⇒#906@グラフ;

📈 非直線抵抗と直線抵抗

906_非直線抵抗と直線抵抗

import numpy as np
import matplotlib.pyplot as plt

#fig, ax = plt.subplots(figsize=(2.9, 2.1)) 
fig, ax = plt.subplots()

#----------------
#_📈_906_非直線抵抗と直線抵抗
xy_906 = [(0,0) \
, (0.0234375,1.13243E-14) \
, (0.046875,2.91367E-12) \
, (0.0703125,7.4674E-11) \
, (0.09375,7.45899E-10) \
, (0.1171875,4.44591E-09) \
, (0.140625,1.91166E-08) \
, (0.1640625,6.56122E-08) \
, (0.1875,1.9095E-07) \
, (0.2109375,4.89936E-07) \
, (0.234375,1.13815E-06) \
, (0.2578125,2.43971E-06) \
, (0.28125,4.89376E-06) \
, (0.3046875,9.28395E-06) \
, (0.328125,1.67957E-05) \
, (0.3515625,2.91666E-05) \
, (0.375,4.88749E-05) \
, (0.3984375,7.93727E-05) \
, (0.421875,0.000125369) \
, (0.4453125,0.000193168) \
, (0.46875,0.00029107) \
, (0.4921875,0.000429834) \
, (0.515625,0.00062321) \
, (0.5390625,0.00088853) \
, (0.5625,0.001247365) \
, (0.5859375,0.001726217) \
, (0.609375,0.00235723) \
, (0.6328125,0.003178883) \
, (0.65625,0.004236605) \
, (0.6796875,0.005583234) \
, (0.703125,0.007279236) \
, (0.7265625,0.009392558) \
, (0.75,0.011998009) \
, (0.7734375,0.01517604) \
, (0.796875,0.019010851) \
, (0.8203125,0.023587795) \
, (0.84375,0.028990146) \
, (0.8671875,0.035295417) \
, (0.890625,0.042571505) \
, (0.9140625,0.050873067) \
, (0.9375,0.060238518) \
, (0.9609375,0.070688032) \
, (0.984375,0.082222791) \
, (1.0078125,0.094825533) \
, (1.03125,0.108462301) \
, (1.0546875,0.123085105) \
, (1.078125,0.138635132) \
, (1.1015625,0.155046139) \
, (1.125,0.172247693) \
, (1.1484375,0.190168034) \
, (1.171875,0.208736412) \
, (1.1953125,0.227884874) \
, (1.21875,0.247549496) \
, (1.2421875,0.26767116) \
, (1.265625,0.288195931) \
, (1.2890625,0.309075148) \
, (1.3125,0.330265296) \
, (1.3359375,0.351727744) \
, (1.359375,0.373428383) \
, (1.3828125,0.395337238) \
, (1.40625,0.417428051) \
, (1.4296875,0.439677883) \
, (1.453125,0.462066729) \
, (1.4765625,0.484577167) \
, (1.5,0.507194033) \
, (1.5234375,0.529904138) \
, (1.546875,0.552696007) \
, (1.5703125,0.575559657) \
, (1.59375,0.598486396) \
, (1.6171875,0.621468653) \
, (1.640625,0.64449983) \
, (1.6640625,0.667574166) \
, (1.6875,0.690686631) \
, (1.7109375,0.713832827) \
, (1.734375,0.737008903) \
, (1.7578125,0.760211482) \
, (1.78125,0.783437603) \
, (1.8046875,0.806684662) \
, (1.828125,0.829950369) \
, (1.8515625,0.853232706) \
, (1.875,0.876529891) \
, (1.8984375,0.899840354) \
, (1.921875,0.923162702) \
, (1.9453125,0.946495704) \
, (1.96875,0.969838268) \
, (1.9921875,0.993189422) \
, (2.015625,1.016548306) \
, (2.0390625,1.03991415) \
, (2.0625,1.063286272) \
, (2.0859375,1.08666406) \
, (2.109375,1.110046969) \
, (2.1328125,1.133434511) \
, (2.15625,1.156826249) \
, (2.1796875,1.180221791) \
, (2.203125,1.203620786) \
, (2.2265625,1.227022917) \
, (2.25,1.250427901) \
, (2.2734375,1.273835481) \
, (2.296875,1.297245428) \
, (2.3203125,1.320657531) \
, (2.34375,1.344071605) \
, (2.3671875,1.367487478) \
, (2.390625,1.390904996) \
, (2.4140625,1.414324021) \
, (2.4375,1.437744425) \
, (2.4609375,1.461166094) \
, (2.484375,1.484588924) \
, (2.5078125,1.508012819) \
, (2.53125,1.531437695) \
, (2.5546875,1.554863471) \
, (2.578125,1.578290076) \
, (2.6015625,1.601717446) \
, (2.625,1.625145519) \
, (2.6484375,1.648574242) \
, (2.671875,1.672003565) \
, (2.6953125,1.695433442) \
, (2.71875,1.718863831) \
, (2.7421875,1.742294694) \
, (2.765625,1.765725995) \
, (2.7890625,1.789157703) \
, (2.8125,1.812589787) \
, (2.8359375,1.83602222) \
, (2.859375,1.859454978) \
, (2.8828125,1.882888036) \
, (2.90625,1.906321374) \
, (2.9296875,1.929754972) \
, (2.953125,1.953188812) \
, (2.9765625,1.976622877) \
]
z_906 = [list(t) for t in zip(*xy_906)]; x_906 = z_906[0]; y_906 = z_906[1]

