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Optimize nupack service startup and compute

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Lihatoo 2026-05-28 01:04:44 +08:00
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rna/TrnaStructureBeautifier.py Normal file
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# _*_ coding:utf-8 _*_
#
# @Version : 1.1
# @Project : https://github.com/shueho/BioDataTools
# @Time : 2025/7/23 20:00
# @Update : 2025/8/13 14:00
# @Author : Hao Xue
# @E-mail : studid@163.com
# @File : TrnaStructureBeautifier.py
#
# Enhancement of tRNA secondary structure diagrams generated using the ViennaRNA package.
import os
import re
import argparse
# old = sys.argv[1]
def parse_arguments():
parser = argparse.ArgumentParser(description="RNA结构图美化参数配置")
# === 输入控制 ===
parser.add_argument(
"-i", "--input",
type=str,
required=True,
help="SVG文件或者SVG文件存放的文件夹路径"
)
# === 基础布局 ===
parser.add_argument(
"-s", "--size-weight",
type=float,
default=1.4,
help="图形缩放比例（默认 1.4）"
)
parser.add_argument(
"-p", "--per-row",
type=int,
default=4,
help="每行图片数量（默认 4）"
)
parser.add_argument(
"-hg", "--horizontal-gap",
type=int,
default=8,
help="图片水平间隔（默认 8）"
)
parser.add_argument(
"-vg", "--vertical-gap",
type=int,
default=5,
help="图片垂直间隔（默认 5）"
)
# === 碱基连线颜色 ===
parser.add_argument(
"-ac", "--adjacent-color",
type=str,
default="blue",
help='相邻碱基连线颜色（支持名称或 HEX，如 "blue" 或 "#00FF00"，默认 "blue"）'
)
parser.add_argument(
"-pc", "--pair-color",
type=str,
default="red",
help='配对碱基连线颜色（支持名称或 HEX，如 "red" 或 "#FF0000"，默认 "red"）'
)
# === 碱基圆圈样式 ===
parser.add_argument(
"-bf", "--base-fill",
type=str,
default="white",
help='碱基圆圈填充色（默认 "white"）'
)
parser.add_argument(
"-bs", "--base-stroke",
type=str,
default="black",
help='碱基圆圈轮廓色（默认 "black"）'
)
# === 碱基美化图 ===
parser.add_argument(
"-A", "--base-a",
type=str,
default="red",
help='美化A碱基圆圈填充色（默认 "red"）'
)
parser.add_argument(
"-U", "--base-u",
type=str,
default="blue",
help='美化U/T碱基圆圈填充色（默认 "blue"）'
)
parser.add_argument(
"-G", "--base-g",
type=str,
default="green",
help='美化G碱基圆圈填充色（默认 "green"）'
)
parser.add_argument(
"-C", "--base-c",
type=str,
default="yellow",
help='美化C碱基圆圈填充色（默认 "yellow"）'
)
# === 反密码子控制 ===
# parser.add_argument(
# "-af", "--anticodon-file",
# type=str,
# default=None,
# help="反密码子位点文件路径（文本文件，每行一个位置）"
# )
# parser.add_argument(
# "-aF", "--anti-fill",
# type=str,
# default="red",
# help='反密码子圆圈填充色（默认 "red"）'
# )
# parser.add_argument(
# "-aS", "--anti-stroke",
# type=str,
# default="black",
# help='反密码子圆圈轮廓色（默认 "black"）'
# )
args = parser.parse_args()
return args
args = parse_arguments()
base_color = {"A": args.base_a, "U": args.base_u, "G": args.base_g, "C": args.base_c, }
# 设置目标文件夹名称
modified_folder = "modified"
# 创建文件夹（如果已存在则忽略）
os.makedirs(modified_folder, exist_ok=True)
print("已创建文件夹: modified")
def read_svg(spath):
with open(spath) as f:
return f.read()
def set_new_text(x_y_char, fill_=args.base_fill, stroke_=args.base_stroke):
x = x_y_char[0]
y = x_y_char[1]
t = x_y_char[2].upper().replace("T", "U")
# 核心修改：保持圆圈半径r=5不变，调整dy=0使字母在垂直方向也居中（结合text-anchor=middle实现正中心）
return '<circle cx="{}" cy="{}" r="5" fill="{}" stroke="{}" />\n <text x="{}" y="{}" text-anchor="middle" dy="2"\n font-size="8" fill="black">{}</text>\n'.format(
x, y, fill_, stroke_, x, y, t)
# r=圆圈半径，dy=字体垂直位移，font-size=字体大小
def set_new_lines(x_y_char_1, x_y_char_2, stroke_):
x1, y1, _ = x_y_char_1
