def relation(interval_or_relation, var=x):
"""Return LaTeX that represents an interval or a relation as a chained inequality.
e.g. [1, 5] --> 1 < x < 5
"""
if isinstance(interval_or_relation, (sympy.StrictLessThan, sympy.LessThan, sympy.StrictGreaterThan, sympy.GreaterThan)):
interval = functions.relation_to_interval(interval_or_relation)
else:
interval = interval_or_relation
if isinstance(interval_or_relation, sympy.Union):
raise NotImplementedError('unions are not yet supported')
if interval.left == -sympy.oo and interval.right == sympy.oo:
return r'{0} < {1} < {2}'.format(sympy.latex(-sympy.oo), sympy.latex(var), sympy.latex(sympy.oo))
elif interval.left == -sympy.oo:
operator = r'<' if interval.right_open else r'\le'
return r'{0} {1} {2}'.format(sympy.latex(var), operator, sympy.latex(interval.right))
elif interval.right == sympy.oo:
operator = r'>' if interval.left_open else r'\ge'
return r'{0} {1} {2}'.format(sympy.latex(var), operator, sympy.latex(interval.left))
else:
left_operator = r'<' if interval.left_open else r'\le'
right_operator = r'<' if interval.right_open else r'\le'
return r'{0} {1} {2} {3} {4}'.format(
sympy.latex(interval.left),
left_operator,
sympy.latex(var),
right_operator,
sympy.latex(interval.right)
)
def print_latex():
# edo_main()
for i in range(1, 7):
Respostas[i] = sympy.nsimplify(Respostas[i], rational=True, tolerance=0.05).evalf(prec)
# 0- Raizes; 1- Forma Natural da respsota; 2- Resposta Natural;
# 3- Resposta Particular; 4- Resposta Transitoria; 5- Respsota Forcada
# 6- Resposta Completa; 7-Sinal de entrada x(t); 8 - eq
###
eqDiferencialEntradaLatex = latex(Respostas[8])
##Perfumaria
dif = 0.9 - 0.77
xdif = -0.15
font = {"family": "Sans", "weight": "normal", "size": 18}
plt.rc("font", **font)
##Obtendo as respostas em Latex
RespostasEmLatex = [0] * (len(Respostas))
raizEmLatex = [0] * (len(Respostas[0]))
str_raizLatex = ""
for i in range(len(Respostas[0])):
raizEmLatex[i] = "$" + str(latex(Respostas[0][i])) + "$"
for i in range(len(raizEmLatex)):
rn = "r" + str(i + 1) + " = "
rn = "$" + str(latex(rn)) + "$"
str_raizLatex = str_raizLatex + "\t" + rn + raizEmLatex[i]
##print len(RespostasEmLatex)
for i in range(len(Respostas)):
RespostasEmLatex[i] = "$" + str(latex(Respostas[i])) + "$"
# print RespostasEmLatex
# xTLatex = '$' + latex(xT) +'$'
###Preparando para imprimir
log_figure = plt.figure("Representacao", facecolor="white")
ax1 = plt.axes(frameon=False)
ax1.get_xaxis().tick_bottom()
ax1.get_xaxis().set_visible(False)
ax1.axes.get_yaxis().set_visible(False)
for i in range(0, 8, 1):
plt.axhline(0.86 - dif * i, xmin=-5, xmax=5, color="black", lw=0.2, linestyle=":")
# log_figure.figure("Forma_Representativa:")
plt.title("")
plt.text(xdif, 0.89, "Eq dif: 0=" + ur"$" + eqDiferencialEntradaLatex + "$")
plt.text(xdif, 0.89 - dif, "Forma Natural:" + ur"" + RespostasEmLatex[1])
plt.text(xdif, 0.9 - 2 * dif, "yn(t) = " + ur"" + RespostasEmLatex[2])
plt.text(xdif, 0.9 - 3 * dif, "ypar(t) = " + ur"" + RespostasEmLatex[3])
plt.text(xdif, 0.9 - 4 * dif, "ytran(t) = " + ur"" + RespostasEmLatex[4])
plt.text(xdif, 0.9 - 5 * dif, "yfor(t) = " + ur"" + RespostasEmLatex[5])
plt.text(xdif, 0.9 - 6 * dif, "yc(t) = " + ur"" + RespostasEmLatex[6])
plt.text(xdif, 0.9 - 7 * dif, "x(t) = " + ur"" + RespostasEmLatex[7])
plt.text(xdif, 0.9 - 8 * dif, "Raiz(es): " + ur"" + str_raizLatex)
plt.subplots_adjust(left=0.11, bottom=0.08, right=0.50, top=0.88, wspace=0.22, hspace=0.21)
##log_figure.set_size_inches(19.2,10.8)
# log_figure.show()
plt.show()
return log_figure
def formula(quantity):
""" returns error formula of quantity as latex code
Args:
quantity: Quantity object
Return:
latex code string of error formula
"""
assert isinstance(quantity, Quantity)
if quantity.error_formula is None:
raise ValueError("quantity '%s' doesn't have an error formula." % quantity.name)
formula = quantity.error_formula
if isinstance(formula,str):
return formula
else:
# replace "_err" by sigma function
sigma = Function("\sigma")
for var in formula.free_symbols:
if var.name[-4:] == "_err":
formula = formula.subs(var, sigma( Symbol(var.name[:-4], **var._assumptions)))
latex_code = latex(sigma(quantity)) + " = " + latex(formula)
form_button, form_code = pytex.hide_div('Formula', '$%s$' % (latex_code) , hide = False)
latex_button, latex_code = pytex.hide_div('LaTex', latex_code)
res = 'Error Formula for %s<div width=20px/>%s%s<hr/>%s<br>%s' % (
'$%s$' % latex(quantity), form_button, latex_button, form_code, latex_code)
return render_latex(res)
def baseparms_pretty_latex(delta,Pb,Pd,Kd):
base_latex = []
delta_b = Pb.T * delta
delta_d = Pd.T * delta
n_b = len(delta_b)
n_d = len(delta_d)
for i in range(n_b):
_latex = latex( delta_b[i] )
l = []
for j in range(n_d):
c = Kd[i,j]
if c == -1 or c == 1:
_latex += ' ' + ('+ ' if c > 0 else'') + latex( c * delta_d[j] )
elif c != 0 and j not in l:
ll = []
for jj in range(j,n_d):
cc = Kd[i,jj]
if cc == c:
l.append(jj)
ll.append(delta_d[jj])
p = (' \, ( ',' ) ') if (len(ll) > 1) else (' \, ','')
ll_sum = ' + '.join( [ latex( lli ) for lli in ll] )
_latex += ' ' + ('+ ' if c > 0 else'') + latex( c.n() ) + p[0] + ll_sum + p[1]
base_latex.append(_latex)
return base_latex;
def formula(self, quantity, adjust=True):
""" returns error formula of quantity as latex code
Args:
quantity: name of quantity or Quantity object
adjust: if True, replaces "_err" suffix by "\sigma" function and adds equals sign in front
Return:
latex code string of error formula
"""
quantity = quantities.parse_expr(quantity, self.data)
assert isinstance(quantity, quantities.Quantity)
if quantity.error_formula is None:
raise ValueError("quantity '%s' doesn't have an error formula.")
