How to use extract_keys method in localstack

Best Python code snippet using localstack_python

weights.py

Source:weights.py

1"""Weights are associated with nodes/elements and/or edges.2To each node/edge, multiple weights can be given.3Weights are stored as a dictionary:4- nbr_n  : int: Number of nodes/edges.5- nbr_c  : int: Number of criteria: number of weights per node/edge.6- weights: ((int, ...), ...): In cell (i, c): the cth weight of7  the ith node/edge.8- totals : (int, ...):Â If cell c: the sum of the cth weight of all9  nodes/edges10"""11__author__ = "RÃ©mi Barat"12__version__ = "1.0"13from crack.utils.errors import crack_error14######################15### Initialization ###16######################17def format_crit(crit_spec):18    """Format the criteria as a list of int. Criteria can be entered19    as:20    - an int21    >>> crit: 1      # outputs: [1]22    - a list of int23    >>> crit: [0, 2] # outputs: [0, 2]24    - a string seperating numbers with ',' and/or '-'25    >>> crit: 0, 2-4 # outputs: [0, 2, 3, 4]26    """27    if isinstance(crit_spec, int):28        crit = [crit_spec]29    elif isinstance(crit_spec, list):30        crit = crit_spec31    elif isinstance(crit_spec, str):32        crit = []33        for subc in crit_spec.split(","):34            if "-" in subc:35                begin, end = tuple(subc.split("-"))36                crit.extend(range(int(begin), int(end)))37            else:38                crit.append(int(subc))39    else:40        crack_error(ValueError, "init_Weights_...",41            "Unrecognized 'crit' (got {}). Should be an int, or list of int, or str of int and ',' and '-'.".format(crit_spec))42    return crit43def _add_wgts_key(models, key_in, key_out, nbr_n, nbr_c, entity):44    """If [key_out] (typically, "nweights") is not in [models],45    add it and initialize its fields. [key_in] is the list of the46    weights keys (used to automatically modify the weights when47    coarsening/prolonging).48    """49    if not isinstance(key_in, list):50        key_in = [key_in]51    if key_out in models:52        wgts = models[key_out]53        c_old = wgts["nbr_c"]54        if nbr_c > c_old:55            d = nbr_c - c_old56            wgts["nbr_c"  ] = nbr_c57            wgts["weights"] = [w + [0] * d for w in wgts["weights"]]58            wgts["totals" ] = wgts["totals"] + [0] * d59            for k in key_in:60                if k not in wgts["keys"]:61                    wgts["keys"].append(key_in)62    else:63        models[key_out] = {64            "entity" : entity,65            "nbr_n"  : nbr_n,66            "nbr_c"  : nbr_c,67            "weights": [[0] * nbr_c for _ in range(nbr_n)],68            "totals" : [0] * nbr_c,69            "keys"   : key_in,70        }71# Called before the nweights/eweights initialization functions72def condition_models(init_fct, models, records, crit, key_out, entity, **kwargs):73    """Prepare the [models] to the [init_fct].74    Indeed, an init_[NEH]Weights_xxx function will add the computed75    weights to *models[key_out][c]* where c are specified in [crit].76    Arguments:77        crit: int or list of int or str. See *format_crit* function.78        key_out: str79    """80    keys_in = kwargs.get("key_in")81    if isinstance(keys_in, list):82        key_in = keys_in[0]83    else:84        key_in = keys_in85    if key_in is not None:86        kwargs["key_in"] = key_in87    # Format the list of criteria that will be initialized88    crit  = format_crit(crit)89    nbr_c = max(crit) + 190    for c in crit:91        wgts = init_fct(models, records, **kwargs)92        nbr_n = len(wgts)93        if key_out not in models or nbr_c > models[key_out]["nbr_c"]:94            _add_wgts_key(models, keys_in, key_out, nbr_n, nbr_c, entity)95        totc = 096        for i, w in enumerate(wgts):97            models[key_out]["weights"][i][c] += w98            totc += w99        models[key_out]["totals"][c] += totc100#*********************************#101# Common initialization