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1.快速订单新增特征识别路径字段

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2.修复销售经理和销售总监看不到快速订单菜单
3.优化系统设置页面，新增特征识别路径展示，去掉重复的业务平台参数配置展示
4.快速订单去掉老版本的特征识别的代码及包，新增最新的特征识别方法
This commit is contained in:
jinling.yang
2024-02-20 17:33:06 +08:00
parent 4379854b89
commit 5646cc492e
11 changed files with 843 additions and 39 deletions
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201
sf_sale/models/preload_datas_functions.py Normal file
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import psycopg2
# import pandas as pd
def load_and_convert_data(table_name, column_names):
connection = None
data = []
try:
# connection = psycopg2.connect(user="odoo",
# password="odoo",
# host="localhost",
# port="5432",
# database="www1")
connection = psycopg2.connect(user="odoo",
password="odoo",
host="120.76.195.146",
port="15432",
database="bfm_dev1")
cursor = connection.cursor()
# Construct the query string using the table name passed in
query = f"SELECT {', '.join(column_names)} FROM {table_name};"
cursor.execute(query)
# Fetch all rows from cursor
data = cursor.fetchall()
except (Exception, psycopg2.Error) as error:
print("Error fetching data from PostgreSQL table", error)
finally:
# Always close database connection after work done
if (connection):
cursor.close()
connection.close()
# Convert the list of tuples to DataFrame
# df = pd.DataFrame(data, columns=column_names)
#
# # Convert all string columns to float
# for col in df.columns:
# if df[col].dtype == 'object':
# df[col] = df[col].astype(float)
return 'df'
def get_suitable_hole_working_hours(df, target_diameter, target_depth):
"""
从钻孔、铰孔数据中获取符合要求的最小工时
"""
# df为输入的数据，target_diameter为目标孔径，target_depth为目标孔深
df_diameter_filtered = df.loc[df['hole_diameter'] >= target_diameter]
if not df_diameter_filtered.empty:
min_diameter = df_diameter_filtered['hole_diameter'].min()
df_depth_filtered = df_diameter_filtered.loc[
(df_diameter_filtered['hole_diameter'] == min_diameter) & (
df_diameter_filtered['hole_depth'] >= target_depth)]
if not df_depth_filtered.empty:
min_depth_row = df_depth_filtered.loc[df_depth_filtered['hole_depth'].idxmin()]
min_working_hours = min_depth_row['working_hours']
return min_working_hours
else:
print("No records found where hole_depth is bigger than the target depth")
return None
else:
print("No records found where hole_diameter is bigger than the target diameter")
return None
def get_suitable_blank_working_hours(df, blank_height, blank_length, blank_width):
"""
从毛坯数据中获取符合要求的最小工时
"""
# df为输入的数据，blank_height为目标毛坯高度，blank_length为目标毛坯长度，blank_width为目标毛坯宽度
df_height_filtered = df.loc[df['blank_height'] >= blank_height]
if not df_height_filtered.empty:
min_height = df_height_filtered['blank_height'].min()
df_length_filtered = df_height_filtered.loc[
(df_height_filtered['blank_height'] == min_height) & (
df_height_filtered['blank_length'] >= blank_length)]
if not df_length_filtered.empty:
min_length_row = df_length_filtered.loc[df_length_filtered['blank_length'].idxmin()]
min_working_hours = min_length_row['working_hours']
return min_working_hours
else:
print("No records found where blank_length is bigger than the target length")
return None
else:
print("No records found where blank_height is bigger than the target height")
return None
def get_suitable_rough_working_hours(df, rough_depth):
"""
从粗加工数据中获取符合要求的最小工时
"""
# df为输入的数据，rough_depth为目标粗加工深度
df_depth_filtered = df.loc[df['rough_depth'] >= rough_depth]
if not df_depth_filtered.empty:
min_depth_row = df_depth_filtered.loc[df_depth_filtered['rough_depth'].idxmin()]
min_working_hours = min_depth_row['working_hours']
return min_working_hours
else:
print("No records found where rough_depth is bigger than the target depth")
