Add initial version of chapter 11, part 4
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9 changed files with 2927 additions and 222 deletions
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@ -808,7 +808,7 @@
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}
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"source": [
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"Every instance comes with a special `.__class__` attribute that also references the corresponding class object."
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"`v`'s semantic \"value\" is not so clear yet. We fix this in the next section."
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"outputs": [
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{
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"data": {
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"text/plain": [
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"__main__.Vector"
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]
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"execution_count": 21,
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"metadata": {},
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"output_type": "execute_result"
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],
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"source": [
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"v.__class__"
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]
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{
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"cell_type": "markdown",
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"source": [
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"`v`'s semantic \"value\" is not so clear yet. We fix this in the next section."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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"outputs": [
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{
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"data": {
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@ -861,7 +826,7 @@
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"<__main__.Vector at 0x7f9b9416d760>"
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]
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},
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"execution_count": 22,
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"execution_count": 21,
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"metadata": {},
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"output_type": "execute_result"
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@ -885,7 +850,7 @@
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{
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"cell_type": "code",
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"execution_count": 23,
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"execution_count": 22,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -910,7 +875,7 @@
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{
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"cell_type": "code",
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"execution_count": 24,
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"execution_count": 23,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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@ -946,7 +911,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"execution_count": 24,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -983,7 +948,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"execution_count": 25,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -996,7 +961,7 @@
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"[1.0, 2.0, 3.0]"
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]
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},
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"execution_count": 26,
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"execution_count": 25,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -1031,7 +996,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"execution_count": 26,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -1042,6 +1007,30 @@
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"x = 1, 2, 3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(1, 2, 3)"
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]
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},
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"execution_count": 27,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"x"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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@ -1062,30 +1051,6 @@
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"output_type": "execute_result"
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}
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],
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"source": [
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"x"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(1, 2, 3)"
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]
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},
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"execution_count": 29,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"(1, 2, 3)"
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]
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@ -1103,7 +1068,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"execution_count": 29,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -1144,7 +1109,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"execution_count": 30,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -1157,7 +1122,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 32,
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"execution_count": 31,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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@ -1170,7 +1135,7 @@
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"Vector((1.000, 2.000, 3.000))"
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]
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},
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"execution_count": 32,
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"execution_count": 31,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -1192,7 +1157,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"execution_count": 32,
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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@ -1205,7 +1170,7 @@
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"Vector((1.000, 2.000, 3.000))"
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]
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},
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"execution_count": 33,
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"execution_count": 32,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -1227,7 +1192,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"execution_count": 33,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -1240,7 +1205,7 @@
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"'Vector((1.000, 2.000, 3.000))'"
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]
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},
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"execution_count": 34,
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"execution_count": 33,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -1266,7 +1231,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 35,
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"execution_count": 34,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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@ -1279,7 +1244,7 @@
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"'Vector(1.0, ..., 3.0)[3]'"
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]
