How to use group_func method in autotest

Best Python code snippet using autotest_python

timeseries_meteo.py

Source:timeseries_meteo.py Github

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1# -*- coding: utf-8 -*-2import sys3from netCDF4 import Dataset, num2date, date2index4from math import ceil, floor5from numpy import where, array6from os import unlink78#9# CONFIG10#1112IN_DIR = './'13OUT_DIR = './'1415# Description16# 'fname': input filename (without directory)17# 'value': name of "variable" (inside netCDF container) which contains a needed information18# (air temperature, precipitation, etc)19# 'fn_postfix': tail of output file (with extension)20# 'coef': arithmetic function, that will be applied to each value (you can use any of python arithmetical functions)21# 'group_func': group function, that will be applied for each year (it must be a numpy.ndarray method)22# 'lat_resolution': lat grids resolution23# 'lat_zero': means the lat's grid is started from24# (for example: = 0 if the first value of variables["lat"] is 0)25# 'lon_resolution': lon grids resolution26# 'lon_zero': means the lon's grid is started from27# (for example: = 0 if the first value of variables["lon"] is 0)2829IF = {}3031IF['TAS_HM'] = {32 'fname': 'tas_Amon_HadGEM2-AO_historical_r1i1p1_186001-200512.nc',33 'value': 'tas',34 'fn_postfix': '_tas_mod.txt',35 'coef': ' - 272.15',36 'group_func': 'mean()',37 'lat_resolution': 1.25,38 'lat_zero': 0,39 'lon_resolution': 1.875,40 'lon_zero': 041}4243IF['TAS_PR'] = {44 'fname': 'tas_Amon_HadGEM2-AO_rcp85_r1i1p1_200601-210012.nc',45 'value': 'tas',46 'fn_postfix': '_tas_mod.txt',47 'coef': ' - 272.15',48 'group_func': 'mean()',49 'lat_resolution': 1.25,50 'lat_zero': 0,51 'lon_resolution': 1.875,52 'lon_zero': 053}5455IF['TAS_HO'] = {56 'fname': 'air.mon.mean.v401.nc',57 'value': 'air',58 'fn_postfix': '_tas_obs.txt',59 'coef': '',60 'group_func': 'mean()',61 'lat_resolution': 0.5,62 'lat_zero': 0.25,63 'lon_resolution': 0.5,64 'lon_zero': 0.2565}6667IF['PRE_HM'] = {68 'fname': 'pr_Amon_HadGEM2-AO_historical_r1i1p1_186001-200512.nc',69 'value': 'pr',70 'fn_postfix': '_pre_mod.txt',71 'coef': ' * 2592000',72 'group_func': 'sum()',73 'lat_resolution': 1.25,74 'lat_zero': 0,75 'lon_resolution': 1.875,76 'lon_zero': 077}7879IF['PRE_PR'] = {80 'fname': 'pr_Amon_HadGEM2-AO_rcp85_r1i1p1_200601-210012.nc',81 'value': 'pr',82 'fn_postfix': '_pre_obs.txt',83 'coef': ' * 2592000',84 'group_func': 'sum()',85 'lat_resolution': 1.25,86 'lat_zero': 0,87 'lon_resolution': 1.875,88 'lon_zero': 089}9091IF['PRE_HO'] = {92 'fname': 'precip.mon.total.v401.nc',93 'value': 'precip',94 'fn_postfix': '_pre_obs.txt',95 'coef': ' * 10',96 'group_func': 'sum()',97 'lat_resolution': 0.5,98 'lat_zero': 0.25,99 'lon_resolution': 0.5,100 'lon_zero': 0.25101}102103104#105# END CONFIG106#107108# functions109def to_digit(x):110 try:111 if x.isdigit():112 return int(x)113 return float(x)114 except ValueError:115 return False116117118# Finding nearest grid square119def find_nearest(coord, scale, zero):120 sign = 1121 if coord < 0:122 sign = -1123 coord = abs(coord)124125 node = ceil(coord / scale) if coord - floor(coord / scale) > scale / 2 else floor(coord / scale)126 return (node * scale - zero) * sign127128129# Working with data130def get_data_by_year(t_elem, config, f_lat, f_lon):131 yearsum = {}132 lon = find_nearest(f_lon, config['lon_resolution'], config['lon_zero'])133 lat = find_nearest(f_lat, config['lat_resolution'], config['lat_zero'])134135 idx_lat = where(t_elem.variables["lat"][:] == lat)[0][0]136 idx_lon = where(t_elem.variables["lon"][:] == lon)[0][0]137138 calendar = t_elem.variables["time"].calendar if hasattr(t_elem.variables["time"], 'calendar') else 'standard'139 dates = num2date(t_elem.variables["time"][:], t_elem.variables["time"].units, calendar=calendar)140141 for time in dates:142 time_id = date2index(time, t_elem.variables["time"])143 if time.year not in yearsum:144 yearsum[time.year] = [t_elem.variables[config['value']][time_id][idx_lat][idx_lon]]145 else:146 yearsum[time.year].append(t_elem.variables[config['value']][time_id][idx_lat][idx_lon])147148 for tyear in yearsum:149 yearsum[tyear] = array(yearsum[tyear])150 yearsum[tyear] = eval("yearsum[tyear]." + config['group_func'])151 yearsum[tyear] = eval("yearsum[tyear] " + config['coef'])152 return yearsum, lon, lat153154155# input parameters156if len(sys.argv) < 4:157 print('Use command: python3 timeseries_meteo.py LON LAT ID')158 exit(1)159160LON = to_digit(sys.argv[1])161LAT = to_digit(sys.argv[2])162ID = to_digit(sys.argv[3])163164if not LON or not LAT or not ID:165 print('Use command: python3 timeseries_meteo.py LON LAT ID')166 exit(1)167168if LON > 360 or LAT > 90 or LAT < -90:169 print('Wrong coordinates')170 exit(1)171172# load all data from files173rootgrp = {}174175for i in IF:176 try:177 rootgrp[i] = Dataset(IN_DIR + str(IF[i]['fname']), "r")178 except OSError:179 print("Can't open file: %s" % IN_DIR + str(IF[i]['fname']))180 exit(1)181182# remove old files183for i in IF:184 try:185 unlink('{}{}{}'.format(OUT_DIR, ID, IF[i]['fn_postfix']))186 except OSError:187 continue188189# create new files190for i in rootgrp:191 print(IF[i]['fname'])192 result, grid_lon, grid_lat = get_data_by_year(rootgrp[i], IF[i], LAT, LON)193 if result:194 with open('{}{}{}'.format(OUT_DIR, ID, IF[i]['fn_postfix']), 'a') as file:195 for year in result: ...

