float64 2-D Grid — Exact-Repr CSV Twin (.csv)
Every element of the float64 .npy array written as its shortest round-tripping decimal representation, one row per element in C order. Parsing this text back to float64 reproduces the binary array bit for bit, so it is a usable oracle rather than a lossy printout.
row,col,value_exact_repr
0,0,0.0
0,1,0.183673469388
0,2,0.734693877551
0,3,1.65306122449
0,4,2.938775510204
0,5,4.591836734694
0,6,6.612244897959
0,7,9.0
1,0,0.0
1,1,0.122954967111
1,2,0.491819868443
1,3,1.106594703997
1,4,1.967279473773
1,5,3.07387417777
1,6,4.426378815989
1,7,6.02479338843
2,0,0.0
2,1,0.074380165289
2,2,0.297520661157
2,3,0.669421487603
2,4,1.190082644628
2,5,1.859504132231
2,6,2.677685950413
2,7,3.644628099174
3,0,0.0
3,1,0.037949063923
3,2,0.151796255692
3,3,0.341541575308
3,4,0.607185022769
3,5,0.948726598077
3,6,1.366166301231
3,7,1.859504132231
4,0,0.0
4,1,0.013661663012
4,2,0.054646652049
4,3,0.122954967111
4,4,0.218586608197
4,5,0.341541575308
4,6,0.491819868443
4,7,0.669421487603
5,0,0.0
5,1,0.001517962557
5,2,0.006071850228
5,3,0.013661663012
5,4,0.024287400911
5,5,0.037949063923
5,6,0.054646652049
5,7,0.074380165289
6,0,0.0Specifications
- Rows
- 96
- Columns
- 3
- Notation
- Python shortest round-trip repr
- Round Trip Exact
- true
- Order
- C (row-major)
Testing contract
Reference control- Scenario
- Parse every value_exact_repr with a standard float parser and compare the result bit-for-bit against the paired .npy array.
- Expected result
- All 96 values compare equal under an exact bit comparison, not merely within a tolerance, because the decimal strings are shortest round-trip representations.
What is a .csv file?
CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.
How to use this file
Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.
How to use this file for testing
“float64 2-D Grid — Exact-Repr CSV Twin (.csv)” is a deterministic Novus Examples fixture for Scientific data, Conversion testing, Editor testing. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.
Documented properties for this file: 96 rows · 3 columns. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.
Code examples
import pandas as pd
df = pd.read_csv("float64-grid-2d.csv")
print(df.head())
print(df.dtypes)Related files
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