for k in range(0, len(qq)): # 从1开始 计算扩散 cc = gaussnmdl_ins(qq[k], tt[k], t_end, umean, h_leak, sigmax, sigmay, sigmaz, X, Y, h_observe, inverse, hi=10e50) # 计算扩散浓度 cc1 = np.flip(cc, axis=0) cc = np.concatenate((cc, cc1), axis=0) total_leak = cc.sum() # 对每个网格的浓度进行求和 cc[cc >= uel] = 0 cc[cc <= 0.9 * lel] = 0 ccb = cc.copy() part_leak = ccb.sum() x1 = ccb.sum(axis=0) y1 = np.arange(-len(x1) / 2, len(x1) / 2) c1 = x1 * y1 numerator = c1.sum() denominator = cc.sum() + 1e-6 # 防止出现0 if numerator > 0: O = (numerator / denominator) * (rangex * 2 / gridnumber) # 计算参与爆炸的蒸汽云的质心坐标,防止分母为0 r = part_leak / (total_leak + 1e-6) Mg = qq[k] * r * 0.2 else: O = (numerator / denominator) * (rangex * 2 / gridnumber) Mg = 1e-6 # 计算超压值 Pa = Pa_vce(x, y, O, Hc, H_TNT, Mg, fe_del) Pa_arr.append(Pa) MG.append("距离") distance = np.sqrt((x - O) ** 2 + y ** 2) MG.append(format(distance, ".1f")) MG.append("蒸汽云质量") MG.append(format(Mg, ".1f")) # 计算概率与后果 pign = pdel * p_fire # 本阶段的点火概率 p += pign MG.append("点火概率" + format(pign, ".2g")) p_up, ttf = P_upgrade("超压", tank2_pressure, Pa, tank2_V) p_add += pign * p_up MG.append("累计概率" + str(p_add)) pdel = 1 - p 从python语法角度这段代码怎么优化

从语法角度来看，这段代码的优化建议如下：

1. 减少不必要的括号和空格，使代码更加简洁易读。

2. 尽量使用向量化计算，避免循环，提高计算效率。

3. 使用更加具有表现力的变量名，增加代码的可读性。

4. 使用常量或者全局变量代替重复计算的值，减少计算量。

5. 使用列表推导式代替循环生成列表，提高代码的效率。

6. 将代码分成多个函数，使得每个函数只完成一个功能，提高代码的可维护性。

下面是对应的优化代码：

def calculate_diffusion(qq, tt, t_end, umean, h_leak, sigmax, sigmay, sigmaz, X, Y, h_observe, inverse, hi):
    cc_arr = []
    for q, t in zip(qq, tt):
        cc = gaussnmdl_ins(q, t, t_end, umean, h_leak, sigmax, sigmay, sigmaz, X, Y, h_observe, inverse, hi)
        cc1 = np.flip(cc, axis=0)
        cc = np.concatenate((cc, cc1), axis=0)
        cc[cc >= uel] = 0
        cc[cc <= 0.9 * lel] = 0
        cc_arr.append(cc)
    return cc_arr


def calculate_leak(cc_arr):
    total_leak_arr = []
    part_leak_arr = []
    for cc in cc_arr:
        total_leak = cc.sum()
        part_leak = cc.copy().sum()
        total_leak_arr.append(total_leak)
        part_leak_arr.append(part_leak)
    return total_leak_arr, part_leak_arr


def calculate_mg(qq, total_leak_arr, part_leak_arr, MG):
    for q, total_leak, part_leak in zip(qq, total_leak_arr, part_leak_arr):
        numerator = ((cc := np.sum(cc_arr, axis=0)) * (y1 := np.arange(-len(cc) / 2, len(cc) / 2))).sum()
        denominator = cc.sum() + 1e-6
        O = (numerator / denominator) * (rangex * 2 / gridnumber)
        r = q * part_leak / (total_leak + 1e-6)
        Mg = r * 0.2 if numerator > 0 else 1e-6
        MG.extend(["距离", format(np.sqrt((x - O) ** 2 + y ** 2), ".1f"), "蒸汽云质量", format(Mg, ".1f")])
    return MG


def calculate_pa(qq, total_leak_arr, part_leak_arr, MG):
    Pa_arr = []
    for q, total_leak, part_leak in zip(qq, total_leak_arr, part_leak_arr):
        numerator = ((cc := np.sum(cc_arr, axis=0)) * (y1 := np.arange(-len(cc) / 2, len(cc) / 2))).sum()
        denominator = cc.sum() + 1e-6
        O = (numerator / denominator) * (rangex * 2 / gridnumber)
        Mg = r * 0.2 if numerator > 0 else 1e-6
        Pa = Pa_vce(x, y, O, Hc, H_TNT, Mg, fe_del)
        Pa_arr.append(Pa)
        MG.extend(["点火概率" + format(pign := pdel * p_fire, ".2g"), "累计概率" + str(p_add := p_add + pign * P_upgrade("超压", tank2_pressure, Pa, tank2_V)[0])])
        pdel = 1 - p
    return Pa_arr, MG


cc_arr = calculate_diffusion(qq, tt, t_end, umean, h_leak, sigmax, sigmay, sigmaz, X, Y, h_observe, inverse, hi)
total_leak_arr, part_leak_arr = calculate_leak(cc_arr)
MG = calculate_mg(qq, total_leak_arr, part_leak_arr, MG)
Pa_arr, MG = calculate_pa(qq, total_leak_arr, part_leak_arr, MG)