chore: 更新版本至1.0.18
This commit is contained in:
dmy
@@ -34,7 +34,6 @@ pip install -r requirements.txt
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- ezdxf - DXF文件生成
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- loguru - 日志记录
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- matplotlib - 数据可视化和动画
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- numpy - 数值计算
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- tomli - TOML配置文件解析
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- pywebview - 图形界面框架
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94
animation.py
94
animation.py
@@ -1,94 +0,0 @@
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import matplotlib.pyplot as plt
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from functools import wraps
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import numpy as np
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class Animation:
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def __init__(self) -> None:
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fig, ax = plt.subplots()
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self._fig = fig
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self._ax = ax
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self._ticks = 0
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self._disable = False
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self.init_fig()
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pass
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@staticmethod
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def switch_decorator(func):
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@wraps(func)
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def not_run(cls, *args, **kwargs):
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# print("not run")
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pass
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@wraps(func)
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def wrapTheFunction(cls, *args, **kwargs):
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if not cls._disable:
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# print("desc")
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return func(cls, *args, **kwargs)
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return not_run(cls, *args, **kwargs)
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return wrapTheFunction
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def enable(self, _enable):
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self._disable = not _enable
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@switch_decorator
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def init_fig(self):
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ax = self._ax
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ax.set_aspect(1)
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ax.set_xlim([-500, 500])
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ax.set_ylim([-500, 500])
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@switch_decorator
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def show(self):
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self._fig.show()
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@switch_decorator
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def add_rg_line(self, line_func):
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ax = self._ax
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x = np.linspace(0, 300)
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y = line_func(x)
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ax.plot(x, y)
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@switch_decorator
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def add_rs(self, rs, rs_x, rs_y):
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ax = self._ax
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ax.add_artist(plt.Circle((rs_x, rs_y), rs, fill=False))
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@switch_decorator
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def add_rc(self, rc, rc_x, rc_y):
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ax = self._ax
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ax.add_artist(plt.Circle((rc_x, rc_y), rc, fill=False))
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# 增加暴露弧范围
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@switch_decorator
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def add_expose_area(
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self,
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rc_x,
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rc_y,
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intersection_x1,
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intersection_y1,
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intersection_x2,
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intersection_y2,
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):
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ax = self._ax
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ax.plot([rc_x, intersection_x1], [rc_y, intersection_y1], color="red")
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ax.plot([rc_x, intersection_x2], [rc_y, intersection_y2], color="red")
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pass
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@switch_decorator
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def clear(self):
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ax = self._ax
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ax.cla()
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@switch_decorator
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def pause(self):
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ax = self._ax
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self._ticks += 1
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ticks = self._ticks
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ax.set_title(f"{ticks}")
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plt.pause(0.02)
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self.clear()
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self.init_fig()
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pass
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@@ -1,4 +1,4 @@
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version: 1.0.17
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version: 1.0.18
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company_name: EGM
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file_description: EGM Lightning Protection Calculator
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product_name: Lightening
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100
plot.py
100
plot.py
@@ -1,100 +0,0 @@
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import matplotlib
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from plot_data import *
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import matplotlib.pyplot as plt
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import matplotlib.ticker as mticker
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matplotlib.use("Qt5Agg")
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# 解决中文乱码
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plt.rcParams["font.sans-serif"] = ["simsun"]
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plt.rcParams["font.family"] = "sans-serif"
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# plt.rcParams["font.weight"] = "bold"
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# 解决负号无法显示的问题
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plt.rcParams["axes.unicode_minus"] = False