formula = quantity.error_formula
if isinstance(formula,str):
return formula
else:
# replace "_err" by sigma function
if adjust:
sigma = Function("\sigma")
for var in formula.free_symbols:
if var.name[-4:] == "_err":
formula = formula.subs(var, sigma( Symbol(var.name[:-4], **var._assumptions)))
return latex(sigma(quantity)) + " = " + latex(formula)
return formula
def table_groesse(expr,variables,container,name,formula=False,einheit="default"):
(X,expr,Sexpr)=eval_expr(expr,variables,container,name)
if einheit!="default":
X.convert_einheit(einheit)
x=ur"\bigskip"
if formula==True:
x+=ur"\begin{equation*} "+name+" = "+sy.latex(expr)+"\end{equation*}"
x+=ur"\begin{equation*} S"+name+" = "+sy.latex(Sexpr)+"\end{equation*}"
s=ur""
s2=ur""
if X.x.dimensionality.string != "dimensionless":
x+=ur"S"+name+" = "+sy.latex(Sexpr)+ur"\\"
s=ur""
s2=ur""
if X.x.dimensionality.string != "dimensionless":
s+=name+" in "+str(X.x.dimensionality.string)
else:
s+=name
for k in X.x.magnitude:
s+="& %.3f " % k
s2+="r|"
s+=ur"\\ \hline "
if X.Sx.dimensionality.string!= "dimensionless":
s+="S"+name+" in "+str(X.Sx.dimensionality.string)
else:
s+="S"+name
for k in X.Sx.magnitude:
s+="& %.3f " % k
s+=ur"\\ \hline"
x+=ur"""\normalsize \vspace{3 mm}
\begin{tabular}{| l | """+s2+"""}
\hline
"""+s+ur"""
\end{tabular} \\ \bigskip """
return x
def arc_length_explain(self, start, stop, a_type = None,
explanation_type=None, preview = None):
if a_type is None:
a_type = self.a_type
v = self.v_
u = self.u
start = sym.sympify(start)
stop = sym.sympify(stop)
if explanation_type is None:
explanation_type = self.kwargs.get('explanation_type', 'simple')
if preview is None:
preview = self.kwargs.get('preview', False)
explanation = ArcLengthProb(path='arc_length/explanation',
a_type = a_type,
explanation_type = explanation_type,
preview = preview).explain()
explanation += """
<p>
For this problem the curve is $_C$_ is given by $_%s$_
with the independent variable being $_%s$_ on the interval
$_[%s,%s]$_. So the arc length is
$$s =\\int_{%s}^{%s} \sqrt{1+\\left(\\frac{d%s}{d%s}\\right)^2}\,d%s$$
$$\\frac{d%s}{d%s} = %s = %s$$
\\begin{align}
\\sqrt{1 + \\left(%s\\right)^2} &= \\sqrt{%s} \\\\
&= \sqrt{\\left(%s\\right)^2} = %s
\\end{align}
</p>
"""%tuple(map(lambda x: sym.latex(x).replace("\\log","\\ln"),
[sym.Eq(v, self.v), u, start, stop, start, stop,
v, u, u, v, u,
self.Dv, self.dv, self.dv, 1 + (self.dv**2).expand(),
self.ds, self.ds]))
aa = [sym.latex(self.arc_length(start, stop,'integral')),
"\\left." + sym.latex(self.Ids).replace('\\log', '\\ln') +
"\\right|_{%s=%s}^{%s=%s}"%(u, start, u, stop),
sym.latex(self.arc_length(start, stop,'exact')).replace("\\log", "\\ln") +
'\\approx %.3f'%(self.arc_length(start, stop,'numeric'))]
# Add self.numeric / self.anti
explanation += """
<p>
Thus the arclength is given by
%s
</p>
"""%(tools.align(*aa))
#
return explanation
def simplex_table_to_tex_table_only(table):
ret = """\\begin{tabular}{|c|"""
ret += ("c|"*(table.amount_of_vars + 1))
ret += "} \\hline"
ret += " & \\T \\B $ "
for j in range(table.amount_of_vars):
ret += "$&$"
ret += "x_{"+"{0:<2}".format(j) +"}"
ret += "$\\\\ \\hline "
for i in range(table.amount_of_equations):
ret += "$x_{" + "{0:<2}".format(table.basis[i]) + "}$"
ret += "& \\T \\B $ "
ret += latex(table.free[i])
for j in range(table.amount_of_vars):
ret += "$&$"
ret += latex(table.limits[i][j])
ret += "$\\\\ \\hline "
ret += "$\Psi$ & $"
ret += latex(table.target_free)
for j in range(table.amount_of_vars):
ret += "$&\\T \\B$"
ret += latex(table.target[j])
ret += "$\\\\ \\hline "
ret += """\\end{tabular}"""
return ret
def print_latex():
# 0- Raizes; 1- Forma Natural da respsota; 2- Resposta Natural;
# 3- Resposta Particular; 4- Resposta Transitoria; 5- Respsota Forcada
# 6- Resposta Completa
# 7-Sinal de entrada x(t)
##Perfumaria
dif = 0.9 -0.75
xdif = -0.15
font = {'family' : 'Arial',
'weight' : 'normal',
'size' : 18}
plt.rc('font', **font)
#plt.rc('text', usetex=True)
##Obtendo as respostas em Latex
RespostasEmLatex = [0]*(len(Respostas))
#print len(RespostasEmLatex)
for i in range(len(Respostas)):RespostasEmLatex[i] = '$'+str(latex(Respostas[i])) +'$'
## Tratamento Inicial para as raizes:
#replace(a, old, new[, count])
#r'$\left( \begin{array}{ll} 2 & 3 \\ 4 & 5 \end{array} \right)$'
#$\begin{bmatrix}-1.5, & 1.0\end{bmatrix}$
#\begin{Bmatrix} x & y \\ z & v \end{Bmatrix}
#print RespostasEmLatex[0]
#RespostasEmLatex[0]= RespostasEmLatex[0].replace("bmatrix","Bmatrix")
#RespostasEmLatex[0]= RespostasEmLatex[0].replace("}$","})$",1)
#print RespostasEmLatex[0]
####
#print RespostasEmLatex
xTLatex = '$' + latex(xT) +'$'
