{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"id": "184e2620-4a92-4a16-9bb7-e5cb5424b785",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "572ed40f-72a3-47d6-b1de-2451a2d34bf3",
"metadata": {},
"outputs": [],
"source": [
"datos11 = pd.read_csv('11.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos12 = pd.read_csv('12.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos13 = pd.read_csv('13.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos14 = pd.read_csv('14.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos15 = pd.read_csv('15.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos16 = pd.read_csv('16.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos17 = pd.read_csv('17.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos18 = pd.read_csv('18.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos19 = pd.read_csv('19.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])\n",
"datos20 = pd.read_csv('20.txt', delimiter=',', names=['t(s)', 'y(m)', 'v_y(m/s)', 'a_y(m/s^2)'])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "ac6183ad-41ed-4330-8176-3b3b329eda5d",
"metadata": {},
"outputs": [
{
"data": {
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" <th>a_y(m/s^2)</th>\n",
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" </thead>\n",
" <tbody>\n",
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" <th>0</th>\n",
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" <td>0.997691</td>\n",
" <td>0.000000</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>0.049967</td>\n",
" <td>0.993072</td>\n",
" <td>-0.231101</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.099933</td>\n",
" <td>0.974596</td>\n",
" <td>-0.300431</td>\n",
" <td>-1.453604</td>\n",
" </tr>\n",
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" <th>3</th>\n",
" <td>0.149900</td>\n",
" <td>0.963048</td>\n",
" <td>-0.323541</td>\n",
" <td>-0.263998</td>\n",
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" <th>4</th>\n",
" <td>0.199867</td>\n",
" <td>0.942263</td>\n",
" <td>-0.369351</td>\n",
" <td>-1.319990</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.249944</td>\n",
" <td>0.926097</td>\n",
" <td>-0.415520</td>\n",
" <td>-1.583988</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.299911</td>\n",
" <td>0.900693</td>\n",
" <td>-0.554642</td>\n",
" <td>-1.055992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.349878</td>\n",
" <td>0.870670</td>\n",
" <td>-0.531532</td>\n",
" <td>0.132146</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399844</td>\n",
" <td>0.847575</td>\n",
" <td>-0.508422</td>\n",
" <td>0.792875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449811</td>\n",
" <td>0.819861</td>\n",
" <td>-0.485312</td>\n",
" <td>-0.395997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499778</td>\n",
" <td>0.799076</td>\n",
" <td>-0.507857</td>\n",
" <td>-1.319990</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549856</td>\n",
" <td>0.769053</td>\n",
" <td>-0.646364</td>\n",
" <td>-3.695971</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599822</td>\n",
" <td>0.734411</td>\n",
" <td>-0.855074</td>\n",
" <td>-3.035977</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649789</td>\n",
" <td>0.683603</td>\n",
" <td>-0.993734</td>\n",
" <td>-0.660729</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699756</td>\n",
" <td>0.635104</td>\n",
" <td>-0.901294</td>\n",
" <td>1.453604</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749722</td>\n",
" <td>0.593534</td>\n",
" <td>-0.831963</td>\n",
" <td>1.847986</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799689</td>\n",
" <td>0.551963</td>\n",
" <td>-0.738702</td>\n",
" <td>2.639980</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849767</td>\n",
" <td>0.519630</td>\n",
" <td>-0.554026</td>\n",
" <td>2.375982</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899733</td>\n",
" <td>0.496536</td>\n",
" <td>-0.485312</td>\n",
" <td>0.659995</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>0.471132</td>\n",
" <td>-0.508422</td>\n",
" <td>-0.792875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.445727</td>\n",
" <td>-0.554642</td>\n",
" <td>-0.264292</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.415704</td>\n",
" <td>-0.554642</td>\n",
" <td>0.264292</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099600</td>\n",
" <td>0.390300</td>\n",
" <td>-0.508422</td>\n",
" <td>1.055992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149567</td>\n",
" <td>0.364896</td>\n",
" <td>-0.461689</td>\n",
" <td>0.527996</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199644</td>\n",
" <td>0.344111</td>\n",
" <td>-0.438604</td>\n",
" <td>-0.131999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249611</td>\n",
" <td>0.321016</td>\n",
" <td>-0.485312</td>\n",
" <td>-1.715987</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299578</td>\n",
" <td>0.295612</td>\n",
" <td>-0.600862</td>\n",
" <td>-2.642916</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349544</td>\n",
" <td>0.260970</td>\n",
" <td>-0.762633</td>\n",
" <td>-0.660729</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399511</td>\n",
" <td>0.219399</td>\n",
" <td>-0.693303</td>\n",
" <td>2.639980</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449478</td>\n",
" <td>0.191686</td>\n",
" <td>-0.461689</td>\n",
" <td>3.167975</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499556</td>\n",
" <td>0.173210</td>\n",
" <td>-0.369351</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549522</td>\n",
" <td>0.154734</td>\n",
" <td>-0.462202</td>\n",
" <td>-0.791994</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599489</td>\n",
" <td>0.127021</td>\n",
" <td>-0.485312</td>\n",
" <td>-0.396437</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>0.106236</td>\n",
" <td>-0.462202</td>\n",
" <td>-0.264292</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699422</td>\n",
" <td>0.080831</td>\n",
" <td>-0.531532</td>\n",
" <td>-0.925021</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749389</td>\n",
" <td>0.053118</td>\n",
" <td>-0.554642</td>\n",
" <td>1.055992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799356</td>\n",
" <td>0.025404</td>\n",
" <td>-0.438604</td>\n",
" <td>2.771979</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849433</td>\n",
" <td>0.009238</td>\n",
" <td>-0.253929</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899400</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
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],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 0.997691 0.000000 0.000000\n",
"1 0.049967 0.993072 -0.231101 0.000000\n",
"2 0.099933 0.974596 -0.300431 -1.453604\n",
"3 0.149900 0.963048 -0.323541 -0.263998\n",
"4 0.199867 0.942263 -0.369351 -1.319990\n",
"5 0.249944 0.926097 -0.415520 -1.583988\n",
"6 0.299911 0.900693 -0.554642 -1.055992\n",
"7 0.349878 0.870670 -0.531532 0.132146\n",
"8 0.399844 0.847575 -0.508422 0.792875\n",
"9 0.449811 0.819861 -0.485312 -0.395997\n",
"10 0.499778 0.799076 -0.507857 -1.319990\n",
"11 0.549856 0.769053 -0.646364 -3.695971\n",
"12 0.599822 0.734411 -0.855074 -3.035977\n",
"13 0.649789 0.683603 -0.993734 -0.660729\n",
"14 0.699756 0.635104 -0.901294 1.453604\n",
"15 0.749722 0.593534 -0.831963 1.847986\n",
"16 0.799689 0.551963 -0.738702 2.639980\n",
"17 0.849767 0.519630 -0.554026 2.375982\n",
"18 0.899733 0.496536 -0.485312 0.659995\n",
"19 0.949700 0.471132 -0.508422 -0.792875\n",
"20 0.999667 0.445727 -0.554642 -0.264292\n",
"21 1.049633 0.415704 -0.554642 0.264292\n",
"22 1.099600 0.390300 -0.508422 1.055992\n",
"23 1.149567 0.364896 -0.461689 0.527996\n",
"24 1.199644 0.344111 -0.438604 -0.131999\n",
"25 1.249611 0.321016 -0.485312 -1.715987\n",
"26 1.299578 0.295612 -0.600862 -2.642916\n",
"27 1.349544 0.260970 -0.762633 -0.660729\n",
"28 1.399511 0.219399 -0.693303 2.639980\n",
"29 1.449478 0.191686 -0.461689 3.167975\n",
"30 1.499556 0.173210 -0.369351 0.000000\n",
"31 1.549522 0.154734 -0.462202 -0.791994\n",
"32 1.599489 0.127021 -0.485312 -0.396437\n",
"33 1.649456 0.106236 -0.462202 -0.264292\n",
"34 1.699422 0.080831 -0.531532 -0.925021\n",
"35 1.749389 0.053118 -0.554642 1.055992\n",
"36 1.799356 0.025404 -0.438604 2.771979\n",
"37 1.849433 0.009238 -0.253929 0.000000\n",
"38 1.899400 0.000000 0.000000 0.000000"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datos11"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "3167378f-1863-43a5-b038-b279d1ba40b9",
"metadata": {},
"outputs": [
{
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" <th>7</th>\n",
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" <th>8</th>\n",
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" <td>-0.548311</td>\n",
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" <th>9</th>\n",
" <td>0.449811</td>\n",
" <td>0.847032</td>\n",
" <td>-0.616850</td>\n",
" <td>-1.175735</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499778</td>\n",
" <td>0.815068</td>\n",
" <td>-0.662542</td>\n",
" <td>-0.391476</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549744</td>\n",
" <td>0.780822</td>\n",
" <td>-0.661806</td>\n",
" <td>-0.652461</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599822</td>\n",
" <td>0.748858</td>\n",
" <td>-0.707448</td>\n",
" <td>-0.652461</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649789</td>\n",
" <td>0.710046</td>\n",
" <td>-0.753927</td>\n",
" <td>1.174429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699756</td>\n",
" <td>0.673516</td>\n",
" <td>-0.594003</td>\n",
" <td>3.396569</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749722</td>\n",
" <td>0.650685</td>\n",
" <td>-0.388387</td>\n",
" <td>3.527206</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799689</td>\n",
" <td>0.634703</td>\n",
" <td>-0.251309</td>\n",
" <td>1.698284</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849656</td>\n",
" <td>0.625571</td>\n",
" <td>-0.205617</td>\n",
" <td>0.391912</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899622</td>\n",
" <td>0.614155</td>\n",
" <td>-0.228463</td>\n",
" <td>-2.087874</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949589</td>\n",
" <td>0.602740</td>\n",
" <td>-0.387955</td>\n",
" <td>-2.479351</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.575342</td>\n",
" <td>-0.524881</td>\n",
" <td>0.130492</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.550228</td>\n",
" <td>-0.365540</td>\n",
" <td>1.304921</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099600</td>\n",
" <td>0.538813</td>\n",
" <td>-0.342694</td>\n",
" <td>-0.391912</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149567</td>\n",
" <td>0.515982</td>\n",
" <td>-0.456926</td>\n",
" <td>-1.045098</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199533</td>\n",
" <td>0.493151</td>\n",
" <td>-0.434079</td>\n",
" <td>0.914461</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249500</td>\n",
" <td>0.472603</td>\n",
" <td>-0.365540</td>\n",
" <td>1.304776</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299467</td>\n",
" <td>0.456621</td>\n",
" <td>-0.296639</td>\n",
" <td>0.391302</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349556</td>\n",
" <td>0.442922</td>\n",
" <td>-0.319351</td>\n",
" <td>-1.825470</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399556</td>\n",
" <td>0.424658</td>\n",
