diff --git a/lectures/04_NLResistiveCompanion/NL_RC.html b/lectures/04_NLResistiveCompanion/Lecture_SimExample_NLResistiveCompanion.html
similarity index 71%
rename from lectures/04_NLResistiveCompanion/NL_RC.html
rename to lectures/04_NLResistiveCompanion/Lecture_SimExample_NLResistiveCompanion.html
index 86a59f34ec92850511215489272116050f5fb366..b7a27752201ca251784dca64f31b6f632d30dc0c 100644
--- a/lectures/04_NLResistiveCompanion/NL_RC.html
+++ b/lectures/04_NLResistiveCompanion/Lecture_SimExample_NLResistiveCompanion.html
@@ -1,9 +1,14 @@
<!DOCTYPE html>
<html>
-<head><meta charset="utf-8" />
-<title>NL_RC</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
+<head><meta charset="utf-8">
+
+<title>Lecture_SimExample_NLResistiveCompanion</title>
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>
+
+
<style type="text/css">
/*!
*
@@ -199,7 +204,6 @@ th {
*:before,
*:after {
background: transparent !important;
- color: #000 !important;
box-shadow: none !important;
text-shadow: none !important;
}
@@ -6744,15 +6748,15 @@ button.close {
*
*/
/*!
- * Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
+ * Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
* License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
*/
/* FONT PATH
* -------------------------- */
@font-face {
font-family: 'FontAwesome';
- src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
- src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
+ src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
+ src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
font-weight: normal;
font-style: normal;
}
@@ -6809,6 +6813,19 @@ button.close {
border: solid 0.08em #eee;
border-radius: .1em;
}
+.fa-pull-left {
+ float: left;
+}
+.fa-pull-right {
+ float: right;
+}
+.fa.fa-pull-left {
+ margin-right: .3em;
+}
+.fa.fa-pull-right {
+ margin-left: .3em;
+}
+/* Deprecated as of 4.4.0 */
.pull-right {
float: right;
}
@@ -6825,6 +6842,10 @@ button.close {
-webkit-animation: fa-spin 2s infinite linear;
animation: fa-spin 2s infinite linear;
}
+.fa-pulse {
+ -webkit-animation: fa-spin 1s infinite steps(8);
+ animation: fa-spin 1s infinite steps(8);
+}
@-webkit-keyframes fa-spin {
0% {
-webkit-transform: rotate(0deg);
@@ -6846,31 +6867,31 @@ button.close {
}
}
.fa-rotate-90 {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
-webkit-transform: rotate(90deg);
-ms-transform: rotate(90deg);
transform: rotate(90deg);
}
.fa-rotate-180 {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
-webkit-transform: rotate(180deg);
-ms-transform: rotate(180deg);
transform: rotate(180deg);
}
.fa-rotate-270 {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
-webkit-transform: rotate(270deg);
-ms-transform: rotate(270deg);
transform: rotate(270deg);
}
.fa-flip-horizontal {
- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
-webkit-transform: scale(-1, 1);
-ms-transform: scale(-1, 1);
transform: scale(-1, 1);
}
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- filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
-webkit-transform: scale(1, -1);
-ms-transform: scale(1, -1);
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@@ -7355,6 +7376,7 @@ button.close {
.fa-twitter:before {
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+.fa-facebook-f:before,
.fa-facebook:before {
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@@ -7367,6 +7389,7 @@ button.close {
.fa-credit-card:before {
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}
+.fa-feed:before,
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@@ -8004,7 +8027,8 @@ button.close {
.fa-male:before {
content: "\f183";
}
-.fa-gittip:before {
+.fa-gittip:before,
+.fa-gratipay:before {
content: "\f184";
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.fa-sun-o:before {
@@ -8108,7 +8132,7 @@ button.close {
.fa-digg:before {
content: "\f1a6";
}
-.fa-pied-piper:before {
+.fa-pied-piper-pp:before {
content: "\f1a7";
}
.fa-pied-piper-alt:before {
@@ -8234,6 +8258,7 @@ button.close {
content: "\f1ce";
}
.fa-ra:before,
+.fa-resistance:before,
.fa-rebel:before {
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@@ -8247,6 +8272,8 @@ button.close {
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content: "\f1d3";
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+.fa-y-combinator-square:before,
+.fa-yc-square:before,
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@@ -8415,6 +8442,657 @@ button.close {
.fa-meanpath:before {
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}
+.fa-buysellads:before {
+ content: "\f20d";
+}
+.fa-connectdevelop:before {
+ content: "\f20e";
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+ content: "\f210";
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+ content: "\f211";
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+.fa-leanpub:before {
+ content: "\f212";
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+.fa-sellsy:before {
+ content: "\f213";
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+ content: "\f214";
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+ content: "\f215";
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+ content: "\f21a";
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+ content: "\f21b";
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+.fa-motorcycle:before {
+ content: "\f21c";
+}
+.fa-street-view:before {
+ content: "\f21d";
+}
+.fa-heartbeat:before {
+ content: "\f21e";
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+ content: "\f221";
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+ content: "\f222";
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+ content: "\f224";
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+ content: "\f229";
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+.fa-mars-stroke-v:before {
+ content: "\f22a";
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+ content: "\f22b";
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+ content: "\f22c";
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+ content: "\f22d";
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+ content: "\f230";
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+ content: "\f232";
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+ content: "\f234";
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+ content: "\f235";
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+.fa-hotel:before,
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+ content: "\f236";
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+ content: "\f237";
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+.fa-train:before {
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+ content: "\f23b";
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+ content: "\f242";
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+ content: "\f2ca";
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+.fa-shower:before {
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+ content: "\f2da";
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+.fa-microchip:before {
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+}
+.fa-wpexplorer:before {
+ content: "\f2de";
+}
+.fa-meetup:before {
+ content: "\f2e0";
+}
+.sr-only {
+ position: absolute;
+ width: 1px;
+ height: 1px;
+ padding: 0;
+ margin: -1px;
+ overflow: hidden;
+ clip: rect(0, 0, 0, 0);
+ border: 0;
+}
+.sr-only-focusable:active,
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+ position: static;
+ width: auto;
+ height: auto;
+ margin: 0;
+ overflow: visible;
+ clip: auto;
+}
+.sr-only-focusable:active,
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+ overflow: visible;
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/*!
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@@ -8694,6 +9372,10 @@ div.traceback-wrapper {
max-width: 800px;
margin: auto;
}
+div.traceback-wrapper pre.traceback {
+ max-height: 600px;
+ overflow: auto;
+}
/**
* Primary styles
*
@@ -8719,6 +9401,10 @@ body > #header {
z-index: 100;
}
body > #header #header-container {
+ display: flex;
+ flex-direction: row;
+ justify-content: space-between;
+ padding: 5px;
padding-bottom: 5px;
padding-top: 5px;
box-sizing: border-box;
@@ -8750,13 +9436,16 @@ body > #header .header-bar {
padding-top: 1px;
padding-bottom: 1px;
}
-@media (max-width: 991px) {
- #ipython_notebook {
- margin-left: 10px;
- }
-}
[dir="rtl"] #ipython_notebook {
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+ margin-left: 0;
+}
+[dir="rtl"] #ipython_notebook.pull-left {
float: right !important;
+ float: right;
+}
+.flex-spacer {
+ flex: 1;
}
#noscript {
width: auto;
@@ -8791,9 +9480,15 @@ body > #header .header-bar {
input.ui-button {
padding: 0.3em 0.9em;
}
+span#kernel_logo_widget {
+ margin: 0 10px;
+}
span#login_widget {
float: right;
}
+[dir="rtl"] span#login_widget {
+ float: left;
+}
span#login_widget > .button,
#logout {
color: #333;
@@ -8908,6 +9603,9 @@ span#login_widget > .button .badge,
overflow: auto;
flex: 1;
}
+.modal-header {
+ cursor: move;
+}
@media (min-width: 768px) {
.modal .modal-dialog {
width: 700px;
@@ -8928,6 +9626,19 @@ span#login_widget > .button .badge,
display: inline-block;
margin-bottom: -4px;
}
+[dir="rtl"] .center-nav form.pull-left {
+ float: right !important;
+ float: right;
+}
+[dir="rtl"] .center-nav .navbar-text {
+ float: right;
+}
+[dir="rtl"] .navbar-inner {
+ text-align: right;
+}
+[dir="rtl"] div.text-left {
+ text-align: right;
+}
/*!
