CREAT.py

@@ -0,0 +1,134 @@
+import numpy as np
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+from scipy.stats import gaussian_kde
+from scipy.spatial.distance import cdist
+import copy
+
+
+class create():
+    def __init__(self):
+        """
+        data is the x and y coordinate of data.pos
+        contours is the edge points
+        f is the kernel density value
+        levels is the levels for contours
+        x_range  is the range of x label
+        y_range is the range of y label
+
+        """
+        self.data = []
+        self.contours = []
+        self.f = []
+        self.levels = []
+        self.x_range = []
+        self.y_range = []
+
+    def data_pre(self, data_name):
+        with open(data_name, 'r') as f:
+            lines = f.readlines()
+        L_en=len(lines)
+        lines= lines[1:L_en]
+        data = []
+        for line in lines:
+            x, y,z,t = line.strip().split("\t")
+            data.append(list(map(float, [x,y])))
+        data = np.array(data)
+        self.data = data
+        self.x_range = [min(data[:, 0]), max(data[:,0])]
+        self.y_range = [min(data[:, 1]), max(data[:,1])]
+
+    def contours_pre(self, level_nums, gWeight):
+
+        x = self.data[:, 0]
+        y = self.data[:, 1]
+        # 使用scipy库中的gaussian_kde函数计算密度估计
+        kde = gaussian_kde(self.data.T)
+        # 生成网格点坐标
+        xx, yy = np.mgrid[x.min():x.max():200j, y.min():y.max():200j]
+        positions = np.vstack([xx.ravel(), yy.ravel()])
+        # 计算网格点上的密度估计值
+        f = np.reshape(kde(positions).T, xx.shape)
+        # 绘制等高线图
+        levels = []
+        for i in range(level_nums):
+            levels.append(f.max() - (level_nums - i - 1) * (f.max() - f.min()) / gWeight)
+        self.levels = levels
+        contours = plt.contour(xx, yy, f, levels=[levels[0], levels[level_nums - 1]], cmap='coolwarm', alpha=0)
+        plt.close()
+        self_contours = []
+        for i in range(len(contours.allsegs[0])):
+            self_contours += contours.allsegs[0][i].tolist()
+
+        for i in range(len(self_contours)):
+            if self_contours[i] not in self.contours:
+                self.contours += [self_contours[i]]
+
+        self.f = f
+
+
+class well_to_edge():
+    def __init__(self):
+        """
+        name is used to store the well names
+        type is the types of the wells
+        position is the coordinates of wells
+        min_distance is the minimum distances between wells and edge
+        welltoedge_points is the points responding to the min_distance
+        angle is the angles between the shortest distance direction vector from the well to the edge and the positive direction of the y-axis during clockwise rotation;
+        wells_num: the number of wells
+        """
+        self.name = []
+        self.type = []
+        self.position = []
+        self.min_distance = []
+        self.welltoedge_points = []
+        self.angle = []
+        self.wells_num = 0
+
+    def wells_name_and_position(self, wells_name):
+        # 读取井位信息
+        with open(wells_name, 'r') as f_j:
+            j_ing = f_j.readlines()
+        points = []
+        typee = []
+        namee = []
+        for line in j_ing:
+            x, y, type, name = line.strip().split("\t")
+            points.append(list(map(float, [x, y])))
+            typee.append(list(map(int, [type])))
+            namee.append(name.split('\n'))
+        self.position = points
+        self.name = namee
+        self.type = typee
+        self.wells_num = len(points)
+
+    def welltoedge_distance(self, contour_points):
+        min_distance = []
+        contours_p=[]
+        angles=[]
+        wells_num = self.wells_num
+        points = self.position
+        # 定义待计算距离的点
+        for i in range(wells_num):
+            point = np.array([points[i][0], points[i][1]])
+            # 计算点到等高线上所有点之间的距离
+            distances = cdist(point.reshape(1, -1), contour_points)
+            # 取距离的最小值
+            min_distance.append(distances.min())
+            # 记录最短距离对应的点
+            for ii in range(distances.size):
+                if distances[0][ii] == min_distance[-1]:
+                    contours_p.append(contour_points[ii])
+            # 计算角度（y轴为正北方向）
+            direct = contours_p[-1] - point
+            if direct[0] < 0:
+                angles.append(360-np.arccos(np.dot(direct, np.array(([0, 1]))) / np.linalg.norm(
+                    direct)) / np.pi * 180)
+            else:
+                angles.append(np.arccos(np.dot(direct, np.array(([0, 1]))) / np.linalg.norm(
+                   direct)) / np.pi * 180)
+
+        self.min_distance = min_distance
+        self.welltoedge_points = contours_p
+        self.angle = angles

