UOMF: Requirement Analysis and Solution Deciding Template in Yankpad

reqs = [r for r in reqs if r is not None]
ev = [r for r in ev if r is not None]

solutions = ev[0][1:]
req_rows = reqs[1:]
ev_rows = ev[1:]

h = "| Requirement | Cl | W |"
for s in solutions:
    h += " {} cov | pts |".format(s)
lines = [h, "|-"]

totals = [0] * len(solutions)

for i, rr in enumerate(req_rows):
    feat = rr[0]
    cls = int(rr[1])
    try:
        w = int(rr[2])
    except (ValueError, TypeError):
        w = 1
    row = "| {} | {} | {} |".format(feat, cls, w)
    er = ev_rows[i]
    for j in range(len(solutions)):
        cov = int(er[1 + j])
        if cls >= 0:
            pts = cls * w * cov
        else:
            pts = abs(cls) * w * (1 - cov)
        totals[j] += pts
        row += " {} | {:+d} |".format(cov, pts)
    lines.append(row)

lines.append("|-")
total_row = "| *Total* |  |  |"
for t in totals:
    total_row += "  | *{:+d}* |".format(t)
lines.append(total_row)

lines += ["", "| Rank | Solution | Score |", "|-"]
ranked = sorted(zip(solutions, totals), key=lambda x: -x[1])
for rank, (sol, sc) in enumerate(ranked, 1):
    lines.append("| {} | {} | {:+d} |".format(rank, sol, sc))

return "\n".join(lines)	  

`(progn (setq yas--ra-h1 (make-string (+ 1 (or (org-current-level) 0)) ?*) yas--ra-h2 (make-string (+ 2 (or (org-current-level) 0)) ?*)) "")`
`yas--ra-h1` Requirement Analysis: ${2:Project Title}

`yas--ra-h2` Requirements

Define features and classify them by importance.

- *Class* (integer, =-2= to =2=): how important is this feature?
  | -2 | must not have |
  | -1 | don't want    |
  |  0 | neutral       |
  |  1 | nice to have  |
  |  2 | must have     |
- *Weight* (integer ≥ 1): optional amplifier within a class.
  Leave at =1= if all requirements in a class are equally important.

#+NAME: ${1:`(format-time-string "%Y-%m-%d")`}-requirements
| Feature | Class | Weight |
|---------+-------+--------|
| $0      |       |      1 |

`yas--ra-h2` Solution Evaluation

Rate how strongly each solution exhibits each feature.

- *Coverage* (integer, =0= to =2=):
  | 0 | not present      |
  | 1 | somewhat present |
  | 2 | fully present    |
- To add solutions: insert columns with =M-S-<right>=.
- Feature names auto-fill: press =C-c C-c= on the =TBLFM= line.
- Ensure this table has the same number of data rows as the requirements table.

#+NAME: $1-evaluation
| Feature | ${3:Solution A} | ${4:Solution B} |
|---------+-----------------+-----------------+
|         |                 |                 |
#+TBLFM: \$1=remote($1-requirements, @@#\$1)

`yas--ra-h2` Results

Scoring (higher is better):
- Class ≥ 0: =class × weight × coverage=
- Class < 0: =|class| × weight × (1 − coverage)=

Press =C-c C-c= on the source block to compute results.

#+NAME: $1-results
#+BEGIN_SRC python :var reqs=$1-requirements ev=$1-evaluation :colnames no :results value raw
reqs = [r for r in reqs if r is not None]
ev = [r for r in ev if r is not None]

solutions = ev[0][1:]
req_rows = reqs[1:]
ev_rows = ev[1:]

h = "| Requirement | Cl | W |"
for s in solutions:
    h += " {} cov | pts |".format(s)
lines = [h, "|-"]

totals = [0] * len(solutions)

for i, rr in enumerate(req_rows):
    feat = rr[0]
    cls = int(rr[1])
    try:
        w = int(rr[2])
    except (ValueError, TypeError):
        w = 1
    row = "| {} | {} | {} |".format(feat, cls, w)
    er = ev_rows[i]
    for j in range(len(solutions)):
        cov = int(er[1 + j])
        if cls >= 0:
            pts = cls * w * cov
        else:
            pts = abs(cls) * w * (1 - cov)
        totals[j] += pts
        row += " {} | {:+d} |".format(cov, pts)
    lines.append(row)

lines.append("|-")
total_row = "| *Total* |  |  |"
for t in totals:
    total_row += "  | *{:+d}* |".format(t)
lines.append(total_row)

lines += ["", "| Rank | Solution | Score |", "|-"]
ranked = sorted(zip(solutions, totals), key=lambda x: -x[1])
for rank, (sol, sc) in enumerate(ranked, 1):
    lines.append("| {} | {} | {:+d} |".format(rank, sol, sc))

return "\n".join(lines)
#+END_SRC