*
* IPython tree view
@@ -8944,35 +9655,43 @@ span#login_widget > .button .badge,
margin: 0;
}
.alternate_upload input.fileinput {
- text-align: center;
- vertical-align: middle;
- display: inline;
+ position: absolute;
+ display: block;
+ width: 100%;
+ height: 100%;
+ overflow: hidden;
+ cursor: pointer;
opacity: 0;
z-index: 2;
- width: 12ex;
- margin-right: -12ex;
+}
+.alternate_upload .btn-xs > input.fileinput {
+ margin: -1px -5px;
}
.alternate_upload .btn-upload {
+ position: relative;
height: 22px;
}
+::-webkit-file-upload-button {
+ cursor: pointer;
+}
/**
* Primary styles
*
* Author: Jupyter Development Team
*/
-[dir="rtl"] #tabs li {
- float: right;
-}
ul#tabs {
margin-bottom: 4px;
}
-[dir="rtl"] ul#tabs {
- margin-right: 0px;
-}
ul#tabs a {
padding-top: 6px;
padding-bottom: 4px;
}
+[dir="rtl"] ul#tabs.nav-tabs > li {
+ float: right;
+}
+[dir="rtl"] ul#tabs.nav.nav-tabs {
+ padding-right: 0;
+}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
text-decoration: none;
@@ -8991,15 +9710,13 @@ ul.breadcrumb span {
.list_toolbar .tree-buttons {
padding-top: 1px;
}
-[dir="rtl"] .list_toolbar .tree-buttons {
- float: left !important;
-}
-[dir="rtl"] .list_toolbar .pull-right {
- padding-top: 1px;
+[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
float: left !important;
+ float: left;
}
-[dir="rtl"] .list_toolbar .pull-left {
- float: right !important;
+[dir="rtl"] .list_toolbar .col-sm-4,
+[dir="rtl"] .list_toolbar .col-sm-8 {
+ float: right;
}
.dynamic-buttons {
padding-top: 3px;
@@ -9055,7 +9772,7 @@ ul.breadcrumb span {
.list_item > div input {
margin-right: 7px;
margin-left: 14px;
- vertical-align: baseline;
+ vertical-align: text-bottom;
line-height: 22px;
position: relative;
top: -1px;
@@ -9066,6 +9783,9 @@ ul.breadcrumb span {
vertical-align: baseline;
line-height: 22px;
}
+[dir="rtl"] .list_item > div input {
+ margin-right: 0;
+}
.new-file input[type=checkbox] {
visibility: hidden;
}
@@ -9081,6 +9801,14 @@ ul.breadcrumb span {
line-height: 22px;
vertical-align: baseline;
}
+.item_modified {
+ margin-right: 7px;
+ margin-left: 7px;
+}
+[dir="rtl"] .item_modified.pull-right {
+ float: left !important;
+ float: left;
+}
.item_buttons {
line-height: 1em;
margin-left: -5px;
@@ -9108,6 +9836,14 @@ ul.breadcrumb span {
margin-right: 7px;
float: left;
}
+[dir="rtl"] .item_buttons.pull-right {
+ float: left !important;
+ float: left;
+}
+[dir="rtl"] .item_buttons .kernel-name {
+ margin-left: 7px;
+ float: right;
+}
.toolbar_info {
height: 24px;
line-height: 24px;
@@ -9133,18 +9869,32 @@ ul.breadcrumb span {
background-color: transparent;
font-weight: bold;
}
+.sort_button {
+ display: inline-block;
+ padding-left: 7px;
+}
+[dir="rtl"] .sort_button.pull-right {
+ float: left !important;
+ float: left;
+}
#tree-selector {
padding-right: 0px;
}
-[dir="rtl"] #tree-selector a {
- float: right;
-}
#button-select-all {
min-width: 50px;
}
+[dir="rtl"] #button-select-all.btn {
+ float: right ;
+}
#select-all {
margin-left: 7px;
margin-right: 2px;
+ margin-top: 2px;
+ height: 16px;
+}
+[dir="rtl"] #select-all.pull-left {
+ float: right !important;
+ float: right;
}
.menu_icon {
margin-right: 2px;
@@ -9162,6 +9912,12 @@ ul.breadcrumb span {
-moz-osx-font-smoothing: grayscale;
content: "\f114";
}
+.folder_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.folder_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.folder_icon:before.pull-left {
margin-right: .3em;
}
@@ -9179,6 +9935,12 @@ ul.breadcrumb span {
position: relative;
top: -1px;
}
+.notebook_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.notebook_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.notebook_icon:before.pull-left {
margin-right: .3em;
}
@@ -9197,6 +9959,12 @@ ul.breadcrumb span {
top: -1px;
color: #5cb85c;
}
+.running_notebook_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.running_notebook_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.running_notebook_icon:before.pull-left {
margin-right: .3em;
}
@@ -9214,6 +9982,12 @@ ul.breadcrumb span {
position: relative;
top: -2px;
}
+.file_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.file_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.file_icon:before.pull-left {
margin-right: .3em;
}
@@ -9228,8 +10002,11 @@ ul#new-menu {
left: auto;
right: 0;
}
-[dir="rtl"] #new-menu {
- text-align: right;
+#new-menu .dropdown-header {
+ font-size: 10px;
+ border-bottom: 1px solid #e5e5e5;
+ padding: 0 0 3px;
+ margin: -3px 20px 0;
}
.kernel-menu-icon {
padding-right: 12px;
@@ -9276,9 +10053,6 @@ ul#new-menu {
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
border-bottom: 0px;
}
-[dir="rtl"] #running .col-sm-8 {
- float: right !important;
-}
.delete-button {
display: none;
}
@@ -9288,6 +10062,12 @@ ul#new-menu {
.rename-button {
display: none;
}
+.move-button {
+ display: none;
+}
+.download-button {
+ display: none;
+}
.shutdown-button {
display: none;
}
@@ -9328,6 +10108,12 @@ ul#new-menu {
-moz-osx-font-smoothing: grayscale;
width: 20px;
}
+.dirty-indicator.fa-pull-left {
+ margin-right: .3em;
+}
+.dirty-indicator.fa-pull-right {
+ margin-left: .3em;
+}
.dirty-indicator.pull-left {
margin-right: .3em;
}
@@ -9343,6 +10129,12 @@ ul#new-menu {
-moz-osx-font-smoothing: grayscale;
width: 20px;
}
+.dirty-indicator-dirty.fa-pull-left {
+ margin-right: .3em;
+}
+.dirty-indicator-dirty.fa-pull-right {
+ margin-left: .3em;
+}
.dirty-indicator-dirty.pull-left {
margin-right: .3em;
}
@@ -9358,6 +10150,12 @@ ul#new-menu {
-moz-osx-font-smoothing: grayscale;
width: 20px;
}
+.dirty-indicator-clean.fa-pull-left {
+ margin-right: .3em;
+}
+.dirty-indicator-clean.fa-pull-right {
+ margin-left: .3em;
+}
.dirty-indicator-clean.pull-left {
margin-right: .3em;
}
@@ -9373,6 +10171,12 @@ ul#new-menu {
-moz-osx-font-smoothing: grayscale;
content: "\f00c";
}
+.dirty-indicator-clean:before.fa-pull-left {
+ margin-right: .3em;
+}
+.dirty-indicator-clean:before.fa-pull-right {
+ margin-left: .3em;
+}
.dirty-indicator-clean:before.pull-left {
margin-right: .3em;
}
@@ -9417,15 +10221,133 @@ ul#new-menu {
box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
}
+.CodeMirror-dialog {
+ background-color: #fff;
+}
/*!