" <td>-0.479452</td>\n",
" <td>-5.344237</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449556</td>\n",
" <td>0.394977</td>\n",
" <td>-0.844749</td>\n",
" <td>-3.261579</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499556</td>\n",
" <td>0.340183</td>\n",
" <td>-0.890411</td>\n",
" <td>1.174168</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549556</td>\n",
" <td>0.305936</td>\n",
" <td>-0.639269</td>\n",
" <td>3.913894</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599556</td>\n",
" <td>0.276256</td>\n",
" <td>-0.525114</td>\n",
" <td>2.483765</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649556</td>\n",
" <td>0.253425</td>\n",
" <td>-0.388906</td>\n",
" <td>1.436850</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699356</td>\n",
" <td>0.237443</td>\n",
" <td>-0.365744</td>\n",
" <td>1.567647</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749433</td>\n",
" <td>0.216895</td>\n",
" <td>-0.273790</td>\n",
" <td>-0.261362</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799422</td>\n",
" <td>0.210046</td>\n",
" <td>-0.319777</td>\n",
" <td>-3.392042</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849389</td>\n",
" <td>0.184931</td>\n",
" <td>-0.662542</td>\n",
" <td>-4.571288</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899356</td>\n",
" <td>0.143836</td>\n",
" <td>-0.799620</td>\n",
" <td>-2.220834</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1.949322</td>\n",
" <td>0.105023</td>\n",
" <td>-0.845312</td>\n",
" <td>1.698284</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1.999289</td>\n",
" <td>0.059361</td>\n",
" <td>-0.685388</td>\n",
" <td>3.919118</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>2.049256</td>\n",
" <td>0.036530</td>\n",
" <td>-0.388387</td>\n",
" <td>5.094853</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>2.099222</td>\n",
" <td>0.020548</td>\n",
" <td>-0.205617</td>\n",
" <td>2.217873</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>2.149189</td>\n",
" <td>0.015982</td>\n",
" <td>-0.136895</td>\n",
" <td>0.782518</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>2.199289</td>\n",
" <td>0.006849</td>\n",
" <td>-0.159658</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45</th>\n",
" <td>2.249289</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 0.995434 0.000000 0.000000\n",
"1 0.049967 0.981735 -0.228463 0.000000\n",
"2 0.099933 0.972603 -0.205617 0.391912\n",
"3 0.149900 0.961187 -0.205617 -0.391912\n",
"4 0.199867 0.952055 -0.228463 -0.522549\n",
"5 0.249833 0.938356 -0.274155 -1.565906\n",
"6 0.299800 0.924658 -0.365134 -1.826890\n",
"7 0.349878 0.901826 -0.479239 -1.957382\n",
"8 0.399844 0.876712 -0.548311 -1.304921\n",
"9 0.449811 0.847032 -0.616850 -1.175735\n",
"10 0.499778 0.815068 -0.662542 -0.391476\n",
"11 0.549744 0.780822 -0.661806 -0.652461\n",
"12 0.599822 0.748858 -0.707448 -0.652461\n",
"13 0.649789 0.710046 -0.753927 1.174429\n",
"14 0.699756 0.673516 -0.594003 3.396569\n",
"15 0.749722 0.650685 -0.388387 3.527206\n",
"16 0.799689 0.634703 -0.251309 1.698284\n",
"17 0.849656 0.625571 -0.205617 0.391912\n",
"18 0.899622 0.614155 -0.228463 -2.087874\n",
"19 0.949589 0.602740 -0.387955 -2.479351\n",
"20 0.999667 0.575342 -0.524881 0.130492\n",
"21 1.049633 0.550228 -0.365540 1.304921\n",
"22 1.099600 0.538813 -0.342694 -0.391912\n",
"23 1.149567 0.515982 -0.456926 -1.045098\n",
"24 1.199533 0.493151 -0.434079 0.914461\n",
"25 1.249500 0.472603 -0.365540 1.304776\n",
"26 1.299467 0.456621 -0.296639 0.391302\n",
"27 1.349556 0.442922 -0.319351 -1.825470\n",
"28 1.399556 0.424658 -0.479452 -5.344237\n",
"29 1.449556 0.394977 -0.844749 -3.261579\n",
"30 1.499556 0.340183 -0.890411 1.174168\n",
"31 1.549556 0.305936 -0.639269 3.913894\n",
"32 1.599556 0.276256 -0.525114 2.483765\n",
"33 1.649556 0.253425 -0.388906 1.436850\n",
"34 1.699356 0.237443 -0.365744 1.567647\n",
"35 1.749433 0.216895 -0.273790 -0.261362\n",
"36 1.799422 0.210046 -0.319777 -3.392042\n",
"37 1.849389 0.184931 -0.662542 -4.571288\n",
"38 1.899356 0.143836 -0.799620 -2.220834\n",
"39 1.949322 0.105023 -0.845312 1.698284\n",
"40 1.999289 0.059361 -0.685388 3.919118\n",
"41 2.049256 0.036530 -0.388387 5.094853\n",
"42 2.099222 0.020548 -0.205617 2.217873\n",
"43 2.149189 0.015982 -0.136895 0.782518\n",
"44 2.199289 0.006849 -0.159658 0.000000\n",
"45 2.249289 0.000000 0.000000 0.000000"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datos12"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "a94ddc57-8261-4f18-ba59-0db952e9e025",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>t(s)</th>\n",
" <th>y(m)</th>\n",
" <th>v_y(m/s)</th>\n",
" <th>a_y(m/s^2)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.000000</td>\n",
" <td>0.993750</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.049967</td>\n",
" <td>0.972917</td>\n",
" <td>-0.458130</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.100044</td>\n",
" <td>0.947917</td>\n",
" <td>-0.520602</td>\n",
" <td>0.119074</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.150011</td>\n",
" <td>0.920833</td>\n",
" <td>-0.458639</td>\n",
" <td>1.905185</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.199978</td>\n",
" <td>0.902083</td>\n",
" <td>-0.312709</td>\n",
" <td>1.072859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.249944</td>\n",
" <td>0.889583</td>\n",
" <td>-0.333556</td>\n",
" <td>-0.715239</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.299911</td>\n",
" <td>0.868750</td>\n",
" <td>-0.416945</td>\n",
" <td>-1.190741</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.349878</td>\n",
" <td>0.847917</td>\n",
" <td>-0.437306</td>\n",
" <td>0.595370</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399956</td>\n",
" <td>0.825000</td>\n",
" <td>-0.374833</td>\n",
" <td>0.714445</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449922</td>\n",
" <td>0.810417</td>\n",
" <td>-0.333556</td>\n",
" <td>-0.238148</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499889</td>\n",
" <td>0.791667</td>\n",
" <td>-0.416945</td>\n",
" <td>-0.953652</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549856</td>\n",
" <td>0.768750</td>\n",
" <td>-0.437792</td>\n",
" <td>-1.072859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599822</td>\n",
" <td>0.747917</td>\n",
" <td>-0.500334</td>\n",
" <td>-0.952593</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649789</td>\n",
" <td>0.718750</td>\n",
" <td>-0.562250</td>\n",
" <td>-0.833519</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699867</td>\n",
" <td>0.691667</td>\n",
" <td>-0.562250</td>\n",
" <td>-0.119074</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749833</td>\n",
" <td>0.662500</td>\n",
" <td>-0.583723</td>\n",
" <td>0.238148</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799800</td>\n",
" <td>0.633333</td>\n",
" <td>-0.542028</td>\n",
" <td>1.192065</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849767</td>\n",
" <td>0.608333</td>\n",
" <td>-0.458639</td>\n",
" <td>1.430478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899733</td>\n",
" <td>0.587500</td>\n",
" <td>-0.396097</td>\n",
" <td>0.119207</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>0.568750</td>\n",
" <td>-0.437792</td>\n",
" <td>-0.357619</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.543750</td>\n",
" <td>-0.458639</td>\n",
" <td>-1.667037</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.522917</td>\n",
" <td>-0.562250</td>\n",
" <td>-2.262407</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099711</td>\n",
" <td>0.487500</td>\n",
" <td>-0.728843</td>\n",
" <td>-2.024259</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149678</td>\n",
" <td>0.450000</td>\n",
" <td>-0.750500</td>\n",
" <td>-0.476296</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199644</td>\n",
" <td>0.412500</td>\n",
" <td>-0.771348</td>\n",
" <td>0.357619</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249611</td>\n",
" <td>0.372917</td>\n",
" <td>-0.729653</td>\n",
" <td>0.596032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299578</td>\n",
" <td>0.339583</td>\n",
" <td>-0.687959</td>\n",
" <td>2.741750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349544</td>\n",
" <td>0.304167</td>\n",
" <td>-0.500334</td>\n",
" <td>3.095926</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399511</td>\n",
" <td>0.289583</td>\n",
" <td>-0.312361</td>\n",
" <td>1.786111</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449589</td>\n",
" <td>0.272917</td>\n",
" <td>-0.354009</td>\n",
" <td>-1.071667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499556</td>\n",
" <td>0.254167</td>\n",
" <td>-0.416945</td>\n",
" <td>-1.667037</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549522</td>\n",
" <td>0.231250</td>\n",
" <td>-0.521181</td>\n",
" <td>-2.264924</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599489</td>\n",
" <td>0.202083</td>\n",
" <td>-0.646264</td>\n",
" <td>-0.357619</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>0.166667</td>\n",
" <td>-0.583723</td>\n",
" <td>1.430478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699422</td>\n",
" <td>0.143750</td>\n",
" <td>-0.458639</td>\n",
" <td>1.190741</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749389</td>\n",
" <td>0.120833</td>\n",
" <td>-0.478954</td>\n",
" <td>0.595370</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799467</td>\n",
" <td>0.095833</td>\n",
" <td>-0.416482</td>\n",
" <td>2.619630</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849433</td>\n",
" <td>0.079167</td>\n",
" <td>-0.208472</td>\n",
" <td>1.428889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899400</td>\n",
" <td>0.075000</td>\n",
" <td>-0.229320</td>\n",
" <td>-1.788098</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1.949367</td>\n",
" <td>0.056250</td>\n",
" <td>-0.437792</td>\n",
" <td>-2.262407</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1.999333</td>\n",
" <td>0.031250</td>\n",
" <td>-0.458130</td>\n",
" <td>1.190741</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>2.049411</td>\n",
" <td>0.010417</td>\n",
" <td>-0.312361</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>2.099378</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 0.993750 0.000000 0.000000\n",
"1 0.049967 0.972917 -0.458130 0.000000\n",
"2 0.100044 0.947917 -0.520602 0.119074\n",
"3 0.150011 0.920833 -0.458639 1.905185\n",
"4 0.199978 0.902083 -0.312709 1.072859\n",
"5 0.249944 0.889583 -0.333556 -0.715239\n",
"6 0.299911 0.868750 -0.416945 -1.190741\n",
"7 0.349878 0.847917 -0.437306 0.595370\n",
"8 0.399956 0.825000 -0.374833 0.714445\n",
"9 0.449922 0.810417 -0.333556 -0.238148\n",
"10 0.499889 0.791667 -0.416945 -0.953652\n",
"11 0.549856 0.768750 -0.437792 -1.072859\n",
"12 0.599822 0.747917 -0.500334 -0.952593\n",
"13 0.649789 0.718750 -0.562250 -0.833519\n",
"14 0.699867 0.691667 -0.562250 -0.119074\n",
"15 0.749833 0.662500 -0.583723 0.238148\n",
"16 0.799800 0.633333 -0.542028 1.192065\n",
"17 0.849767 0.608333 -0.458639 1.430478\n",
"18 0.899733 0.587500 -0.396097 0.119207\n",
"19 0.949700 0.568750 -0.437792 -0.357619\n",
"20 0.999667 0.543750 -0.458639 -1.667037\n",
"21 1.049633 0.522917 -0.562250 -2.262407\n",
"22 1.099711 0.487500 -0.728843 -2.024259\n",
"23 1.149678 0.450000 -0.750500 -0.476296\n",
"24 1.199644 0.412500 -0.771348 0.357619\n",
"25 1.249611 0.372917 -0.729653 0.596032\n",