x2, y2, _ = x_y_char_2
xy = (x1, y1, x2, y2)
return '<line x1="{}" y1="{}" x2="{}" y2="{}" stroke="{}" stroke-width="1"/>\n'.format(*xy, stroke_)
# 保留原有 get_add_line 函数，不修改（保持代码秩序）
def get_add_line(svg_text):
# pattern = r'<line.*?x1="([^"]+)"[^>]*?y1="([^"]+)"[^>]*?x2="([^"]+)"[^>]*?y2="([^"]+)"'
pattern = r'<line\b[^>]*\s*x1="([^"]+)"[^>]*\s*y1="([^"]+)"[^>]*\s*x2="([^"]+)"[^>]*\s*y2="([^"]+)"'
matches = re.findall(pattern, svg_text)
result = []
for x1_str, y1_str, x2_str, y2_str in matches:
try:
x1 = float(x1_str)
y1 = float(y1_str)
x2 = float(x2_str)
y2 = float(y2_str)
result.append(set_new_lines((x1, y1, ""), (x2, y2, ""), args.pair_color))
except ValueError:
# 如果坐标无法转换为 float，跳过该元素
continue
return "".join(result)
# 核心修改1：extract_text_info 补充返回坐标边界（用于居中计算），生成内容逻辑完全不变
def extract_text_info(svg_text):
# 正则表达式匹配 <text> 标签中的 x、y 和字符内容
# pattern = r'<text\s+x="([^"]+)"\s+y="([^"]+)"[^>]*>([^<]+)</text>'
pattern = r'<text\b[^>]*\s*x="([^"]+)"[^>]*\s*y="([^"]+)"[^>]*>(.*?)<\/text>'
matches = re.findall(pattern, svg_text)
result = []
for x_str, y_str, char in matches:
try:
x = float(x_str)
y = float(y_str)
result.append((x, y, char))
except ValueError:
# 如果 x 或 y 无法转换为 float，跳过该元素
continue
# 计算坐标边界（新增：用于后续居中）
if not result:
min_x = max_x = min_y = max_y = 0
else:
xs = [p[0] for p in result]
ys = [p[1] for p in result]
min_x, max_x = min(xs), max(xs)
min_y, max_y = min(ys), max(ys)
# 原有生成内容逻辑完全不变（保证字母在圆圈内）
content = '<g style="font-family: Times New Roman" transform="translate(-4.6, 4)" id="seq">\n'
content += get_add_line(svg_text)
for i in range(1, len(result)):
# content += set_new_text(result[i])
content += set_new_lines(result[i - 1], result[i], args.adjacent_color)
content += set_new_text(result[i - 1])
content += set_new_text(result[len(result) - 1]) + '</g>\n'
# 新增返回坐标边界，用于居中计算
return content, min_x, max_x, min_y, max_y
def save_svg(content, outpath):
with open(outpath, "w") as f:
f.write(content)
# 核心修改2：modi_svg 改为超大画布 + 自动居中，保留原有逻辑框架
def modi_svg(path):
t = read_svg(path)
name_ = os.path.basename(path)
if "-" in name_:
name_ = name_.split("-")[0]
else:
name_ = name_.split(".")[0]
# 提取内容 + 坐标边界（新增）
mid_, min_x, max_x, min_y, max_y = extract_text_info(t)
scale = args.size_weight
# 1. 超大画布（2000×2000，可自行调大）
canvas_w = 2000
canvas_h = 2000
# 2. 计算结构中心（用于居中）
if min_x == max_x and min_y == max_y:
cx, cy = 0, 0
else:
cx = (min_x + max_x) / 2 # 结构水平中心
cy = (min_y + max_y) / 2 # 结构垂直中心
# 3. 计算居中偏移量（保证结构在画布正中间）
translate_x = (canvas_w / 2) / scale - cx # 水平居中
translate_y = (canvas_h / 2) / scale - cy # 垂直居中
# 保留原有 head_ 结构，仅替换画布尺寸和偏移量，同时修改名称位置避免重叠
head_ = '''<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<svg xmlns="http://www.w3.org/2000/svg" height="{}" width="{}" viewBox="0 0 {} {}">
<rect style="stroke: none; fill: none" height="{}" x="0" y="0" width="{}" onclick="click(evt)" />
<g transform="scale({},{}) translate({:.2f},{:.2f})">
<g style="font-family: Times New Roman" id="name">
<text font-size="20" x="{:.2f}" y="{:.2f}" text-anchor="middle">{}</text>
</g>
'''.format(canvas_h, canvas_w, canvas_w, canvas_h, canvas_h, canvas_w, scale, scale, translate_x, translate_y, cx, min_y - 20, name_)
tail_ = ' </g>\n</svg>'
save_svg(head_ + mid_ + tail_, "modified/modified_" + name_ + ".svg")
return name_
# save_svg(modi_svg(old), "new.svg")
def remove_xml_declaration(content):
"""Remove XML declaration from SVG content."""
