LunarTrace scientific manual#
LUNAR RESEARCH · METHODS · SOFTWARE
From a lunar place and time
to an observation study you can trace.
LunarTrace connects orbital observation discovery, before-and-after comparison, source evidence, and reproducible scientific records. Use the Lab to formulate a question; use the Python library to make its method explicit.
Choose your route#
Use the Lab
Choose a location and reference time. Retrieve actual observations, link their spatial and temporal context, inspect evidence, and explore comparisons.
Understand the science
Read the temporal predicates, objective definitions, retrieval limits, and evidence boundaries. Know what a result can—and cannot—establish.
Work programmatically
Audit an exported investigation, acquire a fresh point-based snapshot, compile with Python, and inspect the resulting artifacts.
Two kinds of research object#
An exploratory investigation is editable. Its reference point and time are supplied by the user. A bounded archive query returns a newly captured population; filters and method choices help investigate it. The Lab does not automatically admit that work as scientific fact.
A retained Study is a stable scientific record. The Chang’e 6 exemplar preserves the historical aggregate and its exact source identities. Its missing original observation and pair rows are not reconstructed to make the interface richer.
Objects are explored. Studies make scientific arguments.
Note
This manual describes the Lab R2 implementation and Python package 0.1.0. Implementation, local qualification, public deployment, and scientific admission are separate. Check the deployed revision before assuming that every source feature is present in a particular preview. The source repository remains private; the Python package is available at https://pypi.org/project/lunartrace/0.1.0/; no hosted Python execution service is claimed.
What you can carry away#
An exported Lab investigation can include the query definition, actual metadata-response bytes and hashes, normalized exploratory observations, the deliberately included analysis population, and the exploratory comparison result. A shared URL carries intent only, not a reproducible archive snapshot.
The Python continuation makes acquisition an explicit operation. A fresh query is new evidence, not a promise to recover the same changing archive population. See From exploration to reproducible computation.