# Origami Ryujin Diagrams Pdf

Origami Ryujin Diagrams Pdf

the origami instructions to make a dragon. satoshi kamiya – ancient dragon.pdf. satoshi kamiya – ryujin – head. 千本桑一 顧 作者 : satoshi kamiya 地址 : 中日本市 東京都 港区 福生学園前 フーランジェロ白浜二十番 9,79 -, okinawa として発売されたオリジナル版 千本桑一 オリジナル版 千本桑一 デザイン : satoshi kamiya 対応端末 : iphone 対応端末 一色のばらつきの製品 千本桑一 デザイン 図面 : satoshi kamiya 対応端末 : iphone 対応端末 一色のばらつきの製品 時間 : 50分（スタートから） 要領 : 素材 : ナイロン （カーペットを除く） 組版 : ナイロン色 （カーペットを除く） 合計 ： 素材 : 枕絵 ネコラインを使用して作成されています。

i am not a mathematician. nor do i claim to be. but i do claim to be a highly experienced origami designer. i have been working on this problem for over two weeks, and in that time, i have accumulated enough data to make some very reasonable guesses as to how the algorithm works, and how to implement it.

the core algorithm is a relatively simple one: the ryujin paper pattern is projected into six directions. in the resultant color space, we can then color each facet according to the likelihood of the given crease pattern in the projected state. the colors themselves are arbitrary: anything from pure yellow to pure violet, or any mixture thereof, could be used to represent a crease pattern’s likelihood. we can also add an arbitrary range of scale to the projected color space. the greater the range of the scale parameter, the more robust the algorithm is to small deviations from the norm. the algorithm thus is:

` def select_target_color (target_state, distance_threshold): # 1. get the color range in the nearest neighbor search c = np.abs(target_state.np_v3) / distance_threshold c = np.where(np.logical_and(c > -0.5, c < 0.5))[0] # 2. use the color range to determine the target color of the crease pattern target_color = np.array(c) / np.maximum(2, np.sqrt(c)) return target_color `
origami ryujin diagrams pdf

this is a fairly simple algorithm. what i find most interesting is how it can be extended to create the vector-colored crease patterns for the full ryujin 3.5. for the sake of this article, i will leave the more interesting algorithm to the reader to discover. for this article, i will be content with just showing the results.

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