File size: 7,564 Bytes
055f287 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 | #!/usr/bin/env bash
# Re-create the SPE-1 Arrow dataset from scratch via CRCNS download.
#
# Usage (from the dataset root, e.g. systems/datasets/spe1/):
# CRCNS_USERNAME=your_user CRCNS_PASSWORD=your_pass \
# bash scripts/prepare.sh
#
# If CRCNS_PASSWORD is unset you will be prompted interactively.
#
# Environment overrides:
# CRCNS_USERNAME CRCNS account username (REQUIRED)
# CRCNS_PASSWORD CRCNS account password (prompted if unset)
# SPE1_RAW_DIR Where to store the downloaded raw data (default: ./.raw)
# SPE1_OUT_DIR Where to write Arrow datasets (default: .)
# SPE1_CELLS Space-separated cell IDs (default: all 12)
# SPE1_DURATION Recording seconds per cell (default: 300)
# PYTHON Python interpreter to use (default: python3)
#
# Required Python packages:
# pip install requests scipy pandas openpyxl spikeinterface datasets numpy
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
DATASET_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)"
PYTHON="${PYTHON:-python3}"
SPE1_OUT_DIR="${SPE1_OUT_DIR:-${DATASET_ROOT}}"
SPE1_RAW_DIR="${SPE1_RAW_DIR:-${SPE1_OUT_DIR}/.raw}"
SPE1_DURATION="${SPE1_DURATION:-300}"
# Default: 11 Zhao et al. 2026 cells + c5 (longest WC-IC, used for V(t) plots).
DEFAULT_CELLS="c5 c14 c15 c16 c19 c24 c26 c28 c29 c37 c45 c46"
SPE1_CELLS="${SPE1_CELLS:-${DEFAULT_CELLS}}"
CONVERTER="${SCRIPT_DIR}/convert_to_arrow.py"
LOG_DIR="${SPE1_OUT_DIR}/.logs"
DATA_DIR="${SPE1_RAW_DIR}/Recordings"
CHAN_MAP="${SPE1_RAW_DIR}/chanMap.mat"
SUMMARY_XLS="${SPE1_RAW_DIR}/Data Summary.xlsx"
# CRCNS dataset paths.
CRCNS_DATA_PREFIX="spe-1/data"
CRCNS_ANCILLARY=(
"spe-1/chanMap.mat"
"spe-1/Data Summary.xlsx"
)
mkdir -p "${SPE1_OUT_DIR}" "${LOG_DIR}" "${SPE1_RAW_DIR}" "${DATA_DIR}"
log() { echo "[$(date '+%H:%M:%S')] $*"; }
die() { echo "ERROR: $*" >&2; exit 1; }
if [[ -z "${CRCNS_USERNAME:-}" ]]; then
die "CRCNS_USERNAME is required. Register a free account at
https://crcns.org/register
and re-run with:
CRCNS_USERNAME=<user> CRCNS_PASSWORD=<pass> bash $0"
fi
if [[ -z "${CRCNS_PASSWORD:-}" ]]; then
read -r -s -p "CRCNS password for ${CRCNS_USERNAME}: " CRCNS_PASSWORD
echo
export CRCNS_PASSWORD
fi
log "SPE-1 prepare pipeline (CRCNS)"
log " Output: ${SPE1_OUT_DIR}"
log " Raw data: ${SPE1_RAW_DIR}"
log " Cells: ${SPE1_CELLS}"
log " Duration: ${SPE1_DURATION}s per cell"
# ---------------------------------------------------------------------------
# Validate Python environment
# ---------------------------------------------------------------------------
"${PYTHON}" - <<'PYCHECK'
import sys
missing = []
for pkg in ["requests", "scipy", "spikeinterface", "datasets", "numpy", "pandas"]:
try:
__import__(pkg)
except ImportError:
missing.append(pkg)
if missing:
sys.exit("Missing packages: " + ", ".join(missing) +
"\nInstall with: pip install " + " ".join(missing))
print(" All required packages present.")