*
* IPython notebook
*
*/
-/* CSS font colors for translated ANSI colors. */
+/* CSS font colors for translated ANSI escape sequences */
+/* The color values are a mix of
+ http://www.xcolors.net/dl/baskerville-ivorylight and
+ http://www.xcolors.net/dl/euphrasia */
+.ansi-black-fg {
+ color: #3E424D;
+}
+.ansi-black-bg {
+ background-color: #3E424D;
+}
+.ansi-black-intense-fg {
+ color: #282C36;
+}
+.ansi-black-intense-bg {
+ background-color: #282C36;
+}
+.ansi-red-fg {
+ color: #E75C58;
+}
+.ansi-red-bg {
+ background-color: #E75C58;
+}
+.ansi-red-intense-fg {
+ color: #B22B31;
+}
+.ansi-red-intense-bg {
+ background-color: #B22B31;
+}
+.ansi-green-fg {
+ color: #00A250;
+}
+.ansi-green-bg {
+ background-color: #00A250;
+}
+.ansi-green-intense-fg {
+ color: #007427;
+}
+.ansi-green-intense-bg {
+ background-color: #007427;
+}
+.ansi-yellow-fg {
+ color: #DDB62B;
+}
+.ansi-yellow-bg {
+ background-color: #DDB62B;
+}
+.ansi-yellow-intense-fg {
+ color: #B27D12;
+}
+.ansi-yellow-intense-bg {
+ background-color: #B27D12;
+}
+.ansi-blue-fg {
+ color: #208FFB;
+}
+.ansi-blue-bg {
+ background-color: #208FFB;
+}
+.ansi-blue-intense-fg {
+ color: #0065CA;
+}
+.ansi-blue-intense-bg {
+ background-color: #0065CA;
+}
+.ansi-magenta-fg {
+ color: #D160C4;
+}
+.ansi-magenta-bg {
+ background-color: #D160C4;
+}
+.ansi-magenta-intense-fg {
+ color: #A03196;
+}
+.ansi-magenta-intense-bg {
+ background-color: #A03196;
+}
+.ansi-cyan-fg {
+ color: #60C6C8;
+}
+.ansi-cyan-bg {
+ background-color: #60C6C8;
+}
+.ansi-cyan-intense-fg {
+ color: #258F8F;
+}
+.ansi-cyan-intense-bg {
+ background-color: #258F8F;
+}
+.ansi-white-fg {
+ color: #C5C1B4;
+}
+.ansi-white-bg {
+ background-color: #C5C1B4;
+}
+.ansi-white-intense-fg {
+ color: #A1A6B2;
+}
+.ansi-white-intense-bg {
+ background-color: #A1A6B2;
+}
+.ansi-default-inverse-fg {
+ color: #FFFFFF;
+}
+.ansi-default-inverse-bg {
+ background-color: #000000;
+}
+.ansi-bold {
+ font-weight: bold;
+}
+.ansi-underline {
+ text-decoration: underline;
+}
+/* The following styles are deprecated an will be removed in a future version */
.ansibold {
font-weight: bold;
}
+.ansi-inverse {
+ outline: 0.5px dotted;
+}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
color: black;
@@ -9503,12 +10425,20 @@ div.cell {
/* This acts as a spacer between cells, that is outside the border */
margin: 0px;
outline: none;
- border-left-width: 1px;
- padding-left: 5px;
- background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
+ position: relative;
+ overflow: visible;
+}
+div.cell:before {
+ position: absolute;
+ display: block;
+ top: -1px;
+ left: -1px;
+ width: 5px;
+ height: calc(100% + 2px);
+ content: '';
+ background: transparent;
}
div.cell.jupyter-soft-selected {
- border-left-color: #90CAF9;
border-left-color: #E3F2FD;
border-left-width: 1px;
padding-left: 5px;
@@ -9521,27 +10451,39 @@ div.cell.jupyter-soft-selected {
border-color: transparent;
}
}
-div.cell.selected {
+div.cell.selected,
+div.cell.selected.jupyter-soft-selected {
border-color: #ababab;
- border-left-width: 0px;
- padding-left: 6px;
- background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
+}
+div.cell.selected:before,
+div.cell.selected.jupyter-soft-selected:before {
+ position: absolute;
+ display: block;
+ top: -1px;
+ left: -1px;
+ width: 5px;
+ height: calc(100% + 2px);
+ content: '';
+ background: #42A5F5;
}
@media print {
- div.cell.selected {
+ div.cell.selected,
+ div.cell.selected.jupyter-soft-selected {
border-color: transparent;
}
}
-div.cell.selected.jupyter-soft-selected {
- border-left-width: 0;
- padding-left: 6px;
- background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
-}
.edit_mode div.cell.selected {
border-color: #66BB6A;
- border-left-width: 0px;
- padding-left: 6px;
- background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
+}
+.edit_mode div.cell.selected:before {
+ position: absolute;
+ display: block;
+ top: -1px;
+ left: -1px;
+ width: 5px;
+ height: calc(100% + 2px);
+ content: '';
+ background: #66BB6A;
}
@media print {
.edit_mode div.cell.selected {
@@ -9737,7 +10679,9 @@ div.input_area > div.highlight > pre {
.CodeMirror-lines {
/* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
/* we have set a different line-height and want this to scale with that. */
- padding: 0.4em;
+ /* Note that this should set vertical padding only, since CodeMirror assumes
+ that horizontal padding will be set on CodeMirror pre */
+ padding: 0.4em 0;
}
.CodeMirror-linenumber {
padding: 0 8px 0 4px;
@@ -9747,12 +10691,25 @@ div.input_area > div.highlight > pre {
border-top-left-radius: 2px;
}
.CodeMirror pre {
- /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
- /* .CodeMirror-lines */
- padding: 0;
+ /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
+ use .CodeMirror-lines for vertical */
+ padding: 0 0.4em;
border: 0;
border-radius: 0;
}
+.CodeMirror-cursor {
+ border-left: 1.4px solid black;
+}
+@media screen and (min-width: 2138px) and (max-width: 4319px) {
+ .CodeMirror-cursor {
+ border-left: 2px solid black;
+ }
+}
+@media screen and (min-width: 4320px) {
+ .CodeMirror-cursor {
+ border-left: 4px solid black;
+ }
+}
/*
Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
@@ -10005,6 +10962,9 @@ div.output_area img.unconfined,
div.output_area svg.unconfined {
max-width: none;
}
+div.output_area .mglyph > img {
+ max-width: none;
+}
/* This is needed to protect the pre formating from global settings such
as that of bootstrap */
.output {
@@ -10043,7 +11003,7 @@ div.output_area svg.unconfined {
}
div.output_area pre {
margin: 0;
- padding: 0;
+ padding: 1px 0 1px 0;
border: 0;
vertical-align: baseline;
color: black;
@@ -10203,39 +11163,35 @@ div.output_unrecognized a:hover {
.rendered_html h6:first-child {
margin-top: 1em;
}
+.rendered_html ul:not(.list-inline),
+.rendered_html ol:not(.list-inline) {
+ padding-left: 2em;
+}
.rendered_html ul {
list-style: disc;
- margin: 0em 2em;
- padding-left: 0px;
}
.rendered_html ul ul {
list-style: square;
- margin: 0em 2em;
+ margin-top: 0;
}
.rendered_html ul ul ul {
list-style: circle;
- margin: 0em 2em;
}
.rendered_html ol {
list-style: decimal;
- margin: 0em 2em;
- padding-left: 0px;
}
.rendered_html ol ol {
list-style: upper-alpha;
- margin: 0em 2em;
+ margin-top: 0;
}
.rendered_html ol ol ol {
list-style: lower-alpha;
- margin: 0em 2em;
}
.rendered_html ol ol ol ol {
list-style: lower-roman;
- margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
list-style: decimal;
- margin: 0em 2em;
}
.rendered_html * + ul {
margin-top: 1em;
@@ -10249,14 +11205,23 @@ div.output_unrecognized a:hover {
}
.rendered_html pre {
margin: 1em 2em;
+ padding: 0px;
+ background-color: #fff;
+}
+.rendered_html code {
+ background-color: #eff0f1;
+}
+.rendered_html p code {
+ padding: 1px 5px;
+}
+.rendered_html pre code {
+ background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
border: 0;
- background-color: #fff;
color: #000;
font-size: 100%;
- padding: 0px;
}
.rendered_html blockquote {
margin: 1em 2em;
@@ -10264,25 +11229,37 @@ div.output_unrecognized a:hover {
.rendered_html table {
margin-left: auto;
margin-right: auto;
- border: 1px solid black;
+ border: none;
border-collapse: collapse;
+ border-spacing: 0;
+ color: black;
+ font-size: 12px;
+ table-layout: fixed;
+}
+.rendered_html thead {
