Richard Huang Torenable

## xgb_tb.py
'''
Updates:
1. Using tensorboardX to replace tensorboard_logger as I prefer tensorboardX's API
2. Log the tree growth process, which would be displayed under "IMAGES" tab in Tensorboard
'''

import pandas as pd
import xgboost as xgb

from sklearn.model_selection import train_test_split

## postgis_enable.sql
-- When encoutner "SQL Error [42704]: ERROR: type "geography" does not exist", try the following

CREATE EXTENSION Postgis;

## knime Batch execute
# Windows:
knime.exe -consoleLog -noexit -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowFile="PathToYourWorkflow.zip" -destFile="OutputPathToYourWorkflow.zip"

# Mac
/Applications/KNIME\ 3.5.3.app/Contents/MacOS/Knime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowFile="PathToYourWorkflow.zip" -destFile="OutputPathToYourWorkflow.zip"

# Linux
knime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowFile="PathToYourWorkflow.zip" -destFile="OutputPathToYourWorkflow.zip"

## authorization_flask.py
# http://book.pythontips.com/en/latest/decorators.html

from functools import wraps
from flask import request

def requires_auth(func):
  @wraps(func)
  def wrapper(*args, **kwargs):
    auth = request.authorization
    if not auto or not check_auth(auth.username, auth.password):

## use_list_as_parameter.R
paras = jsonlite::read_json("/path/to/config.json")

do.call("func", paras) # analogue using dictionary as keywoard paramters `func(**paras)` in python
do.call(func, paras)

## ggplot_basic.R
library(ggplot2)

# var ~ grp
ggplot(aes(x = grp, y = var)) + geom_boxplot()

## rJava_loader.R
# Credit to Paul Klemm's post [Load rJava in RStudio using macOS 10.12](http://paulklemm.com/blog/2017-02-12-fix-onload-failed-rjava-macos/)

dyn.load(paste0(system2('/usr/libexec/java_home', stdout = TRUE), '/jre/lib/server/libjvm.dylib'))

# then load any packages associated to JVM

## EM_decomposition.r
library(mixtools)

mixmdl = normalmixEM(train$y)

plot(mixmdl, which = 2)
lines(density(train$y), lty=2, lwd=2)

# credit to [Ron Pearson](https://www.r-bloggers.com/fitting-mixture-distributions-with-the-r-package-mixtools/)

## sklearn_template.py
import sklearn

######################
# Estimator
######################

# (Analogue to Keras) Initialization all-in-one
# bind symbol
# define loss function + optimizer
# (optional) metrics for output evaluation

## monetdb_bulk_load_csv.sql
COPY OFFSET 2 INTO target.table FROM '/full/path/to/the.csv'
USING
  DELIMITERS ',', '\n', '\"'
  NULL AS ''
	'''
	Updates:
	1. Using tensorboardX to replace tensorboard_logger as I prefer tensorboardX's API
	2. Log the tree growth process, which would be displayed under "IMAGES" tab in Tensorboard
	'''

	import pandas as pd
	import xgboost as xgb

	from sklearn.model_selection import train_test_split
	-- When encoutner "SQL Error [42704]: ERROR: type "geography" does not exist", try the following

	CREATE EXTENSION Postgis;
	# Windows:
	knime.exe -consoleLog -noexit -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowFile="PathToYourWorkflow.zip" -destFile="OutputPathToYourWorkflow.zip"

	# Mac
	/Applications/KNIME\ 3.5.3.app/Contents/MacOS/Knime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowFile="PathToYourWorkflow.zip" -destFile="OutputPathToYourWorkflow.zip"

	# Linux
	knime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowFile="PathToYourWorkflow.zip" -destFile="OutputPathToYourWorkflow.zip"
	# http://book.pythontips.com/en/latest/decorators.html

	from functools import wraps
	from flask import request

	def requires_auth(func):
	@wraps(func)
	def wrapper(args, *kwargs):
	auth = request.authorization
	if not auto or not check_auth(auth.username, auth.password):
	paras = jsonlite::read_json("/path/to/config.json")

	do.call("func", paras) # analogue using dictionary as keywoard paramters `func(**paras)` in python
	do.call(func, paras)
	library(ggplot2)

	# var ~ grp
	ggplot(aes(x = grp, y = var)) + geom_boxplot()
	# Credit to Paul Klemm's post [Load rJava in RStudio using macOS 10.12](http://paulklemm.com/blog/2017-02-12-fix-onload-failed-rjava-macos/)

	dyn.load(paste0(system2('/usr/libexec/java_home', stdout = TRUE), '/jre/lib/server/libjvm.dylib'))

	# then load any packages associated to JVM
	library(mixtools)

	mixmdl = normalmixEM(train$y)

	plot(mixmdl, which = 2)
	lines(density(train$y), lty=2, lwd=2)

	# credit to [Ron Pearson](https://www.r-bloggers.com/fitting-mixture-distributions-with-the-r-package-mixtools/)
	import sklearn

	######################
	# Estimator
	######################

	# (Analogue to Keras) Initialization all-in-one
	# bind symbol
	# define loss function + optimizer
	# (optional) metrics for output evaluation
	COPY OFFSET 2 INTO target.table FROM '/full/path/to/the.csv'
	USING
	DELIMITERS ',', '\n', '\"'
	NULL AS ''