"26 1.299578 0.339583 -0.687959 2.741750\n",
"27 1.349544 0.304167 -0.500334 3.095926\n",
"28 1.399511 0.289583 -0.312361 1.786111\n",
"29 1.449589 0.272917 -0.354009 -1.071667\n",
"30 1.499556 0.254167 -0.416945 -1.667037\n",
"31 1.549522 0.231250 -0.521181 -2.264924\n",
"32 1.599489 0.202083 -0.646264 -0.357619\n",
"33 1.649456 0.166667 -0.583723 1.430478\n",
"34 1.699422 0.143750 -0.458639 1.190741\n",
"35 1.749389 0.120833 -0.478954 0.595370\n",
"36 1.799467 0.095833 -0.416482 2.619630\n",
"37 1.849433 0.079167 -0.208472 1.428889\n",
"38 1.899400 0.075000 -0.229320 -1.788098\n",
"39 1.949367 0.056250 -0.437792 -2.262407\n",
"40 1.999333 0.031250 -0.458130 1.190741\n",
"41 2.049411 0.010417 -0.312361 0.000000\n",
"42 2.099378 0.000000 0.000000 0.000000"
]
},
"execution_count": 35,
"metadata": {},
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}
],
"source": [
"datos13"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "d7ed3a98-1f1d-436c-8869-9e31c63c7e39",
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{
"data": {
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" <td>0.000000</td>\n",
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" <td>0.984055</td>\n",
" <td>-0.159560</td>\n",
" <td>0.000000</td>\n",
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" <td>0.099933</td>\n",
" <td>0.974943</td>\n",
" <td>-0.205148</td>\n",
" <td>-1.173057</td>\n",
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" <th>3</th>\n",
" <td>0.149900</td>\n",
" <td>0.963553</td>\n",
" <td>-0.273531</td>\n",
" <td>-1.824756</td>\n",
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" <th>4</th>\n",
" <td>0.199867</td>\n",
" <td>0.947608</td>\n",
" <td>-0.387502</td>\n",
" <td>-1.952923</td>\n",
" </tr>\n",
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" <th>5</th>\n",
" <td>0.249833</td>\n",
" <td>0.924829</td>\n",
" <td>-0.478147</td>\n",
" <td>-0.911364</td>\n",
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" <tr>\n",
" <th>6</th>\n",
" <td>0.299911</td>\n",
" <td>0.899772</td>\n",
" <td>-0.478147</td>\n",
" <td>-0.130195</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>0.349878</td>\n",
" <td>0.876993</td>\n",
" <td>-0.478679</td>\n",
" <td>0.390585</td>\n",
" </tr>\n",
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" <th>8</th>\n",
" <td>0.399844</td>\n",
" <td>0.851936</td>\n",
" <td>-0.455885</td>\n",
" <td>0.782038</td>\n",
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" <th>9</th>\n",
" <td>0.449811</td>\n",
" <td>0.831435</td>\n",
" <td>-0.387502</td>\n",
" <td>0.391019</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499778</td>\n",
" <td>0.813212</td>\n",
" <td>-0.410296</td>\n",
" <td>-0.521359</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549744</td>\n",
" <td>0.790433</td>\n",
" <td>-0.455885</td>\n",
" <td>-0.782038</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599711</td>\n",
" <td>0.767654</td>\n",
" <td>-0.478679</td>\n",
" <td>-0.650975</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649678</td>\n",
" <td>0.742597</td>\n",
" <td>-0.523685</td>\n",
" <td>-0.650975</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699756</td>\n",
" <td>0.715262</td>\n",
" <td>-0.546454</td>\n",
" <td>0.520780</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749722</td>\n",
" <td>0.687927</td>\n",
" <td>-0.478679</td>\n",
" <td>1.171754</td>\n",
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" <tr>\n",
" <th>16</th>\n",
" <td>0.799689</td>\n",
" <td>0.667426</td>\n",
" <td>-0.410296</td>\n",
" <td>-0.521359</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849656</td>\n",
" <td>0.646925</td>\n",
" <td>-0.524267</td>\n",
" <td>-0.130340</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899622</td>\n",
" <td>0.615034</td>\n",
" <td>-0.478679</td>\n",
" <td>1.171754</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949589</td>\n",
" <td>0.599089</td>\n",
" <td>-0.341534</td>\n",
" <td>0.130195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.580866</td>\n",
" <td>-0.478147</td>\n",
" <td>-2.734093</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.551253</td>\n",
" <td>-0.638239</td>\n",
" <td>-2.603898</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099600</td>\n",
" <td>0.517084</td>\n",
" <td>-0.729416</td>\n",
" <td>0.782038</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149567</td>\n",
" <td>0.478360</td>\n",
" <td>-0.592650</td>\n",
" <td>2.867473</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199533</td>\n",
" <td>0.457859</td>\n",
" <td>-0.387502</td>\n",
" <td>3.519172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249500</td>\n",
" <td>0.439636</td>\n",
" <td>-0.273531</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299467</td>\n",
" <td>0.430524</td>\n",
" <td>-0.341534</td>\n",
" <td>-3.254872</td>\n",
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" <th>27</th>\n",
" <td>1.349544</td>\n",
" <td>0.405467</td>\n",
" <td>-0.637530</td>\n",
" <td>-4.947406</td>\n",
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" <tr>\n",
" <th>28</th>\n",
" <td>1.399511</td>\n",
" <td>0.366743</td>\n",
" <td>-0.843387</td>\n",
" <td>-1.432144</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449478</td>\n",
" <td>0.321184</td>\n",
" <td>-0.797798</td>\n",
" <td>1.694416</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499444</td>\n",
" <td>0.287016</td>\n",
" <td>-0.638239</td>\n",
" <td>2.867473</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549411</td>\n",
" <td>0.257403</td>\n",
" <td>-0.524267</td>\n",
" <td>1.432144</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599378</td>\n",
" <td>0.234624</td>\n",
" <td>-0.478147</td>\n",
" <td>-1.432144</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>0.209567</td>\n",
" <td>-0.660299</td>\n",
" <td>-2.994483</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699422</td>\n",
" <td>0.168565</td>\n",
" <td>-0.820593</td>\n",
" <td>-1.562339</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749389</td>\n",
" <td>0.127563</td>\n",
" <td>-0.797798</td>\n",
" <td>1.694416</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799356</td>\n",
" <td>0.088838</td>\n",
" <td>-0.661033</td>\n",
" <td>3.258492</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849322</td>\n",
" <td>0.061503</td>\n",
" <td>-0.455885</td>\n",
" <td>5.474267</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899289</td>\n",
" <td>0.043280</td>\n",
" <td>-0.136765</td>\n",
" <td>7.290914</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1.949256</td>\n",
" <td>0.047836</td>\n",
" <td>0.295996</td>\n",
" <td>3.775652</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1.999333</td>\n",
" <td>0.072893</td>\n",
" <td>0.295996</td>\n",
" <td>-2.213313</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>2.049300</td>\n",
" <td>0.077449</td>\n",
" <td>0.000000</td>\n",
" <td>-5.468185</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>2.099267</td>\n",
" <td>0.072893</td>\n",
" <td>-0.227942</td>\n",
" <td>-3.649511</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>2.149233</td>\n",
" <td>0.054670</td>\n",
" <td>-0.387502</td>\n",
" <td>-2.215775</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>2.199200</td>\n",
" <td>0.034169</td>\n",
" <td>-0.433090</td>\n",
" <td>0.650975</td>\n",
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" <th>45</th>\n",
" <td>2.249167</td>\n",
" <td>0.011390</td>\n",
" <td>-0.341534</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td>2.299244</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
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],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 0.990888 0.000000 0.000000\n",
"1 0.049967 0.984055 -0.159560 0.000000\n",
"2 0.099933 0.974943 -0.205148 -1.173057\n",
"3 0.149900 0.963553 -0.273531 -1.824756\n",
"4 0.199867 0.947608 -0.387502 -1.952923\n",
"5 0.249833 0.924829 -0.478147 -0.911364\n",
"6 0.299911 0.899772 -0.478147 -0.130195\n",
"7 0.349878 0.876993 -0.478679 0.390585\n",
"8 0.399844 0.851936 -0.455885 0.782038\n",
"9 0.449811 0.831435 -0.387502 0.391019\n",
"10 0.499778 0.813212 -0.410296 -0.521359\n",
"11 0.549744 0.790433 -0.455885 -0.782038\n",
"12 0.599711 0.767654 -0.478679 -0.650975\n",
"13 0.649678 0.742597 -0.523685 -0.650975\n",
"14 0.699756 0.715262 -0.546454 0.520780\n",
"15 0.749722 0.687927 -0.478679 1.171754\n",
"16 0.799689 0.667426 -0.410296 -0.521359\n",
"17 0.849656 0.646925 -0.524267 -0.130340\n",
"18 0.899622 0.615034 -0.478679 1.171754\n",
"19 0.949589 0.599089 -0.341534 0.130195\n",
"20 0.999667 0.580866 -0.478147 -2.734093\n",
"21 1.049633 0.551253 -0.638239 -2.603898\n",
"22 1.099600 0.517084 -0.729416 0.782038\n",
"23 1.149567 0.478360 -0.592650 2.867473\n",
"24 1.199533 0.457859 -0.387502 3.519172\n",
"25 1.249500 0.439636 -0.273531 0.000000\n",
"26 1.299467 0.430524 -0.341534 -3.254872\n",
"27 1.349544 0.405467 -0.637530 -4.947406\n",
"28 1.399511 0.366743 -0.843387 -1.432144\n",
"29 1.449478 0.321184 -0.797798 1.694416\n",
"30 1.499444 0.287016 -0.638239 2.867473\n",
"31 1.549411 0.257403 -0.524267 1.432144\n",
"32 1.599378 0.234624 -0.478147 -1.432144\n",
"33 1.649456 0.209567 -0.660299 -2.994483\n",
"34 1.699422 0.168565 -0.820593 -1.562339\n",
"35 1.749389 0.127563 -0.797798 1.694416\n",
"36 1.799356 0.088838 -0.661033 3.258492\n",
"37 1.849322 0.061503 -0.455885 5.474267\n",
"38 1.899289 0.043280 -0.136765 7.290914\n",
"39 1.949256 0.047836 0.295996 3.775652\n",
"40 1.999333 0.072893 0.295996 -2.213313\n",
"41 2.049300 0.077449 0.000000 -5.468185\n",
"42 2.099267 0.072893 -0.227942 -3.649511\n",
"43 2.149233 0.054670 -0.387502 -2.215775\n",
"44 2.199200 0.034169 -0.433090 0.650975\n",
"45 2.249167 0.011390 -0.341534 0.000000\n",
"46 2.299244 0.000000 0.000000 0.000000"
]
},
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}
],
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},
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{
"data": {
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" <td>-0.312361</td>\n",
" <td>1.530952</td>\n",
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" <th>3</th>\n",
" <td>0.150011</td>\n",
" <td>0.941964</td>\n",
" <td>-0.245427</td>\n",
" <td>-0.127579</td>\n",
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" <th>4</th>\n",
" <td>0.199978</td>\n",
" <td>0.933036</td>\n",
" <td>-0.290372</td>\n",
" <td>-1.403373</td>\n",
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" <th>5</th>\n",
" <td>0.249944</td>\n",
" <td>0.912946</td>\n",
" <td>-0.424390</td>\n",
" <td>-1.660376</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.299911</td>\n",
" <td>0.890625</td>\n",
" <td>-0.446726</td>\n",
" <td>0.255443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.349878</td>\n",
" <td>0.868304</td>\n",
" <td>-0.402054</td>\n",
" <td>-0.255443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399844</td>\n",
" <td>0.850446</td>\n",
" <td>-0.446726</td>\n",
" <td>-0.510317</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449811</td>\n",
" <td>0.823661</td>\n",
" <td>-0.490853</td>\n",
" <td>-0.255159</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499889</td>\n",
" <td>0.801339</td>\n",
" <td>-0.446230</td>\n",
" <td>0.765476</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549856</td>\n",
" <td>0.779018</td>\n",
" <td>-0.424390</td>\n",