data.pos

@@ -1,113 +0,0 @@
-112
--45.9	-71.2	1009.9	10.384
--74.3	135.3	1006.9	65.182
-4.1	-38.5	1007.9	96.275
--6	148.3	1006.9	254.818
-26.9	-5.9	1005.9	353.900
--80.9	-10.8	1006.9	400.117
--12.7	-127.7	1006.9	554.83
-66.9	-31.1	1009.9	837.881
--28.1	-39.8	1006.9	1031.90
--32.8	20.5	1006.9	1281.306
-36.5	-25.1	1006.9	1411.553
--92.1	13.7	1006.9	1439.940
--79.2	105.5	1011.9	1500.433
-99.7	63.1	1006.9	1542.607
--26.3	3.3	1006.9	1549.297
--63.1	-0.1	1010.9	1685.309
--11.3	4.1	1004.9	1923.693
-34.6	-51.2	1006.9	2083.725
-36	69.5	1001.9	2136.755
-177.9	0.5	1012.9	2311.923
--3.7	-5.8	1003.9	2345.193
--8.1	-9	1004.9	2497.272
--18.1	-5.2	1001.9	2673.628
-109.9	1.4	1006.9	2687.248
-137.8	-41.5	1006.9	2729.813
-44	-0.5	1008.9	2908.834
--5.2	-32.3	1006.9	2913.675
-198.3	60.8	1006.9	3084.214
-11.1	-91.6	1006.9	3298.919
--4.9	4.9	1013.9	3523.955
-19.6	-35.7	1008.9	3695.617
--37.4	-26.9	1008.9	3916.784
-137.6	-42.9	1008.9	3938.952
-7.1	-10.1	1006.9	4063.108
-80.6	-103.8	1006.9	4107.944
-8.9	-20.9	1006.9	4183.385
--44	-6	1007.9	4310.811
--50.1	28.4	1009.9	4491.107
-104	97.2	1001.9	4715.866
--60.3	-41.4	1006.9	4772.88
-61.3	58.9	1006.9	5042.962
--121.1	-82.8	1006.9	5181.381
-31.5	-22.7	1002.9	5373.757
--41.9	170	1006.9	5472.766
--7.3	5.2	1006.9	5521.58
-82.8	102.9	1011.9	5636.275
-154.7	106.1	1011.9	5756.394
--37.8	18.5	998.9	5880.473
--151.5	-1.2	1005.9	5907.330
-10.2	4.8	1007.9	6024.836
-80.3	26.1	1002.9	6050.715
--144.7	-101.9	1004.9	6163.211
-9.1	-57.8	1006.9	6404.898
--122.7	-22.3	1011.9	6442.493
-8	2.4	1007.9	6652.171
--182.8	-0.4	1004.9	6935.490
-25	48.1	1006.9	7113.943
--93.6	116.2	1006.9	7237.796
--110.2	-14	1006.9	7414.765
--101.6	-19.4	1014.9	7642.493
--76.8	-12.3	1007.9	7755.607
-1.6	-26.1	1008.9	7814.322
--201.5	1.2	1006.9	7915.129
-37.5	63.5	1004.9	8003.43
-21.2	-173.7	1006.9	8089.478
--5.5	143.1	1004.9	8316.296
--67.6	-52.5	1007.9	8394.665
--156.4	15.6	1010.9	8604.577
--89.1	31.6	1007.9	8730.251
--34.6	-29.8	1006.9	8874.838
-11.5	-131.3	1008.9	8938.423
-10.2	4.9	1004.9	8958.814
-9.2	-46.1	1006.9	9135.222
-95.2	171	1010.9	9267.394
-19.3	50.3	1010.9	9344.557
-127.7	-61.9	1010.9	9574.948
-7.5	-96.9	1005.9	9668.554
-6.1	-74.5	1008.9	9855.509
--148.6	22.3	1009.9	9903.75
-39.2	103.1	1010.9	10066.866
--80.4	48	1006.9	10208.58
-157.1	101.1	1006.9	10490.953
--92	30.2	1007.9	10499.380
-111.1	73.2	1009.9	10643.279
-1.4	-29.7	1006.9	10690.866
-9.7	-141.4	1007.9	10804.785
--0.4	2.5	1003.9	11081.846
--8.9	-144.1	1000.9	11233.580
--92.8	-26.4	1009.9	11419.149
--35.8	38.4	1006.9	11657.103
-62.8	149.6	1006.9	11853.628
-40.7	73.8	1009.9	11895.399
--38.8	-56.2	1004.9	12158.102
-69.3	-101.4	1004.9	12196.795
--7.4	-4.4	1000.9	12254.790
--176.5	-81.9	1001.9	12306.909
--34.5	-42.2	1008.9	12375.591
--2.5	3.9	1010.9	12391.64
--2.5	-1	1008.9	12561.584
--128.9	-34.1	1006.9	12669.326
-83.6	52.6	1001.9	12799.414
--48.4	28.4	1005.9	13009.623
--55.2	20.7	1002.9	13277.377
-2	-8.8	1010.9	13432.271
--63.7	62.3	1006.9	13496.217
-29.3	29.6	1007.9	13550.730
-26	-0.2	1009.9	13572.226
-108.2	104.8	1006.9	13675.451
--34.5	129	1006.9	14009.216
-113.9	133.5	1006.9	14096.519
--32.7	-58.4	1006.9	14356.918
-1	45.2	1003.9	14454.743