return None
def get_suitable_finish_working_hours(df, finish_depth, finish_tool_diameter):
"""
从精加工数据中获取符合要求的最小工时
"""
# df为输入的数据，finish_depth为目标精加工深度，finish_tool_diameter为目标精加工刀具直径
df_depth_filtered = df.loc[df['finish_depth'] >= finish_depth]
if not df_depth_filtered.empty:
min_depth = df_depth_filtered['finish_depth'].min()
df_tool_diameter_filtered = df_depth_filtered.loc[
(df_depth_filtered['finish_depth'] == min_depth) & (
df_depth_filtered['finish_tool_diameter'] >= finish_tool_diameter)]
if not df_tool_diameter_filtered.empty:
min_tool_diameter_row = df_tool_diameter_filtered.loc[
df_tool_diameter_filtered['finish_tool_diameter'].idxmin()]
min_working_hours = min_tool_diameter_row['working_hours']
return min_working_hours
else:
print("No records found where finish_tool_diameter is bigger than the target tool diameter")
return None
else:
print("No records found where finish_depth is bigger than the target depth")
return None
def get_suitable_chamfer_working_hours(df, chamfer_length, chamfer_size):
"""
根据倒角长度获得倒角工时，装夹平面耗时clamping_type_plane和装夹斜面耗时clamping_type_slope
"""
# df为输入的数据，chamfer_length为目标倒角长度，clamping_type_plane为目标装夹平面耗时，clamping_type_slope为目标装夹斜面耗时
df_length_filtered = df.loc[df['chamfer_length'] >= chamfer_length]
df_chamfer_size_filtered = df.loc[df['chamfer_size'] >= chamfer_size]
if not df_length_filtered.empty and not df_chamfer_size_filtered.empty:
min_length_row = df_length_filtered.loc[df_length_filtered['chamfer_length'].idxmin()]
min_chamfer_size_row = df_chamfer_size_filtered.loc[df_chamfer_size_filtered['chamfer_size'].idxmin()]
clamping_time = min_length_row['clamping_time']
clamping_type_plane = min_length_row['clamping_type_plane']
clamping_type_slope = min_length_row['clamping_type_slope']
coefficient = min_chamfer_size_row['coefficient']
return clamping_time, clamping_type_plane, clamping_type_slope, coefficient
else:
print("No records found where chamfer_length is bigger than the target length")
return None
df_hole_duration = load_and_convert_data('hole_duration', ['hole_diameter', 'hole_depth', 'working_hours'])
df_j_hole_duration = load_and_convert_data('j_hole_duration', ['hole_diameter', 'hole_depth', 'working_hours'])
df_chamfer_duration = load_and_convert_data('chamfer_duration',
['chamfer_length', 'clamping_time', 'chamfer_size', 'coefficient',
'clamping_type_plane', 'clamping_type_slope'])
df_blank_duration = load_and_convert_data('blank_duration',
['blank_length', 'blank_width', 'blank_height', 'working_hours'])
df_rough_duration = load_and_convert_data('rough_duration', ['rough_depth', 'working_hours'])
df_finish_duration = load_and_convert_data('finish_duration',
['finish_depth', 'finish_tool_diameter', 'working_hours'])
if __name__ == '__main__':
min_working_hours = get_suitable_hole_working_hours(df_hole_duration, 24, 150)
print('min_working_hours', min_working_hours)
min_j_working_hours = get_suitable_hole_working_hours(df_j_hole_duration, 10, 15)
print('min_j_working_hours', min_j_working_hours)
min_blank_working_hours = get_suitable_blank_working_hours(df_blank_duration, 150, 300, 300)
print('min_blank_working_hours', min_blank_working_hours)
min_rough_working_hours = get_suitable_rough_working_hours(df_rough_duration, 49)
print('min_rough_working_hours', min_rough_working_hours)
min_finish_working_hours = get_suitable_finish_working_hours(df_finish_duration, 0.5, 10)
print('min_finish_working_hours', min_finish_working_hours)
clamping_time, clamping_type_plane, clamping_type_slope, coefficient = get_suitable_chamfer_working_hours(
df_chamfer_duration, 10, 1.5)
print('clamping_time', clamping_time)
print('clamping_type_plane', clamping_type_plane)
print('clamping_type_slope', clamping_type_slope)
print('coefficient', coefficient)