" <td>1.148214</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599822</td>\n",
" <td>0.758929</td>\n",
" <td>-0.335045</td>\n",
" <td>0.894049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649789</td>\n",
" <td>0.745536</td>\n",
" <td>-0.312709</td>\n",
" <td>-1.530952</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699756</td>\n",
" <td>0.727679</td>\n",
" <td>-0.490853</td>\n",
" <td>-3.061905</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749833</td>\n",
" <td>0.696429</td>\n",
" <td>-0.647034</td>\n",
" <td>-1.913691</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799800</td>\n",
" <td>0.662946</td>\n",
" <td>-0.670090</td>\n",
" <td>-0.765476</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849767</td>\n",
" <td>0.629464</td>\n",
" <td>-0.714762</td>\n",
" <td>0.766328</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899733</td>\n",
" <td>0.591518</td>\n",
" <td>-0.625417</td>\n",
" <td>4.087080</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>0.566964</td>\n",
" <td>-0.290372</td>\n",
" <td>2.937589</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.562500</td>\n",
" <td>-0.268036</td>\n",
" <td>-1.020635</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.540179</td>\n",
" <td>-0.468542</td>\n",
" <td>-4.465278</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099711</td>\n",
" <td>0.515625</td>\n",
" <td>-0.669345</td>\n",
" <td>-2.806746</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149678</td>\n",
" <td>0.473214</td>\n",
" <td>-0.804107</td>\n",
" <td>-1.786111</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199644</td>\n",
" <td>0.435268</td>\n",
" <td>-0.804107</td>\n",
" <td>-0.766328</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249611</td>\n",
" <td>0.392857</td>\n",
" <td>-0.893453</td>\n",
" <td>-1.021770</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299578</td>\n",
" <td>0.345982</td>\n",
" <td>-0.915789</td>\n",
" <td>2.682146</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349544</td>\n",
" <td>0.301339</td>\n",
" <td>-0.647753</td>\n",
" <td>5.485913</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399511</td>\n",
" <td>0.281250</td>\n",
" <td>-0.312361</td>\n",
" <td>3.317064</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449589</td>\n",
" <td>0.270089</td>\n",
" <td>-0.312361</td>\n",
" <td>0.510317</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499556</td>\n",
" <td>0.250000</td>\n",
" <td>-0.312709</td>\n",
" <td>-0.255159</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549522</td>\n",
" <td>0.238839</td>\n",
" <td>-0.290372</td>\n",
" <td>0.127721</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599489</td>\n",
" <td>0.220982</td>\n",
" <td>-0.335045</td>\n",
" <td>-2.682146</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>0.205357</td>\n",
" <td>-0.513735</td>\n",
" <td>-0.127721</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699422</td>\n",
" <td>0.169643</td>\n",
" <td>-0.446726</td>\n",
" <td>2.296429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749389</td>\n",
" <td>0.160714</td>\n",
" <td>-0.178492</td>\n",
" <td>1.020635</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799467</td>\n",
" <td>0.151786</td>\n",
" <td>-0.356984</td>\n",
" <td>-2.806746</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849433</td>\n",
" <td>0.125000</td>\n",
" <td>-0.513735</td>\n",
" <td>-2.679167</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899400</td>\n",
" <td>0.100446</td>\n",
" <td>-0.580744</td>\n",
" <td>-1.532655</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1.949367</td>\n",
" <td>0.066964</td>\n",
" <td>-0.692426</td>\n",
" <td>-0.894049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1.999333</td>\n",
" <td>0.031250</td>\n",
" <td>-0.670090</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>2.049300</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 0.995536 0.000000 0.000000\n",
"1 0.049967 0.973214 -0.379717 0.000000\n",
"2 0.099933 0.957589 -0.312361 1.530952\n",
"3 0.150011 0.941964 -0.245427 -0.127579\n",
"4 0.199978 0.933036 -0.290372 -1.403373\n",
"5 0.249944 0.912946 -0.424390 -1.660376\n",
"6 0.299911 0.890625 -0.446726 0.255443\n",
"7 0.349878 0.868304 -0.402054 -0.255443\n",
"8 0.399844 0.850446 -0.446726 -0.510317\n",
"9 0.449811 0.823661 -0.490853 -0.255159\n",
"10 0.499889 0.801339 -0.446230 0.765476\n",
"11 0.549856 0.779018 -0.424390 1.148214\n",
"12 0.599822 0.758929 -0.335045 0.894049\n",
"13 0.649789 0.745536 -0.312709 -1.530952\n",
"14 0.699756 0.727679 -0.490853 -3.061905\n",
"15 0.749833 0.696429 -0.647034 -1.913691\n",
"16 0.799800 0.662946 -0.670090 -0.765476\n",
"17 0.849767 0.629464 -0.714762 0.766328\n",
"18 0.899733 0.591518 -0.625417 4.087080\n",
"19 0.949700 0.566964 -0.290372 2.937589\n",
"20 0.999667 0.562500 -0.268036 -1.020635\n",
"21 1.049633 0.540179 -0.468542 -4.465278\n",
"22 1.099711 0.515625 -0.669345 -2.806746\n",
"23 1.149678 0.473214 -0.804107 -1.786111\n",
"24 1.199644 0.435268 -0.804107 -0.766328\n",
"25 1.249611 0.392857 -0.893453 -1.021770\n",
"26 1.299578 0.345982 -0.915789 2.682146\n",
"27 1.349544 0.301339 -0.647753 5.485913\n",
"28 1.399511 0.281250 -0.312361 3.317064\n",
"29 1.449589 0.270089 -0.312361 0.510317\n",
"30 1.499556 0.250000 -0.312709 -0.255159\n",
"31 1.549522 0.238839 -0.290372 0.127721\n",
"32 1.599489 0.220982 -0.335045 -2.682146\n",
"33 1.649456 0.205357 -0.513735 -0.127721\n",
"34 1.699422 0.169643 -0.446726 2.296429\n",
"35 1.749389 0.160714 -0.178492 1.020635\n",
"36 1.799467 0.151786 -0.356984 -2.806746\n",
"37 1.849433 0.125000 -0.513735 -2.679167\n",
"38 1.899400 0.100446 -0.580744 -1.532655\n",
"39 1.949367 0.066964 -0.692426 -0.894049\n",
"40 1.999333 0.031250 -0.670090 0.000000\n",
"41 2.049300 0.000000 0.000000 0.000000"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datos15"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "f4e233df-1032-4759-ac4f-e3af9a550ce7",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>t(s)</th>\n",
" <th>y(m)</th>\n",
" <th>v_y(m/s)</th>\n",
" <th>a_y(m/s^2)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.000000</td>\n",
" <td>1.004762</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.049967</td>\n",
" <td>0.995238</td>\n",
" <td>-0.238254</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.099933</td>\n",
" <td>0.980952</td>\n",
" <td>-0.190603</td>\n",
" <td>0.272472</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.149900</td>\n",
" <td>0.976190</td>\n",
" <td>-0.166778</td>\n",
" <td>-0.408708</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.199867</td>\n",
" <td>0.964286</td>\n",
" <td>-0.262080</td>\n",
" <td>-2.043540</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.249833</td>\n",
" <td>0.950000</td>\n",
" <td>-0.357381</td>\n",
" <td>-1.496931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.299800</td>\n",
" <td>0.928571</td>\n",
" <td>-0.428381</td>\n",
" <td>-0.544339</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.349878</td>\n",
" <td>0.907143</td>\n",
" <td>-0.404582</td>\n",
" <td>-0.408254</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399844</td>\n",
" <td>0.888095</td>\n",
" <td>-0.452683</td>\n",
" <td>0.136085</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449811</td>\n",
" <td>0.861905</td>\n",
" <td>-0.428857</td>\n",
" <td>0.272472</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499778</td>\n",
" <td>0.845238</td>\n",
" <td>-0.381207</td>\n",
" <td>1.905185</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549744</td>\n",
" <td>0.823809</td>\n",
" <td>-0.285587</td>\n",
" <td>0.544339</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599822</td>\n",
" <td>0.816667</td>\n",
" <td>-0.261788</td>\n",
" <td>-0.952593</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649789</td>\n",
" <td>0.797619</td>\n",
" <td>-0.428857</td>\n",
" <td>-2.449524</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699756</td>\n",
" <td>0.773810</td>\n",
" <td>-0.500334</td>\n",
" <td>-0.953652</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749722</td>\n",
" <td>0.747619</td>\n",
" <td>-0.524159</td>\n",
" <td>-1.907304</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799689</td>\n",
" <td>0.721429</td>\n",
" <td>-0.667111</td>\n",
" <td>-2.179776</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849656</td>\n",
" <td>0.680952</td>\n",
" <td>-0.786238</td>\n",
" <td>-0.136085</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899622</td>\n",
" <td>0.642857</td>\n",
" <td>-0.666370</td>\n",
" <td>1.633016</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>0.614286</td>\n",
" <td>-0.594974</td>\n",
" <td>-1.224762</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.583333</td>\n",
" <td>-0.786238</td>\n",
" <td>-4.490794</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.535714</td>\n",
" <td>-1.072143</td>\n",
" <td>-2.316012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099600</td>\n",
" <td>0.476191</td>\n",
" <td>-1.048318</td>\n",
" <td>1.634832</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149567</td>\n",
" <td>0.430952</td>\n",
" <td>-0.857715</td>\n",
" <td>4.087080</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199533</td>\n",
" <td>0.390476</td>\n",
" <td>-0.667111</td>\n",
" <td>1.360847</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249500</td>\n",
" <td>0.364286</td>\n",
" <td>-0.666370</td>\n",
" <td>-0.816508</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299578</td>\n",
" <td>0.323809</td>\n",
" <td>-0.809164</td>\n",
" <td>-1.905185</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349544</td>\n",
" <td>0.283333</td>\n",
" <td>-0.833889</td>\n",
" <td>-0.408254</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399511</td>\n",
" <td>0.240476</td>\n",
" <td>-0.857715</td>\n",
" <td>-1.089888</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449478</td>\n",
" <td>0.197619</td>\n",
" <td>-0.929191</td>\n",
" <td>2.316012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499444</td>\n",
" <td>0.147619</td>\n",
" <td>-0.690937</td>\n",
" <td>6.123810</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549411</td>\n",
" <td>0.128571</td>\n",
" <td>-0.237989</td>\n",
" <td>6.259894</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599489</td>\n",
" <td>0.123810</td>\n",
" <td>-0.071397</td>\n",
" <td>2.313439</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>0.121429</td>\n",
" <td>-0.023825</td>\n",
" <td>-1.224762</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699422</td>\n",
" <td>0.121429</td>\n",
" <td>-0.166778</td>\n",
" <td>-4.495788</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749389</td>\n",
" <td>0.104762</td>\n",
" <td>-0.500334</td>\n",
" <td>-3.950844</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799356</td>\n",
" <td>0.071429</td>\n",
" <td>-0.595635</td>\n",
" <td>0.680423</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849322</td>\n",
" <td>0.045238</td>\n",
" <td>-0.404582</td>\n",
" <td>0.952593</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899400</td>\n",
" <td>0.030952</td>\n",
" <td>-0.452180</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1.949367</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 1.004762 0.000000 0.000000\n",
"1 0.049967 0.995238 -0.238254 0.000000\n",
"2 0.099933 0.980952 -0.190603 0.272472\n",
