diff --git a/3exercises/ex23.py b/3exercises/ex23.py new file mode 100644 index 0000000..1c4c135 --- /dev/null +++ b/3exercises/ex23.py @@ -0,0 +1,23 @@ +import sys +script, input_encoding, error = sys.argv + + +def main(language_file, encoding, errors): # Define "main" function. + line = language_file.readline() # Read 1 line. + + if line: # If this is true (which it will be as long as it is not the end of the file) + print_line(line, encoding, errors) # Call print_line function + return main(language_file, encoding, errors) # Call this function, the if statement will keep it from being an infinite loop. An ingenious sort of "for loop". + + +def print_line(line, encoding, errors): # Define print line function, which does actual encoding of lanugages. + next_lang = line.strip() # Strip trailing \n + raw_bytes = next_lang.encode(encoding, errors=errors) # Encode language from languages.txt and ecode it into raw bytes. Pass encoding argument to encode() + cooked_string = raw_bytes.decode(encoding, errors=errors) # Decode from raw bytes to a string. + + print(raw_bytes, "<==>", cooked_string) # Print raw bytes on the left side, strings on the right. + + +languages = open("languages.txt", encoding="utf-8") # Open languages file. + +main(languages, input_encoding, error) # Run main function with current paramaters and kick-start the loop. diff --git a/3exercises/languages.txt b/3exercises/languages.txt new file mode 100644 index 0000000..6d47317 --- /dev/null +++ b/3exercises/languages.txt @@ -0,0 +1,97 @@ +Afrikaans +አማርኛ +Аҧсшәа +العربية +Aragonés +Arpetan +Azərbaycanca +Bamanankan +বাংলা +Bân-lâm-gú +Беларуская +Български +Boarisch +Bosanski +Буряад +Català +Чӑвашла +Čeština +Cymraeg +Dansk +Deutsch +Eesti +Ελληνικά +Español +Esperanto +فارسی +Français +Frysk +Gaelg +Gàidhlig +Galego +한국어 +Հայերեն +हिन्दी +Hrvatski +Ido +Interlingua +Italiano +עברית +ಕನ್ನಡ +Kapampangan +ქართული +Қазақша +Kreyòl ayisyen +Latgaļu +Latina +Latviešu +Lëtzebuergesch +Lietuvių +Magyar +Македонски +Malti +मराठी +მარგალური +مازِرونی +Bahasa Melayu +Монгол +Nederlands +नेपाल भाषा +日本語 +Norsk bokmål +Nouormand +Occitan +Oʻzbekcha/ўзбекча +ਪੰਜਾਬੀ +پنجابی +پښتو +Plattdüütsch +Polski +Português +Română +Romani +Русский +Seeltersk +Shqip +Simple English +Slovenčina +کوردیی ناوەندی +Српски / srpski +Suomi +Svenska +Tagalog +தமிழ் +ภาษาไทย +Taqbaylit +Татарча/tatarça +తెలుగు +Тоҷикӣ +Türkçe +Українська +اردو +Tiếng Việt +Võro +文言 +吴语 +ייִדיש +中文 diff --git a/Codecadmey Projects/Reggie's+Linear+Regression/.ipynb_checkpoints/Reggie_Linear_Regression_Skeleton-checkpoint.ipynb b/Codecadmey Projects/Reggie's+Linear+Regression/.ipynb_checkpoints/Reggie_Linear_Regression_Skeleton-checkpoint.ipynb index 301cceb..d45c819 100644 --- a/Codecadmey Projects/Reggie's+Linear+Regression/.ipynb_checkpoints/Reggie_Linear_Regression_Skeleton-checkpoint.ipynb +++ b/Codecadmey Projects/Reggie's+Linear+Regression/.ipynb_checkpoints/Reggie_Linear_Regression_Skeleton-checkpoint.ipynb @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -76,7 +76,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -103,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -113,7 +113,9 @@ "0\n", "1\n", "1\n", - "5\n" + "5\n", + "0.40000000000000036\n", + "0.0\n" ] } ], @@ -125,7 +127,9 @@ "#the point (3, 3) should be 1 unit away from the line y = x - 1:\n", "print(calculate_error(1, -1, (3, 3)))\n", "#the point (3, 3) should be 5 units away from the line y = -x + 1:\n", - "print(calculate_error(-1, 1, (3, 3)))" + "print(calculate_error(-1, 1, (3, 3)))\n", + "print(calculate_error(0.3, 1.7, (3, 3)))\n", + "print(calculate_error(1.0, 0.0, (3, 3)))" ] }, { @@ -139,7 +143,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -161,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -172,7 +176,7 @@ " for point in points:\n", " totalerror += calculate_error(m, b, point)\n", " \n", - " return totalerror" + " return abs(totalerror)" ] }, { @@ -184,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -249,12 +253,10 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ - "possible_ms = #your list comprehension here " + "possible_ms = [mv * 0.1 for mv in range(-100, 100)] #your list comprehension here " ] }, { @@ -267,12 +269,10 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ - 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16, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -345,12 +2788,14 @@ "3.5" ] }, - "execution_count": 16, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], - "source": [] + "source": [ + "get_y(0.3, 1.7, 6)" + ] }, { "cell_type": "markdown", @@ -361,12 +2806,50 @@ "Now, Reggie can use this model to predict the bounce of all kinds of sizes of balls he may choose to include in the ball pit!" ] }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.1" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_y(0.3, 1.7, 8)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.3999999999999995" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_y(0.3, 1.7, 9)" + ] + }, { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } diff --git a/Codecadmey Projects/Reggie's+Linear+Regression/Reggie_Linear_Regression_Skeleton.ipynb b/Codecadmey Projects/Reggie's+Linear+Regression/Reggie_Linear_Regression_Skeleton.ipynb index 301cceb..d45c819 100644 --- a/Codecadmey Projects/Reggie's+Linear+Regression/Reggie_Linear_Regression_Skeleton.ipynb +++ b/Codecadmey Projects/Reggie's+Linear+Regression/Reggie_Linear_Regression_Skeleton.ipynb @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -76,7 +76,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -103,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -113,7 +113,9 @@ "0\n", "1\n", "1\n", - "5\n" + "5\n", + "0.40000000000000036\n", + "0.0\n" ] } ], @@ -125,7 +127,9 @@ "#the point (3, 3) should be 1 unit away from the line y = x - 1:\n", "print(calculate_error(1, -1, (3, 3)))\n", "#the point (3, 3) should be 5 units away from the line y = -x + 1:\n", - "print(calculate_error(-1, 1, (3, 3)))" + "print(calculate_error(-1, 1, (3, 3)))\n", + "print(calculate_error(0.3, 1.7, (3, 3)))\n", + "print(calculate_error(1.0, 0.0, (3, 3)))" ] }, { @@ -139,7 +143,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -161,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -172,7 +176,7 @@ " for point in points:\n", " totalerror += calculate_error(m, b, point)\n", " \n", - " return totalerror" + " return abs(totalerror)" ] }, { @@ -184,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -249,12 +253,10 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ - "possible_ms = #your list comprehension here " + "possible_ms = [mv * 0.1 for mv in range(-100, 100)] #your list comprehension here " ] }, { @@ -267,12 +269,10 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ - "possible_bs = #your list comprehension here" + "possible_bs = [bv * 0.1 for bv in range(-200, 200)] #your list comprehension here" ] }, { @@ -300,18 +300,2461 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "0.30000000000000004 1.7000000000000002 4.999999999999999\n" + "168.0\n", + "-10.0\n", + "-20.0\n", + "167.60000000000002\n", + "-10.0\n", + "-19.900000000000002\n", + "167.2\n", + "-10.0\n", + "-19.8\n", + "166.8\n", + 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0\n", + "\n", + "for m in possible_ms:\n", + " for b in possible_bs:\n", + " err = calculate_all_error(m, b, datapoints)\n", + " if smallest_error > err:\n", + " smallest_error = err\n", + " print(smallest_error)\n", + " best_m = m\n", + " print(best_m)\n", + " best_b = b\n", + " print(best_b)\n", + " \n", + "print(best_m)\n", + "print(best_b)\n", + "print(smallest_error)\n", + " " + ] }, { "cell_type": "markdown", @@ -336,7 +2779,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -345,12 +2788,14 @@ "3.5" ] }, - "execution_count": 16, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], - "source": [] + "source": [ + "get_y(0.3, 1.7, 6)" + ] }, { "cell_type": "markdown", @@ -361,12 +2806,50 @@ "Now, Reggie can use this model to predict the bounce of all kinds of sizes of balls he may choose to include in the ball pit!" ] }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.1" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_y(0.3, 1.7, 8)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.3999999999999995" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_y(0.3, 1.7, 9)" + ] + }, { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] }