File size: 5,594 Bytes
2955ecc | 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 | #!/usr/bin/env python3
"""Figure 4: coarse provider-account calculations relative to the threshold."""
from __future__ import annotations
import json
import matplotlib.pyplot as plt
from matplotlib.ticker import FixedLocator, FuncFormatter
from style import (
BLUE,
FULL_WIDTH_IN,
INK,
LIGHT_GREY,
MID_GREY,
WHITE,
HERE,
assert_text_floor,
remove_spines,
save_figure,
)
SPEC = HERE / "specs" / "provider_operations_coarse.json"
OUTPUT = HERE / "fig_provider_operations.pdf"
FIGURE_TEXT_PT = 8.5
TOP_LEVEL_ALLOW_LIST = {
"schema_version",
"artifact_id",
"status",
"source_window",
"policy_threshold_operations",
"operation_convention",
"rate_registry",
"disclosure_approval",
"descriptive_operation_calculations",
"privacy",
}
EXPECTED_IDS = [
"minute_observed_per_sku",
"independent_sku_peaks_per_sku",
"independent_sku_peaks_uniform",
]
def load_coarse_artifact() -> tuple[list[dict], float]:
data = json.loads(SPEC.read_text(encoding="utf-8"))
extra = set(data) - TOP_LEVEL_ALLOW_LIST
missing = TOP_LEVEL_ALLOW_LIST - set(data)
if extra or missing:
raise ValueError(f"coarse provider schema mismatch; extra={extra}, missing={missing}")
if data["schema_version"] != "1":
raise ValueError("unsupported coarse provider schema")
if data["status"] not in {"provisional", "manifest_bound_final"}:
raise ValueError("provider artifact must declare provisional or final status")
if data["status"] == "manifest_bound_final":
for key in ("operation_convention", "rate_registry", "disclosure_approval"):
if not data[key].get("identifier") and not data[key].get("reference"):
raise ValueError(f"final provider artifact lacks required {key} binding")
if data["source_window"]["inclusive_minute_bin_duration_seconds"] != 4_074_120:
raise ValueError("provider duration changed; review manuscript and plot")
privacy = data["privacy"]
if privacy != {
"coarse_allow_list_enforced": True,
"contains_row_level_records": False,
"contains_provider_or_account_identifiers": False,
}:
raise ValueError("provider coarse-artifact privacy declaration changed")
calculations = data["descriptive_operation_calculations"]
if [item["id"] for item in calculations] != EXPECTED_IDS:
raise ValueError("provider calculation bases or ordering changed")
threshold = float(data["policy_threshold_operations"])
if threshold != 1e25:
raise ValueError("unexpected policy threshold")
for item in calculations:
if set(item) != {"id", "short_label", "operations", "marker"}:
raise ValueError(f"{item['id']} contains a field outside the coarse allow-list")
item["ratio"] = float(item["operations"]) / threshold
if item["operations"] <= 0:
raise ValueError("log-scale operation values must be positive")
return calculations, threshold
def tick_formatter(value, _position):
labels = {0.5: "0.5", 1.0: "1", 2.0: "2", 5.0: "5"}
return labels.get(round(float(value), 8), "")
def main() -> None:
calculations, _threshold = load_coarse_artifact()
y_values = [2, 1, 0]
fig, ax = plt.subplots(figsize=(FULL_WIDTH_IN, 1.72))
fig.subplots_adjust(left=0.245, right=0.985, bottom=0.30, top=0.90)
for y in y_values:
ax.axhline(y, color=LIGHT_GREY, lw=0.5, zorder=0)
ax.axvline(1, color=INK, lw=0.8, ls=(0, (3, 2)), zorder=1)
for item, y in zip(calculations, y_values):
ratio = item["ratio"]
face = BLUE if item["id"] == "minute_observed_per_sku" else WHITE
ax.scatter(
[ratio],
[y],
s=34,
marker=item["marker"],
facecolor=face,
edgecolor=BLUE,
linewidth=1.0,
zorder=3,
)
if ratio > 4:
ax.annotate(
f"{ratio:.3f}",
(ratio, y),
xytext=(-6, 0),
textcoords="offset points",
ha="right",
va="center",
color=BLUE,
fontsize=FIGURE_TEXT_PT,
)
else:
ax.annotate(
f"{ratio:.3f}",
(ratio, y),
xytext=(6, 0),
textcoords="offset points",
ha="left",
va="center",
color=BLUE,
fontsize=FIGURE_TEXT_PT,
)
ax.text(
1.0,
2.27,
r"threshold $T$",
ha="center",
va="bottom",
fontsize=FIGURE_TEXT_PT,
bbox={"facecolor": WHITE, "edgecolor": "none", "pad": 0.8},
zorder=5,
)
ax.set_xscale("log")
ax.set_xlim(0.40, 7.0)
ax.set_ylim(-0.55, 2.48)
ax.xaxis.set_major_locator(FixedLocator([0.5, 1.0, 2.0, 5.0]))
ax.xaxis.set_major_formatter(FuncFormatter(tick_formatter))
ax.minorticks_off()
ax.set_yticks(y_values)
ax.set_yticklabels([item["short_label"] for item in calculations])
ax.tick_params(axis="both", labelsize=FIGURE_TEXT_PT)
ax.tick_params(axis="y", length=0, pad=7)
ax.set_xlabel(r"calculated operations / threshold $T$", fontsize=FIGURE_TEXT_PT)
remove_spines(ax, ("top", "right", "left"))
assert_text_floor(fig, FIGURE_TEXT_PT)
save_figure(
fig,
OUTPUT,
subject="Provisional coarse provider-account operation calculations relative to T",
)
if __name__ == "__main__":
main()
|