"3 0.149900 0.976190 -0.166778 -0.408708\n",
"4 0.199867 0.964286 -0.262080 -2.043540\n",
"5 0.249833 0.950000 -0.357381 -1.496931\n",
"6 0.299800 0.928571 -0.428381 -0.544339\n",
"7 0.349878 0.907143 -0.404582 -0.408254\n",
"8 0.399844 0.888095 -0.452683 0.136085\n",
"9 0.449811 0.861905 -0.428857 0.272472\n",
"10 0.499778 0.845238 -0.381207 1.905185\n",
"11 0.549744 0.823809 -0.285587 0.544339\n",
"12 0.599822 0.816667 -0.261788 -0.952593\n",
"13 0.649789 0.797619 -0.428857 -2.449524\n",
"14 0.699756 0.773810 -0.500334 -0.953652\n",
"15 0.749722 0.747619 -0.524159 -1.907304\n",
"16 0.799689 0.721429 -0.667111 -2.179776\n",
"17 0.849656 0.680952 -0.786238 -0.136085\n",
"18 0.899622 0.642857 -0.666370 1.633016\n",
"19 0.949700 0.614286 -0.594974 -1.224762\n",
"20 0.999667 0.583333 -0.786238 -4.490794\n",
"21 1.049633 0.535714 -1.072143 -2.316012\n",
"22 1.099600 0.476191 -1.048318 1.634832\n",
"23 1.149567 0.430952 -0.857715 4.087080\n",
"24 1.199533 0.390476 -0.667111 1.360847\n",
"25 1.249500 0.364286 -0.666370 -0.816508\n",
"26 1.299578 0.323809 -0.809164 -1.905185\n",
"27 1.349544 0.283333 -0.833889 -0.408254\n",
"28 1.399511 0.240476 -0.857715 -1.089888\n",
"29 1.449478 0.197619 -0.929191 2.316012\n",
"30 1.499444 0.147619 -0.690937 6.123810\n",
"31 1.549411 0.128571 -0.237989 6.259894\n",
"32 1.599489 0.123810 -0.071397 2.313439\n",
"33 1.649456 0.121429 -0.023825 -1.224762\n",
"34 1.699422 0.121429 -0.166778 -4.495788\n",
"35 1.749389 0.104762 -0.500334 -3.950844\n",
"36 1.799356 0.071429 -0.595635 0.680423\n",
"37 1.849322 0.045238 -0.404582 0.952593\n",
"38 1.899400 0.030952 -0.452180 0.000000\n",
"39 1.949367 0.000000 0.000000 0.000000"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datos16"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "e7bfa2a6-d726-46d9-8dea-52ba1fcc4ae3",
"metadata": {},
"outputs": [
{
"data": {
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" <td>9.854015e-01</td>\n",
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" <td>9.635036e-01</td>\n",
" <td>-0.438248</td>\n",
" <td>-0.278129</td>\n",
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" <td>0.150011</td>\n",
" <td>9.416058e-01</td>\n",
" <td>-0.365207</td>\n",
" <td>0.417658</td>\n",
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" <th>4</th>\n",
" <td>0.199978</td>\n",
" <td>9.270073e-01</td>\n",
" <td>-0.365207</td>\n",
" <td>-0.695323</td>\n",
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" <th>5</th>\n",
" <td>0.249944</td>\n",
" <td>9.051095e-01</td>\n",
" <td>-0.462082</td>\n",
" <td>-0.695323</td>\n",
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" <tr>\n",
" <th>6</th>\n",
" <td>0.300022</td>\n",
" <td>8.807786e-01</td>\n",
" <td>-0.437762</td>\n",
" <td>-0.556258</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>0.349989</td>\n",
" <td>8.613139e-01</td>\n",
" <td>-0.486943</td>\n",
" <td>-2.781292</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399956</td>\n",
" <td>8.321168e-01</td>\n",
" <td>-0.730414</td>\n",
" <td>-5.011894</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449922</td>\n",
" <td>7.883212e-01</td>\n",
" <td>-0.998232</td>\n",
" <td>-5.429552</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499889</td>\n",
" <td>7.323601e-01</td>\n",
" <td>-1.266051</td>\n",
" <td>-3.341263</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549856</td>\n",
" <td>6.618005e-01</td>\n",
" <td>-1.363439</td>\n",
" <td>0.278129</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599822</td>\n",
" <td>5.961071e-01</td>\n",
" <td>-1.216005</td>\n",
" <td>4.450068</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649900</td>\n",
" <td>5.401460e-01</td>\n",
" <td>-0.924164</td>\n",
" <td>6.396972</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699867</td>\n",
" <td>5.036496e-01</td>\n",
" <td>-0.559984</td>\n",
" <td>6.257908</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749833</td>\n",
" <td>4.841849e-01</td>\n",
" <td>-0.292166</td>\n",
" <td>1.392193</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799800</td>\n",
" <td>4.744526e-01</td>\n",
" <td>-0.389554</td>\n",
" <td>-1.670631</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849767</td>\n",
" <td>4.452555e-01</td>\n",
" <td>-0.535637</td>\n",
" <td>-2.784386</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899733</td>\n",
" <td>4.209246e-01</td>\n",
" <td>-0.608678</td>\n",
" <td>-1.251582</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>3.844282e-01</td>\n",
" <td>-0.705283</td>\n",
" <td>-0.973452</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999778</td>\n",
" <td>3.503650e-01</td>\n",
" <td>-0.680963</td>\n",
" <td>2.225034</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049744</td>\n",
" <td>3.163017e-01</td>\n",
" <td>-0.511290</td>\n",
" <td>2.364098</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099711</td>\n",
" <td>2.992701e-01</td>\n",
" <td>-0.389554</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149678</td>\n",
" <td>2.773723e-01</td>\n",
" <td>-0.535637</td>\n",
" <td>-4.455017</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199644</td>\n",
" <td>2.457421e-01</td>\n",
" <td>-0.827802</td>\n",
" <td>-0.835316</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249611</td>\n",
" <td>1.946472e-01</td>\n",
" <td>-0.706067</td>\n",
" <td>2.920357</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299578</td>\n",
" <td>1.751825e-01</td>\n",
" <td>-0.413442</td>\n",
" <td>4.032874</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349656</td>\n",
" <td>1.532847e-01</td>\n",
" <td>-0.364801</td>\n",
" <td>0.417194</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399622</td>\n",
" <td>1.386861e-01</td>\n",
" <td>-0.340860</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449589</td>\n",
" <td>1.192214e-01</td>\n",
" <td>-0.389554</td>\n",
" <td>0.556877</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499556</td>\n",
" <td>9.975669e-02</td>\n",
" <td>-0.292166</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549522</td>\n",
" <td>9.002433e-02</td>\n",
" <td>-0.340860</td>\n",
" <td>-1.113754</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599489</td>\n",
" <td>6.569343e-02</td>\n",
" <td>-0.462595</td>\n",
" <td>-0.417194</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>4.379562e-02</td>\n",
" <td>-0.364801</td>\n",
" <td>-0.139065</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699533</td>\n",
" <td>2.919708e-02</td>\n",
" <td>-0.437762</td>\n",
" <td>0.000000</td>\n",
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" <tr>\n",
" <th>35</th>\n",
" <td>1.749500</td>\n",
" <td>2.220446e-16</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
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" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 9.975669e-01 0.000000 0.000000\n",
"1 0.050078 9.854015e-01 -0.340481 0.000000\n",
"2 0.100044 9.635036e-01 -0.438248 -0.278129\n",
"3 0.150011 9.416058e-01 -0.365207 0.417658\n",
"4 0.199978 9.270073e-01 -0.365207 -0.695323\n",
"5 0.249944 9.051095e-01 -0.462082 -0.695323\n",
"6 0.300022 8.807786e-01 -0.437762 -0.556258\n",
"7 0.349989 8.613139e-01 -0.486943 -2.781292\n",
"8 0.399956 8.321168e-01 -0.730414 -5.011894\n",
"9 0.449922 7.883212e-01 -0.998232 -5.429552\n",
"10 0.499889 7.323601e-01 -1.266051 -3.341263\n",
"11 0.549856 6.618005e-01 -1.363439 0.278129\n",
"12 0.599822 5.961071e-01 -1.216005 4.450068\n",
"13 0.649900 5.401460e-01 -0.924164 6.396972\n",
"14 0.699867 5.036496e-01 -0.559984 6.257908\n",
"15 0.749833 4.841849e-01 -0.292166 1.392193\n",
"16 0.799800 4.744526e-01 -0.389554 -1.670631\n",
"17 0.849767 4.452555e-01 -0.535637 -2.784386\n",
"18 0.899733 4.209246e-01 -0.608678 -1.251582\n",
"19 0.949700 3.844282e-01 -0.705283 -0.973452\n",
"20 0.999778 3.503650e-01 -0.680963 2.225034\n",
"21 1.049744 3.163017e-01 -0.511290 2.364098\n",
"22 1.099711 2.992701e-01 -0.389554 0.000000\n",
"23 1.149678 2.773723e-01 -0.535637 -4.455017\n",
"24 1.199644 2.457421e-01 -0.827802 -0.835316\n",
"25 1.249611 1.946472e-01 -0.706067 2.920357\n",
"26 1.299578 1.751825e-01 -0.413442 4.032874\n",
"27 1.349656 1.532847e-01 -0.364801 0.417194\n",
"28 1.399622 1.386861e-01 -0.340860 0.000000\n",
"29 1.449589 1.192214e-01 -0.389554 0.556877\n",
"30 1.499556 9.975669e-02 -0.292166 0.000000\n",
"31 1.549522 9.002433e-02 -0.340860 -1.113754\n",
"32 1.599489 6.569343e-02 -0.462595 -0.417194\n",
"33 1.649456 4.379562e-02 -0.364801 -0.139065\n",
"34 1.699533 2.919708e-02 -0.437762 0.000000\n",
"35 1.749500 2.220446e-16 0.000000 0.000000"
]
},
"execution_count": 39,
"metadata": {},
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}
],
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]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "7207cb76-c393-4d02-8282-bf2e521d3dde",
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{
"data": {
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" <td>-0.419394</td>\n",
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" <td>-0.465993</td>\n",
" <td>-1.865216</td>\n",
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" <th>13</th>\n",
" <td>0.649789</td>\n",
" <td>0.755245</td>\n",
" <td>-0.559814</td>\n",
" <td>-1.065838</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699756</td>\n",
" <td>0.720280</td>\n",
" <td>-0.629791</td>\n",
" <td>-0.933645</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749722</td>\n",
" <td>0.692308</td>\n",
" <td>-0.606465</td>\n",
" <td>1.600535</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799689</td>\n",
" <td>0.659674</td>\n",
" <td>-0.513163</td>\n",
" <td>1.600535</td>\n",
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" <tr>\n",
" <th>17</th>\n",
" <td>0.849656</td>\n",
" <td>0.641026</td>\n",
" <td>-0.396535</td>\n",
" <td>1.465527</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899622</td>\n",
" <td>0.620047</td>\n",
" <td>-0.396094</td>\n",
" <td>0.666149</td>\n",
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" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>0.601399</td>\n",
" <td>-0.326195</td>\n",
" <td>0.532919</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.587413</td>\n",
" <td>-0.326558</td>\n",
" <td>-0.266460</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.568765</td>\n",
" <td>-0.373209</td>\n",
" <td>-0.533512</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099600</td>\n",
" <td>0.550117</td>\n",
" <td>-0.373209</td>\n",
" <td>-0.800268</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149567</td>\n",
" <td>0.531469</td>\n",
" <td>-0.443186</td>\n",
" <td>-1.733913</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199533</td>\n",
" <td>0.505827</td>\n",
" <td>-0.559814</td>\n",
" <td>-3.730433</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249500</td>\n",
" <td>0.475525</td>\n",
" <td>-0.792189</td>\n",
" <td>-1.065838</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299578</td>\n",
" <td>0.426573</td>\n",
" <td>-0.745589</td>\n",
" <td>3.730433</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349544</td>\n",
" <td>0.400932</td>\n",
" <td>-0.349884</td>\n",
" <td>5.462419</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399511</td>\n",
" <td>0.391608</td>\n",
" <td>-0.186605</td>\n",
" <td>1.333779</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449478</td>\n",
" <td>0.382284</td>\n",