ax.scatter(x_906, y_906)
ax.plot(x_906, y_906)
ax.annotate('ID=906' \
, xy=(np.mean(x_906),np.mean(y_906)) \
, xytext=(np.mean(x_906)+ np.std(y_906), np.mean(y_906) + np.std(y_906)) \
, arrowprops=dict(arrowstyle="->"))
#----------------

plt.show()

図 1 . python コード

A4 （210 × 297mm）あるいは少し大きめのレターサイズ（215.9 × 279.4ミリ）が一般的です。 2 カラムとすると 3.34645669291339インチ程度。アスペクトを 4:3にすれば、2.9インチ×2.1インチぐらいの図が論文投稿の図として適切です。

サーバーサイドスクリプト

サーバーサイドでラスタライズ（bmp,jpg,png）しているので、レスポンシブな表示が可能です。サーバーサイドでダイナミックに生成している画像なので、ダウンロードだけでなく、リンクもできます。

クライアントサイドスクリプト

図 3 . canvas 非直線抵抗と直線抵抗

クライアントサイドでラスタライズ（bmp,jpg,png）しているので、レスポンシブな表示が可能です。クライアントサイドでダイナミックに生成している画像なので、ダウンロードはできますが、リンクはできません。

図 4 . google chart APIを使った描画

xmin	0
xmax	3
ymin	-1
ymax	2

0 0 0.0234375 1.13243E-14 0.046875 2.91367E-12 0.0703125 7.4674E-11 0.09375 7.45899E-10 0.1171875 4.44591E-09 0.140625 1.91166E-08 0.1640625 6.56122E-08 0.1875 1.9095E-07 0.2109375 4.89936E-07 0.234375 1.13815E-06 0.2578125 2.43971E-06 0.28125 4.89376E-06 0.3046875 9.28395E-06 0.328125 1.67957E-05 0.3515625 2.91666E-05 0.375 4.88749E-05 0.3984375 7.93727E-05 0.421875 0.000125369 0.4453125 0.000193168 0.46875 0.00029107 0.4921875 0.000429834 0.515625 0.00062321 0.5390625 0.00088853 0.5625 0.001247365 0.5859375 0.001726217 0.609375 0.00235723 0.6328125 0.003178883 0.65625 0.004236605 0.6796875 0.005583234 0.703125 0.007279236 0.7265625 0.009392558 0.75 0.011998009 0.7734375 0.01517604 0.796875 0.019010851 0.8203125 0.023587795 0.84375 0.028990146 0.8671875 0.035295417 0.890625 0.042571505 0.9140625 0.050873067 0.9375 0.060238518 0.9609375 0.070688032 0.984375 0.082222791 1.0078125 0.094825533 1.03125 0.108462301 1.0546875 0.123085105 1.078125 0.138635132 1.1015625 0.155046139 1.125 0.172247693 1.1484375 0.190168034 1.171875 0.208736412 1.1953125 0.227884874 1.21875 0.247549496 1.2421875 0.26767116 1.265625 0.288195931 1.2890625 0.309075148 1.3125 0.330265296 1.3359375 0.351727744 1.359375 0.373428383 1.3828125 0.395337238 1.40625 0.417428051 1.4296875 0.439677883 1.453125 0.462066729 1.4765625 0.484577167 1.5 0.507194033 1.5234375 0.529904138 1.546875 0.552696007 1.5703125 0.575559657 1.59375 0.598486396 1.6171875 0.621468653 1.640625 0.64449983 1.6640625 0.667574166 1.6875 0.690686631 1.7109375 0.713832827 1.734375 0.737008903 1.7578125 0.760211482 1.78125 0.783437603 1.8046875 0.806684662 1.828125 0.829950369 1.8515625 0.853232706 1.875 0.876529891 1.8984375 0.899840354 1.921875 0.923162702 1.9453125 0.946495704 1.96875 0.969838268 1.9921875 0.993189422 2.015625 1.016548306 2.0390625 1.03991415 2.0625 1.063286272 2.0859375 1.08666406 2.109375 1.110046969 2.1328125 1.133434511 2.15625 1.156826249 2.1796875 1.180221791 2.203125 1.203620786 2.2265625 1.227022917 2.25 1.250427901 2.2734375 1.273835481 2.296875 1.297245428 2.3203125 1.320657531 2.34375 1.344071605 2.3671875 1.367487478 2.390625 1.390904996 2.4140625 1.414324021 2.4375 1.437744425 2.4609375 1.461166094 2.484375 1.484588924 2.5078125 1.508012819 2.53125 1.531437695 2.5546875 1.554863471 2.578125 1.578290076 2.6015625 1.601717446 2.625 1.625145519 2.6484375 1.648574242 2.671875 1.672003565 2.6953125 1.695433442 2.71875 1.718863831 2.7421875 1.742294694 2.765625 1.765725995 2.7890625 1.789157703 2.8125 1.812589787 2.8359375 1.83602222 2.859375 1.859454978 2.8828125 1.882888036 2.90625 1.906321374 2.9296875 1.929754972 2.953125 1.953188812 2.9765625 1.976622877

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図形と関数

<figure>
<img src="https://a.yamagata-u.ac.jp/amenity/Laboratory/xyGraphImage.aspx?id=906" />
<figcaption>
<a href="https://edu.yz.yamagata-u.ac.jp/developer/Asp/Youzan/Laboratory/Plot/Plot_Index.asp">Fig</a> <a href="https://edu.yz.yamagata-u.ac.jp/developer/Asp/Youzan/Laboratory/Plot/@Plot.asp?nxyGraphID=906"> 非直線抵抗と直線抵抗 </a>
<div> </div>
</figcaption>
</figure>

動画、音声及び写真を含む図表等を転載する場合には転載許諾書による同意があった方が無難です。動画、音声及び写真を含む図表等の転載許諾書

https://edu.yz.yamagata-u.ac.jp/developer/Asp/Youzan/Laboratory/Plot/@Plot.asp?nxyGraphID=906

名称：教育用公開ウェブサービス

URL： 🔗 https://edu.yz.yamagata-u.ac.jp/

管理運用：山形大学学術情報基盤センター

🎄🎂🌃🕯🎉

名称：サイバーキャンパス「鷹山」

URL: 🔗 http://amenity.yz.yamagata-u.ac.jp/

管理運用：山形大学データベースアメニティ研究会

〒992-8510 山形県米沢市城南4丁目3-16

名称	グラフ	説明

指数関数		python +matplotlib import numpy as np import math import matplotlib.pyplot as plt xy = [(p, math.exp(p)) for p in \ np.arange(start = - 2, stop = 2, step = 0.1)] z = [list(t) for t in zip(*xy)]; x = z[0]; y = z[1] fig, ax = plt.subplots() ax.plot(x, y) plt.show()
逆ネルンスト		電池の充放電曲線で現れます。
確率曲線
正規分布関数		確率統計で多用されます。品質管理でも大切です。