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},
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"execution_count": 35,
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"execution_count": 34,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -1301,7 +1266,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 36,
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"execution_count": 35,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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@ -1342,14 +1307,14 @@
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}
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},
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"source": [
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"Below is a first implementation of the `Matrix` class that stores the entries internally as a `list` of `list`s.\n",
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"Below is a first implementation of the `Matrix` class that stores the `._entries` internally as a `list` of `list`s.\n",
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"\n",
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"The `.__init__()` method ensures that all the rows come with the same number of columns. Again, we do not allow `Matrix` instances without any entries."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"execution_count": 36,
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"metadata": {
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"code_folding": [],
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"slideshow": {
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@ -1391,7 +1356,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"execution_count": 37,
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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@ -1404,7 +1369,7 @@
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"94113690738160"
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]
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},
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"execution_count": 38,
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"execution_count": 37,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -1413,6 +1378,30 @@
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"id(Matrix)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"type"
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]
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},
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"execution_count": 38,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"type(Matrix)"
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]
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},
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"cell_type": "code",
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"execution_count": 39,
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@ -1421,30 +1410,6 @@
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"slide_type": "skip"
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}
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"outputs": [
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{
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"data": {
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"text/plain": [
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"type"
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]
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},
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"execution_count": 39,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"type(Matrix)"
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]
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{
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"cell_type": "code",
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"execution_count": 40,
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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}
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"outputs": [
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{
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"data": {
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"__main__.Matrix"
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]
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},
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"execution_count": 40,
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"execution_count": 39,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 41,
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"execution_count": 40,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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},
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{
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"cell_type": "code",
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"execution_count": 42,
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"execution_count": 41,
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"metadata": {
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"slideshow": {
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"slide_type": "skip"
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"140306180401856"
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]
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},
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"execution_count": 42,
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"execution_count": 41,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 43,
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"execution_count": 42,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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"__main__.Matrix"
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]
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},
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"execution_count": 43,
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"execution_count": 42,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 44,
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"execution_count": 43,
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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"Matrix(((1.000, 2.000, 3.000,), (4.000, 5.000, 6.000,), (7.000, 8.000, 9.000,)))"
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]
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},
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"execution_count": 44,
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"execution_count": 43,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"metadata": {
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"slideshow": {
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"slide_type": "fragment"
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{
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"cell_type": "code",
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"execution_count": 45,
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"metadata": {
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"slideshow": {
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},
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"cell_type": "code",
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"execution_count": 47,
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"execution_count": 46,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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"source": [
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"The methods we have seen so far are all **instance methods**. The characteristic idea behind an instance method is that the behavior it provides either depends on the state of a concrete instance or mutates it. In other words, an instance method *always* works with attributes on the `self` argument. If a method does *not* need access to `self` to do its job, it is conceptually *not* an instance method and we should probably convert it into another kind of method as shown below.\n",
