90 lines
4.2 KiB
Python
90 lines
4.2 KiB
Python
import random
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from optimizer_common import *
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def load_data(filename: str, load_cp_data=True, load_feeder_data=True, component_register=False):
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# 锁定随机数种子
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random.seed(0)
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# 读取PCB数据
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filename = 'data/' + filename
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pcb_data = pd.DataFrame(pd.read_csv(filepath_or_buffer=filename, sep='\t', header=None))
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if len(pcb_data.columns) <= 17:
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step_col = ["ref", "x", "y", "z", "r", "part", "desc", "fdr", "nz", "hd", "cs", "cy", "sk", "bl", "ar",
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"pl", "lv"]
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elif len(pcb_data.columns) <= 18:
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step_col = ["ref", "x", "y", "z", "r", "part", "desc", "fdr", "nz", "hd", "cs", "cy", "sk", "bl", "ar", "fid",
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"pl", "lv"]
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else:
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step_col = ["ref", "x", "y", "z", "r", "part", "desc", "fdr", "nz", "hd", "cs", "cy", "sk", "bl", "ar", "fid",
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"", "pl", "lv"]
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pcb_data.columns = step_col
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pcb_data = pcb_data.dropna(axis=1)
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# 坐标系处理
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# pcb_data = pcb_data.sort_values(by = ['x', 'y'], ascending = True)
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# pcb_data["x"] = pcb_data["x"].apply(lambda x: -x)
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# 注册元件检查
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component_data = None
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if load_cp_data:
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part_feeder_assign = defaultdict(set)
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part_col = ["part", "desc", "fdr", "nz", 'camera', 'group', 'feeder-limit']
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try:
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component_data = pd.DataFrame(pd.read_csv(filepath_or_buffer='component.txt', sep='\t', header=None), columns=part_col)
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except:
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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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slot = data['fdr'].split(' ')[0]
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if part not in component_data['part'].values:
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if not component_register:
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raise Exception("unregistered component: " + component_data['part'].values)
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else:
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component_data = pd.concat([component_data,
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pd.DataFrame([part, '', 'SM8', nozzle, '飞行相机1', 'CHIP-Rect', 0],
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index=part_col).T], ignore_index=True)
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# warning_info = 'register component ' + part + ' with default feeder type'
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# warnings.warn(warning_info, UserWarning)
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part_index = component_data[component_data['part'] == part].index.tolist()[0]
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part_feeder_assign[part].add(slot)
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if nozzle != 'A' and component_data.loc[part_index]['nz'] != nozzle:
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warning_info = 'the nozzle type of component ' + part + ' is not consistent with the pcb data'
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warnings.warn(warning_info, UserWarning)
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for idx, data in component_data.iterrows():
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if data['fdr'][0:3] == 'SME': # 电动供料器和气动供料器参数一致
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component_data.at[idx, 'fdr'] = data['fdr'][0:2] + data['fdr'][3:]
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for part, slots in part_feeder_assign.items():
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part_index = component_data[component_data['part'] == part].index.tolist()[0]
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component_data.at[part_index, 'feeder-limit'] = max(len(slots), component_data.at[part_index, 'feeder-limit'])
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# 读取供料器基座数据
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feeder_data = pd.DataFrame(columns=range(3))
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if load_feeder_data:
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for data in pcb_data.iterrows():
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fdr = data[1]['fdr']
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slot, part = fdr.split(' ')
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if slot[0] != 'F' and slot[0] != 'R':
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continue
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slot = int(slot[1:]) if slot[0] == 'F' else int(slot[1:]) + max_slot_index // 2
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feeder_data = pd.concat([feeder_data, pd.DataFrame([slot, part, 1]).T])
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feeder_data.columns = ['slot', 'part', 'arg'] # arg表示是否为预分配，不表示分配数目
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feeder_data.drop_duplicates(subset='slot', inplace=True, ignore_index=True)
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# 随机移除部分已安装的供料器
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if load_feeder_data == 2:
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drop_index = random.sample(list(range(len(feeder_data))), len(feeder_data) // 2)
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feeder_data.drop(index=drop_index, inplace=True)
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feeder_data.sort_values(by='slot', ascending=True, inplace=True, ignore_index=True)
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else:
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feeder_data.columns = ['slot', 'part', 'arg'] # 同上
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return pcb_data, component_data, feeder_data
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