"""
Generate the Lesson 4 EmotionMap Word fallback template.

The primary submission route is the single-page PDF the toy app
exports. This Word document is the paper fallback for students who
cannot run the app — six labelled slots in a 2x3 grid, a Format
checkbox, the privacy confirm, and a short reflection prompt.

Run with:
    uv run python scratch/build_emotionmap_template.py
"""

from __future__ import annotations

from pathlib import Path

from docx import Document
from docx.enum.table import WD_ALIGN_VERTICAL
from docx.shared import Cm, Pt, RGBColor


REPO_ROOT = Path(__file__).resolve().parent.parent
# The Word doc is a teaching-bundle artefact, not a Space asset.
# Default output is the lesson folder; override with $TOTES_TEMPLATE_OUT
# if running from a different machine.
DEFAULT_OUT = (
    Path.home() / "Code/teaching/online-teaching-for-bence"
    / "Lesson4-EmotionMap-template.docx"
)
OUT_PATH = Path(
    __import__("os").environ.get("TOTES_TEMPLATE_OUT", DEFAULT_OUT)
)

GREY = RGBColor(0x55, 0x55, 0x55)
EMOTIONS = ["Happy", "Sad", "Fear", "Disgust", "Anger", "Surprise"]


def add_heading(doc, text, level):
    return doc.add_heading(text, level=level)


def add_para(doc, text, italic=False, grey=False, bold=False, size=None):
    p = doc.add_paragraph()
    run = p.add_run(text)
    run.italic = italic
    run.bold = bold
    if grey:
        run.font.color.rgb = GREY
    if size is not None:
        run.font.size = Pt(size)
    return p


def add_instruction(doc, text):
    add_para(doc, text, italic=True, grey=True, size=10)


def add_kv_table(doc, fields):
    tbl = doc.add_table(rows=1 + len(fields), cols=2)
    tbl.style = "Table Grid"
    hdr = tbl.rows[0].cells
    hdr[0].text = "Field"
    hdr[1].text = "Your entry"
    for cell in hdr:
        for p in cell.paragraphs:
            for run in p.runs:
                run.bold = True
    for i, field in enumerate(fields, start=1):
        tbl.rows[i].cells[0].text = field
        tbl.rows[i].cells[1].text = ""
    doc.add_paragraph()


def add_replication_grid(doc):
    """2x3 grid of slot cells. Each cell has the emotion name, a
    paste-image placeholder, and a one-line classifier-result field."""
    tbl = doc.add_table(rows=2, cols=3)
    tbl.style = "Table Grid"
    for row in range(2):
        for col in range(3):
            idx = row * 3 + col
            emo = EMOTIONS[idx]
            cell = tbl.rows[row].cells[col]
            cell.vertical_alignment = WD_ALIGN_VERTICAL.TOP
            cell.text = ""
            # Slot number and intended emotion
            p_title = cell.paragraphs[0]
            r_title = p_title.add_run(f"{idx + 1}.  {emo.upper()}")
            r_title.bold = True
            r_title.font.size = Pt(11)
            # Image placeholder
            p_img = cell.add_paragraph()
            r_img = p_img.add_run("[paste face or wireframe here]")
            r_img.italic = True
            r_img.font.color.rgb = GREY
            r_img.font.size = Pt(9)
            # Classifier line
            p_cls = cell.add_paragraph()
            r_cls = p_cls.add_run("Classifier said: ____________ (___ .__ )")
            r_cls.font.size = Pt(9)
            # Verdict
            p_v = cell.add_paragraph()
            r_v = p_v.add_run("Agreed / Disagreed (circle one)")
            r_v.font.size = Pt(9)
            r_v.font.color.rgb = GREY
    doc.add_paragraph()


def build():
    doc = Document()

    for section in doc.sections:
        section.top_margin = Cm(1.5)
        section.bottom_margin = Cm(1.5)
        section.left_margin = Cm(1.8)
        section.right_margin = Cm(1.8)

    doc.add_heading("Lesson 4 EmotionMap — six-emotion replication challenge", level=0)

    add_para(
        doc,
        "Pose each of the six basic emotions in turn. Note what the toy "
        "app's classifier read on each attempt. This Word document is "
        "the paper fallback — the primary submission is the single-page "
        "PDF exported from the app.",
        italic=True,
        grey=True,
    )

    add_heading(doc, "Your details", 1)
    add_kv_table(doc, ["Name", "Student number", "Format chosen (A or B)", "Date"])

    add_instruction(
        doc,
        "Format A — Face: paste cropped face thumbnails in each slot. "
        "Format B — Wireframe: paste the anonymised landmark wireframes "
        "the app generates when Wireframe mode is on. Both formats "
        "carry equal weight.",
    )

    add_heading(doc, "Replication grid", 1)
    add_replication_grid(doc)

    add_heading(doc, "Privacy ground rules — confirm", 1)
    add_para(doc, "[ ] I chose my format before I started posing.")
    add_para(doc, "[ ] I understand that the toy app uploads nothing "
                  "beyond the model inference call and stores nothing on "
                  "a server.")
    add_para(doc, "[ ] (Format A only) I consent to my tutor reviewing "
                  "my face-bearing captures.")

    add_heading(doc, "Reflection (2–3 sentences)", 1)
    add_para(doc, "Pick ONE of the prompts and answer in 2–3 sentences.")
    add_para(
        doc,
        "1. Which of the six basic emotions was easiest for the "
        "classifier to recognise on your face? Which was hardest? What "
        "do you think drives that gap — your face, the model, or both?",
    )
    add_para(
        doc,
        "2. Look across your six slots. Are some emotions consistently "
        "recognised, and others much more variable? What does that "
        "variability look like for you, and how might it differ for "
        "someone else in the cohort?",
    )
    add_para(
        doc,
        "3. Did the classifier ever pick a different top emotion from "
        "the one you intended? When it did, what did it pick instead — "
        "and what does that suggest about how 'readable' a felt state "
        "is on a face?",
    )

    # blank space for the reflection answer
    rtbl = doc.add_table(rows=5, cols=1)
    rtbl.style = "Table Grid"
    for r in rtbl.rows:
        r.cells[0].text = ""

    doc.save(OUT_PATH)
    print(f"Wrote {OUT_PATH}")


if __name__ == "__main__":
    build()