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Improve code examples in "Save jobs" (#1231)
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The "Save jobs" notebooks made a couple of assumptions that are not
always true:

1. It assumed the most recent job submitted has completed.
2. It assumed the most recent job submitted was a sampler job.

This PR changes the code examples to handle both these cases
(75c09f1), and re-runs the notebook
(e6ff1cb).

Fixes #1227.
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@frankharkins
frankharkins authored Apr 24, 2024
1 parent 7a49dba commit bb37207
Showing 1 changed file with 106 additions and 19 deletions.
125 changes: 106 additions & 19 deletions docs/run/save-jobs.ipynb
View file
Original file line number Diff line number Diff line change
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{
"data": {
"text/plain": [
"[<RuntimeJob('cogiau7imm49f6et38a0', 'sampler')>,\n",
" <RuntimeJob('crgja91qzd5000886v60', 'sampler')>,\n",
" <RuntimeJob('cogi9gftcirtooeunfe0', 'sampler')>]"
"[<RuntimeJob('crmfqhetdjr0008dzb7g', 'estimator')>,\n",
" <RuntimeJob('crmfq4m14ys00088aqk0', 'estimator')>,\n",
" <RuntimeJob('crm3r8stdjr0008dyqp0', 'qasm3-runner')>]"
]
},
"execution_count": 1,
Expand Down Expand Up @@ -72,14 +72,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"cogiau7imm49f6et38a0\n"
"crmfqhetdjr0008dzb7g\n"
]
}
],
"source": [
"# Get ID of most recent job for demonstration.\n",
"# This will not work if you've never submitted a job.\n",
"job_id = service.jobs()[0].job_id()\n",
"# Get ID of most recent successful job for demonstration.\n",
"# This will not work if you've never successfully run a job.\n",
"job_id = service.jobs(pending=False)[0].job_id()\n",
"print(job_id)"
]
},
Expand All @@ -92,7 +92,55 @@
{
"data": {
"text/plain": [
"PrimitiveResult([PubResult(data=DataBin(meas=BitArray(<shape=(), num_shots=10, num_bits=2>)), metadata={'circuit_metadata': {}})], metadata={'version': 2})"
"PrimitiveResult([PubResult(data=DataBin<99>(evs=[ 0.64570064 0.31953125 0.15481172 0.15026362 0.1015873 0.06350626\n",
" 0.02247191 0.03113208 0.02272727 -0.01854839 0.02457757 -0.02230769\n",
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" 0.00245098 0.05736434 -0.00078616 -0.01820941 0.02724359 0.03257576\n",
" -0.0229709 0.01394052 0.03928571 0.02599388 -0.0015625 0.02323718\n",
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" 0.00152905 -0.02941176 -0.03215926 0.01529791 0.01905488 0.01687117\n",
" -0.00152905 0.03466872 0.00381098 -0.02531646 0.04984424 0.03257576\n",
" 0.00716561 0.0375 0.01192369], stds=[0.0301912 0.02439315 0.03771335 0.02273161 0.02739113 0.0295477\n",
" 0.03288008 0.02413365 0.03831347 0.02884026 0.02536583 0.02681657\n",
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" 0.02246694 0.0222245 0.02612686 0.0202093 0.020652 0.02290411\n",
" 0.02298056 0.02069357 0.02485448 0.02475432 0.0265815 0.02261385\n",
" 0.02070769 0.023968 0.0236309 0.01825162 0.02616927 0.0259223\n",
" 0.02572882 0.02750496 0.0233063 0.02454793 0.02621478 0.03324334\n",
" 0.02369112 0.02301501 0.02882225 0.03405876 0.0237285 0.07714824\n",
" 0.05473595 0.03195926 0.03185138 0.02856942 0.02328771 0.0266565\n",
" 0.01628194 0.02089134 0.02544533 0.02144492 0.02448796 0.02196046\n",