###Preparando para imprimir
log_figure = plt.figure("Representacao",facecolor='white')
ax1 = plt.axes(frameon = False)
ax1.get_xaxis().tick_bottom()
ax1.get_xaxis().set_visible(False)
ax1.axes.get_yaxis().set_visible(False)
for i in range(0,7,1):plt.axhline(dif*i,xmin = -5,xmax = 5, color = 'black',lw =1.5, linestyle = ':')
#log_figure.figure("Forma_Representativa:")
plt.title('')
#print RespostasEmLatex[0]
#plt.text(xdif,0.05,'Raizes:'+str(Respostas[0]))
plt.text(xdif,0.9,'Forma Natural:'+ur''+RespostasEmLatex[1])
plt.text(xdif,0.9-dif,'yn(t) = '+ur''+RespostasEmLatex[2])
plt.text(xdif,0.9-2*dif,'ypar(t) = '+ur''+RespostasEmLatex[3])
plt.text(xdif,0.9-3*dif,'ytran(t) = '+ur''+RespostasEmLatex[4])
plt.text(xdif,0.9-4*dif,'yfor(t) = '+ur''+RespostasEmLatex[5])
plt.text(xdif,0.9-5*dif,'yc(t) = '+ur''+RespostasEmLatex[6])
plt.text(xdif,0.9-6*dif,'x(t) = '+ur''+xTLatex)
log_figure.show()
def visit_Call(self, node):
buffer = []
fname = node.func.id
# Only apply to lowercase names (i.e. functions, not classes)
if fname in self.__class__.EXCEPTIONS:
node.func.id = self.__class__.EXCEPTIONS[fname].__name__
self.latex = sympy.latex(self.evaluator.eval_node(node))
else:
result = self.format(fname, node)
if result:
self.latex = result
elif fname[0].islower() and fname not in OTHER_SYMPY_FUNCTIONS:
buffer.append("\\mathrm{%s}" % fname.replace('_', '\\_'))
buffer.append('(')
latexes = []
for arg in node.args:
if isinstance(arg, ast.Call) and arg.func.id[0].lower() == arg.func.id[0]:
latexes.append(self.visit_Call(arg))
else:
latexes.append(sympy.latex(self.evaluator.eval_node(arg)))
buffer.append(', '.join(latexes))
buffer.append(')')
self.latex = ''.join(buffer)
else:
self.latex = sympy.latex(self.evaluator.eval_node(node))
return self.latex
def solution_statement(self):
lines = solutions.Lines()
derivative = self._qp['equation'].diff()
lines += r'''$y = {equation}, y' = {derivative}$'''.format(
equation=sympy.latex(self._qp['equation']),
derivative=sympy.latex(derivative)
)
original_y_coordinate = self._qp['equation'].subs({x: self._qp['location']})
lines += r'$y({original_x_coordinate}) = {original_y_coordinate}$'.format(
original_x_coordinate=self._qp['location'],
original_y_coordinate=original_y_coordinate
)
derivative_at_original_location = derivative.subs({x: self._qp['location']})
lines += r'''$y'({original_x_coordinate}) = {derivative_at_original_location}$'''.format(
original_x_coordinate=self._qp['location'],
derivative_at_original_location=sympy.latex(derivative_at_original_location)
)
unevaluated_approximation_of_answer = noevals.noevalAdd(original_y_coordinate, noevals.noevalMul(self._qp['delta'], derivative_at_original_location))
answer = original_y_coordinate + self._qp['delta'] * derivative_at_original_location
lines += r'$\therefore y({new_x_coordinate}) \approx {unevaluated_approximation_of_answer} = {answer}$'.format(
new_x_coordinate=self._qp['new_location'],
unevaluated_approximation_of_answer=noevals.latex(unevaluated_approximation_of_answer),
answer=sympy.latex(answer)
)
return lines.write()
def solution_statement(self):
lines = solutions.Lines()
second_derivative = self._qp['equation'].diff().diff()
second_derivative_leibniz_form = r'{derivative}({location})'.format(
derivative=expressions.derivative(upper_variable="x", lower_variable="y", degree=2),
location=self._qp['location']
)
second_derivative_at_original_location = second_derivative.subs({x: self._qp['location']})
lines += r'''The function is {concave_or_convex} at $x = {location}$ since the second derivative
${second_derivative_leibniz_form} = {second_derivative_at_original_location}$ is {greater_than_or_less_than} than $0$.'''.format(
concave_or_convex=self._qp['concave_or_convex'],
location=self._qp['location'],
second_derivative_leibniz_form=second_derivative_leibniz_form,
second_derivative_at_original_location=sympy.latex(second_derivative_at_original_location),
greater_than_or_less_than='greater than' if second_derivative_at_original_location > 0 else 'less than'
)
lines += r'''Therefore, the gradient of ${equation}$ {increases_or_decreases} as $x$ moves from ${location}$ to ${new_location}$
and as a result, linear approximation {under_or_over}estimates the true value of ${unevaluated_f_of_new_location}$'''.format(
equation=sympy.latex(self._qp['equation']),
increases_or_decreases='increases' if second_derivative_at_original_location > 0 else 'decreases',
location=self._qp['location'],
new_location=self._qp['new_location'],
under_or_over='under' if self._qp['concave_or_convex'] else 'over',
unevaluated_f_of_new_location=sympy.latex(self._qi['noeval_equation'].subs({x: self._qp['new_location']}))
