SD主机控制器简化规范4.20版解析

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"PartA2_SD Host_Controller_Simplified_Specification_Ver4.20.pdf" 是关于SDIO协议的详细规格文档,该文档是SD Host Controller简化的规范,版本4.20,由SD Association的技术委员会在2018年7月25日发布。这个规范覆盖了对SD主机控制器的最新更新,包括UHS-I I的支持、共享总线支持、ADMA3(Advanced DMA Mode 3)支持以及64位系统寻址支持。 SDIO(Secure Digital Input/Output)协议是一种用于SD卡和主机之间传输数据和控制信号的接口标准。它不仅提供了数据传输功能,还允许设备通过SD卡接口进行输入输出操作,例如Wi-Fi模块、GPS接收器或蓝牙模块等。SDIO协议扩展了传统的SD卡功能,使得单一的物理接口可以处理多种不同的I/O功能。 在SD Host Controller Simplified Specification Version 4.20中,有以下几个关键点: 1. **UHS-I (Ultra High Speed Phase 1)**:这是SD卡的一个高速模式,旨在提高数据传输速率。UHS-I支持更高的总线速度,如104MB/s(UHS-1 Class 1)和312MB/s(UHS-1 Class 3),以满足高清视频和其他大数据量应用的需求。 2. **Shared Bus Support**:此特性允许多个SD或SDIO设备共享同一总线,从而节省系统资源并简化硬件设计。通过时分复用技术,可以在不同设备间切换,实现多设备同时通信。 3. **ADMA3 (Advanced DMA Mode 3)**:高级直接存储访问模式3是SD主机控制器的一种增强数据传输方式,它允许更高效的数据处理,减少了CPU的参与,提高了数据吞吐量和系统的整体性能。 4. **64-bit System Addressing Support**:这一更新意味着SD主机控制器现在能够支持64位地址空间,显著扩大了可寻址内存,对于处理大量数据的应用尤其有利,如高清视频录制和播放。 5. **Revised Disclaimers**:2018年的修订版可能包含了一些法律免责声明的更新,确保了规范的使用符合SD Association的规定和版权要求。 SD Host Controller Simplified Specification Version 4.20是SDIO设备开发者和硬件工程师的重要参考资料,它详细规定了SD主机控制器如何与SDIO设备交互,以实现高速、高效且灵活的数据传输和设备控制。这个规范的更新反映了SD技术的持续演进,以适应不断增长的存储和I/O需求。

优化这段代码:def calTravelCost(route_list,model): timetable_list=[] distance_of_routes=0 time_of_routes=0 obj=0 for route in route_list: timetable=[] vehicle=model.vehicle_dict[route[0]] travel_distance=0 travel_time=0 v_type = route[0] free_speed=vehicle.free_speed fixed_cost=vehicle.fixed_cost variable_cost=vehicle.variable_cost for i in range(len(route)): if i == 0: next_node_id=route[i+1] travel_time_between_nodes=model.distance_matrix[v_type,next_node_id]/free_speed departure=max(0,model.demand_dict[next_node_id].start_time-travel_time_between_nodes) timetable.append((int(departure),int(departure))) elif 1<= i <= len(route)-2: last_node_id=route[i-1] current_node_id=route[i] current_node = model.demand_dict[current_node_id] travel_time_between_nodes=model.distance_matrix[last_node_id,current_node_id]/free_speed arrival=max(timetable[-1][1]+travel_time_between_nodes,current_node.start_time) departure=arrival+current_node.service_time timetable.append((int(arrival),int(departure))) travel_distance += model.distance_matrix[last_node_id, current_node_id] travel_time += model.distance_matrix[last_node_id, current_node_id]/free_speed+\ + max(current_node.start_time - arrival, 0) else: last_node_id = route[i - 1] travel_time_between_nodes = model.distance_matrix[last_node_id,v_type]/free_speed departure = timetable[-1][1]+travel_time_between_nodes timetable.append((int(departure),int(departure))) travel_distance += model.distance_matrix[last_node_id,v_type] travel_time += model.distance_matrix[last_node_id,v_type]/free_speed distance_of_routes+=travel_distance time_of_routes+=travel_time if model.opt_type==0: obj+=fixed_cost+travel_distance*variable_cost else: obj += fixed_cost + travel_time *variable_cost timetable_list.append(timetable) return timetable_list,time_of_routes,distance_of_routes,obj