data1.pos

@@ -1,114 +0,0 @@
-112
--45.9	-71.2	1009.9	10.384
--74.3	135.3	1006.9	65.182
-4.1	-38.5	1007.9	96.275
--6	148.3	1006.9	254.818
-26.9	-5.9	1005.9	353.900
--80.9	-10.8	1006.9	400.117
--12.7	-127.7	1006.9	554.83
-66.9	-31.1	1009.9	837.881
--28.1	-39.8	1006.9	1031.90
--32.8	20.5	1006.9	1281.306
-36.5	-25.1	1006.9	1411.553
--92.1	13.7	1006.9	1439.940
--79.2	105.5	1011.9	1500.433
-99.7	63.1	1006.9	1542.607
--26.3	3.3	1006.9	1549.297
--63.1	-0.1	1010.9	1685.309
--11.3	4.1	1004.9	1923.693
-34.6	-51.2	1006.9	2083.725
-36	69.5	1001.9	2136.755
-177.9	0.5	1012.9	2311.923
--3.7	-5.8	1003.9	2345.193
--8.1	-9	1004.9	2497.272
--18.1	-5.2	1001.9	2673.628
-109.9	1.4	1006.9	2687.248
-137.8	-41.5	1006.9	2729.813
-44	-0.5	1008.9	2908.834
--5.2	-32.3	1006.9	2913.675
-198.3	60.8	1006.9	3084.214
-11.1	-91.6	1006.9	3298.919
--4.9	4.9	1013.9	3523.955
-19.6	-35.7	1008.9	3695.617
--37.4	-26.9	1008.9	3916.784
-137.6	-42.9	1008.9	3938.952
-7.1	-10.1	1006.9	4063.108
-80.6	-103.8	1006.9	4107.944
-8.9	-20.9	1006.9	4183.385
--44	-6	1007.9	4310.811
--50.1	28.4	1009.9	4491.107
-104	97.2	1001.9	4715.866
--60.3	-41.4	1006.9	4772.88
-61.3	58.9	1006.9	5042.962
--121.1	-82.8	1006.9	5181.381
-31.5	-22.7	1002.9	5373.757
--41.9	170	1006.9	5472.766
--7.3	5.2	1006.9	5521.58
-82.8	102.9	1011.9	5636.275
-154.7	106.1	1011.9	5756.394
--37.8	18.5	998.9	5880.473
--151.5	-1.2	1005.9	5907.330
-10.2	4.8	1007.9	6024.836
-80.3	26.1	1002.9	6050.715
--144.7	-101.9	1004.9	6163.211
-9.1	-57.8	1006.9	6404.898
--122.7	-22.3	1011.9	6442.493
-8	2.4	1007.9	6652.171
--182.8	-0.4	1004.9	6935.490
-25	48.1	1006.9	7113.943
--93.6	116.2	1006.9	7237.796
--110.2	-14	1006.9	7414.765
--101.6	-19.4	1014.9	7642.493
--76.8	-12.3	1007.9	7755.607
-1.6	-26.1	1008.9	7814.322
--201.5	1.2	1006.9	7915.129
-47.5	67.5	1001.9	8009.43
-21.3	-173.7	1006.9	8089.478
--1.5	143.1	1004.9	8616.296
--6.6	-52.5	1027.9	8394.665
--16.4	15.6	1310.9	8694.577
--89.1	31.6	1007.9	8730.251
--34.6	-29.8	1006.9	8874.838
-11.5	-131.3	1008.9	8938.423
-10.2	4.9	1004.9	8958.814
-9.2	-46.1	1006.9	9135.222
-95.2	171	1010.9	9267.394
-19.3	50.3	1010.9	9344.557
-127.7	-61.9	1010.9	9574.948
-7.5	-96.9	1005.9	9668.554
-6.1	-74.5	1008.9	9855.509
--148.6	22.3	1009.9	9903.75
-39.2	103.1	1010.9	10066.866
--80.4	48	1006.9	10208.58
-157.1	101.1	1006.9	10490.953
--92	30.2	1007.9	10499.380
-111.1	73.2	1009.9	10643.279
-1.4	-29.7	1006.9	10690.866
-9.7	-141.4	1007.9	10804.785
--0.4	2.5	1003.9	11081.846
--8.9	-144.1	1000.9	11233.580
--92.8	-26.4	1009.9	11419.149
--35.8	38.4	1006.9	11657.103
-62.8	149.6	1006.9	11853.628
-40.7	73.8	1009.9	11895.399
--38.8	-56.2	1004.9	12158.102
-69.3	-101.4	1004.9	12196.795
--7.4	-4.4	1000.9	12254.790
--176.5	-81.9	1001.9	12306.909
--34.5	-42.2	1008.9	12375.591
--2.5	3.9	1010.9	12391.64
--2.5	-1	1008.9	12561.584
--128.9	-34.1	1006.9	12669.326
-83.6	52.6	1001.9	12799.414
--48.4	28.4	1005.9	13009.623
--55.2	20.7	1002.9	13277.377
-2	-8.8	1010.9	13432.271
--63.7	62.3	1006.9	13496.217
-29.3	29.6	1007.9	13550.730
-26	-0.2	1009.9	13572.226
-108.2	104.8	1006.9	13675.451
--34.5	129	1006.9	14009.216
-113.9	133.5	1006.9	14096.519
--32.7	-58.4	1006.9	14356.918
-1	45.2	1003.9	14454.743
--145.3	32.2	1008.9	14323.789