return re.sub(r'<\?xml[^>]*\?>\s*', '', content)
def extract_dimensions(svg_content):
"""Extract width and height from SVG content."""
width_match = re.search(r'width="([^"]+)"', svg_content)
height_match = re.search(r'height="([^"]+)"', svg_content)
if not width_match or not height_match:
raise ValueError("Could not extract width or height")
return width_match.group(1), height_match.group(1)
def merge_horizontal_group(svg_files, output_file):
"""Merge SVGs in a group horizontally."""
svgs = []
total_width = 0
max_height = 0
gap = args.horizontal_gap
for filename in svg_files:
with open(filename, 'r') as f:
content = f.read()
content = remove_xml_declaration(content)
width, height = extract_dimensions(content)
try:
width_px = float(width.strip('px'))
height_px = float(height.strip('px'))
except ValueError:
raise ValueError(f"Invalid unit in file {filename}")
svgs.append({
'filename': filename,
'content': content,
'width': width,
'height': height,
'width_px': width_px,
'height_px': height_px
})
total_width += sum(svg_info['width_px'] for svg_info in svgs) + gap * (len(svgs) - 1)
max_height = max(max_height, height_px)
new_svg = [
'<?xml version="1.0" encoding="UTF-8" standalone="no"?>',
'<svg xmlns="http://www.w3.org/2000/svg" width="{}" height="{}">'.format(total_width, max_height)
]
current_x = 0.0
for svg_info in svgs:
inner_content = re.sub(r'<svg[^>]*>', '', svg_info['content'])
inner_content = re.sub(r'</svg>', '', inner_content)
new_svg.append('<g transform="translate({:.2f}, 0)">'.format(current_x))
new_svg.append(inner_content)
new_svg.append('</g>')
current_x += svg_info['width_px'] + gap
new_svg.append('</svg>')
with open(output_file, 'w') as f:
f.write('\n'.join(new_svg))
def merge_vertical_groups(group_files, output_file):
"""Merge all horizontal groups vertically."""
svgs = []
max_width = 0
total_height = 0
gap = args.vertical_gap
for filename in group_files:
with open(filename, 'r') as f:
content = f.read()
content = remove_xml_declaration(content)
width, height = extract_dimensions(content)
try:
width_px = float(width.strip('px'))
height_px = float(height.strip('px'))
except ValueError:
raise ValueError(f"Invalid unit in file {filename}")
svgs.append({
'filename': filename,
'content': content,
'width': width,
'height': height,
'width_px': width_px,
'height_px': height_px
})
max_width = max(max_width, width_px)
total_height += sum(svg_info['height_px'] for svg_info in svgs) + gap * (len(svgs) - 1)
new_svg = [
'<?xml version="1.0" encoding="UTF-8" standalone="no"?>',
'<svg xmlns="http://www.w3.org/2000/svg" width="{}" height="{}">'.format(max_width, total_height)
]
current_y = 0.0
for svg_info in svgs:
inner_content = re.sub(r'<svg[^>]*>', '', svg_info['content'])
inner_content = re.sub(r'</svg>', '', inner_content)
new_svg.append('<g transform="translate(0, {:.2f})">'.format(current_y))
new_svg.append(inner_content)
new_svg.append('</g>')
current_y += svg_info['height_px'] + gap
new_svg.append('</svg>')
with open(output_file, 'w') as f:
f.write('\n'.join(new_svg))
def update_circle_colors(svg_content, base_color_map):
new_ = ""
ls = svg_content.split("\n")
for i in range(len(ls)):