)
return lines.write()
def solution_statement(self):
lines = solutions.Lines()
if self._qp['question_type'] == 'one_x':
answer = self._qp['prob_table'][self._qp['x_value']] ** self._qp['n_days']
lines += r'$Pr(X = {x_value}$, {n_days} days in a row$) = {probability_of_x}^{n_days} = {answer}.$'.format(
x_value=self._qp['x_value'],
n_days=self._qp['n_days'],
probability_of_x=sympy.latex(self._qp['prob_table'][self._qp['x_value']]),
answer=sympy.latex(answer)
)
elif self._qp['question_type'] == 'any_x':
sum_of_probabilities = ' + '.join([r'''Pr(X = {0})^{1}'''.format(k, self._qp['n_days']) for k in self._qp['prob_table']])
lines += r'''$Pr(X$ is the same number {n_days} days in a row$) = {sum_of_probabilities}$'''.format(
n_days=self._qp['n_days'],
sum_of_probabilities=sum_of_probabilities
)
sum_of_probabilities = ' + '.join(['({0})^{1}'.format(sympy.latex(v), self._qp['n_days']) for v in self._qp['prob_table'].values()])
answer = sum(v ** self._qp['n_days'] for v in self._qp['prob_table'].values())
lines += r'''$= {sum_of_probabilities} = {answer}$'''.format(
sum_of_probabilities=sum_of_probabilities,
answer=sympy.latex(answer)
)
return lines.write()
def prob1_25(part=1):
cs = CartesianCS
x, y, z = sym.symbols('x, y, z')
A = sym.Matrix([cs.x, 2*cs.y, 3*cs.z])
B = sym.Matrix([3 * cs.y, -2 * cs.x, 0])
print('\\item \\curl{A} = $%s$' % my_xyzvec(cs.curl(A)))
print('\\item \\curl{B} = $%s$' % my_xyzvec(cs.curl(B)))
print('\\item \\diver{A} = $%s$' % sym.latex(cs.div(A)))
print('\\item \\diver{B} = $%s$' % sym.latex(cs.div(B)))
if part == 1:
lhs = cs.div(A.cross(B))
print('lhs = %s' % sym.latex(lhs))
t1 = B.dot(cs.curl(A))
print('B dot (curl(A): %s' %sym.latex(t1))
t2 = A.dot(cs.curl(B))
print('A dot (curl(B): %s' % sym.latex(t2))
rhs = t1 - t2
print('B dot curl(A) - A dot curl(B): %s' % sym.latex(rhs))
if part == 2:
lhs = cs.grad(A.dot(B))
print('lhs = %s' % sym.latex(lhs))
t1 = B.dot(cs.curl(A))
print('B dot (curl(A): %s' %sym.latex(t1))
t2 = A.dot(cs.curl(B))
print('A dot (curl(B): %s' % sym.latex(t2))
rhs = t1 - t2
print('B dot curl(A) - A dot curl(B): %s' % sym.latex(rhs))
def __str__(self):
s = ""
xi = [r'\vec i', r'\vec j', r'\vec k']
phi = r"\phi(\vec r)"
for key in sorted(self.stateMap.keys()):
s += self.beginTable()
qNums = str(self.stateMap[key]).strip("]").strip("[")
genericFactor = self.genericFactor(self.stateMap[key])
s += "$\phi_{%d} \\rightarrow \phi_{%s}$\\\\\n" % (key, qNums)
s += "\hline\n"
s += "$%s$ & $%s$\\\\\n" % (phi, latex(self.orbitals[key]/genericFactor))
s += "\hline\n"
for i in range(self.dim):
s+= "$%s\cdot \\nabla %s$ & $%s$\\\\\n" % \
(xi[i], phi, latex(self.gradients[key][i]/genericFactor))
s += "\hline\n"
s += "$\\nabla^2 %s$ & $%s$\\\\\n" % (phi, latex(self.Laplacians[key]/genericFactor))
s += self.endTable(caption="Orbital expressions %s : %s. Factor $%s$ is omitted." % \
(self.__class__.__name__, qNums, latex(genericFactor)))
if (key+1)%self.figsPrPage == 0:
s += "\\clearpage\n"
return s
def simplex_table_to_tex_solution_only(table):
solution = ''
var, target = table.solution
for i in range(table.amount_of_vars):
solution += "$x_{" + "{0:<2}".format(i) + "} = " + latex(var[i]) + '$\\\\'
solution += '$\Psi = ' + latex(target) + '$'
return solution
def print_latex():
# 0- Raizes; 1- Forma Natural da respsota; 2- Resposta Natural;
# 3- Resposta Particular; 4- Resposta Transitoria; 5- Respsota Forcada
# 6- Resposta Completa
# 7-Sinal de entrada x(t)
dif = 0.9 -0.75
fontSize = 18
##Obtendo as respostas em Latex
RespostasEmLatex = [0]*(len(Respostas))
print len(RespostasEmLatex)
for i in range(len(Respostas)):RespostasEmLatex[i] = '$'+str(latex(Respostas[i])) +'$'
#print RespostasEmLatex
xTLatex = '$' + latex(xT) +'$'
###Preparando para imprimir
log_figure = plt.figure('Latex Representation')
plt.title('Respostas na forma representativa',fontsize = fontSize)
plt.text(0.001,0.9,'Forma Natural:'+ur''+RespostasEmLatex[1],fontsize = fontSize)
plt.text(0.001,0.9-dif,'yn(t) = '+ur''+RespostasEmLatex[2],fontsize = fontSize)
plt.text(0.001,0.9-2*dif,'ypar(t) = '+ur''+RespostasEmLatex[3],fontsize = fontSize)
plt.text(0.001,0.9-3*dif,'ytran(t) = '+ur''+RespostasEmLatex[4],fontsize = fontSize)
plt.text(0.001,0.9-4*dif,'yfor(t) = '+ur''+RespostasEmLatex[5],fontsize = fontSize)
plt.text(0.001,0.9-5*dif,'yc(t) = '+ur''+RespostasEmLatex[6],fontsize = fontSize)
plt.text(0.001,0.9-6*dif,'x(t) = '+ur''+xTLatex,fontsize = fontSize)
log_figure.show()
def problem_to_str(obj, gs = None, hs = None, plain = True):
strret = ''
gpresent = gs is not None and len(gs)>0