" <td>-0.233256</td>\n",
" <td>0.533512</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499444</td>\n",
" <td>0.368298</td>\n",
" <td>-0.163279</td>\n",
" <td>-2.531365</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549411</td>\n",
" <td>0.365967</td>\n",
" <td>-0.396094</td>\n",
" <td>-4.663041</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599489</td>\n",
" <td>0.328671</td>\n",
" <td>-0.745589</td>\n",
" <td>-6.927946</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>0.291375</td>\n",
" <td>-1.003000</td>\n",
" <td>-3.597203</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699422</td>\n",
" <td>0.228438</td>\n",
" <td>-1.189604</td>\n",
" <td>-2.534180</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749389</td>\n",
" <td>0.172494</td>\n",
" <td>-1.189604</td>\n",
" <td>1.200401</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799356</td>\n",
" <td>0.109557</td>\n",
" <td>-1.119628</td>\n",
" <td>2.131676</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849322</td>\n",
" <td>0.060606</td>\n",
" <td>-0.931987</td>\n",
" <td>6.927946</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899400</td>\n",
" <td>0.016317</td>\n",
" <td>-0.489293</td>\n",
" <td>6.528257</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1.949367</td>\n",
" <td>0.011655</td>\n",
" <td>-0.163279</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1.999333</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 0.988345 0.000000 0.000000\n",
"1 0.049967 0.979021 -0.209930 0.000000\n",
"2 0.099933 0.967366 -0.326558 -0.533512\n",
"3 0.149900 0.946387 -0.303233 0.133378\n",
"4 0.199867 0.937063 -0.256581 -0.400134\n",
"5 0.249833 0.920746 -0.373209 -1.065838\n",
"6 0.299800 0.899767 -0.372795 -0.266460\n",
"7 0.349878 0.883450 -0.372795 -0.532919\n",
"8 0.399844 0.862471 -0.443186 -0.666149\n",
"9 0.449811 0.839161 -0.443186 0.666890\n",
"10 0.499778 0.818182 -0.373209 0.000000\n",
"11 0.549744 0.801865 -0.419394 -0.532919\n",
"12 0.599822 0.776224 -0.465993 -1.865216\n",
"13 0.649789 0.755245 -0.559814 -1.065838\n",
"14 0.699756 0.720280 -0.629791 -0.933645\n",
"15 0.749722 0.692308 -0.606465 1.600535\n",
"16 0.799689 0.659674 -0.513163 1.600535\n",
"17 0.849656 0.641026 -0.396535 1.465527\n",
"18 0.899622 0.620047 -0.396094 0.666149\n",
"19 0.949700 0.601399 -0.326195 0.532919\n",
"20 0.999667 0.587413 -0.326558 -0.266460\n",
"21 1.049633 0.568765 -0.373209 -0.533512\n",
"22 1.099600 0.550117 -0.373209 -0.800268\n",
"23 1.149567 0.531469 -0.443186 -1.733913\n",
"24 1.199533 0.505827 -0.559814 -3.730433\n",
"25 1.249500 0.475525 -0.792189 -1.065838\n",
"26 1.299578 0.426573 -0.745589 3.730433\n",
"27 1.349544 0.400932 -0.349884 5.462419\n",
"28 1.399511 0.391608 -0.186605 1.333779\n",
"29 1.449478 0.382284 -0.233256 0.533512\n",
"30 1.499444 0.368298 -0.163279 -2.531365\n",
"31 1.549411 0.365967 -0.396094 -4.663041\n",
"32 1.599489 0.328671 -0.745589 -6.927946\n",
"33 1.649456 0.291375 -1.003000 -3.597203\n",
"34 1.699422 0.228438 -1.189604 -2.534180\n",
"35 1.749389 0.172494 -1.189604 1.200401\n",
"36 1.799356 0.109557 -1.119628 2.131676\n",
"37 1.849322 0.060606 -0.931987 6.927946\n",
"38 1.899400 0.016317 -0.489293 6.528257\n",
"39 1.949367 0.011655 -0.163279 0.000000\n",
"40 1.999333 0.000000 0.000000 0.000000"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datos18"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "89780e11-ce95-4e91-962a-4ad9b0eb0abc",
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>t(s)</th>\n",
" <th>y(m)</th>\n",
" <th>v_y(m/s)</th>\n",
" <th>a_y(m/s^2)</th>\n",
" </tr>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.049967</td>\n",
" <td>0.985037</td>\n",
" <td>-0.224589</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.099933</td>\n",
" <td>0.977556</td>\n",
" <td>-0.224589</td>\n",
" <td>-0.713455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.149900</td>\n",
" <td>0.962593</td>\n",
" <td>-0.324406</td>\n",
" <td>-2.425748</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.199867</td>\n",
" <td>0.945137</td>\n",
" <td>-0.449177</td>\n",
" <td>-1.712293</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.249833</td>\n",
" <td>0.917706</td>\n",
" <td>-0.524040</td>\n",
" <td>-0.142533</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.299800</td>\n",
" <td>0.892768</td>\n",
" <td>-0.448678</td>\n",
" <td>1.140261</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.349878</td>\n",
" <td>0.872818</td>\n",
" <td>-0.398825</td>\n",
" <td>0.570130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399844</td>\n",
" <td>0.852868</td>\n",
" <td>-0.399269</td>\n",
" <td>0.285065</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449811</td>\n",
" <td>0.832918</td>\n",
" <td>-0.374314</td>\n",
" <td>-1.569602</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499778</td>\n",
" <td>0.815461</td>\n",
" <td>-0.524040</td>\n",
" <td>-1.569602</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549744</td>\n",
" <td>0.780549</td>\n",
" <td>-0.598903</td>\n",
" <td>2.280521</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599711</td>\n",
" <td>0.755611</td>\n",
" <td>-0.274192</td>\n",
" <td>2.993184</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649789</td>\n",
" <td>0.753117</td>\n",
" <td>-0.224339</td>\n",
" <td>-0.997728</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699756</td>\n",
" <td>0.733167</td>\n",
" <td>-0.449177</td>\n",
" <td>-2.850651</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749722</td>\n",
" <td>0.708229</td>\n",
" <td>-0.499086</td>\n",
" <td>-1.712293</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799689</td>\n",
" <td>0.683292</td>\n",
" <td>-0.598903</td>\n",
" <td>-5.136879</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849656</td>\n",
" <td>0.648379</td>\n",
" <td>-0.998172</td>\n",
" <td>-5.131172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899622</td>\n",
" <td>0.583541</td>\n",
" <td>-1.196476</td>\n",
" <td>1.140261</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>0.528678</td>\n",
" <td>-0.847504</td>\n",
" <td>6.271433</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999667</td>\n",
" <td>0.498753</td>\n",
" <td>-0.524040</td>\n",
" <td>5.273705</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049633</td>\n",
" <td>0.476309</td>\n",
" <td>-0.349360</td>\n",
" <td>3.995350</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099600</td>\n",
" <td>0.463840</td>\n",
" <td>-0.124771</td>\n",
" <td>0.428073</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149567</td>\n",
" <td>0.463840</td>\n",
" <td>-0.249543</td>\n",
" <td>-1.712293</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199533</td>\n",
" <td>0.438903</td>\n",
" <td>-0.399269</td>\n",
" <td>-3.705847</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249500</td>\n",
" <td>0.423940</td>\n",
" <td>-0.523458</td>\n",
" <td>-1.567858</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299578</td>\n",
" <td>0.386534</td>\n",
" <td>-0.648091</td>\n",
" <td>-2.850651</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349544</td>\n",
" <td>0.359102</td>\n",
" <td>-0.723674</td>\n",
" <td>-1.282793</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399511</td>\n",
" <td>0.314215</td>\n",
" <td>-0.848446</td>\n",
" <td>-0.856147</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449478</td>\n",
" <td>0.274314</td>\n",
" <td>-0.773583</td>\n",
" <td>0.427598</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499444</td>\n",
" <td>0.236908</td>\n",
" <td>-0.797651</td>\n",
" <td>-1.995456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549522</td>\n",
" <td>0.194514</td>\n",
" <td>-0.972136</td>\n",
" <td>-2.993184</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599489</td>\n",
" <td>0.139651</td>\n",
" <td>-1.122943</td>\n",
" <td>1.282793</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649456</td>\n",
" <td>0.082294</td>\n",
" <td>-0.873400</td>\n",
" <td>5.710295</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699422</td>\n",
" <td>0.052369</td>\n",
" <td>-0.342002</td>\n",
" <td>5.237220</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.766122</td>\n",
" <td>0.042394</td>\n",
" <td>-0.112210</td>\n",
" <td>-0.418858</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.832767</td>\n",
" <td>0.037406</td>\n",
" <td>-0.363447</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.882767</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 1.000000 0.000000 0.000000\n",
"1 0.049967 0.985037 -0.224589 0.000000\n",
"2 0.099933 0.977556 -0.224589 -0.713455\n",
"3 0.149900 0.962593 -0.324406 -2.425748\n",
"4 0.199867 0.945137 -0.449177 -1.712293\n",
"5 0.249833 0.917706 -0.524040 -0.142533\n",
"6 0.299800 0.892768 -0.448678 1.140261\n",
"7 0.349878 0.872818 -0.398825 0.570130\n",
"8 0.399844 0.852868 -0.399269 0.285065\n",
"9 0.449811 0.832918 -0.374314 -1.569602\n",
"10 0.499778 0.815461 -0.524040 -1.569602\n",
"11 0.549744 0.780549 -0.598903 2.280521\n",
"12 0.599711 0.755611 -0.274192 2.993184\n",
"13 0.649789 0.753117 -0.224339 -0.997728\n",
"14 0.699756 0.733167 -0.449177 -2.850651\n",
"15 0.749722 0.708229 -0.499086 -1.712293\n",
"16 0.799689 0.683292 -0.598903 -5.136879\n",
"17 0.849656 0.648379 -0.998172 -5.131172\n",
"18 0.899622 0.583541 -1.196476 1.140261\n",
"19 0.949700 0.528678 -0.847504 6.271433\n",
"20 0.999667 0.498753 -0.524040 5.273705\n",
"21 1.049633 0.476309 -0.349360 3.995350\n",
"22 1.099600 0.463840 -0.124771 0.428073\n",
"23 1.149567 0.463840 -0.249543 -1.712293\n",
"24 1.199533 0.438903 -0.399269 -3.705847\n",
"25 1.249500 0.423940 -0.523458 -1.567858\n",
"26 1.299578 0.386534 -0.648091 -2.850651\n",
"27 1.349544 0.359102 -0.723674 -1.282793\n",
"28 1.399511 0.314215 -0.848446 -0.856147\n",
"29 1.449478 0.274314 -0.773583 0.427598\n",
"30 1.499444 0.236908 -0.797651 -1.995456\n",
"31 1.549522 0.194514 -0.972136 -2.993184\n",
"32 1.599489 0.139651 -1.122943 1.282793\n",
"33 1.649456 0.082294 -0.873400 5.710295\n",
"34 1.699422 0.052369 -0.342002 5.237220\n",
"35 1.766122 0.042394 -0.112210 -0.418858\n",
"36 1.832767 0.037406 -0.363447 0.000000\n",
"37 1.882767 0.000000 0.000000 0.000000"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datos19"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "16004674-fbc6-4830-9203-435e1bf3d993",
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>t(s)</th>\n",
" <th>y(m)</th>\n",
" <th>v_y(m/s)</th>\n",
" <th>a_y(m/s^2)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.050078</td>\n",
" <td>0.992908</td>\n",
" <td>-0.141781</td>\n",
" <td>0.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.100044</td>\n",
" <td>0.985816</td>\n",
" <td>-0.189251</td>\n",
" <td>-2.702390e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.150011</td>\n",
" <td>0.973995</td>\n",
" <td>-0.189251</td>\n",
" <td>2.705396e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.199978</td>\n",
" <td>0.966903</td>\n",
" <td>-0.141939</td>\n",
" <td>1.531731e-14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.249944</td>\n",
" <td>0.959811</td>\n",
" <td>-0.189041</td>\n",
" <td>-1.351195e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.300022</td>\n",
" <td>0.947990</td>\n",
" <td>-0.283562</td>\n",
" <td>-2.432151e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.349989</td>\n",
" <td>0.931442</td>\n",
" <td>-0.425816</td>\n",
