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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'anonymous_contig_id,ground_truth_label'}) and 11 missing columns ({'sample_3.tsv', 'sample_2.tsv', 'contigname', 'sample_1.tsv', 'sample_5.tsv', 'sample_9.tsv', 'sample_7.tsv', 'sample_8.tsv', 'sample_4.tsv', 'sample_6.tsv', 'sample_0.tsv'}).
This happened while the csv dataset builder was generating data using
hf://datasets/rongye1/TaxDistill/marine_ground_truth_v226_lineage_strict.csv (at revision 18999022d8fa60fd90faa3a2a798e5d18be8d5c3), [/tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/abundances.tsv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/abundances.tsv), /tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/marine_ground_truth_v226_lineage_strict.csv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/marine_ground_truth_v226_lineage_strict.csv), /tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_marine_taxonomy.tsv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_marine_taxonomy.tsv), /tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_results_taxometer_fixed.tsv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_results_taxometer_fixed.tsv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
anonymous_contig_id,ground_truth_label: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 439
to
{'contigname': Value('string'), 'sample_0.tsv': Value('float64'), 'sample_1.tsv': Value('float64'), 'sample_2.tsv': Value('float64'), 'sample_3.tsv': Value('float64'), 'sample_4.tsv': Value('float64'), 'sample_5.tsv': Value('float64'), 'sample_6.tsv': Value('float64'), 'sample_7.tsv': Value('float64'), 'sample_8.tsv': Value('float64'), 'sample_9.tsv': Value('float64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'anonymous_contig_id,ground_truth_label'}) and 11 missing columns ({'sample_3.tsv', 'sample_2.tsv', 'contigname', 'sample_1.tsv', 'sample_5.tsv', 'sample_9.tsv', 'sample_7.tsv', 'sample_8.tsv', 'sample_4.tsv', 'sample_6.tsv', 'sample_0.tsv'}).
This happened while the csv dataset builder was generating data using
hf://datasets/rongye1/TaxDistill/marine_ground_truth_v226_lineage_strict.csv (at revision 18999022d8fa60fd90faa3a2a798e5d18be8d5c3), [/tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/abundances.tsv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/abundances.tsv), /tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/marine_ground_truth_v226_lineage_strict.csv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/marine_ground_truth_v226_lineage_strict.csv), /tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_marine_taxonomy.tsv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_marine_taxonomy.tsv), /tmp/hf-datasets-cache/medium/datasets/82758159665562-config-parquet-and-info-rongye1-TaxDistill-b8f9f11c/hub/datasets--rongye1--TaxDistill/snapshots/18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_results_taxometer_fixed.tsv (origin=hf://datasets/rongye1/TaxDistill@18999022d8fa60fd90faa3a2a798e5d18be8d5c3/mmseq2_results_taxometer_fixed.tsv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
contigname string | sample_0.tsv float64 | sample_1.tsv float64 | sample_2.tsv float64 | sample_3.tsv float64 | sample_4.tsv float64 | sample_5.tsv float64 | sample_6.tsv float64 | sample_7.tsv float64 | sample_8.tsv float64 | sample_9.tsv float64 |
|---|---|---|---|---|---|---|---|---|---|---|
S1CS0C21 | 2.580061 | 0.134144 | 2.193462 | 1.46643 | 0.906684 | 0.982545 | 0.682839 | 0.441054 | 1.889329 | 1.159334 |
S1CS0C46 | 3.978518 | 0.230162 | 0.920649 | 1.131083 | 1.446734 | 0.572117 | 1.808417 | 0.657606 | 0.822008 | 0.113254 |
S1CS0C128 | 2.904307 | 1.69522 | 1.434459 | 1.889293 | 0.786779 | 0.358713 | 1.568752 | 1.75365 | 1.735839 | 1.102515 |
S1CS0C163 | 3.224442 | 0.098788 | 2.409109 | 1.045531 | 1.15528 | 0.620496 | 0.277621 | 0.212699 | 0.281278 | 0.126848 |
S1CS0C209 | 3.295438 | 0.145157 | 0.344552 | 0.225685 | 0.909755 | 0.132454 | 0.109255 | 0.020407 | 0.427948 | 1.323551 |
S1CS0C216 | 0.752505 | 0.419812 | 0.381569 | 0.677342 | 0.927079 | 0.529637 | 0.355681 | 1.605017 | 0.709738 | 1.081603 |
S1CS0C221 | 1.897615 | 2.057491 | 1.16658 | 1.474205 | 1.766819 | 1.790889 | 2.108458 | 1.464285 | 1.033669 | 1.636279 |
S1CS0C307 | 0.589456 | 1.474271 | 1.456919 | 1.819552 | 2.79221 | 2.526868 | 3.160879 | 2.369629 | 1.89142 | 3.239103 |
S1CS0C400 | 0.548462 | 1.037085 | 0.530594 | 0.689585 | 3.7636 | 1.447412 | 2.201941 | 2.989902 | 1.392036 | 2.291876 |
S1CS0C453 | 3.981767 | 0.308201 | 1.221115 | 2.204336 | 2.21042 | 1.803311 | 1.1387 | 0.923562 | 0.468413 | 0.164152 |
S1CS0C482 | 0.704723 | 0.755462 | 0.782125 | 0.819782 | 1.138211 | 1.141768 | 1.027231 | 1.188982 | 1.119623 | 1.672713 |
S1CS0C540 | 0.499429 | 0.550914 | 0.653041 | 0.505478 | 0.932022 | 0.552563 | 0.605169 | 0.425386 | 0.475721 | 0.370635 |
S1CS0C612 | 1.748098 | 0.949081 | 2.179668 | 1.017451 | 0.460225 | 0.189142 | 0.557621 | 0.614164 | 1.197696 | 0.99531 |
S1CS0C617 | 1.107802 | 0.346539 | 1.025614 | 0.305461 | 0.135583 | 0.976795 | 1.348569 | 0.578603 | 0.320847 | 0.080981 |
S1CS0C628 | 1.124791 | 1.852969 | 1.11125 | 1.070776 | 0.753687 | 0.594147 | 0.573496 | 1.751247 | 0.532891 | 0.564056 |
