feat: IMAP mail sync with thread-to-contact matching (PRD §6.1)
Real IMAP connection via imapflow library: - Connects to IMAP server (IMAPFlow, TLS on port 993) - Fetches recent messages (configurable limit, default 20) - Extracts: from, fromEmail, subject, date, snippet (200 chars) - Thread-to-contact matching (PRD §6.1): 1. Match sender email against persons table 2. If no person match, extract domain and match against company.website 3. Returns matchedCompany + matchedPerson for each email - Audit-logged (action: crm.mailsync:imap) - Zod validated (host, port, user, password, folder, limit) - 502 on IMAP connection failure with detail - 400 on validation failure Tested: invalid creds → 502 'IMAP connection failed', missing host → 400
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# Figure Contract
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Core conclusion:
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Figure archetype:
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Target output:
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Final size:
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Panel map:
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- a:
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- b:
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- c:
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Evidence hierarchy:
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- hero evidence:
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- validation evidence:
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- controls / robustness:
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Statistics needed:
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Source data needed:
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Reviewer risk:
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# Figure Examples
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Reference matplotlib / seaborn scripts producing publication-grade figures
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for AI4S research papers. Reproduce with:
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```bash
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pip install matplotlib seaborn
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cd <where-you-want-the-pdf>
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python make_fig_02_horizon_sweep.py
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python make_fig_03_heatmap.py
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python make_fig_04_ablation.py
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```
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These are illustrative templates — copy and adapt for your data. They were
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extracted from a successful enrichment run of the `paper-writer` skill on
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the topic *Transformer-based time-series forecasting* (May 2026); the data
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embedded inline are simulated and meant only to illustrate the formatting.
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Start by filling `FIGURE_CONTRACT_TEMPLATE.md` for the figure you are about to make.
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Then reuse `style_kit.py` so exports, palette, panel labels, and simulated
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watermarks stay consistent across the experiment package.
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## Style summary
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- Shared `style_kit.py` with editable SVG text and PDF font embedding
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- Explicit color palette (no default cycle)
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- Removed top/right spines
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- `axes.grid` on at low alpha
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- Figure sizes targeted at column-width (3.4-5.0 inches wide)
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- "simulated" watermark in italic gray for runs from the simulator path
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- Save PDF + SVG + TIFF together when the environment allows it
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See the `paper-writer` skill's `references/02-figures-publication-grade.md`
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for the full taste guide.
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"""Generate fig_02_horizon_sweep.pdf — MSE vs forecast horizon (publication style)."""
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import os
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import matplotlib.pyplot as plt
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import numpy as np
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from style_kit import (
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DEFAULT_COLORS,
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add_panel_label,
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add_simulated_watermark,
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apply_publication_style,
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save_publication_bundle,
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)
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apply_publication_style()
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MARKERS = ["o", "s", "^", "D"]
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horizons = np.array([96, 192, 336, 720])
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methods = {
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"DLinear": np.array([0.345, 0.380, 0.420, 0.498]),
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"PatchTST": np.array([0.330, 0.358, 0.395, 0.469]),
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"iTransformer": np.array([0.328, 0.354, 0.392, 0.466]),
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"Ours": np.array([0.319, 0.346, 0.385, 0.460]),
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}
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fig, ax = plt.subplots(figsize=(5.0, 3.2))
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for (name, vals), color, marker in zip(methods.items(), DEFAULT_COLORS, MARKERS):
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ax.plot(horizons, vals, marker=marker, color=color, label=name)
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ax.set_xlabel(r"Forecast horizon $H$")
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ax.set_ylabel("MSE on ETTm1 (lower is better)")
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ax.set_xscale("log", base=2)
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ax.set_xticks(horizons)
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ax.set_xticklabels([str(h) for h in horizons])
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ax.legend(frameon=False, loc="upper left")
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add_panel_label(ax, "(a)")
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add_simulated_watermark(ax)
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plt.tight_layout(pad=0.4)
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out = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fig_02_horizon_sweep")
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save_publication_bundle(fig, out)
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plt.close(fig)
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print(f"Wrote {out}.pdf/.svg/.tiff")
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"""Generate fig_03_method_x_dataset_heatmap.pdf — MSE heatmap across methods × datasets."""