" <td>-8.107171e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399956</td>\n",
" <td>0.905437</td>\n",
" <td>-0.402159</td>\n",
" <td>6.763490e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449922</td>\n",
" <td>0.891253</td>\n",
" <td>-0.307534</td>\n",
" <td>6.763490e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499889</td>\n",
" <td>0.874704</td>\n",
" <td>-0.354847</td>\n",
" <td>-9.468886e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549856</td>\n",
" <td>0.855792</td>\n",
" <td>-0.402159</td>\n",
" <td>-6.755976e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599822</td>\n",
" <td>0.834515</td>\n",
" <td>-0.425343</td>\n",
" <td>-1.621434e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649900</td>\n",
" <td>0.813239</td>\n",
" <td>-0.543494</td>\n",
" <td>-6.755976e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699867</td>\n",
" <td>0.780142</td>\n",
" <td>-0.544098</td>\n",
" <td>-9.458367e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749833</td>\n",
" <td>0.758865</td>\n",
" <td>-0.567754</td>\n",
" <td>-1.352698e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799800</td>\n",
" <td>0.723404</td>\n",
" <td>-0.733349</td>\n",
" <td>-1.487968e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849767</td>\n",
" <td>0.685579</td>\n",
" <td>-0.709693</td>\n",
" <td>2.164317e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899733</td>\n",
" <td>0.652482</td>\n",
" <td>-0.520442</td>\n",
" <td>3.242869e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949700</td>\n",
" <td>0.633570</td>\n",
" <td>-0.354452</td>\n",
" <td>1.756554e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999778</td>\n",
" <td>0.617021</td>\n",
" <td>-0.354452</td>\n",
" <td>6.755976e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049744</td>\n",
" <td>0.598109</td>\n",
" <td>-0.307534</td>\n",
" <td>-4.053586e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099711</td>\n",
" <td>0.586288</td>\n",
" <td>-0.354847</td>\n",
" <td>-1.758507e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149678</td>\n",
" <td>0.562648</td>\n",
" <td>-0.520442</td>\n",
" <td>-3.246475e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199644</td>\n",
" <td>0.534279</td>\n",
" <td>-0.662380</td>\n",
" <td>-5.404781e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249611</td>\n",
" <td>0.496454</td>\n",
" <td>-0.614384</td>\n",
" <td>2.702390e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299689</td>\n",
" <td>0.472813</td>\n",
" <td>-0.354452</td>\n",
" <td>4.458944e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349656</td>\n",
" <td>0.460993</td>\n",
" <td>-0.165595</td>\n",
" <td>1.756554e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399622</td>\n",
" <td>0.456265</td>\n",
" <td>-0.165595</td>\n",
" <td>-2.029047e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449589</td>\n",
" <td>0.444444</td>\n",
" <td>-0.378503</td>\n",
" <td>-2.705396e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499556</td>\n",
" <td>0.418440</td>\n",
" <td>-0.473129</td>\n",
" <td>-1.621434e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549522</td>\n",
" <td>0.397163</td>\n",
" <td>-0.496233</td>\n",
" <td>-1.486315e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599600</td>\n",
" <td>0.368794</td>\n",
" <td>-0.638014</td>\n",
" <td>-2.837510e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649567</td>\n",
" <td>0.333333</td>\n",
" <td>-0.780662</td>\n",
" <td>-6.755976e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699533</td>\n",
" <td>0.290780</td>\n",
" <td>-0.733349</td>\n",
" <td>2.299587e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.749500</td>\n",
" <td>0.260047</td>\n",
" <td>-0.520442</td>\n",
" <td>1.893777e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>1.799467</td>\n",
" <td>0.238771</td>\n",
" <td>-0.520442</td>\n",
" <td>2.975936e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>1.849433</td>\n",
" <td>0.208038</td>\n",
" <td>-0.307534</td>\n",
" <td>1.487968e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.899400</td>\n",
" <td>0.208038</td>\n",
" <td>-0.236564</td>\n",
" <td>-2.972629e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>1.949367</td>\n",
" <td>0.184397</td>\n",
" <td>-0.685275</td>\n",
" <td>-4.999422e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>1.999444</td>\n",
" <td>0.139480</td>\n",
" <td>-0.779795</td>\n",
" <td>-2.567271e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>2.049411</td>\n",
" <td>0.106383</td>\n",
" <td>-0.851632</td>\n",
" <td>-5.404781e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>2.099378</td>\n",
" <td>0.054374</td>\n",
" <td>-0.922601</td>\n",
" <td>2.840666e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>2.149344</td>\n",
" <td>0.014184</td>\n",
" <td>-0.544098</td>\n",
" <td>0.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>2.199311</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 1.000000 0.000000 0.000000e+00\n",
"1 0.050078 0.992908 -0.141781 0.000000e+00\n",
"2 0.100044 0.985816 -0.189251 -2.702390e-01\n",
"3 0.150011 0.973995 -0.189251 2.705396e-01\n",
"4 0.199978 0.966903 -0.141939 1.531731e-14\n",
"5 0.249944 0.959811 -0.189041 -1.351195e+00\n",
"6 0.300022 0.947990 -0.283562 -2.432151e+00\n",
"7 0.349989 0.931442 -0.425816 -8.107171e-01\n",
"8 0.399956 0.905437 -0.402159 6.763490e-01\n",
"9 0.449922 0.891253 -0.307534 6.763490e-01\n",
"10 0.499889 0.874704 -0.354847 -9.468886e-01\n",
"11 0.549856 0.855792 -0.402159 -6.755976e-01\n",
"12 0.599822 0.834515 -0.425343 -1.621434e+00\n",
"13 0.649900 0.813239 -0.543494 -6.755976e-01\n",
"14 0.699867 0.780142 -0.544098 -9.458367e-01\n",
"15 0.749833 0.758865 -0.567754 -1.352698e+00\n",
"16 0.799800 0.723404 -0.733349 -1.487968e+00\n",
"17 0.849767 0.685579 -0.709693 2.164317e+00\n",
"18 0.899733 0.652482 -0.520442 3.242869e+00\n",
"19 0.949700 0.633570 -0.354452 1.756554e+00\n",
"20 0.999778 0.617021 -0.354452 6.755976e-01\n",
"21 1.049744 0.598109 -0.307534 -4.053586e-01\n",
"22 1.099711 0.586288 -0.354847 -1.758507e+00\n",
"23 1.149678 0.562648 -0.520442 -3.246475e+00\n",
"24 1.199644 0.534279 -0.662380 -5.404781e-01\n",
"25 1.249611 0.496454 -0.614384 2.702390e+00\n",
"26 1.299689 0.472813 -0.354452 4.458944e+00\n",
"27 1.349656 0.460993 -0.165595 1.756554e+00\n",
"28 1.399622 0.456265 -0.165595 -2.029047e+00\n",
"29 1.449589 0.444444 -0.378503 -2.705396e+00\n",
"30 1.499556 0.418440 -0.473129 -1.621434e+00\n",
"31 1.549522 0.397163 -0.496233 -1.486315e+00\n",
"32 1.599600 0.368794 -0.638014 -2.837510e+00\n",
"33 1.649567 0.333333 -0.780662 -6.755976e-01\n",
"34 1.699533 0.290780 -0.733349 2.299587e+00\n",
"35 1.749500 0.260047 -0.520442 1.893777e+00\n",
"36 1.799467 0.238771 -0.520442 2.975936e+00\n",
"37 1.849433 0.208038 -0.307534 1.487968e+00\n",
"38 1.899400 0.208038 -0.236564 -2.972629e+00\n",
"39 1.949367 0.184397 -0.685275 -4.999422e+00\n",
"40 1.999444 0.139480 -0.779795 -2.567271e+00\n",
"41 2.049411 0.106383 -0.851632 -5.404781e-01\n",
"42 2.099378 0.054374 -0.922601 2.840666e+00\n",
"43 2.149344 0.014184 -0.544098 0.000000e+00\n",
"44 2.199311 0.000000 0.000000 0.000000e+00"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datos20"
]
},
{
"cell_type": "code",
"execution_count": 98,
"id": "fb233235-e1d9-43ca-92a1-80ff0af0f9b9",
"metadata": {},
"outputs": [],
"source": [
"MediaDatosExperimentales = (datos11+datos12+datos13+datos14+datos15+datos16+datos17+datos18+datos19+datos20)/10\n",
"MediaDatosExperimentales = MediaDatosExperimentales.iloc[:36]"
]
},
{
"cell_type": "code",
"execution_count": 99,
"id": "4bc9bca7-b351-4b32-9268-9f9d0728ffba",
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>t(s)</th>\n",
" <th>y(m)</th>\n",
" <th>v_y(m/s)</th>\n",
" <th>a_y(m/s^2)</th>\n",
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" <td>0.000000</td>\n",
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" <th>1</th>\n",
" <td>0.049989</td>\n",
" <td>0.984260</td>\n",
" <td>-0.261201</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.099967</td>\n",
" <td>0.970284</td>\n",
" <td>-0.291341</td>\n",
" <td>-0.210759</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.149944</td>\n",
" <td>0.955136</td>\n",
" <td>-0.285563</td>\n",
" <td>-0.271594</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.199911</td>\n",
" <td>0.941744</td>\n",
" <td>-0.306338</td>\n",
" <td>-0.897727</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>0.249889</td>\n",
" <td>0.924518</td>\n",
" <td>-0.383152</td>\n",
" <td>-1.118869</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.299889</td>\n",
" <td>0.903437</td>\n",
" <td>-0.423277</td>\n",
" <td>-0.660732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>0.349900</td>\n",
" <td>0.882188</td>\n",
" <td>-0.441777</td>\n",
" <td>-0.505778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.399878</td>\n",
" <td>0.859266</td>\n",
" <td>-0.476189</td>\n",
" <td>-0.410643</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.449844</td>\n",
" <td>0.834596</td>\n",
" <td>-0.486620</td>\n",
" <td>-0.705746</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.499822</td>\n",
" <td>0.810631</td>\n",
" <td>-0.534322</td>\n",
" <td>-0.637357</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.549800</td>\n",
" <td>0.781189</td>\n",
" <td>-0.569572</td>\n",
" <td>-0.316064</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.599800</td>\n",
" <td>0.753689</td>\n",
" <td>-0.551990</td>\n",
" <td>-0.139395</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.649800</td>\n",
" <td>0.725990</td>\n",
" <td>-0.582697</td>\n",
" <td>-0.129346</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.699789</td>\n",
" <td>0.695427</td>\n",
" <td>-0.577824</td>\n",
" <td>0.276410</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.749767</td>\n",
" <td>0.668228</td>\n",
" <td>-0.541942</td>\n",
" <td>0.289184</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.799733</td>\n",
" <td>0.641262</td>\n",
" <td>-0.551451</td>\n",
" <td>-0.463123</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.849711</td>\n",
" <td>0.613112</td>\n",
" <td>-0.588359</td>\n",
" <td>0.041256</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.899678</td>\n",
" <td>0.582459</td>\n",
" <td>-0.560203</td>\n",
" <td>0.938087</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0.949678</td>\n",
" <td>0.557103</td>\n",
" <td>-0.479448</td>\n",
" <td>0.580063</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.999689</td>\n",
" <td>0.534507</td>\n",
" <td>-0.495660</td>\n",
" <td>-0.213848</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1.049655</td>\n",
" <td>0.507548</td>\n",
" <td>-0.520275</td>\n",
" <td>-0.465780</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.099644</td>\n",
" <td>0.482503</td>\n",
" <td>-0.526942</td>\n",
" <td>-0.388076</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1.149611</td>\n",
" <td>0.454873</td>\n",
" <td>-0.567239</td>\n",
" <td>-0.697265</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>1.199588</td>\n",
" <td>0.425812</td>\n",
" <td>-0.595202</td>\n",
" <td>-0.355830</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>1.249556</td>\n",
" <td>0.395388</td>\n",
" <td>-0.604996</td>\n",
" <td>0.133559</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1.299567</td>\n",
" <td>0.365323</td>\n",
" <td>-0.581352</td>\n",
