def plot():
cur.execute("SELECT z,v FROM zvaq;")
# cur.execute("SELECT z,a FROM zvaq")
# cur.execute("SELECT z,q FROM zo")
data = np.array(cur.fetchall())
y = data[:, 0]
x = data[:, 1]
yx = np.polyfit(x, y, 2)
p1 = np.poly1d(yx)
plt.plot(x, y, 'o', label='original points')
xnew = np.linspace(x.min(), x.max(), 1000)
ynew = Interpolate.inter1d(x, p1(x), xnew)
plt.plot(xnew, ynew, '--', label='fit')
plt.text(1000, 94,
"$y={}x^2+{}x+{}$"
.format(round(float(yx[0]), 8),
round(float(yx[1]), 4),
round(float(yx[2]), 4)))
# plt.text(100, 150,
# "$y=4.9\\times 10^{-5}x^2+0.1113x+101.4907$")
# plt.xlabel("$V(10^8m^3)$")
# plt.xlabel("$A(km^2)$")
plt.xlabel("$Q(m^3/s)$")
plt.ylabel("$Z(m)$")
plt.grid()
plt.legend()
plt.show()
def __init__(self, data, error, z_s, z_d, zo, k, zv, odh, mon_d=30.4):
# 接受参数 data-> 数据
# data = {
# 'gsq':{mon1:Q1, mon2:Q2, mon3:Q3},
# 'xsq':{mon1:Q1, mon2:Q2, mon3:Q3},
# 'bxbg':{mon1:Q1, mon2:Q2, mon3:Q3},
# }
# error->误差, Z_s->高水位，Z_d->死水位
# 常参定义
self.zo_x = zo[:, 1]
self.zo_y = zo[:, 0]
self.K_H = k[:, 0]
self.K_K = k[:, 1]
self.zv_x = zv[:, 0]
self.zv_y = zv[:, 1]
self.odh_q = odh[:, 0]
self.odh_dh = odh[:, 1]
self.error = error
# self.des_q = des_q
self.mon_d = mon_d
self.Z_s = z_s # 正常蓄水位
self.Z_d = z_d # 死水位
self.data = data # 枯水年径流过程
xnew = np.linspace(self.zv_x.min(), self.zv_x.max(), len(self.zv_x) * 100)
self.V_s = Interpolate.inter1d(list(self.zv_x), list(self.zv_y), xnew, self.Z_s)[1] # V蓄
self.V_d = Interpolate.inter1d(list(self.zv_x), list(self.zv_y), xnew, self.Z_d)[1] # V死
self.V_x = np.array(self.V_s) - np.array(self.V_d) # V兴
self.dh = 1 # 水头损失
self.matrix = None # 结果矩阵
# 月份映射关系
self.map = {
5: 1,
6: 2,
7: 3,
8: 4,
9: 5,
10: 6,
11: 7,
12: 8,
1: 9,
2: 10,
3: 11,
4: 12
}
# 变参数定义
self.N = 600*10000
self.N_eq = self.N
self.N_chk = np.zeros((13, 1)) # 检验出力
self.Q_na = np.zeros((13, 1)) # 来水
self.Q_y = np.zeros((13, 1)) # 引用流量
self.qy() # 初始化Q引
self.Q_xg = np.zeros((13, 1)) # 蓄水供水流量
self.V_xg = np.zeros((13, 1)) # 蓄水供水水量
self.V_begin = np.zeros((13, 1)) # 时段初水量
self.V_begin[0] = self.V_d
self.Z_u = np.zeros((13, 1)) # 上游均水头
self.Z_d = np.zeros((13, 1)) # 下游均水头
self.Z_ave = np.zeros((13, 1)) # 平均水头
self.V_ave = np.zeros((13, 1)) # 时段平均水量
self.K = np.zeros((13, 1)) # 出力系数
self.dh = np.zeros((13, 1)) # 损失水头
mons = [0]
mons.extend(list(self.map.keys()))
self.mon = np.array(mons, dtype=float).reshape((13, 1))
def _dh(self, q):
xnew = np.linspace(self.odh_q.min(), self.odh_q.max(), len(self.odh_q)*100)
dh = Interpolate.inter1d(self.odh_q, self.odh_dh, xnew, q)
return dh
def _k(self, h):
xnew = np.linspace(self.K_H.min(), self.K_H.max(), len(self.K_H)*100)
k = Interpolate.inter1d(self.K_H, self.K_K, xnew, h)
return k
def h_u(self, v):
xnew = np.linspace(self.zv_y.min(), self.zv_y.max(), len(self.zv_y)*100)
h = Interpolate.inter1d(list(self.zv_y), list(self.zv_x), xnew, v)
return h
def h_d(self, q):
xnew = np.linspace(self.zo_x.min(), self.zo_x.max(), len(self.zo_x)*100)
h = Interpolate.inter1d(list(self.zo_x), list(self.zo_y), xnew, q)
return h
# print(round(d, 0))
#
# print('\n')
#
# for d in q_des02:
# print(round(d, 0))
#
# print('\n')
#
# for d in q_des01:
# print(round(d, 0))
# 插值，使曲线光滑
t = np.array([i for i in range(len(q15))])
xnew = np.linspace(t.min(), t.max(), 360)
ynew15 = Interpolate.inter1d(t, q15, xnew)
ynew5 = Interpolate.inter1d(t, q_des5, xnew)
ynew02 = Interpolate.inter1d(t, q_des02, xnew)
ynew01 = Interpolate.inter1d(t, q_des01, xnew)
# 绘图
plt.plot(xnew, ynew15, '-', label='$typical \quad year$') # 典型年
plt.plot(xnew, ynew5, '--', label='$5\%$') # 设计防洪标准5%
plt.plot(xnew, ynew02, '-.', label='$0.2\%$') # 设计洪水0.2%
plt.plot(xnew, ynew01, ':', label='$0.1\%$') # 校核洪水0.1%
plt.grid()
# plt.xticks(t, t)
plt.xlabel('$day$')
plt.ylabel('$Q(m^3/s)$')
plt.legend()
plt.show()