S1CS0C710 | 1.386207 | 1.161582 | 0.583605 | 1.371838 | 1.276653 | 0.509935 | 0.565471 | 0.138887 | 0.489036 | 0.765419 |
S1CS0C774 | 0.646191 | 1.022416 | 0.618132 | 0.293521 | 0.155403 | 0.214537 | 0.534781 | 0.510069 | 1.466535 | 1.547022 |
S1CS0C781 | 1.96744 | 2.361038 | 0.828444 | 1.867583 | 0.964612 | 0.002306 | 0.438981 | 0.483861 | 1.130452 | 0 |
S1CS0C798 | 4.075396 | 1.763105 | 2.571858 | 1.760156 | 0.316466 | 0.809916 | 1.450928 | 1.366325 | 1.659477 | 1.067529 |
S1CS0C828 | 0.625622 | 0.711818 | 0.884461 | 0.865415 | 1.417834 | 1.038737 | 0.81289 | 1.594255 | 1.357109 | 1.578152 |
S1CS0C853 | 2.770516 | 0.520378 | 3.073361 | 0.926517 | 0.184389 | 0.245392 | 0.180116 | 0.317113 | 1.338141 | 0.15005 |
S1CS0C893 | 3.596446 | 1.663113 | 0.705759 | 1.272045 | 1.365103 | 1.05373 | 1.43401 | 1.350139 | 1.980527 | 2.01365 |
S1CS0C900 | 1.625944 | 1.646804 | 1.015722 | 1.813565 | 1.689326 | 1.532854 | 1.738303 | 1.829032 | 0.943673 | 1.784357 |
S1CS0C912 | 2.420538 | 2.273839 | 0.953545 | 1.430318 | 0.224939 | 0.293399 | 0.513447 | 0.146699 | 0.183374 | 0.110024 |
S1CS0C958 | 4.239749 | 2.369764 | 1.598245 | 1.080186 | 0.4356 | 0.681605 | 0.877468 | 0.720476 | 1.353416 | 0.830461 |
S1CS0C986 | 1.370072 | 0.887995 | 1.412145 | 0.760444 | 0.308489 | 0.577353 | 0.37725 | 0.320852 | 1.251094 | 0.916583 |
S1CS0C988 | 0.64546 | 0.738825 | 0.71086 | 0.690617 | 1.738341 | 1.008713 | 0.74843 | 1.47096 | 1.034933 | 1.215754 |
S1CS0C1012 | 1.406567 | 1.238773 | 1.176603 | 1.138429 | 0.879404 | 0.823562 | 1.517672 | 1.230664 | 1.534422 | 1.074994 |
S1CS0C1026 | 0.663333 | 0.682096 | 0.783721 | 0.843025 | 1.569868 | 0.902195 | 0.80691 | 1.201749 | 0.732217 | 1.185762 |
S1CS0C1034 | 4.711481 | 1.859677 | 1.991955 | 2.045545 | 0.466746 | 0.528204 | 1.151086 | 1.186964 | 0.758255 | 0.570787 |
S1CS0C1041 | 9.934928 | 3.684612 | 0.1419 | 0.121319 | 0.069699 | 0.112747 | 0.14014 | 0.028668 | 0.111204 | 0.052205 |
S1CS0C1287 | 0.735084 | 0.515702 | 0.755682 | 1.109103 | 0.351823 | 0.52173 | 0.498954 | 0.78237 | 0.757131 | 0.621453 |
S1CS0C1313 | 0.906859 | 0.712837 | 0.726316 | 1.634134 | 0.318981 | 0.61062 | 0.757102 | 0.942491 | 0.924398 | 1.279299 |
S1CS0C1343 | 1.812268 | 0.209108 | 1.045539 | 1.010688 | 1.324349 | 0.069703 | 0 | 1.951673 | 0.139405 | 0.27881 |
S1CS0C1388 | 0.821034 | 0.415567 | 1.020778 | 0.641866 | 1.038094 | 0.598615 | 0.098945 | 1.094987 | 0.826187 | 0.089669 |
S1CS0C1453 | 3.246956 | 1.28083 | 0.8419 | 1.97246 | 0.05515 | 0.378251 | 1.160019 | 0.153762 | 2.071773 | 0.772713 |