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import os
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import matplotlib.pyplot as plt
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import seaborn as sns
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import numpy as np
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from style_kit import add_panel_label, add_simulated_watermark, apply_publication_style, save_publication_bundle
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apply_publication_style()
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datasets = ["ETTh1", "ETTh2", "ETTm1", "ETTm2", "ECL", "Traffic", "Weather"]
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methods = ["DLinear", "Informer", "Autoformer", "FEDformer",
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"PatchTST", "iTrans.", "TimeMixer", "Ours"]
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mse = np.array([
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[0.394, 0.495, 0.439, 0.411, 0.371, 0.364, 0.358, 0.355],
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[0.310, 0.452, 0.388, 0.358, 0.301, 0.294, 0.290, 0.287],
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[0.382, 0.512, 0.421, 0.401, 0.366, 0.359, 0.357, 0.354],
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[0.279, 0.401, 0.336, 0.318, 0.262, 0.258, 0.254, 0.252],
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[0.166, 0.219, 0.187, 0.179, 0.158, 0.151, 0.150, 0.149],
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[0.434, 0.608, 0.545, 0.508, 0.412, 0.406, 0.405, 0.402],
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[0.241, 0.318, 0.281, 0.265, 0.227, 0.224, 0.223, 0.220],
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])
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fig, ax = plt.subplots(figsize=(6.4, 3.4))
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sns.heatmap(
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mse, annot=True, fmt=".3f",
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xticklabels=methods, yticklabels=datasets,
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cmap="RdYlGn_r",
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cbar_kws={"label": "MSE", "shrink": 0.7, "pad": 0.02},
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annot_kws={"size": 7.5},
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linewidths=0.4, linecolor="white",
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ax=ax,
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)
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ax.set_xticklabels(ax.get_xticklabels(), rotation=30, ha="right")
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ax.set_yticklabels(ax.get_yticklabels(), rotation=0)
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add_panel_label(ax, "(b)")
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add_simulated_watermark(ax, y=-0.16)
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plt.tight_layout(pad=0.4)
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out = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fig_03_method_x_dataset_heatmap")
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save_publication_bundle(fig, out)
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plt.close(fig)
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print(f"Wrote {out}.pdf/.svg/.tiff")
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"""Generate fig_04_ablation_panels.pdf — 2x2 ablation panel figure."""
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import os
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import matplotlib.pyplot as plt
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import numpy as np
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from style_kit import PALETTE, add_simulated_watermark, apply_publication_style, save_publication_bundle
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apply_publication_style()
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PRIMARY = PALETTE["blue_main"]
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ABLATION = PALETTE["red_strong"]
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DATASETS = ["ETTm1", "Electricity", "Traffic", "Weather"]
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horizons = np.array([96, 192, 336, 720])
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full = {
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"ETTm1": np.array([0.319, 0.346, 0.385, 0.460]),
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"Electricity": np.array([0.131, 0.142, 0.149, 0.171]),
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"Traffic": np.array([0.352, 0.378, 0.402, 0.451]),
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"Weather": np.array([0.179, 0.198, 0.220, 0.272]),
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}
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no_patch = {
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"ETTm1": np.array([0.354, 0.382, 0.422, 0.499]),
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"Electricity": np.array([0.143, 0.155, 0.164, 0.186]),
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"Traffic": np.array([0.378, 0.408, 0.434, 0.486]),
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"Weather": np.array([0.198, 0.221, 0.247, 0.301]),
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}
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fig, axes = plt.subplots(2, 2, figsize=(6.6, 4.4), sharex=True)
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for ax, name in zip(axes.flat, DATASETS):
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ax.plot(horizons, full[name], marker="o", color=PRIMARY, label="Full")
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ax.plot(horizons, no_patch[name], marker="s", linestyle="--",
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color=ABLATION, label=r"$-$ patching")
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ax.set_title(name)
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ax.set_xscale("log", base=2)
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ax.set_xticks(horizons)
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ax.set_xticklabels([str(h) for h in horizons])
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ax.grid(True, alpha=0.25, linewidth=0.4)
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ax.spines["top"].set_visible(False)
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ax.spines["right"].set_visible(False)
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for ax in axes[:, 0]:
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ax.set_ylabel("MSE")
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for ax in axes[-1, :]:
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ax.set_xlabel(r"Horizon $H$")
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handles, labels = axes[0, 0].get_legend_handles_labels()
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fig.legend(handles, labels, loc="upper center", bbox_to_anchor=(0.5, 1.02),
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ncol=2, frameon=False)
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for ax, label in zip(axes.flat, "abcd"):
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ax.text(-0.15, 1.05, f"({label})", transform=ax.transAxes,
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fontweight="bold", fontsize=10)
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add_simulated_watermark(fig.axes[-1], y=-0.22)
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plt.tight_layout(rect=(0.0, 0.01, 1.0, 0.95))
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out = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fig_04_ablation_panels")
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save_publication_bundle(fig, out)
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plt.close(fig)
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print(f"Wrote {out}.pdf/.svg/.tiff")
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# Dependencies for the publication-figure example scripts.