hpresent = hs is not None and len(hs)>0
if not plain:
strret += 'Minimizing '
strret += '$\mathcal{L}(%s)$' % sp.latex(obj)
if gpresent or hpresent:
strret += ('\n\nsubject to \t')
if gpresent:
for g in gs:
strret += ' $%s$, \t' % sp.latex(g)
strret += '\n'
if hpresent:
for h in hs:
strret += '$\mathcal{L}(%s) = 0$, \t' % sp.latex(h)
strret = strret.strip(',')
else:
strret += '\t subject to no constraints'
else:
strret += 'Minimizing '
strret += ' L(%s) ' % str(obj)
if gpresent or hpresent:
strret += ('\nsubject to \t')
if gpresent:
for g in gs:
strret += ' %s, \t' % str(g)
strret += '\n'
if hpresent:
for h in hs:
strret += '$L(%s) = 0$, \t' % str(h)
strret = strret.strip(',')
else:
strret += '\t subject to no constraints'
return strret
def do_it(j_foo, s0, _s0, s1, _s1, is_swap, is_map, zones_amount):
s0_max, s0_min = process_maxmin(_s0)
s1_max, s1_min = process_maxmin(_s1)
j_foo = j_foo.replace(str(s0), 'x')
j_foo = j_foo.replace(str(s1), 'y')
j_foo = j_foo.replace('L', '')
zone_pl = ''
is_zone = False
if zones_amount != None:
is_zone = True
zone_pl += "set pal maxcolors 4; set pm3d corners2color c1; unset colorbox;"
map_pl = 'set pm3d\n'
if is_map: map_pl += 'set pm3d map\n'
for (x, y) in [(0, 0), (0, 1), (1, 0), (1, 1)]:
file_mod = list()
if is_map: file_mod.append('map')
if is_zone: file_mod.append('zone')
if is_swap: file_mod.append('swap')
if x: file_mod.append('rx')
if y: file_mod.append('ry')
s0_rev, s0_max, s0_min = process_reverse(x, s0_max, s0_min)
s1_rev, s1_max, s1_min = process_reverse(y, s1_max, s1_min)
gr3d = gnu_rend()
gr3d.put_some(plot_tpl % (latex(s0), s0_min, s0_max, s0_rev, latex(s1), s1_min, s1_max, s1_rev,
map_pl, zone_pl, j_foo) )
gr3d.compile( report_plot_file_name % ( (len(file_mod) and "_" or "") + "_".join(file_mod) ) )
def print_latex_new():
##Obtendo as respostas em Latex
RespostasEmLatex = [0]*(len(Respostas))
raizEmLatex = [0]*(len(Respostas[0]))
str_raizLatex =""
for i in range(len(Respostas[0])):
raizEmLatex[i] = '$'+str(latex(Respostas[0][i])) +'$'
for i in range(len(raizEmLatex)):
rn = "r"+str(i+1)+" = "
rn = '$'+str(latex(rn)) +'$'
str_raizLatex = str_raizLatex+"\t"+rn+raizEmLatex[i]
##print len(RespostasEmLatex)
for i in range(len(Respostas)):
RespostasEmLatex[i] = '$'+str(latex(Respostas[i])) +'$'
#print RespostasEmLatex
#xTLatex = '$' + latex(xT) +'$'
###Preparando para imprimir
dif = 0.9 -0.77
xdif = -0.15
font = {'family' : 'Sans',
'weight' : 'normal',
'size' : 18}
figure_latex = Figure(facecolor = 'white')
plot_latex = figure_latex.add_subplot(111)
#plot_latex.rc('font',**font)
#axes_latex = plot_latex.axes(frameon = False)
#axes_latex.get_xaxis().tick_bottom()
#axes_latex.get_xaxis().set_visible(False)
#axes_latex.axes.get_yaxis().set_visible(False)
plot_latex.plot(arange(0.0,50.0,1.2))
plot_latex.canvas.draw()
def solution_statement(self):
lines = solutions.Lines()
ball_combinations = itertools.combinations(self._qp['items'], self._qp['n_selections'])
valid_total_sum_combinations = [i for i in ball_combinations if sum(i) == self._qp['sum']]
# e.g. Pr(sum = 14) = 3! * Pr(ball1 = 3 and ball2 = 5 and ball3 = 6)
lines += r'$Pr(\text{{sum}} = {sum}) = {sum_of_probabilities}$'.format(
sum=self._qp['sum'],
sum_of_probabilities=expressions.sum_combination_probabilities(valid_total_sum_combinations)
)
probability_of_a_single_combination = self.single_combination_probability()
prob_instance = r'{n_valid_permutations} \times {probability_of_a_single_combination}'.format(
n_valid_permutations=math.factorial(self._qp['n_selections']),
probability_of_a_single_combination=sympy.latex(probability_of_a_single_combination)
)
# e.g. = 6 * (1/120) + 6 * (1/120)
lines += r'$= {probabilities_sum}$'.format(
probabilities_sum=' + '.join([prob_instance] * len(valid_total_sum_combinations))
)
answer = probability_of_a_single_combination * math.factorial(self._qp['n_selections']) * len(valid_total_sum_combinations)
# e.g. = 1/20
lines += r'$= {answer}$'.format(answer=sympy.latex(answer))
return lines.write()
def print_model(model, print_residuals=True):
from sympy import latex
if print_residuals:
from dolo.symbolic.model import compute_residuals
res = compute_residuals(model)
if len(model.equations_groups) > 0:
if print_residuals:
eqs = [["", "Equations", "Residuals"]]
else:
eqs = [["", "Equations"]]
for groupname in model.equations_groups:
eqg = model.equations_groups
eqs.append([groupname, ""])
if print_residuals:
eqs.extend(
[["", "${}$".format(latex(eq)), str(res[groupname][i])] for i, eq in enumerate(eqg[groupname])]
)
else:
eqs.extend([["", "${}$".format(latex(eq))] for eq in eqg[groupname]])
txt = print_table(eqs, header=True)
