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rename package tinymfv -> moralmaps (repo -> moral-maps)

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Import name tinymfv -> moralmaps, pip name tiny-mfv -> moral-maps, GitHub
URLs wassname/tinymfv -> wassname/moral-maps. HuggingFace dataset id
wassname/tiny-mfv left as-is (separate namespace, published data artifact).
Historical docs/spec/* and RESEARCH_JOURNAL keep their dated paths.

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
This commit is contained in:
wassname
2026-07-09 10:41:49 +08:00
co-authored by Claudypoo
parent ca76c0e05e
commit 469788c418
60 changed files with 111 additions and 111 deletions
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scripts/plot_steer_showcase.py
+7 -7
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@@ -1,4 +1,4 @@
"""Showcase tinymfv's plotting on a real steering run.
"""Showcase moralmaps's plotting on a real steering run.
Consumes a steering-lite `run_allinstr_showcase.py` output dir (one calibrated
activation-steering vector administered across every instrument over a signed
@@ -13,7 +13,7 @@ probabilities cannot share a raw axis with 1-5 survey scores. It still goes
through the same plot_ipsative_pca / plot_range functions.
cs are SIGNED multipliers of the calibrated coefficient C (0 = base). The public
README plots show the coherent path: c=0 plus each +/-c row whose tinymfv answer mass
README plots show the coherent path: c=0 plus each +/-c row whose moralmaps answer mass
stays above the requested fraction of base. Incoherent rows are dropped.
uv run python scripts/plot_steer_showcase.py \
@@ -35,9 +35,9 @@ matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import tinymfv as T
from tinymfv import get_instrument
from tinymfv.zones import zones_for
import moralmaps as T
from moralmaps import get_instrument
from moralmaps.zones import zones_for
# 16pf turned off: even at 6 macro zones its ipsative map is an unreadable pile-up (that instrument
# doesn't separate cultures; Brazil/Ecuador stretch Latin America across the whole plot). -- Claude
@@ -49,7 +49,7 @@ def _frac(x, scale_max: int) -> np.ndarray:
def read_human_csv(path: str) -> dict[tuple[str, str], float]:
"""{(country, foundation): mean} from a tinymfv human_<instrument>.csv."""
"""{(country, foundation): mean} from a moralmaps human_<instrument>.csv."""
out: dict[tuple[str, str], float] = {}
with open(path, newline="") as fh:
for r in csv.DictReader(fh):
@@ -212,7 +212,7 @@ def plot_ordinal(run_dir: Path, out: Path, name: str, vec_label: str, C: float,
# Alternative NAMED-AXIS value map (interpretable poles, no compass/minimap): project the
# societies + the AI base/steered points onto the instrument's two named value axes, and draw the
# steer as a CONNECTED base->+c/-c path (same visual language as the ipsative map's trajectory).
from tinymfv.value_axes import VALUE_AXES, value_coords, axis_score
from moralmaps.value_axes import VALUE_AXES, value_coords, axis_score
if name in VALUE_AXES:
Pval, poles = value_coords(Mfrac, dims, name)
(_, _, xa), (_, _, ya) = VALUE_AXES[name]