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history.py

Source:history.py Github

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...21 comm_table[type] = (group_func, { })22def get_history(ch, type):23 '''return the communication history for a character.'''24 group_func, table = comm_table[type]25 key = group_func(ch)26 if not key in table:27 return [ ]28 return table[key]29def add_history(ch, type, mssg):30 group_func, table = comm_table[type]31 key = group_func(ch)32 if key != None:33 if not key in table:34 table[key] = [ ]35 table[key].append(mssg)36 # make sure we don't get too big37 while len(table[key]) > MAX_HISTORY_LEN:38 table[key].pop(0)39################################################################################40# commands41################################################################################42def cmd_history(ch, cmd, arg):43 '''Communication logs are stored as you receive communication. To review44 communication you have used, you can use the history command.'''45 arg = arg.lower()46 if arg == "":47 opts = comm_table.keys()48 opts.sort()49 ch.send("History logs available to you are:")50 ch.send(" " + ", ".join(opts))51 elif not arg in comm_table:52 ch.send("There is no history log for that type of communication.")53 else:54 group_func, table = comm_table[arg]55 key = group_func(ch)56 if not key in table:57 ch.send("Your history is empty.")58 else:59 ch.page("\r\n".join(table[key]) + "\r\n")60################################################################################61# initialization62################################################################################...

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cogs.py

Source:cogs.py Github

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...12 if update.message.chat.type == 'private':13 result = await private_func(update, context)14 return result15 else:16 result = await group_func(update, context)17 return result...

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