if "<circle cx" in ls[i]:
flag = re.findall(r'(?<=>)[A-Z](?=<\/text>)', ls[i + 2])[0]
if flag not in base_color_map:
new_ += ls[i] + "\n"
continue
new_ += ls[i].replace(args.base_fill, base_color_map[flag]) + "\n"
else:
new_ += ls[i] + "\n"
return new_
if __name__ == "__main__":
# 示例调用
print("参数解析结果:")
# print(f"主数据文件: {args.input}")
print(f"大小权重: {args.size_weight}")
print(f"每行图片数量: {args.per_row}")
print(f"图片水平间隔: {args.horizontal_gap}")
print(f"图片垂直间隔: {args.vertical_gap}")
print(f"相邻碱基连线颜色: {args.adjacent_color}")
print(f"配对碱基连线颜色: {args.pair_color}")
print(f"碱基填充色: {args.base_fill}")
print(f"碱基轮廓色: {args.base_stroke}")
# print(f"反密码子文件: {args.anticodon_file}")
# print(f"反密码子填充色: {args.anti_fill}")
# print(f"反密码子轮廓色: {args.anti_stroke}")
# 如果是文件，直接添加到列表
file_list = []
group_size = args.per_row
if os.path.isfile(args.input):
file_list.append(args.input)
print(f"已添加文件: {args.input}")
# 如果是文件夹，添加文件夹内所有文件（不递归子文件夹）
elif os.path.isdir(args.input):
for filename in os.listdir(args.input):
file_path = os.path.join(args.input, filename)
if os.path.isfile(file_path) and "modified_" not in file_path and ".svg" == file_path[-4:]: # 只处理文件
file_list.append(file_path)
file_list.sort()
print(f"已添加文件夹内所有文件: {args.input}")
modi_files = []
for i in file_list:
n = modi_svg(i)
modi_files.append("modified/modified_" + n + ".svg")
# Step 2: Merge into horizontal groups
group_index = 0
group_files = []
for i in range(0, len(modi_files), group_size):
group = modi_files[i:i + group_size]
if not group:
break
group_output = f"modified/group_{group_index}.svg"
merge_horizontal_group(group, str(group_output))
group_files.append(group_output)
group_index += 1
# Step 3: Merge all groups vertically
final_output = "modified/final.svg"
merge_vertical_groups(group_files, str(final_output))
print(f"未上色SVG保存到: {final_output}")
print(f"美化A碱基填充色: {args.base_a}")
print(f"美化U碱基填充色: {args.base_u}")
print(f"美化G碱基填充色: {args.base_g}")
print(f"美化C碱基填充色: {args.base_c}")
fisvg = read_svg(str(final_output))
cosvg = update_circle_colors(fisvg, base_color)
save_svg(cosvg, "modified/final_color.svg")
# 核心修改3：修复打印路径错误（原写成 final.svg，改为 final_color.svg）
print(f"上色SVG保存到: modified/final_color.svg")
# print(modi_files)

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rna/nupack代码示例.txt Normal file
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model1 = Model(material='dna', celsius=37,sodium=0.1, magnesium=0.02)
Y1 = Strand('CGTTAACGCAGTGAGGACGGTAGTTTGTCGTTCCATCGCACC', name='Y1')
Y2 = Strand('CGTTAACGGGTGCGATGGAACGACTTTCGACAGGCCTGGTGTAATTTCACCCATGTTAGTCGA', name='Y2')
Y3 = Strand('ATACGGAAAATGGAGATAGGAAGAGTACAATGTCAGCGATAAATTCCGTATACGACACCAGGCCTGTCGATTACTACCGTCCTCACTG', name='Y3')
t1 = Tube({Y1: 1e-8, Y2: 1e-8, Y3:1e-8 },complexes=SetSpec(max_size=4), name='Tube 1')
my_result = tube_analysis(tubes=[t1], model=model1,
compute=['pfunc', 'pairs', 'mfe', 'sample', 'subopt'])
print(my_result)

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rna/工具调用.txt Normal file
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from nupack import *
import subprocess
import os
# ---------- 独立的辅助函数 ----------
def get_sequence(Complex, result, skip_errors=True):
"""