S1CS0C1459 | 1.222652 | 1.476899 | 0.812085 | 1.199 | 1.401099 | 0.782455 | 0.98985 | 0.96445 | 0.914247 | 0.684795 |
S1CS0C1524 | 4.809069 | 1.410166 | 2.597454 | 0.71599 | 1.491647 | 1.044153 | 0.603288 | 0.908247 | 0.477327 | 2.550716 |
S1CS0C1532 | 1.532176 | 0.058444 | 2.472209 | 0.862595 | 0.413386 | 0.500893 | 0.348624 | 0.315815 | 0.928804 | 1.183418 |
S1CS0C1534 | 1.703575 | 1.659933 | 0.94624 | 1.589686 | 1.729448 | 2.514689 | 1.728219 | 1.186798 | 0.920881 | 1.671001 |
S1CS0C1538 | 1.706447 | 0.754345 | 2.183442 | 0.916436 | 0.364316 | 0.088744 | 0.274404 | 0.602537 | 0.878678 | 1.034563 |
S1CS0C1559 | 1.529224 | 2.745705 | 1.715906 | 1.244107 | 0.790276 | 1.081203 | 1.238685 | 0.861295 | 1.037285 | 0.266082 |
S1CS0C1584 | 2.458797 | 1.467696 | 1.147568 | 1.406388 | 0.296455 | 0.33366 | 0.93627 | 0.658246 | 0.90805 | 0.612194 |
S1CS0C1619 | 0.495733 | 0.774626 | 0.117832 | 0.664463 | 2.399877 | 1.659415 | 1.571564 | 1.633618 | 1.943189 | 1.613398 |
S1CS0C1652 | 3.001193 | 3.492698 | 2.239743 | 2.746408 | 3.38522 | 1.635999 | 2.5722 | 2.233135 | 1.793815 | 1.373276 |
S1CS0C1737 | 3.371658 | 1.463649 | 2.27016 | 1.340019 | 0.470674 | 0.631105 | 1.257961 | 1.250792 | 1.751643 | 1.060376 |
S1CS0C1765 | 0.62341 | 0.703024 | 0.798884 | 0.488966 | 1.356102 | 1.111621 | 0.806524 | 1.552601 | 1.31571 | 1.351109 |
S1CS0C1832 | 1.341922 | 1.414649 | 1.138602 | 2.459296 | 1.003582 | 1.606501 | 1.324752 | 1.132915 | 0.641603 | 1.582098 |
S1CS0C1855 | 4.909347 | 2.670721 | 2.39469 | 1.831806 | 0.944803 | 0.627028 | 1.141268 | 2.151961 | 1.655366 | 1.734463 |
S1CS0C1885 | 1.403607 | 0.600225 | 1.315129 | 0.412411 | 0.120305 | 1.394322 | 1.78486 | 1.091655 | 0.384282 | 0.069055 |
S1CS0C1889 | 2.154236 | 0.214812 | 1.580401 | 1.816136 | 0 | 0.030687 | 0.061375 | 0.381268 | 0.775554 | 0.036267 |
S1CS0C1927 | 4.783096 | 2.428945 | 1.18362 | 2.120953 | 0.230616 | 0.13089 | 0.052356 | 1.402393 | 0.532909 | 0.897532 |
S1CS0C1937 | 0.604075 | 0.560353 | 0.624609 | 0.591525 | 0.962198 | 0.649375 | 0.531425 | 0.671941 | 0.559644 | 0.367222 |
S1CS0C1940 | 5.283865 | 0.475247 | 0.239826 | 0.276163 | 2.093023 | 0.174419 | 0.765504 | 0.087209 | 0.131254 | 0.140504 |
S1CS0C2012 | 5.89618 | 0.1108 | 0.172765 | 0.163995 | 1.415785 | 0.388923 | 0.445163 | 0.072423 | 0.064855 | 0.148545 |
S1CS0C2035 | 1.052647 | 0.970844 | 1.226719 | 2.002048 | 0.122103 | 0.101777 | 0.00066 | 0.789141 | 0.710012 | 1.204276 |
S1CS0C2043 | 2.439591 | 1.88197 | 0.627323 | 1.08039 | 0 | 0.284172 | 0.662175 | 0 | 1.951673 | 0.702388 |
S1CS0C2068 | 4.263467 | 0.182411 | 1.331636 | 1.809918 | 2.559423 | 2.035229 | 1.540747 | 0.46369 | 0.500849 | 0.080645 |
