id: tags:
``` python
r.events.hits
```
%% Output
<ChunkedArray [176 125 318 ... 84 255 105] at 0x7fa25a165ed0>
<ChunkedArray [176 125 318 ... 84 255 105] at 0x7fb5da350350>
%% Cell type:markdown id: tags:
lazyarrays can be used with any Numpy universal function. For example:
%% Cell type:code id: tags:
``` python
import numpy as np
np.log(r.events.hits)
```
%% Output
<ChunkedArray [5.170483995038151 4.8283137373023015 5.762051382780177 ... 4.430816798843313 5.541263545158426 4.653960350157523] at 0x7fa25b0a5c50>
<ChunkedArray [5.170483995038151 4.8283137373023015 5.762051382780177 ... 4.430816798843313 5.541263545158426 4.653960350157523] at 0x7fb60fcdd2d0>
%% Cell type:markdown id: tags:
let's look at event 0:
%% Cell type:code id: tags:
``` python
r.events[0]
```
%% Output
offline event:
id : 1
det_id : 44
mc_id : 0
run_id : 5971
mc_run_id : 0
frame_index : 182
trigger_mask : 22
trigger_counter : 0
overlays : 60
hits : 176
trks : 56
w : []
w2list : []
w3list : []
mc_t : 0.0
mc_hits : 0
mc_trks : 0
comment : b''
index : 0
flags : 0
t_fSec : 1567036818
t_fNanoSec : 200000000
%% Cell type:code id: tags:
``` python
r.events[0].overlays
```
%% Output
60
%% Cell type:code id: tags:
``` python
r.events[0].hits
```
%% Output
176
%% Cell type:markdown id: tags:
# read hits data:
%% Cell type:code id: tags:
``` python
r.hits.dom_id
```
%% Output
<ChunkedArray [[806451572 806451572 806451572 ... 809544061 809544061 809544061] [806451572 806451572 806451572 ... 809524432 809526097 809544061] [806451572 806451572 806451572 ... 809544061 809544061 809544061] ... [806451572 806455814 806465101 ... 809526097 809544058 809544061] [806455814 806455814 806455814 ... 809544061 809544061 809544061] [806455814 806455814 806455814 ... 809544058 809544058 809544061]] at 0x7fa25a165250>
<ChunkedArray [[806451572 806451572 806451572 ... 809544061 809544061 809544061] [806451572 806451572 806451572 ... 809524432 809526097 809544061] [806451572 806451572 806451572 ... 809544061 809544061 809544061] ... [806451572 806455814 806465101 ... 809526097 809544058 809544061] [806455814 806455814 806455814 ... 809544061 809544061 809544061] [806455814 806455814 806455814 ... 809544058 809544058 809544061]] at 0x7fb5da350fd0>
%% Cell type:code id: tags:
``` python
r.hits.tot
```
%% Output
<ChunkedArray [[24 30 22 ... 38 26 23] [29 26 22 ... 26 28 24] [27 19 13 ... 27 24 16] ... [22 22 9 ... 27 32 27] [30 32 17 ... 30 24 29] [27 41 36 ... 29 24 28]] at 0x7fa25a1dcf10>
<ChunkedArray [[24 30 22 ... 38 26 23] [29 26 22 ... 26 28 24] [27 19 13 ... 27 24 16] ... [22 22 9 ... 27 32 27] [30 32 17 ... 30 24 29] [27 41 36 ... 29 24 28]] at 0x7fb5da3a3310>
%% Cell type:code id: tags:
``` python
r[0].hits
```
%% Output
<OfflineHits: 176 parsed elements>
%% Cell type:code id: tags:
``` python
r[0].hits.dom_id
```
%% Output
array([806451572, 806451572, 806451572, 806451572, 806455814, 806455814,
806455814, 806483369, 806483369, 806483369, 806483369, 806483369,
806483369, 806483369, 806483369, 806483369, 806483369, 806487219,
806487226, 806487231, 806487231, 808432835, 808435278, 808435278,
808435278, 808435278, 808435278, 808447180, 808447180, 808447180,
808447180, 808447180, 808447180, 808447180, 808447180, 808447186,
808451904, 808451904, 808472265, 808472265, 808472265, 808472265,
808472265, 808472265, 808472265, 808472265, 808488895, 808488990,
