DSLituiev’s gists

DSLituiev / language_model_gru.ipynb

Last active October 21, 2020 20:51

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DSLituiev / find_first_nonnegative.py

Last active September 11, 2019 03:22

find index of first non-negative value in a sorted list

	def split(x):
	"""return the index of the first non-negative value in a sorted list:
	legend for comments:
	"-" stands for negative
	"+" stands for non-negative
	"""
	# check for corner cases:
	if len(x)==0:
	return 0
	elif len(x)==1:

DSLituiev / install_gdb_with_conda_on_mac.sh

Created April 12, 2018 14:59

installing gdb on MacOS with conda python support

	# install gettext; after installation it outputs LDFLAGS and CPPFLAGS values.
	brew reinstall gettext
	# export gettext and conda-specific flags
	export LDFLAGS="-Wl,-rpath,/Applications/anaconda3/lib/ -L/Applications/anaconda3/lib/ -L/usr/local/opt/gettext/lib"
	export CPPFLAGS="-I/usr/local/opt/gettext/include"

	# extract gdb
	tar xvf gdb-8.1.tar.gz
	cd gdb-8.1

DSLituiev / sparse_categorical_crossentropy_with_segmentation.py

Created November 1, 2017 04:54

	#!/usr/bin/env python3
	# -- coding: utf-8 --
	"""
	Created on Wed Oct 25 13:44:51 2017

	@author: dlituiev
	"""
	import os
	import numpy as np
	from uuid import uuid1

DSLituiev / segm_metric_testcase.py

Created October 31, 2017 02:44

segmentation metric with tensorflow

	"""
	Created on Wed Oct 25 13:44:51 2017

	@author: dlituiev
	"""
	import numpy as np
	import keras
	from keras import backend as K
	from keras.layers import (InputLayer, Conv2D, Dense, Activation,
	AveragePooling2D, GlobalAveragePooling2D)

DSLituiev / keras_constant_init_bug.py

Created October 9, 2017 23:43

Initialization with constant results in error when chaining layers

	import sys
	import numpy as np
	import keras
	from keras.models import load_model, Model
	from keras.layers import Conv2D, MaxPool2D, GlobalAveragePooling2D, Dense, Dropout
	from keras import backend as K
	from keras.applications.inception_v3 import InceptionV3

	def get_model(
	dropout=0.5,

DSLituiev / pandas_df_ds_bug_on_subset.py

Last active June 22, 2017 18:10

	import pandas as pd
	all_cols = ['0_AnatomicRegionSequence_CodeMeaning',
	'0_AnatomicRegionSequence_CodeValue',
	'0_AnatomicRegionSequence_CodingSchemeDesignator',
	'0_ContributingEquipmentSequence_ContributionDateTime',
	'0_ContributingEquipmentSequence_ContributionDescription',
	'0_ContributingEquipmentSequence_InstitutionName',
	'0_ContributingEquipmentSequence_Manufacturer',
	'0_ContributingEquipmentSequence_StationName',
	'0_ContributingEquipmentSequence__0_PurposeOfReferenceCodeSequence_CodeMeaning',

DSLituiev / gist:31063fc862b35a729142d3949e803c73

Last active October 5, 2016 21:26

ggplot error on colouring points

dfstr = '''{"FDR":{"0":0.0000001434,"1":0.0974543339,"2":0.5637882089,"3":0.7592318769,"4":0.82376489,"5":0.876232133,"6":0.891150062,"7":0.9234070548,"8":0.9421697501,"9":0.9421697501,"10":0.9534575004,"11":0.9686912495,"12":0.9792339965,"13":0.9800272087,"14":0.9814635178,"15":0.9814635178,"16":0.9822809925,"17":0.9832209543,"18":0.9832209543,"19":0.9832209543,"20":0.0079716299,"21":0.6863477759,"22":0.7846481266,"23":0.8596431336,"24":0.8940558933,"25":0.9071788194,"26":0.9269123036,"27":0.9323909829,"28":0.936505473,"29":0.9477474057,"30":0.9479119432,"31":0.9479119432,"32":0.9479119432,"33":0.9479119432,"34":0.9479179113,"35":0.9577011312,"36":0.9589141116,"37":0.9601000647,"38":0.9614078093,"39":0.9657393252,"40":0.0000000308,"41":0.1179302537,"42":0.6074557222,"43":0.7534315164,"44":0.8290719564,"45":0.8917851883,"46":0.9325332126,"47":0.9495263504,"48":0.9532127733,"49":0.9552555496,"50":0.9594234241,"51":0.9675706204,"52":0.9737916651,"53":0.9767958687,"54":0.9767958687,"55":0.9767958687,"56":0.97679

DSLituiev / fast_lmm_corr_error.py

Last active June 5, 2016 05:42

an error which indicates a modification of the X array by reference.

	from __future__ import division, print_function
	import numpy as np
	import pandas as pd
	from pysnptools.snpreader import SnpData
	from pysnptools.kernelreader import KernelData
	from fastlmm.inference.lmm import LMM

	def snp_from_pandas(df, pos = None):
	indiv_ids = zip(df.index.tolist(), ["."] * len(df.index))
	snp_ids = [("_".join(["%s"% y for y in x]) if type(x) in (tuple, list) else "%s"% x) for x in df.columns.tolist()]

DSLituiev / sranj

Created May 10, 2016 06:18

	<Test-sra>
	<Ngs>
	<Latest>
	<ncbi-vdb version=""/>
	<ngs-sdk version=""/>
	</Latest>
	<LibManager.properties/>
	<ncbi-vdb>
	</ncbi-vdb>
	<ngs-sdk>

Dmytro Lituiev DSLituiev