+ border-bottom: 1px solid black;
+ vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
- border: 1px solid black;
- border-collapse: collapse;
- margin: 1em 2em;
-}
-.rendered_html td,
-.rendered_html th {
- text-align: left;
+ text-align: right;
vertical-align: middle;
- padding: 4px;
+ padding: 0.5em 0.5em;
+ line-height: normal;
+ white-space: normal;
+ max-width: none;
+ border: none;
}
.rendered_html th {
font-weight: bold;
}
+.rendered_html tbody tr:nth-child(odd) {
+ background: #f5f5f5;
+}
+.rendered_html tbody tr:hover {
+ background: rgba(66, 165, 245, 0.2);
+}
.rendered_html * + table {
margin-top: 1em;
}
@@ -10309,6 +11286,15 @@ div.output_unrecognized a:hover {
.rendered_html svg.unconfined {
max-width: none;
}
+.rendered_html .alert {
+ margin-bottom: initial;
+}
+.rendered_html * + .alert {
+ margin-top: 1em;
+}
+[dir="rtl"] .rendered_html p {
+ text-align: right;
+}
div.text_cell {
/* Old browsers */
display: -webkit-box;
@@ -10362,9 +11348,18 @@ h6:hover .anchor-link {
overflow-x: auto;
overflow-y: hidden;
}
+.text_cell.rendered .rendered_html tr,
+.text_cell.rendered .rendered_html th,
+.text_cell.rendered .rendered_html td {
+ max-width: none;
+}
.text_cell.unrendered .text_cell_render {
display: none;
}
+.text_cell .dropzone .input_area {
+ border: 2px dashed #bababa;
+ margin: -1px;
+}
.cm-header-1,
.cm-header-2,
.cm-header-3,
@@ -10500,6 +11495,28 @@ kbd {
padding-top: 1px;
padding-bottom: 1px;
}
+.jupyter-keybindings {
+ padding: 1px;
+ line-height: 24px;
+ border-bottom: 1px solid gray;
+}
+.jupyter-keybindings input {
+ margin: 0;
+ padding: 0;
+ border: none;
+}
+.jupyter-keybindings i {
+ padding: 6px;
+}
+.well code {
+ background-color: #ffffff;
+ border-color: #ababab;
+ border-width: 1px;
+ border-style: solid;
+ padding: 2px;
+ padding-top: 1px;
+ padding-bottom: 1px;
+}
/* CSS for the cell toolbar */
.celltoolbar {
border: thin solid #CFCFCF;
@@ -10632,6 +11649,152 @@ select[multiple].celltoolbar select {
margin-left: 5px;
margin-right: 5px;
}
+.tags_button_container {
+ width: 100%;
+ display: flex;
+}
+.tag-container {
+ display: flex;
+ flex-direction: row;
+ flex-grow: 1;
+ overflow: hidden;
+ position: relative;
+}
+.tag-container > * {
+ margin: 0 4px;
+}
+.remove-tag-btn {
+ margin-left: 4px;
+}
+.tags-input {
+ display: flex;
+}
+.cell-tag:last-child:after {
+ content: "";
+ position: absolute;
+ right: 0;
+ width: 40px;
+ height: 100%;
+ /* Fade to background color of cell toolbar */
+ background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
+}
+.tags-input > * {
+ margin-left: 4px;
+}
+.cell-tag,
+.tags-input input,
+.tags-input button {
+ display: block;
+ width: 100%;
+ height: 32px;
+ padding: 6px 12px;
+ font-size: 13px;
+ line-height: 1.42857143;
+ color: #555555;
+ background-color: #fff;
+ background-image: none;
+ border: 1px solid #ccc;
+ border-radius: 2px;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+ -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+ transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+ height: 30px;
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 1px;
+ box-shadow: none;
+ width: inherit;
+ font-size: inherit;
+ height: 22px;
+ line-height: 22px;
+ padding: 0px 4px;
+ display: inline-block;
+}
+.cell-tag:focus,
+.tags-input input:focus,
+.tags-input button:focus {
+ border-color: #66afe9;
+ outline: 0;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+ box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+}
+.cell-tag::-moz-placeholder,
+.tags-input input::-moz-placeholder,
+.tags-input button::-moz-placeholder {
+ color: #999;
+ opacity: 1;
+}
+.cell-tag:-ms-input-placeholder,
+.tags-input input:-ms-input-placeholder,
+.tags-input button:-ms-input-placeholder {
+ color: #999;
+}
+.cell-tag::-webkit-input-placeholder,
+.tags-input input::-webkit-input-placeholder,
+.tags-input button::-webkit-input-placeholder {
+ color: #999;
+}
+.cell-tag::-ms-expand,
+.tags-input input::-ms-expand,
+.tags-input button::-ms-expand {
+ border: 0;
+ background-color: transparent;
+}
+.cell-tag[disabled],
+.tags-input input[disabled],
+.tags-input button[disabled],
+.cell-tag[readonly],
+.tags-input input[readonly],
+.tags-input button[readonly],
+fieldset[disabled] .cell-tag,
+fieldset[disabled] .tags-input input,
+fieldset[disabled] .tags-input button {
+ background-color: #eeeeee;
+ opacity: 1;
+}
+.cell-tag[disabled],
+.tags-input input[disabled],
+.tags-input button[disabled],
+fieldset[disabled] .cell-tag,
+fieldset[disabled] .tags-input input,
+fieldset[disabled] .tags-input button {
+ cursor: not-allowed;
+}
+textarea.cell-tag,
+textarea.tags-input input,
+textarea.tags-input button {
+ height: auto;
+}
+select.cell-tag,
+select.tags-input input,
+select.tags-input button {
+ height: 30px;
+ line-height: 30px;
+}
+textarea.cell-tag,
+textarea.tags-input input,
+textarea.tags-input button,
+select[multiple].cell-tag,
+select[multiple].tags-input input,
+select[multiple].tags-input button {
+ height: auto;
+}
+.cell-tag,
+.tags-input button {
+ padding: 0px 4px;
+}
+.cell-tag {
+ background-color: #fff;
+ white-space: nowrap;
+}
+.tags-input input[type=text]:focus {
+ outline: none;
+ box-shadow: none;
+ border-color: #ccc;
+}
.completions {
position: absolute;
z-index: 110;
@@ -10657,10 +11820,6 @@ select[multiple].celltoolbar select {
.completions select option.context {
color: #286090;
}
-#kernel_logo_widget {
- float: right !important;
- float: right;
-}
#kernel_logo_widget .current_kernel_logo {
display: none;
margin-top: -1px;
@@ -10668,6 +11827,22 @@ select[multiple].celltoolbar select {
width: 32px;
height: 32px;
}
+[dir="rtl"] #kernel_logo_widget {
+ float: left !important;
+ float: left;
+}
+.modal .modal-body .move-path {
+ display: flex;
+ flex-direction: row;
+ justify-content: space;
+ align-items: center;
+}
+.modal .modal-body .move-path .server-root {
+ padding-right: 20px;
+}
+.modal .modal-body .move-path .path-input {
+ flex: 1;
+}
#menubar {
box-sizing: border-box;
-moz-box-sizing: border-box;
@@ -10688,12 +11863,42 @@ select[multiple].celltoolbar select {
#menubar .navbar-collapse {
clear: left;
}
+[dir="rtl"] #menubar .navbar-toggle {
+ float: right;
+}
+[dir="rtl"] #menubar .navbar-collapse {
+ clear: right;
+}
+[dir="rtl"] #menubar .navbar-nav {
+ float: right;
+}
+[dir="rtl"] #menubar .nav {
+ padding-right: 0px;
+}
+[dir="rtl"] #menubar .navbar-nav > li {
+ float: right;
+}
+[dir="rtl"] #menubar .navbar-right {
+ float: left !important;
+}
+[dir="rtl"] ul.dropdown-menu {
+ text-align: right;
+ left: auto;
+}
+[dir="rtl"] ul#new-menu.dropdown-menu {
+ right: auto;
+ left: 0;
+}
.nav-wrapper {
border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
padding-top: 4px;
}
+[dir="rtl"] i.menu-icon.pull-right {
+ float: left !important;
+ float: left;
+}
ul#help_menu li a {
overflow: hidden;
padding-right: 2.2em;
@@ -10701,6 +11906,17 @@ ul#help_menu li a {
ul#help_menu li a i {
margin-right: -1.2em;
}
+[dir="rtl"] ul#help_menu li a {
+ padding-left: 2.2em;
+}
+[dir="rtl"] ul#help_menu li a i {
+ margin-right: 0;
+ margin-left: -1.2em;
+}
+[dir="rtl"] ul#help_menu li a i.pull-right {
+ float: left !important;
+ float: left;
+}
.dropdown-submenu {
position: relative;
}
@@ -10710,6 +11926,10 @@ ul#help_menu li a i {
margin-top: -6px;
margin-left: -1px;