808488990, 808488990, 808488990, 808488990, 808489014, 808489014,
808489117, 808489117, 808489117, 808489117, 808493910, 808946818,
808949744, 808951460, 808951460, 808951460, 808951460, 808951460,
808956908, 808956908, 808959411, 808959411, 808959411, 808961448,
808961448, 808961504, 808961504, 808961655, 808961655, 808961655,
808964815, 808964815, 808964852, 808964908, 808969857, 808969857,
808969857, 808969857, 808969857, 808972593, 808972698, 808972698,
808972698, 808974758, 808974758, 808974758, 808974758, 808974758,
808974758, 808974758, 808974758, 808974758, 808974758, 808974758,
808974773, 808974773, 808974773, 808974773, 808974773, 808974972,
808974972, 808976377, 808976377, 808976377, 808979567, 808979567,
808979567, 808979721, 808979721, 808979721, 808979721, 808979721,
808979721, 808979721, 808979729, 808979729, 808979729, 808981510,
808981510, 808981510, 808981510, 808981672, 808981672, 808981672,
808981672, 808981672, 808981672, 808981672, 808981672, 808981672,
808981672, 808981672, 808981672, 808981672, 808981672, 808981672,
808981672, 808981672, 808981812, 808981812, 808981812, 808981864,
808981864, 808982005, 808982005, 808982005, 808982018, 808982018,
808982018, 808982041, 808982041, 808982077, 808982077, 808982547,
808982547, 808982547, 808997793, 809006037, 809524432, 809526097,
809526097, 809544061, 809544061, 809544061, 809544061, 809544061,
809544061, 809544061], dtype=int32)
%% Cell type:code id: tags:
``` python
r[0].hits[0]
```
%% Output
offline hit:
id : 0
dom_id : 806451572
channel_id : 8
tdc : 0
tot : 24
trig : 1
pmt_id : 0
t : 70104010.0
a : 0.0
pos_x : 0.0
pos_y : 0.0
pos_z : 0.0
dir_x : 0.0
dir_y : 0.0
dir_z : 0.0
pure_t : 0.0
pure_a : 0.0
type : 0
origin : 0
pattern_flags : 0
%% Cell type:code id: tags:
``` python
r[0].hits[0].dom_id
```
%% Output
806451572
%% Cell type:markdown id: tags:
# read tracks data:
%% Cell type:code id: tags:
``` python
r.tracks
```
%% Output
<OfflineTracks: 10 parsed elements>
%% Cell type:code id: tags:
``` python
r.tracks.lik
```
%% Output
<ChunkedArray [[294.6407542676734 294.6407542676734 294.6407542676734 ... 67.81221253265059 67.7756405143316 67.77250505700384] [96.75133289411137 96.75133289411137 96.75133289411137 ... 39.21916536442286 39.184645826013806 38.870325146341884] [560.2775306614813 560.2775306614813 560.2775306614813 ... 118.88577278801066 118.72271313687405 117.80785995187605] ... [71.03251451148226 71.03251451148226 71.03251451148226 ... 16.714140573909347 16.444395245214945 16.34639241716669] [326.440133294878 326.440133294878 326.440133294878 ... 87.79818671079849 87.75488082571873 87.74839444768625] [159.77779654216795 159.77779654216795 159.77779654216795 ... 33.8669134999348 33.821631538334984 33.77240735670646]] at 0x7fa25a0c26d0>
<ChunkedArray [[294.6407542676734 294.6407542676734 294.6407542676734 ... 67.81221253265059 67.7756405143316 67.77250505700384] [96.75133289411137 96.75133289411137 96.75133289411137 ... 39.21916536442286 39.184645826013806 38.870325146341884] [560.2775306614813 560.2775306614813 560.2775306614813 ... 118.88577278801066 118.72271313687405 117.80785995187605] ... [71.03251451148226 71.03251451148226 71.03251451148226 ... 16.714140573909347 16.444395245214945 16.34639241716669] [326.440133294878 326.440133294878 326.440133294878 ... 87.79818671079849 87.75488082571873 87.74839444768625] [159.77779654216795 159.77779654216795 159.77779654216795 ... 33.8669134999348 33.821631538334984 33.77240735670646]] at 0x7fb5da302b50>
