How to use iOutput method in fMBT

Best Python code snippet using fMBT_python

KeysightB1511B.py

Source:KeysightB1511B.py Github

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1from typing import Optional, TYPE_CHECKING, List, Any2from .KeysightB1517A import B1517A3from .constants import IMeasRange, IOutputRange4if TYPE_CHECKING:5 import qcodes.instrument_drivers.Keysight.keysightb15006class B1511B(B1517A):7 """8 Driver for Keysight B1511B Source/Monitor Unit module for B15009 Semiconductor Parameter Analyzer.10 Args:11 parent: mainframe B1500 instance that this module belongs to12 name: Name of the instrument instance to create. If `None`13 (Default), then the name is autogenerated from the instrument14 class.15 slot_nr: Slot number of this module (not channel number)16 asu_present: Flag to acknowledge ASU presence17 """18 def __init__(19 self,20 parent: "qcodes.instrument_drivers.Keysight.keysightb1500.KeysightB1500",21 name: Optional[str],22 slot_nr: int,23 **kwargs: Any24 ):25 super().__init__(parent, name, slot_nr, **kwargs)26 self._valid_i_measure_ranges: List[IMeasRange] = [IMeasRange.AUTO,27 IMeasRange.MIN_1nA,28 IMeasRange.MIN_10nA,29 IMeasRange.MIN_100nA,30 IMeasRange.MIN_1uA,31 IMeasRange.MIN_10uA,32 IMeasRange.MIN_100uA,33 IMeasRange.MIN_1mA,34 IMeasRange.MIN_10mA,35 IMeasRange.MIN_100mA,36 IMeasRange.FIX_1nA,37 IMeasRange.FIX_10nA,38 IMeasRange.FIX_100nA,39 IMeasRange.FIX_1uA,40 IMeasRange.FIX_10uA,41 IMeasRange.FIX_100uA,42 IMeasRange.FIX_1mA,43 IMeasRange.FIX_10mA,44 IMeasRange.FIX_100mA]45 self._asu_valid_i_measure_ranges: List[IMeasRange] = [46 IMeasRange.MIN_1pA, IMeasRange.MIN_10pA, IMeasRange.MIN_100pA,47 IMeasRange.FIX_1pA, IMeasRange.FIX_10pA, IMeasRange.FIX_100pA]48 self._valid_i_output_ranges: List[IOutputRange] = [49 IOutputRange.AUTO, IOutputRange.MIN_1nA, IOutputRange.MIN_10nA,50 IOutputRange.MIN_100nA, IOutputRange.MIN_1uA,51 IOutputRange.MIN_10uA, IOutputRange.MIN_100uA,52 IOutputRange.MIN_1mA, IOutputRange.MIN_10mA, IOutputRange.MIN_100mA]53 self._asu_valid_i_output_ranges: List[IOutputRange] = [54 IOutputRange.MIN_1pA, IOutputRange.MIN_10pA, IOutputRange.MIN_100pA]55 self.asu_present: bool = False56 @property57 def asu_present(self) -> bool:58 return self._asu_present59 @asu_present.setter60 def asu_present(self, val: bool) -> None:61 if not isinstance(val, bool):62 raise TypeError("Expected: True or False")63 self._asu_present = val64 if self.asu_present:65 self._valid_i_measure_ranges = self._valid_i_measure_ranges + \66 self._asu_valid_i_measure_ranges67 self._valid_i_output_ranges = self._valid_i_output_ranges + \68 self._asu_valid_i_output_ranges69 else:70 self._valid_i_measure_ranges = list(71 set(self._valid_i_measure_ranges) -72 set(self._asu_valid_i_measure_ranges)73 )74 self._valid_i_output_ranges = list(75 set(self._valid_i_output_ranges) -76 set(self._asu_valid_i_output_ranges)...

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run_ann.py

Source:run_ann.py Github

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1def _get_predict_fname(out_dir, ioutput, weight, pdf_sampling):2 if pdf_sampling:3 return "%s/fb_%05i_%s_ftidal_pdf_sampling.predict" % (out_dir, ioutput, weight)4 return "%s/fb_%05i_%s.predict" % (out_dir, ioutput, weight)5def _get_results_fname(out_dir, ioutput, weight, NN, pdf_sampling):6 if pdf_sampling:7 return "%s/fb_%05i_NN%i_%s_ftidal_pdf_sampling.results" % (out_dir, ioutput, NN, weight) 8 return "%s/fb_%05i_NN%i_%s.results" % (out_dir, ioutput, NN, weight)9def main(ioutputs, weights_fname, NN):10 import os11 from seren3.utils import which12 _BIN = which("neural-net")13 _CWD = os.getcwd()14 _WEIGHT = "mw"15 def _run(weights_fname, predict_fname, results_fname):16 exe = "%s -l %s -p %s -o %s" % (_BIN, weights_fname, predict_fname, results_fname)17 # print exe18 os.system(exe)19 for ioutput in ioutputs:20 dir_name = "./%i_final/" % (ioutput)21 # Run the standard and tidal force PDF sampled models22 predict_fname = _get_predict_fname(dir_name, ioutput, _WEIGHT, False)23 predict_pdf_sampled_fname = _get_predict_fname(dir_name, ioutput, _WEIGHT, True)24 results_fname = _get_results_fname(dir_name, ioutput, _WEIGHT, NN, False)25 results_pdf_sampled_fname = _get_results_fname(dir_name, ioutput, _WEIGHT, NN, True)26 for pf, rf in zip([predict_fname, predict_pdf_sampled_fname], [results_fname, results_pdf_sampled_fname]):27 _run(weights_fname, pf, rf)28if __name__ == "__main__":29 import sys, os30 ioutputs = [42, 48, 60, 70, 80, 90, 100, 106]31 NN = int(sys.argv[1])32 weights_fname = "/lustre/scratch/astro/ds381/simulations/baryfrac/bc03_fesc2_nohm/neural-net2/NN%i.weights" % NN33 # weights_fname = "/lustre/scratch/astro/ds381/simulations/baryfrac/bc03_fesc2_nohm/neural-net2/106_90_60_NN40_niter100_fb_scaled_ftidal_scaled_logall.weights"34 35 # ioutputs = [int(i) for i in sys.argv[1:-2]]36 # weights_fname = sys.argv[-2]37 # NN = int(sys.argv[-1])38 # paths = ["bc03_fesc1.5_nohm/", "bc03_fesc2_nohm/", "bc03_fesc5_nohm/"]39 # paths = ["bc03_fesc2_nohm/", "bc03_fesc5_nohm/"]40 paths = ["bc03_fesc2_nohm/"]41 lustre_path = "/lustre/scratch/astro/ds381/simulations/baryfrac/"42 full_paths = ["%s/%s/neural-net2/" % (lustre_path, p) for p in paths]43 print "NN = ", NN44 print "Using weights file: ", weights_fname45 print ioutputs46 for fp in full_paths:47 os.chdir(fp)48 print "**************************************************"49 print os.getcwd()50 print "**************************************************"51 main(ioutputs, weights_fname, NN)...

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