giving up

0/tutorial.py

@@ -476,6 +476,10 @@ from collections import namedtuple
 from numbers import Number
 from typing import Self
 
+# a habit that you should take is that you should never blanket import.
+# non of these import * in python, use ::* in rust, using namespace in c++, etc.
+# only import what you need. the IDE will help you.
+
 
 class BungeeJumper:
     """
@@ -517,8 +521,8 @@ class BungeeJumper:
     @property
     def t(self):
         """current time
-        we will not set time, change it through delta + special reset fn,
+
-        """
+        we will not set time, change it through delta + special reset fn,"""
         return self.__time
 
     @property
@@ -590,6 +594,7 @@ class BungeeJumper:
             "table": [i._asdict() for i in self.__table],
         }
 
+    # pylint flagged this for design choice, and i agree.
     def bungee_import(self, t=None, dt=None, vt=None, m=None, cd=None, table=None):
         """overrides, also format from bungee_info only"""
         if t is not None:
@@ -665,16 +670,16 @@ instance instead of doing nothing will be passed into methods as first argument.
 yes, not javas `this`. `this` is a set name.
 python `self` i could change it to whatever. instance will be passed to it.
 
-That is a classmethod.
+That is a method.
 a staticmethod has no such rules.
 """
 
 # do you know you can declare a class without even touching the word class at all? its the power of type().
+# however dont do this oh please
 
 
-@classmethod
+def lda_set_example_arg(inst, arg):
-def lda_set_example_arg(self, arg):
+    inst.lda_example_instance_arg = arg
-    self.lda_example_instance_arg = arg
 
 
 " __init__ is a magic function that will run when you make a class instance"
@@ -694,13 +699,18 @@ LdaExampleClass = type(
 LdaExampleClass.hello_to("lda")  # prints hello lda!
 
 
-def lda_print_example_arg(self):
+def lda_print_example_arg(inst):
-    print("instance:", self.lda_example_instance_arg)
+    print("instance:", inst.lda_example_instance_arg)
-    print("class:", self.lda_example_class_arg)
+    print("class:", inst.lda_example_class_arg)
 
+# @classmethod # class methods passes class as opposed of instance for first arg # i just knew this!
+# def cls_print_example_arg(cls):
+#     print("class:", cls.lda_example_class_arg)
+#     print("instance:", cls.lda_example_instance_arg) # uh oh
 
 # objects can freely add properties
-LdaExampleClass.lda_print_example_arg = classmethod(lda_print_example_arg)
+LdaExampleClass.lda_print_example_arg = lda_print_example_arg
+# LdaExampleClass.cls_print_example_arg = cls_print_example_arg # see note below
 
 lda1 = LdaExampleClass(3)  # this must fit the args of self.__init__()
 lda1.lda_print_example_arg()  # pylint: disable=no-member # ide freak out
@@ -708,6 +718,7 @@ lda1.lda_print_example_arg()  # pylint: disable=no-member # ide freak out
 # and class which is from the above which is 1.
 # Nothing was changed: i dont assign anything to anything in the functions
 # except for lda_set_example_arg
+# lda1.cls_print_example_arg() # crashes as cls LdaExampleClass dont have lda_example_instance_arg instance variable
 
 # dont do this, however, as ide will freak out.
 
@@ -723,6 +734,7 @@ copied_1_20 = one_to_20.copy()  # this shallow copies
 copied_1_20.append(21)
 
 assert copied_1_20 != one_to_20
+assert copied_1_20[-2:] == [20, 21]
 
 # if you have intellicode you can do ctrl + space to get that hints going.
 
@@ -731,3 +743,6 @@ ah yes intellicode.
 You can view methods easily with intellisense if using vscode, 
 and you can also docs.python.org for more
 """
+
+# here is where you should be downloading jupyter to get the Tutorial2 Going.
+# check its website. make sure you have the python, it is in PATH, and the pip exists. Or you can use poetry or miniconda. Or pipx. idfk do research.

