from pandas import ExcelWriter
import numpy as np
import os
import pandas as pd
import xml.etree.ElementTree as et

UCD_trn xml file path

xml_path = r"..\gcam-v5.2\input\extra" # xml file folder
dir_extra = os.listdir(xml_path) # SSP3 uses trn_UCD_SSP3
trn_xml_ls = [file for file in dir_extra if "transportation_UCD_SSP" in file]
trn_xml_path = dict(

zip(    ["ssp" + str(i) for i in [1, 2, 4, 5]],    [os.path.join(xml_path, file) for file in trn_xml_ls],)

)

Car type

tranSubsector_name_ls = [

"Compact Car","Large Car and SUV","Mini Car","Multipurpose Vehicle","Subcompact Car",

]
def get_ene_intensity_xml(path,

                      tranSubsector_name,                       supplysector_name="trn_pass_road_LDV_4W"):xtree = et.parse(path)xroot = xtree.getroot()rows = []for child in xroot:    for region in child:        if region.attrib.get("name") == "China":            for supplysector in region:                if supplysector.attrib.get("name") == supplysector_name:                    for tranSubsector in supplysector:                        if tranSubsector.attrib.get("name") == tranSubsector_name:                            for stubtechnology in tranSubsector:                                if stubtechnology.attrib.get("name") == "FCEV":                                    for period in stubtechnology:                                        for node in period:                                            if node.tag == "minicam-energy-input":                                                for sub_node in node:                                                    if (                                                        sub_node.tag                                                        == "coefficient"                                                    ):                                                        s_region = (                                                                region.attrib.get(                                                                "name"                                                            )                                                        )                                                        s_supplysector = (                                                               supplysector.attrib.get(                                                                "name"                                                            )                                                        )                                                        s_tranSubsector = tranSubsector.attrib.get(                                                            "name"                                                        )                                                        s_stubtechnology = stubtechnology.attrib.get(                                                            "name"                                                        )                                                        s_period = (                                                               period.attrib.get(                                                                "year"                                                            )                                                        )                                                        s_tag = sub_node.tag                                                        s_coefficient = (                                                                float(sub_node.text)                                                            / 1055  # btu/vkm to J/vkm from https://jgcri.github.io/gcam-doc/en_technologies.html                                                        )                                                        rows.append(                                                            dict(                                                                   region=s_region,

supplysector=s_supplysector,
tranSubsector=s_tranSubsector,
stubtechnology=s_stubtechnology,
period=s_period, tag=s_tag,
value=s_coefficient,

                                                            )                                                        )df = pd.DataFrame(rows)return df

def ene_intensity(scenario):

ene_intensity_ls = []for car_type in tranSubsector_name_ls:    ene_intensity = np.array(        get_ene_intensity_xml(scenario, car_type).loc[:, "value"]    )[1:]    ene_intensity_ls.append(ene_intensity)return ene_intensity_ls

columns = range(2000, 2101, 5) #贝宝读取2000到2100年能源强度，步长为五年
df = (

    pd.DataFrame(        ene_intensity(trn_xml_path[key]),        columns=columns,        index=tranSubsector_name_ls,    ))

次要是搞清楚xml文档的数据结构，GCAM交通部门中的构造为
<region>

<supplysector>    <tranSubsector>        <stubtechnology>            <period>                <minicam-energy-input> # 能源强度