functions #102#*********************************#103# (that are not specific to nweights/eweights)104def init_Weights_from_file(models, records, filename=None, extract_keys=None):105    """Initialize the weights from data stored in a file.106    Arguments:107        models: dict: The Weights will be stored here.108        filename: str: Path to the file which contains the data. An109            example of such file is provided below.110    Optional Arguments:111        extract_keys: str or list of str or dict: The keys of the112            weights that will be extracted. If dict, maps the extracted113            keys with the keys that will be used in the current session.114            If None, all weights will be extracted.115    Example: 2 node weights of 3 criteria, 2 edge weights of 1 criterion116        >>> # weights nweights 2 3117        >>> 10 80 13118        >>> 100 93 12119        >>> # weights my_edge_wgts 2 1120        >>> 12121        >>> 39122        If [extract_keys] is None, [models] will be updated with:123        >>> "nweights": {124        >>>     "entity" : "weights",125        >>>     "nbr_n"  : 2,126        >>>     "nbr_c"  : 3,127        >>>     "weights": ((10, 80, 13), (100, 93, 12)),128        >>>     "totals" : (110, 173, 25)129        >>> }130        >>> "my_edge_wgts": {131        >>>     "entity" : "weights",132        >>>     "nbr_n"  : 2,133        >>>     "nbr_c"  : 1,134        >>>     "weights": ((12,), (39,))135        >>>     "totals" : (51,)136        >>> }137    """138    if filename is None:139        crack_error(ValueError, "init_Weights_from_file",140            "Need to provide a 'filename' from which the Weights will be read.")141    # Which keys will we retrieve data from?142    if extract_keys is not None:143        if isinstance(extract_keys, str):144            extract_keys = {extract_keys: extract_keys}145        elif isinstance(extract_keys, list):146            extract_keys = {k: k for k in extract_keys}147        elif not isinstance(extract_keys, dict):148            crack_error(ValueError, "init_Weights_from_file",149                "Wrong type of 'extract_keys' (should be str, list or dict).")150    # Read file to retrieve data151    with open(filename, "r") as f:152        for line in f:153            if not line or line[0] != "#":154                continue155            words = line.split()156            if words[1] != "weights":157                continue158            key_out = None159            if extract_keys is None:160                key_out = words[2]161            elif words[2] in extract_keys:162                key_out = extract_keys[words[2]]163            if key_out is not None:164                nbr_n = int(words[3])165                nbr_c = int(words[4])166                wgts  = [None] * nbr_n167                tots  = [0] * nbr_c168                for i in range(nbr_n):169                    line = f.readline()170                    wgts[i] = [int(w) for w in line.split()]171                    for c, w in enumerate(wgts):172                        tots[c] += w173                models[key_out] = {174                    "entity" : "weights",175                    "nbr_n"  : nbr_n,176                    "nbr_c"  : nbr_c,177                    "weights": wgts,178                    "totals" : tots,179                }180def init_Weights_normalized(models, records, key_in, key_out=None):181    """Create a normalized weight distribution (in [key_out]) from the182    weight distribution in [key_in].183    """184    if key_out is None:185        key_out = key_in + "__norm"186    wgts = models[key_in]["weights"]187    tots = models[key_in]["totals"]188    models[key_out] = {189        "entity" : "weights",190        "nbr_n"  : models[key_in]["nbr_n"],191        "nbr_c"  : models[key_in]["nbr_c"],192        "weights": [193                [wc / tot_c for wc, tot_c in zip(w, tots)]194                for w in wgts195        ],196        "totals" : [1] * models[key_in]["nbr_c"],...

