调整工程架构，增补了几种算法，初步添加神经网路训练拟合代码
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generator.py
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156
generator.py
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import pandas as pd
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from base_optimizer.optimizer_common import *
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class DataMgr:
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def __init__(self):
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self.min_placement_points = 100
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self.max_placement_points = 800
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self.max_component_types = 50
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self.default_feeder_limit = 1
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self.nozzle_type_list = ['CN065', 'CN140', 'CN220', 'CN040']
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self.x_range = [50, 100, 150, 200, 300, 400, 500]
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self.y_range = [50, 100, 150, 200, 300, 400, 500]
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self.counter = 0
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self.pre_file = None
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def generator(self):
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boundary = [random.choice(self.x_range), random.choice(self.y_range)]
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total_points = random.randint(self.min_placement_points, self.max_placement_points)
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# determine the nozzle type of component
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component_list = defaultdict(str)
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for cp_idx in range(min(random.randint(1, self.max_component_types), total_points)):
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component_list['C' + str(cp_idx)] = random.choice(self.nozzle_type_list)
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step_col = ["ref", "x", "y", "z", "r", "part", "desc", "fdr", "nz", "hd", "cs", "cy", "sk", "bl", "ar", "pl", "lv"]
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pcb_data = pd.DataFrame(columns=step_col)
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for idx in range(total_points):
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part = random.choice(list(component_list.keys()))
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nozzle = component_list[part]
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pos_x, pos_y = np.random.uniform(0, boundary[0]), np.random.uniform(0, boundary[1])
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pcb_data = pd.concat([pcb_data, pd.DataFrame([['R' + str(idx), -pos_x, pos_y,
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0.000, 0.000, part, '', 'A', '1-0 ' + nozzle, 1, 1, 1, 0,
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1, 1, 1, 'L0']], columns=pcb_data.columns)], ignore_index=True)
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part_col = ["part", "desc", "fdr", "nz", 'camera', 'group', 'feeder-limit', 'points']
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component_data = pd.DataFrame(columns=part_col)
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for _, data in pcb_data.iterrows():
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part, nozzle = data.part, data.nz.split(' ')[1]
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if part not in component_data['part'].values:
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component_data = pd.concat([component_data, pd.DataFrame(
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[part, '', 'SM8', nozzle, '飞行相机1', 'CHIP-Rect', self.default_feeder_limit, 0], index=part_col).T],
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ignore_index=True)
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part_index = component_data[component_data['part'] == part].index.tolist()[0]
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component_data.loc[part_index, 'points'] += 1
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self.counter += 1
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return pcb_data, component_data
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def recorder(self, file_path, info: OptInfo, pcb_data, component_data):
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lineinfo = '{:.6f}'.format(info.placement_time) + '\t' + str(info.cycle_counter) + '\t' + str(
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info.nozzle_change_counter) + '\t' + str(info.pickup_counter) + '\t' + '{:.3f}'.format(
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info.pickup_movement) + '\t' + '{:.3f}'.format(info.placement_movement)
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lineinfo += '\t' + '{:.3f}'.format(pcb_data['x'].max() - pcb_data['x'].min()) + '\t' + '{:.3f}'.format(
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pcb_data['y'].max() - pcb_data['y'].min())
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point_counter, component_counter = 0, 0
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nozzle_type = set()
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for _, data in component_data.iterrows():
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if data.points == 0:
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continue
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nozzle_type.add(data.nz)
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point_counter += data.points
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component_counter += 1
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lineinfo += '\t' + str(point_counter) + '\t' + str(component_counter) + '\t' + str(len(nozzle_type))
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for _, data in component_data.iterrows():
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lineinfo += '\t' + data.part + '\t' + data.nz + '\t' + str(data.points)
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lineinfo += '\n'
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with open(file_path, 'a') as f:
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f.write(lineinfo)
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f.close()
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def saver(self, file_path: str, pcb_data):
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lineinfo = ''
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for _, data in pcb_data.iterrows():
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lineinfo += '\t' + '{:.3f}'.format(data.x) + '\t' + '{:.3f}'.format(
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data.y) + '\t0.000\t0.000\t' + data.part + '\t\tA\t' + data.nz + '\t1\t1\t1\t1\t1\t1\t1\tN\tL0\n'
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pos = file_path.find('.')
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file_path = file_path[:pos] + '-' + str(self.counter) + file_path[pos:]
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with open(file_path, 'w') as f:
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f.write(lineinfo)
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f.close()
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self.pre_file = file_path
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def remover(self):
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if self.pre_file is not None:
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os.remove(self.pre_file)
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self.pre_file = None
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def encode(self, cp_points: defaultdict[str], cp_nozzle: defaultdict[int], width, height):
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cp2nz = defaultdict(int)
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for idx, nozzle in enumerate(self.nozzle_type_list):
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cp2nz[nozzle] = idx
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total_points = sum(points for points in cp_points.values())
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total_component_types, total_nozzle_types = len(cp_points.keys()), len(set(cp_nozzle.values()))
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data = [total_points, total_component_types, total_nozzle_types]
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data.extend([width, height])
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for component, points in cp_points.items():
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nozzle = cp_nozzle[component]
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data_slice = [0 for _ in range(len(self.nozzle_type_list))]
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data_slice[cp2nz[nozzle]] = points
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data.extend(data_slice)
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for _ in range(self.max_component_types - total_component_types):
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data.extend([0 for _ in range(len(self.nozzle_type_list))])
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return data
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def loader(self, file_path):
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train_data, time_data = [], []
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cycle_data, nozzle_change_data, pickup_data, movement_data, point_data = [], [], [], [], []
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pcb_width, pcb_height = [], []
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with open(file_path, 'r') as file:
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line = file.readline()
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while line:
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items = line.split('\t')
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total_points, total_component_types = int(items[8]), int(items[9])
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cycle_data.append(float(items[1]))
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nozzle_change_data.append(float(items[2]))
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pickup_data.append(float(items[3]))
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movement_data.append(float(items[4]))
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point_data.append(total_points)
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# assembly time data
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time_data.append(float(items[0]))
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cp_points, cp_nozzle = defaultdict(int), defaultdict(str)
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for cp_counter in range(total_component_types):
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component_type, nozzle_type = items[11 + cp_counter * 3], items[12 + cp_counter * 3]
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points = int(items[13 + cp_counter * 3])
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cp_points[component_type], cp_nozzle[component_type] = points, nozzle_type
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train_data.append(self.encode(cp_points, cp_nozzle, float(items[6]), float(items[7])))
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line = file.readline()
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return train_data, time_data, cycle_data, nozzle_change_data, pickup_data, movement_data, point_data
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def get_feature(self):
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return self.max_component_types * len(self.nozzle_type_list) + 5
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