[Arduino] Thermistor, Peltier module 을 활용해 Rising time과 Return Time 다항식 만들기 / 파이썬 / 아두이노

이전 포스팅에서 만든 최종 결과로, 다항식을 만들어볼 예정입니다.

일단 제 실험 결과는 아래처럼 나왔습니다.

Folder	File	Delta	Rise_Time_s	Return_Time_s
delta_-1.0	run_1.csv	-1	1.029	1.027
delta_-1.0	run_2.csv	-1	1.029	1.027
delta_-1.0	run_3.csv	-1	1.03	0.822
delta_-1.0	run_4.csv	-1	1.03	1.027
delta_-1.0	run_5.csv	-1	1.029	1.028
delta_-2.0	run_1.csv	-2	1.648	1.644
delta_-2.0	run_2.csv	-2	1.75	1.644
delta_-2.0	run_3.csv	-2	1.648	1.644
delta_-2.0	run_4.csv	-2	1.75	1.028
delta_-2.0	run_5.csv	-2	1.647	1.644
delta_-3.0	run_1.csv	-3	2.369	2.159
delta_-3.0	run_2.csv	-3	2.265	2.159
delta_-3.0	run_3.csv	-3	2.265	2.055
delta_-3.0	run_4.csv	-3	2.369	2.159
delta_-3.0	run_5.csv	-3	2.367	2.158
delta_-4.0	run_1.csv	-4	2.678	2.467
delta_-4.0	run_2.csv	-4	2.883	2.467
delta_-4.0	run_3.csv	-4	2.883	2.468
delta_-4.0	run_4.csv	-4	2.781	2.467
delta_-4.0	run_5.csv	-4	2.884	2.467
delta_-5.0	run_1.csv	-5	3.296	2.673
delta_-5.0	run_2.csv	-5	3.398	2.672
delta_-5.0	run_3.csv	-5	3.398	2.672
delta_-5.0	run_4.csv	-5	3.398	2.672
delta_-5.0	run_5.csv	-5	3.296	2.467
delta_-6.0	run_1.csv	-6	4.015	2.98
delta_-6.0	run_2.csv	-6	3.811	2.981
delta_-6.0	run_3.csv	-6	3.81	2.981
delta_-6.0	run_4.csv	-6	3.809	2.877
delta_-6.0	run_5.csv	-6	3.81	2.98
delta_0.0	run_1.csv	0
delta_0.0	run_2.csv	0
delta_0.0	run_3.csv	0
delta_0.0	run_4.csv	0
delta_0.0	run_5.csv	0
delta_1.0	run_1.csv	1	1.132	1.028
delta_1.0	run_2.csv	1	1.028	1.027
delta_1.0	run_3.csv	1	1.028	1.13
delta_1.0	run_4.csv	1	1.131	1.028
delta_1.0	run_5.csv	1	1.132	1.027
delta_2.0	run_1.csv	2	1.749	1.748
delta_2.0	run_2.csv	2	1.543	1.541
delta_2.0	run_3.csv	2	1.647	1.645
delta_2.0	run_4.csv	2	1.749	1.644
delta_2.0	run_5.csv	2	1.749	1.644
delta_3.0	run_1.csv	3	2.47	2.262
delta_3.0	run_2.csv	3	2.263	2.261
delta_3.0	run_3.csv	3	2.367	2.159
delta_3.0	run_4.csv	3	2.264	2.261
delta_3.0	run_5.csv	3	2.263	2.261
delta_4.0	run_1.csv	4	2.675	2.673
delta_4.0	run_2.csv	4	2.779	2.569
delta_4.0	run_3.csv	4	2.676	2.364
delta_4.0	run_4.csv	4	2.779	2.467
delta_4.0	run_5.csv	4	2.882	2.569
delta_5.0	run_1.csv	5	3.191	2.776
delta_5.0	run_2.csv	5	3.088	2.878
delta_5.0	run_3.csv	5	3.088	2.775
delta_5.0	run_4.csv	5	2.984	2.775
delta_5.0	run_5.csv	5	3.19	2.57
delta_6.0	run_1.csv	6	3.602	2.877
delta_6.0	run_2.csv	6	3.603	2.878
delta_6.0	run_3.csv	6	3.705	2.877
delta_6.0	run_4.csv	6	3.602	2.981
delta_6.0	run_5.csv	6	3.499	2.878

이제, 이걸 다항식으로 만들어보겠습니다.

 

import numpy as np
import pandas as pd
from numpy.polynomial import Polynomial
import json

# ============================
# 1. Load and clean data
# ============================

# CSV 파일 로드
df = pd.read_csv("delta_summary_rise_return_times.csv")

# NaN 제거
clean_data = df.dropna(subset=["Rise_Time_s", "Return_Time_s"])

# ============================
# 2. Group by Delta and get mean
# ============================

# Delta별 평균 Rise/Return Time 계산
delta_avg = clean_data.groupby("Delta")[["Rise_Time_s", "Return_Time_s"]].mean().reset_index()

# 평균 Rise, Return도 함께 저장
delta_avg["Mean_Time"] = delta_avg[["Rise_Time_s", "Return_Time_s"]].mean(axis=1)

# 컬럼명 명확히
delta_avg.rename(columns={
    "Rise_Time_s": "Mean_Rise_Time_s",
    "Return_Time_s": "Mean_Return_Time_s"
}, inplace=True)
output_path = "delta_mean_times.csv"
round(delta_avg,2).to_csv(output_path, index=False)
# ============================
# 3. Polynomial Fit
# ============================

# Δ별 평균값 추출
deltas = delta_avg["Delta"].values
rise_times = delta_avg["Mean_Rise_Time_s"].values
return_times = delta_avg["Mean_Return_Time_s"].values

# 2차 다항식 피팅 후 standard basis로 변환
rise_poly = Polynomial.fit(deltas, rise_times, 2).convert()
return_poly = Polynomial.fit(deltas, return_times, 2).convert()

# ============================
# 4. Δ 입력 시 평균값 계산 함수
# ============================

def get_rise_return_time(delta_val):
    if delta_val == 0:
        return 0.0, 0.0
    rise = rise_poly(delta_val)
    ret = return_poly(delta_val)
    return round(rise, 2), round(ret, 2)

# 예시 출력
print(f"다항식: rising : {rise_poly} \n return: {return_poly}")
example_outputs = {delta: get_rise_return_time(delta) for delta in [-6, -4.3, -2, 0, 1.5, 3.2, 6]}
print(example_outputs)

# ============================
# 5. 다항식 계수 JSON 저장 (JS 연동용)
# ============================

# 계수 추출
rise_coeffs = rise_poly.coef.tolist()
return_coeffs = return_poly.coef.tolist()

# JSON 파일로 저장
with open("rise_coeffs.json", "w") as f:
    json.dump(rise_coeffs, f)

with open("return_coeffs.json", "w") as f:
    json.dump(return_coeffs, f)

 

최종적으로 저장되는 형태

Delta	Mean_Rise_Time_s	Mean_Return_Time_s	Mean_Time
-6	3.85	2.96	3.41
-5	3.36	2.63	2.99
-4	2.82	2.47	2.64
-3	2.33	2.14	2.23
-2	1.69	1.52	1.6
-1	1.03	0.99	1.01
1	1.09	1.05	1.07
2	1.69	1.64	1.67
3	2.33	2.24	2.28
4	2.76	2.53	2.64
5	3.11	2.75	2.93
6	3.6	2.9	3.25