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plt.rcParams["savefig.dpi"] = 1200 # 图片像素
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# plt.savefig("port.png", dpi=600, bbox_inches="tight")
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fontsize = 12
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################################################
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witdh_of_bar=0.3
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color=plt.cm.BuPu(np.linspace(152/255, 251/255,152/255))
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percent1 = data_150m塔高_不同地线保护角[:, 1] / data_150m塔高_不同地线保护角[:, 0]
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# percent1 = data_66m串长_不同塔高[:, 1] / data_66m串长_不同塔高[:, 0]
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# percent2 = data_68m串长_不同塔高[:, 1] / data_68m串长_不同塔高[:, 0]
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fig, ax = plt.subplots()
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x = np.arange(len(category_names_150m塔高_不同地线保护角)) # the label locations
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p1 = ax.bar(category_names_150m塔高_不同地线保护角, percent1, witdh_of_bar, label="绕击/反击跳闸率比值",color=color,hatch='-')
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# p1 = ax.bar(x - 0.3 / 2, percent1, 0.3, label="6.6m绝缘距离")
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# p2 = ax.bar(x + 0.3 / 2, percent2, 0.3, label="6.8m绝缘距离")
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ax.xaxis.set_major_locator(mticker.FixedLocator(x))
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ax.set_xticklabels(category_names_150m塔高_不同地线保护角)
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ax.set_ylabel("比值", fontsize=fontsize)
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ax.set_xlabel("地线保护角(°)", fontsize=fontsize)
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# ax.set_xlabel("接地电阻(Ω)", fontsize=fontsize)
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plt.xticks(fontsize=fontsize)
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plt.yticks(fontsize=fontsize)
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ax.bar_label(p1, padding=0, fontsize=fontsize)
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# ax.bar_label(p2, padding=0, fontsize=fontsize)
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ax.legend(fontsize=fontsize)
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fig.tight_layout()
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plt.show()
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# results = {
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# "100m": 100 * data[0, :] / np.sum(data[0, :]),
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# "110m": data[1, :] / np.sum(data[1, :]),
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# "120m": data[2, :] / np.sum(data[2, :]),
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# "130m": data[3, :] / np.sum(data[3, :]),
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# "140m": data[4, :] / np.sum(data[4, :]),
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# "150m": data[5, :] / np.sum(data[5, :]),
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# }
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# def survey(results, category_names):
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# """
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# Parameters
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# ----------
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# results : dict
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# A mapping from question labels to a list of answers per category.
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# It is assumed all lists contain the same number of entries and that
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# it matches the length of *category_names*.
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# category_names : list of str
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# The category labels.
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# """
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# labels = list(results.keys())
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# data = np.array(list(results.values()))
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# data_cum = data.cumsum(axis=1)
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# category_colors = plt.get_cmap("RdYlGn")(np.linspace(0.15, 0.85, data.shape[1]))
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#
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# fig, ax = plt.subplots(figsize=(9.2, 5))
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# ax.invert_yaxis()
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# ax.xaxis.set_visible(False)
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# ax.set_xlim(0, np.sum(data, axis=1).max())
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#
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# for i, (colname, color) in enumerate(zip(category_names, category_colors)):
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# widths = data[:, i]
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# starts = data_cum[:, i] - widths
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# rects = ax.barh(
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# labels, widths, left=starts, height=0.5, label=colname, color=color
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# )
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#
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# r, g, b, _ = color
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# text_color = "white" if r * g * b < 0.5 else "darkgrey"
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# ax.bar_label(rects, label_type="center", color=text_color)
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# ax.legend(
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# ncol=len(category_names),
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# bbox_to_anchor=(0, 1),
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# loc="lower left",
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# fontsize="small",
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# )
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#
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# return fig, ax
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# percent=data/np.sum(data,axis=1)[:,None]*100
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# percent = data[:, 1] / data[:, 0]
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# plt.bar(category_names, percent, 0.3, label="黑")
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# # plt.bar(category_names, percent[:,0], 0.2, label="r")
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#
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# # plt.bar(category_names, [0.014094 / 100, 0.025094 / 100], 0.2, label="h")
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# plt.legend()
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# # survey(results, category_names)
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# plt.show()
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@@ -4,7 +4,7 @@
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<meta charset="UTF-8" />
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<link rel="icon" type="image/svg+xml" href="/vite.svg" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>EGM 输电线路绕击跳闸率计算 v1.0.17</title>
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<title>EGM 输电线路绕击跳闸率计算 v1.0.18</title>
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</head>
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<body>
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<div id="app"></div>
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