Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when calculating control system performance metrics such as rise time, overshoot percentage, steady-state error, or settling time for evaluating simulation results.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Time for system to go from 10% to 90% of target value.
def rise_time(times, values, target):
"""Calculate rise time (10% to 90% of target)."""
t10 = t90 = None
for t, v in zip(times, values):
if t10 is None and v >= 0.1 * target:
t10 = t
if t90 is None and v >= 0.9 * target:
t90 = t
break
if t10 is not None and t90 is not None:
return t90 - t10
return None
How much response exceeds target, as percentage.
def overshoot_percent(values, target):
"""Calculate overshoot percentage."""
max_val = max(values)
if max_val <= target:
return 0.0
return ((max_val - target) / target) * 100
Difference between target and final settled value.
def steady_state_error(values, target, final_fraction=0.1):
"""Calculate steady-state error using final portion of data."""
n = len(values)
start = int(n * (1 - final_fraction))
final_avg = sum(values[start:]) / len(values[start:])
return abs(target - final_avg)
Time to stay within tolerance band of target.
def settling_time(times, values, target, tolerance=0.02):
"""Time to settle within tolerance of target."""
band = target * tolerance
lower, upper = target - band, target + band
settled_at = None
for t, v in zip(times, values):
if v < lower or v > upper:
settled_at = None
elif settled_at is None:
settled_at = t
return settled_at
times = [row['time'] for row in results]
values = [row['value'] for row in results]
target = 30.0
print(f"Rise time: {rise_time(times, values, target)}")
print(f"Overshoot: {overshoot_percent(values, target)}%")
print(f"SS Error: {steady_state_error(values, target)}")
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
日本語の概要は準備中です。原文の説明を表示しています。
AC branch pi-model power flow equations (P/Q and |S|) with transformer tap ratio and phase shift, matching `acopf-math-model.md` and MATPOWER branch fields. Use when computing branch flows in either direction, aggregating bus injections for nodal balance, checking MVA (rateA) limits, computing branch loading %, or debugging sign/units issues in AC power flow.
日本語の概要は準備中です。原文の説明を表示しています。
Redact text from PDF documents for blind review anonymization
日本語の概要は準備中です。原文の説明を表示しています。
Use when checking simplified ADA-derived plan-view bathroom accessibility constraints such as turning space, door clear width, toilet centerline, grab bars, and lavatory knee/toe clearance.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze failed GitHub Action jobs for a pull request.
日本語の概要は準備中です。原文の説明を表示しています。
Use when extracting plan-view architectural geometry from DXF files with semantic CAD layers, especially when outputs must normalize rooms, doors, fixtures, clearances, and grab bars into machine-checkable JSON.
日本語の概要は準備中です。原文の説明を表示しています。