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# Install: pip install -r requirements.txt
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matplotlib>=3.7
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numpy>=1.24
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seaborn>=0.13
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"""Shared publication-style helpers for experiment-suite figures."""
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from __future__ import annotations
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from pathlib import Path
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import matplotlib.pyplot as plt
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PALETTE = {
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"blue_main": "#0F4D92",
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"blue_secondary": "#3775BA",
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"green_1": "#DDF3DE",
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"green_2": "#AADCA9",
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"green_3": "#8BCF8B",
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"red_1": "#F6CFCB",
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"red_2": "#E9A6A1",
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"red_strong": "#B64342",
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"neutral_light": "#CFCECE",
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"neutral_mid": "#767676",
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"neutral_dark": "#4D4D4D",
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"neutral_black": "#272727",
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"teal": "#42949E",
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"violet": "#9A4D8E",
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}
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DEFAULT_COLORS = [
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PALETTE["blue_main"],
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PALETTE["green_3"],
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PALETTE["red_strong"],
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PALETTE["teal"],
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PALETTE["violet"],
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PALETTE["neutral_mid"],
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]
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PALETTE_NMI_PASTEL = [
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"#484878",
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"#7884B4",
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"#B4C0E4",
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"#E4E4F0",
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"#E4CCD8",
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"#F0C0CC",
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]
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def apply_publication_style(font_size: int = 9, axes_linewidth: float = 0.6) -> None:
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"""Apply a shared journal-style matplotlib configuration."""
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plt.rcParams.update({
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"font.family": "sans-serif",
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"font.sans-serif": ["Arial", "DejaVu Sans", "Liberation Sans"],
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"font.size": font_size,
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"axes.labelsize": font_size,
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"axes.titlesize": font_size + 1,
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"xtick.labelsize": max(font_size - 1, 6),
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"ytick.labelsize": max(font_size - 1, 6),
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"legend.fontsize": max(font_size - 1, 6),
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"axes.spines.right": False,
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"axes.spines.top": False,
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"axes.linewidth": axes_linewidth,
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"axes.grid": True,
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"grid.alpha": 0.25,
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"grid.linewidth": 0.4,
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"lines.linewidth": 1.4,
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"lines.markersize": 4.5,
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"savefig.dpi": 300,
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"savefig.bbox": "tight",
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"svg.fonttype": "none",
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"pdf.fonttype": 42,
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"ps.fonttype": 42,
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})
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def add_panel_label(ax, label: str, x: float = -0.12, y: float = 1.03) -> None:
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ax.text(
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x, y, label,
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transform=ax.transAxes,
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fontsize=10,
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fontweight="bold",
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ha="left",
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va="bottom",
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)
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def add_simulated_watermark(ax, x: float = 0.99, y: float = 0.02) -> None:
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ax.text(
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x, y, "simulated",
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transform=ax.transAxes,
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ha="right",
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va="bottom",
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fontsize=7,
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color="gray",
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alpha=0.7,
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style="italic",
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)
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def save_publication_bundle(fig, out_base: str, dpi: int = 600) -> None:
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"""Save PDF/SVG/TIFF together when possible."""
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out_path = Path(out_base)
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fig.savefig(out_path.with_suffix(".pdf"))
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fig.savefig(out_path.with_suffix(".svg"))
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fig.savefig(out_path.with_suffix(".tiff"), dpi=dpi)
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