2023-06-11 上传

降低这段代码的重复率:def calTravelCost(route_list,model): timetable_list=[] distance_of_routes=0 time_of_routes=0 obj=0 for route in route_list: timetable=[] vehicle=model.vehicle_dict[route[0]] travel_distance=0 travel_time=0 v_type = route[0] free_speed=vehicle.free_speed fixed_cost=vehicle.fixed_cost variable_cost=vehicle.variable_cost for i in range(len(route)): if i == 0: next_node_id=route[i+1] travel_time_between_nodes=model.distance_matrix[v_type,next_node_id]/free_speed departure=max(0,model.demand_dict[next_node_id].start_time-travel_time_between_nodes) timetable.append((int(departure),int(departure))) elif 1<= i <= len(route)-2: last_node_id=route[i-1] current_node_id=route[i] current_node = model.demand_dict[current_node_id] travel_time_between_nodes=model.distance_matrix[last_node_id,current_node_id]/free_speed arrival=max(timetable[-1][1]+travel_time_between_nodes,current_node.start_time) departure=arrival+current_node.service_time timetable.append((int(arrival),int(departure))) travel_distance += model.distance_matrix[last_node_id, current_node_id] travel_time += model.distance_matrix[last_node_id, current_node_id]/free_speed+\ + max(current_node.start_time - arrival, 0) else: last_node_id = route[i - 1] travel_time_between_nodes = model.distance_matrix[last_node_id,v_type]/free_speed departure = timetable[-1][1]+travel_time_between_nodes timetable.append((int(departure),int(departure))) travel_distance += model.distance_matrix[last_node_id,v_type] travel_time += model.distance_matrix[last_node_id,v_type]/free_speed distance_of_routes+=travel_distance time_of_routes+=travel_time if model.opt_type==0: obj+=fixed_cost+travel_distance*variable_cost else: obj += fixed_cost + travel_time *variable_cost timetable_list.append(timetable) return timetable_list,time_of_routes,distance_of_routes,obj

2023-06-10 上传

优化代码,加背景图import tkinter as tk import numpy as np def change_label(): button.destroy() label.config(text="请输入您的身高体重以及目标体重:") height_label.place(relx=0.5, rely=0.4, anchor="center") height_entry.place(relx=0.5, rely=0.45, anchor="center") weight_label.place(relx=0.5, rely=0.5, anchor="center") weight_entry.place(relx=0.5, rely=0.55, anchor="center") target_label.place(relx=0.5, rely=0.6, anchor="center") target_entry.place(relx=0.5, rely=0.65, anchor="center") submit_button.place(relx=0.5, rely=0.8, anchor="center") def show_buttons(): calculate_low_carb() calculate_medium_carb() calculate_high_carb() label.config(text="您的营养素分配如下:") label.place(relx=0.5, rely=0.2, anchor="center") height_label.destroy() height_entry.destroy() weight_label.destroy() weight_entry.destroy() target_label.destroy() target_entry.destroy() submit_button.destroy() submit_button_1.place(relx=0.5, rely=0.8, anchor="center") def calculate_low_carb(): global low_protein_intake, low_carb_intake, low_fat_intake height = float(height_entry.get()) weight = float(weight_entry.get()) target_weight = float(target_entry.get()) # 根据BMI计算蛋白质摄入量 bmi = weight / (height / 100)**2 if bmi >= 27: low_protein_intake = weight elif bmi >= 24 and bmi < 27: low_protein_intake = weight * 1.5 else: low_protein_intake = weight * 2 # 计算低碳日的碳水摄入量和脂肪摄入量 low_carb_intake = weight low_fat_intake = weight low_carb_label = tk.Label(root, text = "您低碳日的碳水摄入量为{:.1f}克,蛋白质摄入量为{:.1f}克,脂肪摄入量为{:.1f}克".format(low_carb_intake, low_protein_intake, low_fat_intake), font=("Arial", 18)) low_carb_label.place(relx=0.5, rely=0.4, anchor="center") def calculate_medium_carb(): global medium_protein_intake, medium_carb_intake, medium_fat_intake height = float(height_entry.get()) weight = float(weight_entry.get()) target_weight = float(target_entry.get()) # 根据BMI计算蛋白质摄入量 bmi = weight / (height / 100)**2 if bmi >= 27: medium_protein_intake = weight elif bmi >= 24 and bmi < 27: medium_protein_intake = weight * 1.5 else: medium_protein_intake = weight * 2 # 计算中碳日的碳水摄入量和脂肪摄入量 medium_carb_intake = weight * 2 medium_fat_intake = weight * 0.5 medium_carb_label = tk.Label(root, text = "您中碳日的碳水摄入量为{:.1f}克,蛋白质摄入量为{:.1f}克,脂肪摄入量为{:.1f}克".format(medium_carb_intake, medium_protein_intake, medium_fat_intake), font=("Arial", 18)) medium_carb_label.place(relx=0.5, rely=0.5, anchor="center")

2023-05-31 上传