mirror of
https://github.com/titanscouting/tra-analysis.git
synced 2024-11-09 22:44:44 +00:00
Merge branch 'master' into master-staged
This commit is contained in:
commit
b721a2a4ce
@ -21,6 +21,7 @@
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},
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"extensions": [
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"mhutchie.git-graph",
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"donjayamanne.jupyter",
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],
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"postCreateCommand": "pip install -r analysis-master/analysis-amd64/requirements.txt"
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}
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@ -0,0 +1,35 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"string = \"3+4+5\"\n",
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"re.sub(\"\\d+[+]{1}\\d+\", string, sum([int(i) for i in re.split(\"[+]{1}\", re.search(\"\\d+[+]{1}\\d+\", string).group())]))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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@ -12,7 +12,7 @@ __version__ = "1.2.1.003"
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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1.2.1.003:
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- fixed __al__
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- fixed __all__
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1.2.1.002:
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- renamed ArrayTest class to Array
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1.2.1.001:
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@ -414,7 +414,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
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popt, pcov = scipy.optimize.curve_fit(lin, X, y)
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regressions.append((popt.flatten().tolist(), None))
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coeffs = popt.flatten().tolist()
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regressions.append(str(coeffs[0]) + "*x+" + str(coeffs[1]))
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except Exception as e:
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@ -430,7 +431,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
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popt, pcov = scipy.optimize.curve_fit(log, X, y)
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regressions.append((popt.flatten().tolist(), None))
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coeffs = popt.flatten().tolist()
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regressions.append(str(coeffs[0]) + "*log(" + str(coeffs[1]) + "*(x+" + str(coeffs[2]) + "))+" + str(coeffs[3]))
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except Exception as e:
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@ -446,7 +448,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
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popt, pcov = scipy.optimize.curve_fit(exp, X, y)
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regressions.append((popt.flatten().tolist(), None))
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coeffs = popt.flatten().tolist()
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regressions.append(str(coeffs[0]) + "*e^(" + str(coeffs[1]) + "*(x+" + str(coeffs[2]) + "))+" + str(coeffs[3]))
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except Exception as e:
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@ -468,10 +471,14 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
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params = model.steps[1][1].intercept_.tolist()
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params = np.append(params, model.steps[1][1].coef_[0].tolist()[1::])
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params.flatten()
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params = params.tolist()
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plys.append(params)
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params = params.flatten().tolist()
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temp = ""
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counter = 0
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for param in params:
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temp += "(" + str(param) + "*x^" + str(counter) + ")"
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counter += 1
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plys.append(temp)
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regressions.append(plys)
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@ -485,7 +492,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
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popt, pcov = scipy.optimize.curve_fit(sig, X, y)
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regressions.append((popt.flatten().tolist(), None))
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coeffs = popt.flatten().tolist()
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regressions.append(str(coeffs[0]) + "*tanh(" + str(coeffs[1]) + "*(x+" + str(coeffs[2]) + "))+" + str(coeffs[3]))
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except Exception as e:
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162
analysis-master/analysis/equation.ipynb
Normal file
162
analysis-master/analysis/equation.ipynb
Normal file
@ -0,0 +1,162 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import re\n",
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"from decimal import Decimal\n",
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"from functools import reduce"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"def add(string):\n",
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" while(len(re.findall(\"[+]{1}[-]?\", string)) != 0):\n",
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" string = re.sub(\"[-]?\\d+[.]?\\d*[+]{1}[-]?\\d+[.]?\\d*\", str(\"%f\" % reduce((lambda x, y: x + y), [Decimal(i) for i in re.split(\"[+]{1}\", re.search(\"[-]?\\d+[.]?\\d*[+]{1}[-]?\\d+[.]?\\d*\", string).group())])), string, 1)\n",
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" return string"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"def sub(string):\n",
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" while(len(re.findall(\"\\d+[.]?\\d*[-]{1,2}\\d+[.]?\\d*\", string)) != 0):\n",
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" g = re.search(\"\\d+[.]?\\d*[-]{1,2}\\d+[.]?\\d*\", string).group()\n",
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" if(re.search(\"[-]{1,2}\", g).group() == \"-\"):\n",
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" r = re.sub(\"[-]{1}\", \"+-\", g, 1)\n",
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" string = re.sub(g, r, string, 1)\n",
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" elif(re.search(\"[-]{1,2}\", g).group() == \"--\"):\n",
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" r = re.sub(\"[-]{2}\", \"+\", g, 1)\n",
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" string = re.sub(g, r, string, 1)\n",
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" else:\n",
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" pass\n",
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" return string"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"def mul(string):\n",
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" while(len(re.findall(\"[*]{1}[-]?\", string)) != 0):\n",
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" string = re.sub(\"[-]?\\d+[.]?\\d*[*]{1}[-]?\\d+[.]?\\d*\", str(\"%f\" % reduce((lambda x, y: x * y), [Decimal(i) for i in re.split(\"[*]{1}\", re.search(\"[-]?\\d+[.]?\\d*[*]{1}[-]?\\d+[.]?\\d*\", string).group())])), string, 1)\n",
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" return string"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"def div(string):\n",
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" while(len(re.findall(\"[/]{1}[-]?\", string)) != 0):\n",
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" string = re.sub(\"[-]?\\d+[.]?\\d*[/]{1}[-]?\\d+[.]?\\d*\", str(\"%f\" % reduce((lambda x, y: x / y), [Decimal(i) for i in re.split(\"[/]{1}\", re.search(\"[-]?\\d+[.]?\\d*[/]{1}[-]?\\d+[.]?\\d*\", string).group())])), string, 1)\n",
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" return string"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"def exp(string):\n",
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" while(len(re.findall(\"[\\^]{1}[-]?\", string)) != 0):\n",
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" string = re.sub(\"[-]?\\d+[.]?\\d*[\\^]{1}[-]?\\d+[.]?\\d*\", str(\"%f\" % reduce((lambda x, y: x ** y), [Decimal(i) for i in re.split(\"[\\^]{1}\", re.search(\"[-]?\\d+[.]?\\d*[\\^]{1}[-]?\\d+[.]?\\d*\", string).group())])), string, 1)\n",
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" return string"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"def evaluate(string):\n",
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" string = exp(string)\n",
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" string = div(string)\n",
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" string = mul(string)\n",
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" string = sub(string)\n",
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" print(string)\n",
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" string = add(string)\n",
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" return string"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"output_type": "error",
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"ename": "SyntaxError",
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"evalue": "unexpected EOF while parsing (<ipython-input-13-f9fb4aededd9>, line 1)",
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"traceback": [
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"\u001b[1;36m File \u001b[1;32m\"<ipython-input-13-f9fb4aededd9>\"\u001b[1;36m, line \u001b[1;32m1\u001b[0m\n\u001b[1;33m def parentheses(string):\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m unexpected EOF while parsing\n"
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]
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}
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],
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"source": [
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"def parentheses(string):"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": "-158456325028528675187087900672.000000+0.8\n"
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},
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": "'-158456325028528675187087900672.000000'"
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},
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"metadata": {},
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"execution_count": 22
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}
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],
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"source": [
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"string = \"8^32*4/-2+0.8\"\n",
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"evaluate(string)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6-final"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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