%% Cell type:code id: tags:
``` python
r[0].tracks
```
%% Output
<OfflineTracks: 56 parsed elements>
%% Cell type:code id: tags:
``` python
r[0].tracks.lik
```
%% Output
array([294.64075427, 294.64075427, 294.64075427, 291.64653113,
291.27392663, 290.69031512, 289.19290546, 289.08449217,
289.03373947, 288.19030836, 282.92343367, 282.71527118,
282.10762402, 280.20553861, 275.93183966, 273.01809111,
257.46433694, 220.94357656, 194.99426403, 190.47809685,
79.95235686, 78.94389763, 78.90791169, 77.96122466,
77.9579604 , 76.90769883, 75.97546175, 74.91530508,
74.9059469 , 72.94007716, 72.90467038, 72.8629316 ,
72.81280833, 72.80229533, 72.78899435, 71.82404165,
71.80085542, 71.71028058, 70.91130096, 70.89150223,
70.85845637, 70.79081796, 70.76929743, 69.80667603,
69.64058976, 68.93085058, 68.84304037, 68.83154232,
68.79944298, 68.79019375, 68.78581291, 68.72340328,
67.86628937, 67.81221253, 67.77564051, 67.77250506])
%% Cell type:code id: tags:
``` python
r[0].tracks[0]
```
%% Output
offline track:
fUniqueID : 0
fBits : 33554432
id : 1
pos_x : 445.835395997812
pos_y : 615.1089636184813
pos_z : 125.1448339836911
dir_x : 0.0368711082700674
dir_y : -0.48653048395923415
dir_z : -0.872885221293917
t : 70311446.46401498
E : 99.10458562488608
len : 0.0
lik : 294.6407542676734
type : 0
rec_type : 4000
rec_stages : [1, 3, 5, 4]
status : 0
mother_id : -1
hit_ids : []
error_matrix : []
comment : 0
JGANDALF_BETA0_RAD : 0.004957442219414389
JGANDALF_BETA1_RAD : 0.003417848024252858
JGANDALF_CHI2 : -294.6407542676734
JGANDALF_NUMBER_OF_HITS : 142.0
JENERGY_ENERGY : 99.10458562488608
JENERGY_CHI2 : 1.7976931348623157e+308
JGANDALF_LAMBDA : 4.2409761837248484e-12
JGANDALF_NUMBER_OF_ITERATIONS : 10.0
JSTART_NPE_MIP : 24.88469697331908
JSTART_NPE_MIP_TOTAL : 55.88169412579765
JSTART_LENGTH_METRES : 98.89582506402911
JVETO_NPE : 0.0
JVETO_NUMBER_OF_HITS : 0.0
JENERGY_MUON_RANGE_METRES : 344.9767431592819
JENERGY_NOISE_LIKELIHOOD : -333.87773581129136
JENERGY_NDF : 1471.0
JENERGY_NUMBER_OF_HITS : 101.0
%% Cell type:code id: tags:
``` python
r[0].tracks[0].lik
```
%% Output
294.6407542676734
%% Cell type:code id: tags:
``` python
r.tracks.reco.dtype.names
```
%% Output
('JGANDALF_BETA0_RAD',
'JGANDALF_BETA1_RAD',
'JGANDALF_CHI2',
'JGANDALF_NUMBER_OF_HITS',
'JENERGY_ENERGY',
'JENERGY_CHI2',
'JGANDALF_LAMBDA',
'JGANDALF_NUMBER_OF_ITERATIONS',
'JSTART_NPE_MIP',
'JSTART_NPE_MIP_TOTAL',
'JSTART_LENGTH_METRES',
'JVETO_NPE',
'JVETO_NUMBER_OF_HITS',
'JENERGY_MUON_RANGE_METRES',
'JENERGY_NOISE_LIKELIHOOD',
'JENERGY_NDF',
'JENERGY_NUMBER_OF_HITS')
%% Cell type:code id: tags:
``` python
r.tracks.reco["JENERGY_ENERGY"]
```
%% Output
array([99.10458562, 99.10458562, 99.10458562, 37.85515249, 99.10458562,
7.16916787, 99.10458562, 99.10458562, 49.13672986, 20.35137468])
%% Cell type:markdown id: tags:
# read mc hits:
%% Cell type:code id: tags:
``` python
r.mc_hits
```
%% Output
<OfflineHits: 10 parsed elements>
%% Cell type:markdown id: tags:
# read mc tracks:
%% Cell type:code id: tags:
``` python
r.mc_tracks.
r.mc_tracks
```
%% Output
<OfflineTracks: 10 parsed elements>
%% Cell type:code id: tags:
``` python
```