" 0.02090776 0.02034051 0.02206126 0.02163483 0.02571104 0.03089664\n",
" 0.02135038 0.02577374 0.02551062 0.02294048 0.02026551 0.0219107\n",
" 0.02212938 0.02250427 0.0280836 ], ensemble_standard_error=[0.02974919 0.02603545 0.03400854 0.02845832 0.02550986 0.0286863\n",
" 0.03596807 0.03020618 0.04042023 0.02581045 0.02458342 0.02462023\n",
" 0.02446983 0.02496223 0.02473559 0.0251978 0.05486275 0.02568755\n",
" 0.0261032 0.02511901 0.02442856 0.02564456 0.02689571 0.02589194\n",
" 0.02473166 0.04384101 0.02552859 0.03361648 0.10620428 0.02488889\n",
" 0.02614386 0.02483923 0.02515724 0.02428226 0.0513148 0.02425212\n",
" 0.02450734 0.02974316 0.02859573 0.02447125 0.02500003 0.02564716\n",
" 0.02431748 0.02503918 0.02488358 0.02425124 0.02484741 0.02705609\n",
" 0.02453988 0.02427923 0.02458539 0.0246942 0.02543922 0.02716611\n",
" 0.0244275 0.02488375 0.02427955 0.02428533 0.02461928 0.02450356\n",
" 0.02508538 0.02439038 0.02461746 0.02479152 0.02457758 0.02782663\n",
" 0.02893417 0.02488336 0.02717746 0.03413174 0.03125538 0.07381268\n",
" 0.04280605 0.02439182 0.03252825 0.0278795 0.02473417 0.02649038\n",
" 0.0241487 0.02606121 0.02636131 0.0247299 0.02432424 0.02454024\n",
" 0.02446485 0.02690224 0.02451218 0.0257676 0.02439365 0.02454261\n",
" 0.02446485 0.02466509 0.02439038 0.02532341 0.02494752 0.02425212\n",
" 0.02547828 0.02501455 0.02543877]), metadata={'shots': 4096, 'target_precision': 0.015625, 'circuit_metadata': {}, 'resilience': {}, 'num_randomizations': 32})], metadata={'dynamical_decoupling': {'enable': True, 'sequence_type': 'XY4', 'extra_slack_distribution': 'middle', 'scheduling_method': 'alap'}, 'twirling': {'enable_gates': False, 'enable_measure': True, 'num_randomizations': 'auto', 'shots_per_randomization': 'auto', 'interleave_randomizations': True, 'strategy': 'active-accum'}, 'resilience': {'measure_mitigation': True, 'zne_mitigation': False, 'pec_mitigation': False}, 'version': 2})"
]
},
"execution_count": 3,
Expand Down Expand Up @@ -145,16 +193,55 @@
{
"data": {
"text/plain": [
"array([[1],\n",
" [3],\n",
" [3],\n",
" [2],\n",
" [2],\n",
" [1],\n",
" [2],\n",
" [3],\n",
" [0],\n",
" [3]], dtype=uint8)"
"PrimitiveResult([PubResult(data=DataBin<99>(evs=[ 0.64570064 0.31953125 0.15481172 0.15026362 0.1015873 0.06350626\n",
" 0.02247191 0.03113208 0.02272727 -0.01854839 0.02457757 -0.02230769\n",
" 0.02293578 -0.01092044 -0.02472952 -0.00944882 0.03767123 0.02166934\n",
" 0.01305057 -0.01098901 0.01068702 0.01762821 0.01932773 0.01294498\n",
" -0.01468315 -0.01232877 -0.03030303 0.01155462 0.12745098 -0.02332815\n",
" 0.00245098 0.05736434 -0.00078616 -0.01820941 0.02724359 0.03257576\n",
" -0.0229709 0.01394052 0.03928571 0.02599388 -0.0015625 0.02323718\n",
" -0.01215805 -0.00234742 0.00466563 0.03106061 0.01630435 0.0464527\n",
" 0. -0.00151745 0.02841782 0.01697531 0.01351351 -0.01018676\n",
" 0.00152672 0.00622084 0.0060698 0.02579666 0.02 0.01148545\n",
" 0.02586207 0.00381098 -0.01461538 0.04876161 0.00076805 -0.00608696\n",
" -0.00813743 0. -0.03056027 -0.02665245 0.01660156 -0.16216216\n",
" -0.064 -0.01295732 -0.01930894 -0.01829268 0.02163833 0.00496689\n",
" 0.04223228 -0.01465798 -0.01317957 -0.00618238 -0.02963526 -0.00613497\n",
" 0.00152905 -0.02941176 -0.03215926 0.01529791 0.01905488 0.01687117\n",