return txt
else:
if print_residuals:
table = [(i + 1, "${}$".format(latex(eq)), str(res[i])) for i, eq in enumerate(model.equations)]
else:
table = [(i + 1, "${}$".format(latex(eq))) for i, eq in enumerate(model.equations)]
txt = print_table([["", "Equations"]] + table, header=True)
return txt
def _latex(self, *args):
equations = []
t = sympy.Symbol('t')
for eq in self._equations.itervalues():
# do not use SingleEquations._latex here as we want nice alignment
varname = sympy.Symbol(eq.varname)
if eq.type == DIFFERENTIAL_EQUATION:
lhs = sympy.Derivative(varname, t)
else:
# Normal equation or parameter
lhs = varname
if not eq.type == PARAMETER:
rhs = eq.expr.sympy_expr
if len(eq.flags):
flag_str = ', flags: ' + ', '.join(eq.flags)
else:
flag_str = ''
if eq.type == PARAMETER:
eq_latex = r'%s &&& \text{(unit: $%s$%s)}' % (sympy.latex(lhs),
sympy.latex(eq.unit),
flag_str)
else:
eq_latex = r'%s &= %s && \text{(unit: $%s$%s)}' % (sympy.latex(lhs),
sympy.latex(rhs),
sympy.latex(eq.unit),
flag_str)
equations.append(eq_latex)
return r'\begin{align}' + r'\\'.join(equations) + r'\end{align}'
def substitute(expr, var, value):
latex = sympy.latex(expr)
print(latex)
latex = latex.replace(sympy.latex(var), sympy.latex(value))
return latex
def print_latex():
for i in range(1,7):Respostas[i] = sympy.nsimplify(Respostas[i].evalf(prec), rational = True,tolerance = 0.05)
# 0- Raizes; 1- Forma Natural da respsota; 2- Resposta Natural;
# 3- Resposta Particular; 4- Resposta Transitoria; 5- Respsota Forcada
# 6- Resposta Completa
# 7-Sinal de entrada x(t)
###
eqDiferencialEntradaLatex = latex(eq)
##Perfumaria
dif = 0.9 -0.77
xdif = -0.15
font = {'family' : 'Sans',
'weight' : 'normal',
'size' : 18}
plt.rc('font', **font)
##Obtendo as respostas em Latex
RespostasEmLatex = [0]*(len(Respostas))
raizEmLatex = [0]*(len(Respostas[0]))
str_raizLatex =""
for i in range(len(Respostas[0])):
raizEmLatex[i] = '$'+str(latex(Respostas[0][i])) +'$'
for i in range(len(raizEmLatex)):
rn = "r"+str(i+1)+" = "
rn = '$'+str(latex(rn)) +'$'
str_raizLatex = str_raizLatex+"\t"+rn+raizEmLatex[i]
##print len(RespostasEmLatex)
for i in range(len(Respostas)):
RespostasEmLatex[i] = '$'+str(latex(Respostas[i])) +'$'
#print RespostasEmLatex
xTLatex = '$' + latex(xT) +'$'
###Preparando para imprimir
log_figure = plt.figure("Representacao",facecolor='white')
ax1 = plt.axes(frameon = False)
ax1.get_xaxis().tick_bottom()
ax1.get_xaxis().set_visible(False)
ax1.axes.get_yaxis().set_visible(False)
for i in range(0,8,1):
plt.axhline(0.86-dif*i,xmin = -5,xmax = 5, color = 'black',lw =0.2, linestyle = ':')
#log_figure.figure("Forma_Representativa:")
plt.title("Eq dif: 0="+ur'$'+eqDiferencialEntradaLatex+'$', loc = 'left',fontsize = 15)
plt.text(xdif,0.89,'Forma Natural:'+ur''+RespostasEmLatex[1])
plt.text(xdif,0.9-dif,'yn(t) = '+ur''+RespostasEmLatex[2])
plt.text(xdif,0.9-2*dif,'ypar(t) = '+ur''+RespostasEmLatex[3])
plt.text(xdif,0.9-3*dif,'ytran(t) = '+ur''+RespostasEmLatex[4])
plt.text(xdif,0.9-4*dif,'yfor(t) = '+ur''+RespostasEmLatex[5])
plt.text(xdif,0.9-5*dif,'yc(t) = '+ur''+RespostasEmLatex[6])
plt.text(xdif,0.9-6*dif,'x(t) = '+ur''+xTLatex)
plt.text(xdif,0.9-7*dif,'Raiz(es): '+ur''+str_raizLatex)
##log_figure.set_size_inches(19.2,10.8)
#log_figure.show()
plt.show()
return log_figure
def question_statement(self):
return r'Find $Pr(X {minor_direction} {minor_bound} | X {major_direction} {major_bound})$.'.format(
minor_direction=self._qp['minor_direction'],
minor_bound=sympy.latex(self._qp['minor_bound']),
major_direction=self._qp['major_direction'],
major_bound=sympy.latex(self._qp['major_bound'])
)
def solution_statement(self):
lines = solutions.Lines()
if self._qp['question_type'] == 'mean':
lines += r'$E(X) = \sum\limits_{{i=1}}^{{n}} x_{{i}} \times Pr(X = x_{{i}})$'
lines += r'$= {expectation_of_x} = {answer}$'.format(
expectation_of_x=expressions.discrete_expectation_x(self._qp['prob_table']),
answer=self._qp['answer']
)
elif self._qp['question_type'] == 'variance':
lines += r'$Var(X) = E(X^2) - (E(X))^2$'
lines += r'$= [{expectation_of_x_squared}] - [{expectation_of_x}]^2$'.format(
expectation_of_x_squared=expressions.discrete_expectation_x_squared(self._qp['prob_table']),
expectation_of_x=expressions.discrete_expectation_x(self._qp['prob_table'])
)
expectation_of_x = prob_table.expectation_x(self._qp['prob_table'])
expectation_of_x_squared = prob_table.expectation_x(self._qp['prob_table'], power=2)
lines += r'$= {expectation_of_x_squared} - {expectation_of_x}^2 = {answer}$'.format(
expectation_of_x_squared=sympy.latex(expectation_of_x_squared),
expectation_of_x=sympy.latex(expectation_of_x),