S1CS0C2092 | 2.938843 | 2.9324 | 0.073242 | 0.314276 | 0.292969 | 0.073242 | 0.219727 | 0.537807 | 0.23019 | 0.073242 |
S1CS0C2094 | 1.035324 | 0.660953 | 0.462261 | 1.114187 | 0.856004 | 0.527029 | 0.984707 | 0.667482 | 1.109772 | 0.430715 |
S1CS0C2113 | 1.390099 | 1.518812 | 0.360396 | 0.986139 | 0 | 0.148515 | 0.178218 | 0.920792 | 1.039604 | 0.564356 |
S1CS0C2273 | 1.228027 | 0.579093 | 0.85996 | 0.559164 | 1.729492 | 0.521941 | 0.412145 | 0.687336 | 0.372514 | 1.103428 |
S1CS0C2285 | 0.927434 | 0.869922 | 0.800583 | 0.568804 | 0.459562 | 0.428152 | 0.765212 | 0.47375 | 0.717103 | 0.496657 |
S1CS0C2342 | 1.073601 | 1.31237 | 0.958821 | 2.133236 | 0.766949 | 1.478281 | 1.216904 | 0.996033 | 0.439367 | 1.413757 |
S1CS0C2474 | 2.923117 | 0.353336 | 2.996709 | 0.741717 | 0.138849 | 0.126506 | 0.207078 | 0.388477 | 0.823969 | 0.084048 |
S1CS0C2480 | 3.276016 | 2.851641 | 2.076884 | 1.990702 | 1.236883 | 0.086558 | 0.795194 | 1.798953 | 1.413684 | 1.590801 |
S1CS0C2487 | 0.946112 | 0.296511 | 0.267803 | 0.404051 | 3.101051 | 1.192574 | 0.863688 | 0.973721 | 0.447142 | 1.476413 |
S1CS0C2498 | 0.647611 | 1.646349 | 1.279115 | 1.597725 | 2.535747 | 2.583596 | 3.349291 | 2.565681 | 2.365359 | 3.376189 |
S1CS0C2535 | 4.017382 | 1.998891 | 4.458701 | 3.837332 | 4.812059 | 1.98653 | 1.470883 | 3.040435 | 3.409394 | 2.883623 |
S1CS0C2548 | 1.093094 | 1.501034 | 1.048504 | 2.554244 | 1.112392 | 1.769791 | 1.467203 | 1.36528 | 0.538915 | 1.620072 |
S1CS0C2570 | 1.209752 | 1.365665 | 2.078871 | 2.036442 | 0.666654 | 1.472242 | 1.865975 | 1.394325 | 0.800741 | 0.55593 |
S1CS0C2599 | 3.834988 | 3.326321 | 1.57261 | 2.218161 | 0.312104 | 0.830865 | 0.614693 | 2.280519 | 1.339133 | 0.901773 |
S1CS0C2606 | 3.02267 | 0.062972 | 1.196474 | 0.346348 | 0.881612 | 0.629723 | 0.81864 | 0 | 0.125945 | 0.444742 |
S1CS0C2608 | 4.101865 | 0.024909 | 0.049817 | 0.163982 | 0.049817 | 0.051374 | 0.170375 | 0.050648 | 0.051063 | 0.049817 |
S1CS0C2621 | 3.999346 | 2.141805 | 0.476029 | 1.858608 | 0.190534 | 0.366291 | 0.40697 | 1.132964 | 0.486609 | 0.867798 |
S1CS0C2622 | 1.513443 | 0.596271 | 1.024501 | 1.103101 | 0.407632 | 0.211405 | 0.390286 | 1.26843 | 0.332236 | 0.462923 |
S1CS0C2630 | 5.412773 | 0.903462 | 1.299267 | 1.218572 | 0.747295 | 0.112496 | 0.12947 | 0.609994 | 0.226434 | 0.203025 |
S1CS0C2635 | 0.6928 | 0.942236 | 0.545479 | 0.742004 | 4.032339 | 1.528157 | 2.117425 | 2.981441 | 1.645111 | 2.387976 |
S1CS0C2650 | 1.793414 | 0.764284 | 1.638336 | 0.619151 | 0.169786 | 0.520513 | 0.171168 | 0.616264 | 1.191463 | 0.744196 |