" -0.00152905 0.03466872 0.00381098 -0.02531646 0.04984424 0.03257576\n",
" 0.00716561 0.0375 0.01192369], stds=[0.0301912 0.02439315 0.03771335 0.02273161 0.02739113 0.0295477\n",
" 0.03288008 0.02413365 0.03831347 0.02884026 0.02536583 0.02681657\n",
" 0.0272724 0.02060853 0.02863267 0.02421324 0.07009148 0.02684497\n",
" 0.02538034 0.02612797 0.02454662 0.0203859 0.02793376 0.02416668\n",
" 0.02155515 0.03890846 0.02796816 0.03592119 0.13748787 0.02046372\n",
" 0.0226519 0.02212958 0.02610926 0.02304325 0.05380769 0.01890131\n",
" 0.02313008 0.0258601 0.02763123 0.03068307 0.02649207 0.02440182\n",
" 0.02246694 0.0222245 0.02612686 0.0202093 0.020652 0.02290411\n",
" 0.02298056 0.02069357 0.02485448 0.02475432 0.0265815 0.02261385\n",
" 0.02070769 0.023968 0.0236309 0.01825162 0.02616927 0.0259223\n",
" 0.02572882 0.02750496 0.0233063 0.02454793 0.02621478 0.03324334\n",
" 0.02369112 0.02301501 0.02882225 0.03405876 0.0237285 0.07714824\n",
" 0.05473595 0.03195926 0.03185138 0.02856942 0.02328771 0.0266565\n",
" 0.01628194 0.02089134 0.02544533 0.02144492 0.02448796 0.02196046\n",
" 0.02090776 0.02034051 0.02206126 0.02163483 0.02571104 0.03089664\n",
" 0.02135038 0.02577374 0.02551062 0.02294048 0.02026551 0.0219107\n",
" 0.02212938 0.02250427 0.0280836 ], ensemble_standard_error=[0.02974919 0.02603545 0.03400854 0.02845832 0.02550986 0.0286863\n",
" 0.03596807 0.03020618 0.04042023 0.02581045 0.02458342 0.02462023\n",
" 0.02446983 0.02496223 0.02473559 0.0251978 0.05486275 0.02568755\n",
" 0.0261032 0.02511901 0.02442856 0.02564456 0.02689571 0.02589194\n",
" 0.02473166 0.04384101 0.02552859 0.03361648 0.10620428 0.02488889\n",
" 0.02614386 0.02483923 0.02515724 0.02428226 0.0513148 0.02425212\n",
" 0.02450734 0.02974316 0.02859573 0.02447125 0.02500003 0.02564716\n",
" 0.02431748 0.02503918 0.02488358 0.02425124 0.02484741 0.02705609\n",
" 0.02453988 0.02427923 0.02458539 0.0246942 0.02543922 0.02716611\n",
" 0.0244275 0.02488375 0.02427955 0.02428533 0.02461928 0.02450356\n",
" 0.02508538 0.02439038 0.02461746 0.02479152 0.02457758 0.02782663\n",
" 0.02893417 0.02488336 0.02717746 0.03413174 0.03125538 0.07381268\n",
" 0.04280605 0.02439182 0.03252825 0.0278795 0.02473417 0.02649038\n",
" 0.0241487 0.02606121 0.02636131 0.0247299 0.02432424 0.02454024\n",
" 0.02446485 0.02690224 0.02451218 0.0257676 0.02439365 0.02454261\n",
" 0.02446485 0.02466509 0.02439038 0.02532341 0.02494752 0.02425212\n",
" 0.02547828 0.02501455 0.02543877]), metadata={'shots': 4096, 'target_precision': 0.015625, 'circuit_metadata': {}, 'resilience': {}, 'num_randomizations': 32})], metadata={'dynamical_decoupling': {'enable': True, 'sequence_type': 'XY4', 'extra_slack_distribution': 'middle', 'scheduling_method': 'alap'}, 'twirling': {'enable_gates': False, 'enable_measure': True, 'num_randomizations': 'auto', 'shots_per_randomization': 'auto', 'interleave_randomizations': True, 'strategy': 'active-accum'}, 'resilience': {'measure_mitigation': True, 'zne_mitigation': False, 'pec_mitigation': False}, 'version': 2})"
]
},
"execution_count": 5,
Expand All @@ -167,7 +254,7 @@
"with open(\"result.json\", \"r\") as file:\n",
" result = json.load(file, cls=RuntimeDecoder)\n",
"\n",
"result[0].data.meas.array # access measurement data"
"result"
]
},
{
Expand Down

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