Vladimir Fadeev kirlf

## clickhouse_http_insert.sh
# Input format: JSONEachRow
# Note: ClickHouse should works on localhost, or port forwarding should be used in this example:
cat <FILE NAME>.json | curl 'http://localhost:8123/?input_format_skip_unknown_fields=1&query=INSERT%20INTO%20<DATABASE NAME>.<TABLE NAME>%20FORMAT%20JSONEachRow' --data-binary @-

## binary_search_tree.py
import math
from collections import deque


class Node:
    """
    A node of the binary search tree

    Attributes
    __________

## linked_lists.drawio.xml
<?xml version="1.0" encoding="UTF-8"?>
<mxfile host="app.diagrams.net" modified="2022-01-11T20:22:49.942Z" agent="5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.93 Safari/537.36" etag="24cRRxXGFhsO2GzN6IQK" version="16.2.4" type="device"><diagram id="Svfi9QZZ8QGGwfDbvttr" name="Page-1">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

## a_pgload.load
LOAD DATABASE
     FROM mysql://user:password@mysql57:3306/mysql_db
     INTO postgresql://user:password@pgsql:5432/pg_db

 CAST type int with extra auto_increment when (< precision 10) to serial drop typemod drop not null,
      type int with extra auto_increment when (<= 10 precision) to bigserial drop typemod drop not null,
      type int when  (< precision 10) to int drop typemod,
      type int when  (<= 10 precision) to bigint drop typemod,
      type tinyint   with extra auto_increment to serial drop not null,
      type smallint  with extra auto_increment to serial drop not null,

## click_pandas_column_names.py
from datetime import datetime
import pandas as pd
from clickhouse_driver import Client

client = Client('localhost')

db_name = "db_name"
tables_list = ["table_1", "table_2"]
db_table_list = ["{db}.{tb}".format(db=db_name, tb=tb) for tb in tables_list]

## enigma_tools.py
# coding=utf-8
import numpy as np
import matplotlib.pyplot as plt
import numpy.linalg as LA
import scipy.optimize as optim


class UnivFitFunc:

    def __init__(self, err=5, Nmax=1000):

## adaptive_beamforming.py
"""
Developed by Vladimir Fadeev
(https://github.com/kirlf)
Kazan, 2017 / 2020

Python 3.7

The result is uploaded in
https://commons.wikimedia.org/wiki/File:AdaptiveBeamForming.png
"""

## adaptive_filters_1.m
%MatLab/Octave

clear all; close all; clc
%% Initialization

% channel parameters
sigmaS = 1; %signal power
sigmaN = 0.01; %noise power
% CSI (channel state information):
channel = [0.722-1j*0.779; -0.257-1j*0.722; -0.789-1j*1.862];

## huffman.py
# Python 3.8
import math
from queue import Queue
from collections import Counter

class HuffmanCodes:
  def __init__(self):
    pass

  def __huffman_tree_to_table(self, root, prefix, lookup_table):
	# Input format: JSONEachRow
	# Note: ClickHouse should works on localhost, or port forwarding should be used in this example:
	cat <FILE NAME>.json \| curl 'http://localhost:8123/?input_format_skip_unknown_fields=1&query=INSERT%20INTO%20<DATABASE NAME>.<TABLE NAME>%20FORMAT%20JSONEachRow' --data-binary @-
	import math
	from collections import deque


	class Node:
	"""
	A node of the binary search tree

	Attributes
	__________
	LOAD DATABASE
	FROM mysql://user:password@mysql57:3306/mysql_db
	INTO postgresql://user:password@pgsql:5432/pg_db

	CAST type int with extra auto_increment when (< precision 10) to serial drop typemod drop not null,
	type int with extra auto_increment when (<= 10 precision) to bigserial drop typemod drop not null,
	type int when (< precision 10) to int drop typemod,
	type int when (<= 10 precision) to bigint drop typemod,
	type tinyint with extra auto_increment to serial drop not null,
	type smallint with extra auto_increment to serial drop not null,
	from datetime import datetime
	import pandas as pd
	from clickhouse_driver import Client

	client = Client('localhost')

	db_name = "db_name"
	tables_list = ["table_1", "table_2"]
	db_table_list = ["{db}.{tb}".format(db=db_name, tb=tb) for tb in tables_list]
	# coding=utf-8
	import numpy as np
	import matplotlib.pyplot as plt
	import numpy.linalg as LA
	import scipy.optimize as optim


	class UnivFitFunc:

	def __init__(self, err=5, Nmax=1000):
	"""
	Developed by Vladimir Fadeev
	(https://github.com/kirlf)
	Kazan, 2017 / 2020

	Python 3.7

	The result is uploaded in
	https://commons.wikimedia.org/wiki/File:AdaptiveBeamForming.png
	"""
	%MatLab/Octave

	clear all; close all; clc
	%% Initialization

	% channel parameters
	sigmaS = 1; %signal power
	sigmaN = 0.01; %noise power
	% CSI (channel state information):
	channel = [0.722-1j0.779; -0.257-1j0.722; -0.789-1j*1.862];
	# Python 3.8
	import math
	from queue import Queue
	from collections import Counter

	class HuffmanCodes:
	def __init__(self):
	pass

	def __huffman_tree_to_table(self, root, prefix, lookup_table):