S1CS0C2742 | 1.865775 | 2.017449 | 1.451142 | 1.689883 | 1.915689 | 2.631579 | 1.833461 | 1.248559 | 1.257995 | 1.89323 |
S1CS0C2791 | 0.90122 | 0.231051 | 0.329786 | 0.437639 | 3.122847 | 0.795098 | 0.600879 | 0.644047 | 0.337658 | 1.144574 |
S1CS0C2815 | 0.448682 | 0.642399 | 0.591131 | 0.396191 | 0.871841 | 0.923922 | 0.8097 | 1.111233 | 1.080215 | 1.353601 |
S1CS0C2834 | 4.485544 | 2.645165 | 0.467687 | 1.514668 | 0.076531 | 0.350765 | 0.092474 | 1.348397 | 0.467687 | 0.59949 |
S1CS0C2838 | 3.40399 | 1.733734 | 3.703242 | 1.503061 | 1.577873 | 0.810474 | 0.749263 | 0.448878 | 0.729426 | 0.249377 |
S1CS0C2878 | 1.319712 | 0.191224 | 1.87899 | 1.246906 | 0.062948 | 0.096457 | 0.101728 | 0.423266 | 0.616158 | 0.128025 |
S1CS0C2925 | 5.743212 | 0.351981 | 0.815904 | 0.523882 | 0.224812 | 0.342082 | 0.396235 | 0.235429 | 0.866774 | 0.411074 |
S1CS0C2966 | 2.462247 | 0.996205 | 0.411653 | 1.723044 | 0.98955 | 0.139119 | 0.403737 | 0.358877 | 1.393069 | 0.380707 |
S1CS0C2969 | 1.458958 | 1.910477 | 1.108786 | 1.301751 | 1.584388 | 0.91095 | 1.118391 | 1.139763 | 1.046769 | 0.887269 |
S1CS0C2984 | 0.837309 | 0.528915 | 0.63707 | 1.063179 | 1.09739 | 0.320911 | 0.513908 | 0.787679 | 1.351668 | 1.115676 |
S1CS0C3020 | 2.198823 | 3.386304 | 0.694875 | 0.518736 | 0 | 0.085166 | 0.077423 | 0.387117 | 0.437794 | 0.098715 |
S1CS0C3031 | 2.415804 | 0.231797 | 1.455851 | 0.300164 | 0.428949 | 0.298518 | 0.098988 | 0.263968 | 0.464127 | 0.032996 |
S1CS0C3070 | 1.656117 | 0.952103 | 2.399641 | 0.852365 | 0.44475 | 0.146094 | 0.492454 | 0.559644 | 1.240966 | 1.128563 |
S1CS0C3083 | 0.656921 | 1.798168 | 1.285275 | 1.813991 | 2.409272 | 2.881333 | 3.265329 | 2.524136 | 2.511379 | 3.38211 |
S1CS0C3101 | 1.998467 | 0.466491 | 1.297635 | 0.456636 | 0.125931 | 1.812308 | 1.932764 | 0.76106 | 0.737595 | 0.016426 |
S1CS0C3102 | 1.535297 | 0.98744 | 1.660892 | 0.940883 | 0.216273 | 0.538112 | 0.555435 | 0.336726 | 1.484409 | 0.835443 |
S1CS0C3107 | 1.068569 | 0.396418 | 1.058751 | 0.637894 | 0.079017 | 0.591498 | 0.690872 | 0.975885 | 0.761006 | 0.76872 |
S1CS0C3123 | 1.500734 | 0.779893 | 1.79487 | 0.852218 | 0.473708 | 0.04507 | 0.386435 | 0.425655 | 0.947889 | 0.784917 |
S1CS0C3129 | 0.405416 | 0.594537 | 0.92951 | 0.739224 | 2.471496 | 1.195014 | 1.113551 | 0.757864 | 0.271178 | 0.803235 |
S1CS0C3134 | 0.943435 | 0.738303 | 0.681247 | 0.991564 | 1.113439 | 0.956684 | 1.086241 | 0.900828 | 1.369686 | 1.038384 |
S1CS0C3161 | 2.028137 | 2.442727 | 1.378193 | 1.730207 | 1.971085 | 1.175207 | 1.658846 | 1.488447 | 1.480513 | 0.98167 |
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