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import gradio as gr
import pandas as pd
import math
def add_variables(M, L1, L2, LS, A, z, n):
r_m = []
r_l1 = []
r_l2 = []
r_ls = []
if L2 == 0:
if LS == 0:
raise Exception('Error! L2 and LS cannot be both 0, please input again!')
else:
for m in range(math.ceil(2*A / M) + 1):
for l1 in range(math.ceil(2*A / L1) + 1):
for ls in range(math.ceil(2*A / LS) + 1):
total_mass = M * m + L1 * l1 + LS * ls
if (z * A - n <= total_mass <= z * A + n) and ls < m:
r_m.append(m)
r_l1.append(l1)
r_l2.append(None)
r_ls.append(ls)
results = {
'M': r_m,
'L1': r_l1,
'L2': r_l2,
'LS': r_ls,
}
df = pd.DataFrame(results)
print("符合 {} =< {}*m+{}*l1+{}*ls <= {} 并 LS < M 的所有自然数解有{}组，分别为："
.format(A - n, M, L1, LS, A + n, len(r_m)))
print(df.to_markdown(tablefmt="grid"))
df.to_csv("result.csv", index=False)
else:
if LS == 0:
for m in range(math.ceil(2*A / M) + 1):
for l1 in range(math.ceil(2*A / L1) + 1):
for l2 in range(math.ceil(2*A / L2) + 1):
total_mass = M * m + L1 * l1 + L2 * l2
if z * A - n <= total_mass <= z * A + n:
r_m.append(m)
r_l1.append(l1)
r_l2.append(l2)
r_ls.append(None)
results = {
'M': r_m,
'L1': r_l1,
'L2': r_l2,
'LS': r_ls,
}
df = pd.DataFrame(results)
print("符合 {} =< {}*m+{}*l1+{}*l2 <= {} 的所有自然数解有{}组，分别为："
.format(A - n, M, L1, L2, A + n, len(r_m)))
print(df.to_markdown(tablefmt="grid"))
df.to_csv("result.csv", index=False)
else:
for m in range(math.ceil(2*A / M) + 1):
for l1 in range(math.ceil(2*A / L1) + 1):
for l2 in range(math.ceil(2*A / L2) + 1):
for ls in range(math.ceil(2*A / LS) + 1):
total_mass = M * m + L1 * l1 + L2 * l2 + LS * ls
if (z * A - n <= total_mass <= z * A + n) and ls < m:
r_m.append(m)
r_l1.append(l1)
r_l2.append(l2)
r_ls.append(ls)
results = {
'M': r_m,
'L1': r_l1,
'L2': r_l2,
'LS': r_ls,
}
df = pd.DataFrame(results)
print("符合 {} =< {}*m+{}*l1+{}*l2+{}*ls <= {} 并 LS < M 的所有自然数解有{}组，分别为："
.format(A - n, M, L1, L2, LS, A + n, len(r_m)))
print(df.to_markdown(tablefmt="grid"))
df.to_csv("result.csv", index=False)
return df, "result.csv"
iface = gr.Interface(
fn=add_variables,
inputs=["number", "number", "number", "number", "number", "number", "number"],
outputs=["dataframe",'file'],
title="MS",
description="输入：|-M: 金属| -L1: 配体1 | -L2: 配体2 | -LS: 含S配体的相对分子质量 | -A: 质谱上对应的分子量 | -z: 电荷 |"
)
iface.launch(share=True)
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