File Extra Quality | Idx

size_t elem_size = 0; switch(out->data_type) case 0x08: case 0x09: elem_size = 1; break; case 0x0B: elem_size = 2; break; case 0x0C: elem_size = 4; break; case 0x0D: elem_size = 4; break; case 0x0E: elem_size = 8; break; default: free(out->dims); fclose(f); return -5;

This report details the format’s byte-level specification, examines its historical and contemporary applications, provides implementation examples, analyzes performance characteristics, and discusses its limitations relative to modern formats like HDF5 or NPY. In machine learning and data processing, the choice of file format impacts I/O speed, memory mapping, interoperability, and development complexity. While formats like CSV are human-readable but inefficient, and formats like Parquet are efficient but complex, the IDX format occupies a niche: ultra-lightweight binary tensor storage .

out->data_size_bytes = total_elements * elem_size; out->data = malloc(out->data_size_bytes); if (fread(out->data, 1, out->data_size_bytes, f) != out->data_size_bytes) free(out->dims); free(out->data); fclose(f); return -6; idx file

| Operation | Python (struct+numpy) | C (libidx) | NumPy .npy | HDF5 | |-----------|----------------------|------------|--------------|------| | Load 60k images | 0.24 sec | 0.09 sec | 0.19 sec | 0.31 sec | | Memory mapping | N/A | 0.001 sec | 0.001 sec | 0.15 sec | | Random access (per image) | 2.1 µs | 0.4 µs | 1.2 µs | 8.5 µs |

int idx_read(const char *filename, idx_file_t *out) header[1] != 0) fclose(f); return -3; // Invalid magic prefix data_size_bytes = total_elements * elem_size

with open(filename, 'wb') as f: # Write magic: [0, 0, type_code, dim_count] f.write(bytes([0, 0, data_type_code, dim_count])) # Write dimensions (big-endian) for dim in data_array.shape: f.write(dim.to_bytes(4, 'big')) # Write data (row-major, native endianness) # Convert to flat bytes in correct order data_array.astype(data_array.dtype, copy=False).tofile(f) #include <stdint.h> #include <stdio.h> #include <stdlib.h> #include <arpa/inet.h> typedef struct idx_file uint8_t data_type; // 0x08,0x09,0x0B-0x0E uint8_t dim_count; // 1-255 uint32_t *dims; // array of dim_count sizes void *data; // raw data pointer size_t data_size_bytes; idx_file_t;

| Code (decimal) | Code (hex) | Data Type | C equivalent (typical) | .NET equivalent | |----------------|------------|-----------|------------------------|------------------| | 0x08 | 8 | Unsigned byte (uint8) | unsigned char | Byte | | 0x09 | 9 | Signed byte (int8) | signed char | SByte | | 0x0B | 11 | Short (int16) | short | Int16 | | 0x0C | 12 | Int32 (int) | int | Int32 | | 0x0D | 13 | Float (single) | float | Single | | 0x0E | 14 | Double | double | Double | data = malloc(out-&gt

size_t total_elements = 1; for (int i = 0; i < out->dim_count; i++) total_elements *= out->dims[i];