From 28561eef52aab919dfc7ceca5156ee0db0bf3c5e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Szymon=20Parafin=CC=81ski?= Date: Wed, 18 May 2022 08:41:12 +0200 Subject: [PATCH] move color print up --- jupyter.ipynb | 113 ++++++++++++++++++++++++++++---------------------- 1 file changed, 63 insertions(+), 50 deletions(-) diff --git a/jupyter.ipynb b/jupyter.ipynb index 0a63229..9d10982 100644 --- a/jupyter.ipynb +++ b/jupyter.ipynb @@ -2,10 +2,9 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": { "pycharm": { - "is_executing": true, "name": "#%%\n" } }, @@ -14,7 +13,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/tq/jq5nwbnj7v10tls99x99qbh40000gn/T/ipykernel_57719/1134982733.py:12: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n", + "/var/folders/8w/3c34c7kd2n144tvm764_pdbw0000gq/T/ipykernel_84713/1134982733.py:12: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n", " from IPython.core.display import display, HTML\n" ] }, @@ -49,7 +48,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": { "pycharm": { "name": "#%%\n" @@ -115,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": { "pycharm": { "name": "#%%\n" @@ -158,8 +157,12 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, + "execution_count": 6, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [], "source": [ "def calculate(A):\n", @@ -202,7 +205,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": { "pycharm": { "name": "#%%\n" @@ -235,7 +238,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": { "pycharm": { "name": "#%%\n" @@ -274,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": { "pycharm": { "name": "#%%\n" @@ -304,7 +307,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 10, "metadata": { "pycharm": { "name": "#%%\n" @@ -338,7 +341,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 11, "metadata": { "pycharm": { "name": "#%%\n" @@ -348,12 +351,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7c4a40e6f857407586d21ab113128a97", + "model_id": "5de39e03944b4f70a566d6fd4e0e747e", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'rocket', 'koala', '…" + "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'camera', 'coin', 'clock', 'te…" ] }, "metadata": {}, @@ -365,7 +368,7 @@ "" ] }, - "execution_count": 22, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -376,7 +379,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "metadata": { "pycharm": { "name": "#%%\n" @@ -386,7 +389,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3533923ce918489eab6fc7de25234078", + "model_id": "a7efd777338d4ccfb3ab75d50a448d13", "version_major": 2, "version_minor": 0 }, @@ -415,7 +418,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 13, "metadata": { "pycharm": { "name": "#%%\n" @@ -472,7 +475,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": { "pycharm": { "name": "#%%\n" @@ -494,6 +497,22 @@ " plt.imshow(image_reconst)" ] }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def print_color_matrices(img_name,k):\n", + " \"\"\"\n", + " Wyświetlanie macierzy U V S wraz z wymiarami.\n", + " \"\"\"\n", + " image = color_images[img_name]\n", + " original_shape = image.shape\n", + " image_reconst_layers = [compress_svd(image[:,:,i],k)[0] for i in range(3)]\n", + " print(image_reconst_layers)" + ] + }, { "cell_type": "markdown", "metadata": { @@ -507,7 +526,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 16, "metadata": { "pycharm": { "name": "#%%\n" @@ -531,23 +550,7 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "def print_color_matrices(img_name,k):\n", - " \"\"\"\n", - " Wyświetlanie macierzy U V S wraz z wymiarami.\n", - " \"\"\"\n", - " image = color_images[img_name]\n", - " original_shape = image.shape\n", - " image_reconst_layers = [compress_svd(image[:,:,i],k)[0] for i in range(3)]\n", - " print(image_reconst_layers)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "metadata": { "pycharm": { "name": "#%%\n" @@ -557,7 +560,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0af20b426d1240cca1e08e40ede10e98", + "model_id": "51461a1fc1b944a0a967b11590d02c7f", "version_major": 2, "version_minor": 0 }, @@ -574,7 +577,7 @@ "" ] }, - "execution_count": 15, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -585,7 +588,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "metadata": { "pycharm": { "name": "#%%\n" @@ -595,7 +598,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "86f500d175554478ac9805075a809d28", + "model_id": "2ac1906f3030426cab0f7d8e8f5be577", "version_major": 2, "version_minor": 0 }, @@ -635,7 +638,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, "metadata": { "pycharm": { "name": "#%%\n" @@ -673,7 +676,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, "metadata": { "pycharm": { "name": "#%%\n" @@ -697,13 +700,18 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": {}, + "execution_count": 21, + "metadata": { + "collapsed": true, + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e97ca096507f42b49f98dbb87ac5a2ec", + "model_id": "8c96b6ed413848f2ad0bcf849e6c54d0", "version_major": 2, "version_minor": 0 }, @@ -721,8 +729,9 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 22, "metadata": { + "collapsed": true, "pycharm": { "name": "#%%\n" } @@ -731,7 +740,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "71fea739144848d69afb1662172190ad", + "model_id": "00696a30e8374ba2ba4ab98c3ba13a75", "version_major": 2, "version_minor": 0 }, @@ -750,7 +759,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, "outputs": [], "source": [] } @@ -771,7 +784,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.13" + "version": "3.8.9" } }, "nbformat": 4,