}
+[dir="rtl"] .dropdown-submenu > .dropdown-menu {
+ right: 100%;
+ margin-right: -1px;
+}
.dropdown-submenu:hover > .dropdown-menu {
display: block;
}
@@ -10727,12 +11947,24 @@ ul#help_menu li a i {
margin-top: 2px;
margin-right: -10px;
}
+.dropdown-submenu > a:after.fa-pull-left {
+ margin-right: .3em;
+}
+.dropdown-submenu > a:after.fa-pull-right {
+ margin-left: .3em;
+}
.dropdown-submenu > a:after.pull-left {
margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
margin-left: .3em;
}
+[dir="rtl"] .dropdown-submenu > a:after {
+ float: left;
+ content: "\f0d9";
+ margin-right: 0;
+ margin-left: -10px;
+}
.dropdown-submenu:hover > a:after {
color: #262626;
}
@@ -10748,6 +11980,10 @@ ul#help_menu li a i {
float: right;
z-index: 10;
}
+[dir="rtl"] #notification_area {
+ float: left !important;
+ float: left;
+}
.indicator_area {
float: right !important;
float: right;
@@ -10759,6 +11995,10 @@ ul#help_menu li a i {
text-align: center;
width: auto;
}
+[dir="rtl"] .indicator_area {
+ float: left !important;
+ float: left;
+}
#kernel_indicator {
float: right !important;
float: right;
@@ -10775,6 +12015,12 @@ ul#help_menu li a i {
padding-left: 5px;
padding-right: 5px;
}
+[dir="rtl"] #kernel_indicator {
+ float: left !important;
+ float: left;
+ border-left: 0;
+ border-right: 1px solid;
+}
#modal_indicator {
float: right !important;
float: right;
@@ -10786,6 +12032,10 @@ ul#help_menu li a i {
text-align: center;
width: auto;
}
+[dir="rtl"] #modal_indicator {
+ float: left !important;
+ float: left;
+}
#readonly-indicator {
float: right !important;
float: right;
@@ -10815,6 +12065,12 @@ ul#help_menu li a i {
-moz-osx-font-smoothing: grayscale;
content: "\f040";
}
+.edit_mode .modal_indicator:before.fa-pull-left {
+ margin-right: .3em;
+}
+.edit_mode .modal_indicator:before.fa-pull-right {
+ margin-left: .3em;
+}
.edit_mode .modal_indicator:before.pull-left {
margin-right: .3em;
}
@@ -10830,6 +12086,12 @@ ul#help_menu li a i {
-moz-osx-font-smoothing: grayscale;
content: ' ';
}
+.command_mode .modal_indicator:before.fa-pull-left {
+ margin-right: .3em;
+}
+.command_mode .modal_indicator:before.fa-pull-right {
+ margin-left: .3em;
+}
.command_mode .modal_indicator:before.pull-left {
margin-right: .3em;
}
@@ -10845,6 +12107,12 @@ ul#help_menu li a i {
-moz-osx-font-smoothing: grayscale;
content: "\f10c";
}
+.kernel_idle_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.kernel_idle_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.kernel_idle_icon:before.pull-left {
margin-right: .3em;
}
@@ -10860,6 +12128,12 @@ ul#help_menu li a i {
-moz-osx-font-smoothing: grayscale;
content: "\f111";
}
+.kernel_busy_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.kernel_busy_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.kernel_busy_icon:before.pull-left {
margin-right: .3em;
}
@@ -10875,6 +12149,12 @@ ul#help_menu li a i {
-moz-osx-font-smoothing: grayscale;
content: "\f1e2";
}
+.kernel_dead_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.kernel_dead_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.kernel_dead_icon:before.pull-left {
margin-right: .3em;
}
@@ -10890,6 +12170,12 @@ ul#help_menu li a i {
-moz-osx-font-smoothing: grayscale;
content: "\f127";
}
+.kernel_disconnected_icon:before.fa-pull-left {
+ margin-right: .3em;
+}
+.kernel_disconnected_icon:before.fa-pull-right {
+ margin-left: .3em;
+}
.kernel_disconnected_icon:before.pull-left {
margin-right: .3em;
}
@@ -11279,27 +12565,46 @@ div#pager .ui-resizable-handle::after {
flex: 1;
}
span.save_widget {
- margin-top: 6px;
+ height: 30px;
+ margin-top: 4px;
+ display: flex;
+ justify-content: flex-start;
+ align-items: baseline;
+ width: 50%;
+ flex: 1;
}
span.save_widget span.filename {
- height: 1em;
+ height: 100%;
line-height: 1em;
- padding: 3px;
margin-left: 16px;
border: none;
font-size: 146.5%;
+ text-overflow: ellipsis;
+ overflow: hidden;
+ white-space: nowrap;
border-radius: 2px;
}
span.save_widget span.filename:hover {
background-color: #e6e6e6;
}
+[dir="rtl"] span.save_widget.pull-left {
+ float: right !important;
+ float: right;
+}
+[dir="rtl"] span.save_widget span.filename {
+ margin-left: 0;
+ margin-right: 16px;
+}
span.checkpoint_status,
span.autosave_status {
font-size: small;
+ white-space: nowrap;
+ padding: 0 5px;
}
@media (max-width: 767px) {
span.save_widget {
font-size: small;
+ padding: 0 0 0 5px;
}
span.checkpoint_status,
span.autosave_status {
@@ -11343,6 +12648,9 @@ span.autosave_status {
margin-top: 0px;
margin-left: 5px;
}
+.toolbar-btn-label {
+ margin-left: 6px;
+}
#maintoolbar {
margin-bottom: -3px;
margin-top: -8px;
@@ -11363,6 +12671,10 @@ span.autosave_status {
.select-xs {
height: 24px;
}
+[dir="rtl"] .btn-group > .btn,
+.btn-group-vertical > .btn {
+ float: right;
+}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
@@ -11512,6 +12824,10 @@ ul.typeahead-list i {
margin-left: -10px;
width: 18px;
}
+[dir="rtl"] ul.typeahead-list i {
+ margin-left: 0;
+ margin-right: -10px;
+}
ul.typeahead-list {
max-height: 80vh;
overflow: auto;
@@ -11521,6 +12837,13 @@ ul.typeahead-list > li > a {
/* see https://github.com/jupyter/notebook/issues/559 */
white-space: normal;
}
+ul.typeahead-list > li > a.pull-right {
+ float: left !important;
+ float: left;
+}
+[dir="rtl"] .typeahead-list {
+ text-align: right;
+}
.cmd-palette .modal-body {
padding: 7px;
}
@@ -11531,10 +12854,19 @@ ul.typeahead-list > li > a {
outline: none;
}
.no-shortcut {
- display: none;
+ min-width: 20px;
+ color: transparent;
+}
+[dir="rtl"] .no-shortcut.pull-right {
+ float: left !important;
+ float: left;
+}
+[dir="rtl"] .command-shortcut.pull-right {
+ float: left !important;
+ float: left;
}
.command-shortcut:before {
- content: "(command)";
+ content: "(command mode)";
padding-right: 3px;
color: #777777;
}
@@ -11543,6 +12875,10 @@ ul.typeahead-list > li > a {
padding-right: 3px;
color: #777777;
}
+[dir="rtl"] .edit-shortcut.pull-right {
+ float: left !important;
+ float: left;
+}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
background-color: #BBDEFB;
@@ -11551,6 +12887,12 @@ ul.typeahead-list > li > a {
border-width: 1px;
border-radius: 0px;
}
+[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
+ border-left: none;
+}
+[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
+ border-right: none;
+}
#find-and-replace #replace-preview .replace .match {
background-color: #FFCDD2;
border-color: #EF9A9A;
@@ -11747,7 +13089,7 @@ div#notebook {
<!-- Loading mathjax macro -->
<!-- Load mathjax -->
- <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_HTML"></script>
+ <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS_HTML"></script>
<!-- MathJax configuration -->
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
@@ -11772,52 +13114,47 @@ div#notebook {
<div class="container" id="notebook-container">
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div>
-<div class="inner_cell">
+</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
-<h1 id="MSP-Simulation-Example---Nonlinear-Resistive-Companion">MSP Simulation Example - Nonlinear Resistive Companion<a class="anchor-link" href="#MSP-Simulation-Example---Nonlinear-Resistive-Companion">¶</a></h1>