PYCHECK
crcns_download() {
# crcns_download <relative_path_on_portal> <local_output_path>
local fn="$1"
local out="$2"
if [[ -s "${out}" ]]; then
return 0
fi
mkdir -p "$(dirname "${out}")"
CRCNS_FN="${fn}" CRCNS_OUT="${out}" \
"${PYTHON}" - <<'PYDL'
import os, sys, requests
URL = "https://portal.nersc.gov/project/crcns/download/index.php"
fn = os.environ["CRCNS_FN"]
out = os.environ["CRCNS_OUT"]
data = dict(username=os.environ["CRCNS_USERNAME"],
password=os.environ["CRCNS_PASSWORD"],
fn=fn, submit="Login")
tmp = out + ".part"
total = 0
with requests.Session() as s, requests.post(
URL, data=data, stream=True, timeout=60
) as r:
r.raise_for_status()
if r.headers.get("Content-Type", "").startswith("text/html"):
sys.exit("CRCNS returned HTML (likely auth failure): "
+ r.text[:300].replace("\n", " "))
with open(tmp, "wb") as f:
for chunk in r.iter_content(chunk_size=1 << 20):
if chunk:
f.write(chunk)
total += len(chunk)
if total % (256 << 20) < (1 << 20):
print(f" ... {total / (1<<20):.0f} MiB", flush=True)
os.replace(tmp, out)
print(f" Done: {total / (1<<20):.1f} MiB -> {out}")
PYDL
}
# ---------------------------------------------------------------------------
# Step 1 - download ancillary files (chanMap + Data Summary)
# ---------------------------------------------------------------------------
for src in "${CRCNS_ANCILLARY[@]}"; do
fname="$(basename "${src}")"
target="${SPE1_RAW_DIR}/${fname}"
if [[ ! -s "${target}" ]]; then
log "Downloading ${fname} from CRCNS …"
crcns_download "${src}" "${target}"
fi
done
# Mirror the small ancillary files at the dataset root so consumers don't
# need .raw/ to load probe geometry or ground-truth electrode assignments.
cp -u "${CHAN_MAP}" "${SPE1_OUT_DIR}/chanMap.mat"
cp -u "${SUMMARY_XLS}" "${SPE1_OUT_DIR}/Data Summary.xlsx"
# ---------------------------------------------------------------------------
# Step 2 - download + extract per-cell tar.gz archives
# ---------------------------------------------------------------------------
for cell in ${SPE1_CELLS}; do
if [[ -n "$(find "${DATA_DIR}/${cell}" -maxdepth 1 -name '*npx_raw.bin' 2>/dev/null | head -1)" ]]; then
log " ${cell}: already extracted — skipping"
continue
fi
archive="${SPE1_RAW_DIR}/${cell}.tar.gz"
if [[ ! -s "${archive}" ]]; then
log "Downloading ${cell}.tar.gz from CRCNS …"
crcns_download "${CRCNS_DATA_PREFIX}/${cell}.tar.gz" "${archive}" \
2>&1 | tee "${LOG_DIR}/download_${cell}.log"
if [[ ! -s "${archive}" ]]; then
log " ERROR: download failed for ${cell}.tar.gz"
rm -f "${archive}" "${archive}.part"
continue
fi
fi
log "Extracting ${cell}.tar.gz into ${DATA_DIR}/ …"
tar -xzf "${archive}" -C "${DATA_DIR}" \
|| { log " ERROR: extraction failed for ${cell}.tar.gz"; continue; }
done
# ---------------------------------------------------------------------------
# Step 3 - convert each cell to Arrow
# ---------------------------------------------------------------------------
log "Converting cells to Arrow (one cell per subprocess to bound memory) …"
CONVERT_ERRORS=0
SKIPPED_CELLS=""
for cell in ${SPE1_CELLS}; do
npx_bin=$(find "${DATA_DIR}/${cell}" -maxdepth 1 -name "*npx_raw.bin" 2>/dev/null | head -1)
if [[ -z "${npx_bin}" ]]; then
log " Skipping ${cell}: npx_raw.bin not present"
SKIPPED_CELLS="${SKIPPED_CELLS} ${cell}"
continue
fi
log " Converting ${cell} …"
"${PYTHON}" "${CONVERTER}" \
--data-dir "${DATA_DIR}" \
--chan-map "${CHAN_MAP}" \
--summary "${SUMMARY_XLS}" \
--output "${SPE1_OUT_DIR}" \
--cells "${cell}" \
--duration "${SPE1_DURATION}" \
2>&1 | tee "${LOG_DIR}/convert_${cell}.log"
if [[ ${PIPESTATUS[0]} -ne 0 ]]; then
log " ERROR: conversion failed for ${cell}"
CONVERT_ERRORS=$((CONVERT_ERRORS + 1))
fi
done
if [[ -n "${SKIPPED_CELLS}" ]]; then
log "Skipped (npx_raw.bin missing):${SKIPPED_CELLS}"
fi
if [[ ${CONVERT_ERRORS} -gt 0 ]]; then
die "${CONVERT_ERRORS} cell(s) failed to convert. Check ${LOG_DIR}/"
fi
log "Pipeline complete. Datasets at: ${SPE1_OUT_DIR}"
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