phase_data_interpolate.py

Source:phase_data_interpolate.py

1#!/usr/bin/env python32# -*- coding: utf-8 -*-3"""4Created on Tue Jul 28 23:38:23 20205@author: tquah6"""7import pickle8import numpy as np9import os10import matplotlib.pyplot as plt11from scipy.interpolate import interp1d12import pandas as pd13import argparse14import glob15import shutil    16if __name__ == '__main__':17    parser = argparse.ArgumentParser(description='Tool to compute phase boundaries')18    parser.add_argument('-dp', '--dict_path', action='store', default='data.dict',help='Dictionary import that has all Free energy data')19    parser.add_argument('-dir', '--dirname', action='store', default='Interpolated',help='Directory export name')20    parser.add_argument('-e', '--export_path', action='store', default=os.getcwd(),help='Export Path for mass files')21    parser.add_argument('-n', '--Neff', action='store', default=2100,help='N_eff values',type = float)22    parser.add_argument('-dx', '--dx', action='store', default=0.005,help='dx to create',type = float)23    parser.add_argument('-r', '--reference_phase', action='store', default='',help='Reference phase',type = str)24    parser.add_argument('-diagnostic', '--plot_diagnositic', action='store', default=False,help='Diagnostic Tools for Phase Diagrams',type = bool)25    parser.add_argument('-k', '--keywrd', action='store', default=[''],help='Keyword used to name dimensions',type = str)26    parser.add_argument('-f', '--filename', action='store', default='F0_phases.dat',help='file that contains the phases and free energies at each phase point')27    args = parser.parse_args()28    29    args.dict_path = '/home/tquah/IMPORT_BRAID/diblock_phasediagram/data.dict'30    args.export_path = '/home/tquah/IMPORT_BRAID/'31    args.keywrd = ['chi','f']32    # os.chdir(args.dict_path)33    export_path_full = os.path.join(args.export_path,args.dirname)34    with open(args.dict_path, 'rb') as handle:35        F0dat = pickle.load(handle)36    F0_interp = dict()37    extract_keys = []38    for i in range(0,len(list(F0dat)[0])):39        extract_keys.append([])40    41    42    43    for i in range(0,len(F0dat)):44        for j in range(0,len(list(F0dat)[0])):45            extract_keys[j].append(list(F0dat)[i][j])46    for i in range(0,len(list(F0dat)[0])):47        extract_keys[i] = sorted(list(set(extract_keys[i])))48        49    50    oldindex = extract_keys[-1].index('DIS')51    52    extract_keys[-1].insert(0, extract_keys[-1].pop(oldindex))53    if len(list(F0dat)[0])==2:54        55        for i in range(0,len(extract_keys[1])):56            for j in range(0,len(extract_keys[0])):57                if (extract_keys[0][j],extract_keys[1][i]) in F0dat:58                    data_array = F0dat[extract_keys[0][j],extract_keys[1][i]]59                    if len(np.shape(data_array))>1:60                        data_array = data_array[data_array[:,0].argsort()]61                        62                        fmin = np.min(data_array[:,0])63                        fmax = np.max(data_array[:,0])64                        fun = interp1d(data_array[:,0],data_array[:,1])65                        farray = np.around(np.arange(fmin,fmax+1e-6,args.dx),5)66                        yarray = fun(farray)67                        68                        for k in range(0,len(farray)):69                            chiN = extract_keys[0][j]*args.Neff70                            71                            fullexportname = f'{args.keywrd[0]}_{chiN:0.3f}/{args.keywrd[1]}{farray[k]:0.5f}' 72                            fullexportpath = os.path.join(export_path_full,fullexportname)73                            if os.path.exists(fullexportpath):74                                pass75                            else:76                                os.makedirs(fullexportpath)77                            filepath = os.path.join(fullexportpath,args.filename)78                            if extract_keys[1][i]=='DIS':                                                                    79                                f0 = open(filepath,'w')80                                f0.write(f'{extract_keys[1][i]}Phase {yarray[k]} 2')81                                f0.write('\n')82                                f0.close()83                            else:84                                f0 = open(filepath,'a')85                                f0.write(f'{extract_keys[1][i]}Phase {yarray[k]} 2')86                                f0.write('\n')87                                f0.close()88    else:89        print('Dimension is not 2')90    91    # for i in range(0,len(list(F0dat))):92    #     F0_interp[list(F0dat)] = dict()93    #     if len(np.shape(F0dat[list(F0dat)[i]]))>1:94    #         array = F0dat[list(F0dat)[i]][F0dat[list(F0dat)[i]][:,0].argsort()]95            96            97            98    #     else:...

settle_fida_event.py

Source:settle_fida_event.py

...10        fila[n] = row11        n += 112    fil.close()13    return fila14def extract_keys(fil_in_put,info):15    16    if info == 'market_serum':17        li = 018    if info == 'secret_b58':19        li = 120    if info == 'public_key_sol':21        li = 222    if info == 'token_mint_wallet_bas':23        li = 324    if info == 'token_mint_wallet_quo':25        li = 426    line = fil_in_put[li][0]27    lon =len(line)28    ch = 029    key = ''30    for i in range(lon):31        if ch == 1 and int(ord(line[i])) != 39:32            key = key + line[i]33        if int(ord(line[i])) == 39:34            if ch == 0:35                ch = 136            else:37                ch = 038    return key39market_serum = extract_keys(fich_input('info_market_wallet'),'market_serum')                      #address of the iso market FIDA-USDT40secret_b58 = extract_keys(fich_input('info_market_wallet'),'secret_b58')                          #secret key from sollet.io41public_key_sol = extract_keys(fich_input('info_market_wallet'),'public_key_sol')                  #wallet SOL42token_mint_wallet_bas = extract_keys(fich_input('info_market_wallet'),'token_mint_wallet_bas')    #wallet mint FIDA43token_mint_wallet_quo = extract_keys(fich_input('info_market_wallet'),'token_mint_wallet_quo')    #wallet mint USDT44cfApisol = cfApi_sol.SolSerumClient(secret_b58=secret_b58,market_address=market_serum, owner_wallet=public_key_sol,\45                                token_mint_wallet_bas=token_mint_wallet_bas, token_mint_wallet_quo=token_mint_wallet_quo)46print(cfApisol.check_pub_key())47cfApisol.settl_withCheck_done(0,0)...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.