+<h1 id="MSP-Simulation-Example---Nonlinear-Resistive-Companion">MSP Simulation Example - Nonlinear Resistive Companion<a class="anchor-link" href="#MSP-Simulation-Example---Nonlinear-Resistive-Companion">¶</a></h1>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div>
-<div class="inner_cell">
+</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="Sample-Circuit">Sample Circuit<a class="anchor-link" href="#Sample-Circuit">¶</a></h2>
+<h2 id="Sample-Circuit">Sample Circuit<a class="anchor-link" href="#Sample-Circuit">¶</a></h2>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div>
-<div class="inner_cell">
+</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
-<p><img src="data:image/png;base64, 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" width="500" align="left" alt="Sample Circuit" /></p>
+<p><img 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" 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+</div><div class="inner_cell">
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-<p>$E$: $10 V$, $R_S$: $1 \Omega$, $C$: $10 uF$<br>
+<p>$E$=$10 V$, $R_S$=$1 \Omega$, $C$=$10 uF$<br>
$i_R = g(v_R)= \frac{v_R^2}{R_{NL}} $<br>
-$R_{NL}$: $1 \Omega$</p>
+$R_{NL}$=$1 \Omega$</p>
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-<div class="inner_cell">
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<div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="Simulation-Setup">Simulation Setup<a class="anchor-link" href="#Simulation-Setup">¶</a></h2>
+<h2 id="Simulation-Setup">Simulation Setup<a class="anchor-link" href="#Simulation-Setup">¶</a></h2>
</div>
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<div class="cell border-box-sizing code_cell rendered">
<div class="input">
-<div class="prompt input_prompt">In [1]:</div>
+<div class="prompt input_prompt">In [1]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
@@ -11864,16 +13201,15 @@ $R_{NL}$: $1 \Omega$</p>
<span class="n">num_iter</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">npoint</span><span class="p">)</span>
</pre></div>
-</div>
+ </div>
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-<h2 id="Set-Initial-Conditions">Set Initial Conditions<a class="anchor-link" href="#Set-Initial-Conditions">¶</a></h2><ul>
+<h2 id="Set-Initial-Conditions">Set Initial Conditions<a class="anchor-link" href="#Set-Initial-Conditions">¶</a></h2><ul>
<li>Precondition: $ u_C(0)=0 $ </li>
<li>Analytic solution: $ \frac{e_1(0)^2}{R_{NL}} = \frac{E - e_1(0)}{R_s} $ $\Rightarrow R_s e_1(0)^2 + R_{NL} \cdot e_1(0) - R_{NL} E = 0 $</li>
</ul>
@@ -11883,20 +13219,20 @@ $R_{NL}$: $1 \Omega$</p>
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-<div class="prompt input_prompt">In [2]:</div>
+<div class="prompt input_prompt">In [2]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">v1_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="o">-</span><span class="n">R_NL</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">R_NL</span><span class="o">^</span><span class="mi">2</span><span class="o">+</span><span class="mi">4</span><span class="o">*</span><span class="n">Rs</span><span class="o">*</span><span class="n">E</span><span class="o">*</span><span class="n">R_NL</span><span class="p">))</span><span class="o">/</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">Rs</span><span class="p">)</span>
<span class="n">i_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">square</span><span class="p">(</span><span class="n">v1_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span><span class="o">/</span><span class="n">R_NL</span>
<span class="n">v2_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">"Calculated initial conditions: </span><span class="se">\n</span><span class="s2">"</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">"e1(0) = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">v1_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">"e2(0) = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">v2_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">"iR(0) = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">i_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Calculated initial conditions: </span><span class="se">\n</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"e1(0) = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">v1_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"e2(0) = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">v2_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"iR(0) = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">i_trap</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
</pre></div>
-</div>
+ </div>
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@@ -11906,7 +13242,7 @@ $R_{NL}$: $1 \Omega$</p>
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@@ -11924,10 +13260,9 @@ iR(0) = 7.721280737848999
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-<h2 id="Numerical-Integration-and-Newton-Raphson-Loop">Numerical Integration and Newton-Raphson Loop<a class="anchor-link" href="#Numerical-Integration-and-Newton-Raphson-Loop">¶</a></h2><ul>
+<h2 id="Numerical-Integration-and-Newton-Raphson-Loop">Numerical Integration and Newton-Raphson Loop<a class="anchor-link" href="#Numerical-Integration-and-Newton-Raphson-Loop">¶</a></h2><ul>
<li>Application of Trapezoidal integration method</li>
</ul>
@@ -11936,7 +13271,7 @@ iR(0) = 7.721280737848999
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># DC equivalent of capacitor</span>
@@ -12000,33 +13335,32 @@ iR(0) = 7.721280737848999
<span class="n">i_trap</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="n">Ac</span> <span class="o">+</span> <span class="n">v2_trap</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">*</span><span class="n">Gc</span>
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+ </div>
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-<h2 id="Simulation-Results">Simulation Results<a class="anchor-link" href="#Simulation-Results">¶</a></h2><h3 id="Capacitor-Voltage">Capacitor Voltage<a class="anchor-link" href="#Capacitor-Voltage">¶</a></h3>
+<h2 id="Simulation-Results">Simulation Results<a class="anchor-link" href="#Simulation-Results">¶</a></h2><h3 id="Capacitor-Voltage">Capacitor Voltage<a class="anchor-link" href="#Capacitor-Voltage">¶</a></h3>
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+<div class="prompt input_prompt">In [4]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">T_total</span><span class="o">-</span><span class="n">Ts</span><span class="p">,</span><span class="n">Ts</span><span class="p">),</span><span class="n">v2_trap</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Voltage over capacitor: $ e_</span><span class="si">{2}</span><span class="s1"> $'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [s]'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Voltage [V]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Voltage over capacitor: $ e_</span><span class="si">{2}</span><span class="s1"> $'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [s]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Voltage [V]'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
-</div>
+ </div>
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@@ -12036,15 +13370,13 @@ iR(0) = 7.721280737848999
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-<img src="data:image/png;base64,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%0A">