0/tutorial2.ipynb

@@ -250,7 +250,7 @@
     "try:\n",
     "    raise ValueError(\"value eroe\")\n",
     "except ValueError as error:\n",
-    "    print(\"raised\", error)\n"
+    "    print(\"raised\", error)"
    ]
   },
   {
@@ -284,7 +284,8 @@
     "\n",
     "    def quux(tis, arg1):\n",
     "        return arg1, 42\n",
-    "    \n",
+    "\n",
+    "\n",
     "# usage:\n",
     "\n",
     "fbar = Foo()\n",
@@ -340,6 +341,92 @@
    "source": [
     "do research broski\n",
     "\n",
+    "## more python stuff\n",
+    "\n",
+    "### map and filter\n",
+    "\n",
+    "alot of time you would want to do stuff with the List and you would want to have a look at the builtin `map()` or `filter()` or those kind of functions:\n",
+    "\n",
+    "what they do is:\n",
+    "\n",
+    "```python\n",
+    "collection = [something, something_else,]\n",
+    "def function(x) -> y: ...\n",
+    "\n",
+    "new_collection = map(function, collection) \n",
+    "# => each x you run function on it and it returns y.\n",
+    "# put that y in the place x would be in the new_collection\n",
+    "\n",
+    "condition = lambda x: x == True\n",
+    "# lambda is a kind of mini throwaway function. you know closures? yes that\n",
+    "# but it can only do one thing. one singular expression fits in there. life is bad.\n",
+    "# tips. use def if this function deserves a name. for example ReLU is just\n",
+    "# ReLU = lambda x: x if x > 0 else 0\n",
+    "# but you would use want to do def ReLU(x: float) -> float as much as possible\n",
+    "\n",
+    "filtered_collection = filter(condition, collection)\n",
+    "# check for condition for each element of condition and append it into filtered_collection\n",
+    "```\n",
+    "\n",
+    "remember map and filter doesnt return a list back but a special generator object so you would have to call list() on it to use as list.\n",
+    "\n",
+    "why? for performance. generator is lazy."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "we also have this thing:\n",
+    "\n",
+    "### Python list comprehension\n",
+    "\n",
+    "comprehension. fuck do i know what it means. you dont know half these words and so do i.\n",
+    "\n",
+    "a simple way to do fiter_map ig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# you would do this:\n",
+    "oldlist = list(range(1, 40, 3))\n",
+    "newlist = []\n",
+    "for i in oldlist:  # notice this\n",
+    "    if i % 5 == 0:  # notice this\n",
+    "        newlist.append(i)\n",
+    "\n",
+    "list_shorthand = [i for i in oldlist if i % 5 == 0]\n",
+    "\n",
+    "assert list_shorthand == newlist  # same thing!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "its: \n",
+    "```python\n",
+    "something(vals) for vals in collection if condition(vals) if condition2(vals) if etc.\n",
+    "```\n",
+    "and `something(vals)` could well be another comprehension.\n",
+    "\n",
+    "notice for in if. strictly for in if, and not if for in. that if is of something else.\n",
+    "\n",
+    "oh but `something if condition else something_else` i also see how is that\n",
+    "\n",
+    "well that is another shorthand unrelated, but if you can use sure go ahead\n",
+    "\n",
+    "its kinda like the Ternary conditional operator `cond ? true_expr : false_expr` in c or typescript and yes you can go crazy with it just like with typescript"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## what the fuck is this half code half document\n",
     "\n",
     "jupyter. very flexible very dynamic. you can have jupyter running on browser or on vscode i think\n",
@@ -368,7 +455,7 @@
     "except ImportError:\n",
     "    print(\"python -m pip install numpy\")\n",
     "else:\n",
-    "    print(np.array([[1, 5, 7], [2, 6, 8], [3, 4, 9]]))\n"
+    "    print(np.array([[1, 5, 7], [2, 6, 8], [3, 4, 9]]))"
    ]
   },
   {

1/README.md

@@ -0,0 +1,13 @@
+# slide number 1
+
+we will do it in jupyter notebook as it is better for this purpose
+
+## what we kinda learn in slide 1
+
+computer friendly calculation methods. its different to just math.
+
+it is an approximation method for some of the harder problems that would be hard with math alone
+
+it gets the job done for some people  
+doesnt for others  
+it idk

1/intro.ipynb

@@ -0,0 +1,171 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# dont i hate this shit\n",
+    "\n",
+    "im manually translating the slides\n",
+    "\n",
+    "### why numpy and not pure python\n",
+    "\n",
+    "[../0/tutorial2.ipynb#numpy](../0/tutorial2.ipynb#numpy)\n",
+    "\n",
+    "### honestly\n",
+    "\n",
+    "[numpy beginners click here](https://numpy.org/doc/stable/user/absolute_beginners.html)\n",
+    "\n",
+    "## import steps. use for import\n",
+    "\n",
+    "you may need to:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "shellscript"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "pip install numpy matplotlib"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## usage\n",
+    "\n",
+    "make the list in python and then you np.array it and then feed the numpy array to numpy functions\n",
+    "\n",
+    "notice: make it\n",
+    "\n",
+    "1. with same size: `all(len(i) == len(j) for i in pyarray for j in pyarray) == True`\n",
+    "2. all elements have same type `all(type(i) == type(r[0]) for i in r for r in pyarray) == True`\n",
+    "\n",
+    "then you will be able to harness the peak of numpy. Or else goodbye"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pyarray = [\n",
+    "    [1, 2, 3],\n",
+    "    [4, 5, 6],\n",
+    "]\n",
+    "\n",
+    "\n",
+    "numpy_array = np.array(pyarray)\n",
+    "\n",
+    "pyarray, numpy_array"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "the 3:11:2 notation in python is called a slice object. numpy (probably) modified its `array.__index__` to yk accommodate to dimensions\n",
+    "\n",
+    "so normally you wouldnt fit more than one thing in that bracket: now you can! pretty great"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "newarr = numpy_array[:,1:3]\n",
+    "newarr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "kinda cool. normally it would be:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "[i[1:3] for i in pyarray[:]] #uh why so complicated"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "remember this: Python lists count from zero. Everything related to computer memory counts from 0. only Maniacs count from 1.\n",
+    "\n",
+    "also a tip for me actually, for i struggle with matrix rows and columns: `m2d[0,:]` is first Row. `m2d[:, 0]` is first Column.  \n",
+    "row goes across. row number x is counted top down. Column goes top down. column number x is counted left to right "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### numpy array (matrix) operations\n",
+    "\n",
+    "the slides (and numpy also) have all the shit: the slice which we just covered, np.transpose `'`, np.matmul `*`, np.multiply `.*`, matrix divide `/` with np.dot and np.linarg.inv, np.divide `./`, concat arrays with np.concatenate np.stack or np.block etc.\n",
+    "\n",
+    "### math functions\n",
+    "\n",
+    "infinitely easier than matlab with python def\n",
+    "\n",
+    "you know exactly what this means:\n",
+    "\n",
+    "```python\n",
+    "def function(x):\n",
+    "    return 3*x + 2\n",
+    "```\n",
+    "this WILL work with ndarrays as they do have `__mul__` `__rmul__` and `__add__`\n",
+    "\n",
+    "as opposed to matlab with its cumbersome ahh syms\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}