answer=sympy.latex(self._qp['answer'])
)
elif self._qp['question_type'] == 'mode':
lines += r'${answer}$'.format(
answer=prob_table.mode(self._qp['prob_table'])
)
return lines.write()
def solution_statement(self):
lines = solutions.Lines()
integral, integral_intermediate, integral_intermediate_eval = \
expressions.integral_trifecta(expr=self._qp['equation'], lb=self._qi['domain'].left, ub=self._qi['domain'].right)
lines += r'$Pr(X {direction} {unknown}) = {integral}$'.format(
direction=self._qi['inequality'],
unknown=self._qi['unknown'],
integral=integral
)
lines += r'$= {0}$'.format(integral_intermediate)
lines += r'$= {integral_intermediate_eval} = {value}$'.format(
integral_intermediate_eval=integral_intermediate_eval,
value=sympy.latex(self._qi['value'])
)
if self._qp['direction'] == 'left':
left_side = self._qp['equation'].integrate().subs({x: self._qi['unknown']})
right_side = self._qi['value'] + self._qp['equation'].integrate().subs({x: self._qp['domain'].left})
else:
left_side = -1 * self._qp['equation'].integrate().subs({x: self._qi['unknown']})
right_side = self._qi['value'] - self._qp['equation'].integrate().subs({x: self._qp['domain'].right})
lines += r'${0} = {1}$'.format(sympy.latex(left_side), sympy.latex(right_side))
lines += expressions.shrink_solution_set(left_side, self._qp['domain'], expr_equal_to=right_side, var=self._qi['unknown'])
return lines.write()
def integrar(self,event):
x = sympy.Symbol("x")
fx = self.fun.GetValue() # Función original
fx = preproc(fx)
Fx = sympy.integrate(eval(fx)) # Función integrada
str_Fx = "$\int \, (%s) \,dx \,= \,%s + C$"%(sympy.latex(eval(fx)), sympy.latex(Fx))
self.string.set_text(str_Fx)
self.canvas.draw()
def derivar(self,event):
x = sympy.Symbol("x")
fx = self.fun.GetValue() # Función original
fx = preproc(fx)
Fx = sympy.diff(eval(fx)) # Función derivada
str_Fx = "$\\frac{d}{dx}(%s)\, = \,%s$"%(sympy.latex(eval(fx)), sympy.latex(Fx))
self.string.set_text(str_Fx)
self.canvas.draw() # "Redibujar"
def to_latex(self, comments=False):
COMP = {
'LEQ' : r"""\leq""",
'EQ' : r"""=""",
'GEQ' : r"""\geq""",
}
prefix = r"""
\[
\left\{
\begin{array}{"""
prefix += "cc"*(len(self.variables)+2) + "}"
suffix1 = r"""
\end{array}
\right.
\]
\["""
suffix2 = r"""\]"""
lines = [prefix]
if self.standard:
for constraint in self.constraints:
lines.append(constraint.std_latex_array(out_var=self.out))
# import pdb; pdb.set_trace()
utility_line = "z & = & "
utility = self.utility_constraint
if utility.get_scalar()[1] == 0:
skip = True
else:
skip = False
utility_line += sympy.latex(utility.get_scalar()[1])
for variable in self.variables:
var_coeff = utility.get_coeff(variable)[1]
substitution = utility.substitutions.get(variable, variable)
if var_coeff > 0:
if skip:
utility_line += " & & " + sympy.latex(sympy.Mul(var_coeff, substitution, evaluate=False))
skip = False
else:
utility_line += " & + & " + sympy.latex(sympy.Mul(var_coeff, substitution, evaluate=False))
elif var_coeff < 0:
utility_line += " & - & " + sympy.latex(sympy.Mul(-var_coeff, substitution, evaluate=False))
skip = False
lines.append(utility_line)
lines.append(suffix1)
else:
for constraint in self.constraints:
lines.append(constraint.latex_array())
lines.append(suffix1)
lines.append(self.optimizer + " z="+sympy.latex(self.utility))
lines.append(suffix2)
if self.current_solution:
lines.append(self.view_solution())
if comments:
return "\n".join([self.comments] + lines)
else:
return "\n".join(lines)
# argument
# register_size, gates, measurements, controlled_gates, circuit and
# input_register need to be in data
data = json.loads(sys.argv[1])
try:
# Initialize a new simulation using this data
sim = QuantumSimulation(data)
# Run the simulation
sim.simulate()
# Print out a JSONified version of the results
print pipes.quote(
json.dumps({
'results': sim.results,
'probabilities': sim.probabilities
}))
except InvalidMatrix, e:
# If some of the matrices weren't unitary when they were meant to be,
# or weren't hermitian when they were meant to be then return an
# error back to ruby
print pipes.quote(
json.dumps({
'error': {
'type': 'invalid_matrix',
'matrix': urllib.quote(latex(e.matrix)),
'size': e.matrix.rows,
'mtype': e.mtype
}
}))
def eq_solver(equation):
list_eq = []
for eq in equation:
string = ""
# left : 0 , right : 1
for i, side in enumerate(eq.split("=")):
if side[0] not in ["+", "-"]:
side = "+" + side
pos_sign = [i for i, char in enumerate(side) if char in ["+", "-"]]
pos_sign.append(len(side))
for j in range(len(pos_sign) - 1):
string += process_str(side[pos_sign[j]:pos_sign[j + 1]], i)
list_eq.append(string)