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"\n",
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"An example of an instance method from linear algebra is the `.transpose()` method below that switches the rows and columns of an *existing* `Matrix` instance and returns a *new* `Matrix` instance based off that. It is implemented by passing the *iterator* created with the [zip() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#zip) built-in as the `data` argument to the `Matrix` constructor: The expression `zip(*self._entries)` may be a bit hard to understand because of the involved unpacking but simply flips a `Vector`'s rows and columns. The built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor within the `.__init__()` method then materializes the iterator into the `._entries`. Without a concrete `Matrix`'s rows and columns, `.transpose()` does not make sense, conceptually speaking."
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"An example of an instance method from linear algebra is the `.transpose()` method below that switches the rows and columns of an *existing* `Matrix` instance and returns a *new* `Matrix` instance based off that. It is implemented by passing the *iterator* created with the [zip() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#zip) built-in as the `data` argument to the `Matrix` constructor: The expression `zip(*self._entries)` may be a bit hard to understand because of the involved unpacking but simply flips a `Matrix`'s rows and columns. The built-in [list() <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://docs.python.org/3/library/functions.html#func-list) constructor within the `.__init__()` method then materializes the iterator into the `._entries` attribute. Without a concrete `Matrix`'s rows and columns, `.transpose()` does not make sense, conceptually speaking.\n",
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"\n",
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"Also, we see that it is ok to reference a class from within one of its methods. While this seems trivial to some readers, others may find this confusing. The final versions of the `Vector` and `Matrix` classes in the [fourth part <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_nb.png\">](https://nbviewer.jupyter.org/github/webartifex/intro-to-python/blob/develop/11_classes/04_content.ipynb#The-final-Vector-and-Matrix-Classes) of this chapter show how this \"hard coded\" redundancy can be avoided."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"execution_count": 47,
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"metadata": {
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"slideshow": {
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"slide_type": "slide"
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@ -1713,7 +1680,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 49,
|
||||
"execution_count": 48,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "slide"
|
||||
|
|
@ -1724,6 +1691,30 @@
|
|||
"m = Matrix([(1, 2, 3), (4, 5, 6), (7, 8, 9)])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 49,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "fragment"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Matrix(((1.000, 2.000, 3.000,), (4.000, 5.000, 6.000,), (7.000, 8.000, 9.000,)))"
|
||||
]
|
||||
},
|
||||
"execution_count": 49,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"m"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 50,
|
||||
|
|
@ -1732,30 +1723,6 @@
|
|||
"slide_type": "fragment"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Matrix(((1.000, 2.000, 3.000,), (4.000, 5.000, 6.000,), (7.000, 8.000, 9.000,)))"
|
||||
]
|
||||
},
|
||||
"execution_count": 50,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"m"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 51,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "fragment"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
|
|
@ -1763,7 +1730,7 @@
|
|||
"Matrix(((1.000, 4.000, 7.000,), (2.000, 5.000, 8.000,), (3.000, 6.000, 9.000,)))"
|
||||
]
|
||||
},
|
||||
"execution_count": 51,
|
||||
"execution_count": 50,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -1785,7 +1752,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 52,
|
||||
"execution_count": 51,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "slide"
|
||||
|
|
@ -1796,6 +1763,30 @@
|
|||
"n = m.transpose().transpose()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 52,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "fragment"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Matrix(((1.000, 2.000, 3.000,), (4.000, 5.000, 6.000,), (7.000, 8.000, 9.000,)))"
|
||||
]
|
||||
},
|
||||
"execution_count": 52,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 53,
|
||||
|
|
@ -1808,7 +1799,7 @@
|
|||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Matrix(((1.000, 2.000, 3.000,), (4.000, 5.000, 6.000,), (7.000, 8.000, 9.000,)))"
|
||||
"False"
|
||||
]
|
||||
},
|
||||
"execution_count": 53,
|
||||
|
|
@ -1817,7 +1808,18 @@
|
|||
}
|
||||
],
|
||||
"source": [
|
||||
"n"
|
||||
"m is n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "skip"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"Unintuitively, the comparison operator `==` returns a wrong result as `m` and `n` have `_entries` attributes that compare equal. We fix this in the \"*Operator Overloading*\" section later in this chapter."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -1840,41 +1842,6 @@
|
|||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"m is n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "skip"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"Unintuitively, the comparison operator `==` returns a wrong result as `m` and `n` have `_entries` attributes that compare equal. We fix this in the \"*Operator Overloading*\" section later in this chapter."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 55,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "fragment"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"False"
|
||||
]
|
||||
},
|
||||
"execution_count": 55,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"m == n"
|
||||
]
|
||||
|
|
@ -1894,7 +1861,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 56,
|
||||
"execution_count": 55,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "slide"
|
||||
|
|
@ -1933,7 +1900,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 57,
|
||||
"execution_count": 56,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "slide"
|
||||
|
|
@ -1946,7 +1913,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 58,
|
||||
"execution_count": 57,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "fragment"
|
||||
|
|
@ -1959,7 +1926,7 @@
|
|||
"Matrix(((1.000, 2.000, 3.000,), (4.000, 5.000, 6.000,), (7.000, 8.000, 9.000,)))"
|
||||
]
|
||||
},
|
||||
"execution_count": 58,
|
||||
"execution_count": 57,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -2007,7 +1974,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 59,
|
||||
"execution_count": 58,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "slide"
|
||||
|
|
@ -2051,7 +2018,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 60,
|
||||
"execution_count": 59,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "slide"
|
||||
|
|
@ -2064,7 +2031,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 61,
|
||||
"execution_count": 60,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "fragment"
|
||||
|
|
@ -2077,7 +2044,7 @@
|
|||
"(2, 3)"
|
||||
]
|
||||
},
|
||||
"execution_count": 61,
|
||||
"execution_count": 60,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -2099,7 +2066,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 62,
|
||||
"execution_count": 61,
|
||||
"metadata": {
|
||||
"slideshow": {
|
||||
"slide_type": "fragment"
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue