From 06fb4fbeb122c3ef700299a1f817c4d1980c847d Mon Sep 17 00:00:00 2001 From: Filip Gralinski Date: Tue, 8 Mar 2022 18:09:12 +0100 Subject: [PATCH] Aktualizacja notatnika --- wyk/02_Jezyki.ipynb | 899 ++++++--------------- wyk/02_Jezyki.org | 46 +- wyk/02_Jezyki/dna-aminos.png | Bin 15792 -> 7445 bytes wyk/02_Jezyki/dna-chars.png | Bin 12439 -> 5888 bytes wyk/02_Jezyki/dna_length.png | Bin 13466 -> 6065 bytes wyk/02_Jezyki/pt-2-word-ngrams-log-log.png | Bin 11811 -> 6764 bytes wyk/02_Jezyki/pt-3-char-ngrams-log-log.png | Bin 15450 -> 8771 bytes wyk/02_Jezyki/pt-chars.png | Bin 25256 -> 11868 bytes wyk/02_Jezyki/pt-lengths.png | Bin 42193 -> 21390 bytes wyk/02_Jezyki/pt-words-20.png | Bin 17264 -> 7941 bytes wyk/02_Jezyki/pt-words-log-log.png | Bin 14454 -> 8232 bytes wyk/02_Jezyki/pt-words-log.png | Bin 10602 -> 5716 bytes wyk/02_Jezyki/pt-words.png | Bin 12507 -> 6147 bytes wyk/02_Jezyki/voy-chars.png | Bin 19446 -> 9278 bytes wyk/02_Jezyki/voy-log-log.png | Bin 14043 -> 7937 bytes wyk/02_Jezyki/voy-words-20.png | Bin 17097 -> 8442 bytes wyk/02_Jezyki/voy-words-log-log.png | Bin 14043 -> 7937 bytes 17 files changed, 282 insertions(+), 663 deletions(-) diff --git a/wyk/02_Jezyki.ipynb b/wyk/02_Jezyki.ipynb index 68af0ec..a3d48f9 100644 --- a/wyk/02_Jezyki.ipynb +++ b/wyk/02_Jezyki.ipynb @@ -334,7 +334,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_6969/6903746.py:14: UserWarning: Glyph 13 (\r", + "/tmp/ipykernel_8747/6903746.py:14: UserWarning: Glyph 13 (\r", ") missing from current font.\n", " plt.savefig(fname)\n" ] @@ -477,17 +477,29 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ - "" + "'02_Jezyki/pt-words-20.png'" ] }, + "execution_count": 7, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", "text/plain": [ - "" + "'02_Jezyki/pt-words.png'" ] }, + "execution_count": 8, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -542,24 +566,36 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Widać, jak różne skale obejmuje ten wykres. Zastosujemy logartm,\n", - "najpierw tylko do współrzędnej y.\n", + "Widać, jak różne skale obejmuje ten wykres. Zastosujemy logarytm,\n", + "najpierw tylko do współrzędnej $y$.\n", "\n" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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A7QUIANSIAFhwgwFww+btOVcCAIwUAmDB9ffv/O/rWyp7vxAA4B0SAAuu3LpziHQAAYBaEQAL7tCBrV/Wdr+ZcyUAwEghABbc4F6AFoEAALUiABbc+w/ePyIilr/cnXMlAMBIIQAW3P7lnR3AjjGtOVcCAIwUAmDBdY0bExERv35tS86VAAAjhQBYcAfsNyoiIpqbSpFlWc7VAAAjgQBYcOMGAmBffxZbLAQBAGpAACy40a27hujX6zfnWAkAMFIIgAVXKpWipakUERErBUAAoAYEwAYwrm3nNHC/ewABgBoQABvAcYceGBER23a4BxAA2HcCYAMY3docERHdW3fkXAkAMBIIgA1gzEAA/K+X3si3EABgRBAAG0Bp5xqQeHbtpnwLAQBGBAGwAXxo0tiIcBwcAFAbAmADOGpye0REbNnem3MlAMBIIAA2gLZyS0RErNqwNedKAICRQABsABPaR1c/ftNxcADAPhIAG8CB++26929t95s5VgIAjAQCYAMoDS4DjohVvzUNDADsGwGwQRw0cBzca5sqOVcCADQ6AbBBzJjSERERS1/YkHMlAECjEwAbRLll51A5DxgA2FcCYIM4YdpBERHx/PrNOVcCADQ6AbBBtI/euRfgr14VAAGAfSMANogPTNi/+nFvX3+OlQAAjU4AbBDT39dR/fj1zdtzrAQAaHQCYINobd41VE+u3phjJQBAoxMAG8j7x7dFRMSTqwRAAOC9EwAbyMSxO88E3rDFFDAA8N4JgA3k1A8dHBERS371Ws6VAACNLNkAeO2118bRRx8dY8eOjbFjx8asWbPiJz/5Sd5l7dXB7eWIiMiyLOdKAIBGlmwAnDJlSlx55ZXx+OOPx+OPPx6nnXZafOYzn4kVK1bkXdoeHXvIgRERsXHrjthhKxgA4D1KNgCec8458alPfSoOP/zwOPzww+Nv//ZvY//994+lS5fmXdoejd9/VPXjB1eaBgYA3ptkA+Bb9fX1xaJFi2LLli0xa9asvMvZo/bRrdHaXIqIiFUbtuZcDQDQqJIOgMuXL4/9998/yuVyXHDBBXH77bfHUUcdtcfrK5VK9PT0DHkMt7OmT46IiFt+vnrYvzYAMDIkHQA/9KEPxVNPPRVLly6Nb33rWzFv3rx45pln9nj9woULo6Ojo/ro6uoaxmp36jpwTEREtJVbhv1rAwAjQymzpLTqjDPOiMMOOyz+5V/+5W0/X6lUolKpVJ/39PREV1dXdHd3x9ixY4elxoeffz3++P98NCIifn3Fp6K5qTQsXxcARoqenp7o6OgY1n+/i0Yb6S2yLBsS8H5XuVyOcrk8jBXt7vBJ7dWPV/92a0wbOB0EAOCdSjYA/tVf/VXMmTMnurq6YtOmTbFo0aK4//774+677867tL0av3852sstsanSG8+v3ywAAgDvWrIB8NVXX43zzz8/1q5dGx0dHXH00UfH3XffHWeeeWbepf1e7aN3BsDrH3whzjxqYt7lAAANJtkAeMMNN+Rdwnt25lET46ZHVjkRBAB4T5JeBdyoTj9yZ9fvsd9sjFd7tuVcDQDQaATABvTW+/7u++X6HCsBABqRANiAusbtF8ceckBERGyu9OZbDADQcATABnXEwHYwf/PjZ6O/372AAMA7JwA2qJM/ML768W+3bs+xEgCg0QiADWru0Z3RMnAKyBbTwADAuyAANrCxY1ojIuLs//mQaWAA4B0TABvY7IFNoDdXemPTNl1AAOCdEQAb2JWfP7o6Dfzmjr6cqwEAGoUA2ODGtDZHRMQ1963MuRIAoFEIgA2utWXnED76wm9zrgQAaBQCYIP756/MjIiISm9/zpUAAI1CAGxw+5dbIiJi9W+3xrLVG3OuBgBoBAJggztgv9bqxxfesizHSgCARiEANrjOA8bE/E8cFhERGzY7EQQA+P0EwBFg3qxDIyJiW29fZJkNoQGAvRMAR4DywFYwWRbxuWsfjpc2bs25IgCgyATAEWD/cktMaC9HRMSy1W/E//vs+pwrAgCKTAAcAZqbSnH3RR+Lzo7RERGxzakgAMBeCIAjxLi2UfHxD02ICHsCAgB7JwCOIOWBU0H+9eHfxBV3PZtzNQBAUQmAI8hhB7dFRMRvt2yP6x54IbbrBAIAb0MAHEG+cuLU+I9vnVR9Xul1LyAAsDsBcAQplUpxbNcB1efuBQQA3o4AOMI0NZViVPPOYb3p4d/EU2veyLcgAKBwBMARqH10S0RE/B/3Ph9fveFRp4MAAEMIgCPQFZ+bEecc0xkRET3bemNHnwAIAOwiAI5An/zwpPiHLxxdfb69z72AAMAuAuAINXgfYETYDgYAGEIAHKGamkrR0lSKiIjL71wRf/2/non1PdtyrgoAKIKWvAugfg7af1S82lOJO//rlYiI6BjTGt8+/YM5VwUA5E0HcAS7/qvHxf/2yQ/FH04bFxERmyu9OVcEABSBDuAIdvSUA+LoKQfEm9v74ucv/ta9gABAROgAJqF1YEGI1cAAQIQOYBJaW3YuBlnfsy2Wv9QdERHvP7gt2sqGHwBSlGwHcOHChXH88cdHe3t7TJgwIT772c/Gc889l3dZdTG4Jcw9z66Pc655KM655qH41P980AkhAJCoZAPgkiVLYv78+bF06dJYvHhx9Pb2xuzZs2PLli15l1ZznzhiQhw5eWxM7hgdE8eWIyJi1YatUXFPIAAkqZRpA0VExGuvvRYTJkyIJUuWxMc+9rF39J6enp7o6OiI7u7uGDt2bJ0rrI1tO/riiP92d0RELL98drSPbs25IgAYXo3473etuQlsQHf3znvjxo0bt8drKpVKVCqV6vOenp6611VrrW85IaTXGcEAkKRkp4DfKsuyuPjii+OjH/1oTJ8+fY/XLVy4MDo6OqqPrq6uYayyNpqbSjFwQEjs6DcFDAApEgAjYsGCBfGLX/wibrnllr1ed+mll0Z3d3f1sWbNmmGqsLZaBrqAG7fsiO43dz627ejLuSoAYLgkPwV84YUXxp133hkPPPBATJkyZa/XlsvlKJfLw1RZ/bQ2lWJ7RHzy6geqr41qaYobv3Z8nPyB8fkVBgAMi2Q7gFmWxYIFC+K2226Le++9N6ZNm5Z3ScPmjKMm7vba9t7+eGLVxhyqAQCGW7IdwPnz58ePfvSj+M///M9ob2+PdevWRURER0dHjBkzJufq6ut//9Kx8Q9fOKb6/Pv/a0X8cOnq6HVSCAAkIdkO4LXXXhvd3d1x6qmnxuTJk6uPW2+9Ne/ShsWolqZdj+bmiIjY0W9VMACkINkOoO0Pd2lt3rksuE8ABIAkJNsBZJfmgX1hdpgCBoAkCIBUt4XRAQSANCQ7BcwuLQMdwH9buipu+fnq3T4/rm1U/Ps3T4gPTGgf7tIAgDrQASSO6TogmptKkWURO/qy3R6v9lTi0Rd/m3eZAECN6AASHz/84Hjyv50Zb27f/TSQv7p9edz7y/XRb3oYAEYMAZCIiOgY0xodY1p3e72tvPNHpFcABIARwxQwezV4f6AFIgAwcgiA7NXgFjE6gAAwcgiA7JUOIACMPAIge1XtAPYJgAAwUlgEwl4NdgAXP7su1vVs2+N1XePGxAUfOyyaBq4HAIpLAGSvDthvVEREPP1yTzz9cs9er531/oPi2EMOHI6yAIB9IACyV984eVqMHdMaWyu9e7zmpkdWxeubK7Glsvs+ggBA8QiA7FXHfq3xJx+dttdrfvL0unh9cyX6MvcJAkAjsAiEfdZcXSncn3MlAMA7IQCyz3YFwJwLAQDeEQGQfdZsr0AAaCgCIPusubQzAPa7BxAAGoIAyD5rGvgp0gEEgMYgALLPBqeAdQABoDHYBoZ91jQwBfz4bzZGqfTuTgIpRcQJ08bFhLGj61AZAPB2BED2WbmlOSIi/m3pqvi3pave9ftnvK8j/p8LP1rrsgCAPRAA2WffPGVa7Ojrjx3vch+YLZXe+K+Xuvd6xjAAUHsCIPvsxPcfFCe+/6B3/b5fruuJs65+MDL3DgLAsLIIhNwMbh9j9TAADC8BkNyUqvsH5lwIACRGACQ31e1jJEAAGFYCILkZyH/2DwSAYSYAkpvB/QP7BEAAGFYCILlpanIPIADkQQAkN4NTwLaBAYDhJQCSG9vAAEA+BEByYxsYAMiHk0DIzeA2MBERqzdsjVJpLxfXyLi2UdFW9mMPQNr8S0hu3pL/4mP/cN+wfM22Uc1x71+cGhPHjh6WrwcARZT0FPADDzwQ55xzTnR2dkapVIo77rgj75KS0jGmNU47YkKMaW0elkdExJbtffHr9Ztz/s4BIF9JdwC3bNkSxxxzTHz961+Pz3/+83mXk5xSqRT/19eOH7av98n/8UA89+qmcMshAKlLOgDOmTMn5syZk3cZDJOSk0cAICISD4DvVqVSiUqlUn3e09OTYzW8W01WHQNARCR+D+C7tXDhwujo6Kg+urq68i6Jd6Fp4KddBxCA1AmA78Kll14a3d3d1ceaNWvyLol3oRSDR4/kWwcA5M0U8LtQLpejXC7nXQbvUZN7AAEgInQASYiTRwBgp6Q7gJs3b47nn3+++vzFF1+Mp556KsaNGxeHHHJIjpVRDzqAALBT0gHw8ccfj0984hPV5xdffHFERMybNy/+9V//NaeqqJfBDmAmAAKQuKQD4KmnnioMJGSwA2jIAUidewBJhnsAAWAnAZBkuAcQAHYSAEnG4D6AAiAAqRMASUaTn3YAiAgBkITsOgtYBxCAtAmAJKO6CKQ/50IAIGdJbwNDWgYXgfx0xbp4aeOb+RZTAPuNao4vzJwSB7aNyrsUAIaZAEgy2kbt/HH/2TOvxs+eeTXnaophU6U3Lj7z8LzLAGCYCYAk46IzPhgHt5djR5854KfWvBErXumJnjd35F0KADkQAEnGBye2x+Wf/nDeZRTCf//pc7HilR4n4QAkyiIQSFBp8Fi8fMsAICcCICRoIP85FxkgUQIgpGigBZjpAQIkSQCEBOkAAqRNAIQEuQcQIG0CICSoNNAD1AEESJMACAka7ADqAQKkSQCEBLkHECBtAiAkqHoPoAAIkCQBEBJUsg0MQNIEQEiYDiBAmgRASJBtYADSJgBCgmwDA5A2ARAS1FTtAEqAACkSACFB1X0A5T+AJAmAkKDqFHDOdQCQDwEQErRrH0ARECBFAiAkTPwDSJMACAmqbgQtAQIkSQCEBFkDApA2ARAS5B5AgLQJgJAgHUCAtAmAkKCSs+AAkiYAQoJKTgIBSJoACAmqTgHLfwBJSj4A/uAHP4hp06bF6NGjY+bMmfHggw/mXRLUn21gAJKWdAC89dZb46KLLorvfve7sWzZsjjllFNizpw5sXr16rxLg7ratQhEAgRIUdIB8Kqrroo/+ZM/iW9+85tx5JFHxtVXXx1dXV1x7bXX5l0a1NWubWDyrQOAfLTkXUBetm/fHk888UR85zvfGfL67Nmz4+GHH37b91QqlahUKtXnPT09da0R6qU00AP8xUvdcdGiZTlXA7BnZ02fFGdNn5x3GSNOsgHw9ddfj76+vpg4ceKQ1ydOnBjr1q172/csXLgwvve97w1HeVBX49paIyJiXc+2uOOpV3KuBmDPDh3fJgDWQbIBcFB1P7QBWZbt9tqgSy+9NC6++OLq856enujq6qprfVAPpx85Ma4+9yPx+ubK778YIEfHHnJg3iWMSMkGwPHjx0dzc/Nu3b7169fv1hUcVC6Xo1wuD0d5UFetzU3x2WPfl3cZAOQk2UUgo0aNipkzZ8bixYuHvL548eI46aSTcqoKAKD+ku0ARkRcfPHFcf7558dxxx0Xs2bNiuuuuy5Wr14dF1xwQd6lAQDUTdIB8Nxzz40NGzbE97///Vi7dm1Mnz497rrrrpg6dWrepQEA1E0py+wE9l719PRER0dHdHd3x9ixY/MuBwB4B/z7nfA9gAAAqRIAAQASIwACACRGAAQASIwACACQGAEQACAxAiAAQGIEQACAxAiAAACJSfoouH01eIhKT09PzpUAAO/U4L/bKR+GJgDug02bNkVERFdXV86VAADv1qZNm6KjoyPvMnLhLOB90N/fH6+88kq0t7dHqVSq6Z/d09MTXV1dsWbNmmTPKWwExqlxGKvGYawaQyOPU5ZlsWnTpujs7IympjTvhtMB3AdNTU0xZcqUun6NsWPHNtwvVoqMU+MwVo3DWDWGRh2nVDt/g9KMvQAACRMAAQASIwAWVLlcjssuuyzK5XLepbAXxqlxGKvGYawag3FqbBaBAAAkRgcQACAxAiAAQGIEQACAxAiAAACJEQAL6Ac/+EFMmzYtRo8eHTNnzowHH3ww75JGtMsvvzxKpdKQx6RJk6qfz7IsLr/88ujs7IwxY8bEqaeeGitWrBjyZ1Qqlbjwwgtj/Pjx0dbWFp/+9KfjpZdeGnLNxo0b4/zzz4+Ojo7o6OiI888/P954443h+BYb0gMPPBDnnHNOdHZ2RqlUijvuuGPI54dzXFavXh3nnHNOtLW1xfjx4+Pb3/52bN++vR7fdkP6fWP1ta99bbffsRNPPHHINcaq/hYuXBjHH398tLe3x4QJE+Kzn/1sPPfcc0Ou8XuVDgGwYG699da46KKL4rvf/W4sW7YsTjnllJgzZ06sXr0679JGtA9/+MOxdu3a6mP58uXVz/393/99XHXVVXHNNdfEY489FpMmTYozzzyzehZ0RMRFF10Ut99+eyxatCgeeuih2Lx5c8ydOzf6+vqq1/zxH/9xPPXUU3H33XfH3XffHU899VScf/75w/p9NpItW7bEMcccE9dcc83bfn64xqWvry/OPvvs2LJlSzz00EOxaNGi+I//+I+45JJL6vfNN5jfN1YREWedddaQ37G77rpryOeNVf0tWbIk5s+fH0uXLo3FixdHb29vzJ49O7Zs2VK9xu9VQjIK5Q//8A+zCy64YMhrRxxxRPad73wnp4pGvssuuyw75phj3vZz/f392aRJk7Irr7yy+tq2bduyjo6O7J//+Z+zLMuyN954I2ttbc0WLVpUvebll1/OmpqasrvvvjvLsix75plnsojIli5dWr3mkUceySIi++Uvf1mH72pkiYjs9ttvrz4fznG56667sqampuzll1+uXnPLLbdk5XI56+7ursv328h+d6yyLMvmzZuXfeYzn9nje4xVPtavX59FRLZkyZIsy/xepUYHsEC2b98eTzzxRMyePXvI67Nnz46HH344p6rSsHLlyujs7Ixp06bFl770pXjhhRciIuLFF1+MdevWDRmTcrkcH//4x6tj8sQTT8SOHTuGXNPZ2RnTp0+vXvPII49ER0dHnHDCCdVrTjzxxOjo6DC278FwjssjjzwS06dPj87Ozuo1n/zkJ6NSqcQTTzxR1+9zJLn//vtjwoQJcfjhh8ef/umfxvr166ufM1b56O7ujoiIcePGRYTfq9QIgAXy+uuvR19fX0ycOHHI6xMnTox169blVNXId8IJJ8TNN98cP/3pT+P666+PdevWxUknnRQbNmyo/r3vbUzWrVsXo0aNigMPPHCv10yYMGG3rz1hwgRj+x4M57isW7dut69z4IEHxqhRo4zdOzRnzpz493//97j33nvjH//xH+Oxxx6L0047LSqVSkQYqzxkWRYXX3xxfPSjH43p06dHhN+r1LTkXQC7K5VKQ55nWbbba9TOnDlzqh/PmDEjZs2aFYcddljcdNNN1RvV38uY/O41b3e9sd03wzUuxm7fnHvuudWPp0+fHscdd1xMnTo1fvzjH8fnPve5Pb7PWNXPggUL4he/+EU89NBDu33O71UadAALZPz48dHc3Lzb//2sX79+t/9Ton7a2tpixowZsXLlyupq4L2NyaRJk2L79u2xcePGvV7z6quv7va1XnvtNWP7HgznuEyaNGm3r7Nx48bYsWOHsXuPJk+eHFOnTo2VK1dGhLEabhdeeGHceeedcd9998WUKVOqr/u9SosAWCCjRo2KmTNnxuLFi4e8vnjx4jjppJNyqio9lUolnn322Zg8eXJMmzYtJk2aNGRMtm/fHkuWLKmOycyZM6O1tXXINWvXro2nn366es2sWbOiu7s7fv7zn1evefTRR6O7u9vYvgfDOS6zZs2Kp59+OtauXVu95mc/+1mUy+WYOXNmXb/PkWrDhg2xZs2amDx5ckQYq+GSZVksWLAgbrvttrj33ntj2rRpQz7v9yoxw77shL1atGhR1tramt1www3ZM888k1100UVZW1tb9pvf/Cbv0kasSy65JLv//vuzF154IVu6dGk2d+7crL29vfp3fuWVV2YdHR3Zbbfdli1fvjz78pe/nE2ePDnr6emp/hkXXHBBNmXKlOyee+7Jnnzyyey0007LjjnmmKy3t7d6zVlnnZUdffTR2SOPPJI98sgj2YwZM7K5c+cO+/fbKDZt2pQtW7YsW7ZsWRYR2VVXXZUtW7YsW7VqVZZlwzcuvb292fTp07PTTz89e/LJJ7N77rknmzJlSrZgwYLh+8souL2N1aZNm7JLLrkke/jhh7MXX3wxu++++7JZs2Zl73vf+4zVMPvWt76VdXR0ZPfff3+2du3a6mPr1q3Va/xepUMALKB/+qd/yqZOnZqNGjUq+4M/+IPqEn3q49xzz80mT56ctba2Zp2dndnnPve5bMWKFdXP9/f3Z5dddlk2adKkrFwuZx/72Mey5cuXD/kz3nzzzWzBggXZuHHjsjFjxmRz587NVq9ePeSaDRs2ZOedd17W3t6etbe3Z+edd162cePG4fgWG9J9992XRcRuj3nz5mVZNrzjsmrVquzss8/OxowZk40bNy5bsGBBtm3btnp++w1lb2O1devWbPbs2dnBBx+ctba2Zoccckg2b9683cbBWNXf241RRGQ33nhj9Rq/V+koZVmWDXfXEQCA/LgHEAAgMQIgAEBiBEAAgMQIgAAAiREAAQASIwACACRGAAQASIwACACQGAEQACAxAiAAQGIEQACAxAiAAACJEQABABIjAAIAJEYABABIjAAIAJAYARAAIDECIABAYgRAAIDECIAAAIkRAAEAEiMAAgAkRgAEAEiMAAgAkBgBEAAgMQIgAEBiBEAAgMQIgAAAiREAAQASIwACACRGAAQASMz/DxrYP4SYQx7KAAAAAElFTkSuQmCC", "text/plain": [ - "" + "'02_Jezyki/pt-words-log.png'" ] }, + "execution_count": 9, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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", "text/plain": [ - "" + "'02_Jezyki/pt-words-log-log.png'" ] }, + "execution_count": 10, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", "text/plain": [ - "" + "'02_Jezyki/pt-lengths.png'" ] }, + "execution_count": 11, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -769,21 +829,24 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Statystyki, które policzyliśmy dla pojedynczych liter czy wyrazów możemy powtórzyć dla n-gramów.\n", + "Statystyki, które policzyliśmy dla pojedynczych liter czy wyrazów, możemy powtórzyć dla n-gramów.\n", "\n" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 12, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "[('k', 'o', 't'), ('o', 't', 'e'), ('t', 'e', 'k')]" - ] + "data": { + "text/plain": [ + "[('k', 'o', 't'), ('o', 't', 'e'), ('t', 'e', 'k')]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -818,17 +881,29 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ - "" + "'02_Jezyki/pt-3-char-ngrams-log-log.png'" ] }, + "execution_count": 13, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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fbrD6CgCfVMkE4PPPPx8XX3xx//d9n9W76qqr4oEHHoidO3fG1q1b+/+8u7s7brzxxti+fXuMGjUqpk2bFt/97ndjwYIFBZ+dY3P2xEMB+OKbHXHFuUlPAwDFK5fP5/NJD1GsOjs7o6amJjo6OnwesAC++9LOuOahF+KsU2vi8S9fkPQ4ABQp798+A0gR6bsn8KvtndHVczDhaQCgeAlAisbEk0fFyaNHxIGD+Xh1596kxwGAoiUAKRq5XC7O6jsPcLsDoQHgkxKAFJUZfXcE2fZOsoMAQBETgBSVs049FIAvWwEEgE9MAFJUZjSeFBERr/1ib7zb3ZPsMABQpAQgRaV2TFVMqK6M3nzET3d0Jj0OABQlAUjROfv9jSAvvukyMAB8EgKQotN3HuDLb76T7CAAUKQEIEWnLwBfsgIIAJ9IydwLmOzouwT8xp79cf2/tkUu2XGG3blNY+NPP3Na0mMAUEIEIEVn7AkjY/IpJ8Qbu/fHdzbsSHqcYfedF3fE751zapxY6V9XAIaGdxSK0sovzI61r+2OfD6f9CjD6vbVG6M3H7G/q0cAAjBkvKNQlD414cT41IQTkx5j2N255rV4t/tgvHfgYNKjAFBCbAKBFKsaUR4REV09vQlPAkApEYCQYlUVh/4VtQIIwFASgJBifSuA7x2wAgjA0BGAkGIjrQACMAwEIKSYzwACMBwEIKRY1QgrgAAMPQEIKXb4M4ACEIChIwAhxSr7PgPoEjAAQ0gAQor1fwbQCiAAQ0gAQopVVdgEAsDQE4CQYjaBADAcBCCkWKVNIAAMAwEIKXb4VnAuAQMwdAQgpFhl/0HQVgABGDoCEFLMvYABGA4CEFKs0r2AARgGAhBSrH8F0DEwAAwhAQgp5hgYAIaDAIQUcxA0AMNBAEKKVb6/AuhWcAAMJQEIKVblIGgAhoEAhBTruwTsGBgAhpIAhBTr2wTiIGgAhpIAhBSrtAIIwDAQgJBi/cfA9ByMfD6f8DQAlAoBCCnWdy/gfD6i+6BVQACGhgCEFOtbAYxwGRiAoSMAIcVGlpdFLnfof9sIAsBQEYCQYrlcLior+g6DtgIIwNAQgJByDoMGYKgJQEg5h0EDMNQEIKRcpcOgARhiAhBSzgogAENNAELK9R8G7TOAAAwRAQgp13cY9HsuAQMwRAQgpJxjYAAYagIQUq7KCiAAQ0wAQsodPgfQCiAAQ0MAQspVVdgEAsDQEoCQcv3nAApAAIaIAISU6zsHsKvHJWAAhoYAhJRzL2AAhlpF0gMAR9d3EPTufV3x+q59CU8zvBrHjorK91c8ARg+AhBSrm8FcPXL7bH65faEpxleZ9ZVx78tnpf0GAAlTwBCyl34X06J//UfW+Ptd7uTHmXY9Pbmo/O9nni1fW/k8/nI5XJJjwRQ0gQgpNwZtdXx5I0XJT3GsPrl/u6Y9TdrIiIin4/QfwDDyyYQIHFlHwi+3nw+uUEAMkIAAonLxeEClH8Aw08AAonLfeC/RFYAAYafAAQS98GP/Ok/gOEnAIHEfXDXrwAEGH4CEEjcBzeB5H0KEGDYCUAgcQM2geg/gGEnAIHE5RwDA1BQAhBIXG7AJWAAhlvJBOC6devisssui4aGhsjlcvHoo49+5GvWrl0bzc3NUVVVFZMnT44VK1YM/6DAEco+uAmkN8FBADKiZAJw//79MWPGjLj77ruP6fmbN2+OBQsWxNy5c6OtrS1uueWWuO6662LVqlXDPCnw6wYcA2MNEGDYlcy9gOfPnx/z588/5uevWLEiJk2aFMuWLYuIiKlTp8bzzz8fd9xxRyxcuHCYpgQG88EVwF79BzDsSmYF8ON69tlno6WlZcBjl156aTz//PNx4MCBhKaCbBrwGUCbQACGXcmsAH5c7e3tUVtbO+Cx2tra6OnpiT179kR9ff0Rr+nq6oqurq7+7zs7O4d9TsiCnBVAgILK7ApgxMA3nYjDKw+//nifpUuXRk1NTf9XY2PjsM8IWdH3r53PAAIMv8wGYF1dXbS3tw94bNeuXVFRURHjxo0b9DVLliyJjo6O/q9t27YVYlTIhL7PAboCDDD8MnsJeM6cOfH4448PeOyJJ56I2bNnx4gRIwZ9TWVlZVRWVhZiPMicvnV3AQgw/EpmBXDfvn2xYcOG2LBhQ0QcOuZlw4YNsXXr1og4tHp35ZVX9j9/0aJFsWXLlmhtbY2NGzfG/fffH/fdd1/ceOONSYwPmde3AuhOIADDr2RWAJ9//vm4+OKL+79vbW2NiIirrroqHnjggdi5c2d/DEZENDU1xerVq+OGG26Ie+65JxoaGuKuu+5yBAwkpf8zgAAMt5IJwIsuuuiox0c88MADRzx24YUXxgsvvDCMUwHHquz9AOy1DRhg2JXMJWCguOVi8N33AAw9AQikQt8xMD4DCDD8BCCQCo6BASgcAQikQt8FYCuAAMNPAAKpkLMLGKBgBCCQCjmXgAEKRgACqdB3DMzRjnMCYGgIQCAV+lcAE54DIAsEIJAKZY6BASgYAQikhM8AAhSKAARSwQogQOEIQCAV+o+B0X8Aw04AAqngTiAAhSMAgVTouxNI3j5ggGEnAIFU6DsGplf/AQw7AQikQs5B0AAFIwCBVCizAghQMAIQSIW+FUD3AgEYfgIQSAUrgACFIwCBVOjfBSwAAYadAATSwZ1AAApGAAKp4CBogMIRgEAqHL4ErAABhpsABFKhfwUw4TkAskAAAqlw+CDoZOcAyAIBCKTC4VvBKUCA4SYAgVTo/wxgolMAZIMABFKh7P3/GlkBBBh+AhBIhVzfGqD+Axh2AhBIhTIHQQMUjAAE0sFB0AAFIwCBVLACCFA4AhBIBbuAAQpHAAKpcPhewBIQYLgJQCAV3AkEoHAEIJAKh+8EkvAgABkgAIFUOPwZQAUIMNwEIJAKZVYAAQpGAAKpcPgzgAoQYLgJQCAVbAIBKBwBCKRC/zEwPgMIMOwEIJAqVgABhl9F0gMARBxeAXzwR1ti3Wu7E54mGWNPqIzFnzsjxlSNSHoUoMQJQCAVxp4wMiIiXtj6Tryw9Z1kh0nQtIYxsbB5YtJjACVOAAKpsGTBmTFz0knR3dOb9CiJ+N/PvxmbfrE3ujL68wOFJQCBVJhQXRVXzjk96TES8+PNv4xNv9ib9BhARtgEApAidkEDhSAAAQAyRgACpEDfQdgAhSAAAVLEOYhAIQhAAICMEYAAKZCLvlvhAQw/AQgAkDECECAFbAIBCkkAAqSJXSBAAQhAAICMEYAAKeASMFBIAhAgRVwABgpBAAIAZIwABEiBvnMAAQpBAAKkiE3AQCEIQACAjBGAAGngCjBQQAIQIEXyrgEDBSAAAQAyRgACpIArwEAhCUCAFHEBGCgEAQgAkDECECAFcm4GDBSQAARIEZuAgUIoqQC89957o6mpKaqqqqK5uTmefvrpD33uU089Fblc7oivV199tYATAwAUXskE4MMPPxyLFy+OW2+9Ndra2mLu3Lkxf/782Lp161Fft2nTpti5c2f/1xlnnFGgiQEO67sAbAEQKISSCcA777wzvvSlL8XVV18dU6dOjWXLlkVjY2MsX778qK+bMGFC1NXV9X+Vl5cXaGIAgGSURAB2d3fH+vXro6WlZcDjLS0t8cwzzxz1tTNnzoz6+vq45JJL4sknnxzOMQE+lD0gQCFVJD3AUNizZ08cPHgwamtrBzxeW1sb7e3tg76mvr4+Vq5cGc3NzdHV1RXf+ta34pJLLomnnnoq5s2bN+hrurq6oqurq//7zs7OofshAMKt4IDCKIkA7PPrxyjk8/kPPVphypQpMWXKlP7v58yZE9u2bYs77rjjQwNw6dKl8dWvfnXoBgYASEBJXAIeP358lJeXH7Hat2vXriNWBY/mvPPOi5/97Gcf+udLliyJjo6O/q9t27Z94pkBPsgVYKCQSiIAR44cGc3NzbFmzZoBj69ZsybOP//8Y/7rtLW1RX19/Yf+eWVlZYwZM2bAFwBAsSmZS8Ctra3xhS98IWbPnh1z5syJlStXxtatW2PRokURcWj1bvv27fHNb34zIiKWLVsWp59+ekybNi26u7vjwQcfjFWrVsWqVauS/DEAAIZdyQTgFVdcEW+99VbcdtttsXPnzpg+fXqsXr06TjvttIiI2Llz54AzAbu7u+PGG2+M7du3x6hRo2LatGnx3e9+NxYsWJDUjwBkmFvBAYWUy9ty9ol1dnZGTU1NdHR0uBwMHJcbHt4Q327bHrcumBr/fd7kpMeBkub9u0Q+AwgAwLETgAAp4AIwUEgCECBF8u4GDBSAAAQAyBgBCJAGrgEDBSQAAVLEuQxAIQhAAICMEYAAKZB7/xqwBUCgEAQgAEDGCECAFHAnOKCQBCBAitgEAhSCAAQAyBgBCJACrgADhSQAAVLEreCAQhCAAAAZIwABUsAuYKCQBCBAitgFDBSCAAQAyBgBCJACOfuAgQISgAAAGSMAAQAyRgACpIBdwEAhCUCAFMnbBgwUgAAEAMgYAQiQAn2XgC0AAoUgAAEAMkYAAgBkjAAESIVD14BdAQYKQQACAGSMAARIAecAAoUkAAFSxC5goBAEIABAxghAgBRwBRgoJAEIkCJ5+4CBAhCAAAAZIwABUsAuYKCQBCBAitgFDBSCAAQAyBgBCJACOfuAgQISgAAp4gowUAgCEAAgYwQgQArYBQwUkgAESBPbgIECEIAAABkjAAFSoO8KsPU/oBAEIABAxghAgBTI2QUCFJAABEgRe0CAQhCAAAAZIwABADJGAAKkSN4+YKAABCAAQMYIQIAUsAkYKCQBCJAidgEDhSAAAQAyRgACpEAuXAMGCkcAAqSIK8BAIQhAAICMEYAAKWAXMFBIAhAgRewCBgpBAAIAZIwABEiBvivAbgUHFIIABADIGAEIAJAxAhAgBXKHrwEDDDsBCACQMQIQIAVyDgIECkgAAqSIK8BAIQhAAICMEYAAKeACMFBIJRWA9957bzQ1NUVVVVU0NzfH008/fdTnr127Npqbm6OqqiomT54cK1asKNCkAIPLuxccUAAlE4APP/xwLF68OG699dZoa2uLuXPnxvz582Pr1q2DPn/z5s2xYMGCmDt3brS1tcUtt9wS1113XaxatarAkwMAFFbJBOCdd94ZX/rSl+Lqq6+OqVOnxrJly6KxsTGWL18+6PNXrFgRkyZNimXLlsXUqVPj6quvji9+8Ytxxx13FHhygHANGCioiqQHGArd3d2xfv36uPnmmwc83tLSEs8888ygr3n22WejpaVlwGOXXnpp3HfffXHgwIEYMWLEEa/p6uqKrq6u/u87OzuHYHqAw37w6q7Yvbfro58IGfFb0+vit6bXJz1GySmJANyzZ08cPHgwamtrBzxeW1sb7e3tg76mvb190Of39PTEnj17or7+yH/Yli5dGl/96leHbnCA9508emRERPx89/74+e79CU8D6XH6+BME4DAoiQDs8+sHqebz+aMerjrY8wd7vM+SJUuitbW1//vOzs5obGz8pOMC9PvCeafFyaNHxN73epIeBVJl5qSTkx6hJJVEAI4fPz7Ky8uPWO3btWvXEat8ferq6gZ9fkVFRYwbN27Q11RWVkZlZeXQDA3wASdUVsQV505KegwgI0piE8jIkSOjubk51qxZM+DxNWvWxPnnnz/oa+bMmXPE85944omYPXv2oJ//AwAoFSURgBERra2t8U//9E9x//33x8aNG+OGG26IrVu3xqJFiyLi0OXbK6+8sv/5ixYtii1btkRra2ts3Lgx7r///rjvvvvixhtvTOpHAAAoiJK4BBwRccUVV8Rbb70Vt912W+zcuTOmT58eq1evjtNOOy0iInbu3DngTMCmpqZYvXp13HDDDXHPPfdEQ0ND3HXXXbFw4cKkfgQAgILI5R07/4l1dnZGTU1NdHR0xJgxY5IeBwA4Bt6/S+gSMAAAx0YAAgBkjAAEAMgYAQgAkDECEAAgYwQgAEDGCEAAgIwRgAAAGSMAAQAypmRuBZeEvpuodHZ2JjwJAHCs+t63s3wzNAF4HPbu3RsREY2NjQlPAgB8XHv37o2ampqkx0iEewEfh97e3tixY0dUV1dHLpcb0r92Z2dnNDY2xrZt2zJ7n8Lj5Xd4/PwOj5/f4fHzOzx+focD5fP52Lt3bzQ0NERZWTY/DWcF8DiUlZXFxIkTh/XvMWbMGP+yHie/w+Pnd3j8/A6Pn9/h8fM7PCyrK399spm9AAAZJgABADJGAKZUZWVlfOUrX4nKysqkRylafofHz+/w+PkdHj+/w+Pnd8ivswkEACBjrAACAGSMAAQAyBgBCACQMQIQACBjBGAK3XvvvdHU1BRVVVXR3NwcTz/9dNIjFY2lS5fGueeeG9XV1TFhwoS4/PLLY9OmTUmPVdSWLl0auVwuFi9enPQoRWX79u3xZ3/2ZzFu3LgYPXp0nHPOObF+/fqkxyoaPT098Vd/9VfR1NQUo0aNismTJ8dtt90Wvb29SY+WauvWrYvLLrssGhoaIpfLxaOPPjrgz/P5fPz1X/91NDQ0xKhRo+Kiiy6KV155JZlhSZQATJmHH344Fi9eHLfeemu0tbXF3LlzY/78+bF169akRysKa9eujWuuuSZ+9KMfxZo1a6KnpydaWlpi//79SY9WlJ577rlYuXJlnH322UmPUlTefvvt+OxnPxsjRoyI733ve/HTn/40/v7v/z5OOumkpEcrGl//+tdjxYoVcffdd8fGjRvjG9/4Rvzd3/1d/MM//EPSo6Xa/v37Y8aMGXH33XcP+uff+MY34s4774y77747nnvuuairq4vPfe5z/fe2JzscA5Myn/nMZ2LWrFmxfPny/semTp0al19+eSxdujTByYrT7t27Y8KECbF27dqYN29e0uMUlX379sWsWbPi3nvvjb/927+Nc845J5YtW5b0WEXh5ptvjn//93+3en8cfud3fidqa2vjvvvu639s4cKFMXr06PjWt76V4GTFI5fLxbe//e24/PLLI+LQ6l9DQ0MsXrw4brrppoiI6Orqitra2vj6178ef/EXf5HgtBSaFcAU6e7ujvXr10dLS8uAx1taWuKZZ55JaKri1tHRERERY8eOTXiS4nPNNdfEb//2b8dv/uZvJj1K0Xnsscdi9uzZ8Qd/8AcxYcKEmDlzZvzjP/5j0mMVlQsuuCC+//3vx2uvvRYRES+++GL88Ic/jAULFiQ8WfHavHlztLe3D3iPqaysjAsvvNB7TAZVJD0Ah+3ZsycOHjwYtbW1Ax6vra2N9vb2hKYqXvl8PlpbW+OCCy6I6dOnJz1OUfnXf/3XeOGFF+K5555LepSi9MYbb8Ty5cujtbU1brnllvjxj38c1113XVRWVsaVV16Z9HhF4aabboqOjo4488wzo7y8PA4ePBhf+9rX4o//+I+THq1o9b2PDPYes2XLliRGIkECMIVyudyA7/P5/BGP8dGuvfbaeOmll+KHP/xh0qMUlW3btsX1118fTzzxRFRVVSU9TlHq7e2N2bNnx+233x4RETNnzoxXXnklli9fLgCP0cMPPxwPPvhgPPTQQzFt2rTYsGFDLF68OBoaGuKqq65Keryi5j2GCAGYKuPHj4/y8vIjVvt27dp1xP9j4+i+/OUvx2OPPRbr1q2LiRMnJj1OUVm/fn3s2rUrmpub+x87ePBgrFu3Lu6+++7o6uqK8vLyBCdMv/r6+vj0pz894LGpU6fGqlWrEpqo+PzlX/5l3HzzzfFHf/RHERFx1llnxZYtW2Lp0qUC8BOqq6uLiEMrgfX19f2Pe4/JJp8BTJGRI0dGc3NzrFmzZsDja9asifPPPz+hqYpLPp+Pa6+9Nh555JH4wQ9+EE1NTUmPVHQuueSSePnll2PDhg39X7Nnz44//dM/jQ0bNoi/Y/DZz372iOOHXnvttTjttNMSmqj4vPvuu1FWNvAtqry83DEwx6GpqSnq6uoGvMd0d3fH2rVrvcdkkBXAlGltbY0vfOELMXv27JgzZ06sXLkytm7dGosWLUp6tKJwzTXXxEMPPRTf+c53orq6un81taamJkaNGpXwdMWhurr6iM9MnnDCCTFu3DifpTxGN9xwQ5x//vlx++23xx/+4R/Gj3/841i5cmWsXLky6dGKxmWXXRZf+9rXYtKkSTFt2rRoa2uLO++8M774xS8mPVqq7du3L15//fX+7zdv3hwbNmyIsWPHxqRJk2Lx4sVx++23xxlnnBFnnHFG3H777TF69Oj4kz/5kwSnJhF5Uueee+7Jn3baafmRI0fmZ82alV+7dm3SIxWNiBj065//+Z+THq2oXXjhhfnrr78+6TGKyuOPP56fPn16vrKyMn/mmWfmV65cmfRIRaWzszN//fXX5ydNmpSvqqrKT548OX/rrbfmu7q6kh4t1Z588slB/xt41VVX5fP5fL63tzf/la98JV9XV5evrKzMz5s3L//yyy8nOzSJcA4gAEDG+AwgAEDGCEAAgIwRgAAAGSMAAQAyRgACAGSMAAQAyBgBCACQMQIQACBjBCAAQMYIQACAjBGAAAAZIwABADJGAAIAZIwABADIGAEIAJAxAhAAIGMEIABAxghAAICMEYAAABkjAAEAMkYAAgBkjAAEAMgYAQgAkDECEAAgYwQgAEDGCEAAgIwRgAAAGSMAAQAyRgACAGSMAAQAyBgBCACQMf8fMMN88nxOnPwAAAAASUVORK5CYII=", "text/plain": [ - "" + "'02_Jezyki/pt-2-word-ngrams-log-log.png'" ] }, + "execution_count": 14, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "log_rang_log_freq('pt-2-word-ngrams-log-log', ngrams(get_words(pan_tadeusz), 3))" + "log_rang_log_freq('pt-2-word-ngrams-log-log', ngrams(get_words(pan_tadeusz), 2))" ] }, { @@ -880,7 +967,7 @@ "tajemniczym alfabecie, do dzisiaj nieodszyfrowanym. Rękopis stanowi\n", "jedną z największych zagadek historii (i lingwistyki).\n", "\n", - "![Źródło](./02_Jezyki/voynich135.jpg)\n", + "![Źródło: Wikipedia Commons](./02_Jezyki/voynich135.jpg)\n", "\n", "Sami zbadajmy statystyczne własności tekstu manuskryptu. Użyjmy\n", "transkrypcji Vnow, gdzie poszczególne znaki tajemniczego alfabetu\n", @@ -893,15 +980,18 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 15, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "9 OR 9FAM ZO8 QOAR9 Q*R 8ARAM 29 [O82*]OM OPCC9 OP" - ] + "data": { + "text/plain": [ + "'9 OR 9FAM ZO8 QOAR9 Q*R 8ARAM 29 [O82*]OM OPCC9 OP'" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -923,17 +1013,45 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 16, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_8747/6903746.py:14: UserWarning: Glyph 9 (\t) missing from current font.\n", + " plt.savefig(fname)\n" + ] + }, { "data": { - "image/png": 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"text/plain": [ - "" + "'02_Jezyki/voy-chars.png'" ] }, + "execution_count": 16, "metadata": {}, + "output_type": "execute_result" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/lib/python3.10/site-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 9 (\t) missing from current font.\n", + " fig.canvas.print_figure(bytes_io, **kw)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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", "text/plain": [ - "" + "'02_Jezyki/voy-log-log.png'" ] }, + "execution_count": 17, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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"text/plain": [ - "" + "'02_Jezyki/voy-words-20.png'" ] }, + "execution_count": 18, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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jI/XKT4eqc0yEvtrt1aRX81RVU2s6FgAgBNi2AEpS3759VVhY2PBau3at6UhAs2QmxejFiecqOsKphVuK9cs3Vp90o2oAAI6ydQEMCwtTampqw6tLly6mIwHN1j89Xs/dkK0wh6U5q/do2rytpiMBAIKcrQvg5s2blZaWpszMTF133XXatm3bKd/v8/nk9XobvYBgcGHPLnrw+/0kSX/+aKMWbi42nAgAEMxsWwCHDh2qV155RR999JFmzJihvXv3avjw4Tpw4MBJP5Obmyu3293w8ng87ZgYOLUJ53l0TXa6agPSna+v1O7DR0xHAgAEKTaCrldeXq6zzjpL9957r3Jyck74Hp/PJ5/vm+02vF6vPB6PrTeSRHCprPbr6mmL9PUerwaku/X3W89XJ1eY6VgAEFTYCFriylAvJiZG55xzjjZv3nzS97hcLrlcrnZMBTRPZLhTz92QrcufXqjVu0p07kMf63t9U/T9gWcoLT5KkhQR5tCZnaNlWZbhtAAAUyiA9Xw+n9avX68LLrjAdBSgRTyJ0Zp+Y7bue3uttheX651Ve/TOqj2N3nNxnxQ9PWGQIsOdhlICAEyy7S3gX/7yl7riiiuUkZGhoqIiPfTQQ5o3b57Wrl2rbt26NelnMISMYBYIBLR6V4neWblbH6/fp8pqvyTpcEW1amoDuqBHkmbcNIQSCMB2uH7beARw165dmjBhgoqLi9WlSxedf/75Wrx4cZPLHxDsLMvSQE+8Bnri9fsr+zYcX7SlWLe8vFwLNhdr4ovLNGnUWeqeFKOUuEhZlmRJCnPadn0YANiCbUcAWwN/g0CoWrr9oCa+uFTlVf4Tfr9/ultXDkjTZf27qqs7qp3TAUDb4vpNAWwRTiCEsrW7SjRt3hZt3lemnQcqVOU//jFyliWde2aivj8wTVcPTud2MYAOges3BbBFOIHQUfhrAyrz1UiSKqpq9PG6fZqzeo+W7TjU8J4z4qN037jeurx/V1YQAwhpXL8pgC3CCYSObvfhI3pv9R69vGiH9pRUSpKmjOmhKWN6Gk4GAKeP67eNnwQC4NudER+l275zlj7571G67cLukqRZywrE3xsBILRRAAF8q6gIp+6+uKciwx0qLKnUhr2lpiMBAFqAAgigSSLDnRpxVpIk6bONRYbTAABaggIIoMlG9U6WJH22gQIIAKGMAgigyS7q1UWSlLfzkEoqqg2nAQCcLgoggCZLT4hWz5ROqg1I8zfvNx0HAHCaKIAAmuWiXnW3gWcs2Ka3V+xiJBAAQhAFEECzjO2bKklas6tEOf9crR//72K2hQGAEEMBBNAs2d0SNPPWobrtwu5yhTn09R6v1uwqMR0LANAMFEAAzTb8rCRNvTRLl/SrGw18I6/AcCIAQHNQAAGctmuyPZKkOav2qLLabzgNAKCpKIAATtvwszorzR0pb2WN/r1un+k4AIAmogACOG0Oh6Wrs9MlSdPnb1XJEVYEA0AooAACaJHrzstQJ1eYvtrt1TXPLdL6Qi+rggEgyFEAAbTIGfFRmnXb+UqOdWnTvjKN+8sCjX58nvJ2HjIdDQBwEhRAAC3WN82t2ZNHaExWiiKcDm0rLteUWStZGAIAQYoCCKBVnBEfpf+9eYiWPTBGXd2RKjh4RM9+vtV0LADACVAAAbQqd3S4fnN5H0nSc/O26ulPNmvXoQrDqQAAx7ICzNY+bV6vV263WyUlJYqLizMdBwgagUBAP3t5uT7ZUNRwbFj3zro6O13j+qUqxhVmMB0Au+P6TQFsEU4g4OR8NX7NWbVHb63YpcXbDjYcj45w6soBaRqckaDkOJe+07OLLMsymBSA3XD9pgC2CCcQ0DQFByv0zsrdemvFLu040Ph28H9d2F33X5plKBkAO+L6TQFsEU4goHkCgYCWbD+ot/J2aa+3Ugs2F0uSnr8xW9/rm2o4HQC74PpNAWwRTiCgZR56b53+d+F2ucIcmnbDYH23d4rpSABsgOs3q4ABGPSrcb01JitZvppa3fpKnu55Y7XyD7BiGADaGgUQgDHhToem3ZCta4eky18b0Bt5u/Tdxz/XfW+tUcFBiiAAtBVuAbcAQ8hA61mRf0hPfbxZ8zftlySFOy1dP7SbBmXES5K6dY7RQE+8uYAAOgyu3xTAFuEEAlpf3s6DenLuZi3cUtzouGVJs38xghIIoMW4flMAW4QTCGg7CzcX65Uvd6i8qkaFhyu1rbhc552ZqFm3nc++gQBahOs3BbBFOIGA9lFYckSjHvtcvppa/TA7Xb+5rI/c0eGmYwEIUVy/WQQCIAR0dUfpV5f0lmVJb+bt0ugn5unnr+Vp7rp9pqMBQEiiAAIICT8dmak3bhums7rEqLjMpw++2qv//ucqlVZWm44GACGHAgggZAw5M1Hv33WB/nLdQEmSt7JGf1+SbzYUAISgMNMBAKA5XGFOfX/gGaqqqdU9b67Rk3M3aWtRmUb2SNKVA9JYIAIATcAIIICQNH7QGRrdu+4pIm/k7dJdr6/SlFmrdKTKbzoaAAQ9CiCAkBTudGjGTUP0+DUDdNWgM+R0WHp31R79aPqXqqymBALAqVAAAYQsh8PS1dnpeuJHA/X3nw1VfHS41uwq0Ytf7DAdDQCCGgUQQIdwfvfO+s1lfSRJz3y6WUWllYYTAUDwogAC6DB+MOgMDfDEq7zKrz9/tNF0HAAIWhRAAB2Gw2Hpt5fXjQK+kbdL6wu9hhMBQHCiANbLzc2VZVmaMmWK6SgAWiC7W4Iu699VgYA07i8LNHNJvnjiJQA0RgGUtGzZMk2fPl39+/c3HQVAK/jvi3sqzFG3H+D9s9fqqY83G04EAMHF9gWwrKxM119/vWbMmKGEhATTcQC0gu5dOmnWbcP0w+x0SdJfPtmsZz/fYjgVAAQP2xfAyZMn67LLLtOYMWNMRwHQirK7JejP1wzQry7pLUl69MONuujPn+uzDUWGkwGAebZ+FNzrr7+uFStWaNmyZU16v8/nk8/na/ja62WCORDsfj7qLPlq/Hrq483aXlyuiS8t00BPvP735iFK6uQyHQ8AjLDtCGBBQYHuuusuvfbaa4qMjGzSZ3Jzc+V2uxteHo+njVMCaA1TxvTU3Lsv1PndEyVJqwoO6+VFO8yGAgCDrIBNl8e98847+sEPfiCn09lwzO/3y7IsORwO+Xy+Rt+TTjwC6PF4VFJSori4uHbLDuD0BAIBPTl3k/7n07r5gLdekKmp47LkqF8wAsAevF6v3G63ra/ftr0FPHr0aK1du7bRsYkTJ6p379761a9+dVz5kySXyyWXi1tGQKiyLEt3jO6hd1fv0c4DFZqxYLsSYiL0i1Fnm44GAO3KtgUwNjZW/fr1a3QsJiZGnTt3Pu44gI4j3OnQnNtH6q+fbdH0+dv054826t9f71OvlFg99IN+CnfadmYMABvh/+kA2I47KlxTx/XWNdnpqg3UzQmctbxAT3/CfoEA7MG2cwBbA3MIgNAWCAS0ZPtBrcg/pEc/rHt28A+z0/Xg9/sqOsK2N0iADo/rNyOAAGzMsiyd372zfjHqbI0fmCZJejNvl2YuyTecDADaFgUQACQ9ctU56p0aK0n64Ku9htMAQNuiAAKApOiIML008TxJUt7OQ/rwq71ihgyAjooCCAD1Ut2RuvScVEnSpNfy9Pz8bYYTAUDbYBFICzCJFOh49pZU6spnFqqotG7T9winQ11iXfrHrecro3O04XQAWgPXb0YAAaCRVHekltw/Whf0SJIkVflrtfvwEV3/wmLdPWuVKqv9hhMCQMuxzwEA/AfLsvTyxPNUVOpT/sEK/XjGYhUcPKKCg7t1Ue9kXTkgzXREAGgRRgAB4AQcDkup7kidl5mod28fofSEKEnSy4t2qLaWmTMAQhsFEAC+Rd80t35/RV9JdSuEWRwCINRRAAGgCUb2SFL3pBhJ0p8+3KDn5201nAgATh8FEACaIDLcqbk531FmfQl8Yu4mHSjzGU4FAKeHAggATeR0WHr/zguUHOuSr6ZW768tNB0JAE4LBRAAmiEqwqkJ52VIklbmHzYbBgBOEwUQAJppYEa8JOntlbu1dleJ2TAAcBoogADQTIM9CQ1/fn4+i0EAhB4KIAA0kzs6XL+7oo8k6avdjAACCD0UQAA4DeMHniFJ2nGgQq8u3mk4DQA0D4+CA4DTkBAToW6do7XzQIWemrtJ3ZNiZEnyJEbLkxhtOh4AnJIVCAR4ptFp8nq9crvdKikpUVxcnOk4ANrZ/lKfzn3440bHIsMdmnfPRUqJizSUCsC34frNCCAAnLYusS499aOBem7eVtUGAiosqVRpZY0mvZanru5Idenk0tRLsxQZ7jQdFQAaoQACQAuMH3SGxg+qmw/42uKd+vU7X2ll/mGtrP9+9y6ddPPwM43lA4AToQACQCuZcF6GYiPD5D1SrSXbD+q9NYX63ZyvtaWoTP9vfD/T8QCgAQUQAFqJ02Hp+/Wrgy/qnaz31xaqNiC9uninvpuVrIt6JRtOCAB12AYGANpAekK0Nj40TkmdXJKkiS8u0+JtBwynAoA6FEAAaCPhTodyrzqn4evc99dr+vytYvMFAKZRAAGgDV3cJ0XP3ZAtSVq9q0SPvL9By3YcMpwKgN1RAAGgjY3tk6I/XnWO+qe7JUlfbuVWMACzKIAA0MYcDkvXnZehH53rkSR9ua3YcCIAdkcBBIB2cn73zpKkJdsPauSfPtXKfG4FAzCDAggA7aR7Uox6p8YqEJB2HTqiN/J2mY4EwKYogADQTizL0ru3j9BD9ZtCz1ySry1FZYZTAbAjCiAAtCNXmFNXDEhr+PqDtYUG0wCwKwogALQzd1S47r+0tyTp8bmbdKi8ynAiAHZDAQQAA77XN7Xhz/M37zeYBIAdWQG2pD9tXq9XbrdbJSUliouLMx0HQIi5983V+ufyXerkClN0hFOSlBAdoRk3DVFG52jD6YCOi+s3I4AAYMy4c7pKksp8NSoq9amo1KeN+0r13to9hpMB6OgYAWwB/gYBoKV2HapQyZFqSdLbK3brhYXb1dUdqbOTO6mTK0z3X5olTyKjgUBr4vothZkOAAB2lp4QrfSEuj9XVPn1wsLtKiypVGFJpSQpMylG917S22BCAB0RBRAAgsS5ZyZq5s+Gal9ppRZvPahZywv06YYixUWFKz4qXFcNTldEGDN3ALQcBRAAgsjws5MkSWnuKM1aXqANe0v1xw82SJKcDkvXDPGYjAegg+CvkgAQhM49M1E5F/fUD7PTldW1bo7SyoLDKvJWqshbKV+N33BCAKGMRSAtwCRSAO3h70t26oHZXzU6ltQpQp/kjJI7OtxQKiB0cf228QjgtGnT1L9/f8XFxSkuLk7Dhg3TBx98YDoWABznOz27KDUuUg5Lclh1x4rLqvTVnhKzwQCELNuOAP7rX/+S0+nU2WefLUl6+eWX9dhjj2nlypXq27dvk34Gf4MAYMLEF5fqs437dd6ZicpMitF153k0KCPBdCwgZHD9tvEI4BVXXKFLL71UPXv2VM+ePfXwww+rU6dOWrx4seloAHBKPVNiJUlLd9StFH7k/fWGEwEINawCluT3+/XGG2+ovLxcw4YNMx0HAE7pF6POVlp8lPIPVuiFhdu1uahM/tqAnEfvDwPAt7DtCKAkrV27Vp06dZLL5dKkSZM0e/Zs9enT56Tv9/l88nq9jV4A0N7c0eG6efiZ+sWosyRJhyuqNejBf6vgYIXhZABCha0LYK9evbRq1SotXrxYP//5z3XzzTdr3bp1J31/bm6u3G53w8vjYT8uAOYkxkRoSLe6uX/eyhot2X7QcCIAocK2i0BOZMyYMTrrrLP0/PPPn/D7Pp9PPp+v4Wuv1yuPx2PrSaQAzAoEAvr5ayv04dd7ddXgM3T90G4anBEvy+J2MHAyLAKx+QjgfwoEAo0K3n9yuVwN28YcfQGASZZlqVdq3aKQt1fs1tXTFmnuun2GUwEIdrZdBHL//fdr3Lhx8ng8Ki0t1euvv67PP/9cH374oeloANAsVw0+QyvyD2l9oVfFZVXasLdUY/ummo4FIIjZdgRw3759uvHGG9WrVy+NHj1aS5Ys0YcffqiLL77YdDQAaJZunWP06i1D9eOh3SRJf/1si8p8NYZTAQhmth0BfOGFF0xHAIBWdUZ8pCTJV1Or5+dt1X+P7WU4EYBgZdsRQADoaMad07Xhz9uLyw0mARDsKIAA0EHERYbrfyYMkiRt2Fuqfy4v0Kcb9qm2ls0eADRGAQSADiQ1ru428JaiMt375hr99KXl+nxTkeFUAIINBRAAOpDsbgn6yfAz9d3eyQ1lcNt+bgcDaIwCCAAdiNNh6fdX9tXffnKuLulXtxXMtuJybd1fpr0llYbTAQgWtl0FDAAdXeeYCEnSzCX5mrkkX5L0xLUDdNXgdJOxAAQBRgABoIManZWijMRouaPC5Qqr+7/7lfmHzYYCEBQYAQSADqpPWpzm33uRJOlvC7frwffW6VBFleFUAIIBBRAAbCAhJlyStGjrAd30t6WSpHCHpVsv7K7zu3c2GQ2AARRAALCBzKROkqSD5VWav2l/w/Hq2gAFELAhCiAA2MCAdLdm3jq0YSXwhr2lmj5/mw6Vc0sYsCMKIADYgGVZGn5WUsPXy3cc1PT523T4SJXKfDUNx52WpagIp4mIANoRBRAAbCguqm5OYMHBI+r3u48ajluW9NvL+2jiiExT0QC0A7aBAQAb6tY5Wj2SOx13PBCQFmwuNpAIQHtiBBAAbMgV5tRHUy5Ulb+24dhHX+/VXa+vUlllzSk+CaAjoAACgE05HJYiHd/M90uIrntyyKGKKu0tqVSMy6nYyHBT8QC0IW4BAwAkSZ0i68YENheV6fzcT5T9/z7WivxDhlMBaAsUQACAJCkrNU69U2MV7rRkWVKVv1arCw6bjgWgDVAAAQCSpKgIpz6ccqE2P3yprs32SJIqqvyGUwFoCxRAAMBxol11cwOP3SMQQMfBIhAAwHFiIuouD39fvFMffbVXknT5gDTlXNzTZCwArYQRQADAcXqk1O0R6K2s0bbicm0rLtfz87YaTgWgtTACCAA4zpUD0tQ7NU7eymqVVlbrpy8tl6+mVv7agJwOy3Q8AC1EAQQAHMeyLPVKjZUkHTlmIUhltV8xLi4dQKjjv2IAwCm5wr6ZLbR0x0G5o8LljgrXWV2Of5QcgNBAAQQAnJLDYSk6wqmKKr8mvris4fhzN2Trkn6pBpMBOF0sAgEAfKufjcxURmK0MhKj1an+FvCWolLDqQCcLgogAOBb5Yztpfn3XqT5916kH2anS5Iqq2sNpwJwuiiAAIBmcYXXXToqq3lKCBCqmAMIAGgWV1jdU0L2l/m0bX+ZJCkp1qW4yHCTsQA0AwUQANAsUeF1BfDdVXv07qo9Dcc+v2eUUuIiTUYD0ETcAgYANMuoXl3kSYxSbGSYYiPD5LCkI9V+bSkqMx0NQBMxAggAaJasrnFacO93G76+4umFWru7RFU1LAoBQgUjgACAFomo3yjaRwEEQgYFEADQIq6GAsiqYCBUcAsYANAiR0cAZ6/cra/3eBuOW5LG9k1RdrdEQ8kAnAwFEADQIonREZKkzzfu1+cb9zf63r/X7dNnvxxlIBWAU6EAAgBa5O6LeyotPkpV/m/mAB4qr9Ibebt0uKLKYDIAJ0MBBAC0iCcxWr/8Xq9Gx3YUl+uNvF2q9gcMpQJwKiwCAQC0uvD6eYHVflYGA8GIAggAaHXhTksSBRAIVtwCBgC0ughn3fhCbUD6bGORHFZdIQx3WMo+M6HhecIAzLBtAczNzdXbb7+tDRs2KCoqSsOHD9ef/vQn9erV69s/DAA4paNbw0jSxBeXNfretUPS9egPB7R3JADHsO0t4Hnz5mny5MlavHix5s6dq5qaGo0dO1bl5eWmowFAyIuOCNNt3+muPl3jGl5nxEdJkgoOHjGcDoAVCARYoiVp//79Sk5O1rx583ThhRc26TNer1dut1slJSWKi4tr44QAENreX1uoX/x9hc49M0FvTBpuOg5sjOu3jUcA/1NJSYkkKTGRHesBoC2EOY4uDGHcATDNtnMAjxUIBJSTk6ORI0eqX79+J32fz+eTz+dr+Nrr9Z70vQCAxsLrF4bU1LIyGDCNEUBJt99+u9asWaN//OMfp3xfbm6u3G53w8vj8bRTQgAIfWH1W8PUMAIIGGf7EcA77rhDc+bM0fz585Wenn7K906dOlU5OTkNX3u9XkogADRRmKNuzKG8qkYb95Ye9/3YyDCl1S8UAdC2bFsAA4GA7rjjDs2ePVuff/65MjMzv/UzLpdLLperHdIBQMcTEVY3Alhw8Ii+99T8E75nxk1DdHGflPaMBdiSbQvg5MmTNXPmTL377ruKjY3V3r17JUlut1tRUfwNFABaW980t7K7JWhH8fHbbZX6alRVU6tN+0opgEA7sG0BnDZtmiRp1KhRjY6/+OKL+slPftL+gQCgg4sMd+qtn594+5cHZq/V35fkMz8QaCe2LYBsfwgAwcNZv0WMnxXCQLtgFTAAwLiGAshfzoF2QQEEABh3dJPomloKINAeKIAAAOOc9VvE+JkDCLQLCiAAwLj6h4QwAgi0E9suAgEABI+jI4CvfLlDM5fmn/A9rjCH/nhVf13Wv2t7RgM6JEYAAQDGDUh3y2FJtQGpqqb2hK/SyhrNXbfXdFSgQ2AEEABg3OisFK34zcWqqPKf8PtvLN+lJz/epGpuEQOtggIIAAgK8dERio8+8fc6d4qQJNX42ScQaA3cAgYABL1wZ/02MawSBloFBRAAEPTC65cJVzECCLQKCiAAIOiF1RdARgCB1kEBBAAEvfD6J4VUMwIItAoKIAAg6B29BcwqYKB1sAoYABD0wuoXgRyuqNKCzftP+d7eqXHqEutqj1hAyKIAAgCCnivMKUnaeaBCN76w9JTvTerk0pL7R8tZf9sYwPEogACAoDcoI15j+6So4NCRk74nEAhow95SFZf5VFntV4yLSxxwMvzXAQAIepHhTk2/acgp31NVU6uev/5AklTDXEHglFgEAgDoEMKOueXrpwACp0QBBAB0CA4KINBkFEAAQIdxdBSQAgicGgUQANBhHF35W1PLhtHAqVAAAQAdhpMRQKBJKIAAgA6DAgg0DQUQANBhMAcQaBoKIACgw/hmDiAFEDgVNoIGAHQYRwvg/60p1Mr8w9/6/shwhy7uk6LYyPA2TgYEFwogAKDDiAqve2bwM59tafJnbvtOd00dl9VWkYCgRAEEAHQY943L0tsrdqkpN4B3FJdrc1GZikur2jwXEGwogACADuOSfqm6pF9qk947ff5WPfL+BgUCzBeE/bAIBABgSw6rbr5gLQUQNkQBBADY0jcF0HAQwAAKIADAluoXDMvPCCBsiAIIALAlR30DZA4g7IgCCACwJevoLeBaw0EAAyiAAABbcrIIBDZGAQQA2NLROYAsAoEdUQABALbENjCwMwogAMCWrIYRQAog7IcCCACwJaeDfQBhXxRAAIAtHb0FzDYwsCOeBQwAsKWjt4Arq/0qKq08rZ/RpZOrYTsZIJRQAAEAtnR0BHDZjkM67+FPTutnXNI3Vc/dmN2asYB2wS1gAIAtDcqIV2pcpCxLzX4dtXznQXP/AkAL2HoEcP78+XrssceUl5enwsJCzZ49W+PHjzcdCwDQDtITorX4/tGn9dlN+0o19sn5YvogQpWtRwDLy8s1YMAAPfPMM6ajAABCiIMtZBDibD0COG7cOI0bN850DABAiGl4jjD9DyHK1gWwuXw+n3w+X8PXXq/XYBoAgCk8RQShzta3gJsrNzdXbre74eXxeExHAgAYcPQWMP0PoYoC2AxTp05VSUlJw6ugoMB0JACAAZbYRBqhjVvAzeByueRyuUzHAAAY9s1zhM3mAE4XI4AAADSTw8EcQIQ2W48AlpWVacuWLQ1fb9++XatWrVJiYqIyMjIMJgMABDPmACLU2boALl++XBdddFHD1zk5OZKkm2++WS+99JKhVACAYMcqYIQ6WxfAUaNGMYEXANBsR58GxxUEoYo5gAAANJPFCCBCHAUQAIBmOnYOIHeSEIoogAAANNPROYASC0EQmiiAAAA007EFkNvACEUUQAAAmuub/sdCEIQkCiAAAM3kOKYAMgKIUEQBBACgmZgDiFBHAQQAoJmYA4hQZ+uNoAEAOB3H9D89OXeTIsJafzwlxhWmCedmKCEmotV/NkABBACgmcIcllxhDvlqajVjwfY2+9/x+wO6Y3SPNvv5sC8KIAAAzRTmdOjpCYP05bYDbfLzl+04qK92e1Xqq2mTnw9QAAEAOA1j+6ZqbN/UNvnZj7y/Xl/t9vKUEbQZFoEAABBkjk4xpP+hrVAAAQAINkefNWw2BTowCiAAAEHGOvZRI0AboAACABBkjm4zwy1gtBUKIAAAQaZhDiA3gdFGKIAAAAQpRgDRViiAAAAEGYspgGhjFEAAAILM0UUg7AOItkIBBAAgyFhsA4M2RgEEACDIsBE02hoFEACAYFM/BMgqYLQVCiAAAEGGNSBoaxRAAACCDBtBo61RAAEACDINq4AN50DHRQEEACDIMAKItkYBBAAgyHwzB5AGiLZBAQQAIMgwAoi2RgEEACBIUQDRViiAAAAEGYt9ANHGKIAAAAQpRgDRViiAAAAEGYudoNHGKIAAAAQZ9gFEW6MAAgAQZFgFjLZGAQQAIMgcvQPMIhC0FQogAABBxvqmAQJtggIIAECQYQ4g2hoFEACAIPPNHEAqINoGBRAAgCBF/UNboQACABBkGp4EQgNEG6EAAgAQZFgDgrZm+wL47LPPKjMzU5GRkcrOztaCBQtMRwIAAGhTti6As2bN0pQpU/TAAw9o5cqVuuCCCzRu3Djl5+ebjgYAsDEWgaCt2boAPvHEE7rlllv0s5/9TFlZWXrqqafk8Xg0bdo009EAADbGLWC0tTDTAUypqqpSXl6e7rvvvkbHx44dq0WLFp3wMz6fTz6fr+Frr9fbphkBAPZ0dBHIqvzDmvL6SsNpzLqkX6ou6dfVdIwOx7YFsLi4WH6/XykpKY2Op6SkaO/evSf8TG5urv7whz+0RzwAgI0lxERIknYfPqLdq44YTmPWmUkxFMA2YNsCeJTV8LydOoFA4LhjR02dOlU5OTkNX3u9Xnk8njbNBwCwn0v6puqJawfoYHmV6SjGDcpIMB2hQ7JtAUxKSpLT6TxutK+oqOi4UcGjXC6XXC5Xe8QDANhYRJhDVw1ONx0DHZhtF4FEREQoOztbc+fObXR87ty5Gj58uKFUAAAAbc+2I4CSlJOToxtvvFFDhgzRsGHDNH36dOXn52vSpEmmowEAALQZWxfAH/3oRzpw4IAefPBBFRYWql+/fnr//ffVrVs309EAAADajBVgl8nT5vV65Xa7VVJSori4ONNxAABAE3D9tvEcQAAAALuiAAIAANgMBRAAAMBmKIAAAAA2QwEEAACwGQogAACAzVAAAQAAbIYCCAAAYDMUQAAAAJux9aPgWuroQ1S8Xq/hJAAAoKmOXrft/DA0CmALlJaWSpI8Ho/hJAAAoLlKS0vldrtNxzCCZwG3QG1trfbs2aPY2FhZltWqP9vr9crj8aigoMC2zykMZvx+gh+/o+DG7yf4deTfUSAQUGlpqdLS0uRw2HM2HCOALeBwOJSent6m/xtxcXEd7j+8joTfT/DjdxTc+P0Ev476O7LryN9R9qy9AAAANkYBBAAAsBkKYJByuVz63e9+J5fLZToKToDfT/DjdxTc+P0EP35HHRuLQAAAAGyGEUAAAACboQACAADYDAUQAADAZiiAAAAANkMBDELPPvusMjMzFRkZqezsbC1YsMB0JNTLzc3Vueeeq9jYWCUnJ2v8+PHauHGj6Vg4idzcXFmWpSlTppiOgmPs3r1bN9xwgzp37qzo6GgNHDhQeXl5pmNBUk1NjX79618rMzNTUVFR6t69ux588EHV1taajoZWRgEMMrNmzdKUKVP0wAMPaOXKlbrgggs0btw45efnm44GSfPmzdPkyZO1ePFizZ07VzU1NRo7dqzKy8tNR8N/WLZsmaZPn67+/fubjoJjHDp0SCNGjFB4eLg++OADrVu3To8//rji4+NNR4OkP/3pT3ruuef0zDPPaP369Xr00Uf12GOP6emnnzYdDa2MbWCCzNChQzV48GBNmzat4VhWVpbGjx+v3Nxcg8lwIvv371dycrLmzZunCy+80HQc1CsrK9PgwYP17LPP6qGHHtLAgQP11FNPmY4FSffdd5+++OIL7mwEqcsvv1wpKSl64YUXGo5dffXVio6O1quvvmowGVobI4BBpKqqSnl5eRo7dmyj42PHjtWiRYsMpcKplJSUSJISExMNJ8GxJk+erMsuu0xjxowxHQX/Yc6cORoyZIiuueYaJScna9CgQZoxY4bpWKg3cuRIffLJJ9q0aZMkafXq1Vq4cKEuvfRSw8nQ2sJMB8A3iouL5ff7lZKS0uh4SkqK9u7daygVTiYQCCgnJ0cjR45Uv379TMdBvddff10rVqzQsmXLTEfBCWzbtk3Tpk1TTk6O7r//fi1dulR33nmnXC6XbrrpJtPxbO9Xv/qVSkpK1Lt3bzmdTvn9fj388MOaMGGC6WhoZRTAIGRZVqOvA4HAccdg3u233641a9Zo4cKFpqOgXkFBge666y79+9//VmRkpOk4OIHa2loNGTJEjzzyiCRp0KBB+vrrrzVt2jQKYBCYNWuWXnvtNc2cOVN9+/bVqlWrNGXKFKWlpenmm282HQ+tiAIYRJKSkuR0Oo8b7SsqKjpuVBBm3XHHHZozZ47mz5+v9PR003FQLy8vT0VFRcrOzm445vf7NX/+fD3zzDPy+XxyOp0GE6Jr167q06dPo2NZWVl66623DCXCse655x7dd999uu666yRJ55xzjnbu3Knc3FwKYAfDHMAgEhERoezsbM2dO7fR8blz52r48OGGUuFYgUBAt99+u95++219+umnyszMNB0Jxxg9erTWrl2rVatWNbyGDBmi66+/XqtWraL8BYERI0Yct3XSpk2b1K1bN0OJcKyKigo5HI2rgdPpZBuYDogRwCCTk5OjG2+8UUOGDNGwYcM0ffp05efna9KkSaajQXWLC2bOnKl3331XsbGxDaO1brdbUVFRhtMhNjb2uPmYMTEx6ty5M/M0g8Tdd9+t4cOH65FHHtG1116rpUuXavr06Zo+fbrpaJB0xRVX6OGHH1ZGRob69u2rlStX6oknntBPf/pT09HQytgGJgg9++yzevTRR1VYWKh+/frpySefZIuRIHGyuZgvvviifvKTn7RvGDTJqFGj2AYmyLz33nuaOnWqNm/erMzMTOXk5OjWW281HQuSSktL9Zvf/EazZ89WUVGR0tLSNGHCBP32t79VRESE6XhoRRRAAAAAm2EOIAAAgM1QAAEAAGyGAggAAGAzFEAAAACboQACAADYDAUQAADAZiiAAAAANkMBBAAAsBkKIAAAgM1QAAEAAGyGAggAAGAzFEAAAACboQACAADYDAUQAADAZiiAAAAANkMBBAAAsBkKIAAAgM1QAAEAAGyGAggAAGAzFEAAAACboQACAADYDAUQAADAZiiAAAAANkMBBAAAsBkKIAAAgM1QAAEAAGyGAggAAGAzFEAAAACboQACAADYDAUQAADAZiiAAAAANvP/AaFiaqrJfHMyAAAAAElFTkSuQmCC", "text/plain": [ - "" + "'02_Jezyki/voy-words-log-log.png'" ] }, + "execution_count": 19, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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"text/plain": [ - "" + "'02_Jezyki/dna-chars.png'" ] }, + "execution_count": 21, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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"text/plain": [ - "" + "'02_Jezyki/dna-aminos.png'" ] }, + "execution_count": 22, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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", "text/plain": [ - "" + "'02_Jezyki/dna_length.png'" ] }, + "execution_count": 23, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -1179,580 +1372,6 @@ "\n", "fname" ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Entropia\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Entropia** ($E$) to miara nieuporządkowania, niepewności, niewiedzy. Im\n", - "większa entropia, tym mniej wiemy. Pojęcie to pierwotnie wywodzi się z\n", - "termodynamiki, później znaleziono wiele zaskakujących analogii i zastosowań w\n", - "innych dyscyplinach nauki.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Entropia w fizyce\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "W termodynamice entropia jest miarą nieuporządkowania układów\n", - "fizycznych, na przykład pojemników z gazem. Przykładowo, wyobraźmy\n", - "sobie dwa pojemniki z gazem, w którym panuje różne temperatury.\n", - "\n", - "![img](./02_Jezyki/gas-low-entropy.drawio.png)\n", - "\n", - "Jeśli usuniemy przegrodę między pojemnikami, temperatura się wyrówna,\n", - "a uporządkowanie się zmniejszy.\n", - "\n", - "![img](./02_Jezyki/gas-high-entropy.drawio.png)\n", - "\n", - "Innymi słowy, zwiększy się stopień nieuporządkowania układu, czyli właśnie entropia.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### II prawo termodynamiki\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Jedno z najbardziej fundamentalnych praw fizyki, II prawo\n", - "termodynamiki głosi, że w układzie zamkniętym entropia nie spada.\n", - "\n", - "****Pytanie****: Czy to, że napisałem te materiały do wykładu i\n", - "*uporządkowałem* wiedzę odnośnie do statystycznych własności języka, nie\n", - "jest sprzeczne z II prawem termodynamiki?\n", - "\n", - "Konsekwencją II prawa termodynamiki jest śmierć cieplna Wszechświata\n", - "(zob. [wizualizacja przyszłości Wszechświata]([https://www.youtube.com/watch?v=uD4izuDMUQA](https://www.youtube.com/watch?v=uD4izuDMUQA))).\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Entropia w teorii informacji\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Pojęcie entropii zostało „odkryte” na nowo przez Claude'a Shannona,\n", - "gdy wypracował ogólną teorię informacji.\n", - "\n", - "Teoria informacji zajmuje się między innymi zagadnieniem optymalnego kodowania komunikatów.\n", - "\n", - "Wyobraźmy sobie pewne źródło (generator) losowych komunikatów z\n", - "zamkniętego zbioru symboli ($\\Sigma$; nieprzypadkowo używamy oznaczeń\n", - "z poprzedniego wykładu). Nadawca $N$ chce przesłać komunikat o wyniku\n", - "losowania do odbiorcy $O$ używając zer i jedynek (bitów).\n", - "Teorioinformacyjną entropię można zdefiniować jako średnią liczbę\n", - "bitów wymaganych do przesłania komunikatu.\n", - "\n", - "![img](./02_Jezyki/communication.drawio.png)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Obliczanie entropii — proste przykłady\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Załóżmy, że nadawca chce przekazać odbiorcy informację o wyniku rzutu monetą.\n", - "Entropia wynosi wówczas rzecz jasna 1 — na jedno losowanie wystarczy jeden bit\n", - "(informację o tym, że wypadł orzeł, możemy zakodować na przykład za pomocą zera,\n", - "zaś to, że wypadła reszka — za pomocą jedynki).\n", - "\n", - "Rozpatrzmy przypadek, gdy nadawca rzuca ośmiościenną kością. Aby przekazać\n", - "wynik, potrzebuje wówczas 3 bity (a więc entropia ośmiościennej kości\n", - "wynosi 3 bity). Przykładowe kodowanie może mieć następującą postać:\n", - "\n", - "| Wynik|Kodowanie|\n", - "|---|---|\n", - "| 1|001|\n", - "| 2|010|\n", - "| 3|011|\n", - "| 4|100|\n", - "| 5|101|\n", - "| 6|110|\n", - "| 7|111|\n", - "| 8|000|\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Obliczenie entropii — trudniejszy przykład\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Załóżmy, że $\\Sigma = \\{A, B, C, D\\}$, natomiast poszczególne komunikaty\n", - "są losowane zgodnie z następującym rozkładem prawdopodobieństwa:\n", - "$P(A)=1/2$, $P(B)=1/4$, $P(C)=1/8$, $P(D)=1/8$. Ile wynosi entropia w\n", - "takim przypadku? Można by sądzić, że 2, skoro wystarczą 2 bity do\n", - "przekazania wyniku losowania przy zastosowaniu następującego kodowania:\n", - "\n", - "| Wynik|Kodowanie|\n", - "|---|---|\n", - "| A|00|\n", - "| B|01|\n", - "| C|10|\n", - "| D|11|\n", - "\n", - "Problem w tym, że w rzeczywistości nie jest to *optymalne* kodowanie.\n", - "Możemy sprytnie zmniejszyć średnią liczbę bitów wymaganych do\n", - "przekazania losowego wyniku przypisując częstszym wynikom krótsze\n", - "kody, rzadszym zaś — dłuższe. Oto takie optymalne kodowanie:\n", - "\n", - "| Wynik|Kodowanie|\n", - "|---|---|\n", - "| A|0|\n", - "| B|10|\n", - "| C|110|\n", - "| D|111|\n", - "\n", - "Używając takiego kodowanie średnio potrzebujemy:\n", - "\n", - "$$\\frac{1}{2}1 + \\frac{1}{4}2 + \\frac{1}{8}3 + \\frac{1}{8}3 = 1,75$$\n", - "\n", - "bita. Innymi słowy, entropia takiego źródła wynosi 1,75 bita.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Kodowanie musi być jednoznaczne!\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Można by sądzić, że da się stworzyć jeszcze krótsze kodowanie dla omawianego rozkładu nierównomiernego:\n", - "\n", - "| Wynik|Kodowanie|\n", - "|---|---|\n", - "| A|0|\n", - "| B|1|\n", - "| C|01|\n", - "| D|11|\n", - "\n", - "Niestety, nie jest to właściwe rozwiązanie — kodowanie musi być\n", - "jednoznaczne nie tylko dla pojedynczego komunikatu, lecz dla całej sekwencji.\n", - "Na przykład ciąg 0111 nie jest jednoznaczny przy tym kodowaniu (ABBB czy CD?).\n", - "Podane wcześniej kodowanie spełnia warunek jednoznaczności, ciąg 0111 można odkodować tylko\n", - "jako AD.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Ogólny wzór na entropię.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Na podstawie poprzedniego przykładu można dojść do intuicyjnego wniosku, że\n", - "optymalny kod dla wyniku o prawdopodobieństwie $p$ ma długość $-\\log_2(p)$, a zatem ogólnie\n", - "entropia źródła o rozkładzie prawdopodobieństwa $\\{p_1,\\ldots,p_|\\Sigma|\\}$ wynosi:\n", - "\n", - "$$E = -\\sum_{i=1}^{|\\Sigma|} p_i\\log_2(p_i)$$.\n", - "\n", - "Zauważmy, że jest to jeden z nielicznych przypadków, gdy w nauce naturalną\n", - "podstawą logarytmu jest 2 zamiast… podstawy logarytmu naturalnego ($e$).\n", - "\n", - "Teoretycznie można mierzyć entropię używając logarytmu naturalnego\n", - "($\\ln$), jednostką entropii będzie wówczas **nat** zamiast bita,\n", - "niewiele to jednak zmienia i jest mniej poręczne i trudniejsze do interpretacji\n", - "(przynajmniej w kontekście informatyki) niż operowanie na bitach.\n", - "\n", - "****Pytanie**** Ile wynosi entropia zwykłej sześciennej kostki? Jak wygląda\n", - "optymalne kodowanie wyników rzutu taką kostką?\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Entropia dla próby Bernoulliego\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Wiemy już, że entropia dla rzutu monetą wynosi 1 bit. A jaki będzie wynik dla źle wyważonej monety?\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "from math import log\n", - "import numpy as np\n", - "\n", - "def binomial_entropy(p):\n", - " return -(p * log(p, 2) + (1-p) * log(1-p, 2))\n", - "\n", - "x = list(np.arange(0.001,1,0.001))\n", - "y = [binomial_entropy(x) for x in x]\n", - "plt.figure().clear()\n", - "plt.xlabel('prawdopodobieństwo wylosowania orła')\n", - "plt.ylabel('entropia')\n", - "plt.plot(x, y)\n", - "\n", - "fname = f'02_Jezyki/binomial-entropy.png'\n", - "\n", - "plt.savefig(fname)\n", - "\n", - "fname" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Pytanie** Dla oszukańczej monety (np. dla której wypada zawsze orzeł) entropia\n", - "wynosi 0, czy to wynik zgodny z intuicją?\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Entropia a język\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Tekst w danym języku możemy traktować jako ciąg symboli (komunikatów) losowanych według jakiegoś\n", - "rozkładu prawdopodobieństwa. W tym sensie możemy mówić o entropii języka.\n", - "\n", - "Oczywiście, jak zawsze, musimy jasno stwierdzić, czym są symbole\n", - "języka: literami, wyrazami czy jeszcze jakimiś innymi jednostkami.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Pomiar entropii języka — pierwsze przybliżenie\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Załóżmy, że chcemy zmierzyć entropię języka polskiego na przykładzie\n", - "„Pana Tadeusza” — na poziomie znaków. W pierwszym przybliżeniu można\n", - "by policzyć liczbę wszystkich znaków…\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "95" - ] - } - ], - "source": [ - "chars_in_pan_tadeusz = len(set(get_characters(pan_tadeusz)))\n", - "chars_in_pan_tadeusz" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "… założyć jednostajny rozkład prawdopodobieństwa i w ten sposób policzyć entropię:\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6.569855608330948" - ] - } - ], - "source": [ - "from math import log\n", - "\n", - "95 * (1/95) * log(95, 2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Mniej rozrzutne kodowanie\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Przypomnijmy sobie jednak, że rozkład jednostek języka jest zawsze\n", - "skrajnie nierównomierny! Jeśli uwzględnić ten nierównomierny rozkład\n", - "znaków, można opracować o wiele efektywniejszy sposób zakodowania znaków składających się na „Pana Tadeusza”\n", - "(częste litery, np. „a” i „e” powinny mieć krótkie kody, a rzadkie, np. „ź” — dłuższe).\n", - "\n", - "Policzmy entropię przy takim założeniu:\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "4.938605272823633" - ] - } - ], - "source": [ - "from collections import Counter\n", - "from math import log\n", - "\n", - "def unigram_entropy(t):\n", - " counter = Counter(t)\n", - "\n", - " total = counter.total()\n", - " return -sum((p := count / total) * log(p, 2) for count in counter.values())\n", - "\n", - "unigram_entropy(get_characters(pan_tadeusz))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "(Jak dowiemy się na kolejnym wykładzie, zastosowaliśmy tutaj **unigramowy model języka**).\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Ile wynosi entropia rękopisu Wojnicza?\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3.902708104423842" - ] - } - ], - "source": [ - "unigram_entropy(get_characters(voynich))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Rzeczywista entropia?\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "W rzeczywistości entropia jest jeszcze mniejsza, tekst nie jest\n", - "generowany przecież według rozkładu wielomianowego. Istnieją rzecz\n", - "jasna pewne zależności między znakami, np. niemożliwe, żeby po „ń”\n", - "wystąpiły litera „a” czy „e”. Na poziomie wyrazów zależności mogę mieć\n", - "jeszcze bardziej skrajny charakter, np. po wyrazie „przede” prawie na\n", - "pewno wystąpi „wszystkim”, co oznacza, że w takiej sytuacji słowo\n", - "„wszystkim” może zostać zakodowane za pomocą 0 (!) bitów.\n", - "\n", - "Można uwzględnić takie zależności i uzyskać jeszcze lepsze kodowanie,\n", - "a co za tym idzie lepsze oszacowanie entropii. (Jak wkrótce się\n", - "dowiemy, oznacza to użycie digramowego, trigramowego, etc. modelu języka).\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Rozmiar skompresowanego pliku jako przybliżenie entropii\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Celem algorytmów kompresji jest właściwie wyznaczanie efektywnych\n", - "sposobów kodowania danych. Możemy więc użyć rozmiaru skompresowanego pliku w bitach\n", - "(po podzieleniu przez oryginalną długość) jako dobrego przybliżenia entropii.\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3.673019884633768" - ] - } - ], - "source": [ - "import zlib\n", - "\n", - "def entropy_by_compression(t):\n", - " compressed = zlib.compress(t.encode('utf-8'))\n", - " return 8 * len(compressed) / len(t)\n", - "\n", - "entropy_by_compression(pan_tadeusz)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Dla porównania wynik dla rękopisu Wojnicza:\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2.942372881355932" - ] - } - ], - "source": [ - "entropy_by_compression(voynich)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Gra Shannona\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Innym sposobem oszacowania entropii tekstu jest użycie… ludzi. Można poprosić rodzimych użytkowników\n", - "danego języka o przewidywanie kolejnych liter (bądź wyrazów) i w ten sposób oszacować entropię.\n", - "\n", - "**Projekt** Zaimplementuj aplikację webową, która umożliwi „rozegranie” gry Shannona.\n", - "\n" - ] } ], "metadata": { diff --git a/wyk/02_Jezyki.org b/wyk/02_Jezyki.org index 8f95bd5..ca42c72 100644 --- a/wyk/02_Jezyki.org +++ b/wyk/02_Jezyki.org @@ -9,7 +9,7 @@ Używać będziemy generatorów. *Pytanie* Dlaczego generatory zamiast list? -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer import requests url = 'https://wolnelektury.pl/media/book/txt/pan-tadeusz.txt' @@ -31,7 +31,7 @@ Powrót pani *** Znaki -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer from itertools import islice def get_characters(t): @@ -45,7 +45,7 @@ Powrót pani ['K', 's', 'i', 'ę', 'g', 'a', ' ', 'p', 'i', 'e', 'r', 'w', 's', 'z', 'a', '\r', '\n', '\r', '\n', '\r', '\n', '\r', '\n', 'G', 'o', 's', 'p', 'o', 'd', 'a', 'r', 's', 't', 'w', 'o', '\r', '\n', '\r', '\n', 'P', 'o', 'w', 'r', 'ó', 't', ' ', 'p', 'a', 'n', 'i'] :end: -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer from collections import Counter c = Counter(get_characters(pan_tadeusz)) @@ -65,7 +65,7 @@ Napiszmy pomocniczą funkcję, która zwraca *listę frekwencyjną*. Counter({' ': 63444, 'a': 30979, 'i': 29353, 'e': 25343, 'o': 23050, 'z': 22741, 'n': 15505, 'r': 15328, 's': 15255, 'w': 14625, 'c': 14153, 'y': 13732, 'k': 12362, 'd': 11465, '\r': 10851, '\n': 10851, 't': 10757, 'm': 10269, 'ł': 10059, ',': 9130, 'p': 8031, 'u': 7699, 'l': 6677, 'j': 6586, 'b': 5753, 'ę': 5534, 'ą': 4794, 'g': 4775, 'h': 3915, 'ż': 3334, 'ó': 3097, 'ś': 2524, '.': 2380, 'ć': 1956, ';': 1445, 'P': 1265, 'W': 1258, ':': 1152, '!': 1083, 'S': 1045, 'T': 971, 'I': 795, 'N': 793, 'Z': 785, 'J': 729, '—': 720, 'A': 698, 'K': 683, 'ń': 651, 'M': 585, 'B': 567, 'O': 567, 'C': 556, 'D': 552, '«': 540, '»': 538, 'R': 489, '?': 441, 'ź': 414, 'f': 386, 'G': 358, 'L': 316, 'H': 309, 'Ż': 219, 'U': 184, '…': 157, '*': 150, '(': 76, ')': 76, 'Ś': 71, 'F': 47, 'é': 43, '-': 33, 'Ł': 24, 'E': 23, '/': 19, 'Ó': 13, '8': 10, '9': 8, '2': 6, 'v': 5, 'Ź': 4, '1': 4, '3': 3, 'x': 3, 'V': 3, '7': 2, '4': 2, '5': 2, 'q': 2, 'æ': 2, 'à': 1, 'Ć': 1, '6': 1, '0': 1}) :end: -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer from collections import Counter from collections import OrderedDict @@ -88,7 +88,7 @@ OrderedDict([(' ', 63444), ('a', 30979), ('i', 29353), ('e', 25343), ('o', 23050 :end: -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file import matplotlib.pyplot as plt from collections import OrderedDict @@ -119,7 +119,7 @@ Co rozumiemy pod pojęciem słowa czy wyrazu, nie jest oczywiste. W praktyce zal Załóżmy, że przez wyraz rozumieć będziemy nieprzerwany ciąg liter bądź cyfr (oraz gwiazdek — to za chwilę ułatwi nam analizę pewnego tekstu…). -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer from itertools import islice import regex as re @@ -138,7 +138,7 @@ Załóżmy, że przez wyraz rozumieć będziemy nieprzerwany ciąg liter bądź Zobaczmy 20 najczęstszych wyrazów. -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file rang_freq_with_labels('pt-words-20', get_words(pan_tadeusz), top=20) #+END_SRC @@ -147,7 +147,7 @@ Zobaczmy 20 najczęstszych wyrazów. Zobaczmy pełny obraz, już bez etykiet. -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file import matplotlib.pyplot as plt from math import log @@ -172,7 +172,7 @@ Zobaczmy pełny obraz, już bez etykiet. Widać, jak różne skale obejmuje ten wykres. Zastosujemy logarytm, najpierw tylko do współrzędnej $y$. -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file import matplotlib.pyplot as plt from math import log @@ -222,7 +222,7 @@ logarytmicznej dla **obu** osi, otrzymamy kształt zbliżony do linii prostej. Tę własność tekstów nazywamy **prawem Zipfa**. -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file import matplotlib.pyplot as plt from math import log @@ -249,7 +249,7 @@ Tę własność tekstów nazywamy **prawem Zipfa**. Powiązane z prawem Zipfa prawo językowe opisuje zależność między częstością użycia słowa a jego długością. Generalnie im krótsze słowo, tym częstsze. -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file def freq_vs_length(name, g, top=None): freq = freq_list(g) @@ -294,7 +294,7 @@ po prostu na jednostkach, nie na ich podciągach. Statystyki, które policzyliśmy dla pojedynczych liter czy wyrazów, możemy powtórzyć dla n-gramów. -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer def ngrams(iter, size): ngram = [] for item in iter: @@ -317,7 +317,7 @@ Zawsze powinniśmy się upewnić, czy jest jasne, czy chodzi o n-gramy znakowe c *** 3-gramy znakowe -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file log_rang_log_freq('pt-3-char-ngrams-log-log', ngrams(get_characters(pan_tadeusz), 3)) #+END_SRC @@ -326,7 +326,7 @@ Zawsze powinniśmy się upewnić, czy jest jasne, czy chodzi o n-gramy znakowe c *** 2-gramy wyrazowe -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file log_rang_log_freq('pt-2-word-ngrams-log-log', ngrams(get_words(pan_tadeusz), 2)) #+END_SRC @@ -348,7 +348,7 @@ transkrybować manuskrypt, pozostaje sprawą dyskusyjną, natomiast wybór takiego czy innego systemu transkrypcji nie powinien wpływać dramatycznie na analizę statystyczną. -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer import requests voynich_url = 'http://www.voynich.net/reeds/gillogly/voynich.now' @@ -370,28 +370,28 @@ dramatycznie na analizę statystyczną. 9 OR 9FAM ZO8 QOAR9 Q*R 8ARAM 29 [O82*]OM OPCC9 OP :end: -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file rang_freq_with_labels('voy-chars', get_characters(voynich)) #+END_SRC #+RESULTS: [[file:02_Jezyki/voy-chars.png]] -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file log_rang_log_freq('voy-log-log', get_words(voynich)) #+END_SRC #+RESULTS: [[file:02_Jezyki/voy-log-log.png]] -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file rang_freq_with_labels('voy-words-20', get_words(voynich), top=20) #+END_SRC #+RESULTS: [[file:02_Jezyki/voy-words-20.png]] -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file log_rang_log_freq('voy-words-log-log', get_words(voynich)) #+END_SRC @@ -406,7 +406,7 @@ Podstawowe litery są tylko cztery, reprezentują one nukleotydy, z których zbu a, g, c, t. -#+BEGIN_SRC python :session mysession :exports both :results raw drawer +#+BEGIN_SRC ipython :session mysession :exports both :results raw drawer import requests dna_url = 'https://raw.githubusercontent.com/egreen18/NanO_GEM/master/rawGenome.txt' @@ -423,7 +423,7 @@ a, g, c, t. TATAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTA :end: -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file rang_freq_with_labels('dna-chars', get_characters(dna)) #+END_SRC @@ -436,7 +436,7 @@ Nukleotydy rzeczywiście są jak litery, same w sobie nie niosą znaczenia. Dopiero ciągi trzech nukleotydów, /tryplety/, kodują jeden z dwudziestu aminokwasów. -#+BEGIN_SRC python :session mysession :results file +#+BEGIN_SRC ipython :session mysession :results file genetic_code = { 'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M', 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T', @@ -472,7 +472,7 @@ Z aminokwasów zakodowanych przez tryplet budowane są białka. Maszyneria budująca białka czyta sekwencję aż do napotkania trypletu STOP (_ powyżej). 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