test2.py

@@ -0,0 +1,131 @@
+import sys
+from PySide6.QtWidgets import QApplication, QMainWindow, QGraphicsView
+from PySide6.QtUiTools import QUiLoader
+from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
+from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar
+from matplotlib.figure import Figure
+import matplotlib.pyplot as plt
+from PySide6.QtWidgets import QVBoxLayout
+import CREAT
+import numpy as np
+import matplotlib as mpl
+
+
+class MainWindow(QMainWindow):
+    def __init__(self):
+        super().__init__()
+        self.toolbar = None
+        self.canvas = None
+        # 加载UI文件
+        self.ui = QUiLoader().load('QT/PLT2.ui')
+        # 更新图窗
+        self.ui.graphicsView.repaint()
+        self.ui.graphicsView.update()
+        self.graphics_layout = QVBoxLayout(self.ui.graphicsView)
+        # 绘制Matplotlib图形
+        self.ui.pushButton_4.clicked.connect(lambda: self.plot_density())
+
+    def plot_density(self):
+        fig, ax = self.scene_fig()
+        data_name = self.ui.lineEdit.text().split(',')
+        level_nums = self.ui.spinBox_2.value()
+        gWeight = self.ui.spinBox.value()
+        data = CREAT.create()
+        zmin = 1
+        zmax = 0
+        for i in range(len(data_name)):
+            data.data_pre(data_name[i])
+            data.contours_pre(level_nums, gWeight)
+
+            """画出密度等高线"""
+            f = data.f
+            x_min, x_max = data.x_range[0], data.x_range[1]
+            y_min, y_max = data.y_range[0], data.y_range[1]
+            levels = data.levels
+
+            xx, yy = np.mgrid[x_min:x_max:200j, y_min:y_max:200j]
+            # 填充等高线图中间的区域
+            cmap = mpl.colormaps.get_cmap('jet')
+            colors = cmap(np.linspace(0, 1, level_nums))
+            level = [levels[0], levels[-1]]
+            ff = ax.contourf(xx, yy, f, levels=level, colors=colors[level_nums - i - 1:level_nums - i], alpha=1,
+                             zorder=len(data_name) - i)
+            zmin = min(zmin, ff.zmin)
+            zmax = max(zmax, ff.zmax)
+        ax.set_xlabel('X')
+        ax.set_ylabel('Y')
+        ax.set_title('Density Distribution')
+
+        # 生成colorbar
+        sm = mpl.cm.ScalarMappable(cmap=cmap, norm=mpl.colors.Normalize(vmin=zmin, vmax=zmax))
+        sm.set_array([])
+        fig.colorbar(sm, ax=ax)
+
+        wells_name = self.ui.lineEdit_4.text()
+        if wells_name == '':
+            self.canvas_adjust(fig)
+        else:
+            wells = CREAT.well_to_edge()
+            wells.wells_name_and_position(wells_name)
+            wells.welltoedge_distance(data.contours)
+
+            """画井位信息"""
+            typee = wells.type
+            points = wells.position
+            namee = wells.name
+            min_distance = wells.min_distance
+            contours_p = wells.welltoedge_points
+            for i in range(len(points)):
+                if typee[i][0] == 0:
+                    ax.scatter(points[i][0], points[i][1], marker='o', edgecolors='black', facecolors='none', s=100)