" <td>0.738383</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.349568</td>\n",
" <td>0.337251</td>\n",
" <td>-0.530544</td>\n",
" <td>0.709335</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1.399538</td>\n",
" <td>0.312288</td>\n",
" <td>-0.504008</td>\n",
" <td>-0.167453</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1.449530</td>\n",
" <td>0.286874</td>\n",
" <td>-0.547469</td>\n",
" <td>0.216806</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1.499511</td>\n",
" <td>0.257560</td>\n",
" <td>-0.504481</td>\n",
" <td>0.209500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1.549492</td>\n",
" <td>0.236440</td>\n",
" <td>-0.488061</td>\n",
" <td>-0.157956</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>1.599496</td>\n",
" <td>0.208759</td>\n",
" <td>-0.551042</td>\n",
" <td>-0.897100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>1.649477</td>\n",
" <td>0.181348</td>\n",
" <td>-0.565455</td>\n",
" <td>-0.044550</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>1.699438</td>\n",
" <td>0.152245</td>\n",
" <td>-0.549273</td>\n",
" <td>0.307430</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.751089</td>\n",
" <td>0.125882</td>\n",
" <td>-0.460627</td>\n",
" <td>0.282953</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" t(s) y(m) v_y(m/s) a_y(m/s^2)\n",
"0 0.000000 0.996397 0.000000 0.000000\n",
"1 0.049989 0.984260 -0.261201 0.000000\n",
"2 0.099967 0.970284 -0.291341 -0.210759\n",
"3 0.149944 0.955136 -0.285563 -0.271594\n",
"4 0.199911 0.941744 -0.306338 -0.897727\n",
"5 0.249889 0.924518 -0.383152 -1.118869\n",
"6 0.299889 0.903437 -0.423277 -0.660732\n",
"7 0.349900 0.882188 -0.441777 -0.505778\n",
"8 0.399878 0.859266 -0.476189 -0.410643\n",
"9 0.449844 0.834596 -0.486620 -0.705746\n",
"10 0.499822 0.810631 -0.534322 -0.637357\n",
"11 0.549800 0.781189 -0.569572 -0.316064\n",
"12 0.599800 0.753689 -0.551990 -0.139395\n",
"13 0.649800 0.725990 -0.582697 -0.129346\n",
"14 0.699789 0.695427 -0.577824 0.276410\n",
"15 0.749767 0.668228 -0.541942 0.289184\n",
"16 0.799733 0.641262 -0.551451 -0.463123\n",
"17 0.849711 0.613112 -0.588359 0.041256\n",
"18 0.899678 0.582459 -0.560203 0.938087\n",
"19 0.949678 0.557103 -0.479448 0.580063\n",
"20 0.999689 0.534507 -0.495660 -0.213848\n",
"21 1.049655 0.507548 -0.520275 -0.465780\n",
"22 1.099644 0.482503 -0.526942 -0.388076\n",
"23 1.149611 0.454873 -0.567239 -0.697265\n",
"24 1.199588 0.425812 -0.595202 -0.355830\n",
"25 1.249556 0.395388 -0.604996 0.133559\n",
"26 1.299567 0.365323 -0.581352 0.738383\n",
"27 1.349568 0.337251 -0.530544 0.709335\n",
"28 1.399538 0.312288 -0.504008 -0.167453\n",
"29 1.449530 0.286874 -0.547469 0.216806\n",
"30 1.499511 0.257560 -0.504481 0.209500\n",
"31 1.549492 0.236440 -0.488061 -0.157956\n",
"32 1.599496 0.208759 -0.551042 -0.897100\n",
"33 1.649477 0.181348 -0.565455 -0.044550\n",
"34 1.699438 0.152245 -0.549273 0.307430\n",
"35 1.751089 0.125882 -0.460627 0.282953"
]
},
"execution_count": 99,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"MediaDatosExperimentales"
]
},
{
"cell_type": "code",
"execution_count": 103,
"id": "be1cb1ac-e086-43eb-ab45-797c559dd4b6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Posición de la servilleta en función del tiempo')"
]
},
"execution_count": 103,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(MediaDatosExperimentales['t(s)'], MediaDatosExperimentales['y(m)'], label='MediaDatosExperimentales')\n",
"plt.xlabel('Tiempo (s)')\n",
"plt.ylabel('Posición (m)')\n",
"plt.title('Posición de la servilleta en función del tiempo')\n"
]
},
{
"cell_type": "code",
"execution_count": 107,
"id": "de82febd-be5f-46c2-8283-7d43193a3b73",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt #esto es para hacer texto donde especifique que en vez de unir todos los puntos, se deja como una grafica de dispersion#\n",
"plt.scatter(MediaDatosExperimentales['t(s)'], MediaDatosExperimentales['y(m)'])\n",
"plt.xlabel('Tiempo (s)')\n",
"plt.ylabel('Posición en y (m)')\n",
"plt.title('Posición de la servilleta en función del tiempo')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "33ee2a47-e6d8-44e0-85e4-3a6e8486d4c9",
"metadata": {},
"source": [
"Linealización de la servilleta extendida"
]
},
{
"cell_type": "code",
"execution_count": 130,
"id": "57ce5e69-a60c-404b-9c84-0073fa00d47c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 0.000000\n",
"1 0.049989\n",
"2 0.099967\n",
"3 0.149944\n",
"4 0.199911\n",
"5 0.249889\n",
"6 0.299889\n",
"7 0.349900\n",
"8 0.399878\n",
"9 0.449844\n",
"10 0.499822\n",
"11 0.549800\n",
"12 0.599800\n",
"13 0.649800\n",
"14 0.699789\n",
"15 0.749767\n",
"16 0.799733\n",
"17 0.849711\n",
"18 0.899678\n",
"19 0.949678\n",
"20 0.999689\n",
"21 1.049655\n",
"22 1.099644\n",
"23 1.149611\n",
"24 1.199588\n",
"25 1.249556\n",
"26 1.299567\n",
"27 1.349568\n",
"28 1.399538\n",
"29 1.449530\n",
"30 1.499511\n",
"31 1.549492\n",
"32 1.599496\n",
"33 1.649477\n",
"34 1.699438\n",
"35 1.751089\n",
"Name: t(s), dtype: float64"
]
},
"execution_count": 130,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"MediaDatosExperimentales['t(s)']"
]
},
{
"cell_type": "code",
"execution_count": 131,
"id": "f1f6fc91-fad1-459a-939e-be86e00f6bf5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 0.996397\n",
"1 0.984260\n",
"2 0.970284\n",
"3 0.955136\n",
"4 0.941744\n",
"5 0.924518\n",
"6 0.903437\n",
"7 0.882188\n",
"8 0.859266\n",
"9 0.834596\n",
"10 0.810631\n",
"11 0.781189\n",
"12 0.753689\n",
"13 0.725990\n",
"14 0.695427\n",
"15 0.668228\n",
"16 0.641262\n",
"17 0.613112\n",
"18 0.582459\n",
"19 0.557103\n",
"20 0.534507\n",
"21 0.507548\n",
"22 0.482503\n",
"23 0.454873\n",
"24 0.425812\n",
"25 0.395388\n",
"26 0.365323\n",
"27 0.337251\n",
"28 0.312288\n",
"29 0.286874\n",
"30 0.257560\n",
"31 0.236440\n",
"32 0.208759\n",
"33 0.181348\n",
"34 0.152245\n",
"35 0.125882\n",
"Name: y(m), dtype: float64"
]
},
"execution_count": 131,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"MediaDatosExperimentales['y(m)']"
]
},
{
"cell_type": "code",
"execution_count": 132,
"id": "c7391741-fa83-4527-aa25-a65a2b186716",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"36"
]
},
"execution_count": 132,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(MediaDatosExperimentales['y(m)'])"
]
},
{
"cell_type": "code",
"execution_count": 133,
"id": "5f8755d4-f119-4fab-88cf-9c5c272f2c89",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"36"
]
},
"execution_count": 133,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(MediaDatosExperimentales['t(s)'])"
]
},
{
"cell_type": "code",
"execution_count": 150,
"id": "d5fd7965-57f2-4c57-b09b-51e02be10aa7",
"metadata": {},
"outputs": [],
"source": [
"y = np.log(np.abs(MediaDatosExperimentales['y(m)'])[1:35])\n",
"x = np.log(MediaDatosExperimentales['t(s)'][1:35])"
]
},
{
"cell_type": "code",
"execution_count": 151,
"id": "0c046d23-3a02-4e2e-9ac2-5e6d8dc43e1a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Linealización servilleta extendida')"
]
},
"execution_count": 151,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.plot(x,y,'.')\n",
"plt.xlabel(r'$ln(t)$')\n",
"plt.ylabel(r'$ln(y)$')\n",
"plt.title(\"Linealización servilleta extendida\")"
]
},
{
"cell_type": "markdown",
"id": "87395d19-d253-499d-aa61-cd031b8a06ab",
"metadata": {},
"source": [
"Error en mediciones"
]
},
{
"cell_type": "code",
"execution_count": 153,
"id": "1d038188-3a7f-420a-9df4-abbff40e5e12",
"metadata": {},
"outputs": [],
"source": [
"y1 = MediaDatosExperimentales['y(m)']\n",
"y2 = MediaDatosExperimentales['y(m)']\n",
"y3 = MediaDatosExperimentales['y(m)']\n",
"y4 = MediaDatosExperimentales['y(m)']\n",
"y5 = MediaDatosExperimentales['y(m)']\n",
"y6 = MediaDatosExperimentales['y(m)']\n",
"y7 = MediaDatosExperimentales['y(m)']\n",
"y8 = MediaDatosExperimentales['y(m)']\n",
"y9 = MediaDatosExperimentales['y(m)']\n",
"y10 = MediaDatosExperimentales['y(m)']\n",
"\n",
"t1 = MediaDatosExperimentales['t(s)']\n",
"t2 = MediaDatosExperimentales['t(s)']\n",
"t3 = MediaDatosExperimentales['t(s)']\n",
"t4 = MediaDatosExperimentales['t(s)']\n",
"t5 = MediaDatosExperimentales['t(s)']\n",
"t6 = MediaDatosExperimentales['t(s)']\n",
"t7 = MediaDatosExperimentales['t(s)']\n",
"t8 = MediaDatosExperimentales['t(s)']\n",
"t9 = MediaDatosExperimentales['t(s)']\n",
"t10 = MediaDatosExperimentales['t(s)']"
]
},
{
"cell_type": "code",
"execution_count": 154,
"id": "25b7c09b-223c-4e9e-a54a-86c099c8698d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]\n",
" [0.99639723 0.98425983 0.97028413 0.95513588 0.94174415 0.92451841\n",
" 0.9034373 0.88218765 0.85926581 0.83459634 0.81063083 0.78118911\n",
" 0.75368926 0.72598968 0.69542749 0.66822803 0.64126229 0.61311155\n",
" 0.58245949 0.55710349 0.53450709 0.50754793 0.48250283 0.45487334\n",
" 0.42581158 0.39538796 0.36532346 0.33725109 0.31228829 0.2868737\n",
" 0.25755969 0.23644029 0.20875854 0.18134784 0.15224452 0.12588204]]\n"
]
}
],
"source": [
"Alturas=np.array([y1,y2,y3,y4,y5,y6,y7,y8,y9,y10])\n",
"print(Alturas)"
]
},
{
"cell_type": "code",
"execution_count": 155,
"id": "8819d9a8-a256-44b5-9c93-7e9e042ee18e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]\n",
" [0. 0.04998889 0.09996665 0.14994444 0.19991114 0.24988885\n",
" 0.29988888 0.34990002 0.39987776 0.44984443 0.49982224 0.5498\n",
" 0.59979998 0.64980001 0.69978893 0.74976664 0.79973334 0.84971115\n",
" 0.89967775 0.94967778 0.99968892 1.0496552 1.0996444 1.1496114\n",
" 1.1995885 1.2495555 1.2995669 1.3495676 1.3995377 1.4495302\n",
" 1.4995112 1.5494921 1.5994957 1.6494771 1.6994376 1.7510889 ]]\n"
]
}
],
"source": [
"tiempo=np.array([t1,t2,t3,t4,t5,t6,t7,t8,t9,t10])\n",
"print(tiempo)"
]
},
{
"cell_type": "code",
"execution_count": 169,
"id": "a0917e49-2755-4219-8656-264fbd14d70f",
"metadata": {},
"outputs": [],
"source": [
"tiempo_prom = tiempo.mean(axis=0)\n",
"tiempo_error = tiempo.std(axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 157,
"id": "d77f1668-e50e-4aac-81d9-af8137a322dc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"36"
]
},
"execution_count": 157,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(tiempo_prom)"
]
},
{
"cell_type": "code",
"execution_count": 170,
"id": "9683a1e4-12c1-4fee-8314-2c3ee1dc871c",
"metadata": {},
"outputs": [],
"source": [
"y_prom = Alturas.mean(axis=0)\n",
"y_error = Alturas.std(axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 159,
"id": "202fca04-ec9a-41b0-816a-7211d0c378d2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"36"
]
},
"execution_count": 159,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(y_prom)"
]
},
{
"cell_type": "markdown",
"id": "90827561-1c8a-4c93-ba83-301d851897c2",
"metadata": {},
"source": [
"Gráfica medición de error"
]
},
{
"cell_type": "code",
"execution_count": 171,
"id": "f6411ae6-624b-4a92-94ff-2393d468e28d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<function matplotlib.pyplot.show(close=None, block=None)>"
]
},
"execution_count": 171,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.errorbar(tiempo_prom, y_prom, y_error, tiempo_error,fmt=\"o\")\n",
"plt.title(\"Error servilleta extendida\")\n",
"plt.show"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "108073d1-ed5b-4f88-b4dd-0123b6f0163a",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "6ea3f71a-5d7b-4dc0-9293-f3252df47f45",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}