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| import numpy as np | |
| # Some array of booleans of width w and height h | |
| #occupied_map = np.array([[0,0,0,0], | |
| # [1,1,1,0], | |
| # [0,0,0,1], | |
| # [0,1,0,1], | |
| # [0,1,0,0], | |
| # [0,1,1,0], | |
| # [0,0,0,0]], dtype=np.int32).astype(np.bool) |
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| % In preamble. | |
| \usepackage[font=small,skip=0pt,format=hang]{caption} | |
| % Allows you to set the width of table columns. | |
| \newcolumntype{L}[1]{>{\raggedright\let\newline\\\arraybackslash\hspace{0pt}}m{#1}} | |
| \newcolumntype{C}[1]{>{\centering\let\newline\\\arraybackslash\hspace{0pt}}m{#1}} | |
| \newcolumntype{R}[1]{>{\raggedleft\let\newline\\\arraybackslash\hspace{0pt}}m{#1}} | |
| % In document | |
| \begin{table}[H] | |
| {\resizebox{\columnwidth}{!}{ % Use \textwidth for single column format. |
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| F = meshes[0]["Faces"].copy().sort(1) | |
| num_faces = F.shape[0] | |
| edges = {} | |
| for i in range(num_faces): | |
| edges.setdefault(tuple(F[i,:2]), []).append(i) | |
| edges.setdefault(tuple(F[i,1:3]), []).append(i) | |
| edges.setdefault(tuple(F[i,[0,2]]), []).append(i) | |
| neighbours = np.zeros((num_faces, 3), dtype=np.uint32) |
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| # http://machinelearningmastery.com/using-learning-rate-schedules-deep-learning-models-python-keras/ | |
| from keras.callbacks import LearningRateScheduler | |
| generator.compile(loss=laplacian_charbonnier_loss, optimizer=RMSprop(lr=0)) | |
| def step_decay(epoch): | |
| initial_lrate = 0.0002 | |
| drop = 0.5 | |
| epochs_drop = 50.0 |
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| import java.util.Scanner; | |
| public class Bake { | |
| // Constants for bag sizes | |
| static final double[] FLR_SIZES = { 750, 500, 250 }; | |
| static final double[] SUG_SIZES = { 600, 400, 200 }; | |
| static final double[] BUT_SIZES = { 500, 250, 125 }; | |
| static final double[] EGG_SIZES = { 12, 10, 6 }; | |
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| graph contour_tree { | |
| layout="dot" | |
| rankdir=UD | |
| ranksep="0.02" | |
| graph [fontname="helvetica"]; | |
| node [fontname="helvetica"]; | |
| edge [fontname="helvetica"]; | |
| s_3539 [label="108" fontcolor="#0CADBC" shape=none] | |
| s_3459 [label="163" fontcolor="#92BF72" shape=none] | |
| s_3460 [label="163" fontcolor="#92BF72" shape=none] |
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| #pragma once | |
| #include <vector> | |
| #include <string> | |
| #include "../RenderingEssentials/maths/Vec.hpp" | |
| #include "../RenderingEssentials/maths/Common.hpp" | |
| #include "../RenderingEssentials/geom/Geom.hpp" | |
| #include "../RenderingEssentials/utils/Loader.hpp" | |
| #include "../RenderingEssentials/utils/Exporter.hpp" |
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| static inline unsigned char* LoadBMP_24(const std::string &path) { | |
| int w, h; | |
| unsigned char *img = nullptr; | |
| std::ifstream inFile(path, std::ios::in | std::ios::binary); | |
| if (inFile.is_open()) { | |
| /// Header | |
| unsigned char hdr[0x36]; | |
| inFile.read((char*) hdr, 0x12); |
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| #include <cmath> | |
| #include <cstring> | |
| #include <cstdio> | |
| float sensors[9]; | |
| struct float2 { | |
| float x, y; | |
| }; |