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rsr.py
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# --- coding utf-8 ---
# 燃烧热实验数据处理与作图,改成文件input_output形式
# JamesBourbon in 20191210
import numpy as np
import matplotlib.pyplot as plt
import os
import pandas as pd
# 数据输入
path = os.getcwd() # 获取当前执行路径
input_file = '{}/燃烧热_input.csv'.format(path)
data = pd.read_csv(input_file)
data.fillna(0) # 去NaN
Q_phcooh = np.float64(data['Q_phcooh'][0])
m_phcooh = np.float64(data['m_phcooh'][0])
m_nai = np.float64(data['m_nai'][0])
# 单个数据控制进入的方法如上
n_phcooh = np.array(data['n'], dtype=np.float64)
n_nai = np.array(data['n'], dtype=np.float64)
T_phcooh = np.array(data['T_phcooh'], dtype=np.float64)
T_nai = np.array(data['T_nai'], dtype=np.float64)
M_nai = 128.164 # g/mol,内置参数
T_env = 0
# 此算法通过计算平均温度求环境温度
# 如果外读环境温度，需要在内部调整
# 对标准样的测定结果进行雷诺拟合并且作图；用类集成
class T_refine_plt():
def __init__(self, name, n, T_get, T_env,):
# 基本参数设置
self.path = os.getcwd()
self.name = name
self.T = T_get
self.n = n
# 雷诺较正预处理：切线斜率求取
self.P_linear1 = np.polyfit(
self.n[0:10], self.T[0:10], 1)
self.P_linear2 = np.polyfit(
self.n[20:], self.T[20:], 1)
# 反向用T拟合n，可以在插值的同时求出较正温度
# 取n_fin=21,防止其在20处反应不完全
self.P_in_change = np.polyfit(
self.T[10:14], self.n[10:14], 3)
# self.T_mean = T_env 环境温度的提取
self.T_mean = (self.T[9]+self.T[20]) / 2
self.n_mean = np.polyval(
self.P_in_change, self.T_mean)
# 求平均温度和平均温度对应位置
self.main() # 在创建实例的同时执行所有操作
def plt_setting(self):
# 实验数据可视化的基本设置与基本图
plt.rcParams['font.family'] = 'Arial Unicode MS'
plt.rcParams['font.size'] = 18
# 调整matplotlib内部设置使之支持中文,这种方法改变全局设置
label_ex = '实验数据线'
title_ex = '{}燃烧热测定过程的温度-时间图'.format(
self.name)
# 文本配置
lw_exp = 5
ms_exp = 12
self.fig = plt.figure(figsize=(25,16))
plt.plot(self.n, self.T, 'ro-',
linewidth = lw_exp, markersize = ms_exp, label = label_ex)
plt.xlabel(u'n', fontsize=22)
plt.ylabel(u'T / ℃', fontsize=22)
plt.title(title_ex, fontsize=28)
plt.grid(True)
# 作图基本操作
def linear_get_annotate(self):
# 雷诺较正之后的结果可视化
x_T1 = np.arange(self.n[8], self.n[-5], 1)
x_T2 = np.arange(self.n[5], self.n[-7], 1)
y_T1 = np.polyval(self.P_linear1, x_T1)
y_T2 = np.polyval(self.P_linear2, x_T2)
ord_A = np.array(
[self.n_mean, np.polyval(self.P_linear1, self.n_mean)])
ord_B = np.array(
[self.n_mean, np.polyval(self.P_linear2, self.n_mean)])
ord_text1 = np.array([self.n_mean, self.T_mean])
# 写温差的位置
ord_text2 = np.array([self.n[23], self.T[11]])
# 写信息的位置
self.delta_T = ord_B[1] - ord_A[1]
# 较正温差求取
lw_fit = 3
label_math = '拟合较正线'
plt.plot(x_T1, y_T1, 'b:', linewidth=lw_fit, )
plt.plot(x_T2, y_T2, 'b:', linewidth=lw_fit, label=label_math)
x_T_mean = [0, self.n_mean]
y_T_mean = [self.T_mean, self.T_mean]
plt.plot(x_T_mean, y_T_mean, 'b:', linewidth=lw_fit)
# 温差与箭头标注
tick_size = 24
mes_AB = u' ∆T = {:.4f}℃'.format(self.delta_T)
plt.annotate(mes_AB, xy=ord_A, xytext=ord_text1, fontsize=tick_size,
arrowprops=dict(facecolor='black', shrink=2, width=1))
plt.annotate('', xy=ord_B, xytext=ord_text1-np.array([0,0.4]),
arrowprops=dict(facecolor='black', shrink=2, width=1))
# -(0, 0.4)目的在于消去作图时arrow的起点间隔
plt.legend(loc='best')
def plt_tick(self):
# 设置坐标轴范围，模拟坐标纸效果
# 同时也可以保证有效数字和精度
# 这个设置是对该project普适的
x_blank = 1
y_blank = 0.1
x_min = self.n[0] - x_blank
y_min = self.T[0] - y_blank
x_max = self.n[-1] + x_blank
y_max = self.T[-1] + y_blank
x_delta = 1.00
y_delta = 0.10
plt.xlim((x_min, x_max))
plt.ylim((y_min, y_max))
# 设置坐标轴刻度
my_x_ticks = np.arange(x_min, x_max, x_delta)
my_y_ticks = np.arange(y_min, y_max, y_delta)
plt.xticks(my_x_ticks)
plt.yticks(my_y_ticks)
def main(self):
# 执行程序
self.plt_setting()
self.linear_get_annotate()
self.plt_tick()
plt.savefig('{}/{}燃烧热.png'.format(self.path, self.name))
# 对象程序执行同时就保存图片
# 创建数据处理的实例，同时执行实例中全部操作
do_phcooh = T_refine_plt('苯甲酸', n_phcooh, T_phcooh, T_env)
do_nai = T_refine_plt('萘', n_nai, T_nai, T_env)
# 所得数据的处理
C_env = -Q_phcooh * m_phcooh/do_phcooh.delta_T
Q_nai = -C_env * (M_nai/m_nai) * do_nai.delta_T * 1E-3
Qp = Q_nai + (5-7) * 8.3145 * (T_nai[9]+273.15) * 1E-3 # 计算恒压反应热
# 出数据
msg1 = '苯甲酸燃烧较正温差: ∆T1 = {} K\n'.format(do_phcooh.delta_T)
msg2 = '萘燃烧较正温差: ∆T2 = {} K\n'.format(do_nai.delta_T)
msg3 = '体系热容值: C = {} J/K\n'.format(C_env)
msg4 = '测得萘的恒容燃烧热: Qv = {} kJ/mol\n'.format(Q_nai)
msg5 = '燃烧反应: C10H8(s) + 7O2(g) --> 5CO2(g) + 4H2O(l)\n'
msg6 = '萘的恒压燃烧热: Qp = {} kJ/mol\n'.format(Qp)
msg = msg1 + msg2 + msg3 + msg4 + msg5 + msg6
with open('燃烧热_output.txt', 'w') as f:
f.write(msg)
print('数据文件和作图结果均已保存在当前目录')
# plt.show()
print('done! ')