</div>
</div>
@@ -12054,27 +13386,26 @@ iR(0) = 7.721280737848999
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div>
-<div class="inner_cell">
+</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="Capacitor-Current">Capacitor Current<a class="anchor-link" href="#Capacitor-Current">¶</a></h2>
+<h2 id="Capacitor-Current">Capacitor Current<a class="anchor-link" href="#Capacitor-Current">¶</a></h2>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
-<div class="prompt input_prompt">In [5]:</div>
+<div class="prompt input_prompt">In [5]:</div>
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">T_total</span><span class="o">-</span><span class="n">Ts</span><span class="p">,</span><span class="n">Ts</span><span class="p">),</span><span class="n">i_trap</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Current through capacitor'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [s]'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Current [A]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">'Current through capacitor'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [s]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Current [A]'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
-</div>
+ </div>
</div>
</div>
@@ -12084,15 +13415,13 @@ iR(0) = 7.721280737848999
<div class="output_area">
-<div class="prompt"></div>
+ <div class="prompt"></div>
<div class="output_png output_subarea ">
-<img 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ctaklRppYV1RCyNiOVT74FfA35c1vb2Z3iw4QAzSVKllTka/EjgMxExtZ2PZ+aXStzejGxZS5KqrrSwzswbgUeWtf5ODQ0Y1pKkaqv1pVvQCuud3m5UklRh9Q9ru8ElSRVX+7AeHmw6wEySVGn1D+tmg10+z1qSVGG1D2sHmEmSqq4/wtoBZpKkCqt/WDcb7NxtWEuSqqv2YT08aMtaklRttQ9rL92SJFVd/cPaAWaSpIozrCVJ6nF9EdbeFEWSVGWzPsgjIu6dY/kAbsvMhyxcSQtreKDJrolJMpPiCWCSJFXKXE/duiEzHzXbDBHxgwWsZ8END7Q6D3ZNTDI80OxyNZIkHbi5usH/ewfr6GSerhlqFmFtV7gkqaJmDevimdT7iIgnRcS7Z5unVwwNGNaSpGqbqxt8r4h4FPA7wG8BNwGXlFXUQpoKaweZSZKqaq4BZg8Bnl+8NgEXAZGZT12E2hbEsC1rSVLFzdWyvhb4DvAbmbkOICL+pPSqFtBQ2wAzSZKqaK4BZs8BbgO+ERHvjYizaF2uVRkOMJMkVd1cA8z+LTOfBzwU+AbwKuCIiPiniPi1xShwvjxnLUmquo7uYJaZ2zLz45n5TGA18APgtaVWtkDuD+uJLlciSdLBOeDbjWbm3Zl5YWaeVUZBC23qRih2g0uSqmrWsI6I78+1gk7m6SZHg0uSqm6u0eCnRcTVs3wfwCELWM+CczS4JKnq5grrh3awjp4+GexocElS1c0a1pl582IVUpbhQUeDS5Kqrf7Ps7ZlLUmquPqHtQPMJEkV11FYR8TfdTJtP8s2I+IHEfG5Ay1uIUxduuV11pKkquq0Zf30Gaad0+GyrwSu6XDeBTfYDJqNYPtuw1qSVE1zXWf9RxHxI+DUiLi67XUTMNslXVPLrwZ+HXjfwpR74CKCkYEGO3bbDS5Jqqa5Lt36OPBF4G+B17VN35KZd3Ww/guA1wDL9zdDRJwPnA9w/PHHd7DKAzc61LRlLUmqrLke5LE5M3+emc8HNgC7gQSWRcSsyRoRvwFszMwr59jGhZm5JjPXjI2NHWD5nRkeaLLDsJYkVdRcLWsAIuJlwJuAO4Cp/uQEHjHLYk8EzouIc4ERYEVE/Etm/u7Bl3twRgYb7LQbXJJUUR2FNa1HY56amXd2uuLMfD3weoCIeArwZ90IarAbXJJUbZ2OBl8PbC6zkDKN2A0uSaqwTlvWNwLfjIjPAzunJmbm2ztZODO/CXzzQItbKKNDTbbt3NOtzUuSNC+dhvUvitdQ8aqU4YEmm7bu6nYZkiQdlI7COjP/CiAilmTmfeWWtPBaA8zsBpckVVOntxs9MyJ+ClxbfH5kRLyn1MoW0Oig56wlSdXV6QCzC4CzgTsBMvOHwJPLKmqhjQw6GlySVF0dP3UrM9dPm1SZ9BsZ9HajkqTq6nSA2fqIeAKQETFIlx/OcaBGi5Z1ZhIR3S5HkqQD0mnL+g+BlwLHArcAZxSfK2F4cOoxmbauJUnVM2fLOiKawAsz8wWLUE8pRqfCevckI8V7SZKqYs6WdWZOAL+zCLWUZiqgHWQmSaqiTs9ZXxoR7wIuArZNTczM75dS1QIbGWz9TeLlW5KkKuo0rM8ofr65bVoCT1vYcsox1Q2+Y49hLUmqnk7OWTeAf8rMixehnlLs7QbfZVhLkqqnk3PWk8BrFqGW0kyFtddaS5KqqNNLt74WEX8WEcdFxGFTr1IrW0B7z1nbDS5JqqBOz1k/t/jZfm11AicubDnl2NuythtcklRBnT5168FlF1ImB5hJkqqso7COiN+baXpmfmRhyymH56wlSVXWaTf4Y9rejwBnAd8HKhLWrXPWjgaXJFVRp93gL2//HBErgU+WUlEJRuwGlyRVWMePyJxmG1CZ89jDAw0iHGAmSaqmTs9Zf5bW6G9oBfzpQGVukhIRjAw02eFTtyRJFdTpOeu3tb3fA9ycmRtKqKc0I4MN7w0uSaqkWcM6Ik4GjszMb02b/sSIGM7MG0qtbgGNDDYdYCZJqqS5zllfANw7w/R7i+8qY3TQbnBJUjXNFdZHZuaPpk8spp1QSkUlabWs93S7DEmSDthcYb1ylu9GF7KQsi0dbnKf3eCSpAqaK6zXRsT/mj4xIl4CXFlOSeVYOjzAtp22rCVJ1TPXaPBXAZ+JiBdwfzivAYaA3yyzsIW2dGiADXdv73YZkiQdsFnDOjPvAJ4QEU8FHl5M/nxmfr30yhbYkqEm99myliRVUKe3G/0G8I0DWXFEjADfBoaL7XwqM994wBUukKXDA2zznLUkqYI6vSnKwdgJPC0zt0bEIHBpRHwxM/+rxG3u15KhJvc5GlySVEEHe2/wOWXL1uLjYPHKWRYp1dLhAXZPJDt9mIckqWJKC2uAiGhGxFXARuCrmXl5mdubzdKh1pO37ttpWEuSqqXUsM7Micw8A1gNPDYiHj59nog4PyLWRsTa8fHx0mpZMtzq8d9mV7gkqWJKDespmXkPrQFqz5jhuwszc01mrhkbGyuthqVDrbD2xiiSpKopLawjYiwiVhbvR4GnA9eWtb25LBludYN7YxRJUtWUORr8aODDEdGk9UfBxZn5uRK3Nytb1pKkqiotrDPzauBRZa3/QC0tWtZbbVlLkipmUc5Z94L7W9aGtSSpWvomrO8/Z203uCSpWvomrG1ZS5Kqqm/CenTQlrUkqZr6JqwbjWDJUNNLtyRJldM3YQ0+eUuSVE39FdY+eUuSVEF9FdZLhgY8Zy1Jqpy+Cuulw7asJUnV01dhvWTIc9aSpOrpq7BeOuxocElS9fRXWA8NGNaSpMrpq7BeNjLA1h2GtSSpWvoqrFeMDLJl5x4mJrPbpUiS1LH+CuvRQcDHZEqSqqWvwnr5SOthHvdu393lSiRJ6lxfhfWKkVbL+t4dhrUkqTr6K6xHp1rWdoNLkqqjv8K6aFlvsWUtSaqQvgzre718S5JUIf0V1qMOMJMkVU9fhfWy4SKs7QaXJFVIX4X1QLPB0qEmW+wGlyRVSF+FNbRujGI3uCSpSvovrEcG7QaXJFVK/4X16IDd4JKkSum7sF5uy1qSVDF9F9YrRga8g5kkqVL6L6xHbVlLkqql/8J6ZJAtO/aQ6TOtJUnVUFpYR8RxEfGNiPhpRPwkIl5Z1rYOxPKRASYmk/t2TXS7FEmSOlJmy3oP8KeZeTrweOClEXF6idvryIrR1v3BN3uttSSpIkoL68y8LTO/X7zfAlwDHFvW9jp16JIhAO6+b1eXK5EkqTOLcs46Ik4AHgVcPsN350fE2ohYOz4+Xnothy0twnqbLWtJUjWUHtYRsQz4NPCqzLx3+veZeWFmrsnMNWNjY2WXw2FLW93gd9myliRVRKlhHRGDtIL6Y5l5SZnb6tRUN/hdW3d2uRJJkjpT5mjwAN4PXJOZby9rOwdq5ZIhIuCu++wGlyRVQ5kt6ycCLwSeFhFXFa9zS9xeR5qNYOXoIHdvsxtcklQNA2WtODMvBaKs9c/HoUuHPGctSaqMvruDGcBhS4a4a6thLUmqhr4M60OXDnmdtSSpMvoyrFctHeIuz1lLkiqiL8N6qmXtwzwkSVXQl2F92JIhdk8kW3b6XGtJUu/ry7A+dO8tR+0KlyT1vr4M6723HDWsJUkV0KdhPQwY1pKkaujLsF5VdINv8v7gkqQK6MuwPmJFq2V9x72GtSSp9/VlWA8PNDl0ySAbt+zodimSJM2pL8Ma4MgVI7asJUmV0LdhfcSKETbea8taktT7+jasj1w+bMtaklQJ/RvWK0YY37qTiUlvOSpJ6m19HNbDTEwmd26zdS1J6m19G9ZHrBgBYKNd4ZKkHte3YX3kVFh7+ZYkqcf1bVgfsdwbo0iSqqFvw3qsCOvbN9uyliT1tr4N68Fmg7Hlw9y2eXu3S5EkaVZ9G9YAxx06yvq7DGtJUm/r77A+bAnr776v22VIkjSr/g7rQ5dw2+Yd7JmY7HYpkiTtV3+H9WGjTEwmtznITJLUw/o7rA9dAsD6u+wKlyT1rr4O69VTYe15a0lSD+vrsD565QiNwBHhkqSe1tdhPdhscPQho7asJUk9rbSwjogPRMTGiPhxWdtYCMcftoSb7zSsJUm9q8yW9YeAZ5S4/gVx0hFLuWF8K5k+11qS1JtKC+vM/DZwV1nrXygnjy1jy449jG/xgR6SpN7U1+esAU45cjkA12/c2uVKJEmaWdfDOiLOj4i1EbF2fHx80bd/yhHLAFhnWEuSelTXwzozL8zMNZm5ZmxsbNG3P7Z8mBUjA1y/ccuib1uSpE50Pay7LSI45cjlXH+HLWtJUm8q89KtTwCXAadGxIaIeHFZ25qvk8eW2Q0uSepZZY4Gf35mHp2Zg5m5OjPfX9a25uuhRy/nzm27uONeH+ghSeo9fd8NDvCI1YcAcPWGzV2uRJKkfRnWwOlHH0KzEVy94Z5ulyJJ0j4Ma2B0qMkpRyyzZS1J6kmGdeERqw/h6g33eNtRSVLPMawLv7R6JXfft5sNd/u4TElSbzGsC48+fiUAV9zU87czlyT1GcO6cNpRK1i5ZJDLbryz26VIkvQAhnWh0QjOPHEVl91wp+etJUk9xbBu84STVnHLPdtZf5fnrSVJvcOwbnPmSasAuHTdpi5XIknS/QzrNieNLeO4w0b56k9v73YpkiTtZVi3iQjOPv0o/t+6O9myY3e3y5EkCTCs9/GMhx/FrolJvnHdeLdLkSQJMKz38ejjD2Vs+TCf++Gt3S5FkiTAsN5HoxE851HH8vVrN7Jxi4/MlCR1n2E9g+c+5jj2TCafunJDt0uRJMmwnsmJY8t4/ImH8fHLf8GeiclulyNJ6nOG9X685EknsuHu7fz7VZ67liR1l2G9H2eddgSnHb2Cd39zna1rSVJXGdb7ERG88qyTuXF8G5+44hfdLkeS1McM61mc/bCjeMJJq/j7L1/HnVt3drscSVKfMqxnERH81XkPY8fuSV776R/5NC5JUlcY1nM45cjlvPach/K1a+7g/Zfe1O1yJEl9yLDuwB888QSe8bCj+OsvXMPnrnZ0uCRpcRnWHYgILnjeGTzmQYfx6ot+yGe9FakkaREZ1h0aGWzy3v+5hkcedwgv/8QPeOd/Xs/EpOewJUnlM6wPwCGjg3z0xY/jWWccw9u/+jOed+FlXH/Hlm6XJUmqOcP6AI0MNrnguWfw9t9+JNfevoWzL/g2r/nUD7lp07ZulyZJqqmBbhdQRRHBcx69mqecegTv/sY6PnrZzVy8dgO/fMrhPPuMYznrtCNYuWSo22VKkmoieuna4TVr1uTatWu7XcYB27hlBxddsZ5PXPELbt28g2Yj+G/HH8qaE1qvR6xeyaqlQ0REt0uVJPWQiLgyM9fMOV+ZYR0RzwDeATSB92XmW2abv6phPSUz+dEtm/nyT27n0us38ZNb72VPMQht5ZJBTjliGScfsYxjV45y1CGjHH3ICEcdMsLY8mGWDw8Y5pLUZ7oe1hHRBH4GPB3YAHwPeH5m/nR/y1Q9rKfbvmuCq9bfwzW33cv1G7dyw8atrBvfyl3bdu0zbyNgxeggK0cHOWR0kBXFa3Swychgg9HBZuv9UJORgSajQ63Pg80GA81goBEMNBsMFj8HmsFgo0GzEQw2i2mNYLDZoNGARkTxanXrt/9sRBCx7zySpIXVaViXec76scC6zLyxKOiTwLOA/YZ13YwONTnzpFWcedKqB0zfsXuC2zfv4PZ7d3D75h1s2rqTzdt3s3n7bu65b/fe97fcs52duyfZvnuCHbsn2L57gm6etWi0BXhMC/UICFqhPpXrU/E+FfT3f77/077zTn3e/3pom7d9/pnXF3vf00FdbXMflG79TTOfP6bmU/J893c+y8/ndzW/7c7DPA+YfzJ334uf9GCe+chjFn27ZYb1scD6ts8bgMdNnykizgfOBzj++ONLLKd3jAw2OeHwpZxw+NIDWi4z2blncm9wb981we6JZPfEJBOTyZ7JSXZPJHsmkt2Tk+yZSCamprV9N5lJZjKZMFn8bH1OMtk7fX/z3P89TE4W39H6PNVTk3trLn4WUzL3/Y627+6fZ9q0mda3z3f7bnt/3zFTXfP8Qyg5+BXMZ9vzKXt++zy/A9a9fZ7H72le253HwvPcthbO0EB3LqLq+mjwzLyrjMOjAAAGzElEQVQQuBBa3eBdLqenRQQjg01GBpus7HYxkqRFU+afCLcAx7V9Xl1MkyRJB6DMsP4ecEpEPDgihoDnAf9R4vYkSaql0rrBM3NPRLwM+DKtS7c+kJk/KWt7kiTVVannrDPzC8AXytyGJEl1573BJUnqcYa1JEk9zrCWJKnHGdaSJPU4w1qSpB5nWEuS1OMMa0mSepxhLUlSjzOsJUnqcTGfx8UttIgYB25ewFUeDmxawPX1I4/h/HkMF4bHcf48hvO30MfwQZk5NtdMPRXWCy0i1mbmmm7XUWUew/nzGC4Mj+P8eQznr1vH0G5wSZJ6nGEtSVKPq3tYX9jtAmrAYzh/HsOF4XGcP4/h/HXlGNb6nLUkSXVQ95a1JEmV19NhHRHPiIjrImJdRLxuhu+HI+Ki4vvLI+KEtu9eX0y/LiLOnmudEfHgYh3rinUOlb1/i2GRj+HHiuk/jogPRMRg2fu3WBbzOLZ9/86I2FrWPi22Rf63GBHx1xHxs4i4JiJeUfb+LYZFPoZnRcT3I+KqiLg0Ik4ue/8WQ0nH8AMRsTEifjxtXYdFxFcj4vri56EHXXhm9uQLaAI3ACcCQ8APgdOnzfPHwD8X758HXFS8P72Yfxh4cLGe5mzrBC4Gnle8/2fgj7p9DCp4DM8Fonh9og7HsBvHsVhuDfBRYGu397+KxxD4feAjQKP4fES3j0EFj+HPgNPa1vuhbh+DXjyGxXdPBh4N/Hjaut4KvK54/zrg7w629l5uWT8WWJeZN2bmLuCTwLOmzfMs4MPF+08BZ0VEFNM/mZk7M/MmYF2xvhnXWSzztGIdFOt8don7tlgW7RgCZOYXsgBcAawuef8Wy6Iex4hoAn8PvKbk/VpMi3oMgT8C3pyZkwCZubHEfVssi30ME1hRvD8EuLWk/VpMZRxDMvPbwF0zbK99XfPKlV4O62OB9W2fNxTTZpwnM/cAm4FVsyy7v+mrgHuKdexvW1W0mMdwr6L7+4XAl+a9B71hsY/jy4D/yMzbFqj+XrDYx/Ak4LkRsTYivhgRpyzQfnTTYh/DlwBfiIgNtP57fsuC7EV3lXEMZ3Nk23/HtwNHHlzZvR3Wqq73AN/OzO90u5CqiYhjgN8C/rHbtVTcMLAjW3eaei/wgS7XU0V/ApybmauBDwJv73I9lVb0OB705Ve9HNa3AMe1fV5dTJtxnogYoNVVc+csy+5v+p3AymId+9tWFS3mMaRYxxuBMeDVC7IHvWExj+OjgJOBdRHxc2BJRKxbqB3posX+t7gBuKR4/xngEfPeg+5btGMYEWPAIzPz8mL6RcATFmY3uqqMYzibOyLi6GJdRwMHfzqm2yf8ZxkIMADcSOtE/tRAgIdNm+elPHAgwMXF+4fxwIEAN9IaWLDfdQL/ygMHmP1xt49BBY/hS4DvAqPd3vcqH8dp663LALPF/rf4FuAPivdPAb7X7WNQpWNYTN8EPKRY/sXAp7t9DHrxGLYtdwL7DjD7ex44wOytB117tw/eHAf2XFojEm8A3lBMezNwXvF+hFbIrqM1oOnEtmXfUCx3HXDObOsspp9YrGNdsc7hbu9/BY/hnmLaVcXrL7u9/1U8jtO2W4uw7sK/xZXA54EfAZfRaiV2/RhU7Bj+ZnH8fgh8s31dVX6VdAw/AdwG7KbVq/PiYvoq4D+B64GvAYcdbN3ewUySpB7Xy+esJUkShrUkST3PsJYkqccZ1pIk9TjDWpKkHmdYS5LU4wxrqWIiYlXx2MKrIuL2iLil7fN3S9jeiyJiPCLeN8s8o8X2d0XE4Qtdg9TvBuaeRVIvycw7gTMAIuJNtG6c8raSN3tRZr5slpq2A2cUt0iVtMBsWUs1EhFbi59PiYhvRcS/R8SNEfGWiHhBRFwRET+KiJOK+cYi4tMR8b3i9cQOtvGwYj1XRcTVNXmildTTbFlL9fVI4DRaz9m9EXhfZj42Il4JvBx4FfAO4B8y89KIOB74crHMbP4QeEdmfiwihmjdY1pSiQxrqb6+l8WzdCPiBuArxfQfAU8t3v8qcHpETC2zIiKWZebWWdZ7GfCGiFgNXJKZ1y986ZLa2Q0u1dfOtveTbZ8nuf8P9Qbw+Mw8o3gdO0dQk5kfB84DtgNfiIinLXDdkqYxrKX+9hVaXeIARMQZcy0QEScCN2bmO4F/px7PipZ6mmEt9bdXAGuKgWI/pXU+ei6/Dfw4Iq4CHg58pMwCJeEjMiXNLiJeBKyZ7dKttnl/Xsy7qey6pH5iy1rSXLYD53RyUxRgkNY5cUkLyJa1JEk9zpa1JEk9zrCWJKnHGdaSJPU4w1qSpB5nWEuS1OP+P221pjxkO6N4AAAAAElFTkSuQmCC
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%0A">
</div>
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@@ -12102,29 +13431,28 @@ iR(0) = 7.721280737848999
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div>
-<div class="inner_cell">
+</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="I-V-Characteristic-of-Nonlinear-Resistor">I-V Characteristic of Nonlinear Resistor<a class="anchor-link" href="#I-V-Characteristic-of-Nonlinear-Resistor">¶</a></h2>
+<h2 id="I-V-Characteristic-of-Nonlinear-Resistor">I-V Characteristic of Nonlinear Resistor<a class="anchor-link" href="#I-V-Characteristic-of-Nonlinear-Resistor">¶</a></h2>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
-<div class="prompt input_prompt">In [6]:</div>
+<div class="prompt input_prompt">In [6]:</div>
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">v_R_NL</span> <span class="o">=</span> <span class="n">v1_trap</span> <span class="o">-</span> <span class="n">v2_trap</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">v_R_NL</span><span class="p">,</span><span class="n">i_trap</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Voltage [V]'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Current [A]'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">V_exmp_NR</span><span class="p">,</span><span class="n">I_exmp_NR</span><span class="p">,</span> <span class="s1">'x'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="s1">'I-V characteristic of nonlinear resistor'</span><span class="p">,</span><span class="s1">'N-R iterations within one sim time step'</span><span class="p">])</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Voltage [V]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'Current [A]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">V_exmp_NR</span><span class="p">,</span><span class="n">I_exmp_NR</span><span class="p">,</span> <span class="s1">'x'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="s1">'I-V characteristic of nonlinear resistor'</span><span class="p">,</span><span class="s1">'N-R iterations within one sim time step'</span><span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
-</div>
+ </div>
</div>
</div>
@@ -12134,15 +13462,13 @@ iR(0) = 7.721280737848999
<div class="output_area">
-<div class="prompt"></div>
+ <div class="prompt"></div>
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-<img 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%0A">
</div>
</div>
@@ -12152,26 +13478,25 @@ iR(0) = 7.721280737848999
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
-</div>
-<div class="inner_cell">
+</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
-<h1 id="Number-of-Newton-Raphson-Iterations">Number of Newton-Raphson Iterations<a class="anchor-link" href="#Number-of-Newton-Raphson-Iterations">¶</a></h1>
+<h1 id="Number-of-Newton-Raphson-Iterations">Number of Newton-Raphson Iterations<a class="anchor-link" href="#Number-of-Newton-Raphson-Iterations">¶</a></h1>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
-<div class="prompt input_prompt">In [7]:</div>
+<div class="prompt input_prompt">In [7]:</div>
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">Ts</span><span class="p">,</span><span class="n">T_total</span><span class="o">-</span><span class="n">Ts</span><span class="p">,</span><span class="n">Ts</span><span class="p">),</span><span class="n">num_iter</span><span class="p">[</span><span class="mi">1</span><span class="p">:])</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [s]'</span><span class="p">)</span>
-<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# Iterations'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">'Time [s]'</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">'# Iterations'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
-</div>
+ </div>
</div>
</div>
@@ -12181,15 +13506,13 @@ iR(0) = 7.721280737848999
<div class="output_area">
-<div class="prompt"></div>
+ <div class="prompt"></div>
<div class="output_png output_subarea ">
-<img 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%0A">
</div>
</div>
@@ -12197,6 +13520,19 @@ iR(0) = 7.721280737848999
</div>
</div>
+</div>
+<div class="cell border-box-sizing code_cell rendered">
+<div class="input">
+<div class="prompt input_prompt">In [ ]:</div>
+<div class="inner_cell">
+ <div class="input_area">
+<div class=" highlight hl-ipython3"><pre><span></span>
+</pre></div>
+
+ </div>
+</div>
+</div>
+
</div>
</div>
</div>
@@ -12205,4 +13541,4 @@ iR(0) = 7.721280737848999
-</html>
+</html>
\ No newline at end of file