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import numpy as np | |
import pandas as pd | |
from pypesto.store import read_from_hdf5 | |
import os | |
import matplotlib.pyplot as plt | |
from matplotlib import cm | |
from more_itertools import unique_everseen | |
from pathlib import Path | |
import argparse | |
from pypesto.visualize import optimizer_convergence |
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DATASET "x_names" { | |
DATATYPE H5T_STRING { | |
STRSIZE H5T_VARIABLE; | |
STRPAD H5T_STR_NULLTERM; | |
CSET H5T_CSET_UTF8; | |
CTYPE H5T_C_S1; | |
} | |
DATASPACE SIMPLE { ( 71 ) / ( 71 ) } | |
DATA { | |
(0): "init_Cells", "init_Cells_Cycle_G2_rel", |
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def run_optimization(importer, optimizer, output_folder, yaml_file, algorithm_name, num_starts, parallel): | |
""" | |
Run the optimization | |
Parameters | |
---------- | |
importer: | |
PEtab model importer | |
optimizer: | |
name of the optimizer | |
output_folder: |
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# Amici.py | |
def check_gradients(self, x: np.ndarray = None, *args, **kwargs): | |
if x is None and 'petab_problem' in dir(self.amici_object_builder): | |
x = self.amici_object_builder.petab_problem.x_nominal_scaled | |
x_free = self.amici_object_builder.petab_problem.x_free_indices | |
return ObjectiveBase.check_gradients(self, x=x, x_free=x_free, *args, **kwargs) | |
# Base.py |
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parpool(4) | |
parfor K = 1 : 4 | |
if K == 1; compute_function_val(10); end | |
if K == 2; compute_function_val(20); end | |
if K == 3; compute_function_val(30); end | |
if K == 4; compute_function_val(40); end | |
end | |
function y=compute_function_val(m) |
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GameObject cone = GameObject.Find("cone"); | |
Mesh mesh = cone.GetComponent<MeshFilter>().sharedMesh; | |
AssetDatabase.CreateAsset(msh, assetpath); | |
PrefabUtility.SaveAsPrefabAsset(mesh, prefabpath); | |
AssetDatabase.SaveAssets(); | |
AssetDatabase.Refresh(); |
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using UnityEngine; | |
using UnityEditor; | |
using System.Collections; | |
// an Editor method to create a cone primitive (so far no end caps) | |
// the top center is placed at (0/0/0) | |
// the bottom center is placed at (0/0/length) | |
// if either one of the radii is 0, the result will be a cone, otherwise a truncated cone | |
// note you will get inevitable breaks in the smooth shading at cone tips | |
// note the resulting mesh will be created as an asset in Assets/Editor |
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using UnityEngine; | |
using System.Collections; | |
[RequireComponent (typeof (MeshFilter))] | |
public class Cone : MonoBehaviour { | |
/// subdivision | |
public int subdivisions = 10; | |
/// height and radius | |
public float radius = 1f; |
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#!/bin/bash | |
# number of neurons | |
numNeurons=100 | |
# get neurons | |
for index in $(seq 1 "$numNeurons"); do | |
python get_swc.py --search "brain_region=neocortex" \ | |
--filter "cell_type=pyramidal" \ | |
--filter "archive=Hrvoj-Mihic_Semendeferi" \ |
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param( | |
[Parameter(Mandatory=$true)][String]$APPVEYOR_TOKEN="", | |
[Parameter(Mandatory=$true)][String]$PROJECT_SLUG="", | |
[String]$APPVEYOR_USER=stephanmg) | |
if ([string]::IsNullOrWhiteSpace($APPVEYOR_TOKEN)) { "No AppVeyor API token given" } | |
if ([string]::IsNullOrWhiteSpace($PROJECT_SLUG)) { "No project slug to trigger given" } | |
if ([string]::IsNullOrWhiteSpace($APPVEYOR_USER)) { "No Appveyor user given } | |
$headers = @{Authorization = "Bearer $APPVEYOR_TOKEN" } |
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