己知在线的时间>=90分钟的为发烧级网虫 否则是普通网虫。以下程序中的namelist为网 名和一天内玩网游的时间 (分钟)组成的多个 键值对构成的字典。通过对时间的判断,将字 典中发烧级网虫和普通网虫分离成两个字典, 分别输输出他们的网名和一天内玩网游的时间
时间: 2023-05-15 12:06:31 浏览: 94
以下是可以用来分离发烧级网虫和普通网虫的 Python 代码:
```python
namelist = {
"Alice": 120,
"Bob": 60,
"Charlie": 180,
"David": 30,
"Eve": 90
}
feverish = {}
normal = {}
for name, time in namelist.items():
if time >= 90:
feverish[name] = time
else:
normal[name] = time
print("发烧级网虫:")
for name, time in feverish.items():
print(name, time)
print("普通网虫:")
for name, time in normal.items():
print(name, time)
```
这段代码会将 namelist 中的每个键值对遍历一遍,如果时间大于等于 90 分钟,则将该键值对加入 feverish 字典中,否则加入 normal 字典中。最后分别输出两个字典中的网名和时间。
相关问题
补全程序,完成以下功能。已知在线的时间>=90分钟的为发烧级网虫,否则是普通网虫。以下程序中的namelist为网名和一天内玩网游的时间(分钟)组成的多个键值对构成的字典。通过对时间的判断,将字典中发烧级网虫和普通网虫分离成两个字典,分别输出他们的网名和一天内玩网游的时间。 nameList = {'草肥熊': 65, '黄小丫': 52, '大黄鸭': 102, '胳膊粗': 89, '腿脚细': 90, '水蛇腰': 116, '水桶腰': 53} # 网名和时间字典 noPass = {} # 普通网虫字典初始化 Pass = {} # 发烧级网虫字典初始化 for name, onlineTime in nameList. 【1】 # 遍历名单的键值对 if onlineTime < 【2】 : noPass[_ 【3】 ] = onlineTime # 添加普通网虫到普通字典 else: Pass[name] = 【4】 # 添加发烧级网虫到发烧字典 print('发烧级网虫:') for name, onlineTime in Pass.items(): # 遍历发烧级网虫的键值对 print(name, 【5】 ) print('\n普通网虫:') for name in noPass.keys(): print(name, 【6】 ) # 通过网名输出网名和成绩
timeList1 = {} # 存储发烧级网虫的网名和时间
timeList2 = {} # 存储普通网虫的网名和时间
for name, time in nameList.items():
if time >= 90:
timeList1[name] = time
else:
timeList2[name] = time
print("发烧级网虫:")
for name, time in timeList1.items():
print(name, time)
print("普通网虫:")
for name, time in timeList2.items():
print(name, time)
全球等经纬度投影,分辨率为0.25度,WRF模拟中namelist.wps和namelist.input配置样例
好的,以下是你需要的样例配置:
namelist.wps:
```
&share
wrf_core = 'ARW',
max_dom = 1,
start_date = '2021-11-01_00:00:00',
end_date = '2021-11-02_00:00:00',
interval_seconds = 21600,
io_form_geogrid = 2,
/
&geogrid
parent_id = 1,
parent_grid_ratio = 1,
i_parent_start = 1,
j_parent_start = 1,
e_we = 144,
e_sn = 91,
geog_data_res = '15m',
dx = 0.25,
dy = 0.25,
map_proj = 'latlong',
ref_lat = 0.0,
ref_lon = 90.0,
truelat1 = 33.0,
truelat2 = 45.0,
stand_lon = 90.0,
geog_data_path = '/path/to/geog_data/',
/
```
namelist.input:
```
&time_control
run_days = 1,
run_hours = 0,
run_minutes = 0,
run_seconds = 0,
start_year = 2021,
start_month = 11,
start_day = 01,
start_hour = 00,
start_minute = 00,
start_second = 00,
end_year = 2021,
end_month = 11,
end_day = 02,
end_hour = 00,
end_minute = 00,
end_second = 00,
interval_seconds = 21600,
input_from_file = .true.,
history_interval = 60,
frames_per_outfile = 1,
restart = .false.,
restart_interval = 5000,
io_form_history = 2,
io_form_restart = 2,
io_form_input = 2,
io_form_boundary = 2,
debug_level = 0,
/
&domains
time_step = 180,
max_dom = 1,
s_we = 1,
e_we = 144,
s_sn = 1,
e_sn = 91,
s_vert = 1,
e_vert = 31,
dx = 0.25,
dy = 0.25,
grid_id = 1,
parent_id = 0,
i_parent_start = 1,
j_parent_start = 1,
parent_grid_ratio = 1,
parent_time_step_ratio = 1,
feedback = 1,
smooth_option = 0,
/
&physics
mp_physics = 8,
ra_lw_physics = 1,
ra_sw_physics = 1,
radt = 30,
sf_sfclay_physics = 5,
sf_surface_physics = 2,
bl_pbl_physics = 1,
bldt = 0,
cu_physics = 1,
cudt = 5,
isfflx = 1,
ifsnow = 1,
icloud = 1,
surface_input_source = 1,
num_soil_layers = 4,
mp_zero_out = 0,
h_mom_adv_order = 5,
v_mom_adv_order = 3,
use_surface = 1,
p_top_requested = 5000,
num_metgrid_levels = 32,
num_metgrid_soil_levels = 4,
dx = 0.25,
dy = 0.25,
/
&fdda
/
&dynamics
w_damping = 0,
diff_opt = 1,
km_opt = 4,
diff_6th_opt = 0,
diff_6th_factor = 0.12,
base_temp = 290.
damp_opt = 0,
zdamp = 5000.,
dampcoef = 0.2,
khdif = 0,
kvdif = 0,
non_hydrostatic = .true.,
moist_adv_opt = 1,
scalar_adv_opt = 1,
/
&bdy_control
spec_bdy_width = 5,
spec_zone = 1,
relax_zone = 4,
specified = .true.,
nested = .false.,
/
&grib2
/
&namelist_quilt
nio_tasks_per_group = 0,
nio_groups = 1,
/
```
注意:以上配置中的dx和dy都为0.25,这是因为你要使用全球等经纬度投影,分辨率为0.25度的数据。如果你使用其他数据,请根据数据分辨率修改dx和dy的值。另外,如果你没有安装过WRF所需的地理数据,你需要根据实际情况修改namelist.wps中的geog_data_path,指向你的地理数据所在的路径。