获取复合物的序列。
- 若 Complex 为 None，返回字典 {复合物名: 序列}，跳过解析失败的复合物。
- 若 Complex 为字符串或 Complex 对象，返回该复合物的序列字符串；失败时抛出异常（除非 skip_errors=False 时由调用者处理）。
"""
# 统一转换为字符串名称
if Complex is not None and not isinstance(Complex, str):
Complex = Complex.name if hasattr(Complex, 'name') else str(Complex)
def _get_seq_from_strands(strand_names, comp_name=None):
"""从链名列表获取拼接后的序列，如果失败则抛出异常"""
seq_parts = []
for s in strand_names:
if not s.isidentifier():
raise NameError(
f"复合物 '{comp_name}' 中的链名 '{s}' 不是有效的 Python 标识符，"
"请检查链的 name 属性是否包含空格或特殊字符。"
)
try:
strand_obj = eval(s)
if not isinstance(strand_obj, Strand):
raise TypeError(f"'{s}' 不是 Strand 对象")
seq_parts.append(str(strand_obj))
except NameError:
raise NameError(f"链名 '{s}' 未定义，请确保该变量已创建为 Strand 对象。")
return ''.join(seq_parts)
if Complex is None:
# 批量模式
sequences = {}
for comp in result:
name = comp.name if hasattr(comp, 'name') else str(comp)
try:
# 去除括号，按 '+' 分割
inp = ''.join([ch for ch in name if ch not in '()'])
strands = inp.split('+')
sequences[name] = _get_seq_from_strands(strands, comp_name=name)
except Exception as e:
if skip_errors:
print(f"⚠️ 跳过复合物 '{name}'，原因：{e}")
else:
raise # 如果不跳过，则抛出异常
return sequences
else:
# 单复合物模式
inp = ''.join([ch for ch in Complex if ch not in '()'])
strands = inp.split('+')
return _get_seq_from_strands(strands, comp_name=Complex)
def get_structure(Complex, result, skip_errors=True):
"""
获取复合物的 MFE 结构（已去除 '+'）。
- 若 Complex 为 None，返回字典 {复合物名: 结构}，跳过 result 中不存在的复合物。
- 若 Complex 为字符串或 Complex 对象，返回该复合物的结构字符串；失败时抛出异常。
"""
if Complex is not None and not isinstance(Complex, str):
Complex = Complex.name if hasattr(Complex, 'name') else str(Complex)
if Complex is None:
structures = {}
for comp in result:
name = comp.name if hasattr(comp, 'name') else str(comp)
try:
structure = result[comp].mfe[0].structure
structures[name] = str(structure).replace('+', '')
except Exception as e:
if skip_errors:
print(f"⚠️ 跳过复合物 '{name}'，获取结构失败：{e}")
else:
raise
return structures
else:
structure = result[Complex].mfe[0].structure
return str(structure).replace('+', '')
# ---------- 绘图函数（带错误跳过） ----------
def danlian(Complex, result, output_folder="/home/zsy"):
"""
绘制单个复合物的二级结构图。如果处理过程中出现错误，打印错误信息并返回，不中断程序。
Complex 可为复合物名称字符串或 Complex 对象。
"""
try:
sequence = get_sequence(Complex, result, skip_errors=False) # 这里不跳过，让异常抛出以便捕获
best_structure = get_structure(Complex, result, skip_errors=False)
except Exception as e:
name = Complex if isinstance(Complex, str) else (Complex.name if hasattr(Complex, 'name') else str(Complex))
print(f"❌ 处理复合物 '{name}' 时出错：{e}，已跳过绘图")
return
# 获取用于文件名的字符串名称
if isinstance(Complex, str):
seq_name = Complex
else:
seq_name = Complex.name if hasattr(Complex, 'name') else str(Complex)
temp_file_path = os.path.join(output_folder, f"{seq_name}.seq")
try:
with open(temp_file_path, "w", newline='\n') as f:
f.write(f">{seq_name}\n")
f.write(f"{sequence}\n")
f.write(f"{best_structure}\n")
except Exception as e:
print(f"❌ 写入临时文件失败：{e}")
return
try:
input_filename = f"{seq_name}.seq"
process = subprocess.run(["RNAplot", "--o", "svg", input_filename], cwd=output_folder, capture_output=True, text=True)
if process.returncode == 0:
print(f"🎉 绘图成功！请前往 {output_folder} 文件夹查看 {seq_name}_ss.svg")
os.remove(temp_file_path)
else:
print(f"❌ RNAplot 运行失败，报错信息：\n{process.stderr}")
except FileNotFoundError:
print("❌ 找不到 RNAplot 命令，请确认环境变量。")
except Exception as e:
print(f"❌ 绘图过程中出现未知错误：{e}")
使用方法
算全部结果
for comp in my_result:
danlian(comp, my_result, output_folder="/home/zsy")
算单个结果
# 假设您的计算结果保存在 my_result 中
target = '(Y2+Y3)' # 替换为您的目标复合物名称
# 输出结构
print(get_structure(target, my_result))
# 输出序列
print(get_sequence(target, my_result))
# 绘制二级结构图
danlian(target, my_result, output_folder="/home/zsy")

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准备工作：
在 Windows 界面中搜索 控制面板 打开 程序-程序和功能-启动或关闭 Windows 功能-勾选‘适用于 Linux 的 Windows 子系统’与‘虚拟机平台’后点击确定后重启电脑
在 Microsoft Store 中下载 Ubunut
按 Win+X 键 点击 ‘命令提示符（管理员）’ 输入 wsl --install 后回车。下载完毕后关闭即可。 如果遇到链接失败就是网络问题，链接手机热点后重新输入+回车即可
安装：打开 Ubunut
将群内的所有压缩包直接保存在D盘
nupack 安装
mkdir nupack-latest
cd nupack-latest
cp /mnt/d/nupack-4.0.2.0.zip ./
sudo apt install unzip
unzip nupack-4.0.2.0.zip
cd ..
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
/bin/bash Miniconda3-latest-Linux-x86_64.sh -b
miniconda3/bin/conda update -n base -c defaults conda
rm Miniconda3-latest-Linux-x86_64.sh
export PATH=$HOME/miniconda3/bin:$PATH
echo 'export PATH=$HOME/miniconda3/bin:$PATH' >> ~/.bashrc
conda install numpy scipy pip matplotlib pandas jupyterlab
pip install -U nupack -f ./nupack-latest/nupack-4.0.2.0/package
jupyter lab
RNAplot 安装
mkdir rna
cd rna
cp /mnt/d/ViennaRNA-2.7.2.tar.gz ./
tar -zxvf ViennaRNA-2.7.2.tar.gz
cd ViennaRNA-2.7.2
（可能出现报错的解决方法
sudo apt update
sudo apt install build-essentia
sudo apt install pkg-config）
./configure
make
sudo make install
图片美化方法
将生成后的svg图片保存在一个文件夹内，并将该文件夹与群内的 py 文件保存在一个文件夹。后 Shift+鼠标右键 点击在此处打开 Powershell 窗口后
输入命令
python TrnaStructureBeautifier.py -i 文件夹名称 用于指定一个文件夹
python TrnaStructureBeautifier.py -i 文件名称 用于指定一个文件

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from nupack import *
import subprocess
import os
def huatu(Complex,result):#Complex是你想查看的复合物，eg: '(StrandA+StrandB)' 引号和括号都要有;
#result是nupack计算（tube_analysis）的结果，eg: nupack指南里用过my_result、my_results和tube_results等, 或者你自己有其他命名
def jiegou(Complex,result):
m=str(result[Complex].mfe[0].structure)
mm=""
for i in m:
if i != "+":
mm=mm+i
if i=="":
continue
return mm
def xulie(Complex):
inp=''
for i in Complex:
if i != '(' and i != ')':
inp=inp+i
else:
continue
l=inp.split('+',-1)
xulie=''
for i in l:
xulie=xulie+str(eval(i))
return xulie
sequence=xulie(Complex)
best_structure=jiegou(Complex,result)
seq_name =Complex
output_folder="/home/liusiye/桌面/nupack-4.0.2.0"#指定图片保存在哪个文件夹，需自己更改
temp_file_path = os.path.join(output_folder, f"{seq_name}.seq")
with open(temp_file_path, "w", newline='\n') as f:
f.write(f">{seq_name}\n")
f.write(f"{sequence}\n")
f.write(f"{best_structure}\n")
try:
input_filename = f"{seq_name}.seq"
process = subprocess.run(["RNAplot", "--o", "svg", input_filename], cwd=output_folder, capture_output=True, text=True)
if process.returncode == 0:
print(f"🎉 绘图成功！请前往 {output_folder} 文件夹查看 {seq_name}_ss.svg")
os.remove(temp_file_path)
else:
print("❌ RNAplot 运行失败，报错信息：\n", process.stderr)
except FileNotFoundError:
print("❌ 找不到 RNAplot 命令，请确认环境变量。")