print(list_eq)
result = sympy.solve([parse_expr(i) for i in list_eq])
# print(result)
str_result = ""
if type(result) == dict:
for i, key in enumerate(result):
if i == 0:
if len(result) == 1:
str_result += "( {} = {} )".format(
sympy.latex(key), sympy.latex(result[key]))
else:
str_result += "( {} = {} ,".format(
sympy.latex(key), sympy.latex(result[key]))
elif i == len(result) - 1:
str_result += " {} = {} )".format(sympy.latex(key),
sympy.latex(result[key]))
else:
str_result += " {} = {} ,".format(sympy.latex(key),
sympy.latex(result[key]))
return [str_result]
else:
if len(result) == 0:
return ["PHƯƠNG TRÌNH VÔ NGHIỆM"]
list_result = []
for r in result:
str_result = ""
for i, key in enumerate(r):
if i == 0:
if len(r) == 1:
str_result += "( {} = {} )".format(
sympy.latex(key), sympy.latex(r[key]))
else:
str_result += "( {} = {} ,".format(
sympy.latex(key), sympy.latex(r[key]))
elif i == len(r) - 1:
str_result += " {} = {} )".format(sympy.latex(key),
sympy.latex(r[key]))
else:
str_result += " {} = {} ,".format(sympy.latex(key),
sympy.latex(r[key]))
# Replace "//" to "/"
list_result.append(str_result)
return list_result
plt.ylabel('Angle (rad)')
plt.grid()
plt.show()
# DETERMINE THE IMPULSE RESPONSE OF THE SYSTEM (kick)
# F(s) = 1, X1(s) = G_x, x1(t) = inv_lap(x1)
x1_t = sym.inverse_laplace_transform(G_x, s, t)
print(sym.latex(x1_t))
sym.pprint(G_x)
# unfortunately I seem to be getting a bad result here as it cannot be computed in the
# c.impulse_response()
# DETERMINE THE STEP RESPONSE OF THE SYSTEM (push)
x3_step_t = sym.inverse_laplace_transform(G_x/s, s, t)
sym.pprint(x3_step_t)
print(sym.latex(x3_step_t))
'''
# DETERMINE THE FREQUENCY RESPONSE OF THE SYSTEM (shake)
w = sym.symbols('w', real=True, positive=True)
x3_freq_t = sym.inverse_laplace_transform(G_x * w**2 / (s**2 + w**2), s, t)
sym.pprint(x3_freq_t.simplify())
print(sym.latex(x3_freq_t))
'''
t_imp, x3_imp = C.impulse_response(G_x)
plt.plot(t_imp, x3_imp)
plt.xlabel('Time (s)')
plt.ylabel('Angle (rad)')
plt.grid()
plt.show()
'''
def latex(self, prec=15, nested_scope=None):
"""Return the corresponding math mode latex string."""
# pylint: disable=unused-argument
# TODO prec ignored
return sympy.latex(self.sym(nested_scope))
print(r'\bm{\mbox{Two dimensioanal submanifold - Unit sphere}}')
print(r'\text{Basis not normalised}')
sp2coords = (theta, phi) = symbols('theta phi', real=True)
sp2param = [sin(theta) * cos(phi), sin(theta) * sin(phi), cos(theta)]
sp2 = g3.sm(sp2param, sp2coords, norm=False) # submanifold
(etheta, ephi) = sp2.mv() # sp2 basis vectors
(rtheta, rphi) = sp2.mvr() # sp2 reciprocal basis vectors
sp2grad = sp2.grad
sph_map = [1, theta, phi] # Coordinate map for sphere of r = 1
print(r'(\theta,\phi)\rightarrow (r,\theta,\phi) = ', latex(sph_map))
(etheta, ephi) = sp2.mv()
print(r'e_\theta | e_\theta = ', etheta | etheta)
print(r'e_\phi | e_\phi = ', ephi | ephi)
print('g =', sp2.g)
print(r'\text{g\_inv = }', latex(sp2.g_inv))
#print(r'\text{signature = ', latex(sp2.signature()))
Cf1 = sp2.Christoffel_symbols(mode=1)
Cf1 = permutedims(Array(Cf1), (2, 0, 1))
print(r'\text{Christoffel symbols of the first kind: }')
print(r'\Gamma_{1, \alpha, \beta} = ', latex(Cf1[0, :, :]), r'\quad',
r'\Gamma_{2, \alpha, \beta} = ', latex(Cf1[1, :, :]))
sys.path.insert(0, dir_path)
from jkPyLaTeX import LatexDoc, ldtTaller
from random import shuffle
from sympy import symbols, latex, sin, cos, tan, diff
x = symbols('x')
exercises = ''
answers = ''
excN = list(range(2, 10))
shuffle(excN)
for c in excN:
eji = c * x**2 + x * cos(c * x) / x
exercises += ' \\item $%s$' % latex(eji)
answers += ' \\item $%s$' % latex(diff(eji))
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Create the document
doc = ldtTaller('doc', 'Derivative', 'Calculus', '')
# Add content
doc.addSlice('exercises', exercises)
doc.addSlice('answers', answers)
#template or content
fnameMainSlice = './example/example.tex'
doc.setMainSlice(fnameMainSlice)
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#Save the files necessary to compile in ./texOut
display(pF)
# %%
F = -log(pF[0]) - C
F = F.expand(force=True)
F = F.collect(sigma_s)
F = F.collect(Sigma_x)
F = syp.nsimplify(F)
display(F)
# %%
gd_mux = Eq(-diff("F", mux, evaluate=False),
-syp.separatevars(diff(F, mux), force=True),
evaluate=False)
display(gd_mux)
print(syp.latex(gd_mux))
# %%
d_dmux = Eq(-diff("F", dmux, evaluate=False),
-diff(F, dmux).simplify(),
evaluate=False)
display(d_dmux)
print(syp.latex(d_dmux))
# %%
a = symbols("a", real=True)
sa = syp.Function("s")(a)
F = F.subs(s, sa)
da = Eq(-diff("F", "a", evaluate=False),
-diff(F, a).simplify(),