+                    ax.scatter(points[i][0], points[i][1], marker='o', edgecolors='black', facecolors='none', s=50,
+                               linewidths=1)
+                    ax.scatter(points[i][0], points[i][1], marker='o', edgecolors='black', facecolors='none', s=30)
+                    ax.text(points[i][0] + min_distance[i] / 20, points[i][1] - min_distance[i] / 20, f'{namee[i][0]}',
+                            fontdict={'size': '10', 'color': 'b'}, zorder=len(data_name) + 2)  # 井名信息
+                else:
+
+                    ax.scatter(points[i][0], points[i][1], marker='o', edgecolors='black', facecolors='black', s=100, zorder=len(data_name)+1)
+                    ax.text(points[i][0] + min_distance[i] / 20, points[i][1] - min_distance[i] / 20, f'{namee[i][0]}',
+                            fontdict={'size': '10', 'color': 'b'}, zorder=len(data_name) + 2)  # 井名信息
+                    continue
+                # 绘制油井边缘最短距离点的箭头并标出距离
+                ax.quiver(points[i][0], points[i][1], contours_p[i][0] - points[i][0], contours_p[i][1] - points[i][1],
+                          angles='xy', scale=1.03,
+                          scale_units='xy', width=0.002, zorder=len(data_name)+1)  # 绘制箭头
+                ax.text(points[i][0] * 1 / 9 + contours_p[i][0] * 8 / 9 + min_distance[i] / 20,
+                        points[i][1] * 1 / 9 + contours_p[i][1] * 8 / 9 - min_distance[i] / 20, f'{round(min_distance[i], 2)}',
+                        fontdict={'size': '10', 'color': 'g'})  # 标出距离
+                ax.text(points[i][0] * 1 / 2 + contours_p[i][0] * 1 / 2 + min_distance[i] / 20,
+                        points[i][1] * 1 / 2 + contours_p[i][1] * 1 / 2 - min_distance[i] / 20,
+                        r'$\theta$=' f'{round(wells.angle[i], 2)}', fontdict={'size': '10', 'color': 'y'})  # 标出角度
+            self.canvas_adjust(fig)
+
+    def scene_fig(self):
+        fig = Figure()
+        # 在Figure对象中添加子图
+        ax = fig.add_subplot(111)
+        return fig, ax
+
+    def canvas_adjust(self, fig):
+        if self.canvas is not None:
+            # 从布局中删除旧的 canvas 和 toolbar
+            item = self.graphics_layout.takeAt(0)
+            while item:
+                widget = item.widget()
+                if widget:
+                    widget.setParent(None)
+                item = self.graphics_layout.takeAt(0)
+        self.graphics_layout.removeWidget(self.canvas)
+        self.canvas = FigureCanvas(fig)
+        self.toolbar = NavigationToolbar(self.canvas, self.ui.graphicsView)
+        self.toolbar.setParent(self.canvas)
+        self.graphics_layout.addWidget(self.canvas)
+        self.adjustSize()
+
+
+if __name__ == '__main__':
+    app = QApplication([])
+    stats = MainWindow()
+    stats.ui.show()
+    app.exec()

well.txt

@@ -1,6 +0,0 @@
-0 	0 	1	L40-5
--184 	-243 	0	L40-4
--258 	178 	0	L39-5
-188 	-169 	0	L41-5
-242 	321 	0	L40-6
-446 	180 	0	L41-6