Add TsFile (converted from algoplexity/computational-phase-transitions-data)

.gitattributes

@@ -58,3 +58,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+computational_phase_transitions_data_test.tsfile filter=lfs diff=lfs merge=lfs -text
+computational_phase_transitions_data_train.tsfile filter=lfs diff=lfs merge=lfs -text
+computational_phase_transitions_data_train_1.tsfile filter=lfs diff=lfs merge=lfs -text
+computational_phase_transitions_data_train_2.tsfile filter=lfs diff=lfs merge=lfs -text
+computational_phase_transitions_data_train_3.tsfile filter=lfs diff=lfs merge=lfs -text
+computational_phase_transitions_data_train_4.tsfile filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,79 @@
+---
+license: mit
+task_categories:
+- time-series-forecasting
+- tabular-classification
+tags:
+- tsfile
+- timeseries
+- time-series
+- finance
+- econophysics
+- algorithmic-information-theory
+- structural-breaks
+- anomaly-detection
+- format:tsfile
+pretty_name: Computational Phase Transitions (TsFile)
+size_categories:
+- 10M<n<100M
+---
+
+# Financial Structural Breaks & Regime Detection Benchmark (TsFile)
+
+Apache TsFile version of [`algoplexity/computational-phase-transitions-data`](https://huggingface.co/datasets/algoplexity/computational-phase-transitions-data).
+
+## Overview
+
+Large-scale collection of non-stationary, continuous financial time series as an
+immutable data artifact for the Algoplexity research program into Algorithmic
+Information Dynamics (AID) in financial markets. Each `id` is a trajectory — an
+ordered sequence of `(time, value)` pairs under a time-varying control parameter
+`period` — with a per-trajectory boolean label `structural_breakpoint` (whether
+the trajectory exhibits a structural/phase break). The source is split into
+`train` and a reduced `test` set; that split is preserved. Because the train
+split is very large (23.7M rows), it is stored as six sharded files
+(`*_train.tsfile`, `*_train_1.tsfile`, …, `*_train_5.tsfile`) that together form
+one logical table.
+
+## Schema (TsFile structure)
+
+- **Time** (INT64, milliseconds) — the step index within each trajectory (not
+  wall-clock time).
+- **id** (TAG) — the trajectory identifier.
+- **structural_breakpoint** (TAG) — the per-trajectory label (True/False).
+- **period** (FIELD, INT64) — the time-varying control parameter.
+- **value** (FIELD, FLOAT) — the trajectory value.
+
+## Usage
+
+Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file:
+
+```python
+from pathlib import Path
+from tsfile import TsFileReader
+
+path = Path("computational_phase_transitions_data_test.tsfile")
+with TsFileReader(str(path)) as reader:
+    schemas = reader.get_all_table_schemas()
+    print("tables:", list(schemas))
+    table_name = next(iter(schemas))
+    table = schemas[table_name]
+    columns = [column.get_column_name() for column in table.get_columns()]
+    print("columns:", columns)
+    field_names = [
+        column.get_column_name()
+        for column in table.get_columns()
+        if column.get_column_name() not in {"Time", "time"}
+    ]
+    if field_names:
+        with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
+            batch = result.read_arrow_batch()
+            if batch is not None:
+                print(batch.to_pandas().head())
+```
+
+## Source & license
+
+- Original dataset: https://huggingface.co/datasets/algoplexity/computational-phase-transitions-data
+- Author / publisher: algoplexity
+- License: MIT

computational_phase_transitions_data_test.tsfile

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:daf381e1d253c506be9a60355d68bbebc786a7f56e4c53b3661b1696ec78aa00
+size 1111953

computational_phase_transitions_data_train.tsfile

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f28d49ad899fcb1271a1299bc592e88379152025996bc831246a797f81e4c880
+size 21293224

computational_phase_transitions_data_train_1.tsfile

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:32e54273b10d00d5a4258b2f8797c30815a596b07ca6c4fce60b27f7788778c0
+size 21167958

computational_phase_transitions_data_train_2.tsfile

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ca07c7b1ebca44507f8c4c3a890c98f2f6edcb398252719f1262959901b74cb
+size 21404669

computational_phase_transitions_data_train_3.tsfile

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07843bf4588f636c7ee653b7037a2fc310bb35b06e3836cfcfea41ef7b9358f6
+size 21327520

computational_phase_transitions_data_train_4.tsfile

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bc4925bee01f3fab6a83bb19dd1d6625022d53b3cbebdb13399f9ea07d1b4446
+size 21353874