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Notes

• daz scripting documentation: http://docs.daz3d.com/doku.php/public/software/dazstudio/4/referenceguide/scripting/start
• video about manual morph creation: https://www.youtube.com/watch?v=wtxsDxKY5Ok
• useful reference for understanding how to script adjustment of morphs: https://www.sharecg.com/v/91228/view/8/Script/Daz3D-Morphs-Randomizer
• example scripts from daz forum for scripting:
  • morph+clothing: https://www.daz3d.com/forums/discussion/185546/creating-a-morph-via-script-and-getting-clothing-to-conform-solved
  • morph body shape: https://www.daz3d.com/forums/discussion/120751/how-to-script-modifying-a-body-shape

Art packs

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WITH wanted AS (
SELECT 
  session_id, 
  ROW_NUMBER() OVER(PARTITION BY session_id ORDER BY block_timestamp) AS pos, 
  CASE WHEN tx.to_address = "0x698ff47b84837d3971118a369c570172ee7e54c2" THEN TRUE ELSE NULL END AS ok,
  tx.to_address
FROM `crypto-public-data.aux.materialized_sessions` AS sessions JOIN UNNEST(transactions) AS tx
WHERE TRUE
),
raw_referrers AS (

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#!/usr/bin/perl
=pod
--root level tx
SELECT from_address AS u
, ARRAY_AGG(DISTINCT(UNIX_SECONDS(block_timestamp))) AS ss_array
FROM `bigquery-public-data.crypto_ethereum.traces`
WHERE trace_address IS NULL
GROUP BY u
=cut
use strict;

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%.ohlc.csv :
        perl ./coingecko-csv.pl ${@:.ohlc.csv=} > $@
%.meta.jsonl :
        perl ./coingecko-metadata.pl ${@:.meta.jsonl=} > $@
all.meta.jsonl :
        cat `ls *.meta.jsonl | grep -v $@` | perl -ne 'print lc' | sort > $@
all.ohlc.csv :
        cat `ls *.ohlc.csv | grep -v $@` > $@
all :

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SELECT transfers.block_timestamp,transfers.from_address, transfers.to_address, tokens.symbol, tokens.address, SAFE_CAST(transfers.value AS INT64) / POW(10,SAFE_CAST(tokens.decimals AS INT64)) AS token_value
FROM
`bigquery-public-data.crypto_ethereum.token_transfers` AS transfers,
`bigquery-public-data.crypto_ethereum.tokens` AS tokens
WHERE
transfers.token_address = tokens.address
AND tokens.address IN('0x514910771af9ca656af840dff83e8264ecf986ca','0x2260fac5e5542a773aa44fbcfedf7c193bc2c599')
ORDER BY transfers.block_timestamp DESC
LIMIT 1000

allenday

sudo apt-get -y update
sudo apt-get -y install build-essential ca-certificates curl ffmpeg git wget unzip python3-dev python3-pip software-properties-common python3-numpy youtube-dl

#install for GPU
sudo apt-get install mesa-common-dev libegl1-mesa-dev libgles2-mesa-dev
sudo apt purge nvidia-*
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo apt install nvidia-384

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WITH sessions AS (
SELECT
    block_timestamp,
    block_number,
    transaction_index,
    value,
    from_address,
    CASE WHEN trace_type IS NULL THEN 0 ELSE 1 END AS is_from_contract,
    trace_type,
    SUM(is_new_session) OVER (ORDER BY from_address, block_timestamp) AS global_session_id,

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# dependencies
library("moduleColor")
library("dynamicTreeCut")
library("RColorBrewer")


# import data
canna.z = read.csv("~/Downloads/canna-z.csv",header=T,row.names=1)
#https://github.com/mattsarrasin/canna-gen/blob/master/sample_description_list-2.txt
id2name = read.csv('~/Downloads/results-20200327-155748.csv')

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SELECT 
seq_id,source,type,seq_start,seq_end,
ST_MAKELINE(ST_GEOGPOINT(LOG(seq_start)/LOG(10),-0.01),ST_GEOGPOINT(LOG(seq_end)/LOG(10),0.01)) AS range_log10,
score,strand,phase,attributes
FROM `project.dataset.tablename`
LIMIT 1000

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gcloud compute instances create XXX --project=XXX --image-project=deeplearning-platform-release --image-family=tf-latest-gpu --maintenance-policy=TERMINATE --boot-disk-size 200GB --accelerator="type=nvidia-tesla-v100,count=1" --metadata="install-nvidia-driver=True" --zone="us-west1-b"