diff --git a/lib/python3.12/site-packages/sympy/combinatorics/__init__.py b/lib/python3.12/site-packages/sympy/combinatorics/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..220c27a42975555f8fe7770fcef0dd18475c89e1 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/__init__.py @@ -0,0 +1,43 @@ +from sympy.combinatorics.permutations import Permutation, Cycle +from sympy.combinatorics.prufer import Prufer +from sympy.combinatorics.generators import cyclic, alternating, symmetric, dihedral +from sympy.combinatorics.subsets import Subset +from sympy.combinatorics.partitions import (Partition, IntegerPartition, + RGS_rank, RGS_unrank, RGS_enum) +from sympy.combinatorics.polyhedron import (Polyhedron, tetrahedron, cube, + octahedron, dodecahedron, icosahedron) +from sympy.combinatorics.perm_groups import PermutationGroup, Coset, SymmetricPermutationGroup +from sympy.combinatorics.group_constructs import DirectProduct +from sympy.combinatorics.graycode import GrayCode +from sympy.combinatorics.named_groups import (SymmetricGroup, DihedralGroup, + CyclicGroup, AlternatingGroup, AbelianGroup, RubikGroup) +from sympy.combinatorics.pc_groups import PolycyclicGroup, Collector +from sympy.combinatorics.free_groups import free_group + +__all__ = [ + 'Permutation', 'Cycle', + + 'Prufer', + + 'cyclic', 'alternating', 'symmetric', 'dihedral', + + 'Subset', + + 'Partition', 'IntegerPartition', 'RGS_rank', 'RGS_unrank', 'RGS_enum', + + 'Polyhedron', 'tetrahedron', 'cube', 'octahedron', 'dodecahedron', + 'icosahedron', + + 'PermutationGroup', 'Coset', 'SymmetricPermutationGroup', + + 'DirectProduct', + + 'GrayCode', + + 'SymmetricGroup', 'DihedralGroup', 'CyclicGroup', 'AlternatingGroup', + 'AbelianGroup', 'RubikGroup', + + 'PolycyclicGroup', 'Collector', + + 'free_group', +] diff --git a/lib/python3.12/site-packages/sympy/combinatorics/coset_table.py b/lib/python3.12/site-packages/sympy/combinatorics/coset_table.py new file mode 100644 index 0000000000000000000000000000000000000000..06cc427c87c6860892f34735112f2f833d3f7f6d --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/coset_table.py @@ -0,0 +1,1255 @@ +from sympy.combinatorics.free_groups import free_group +from sympy.printing.defaults import DefaultPrinting + +from itertools import chain, product +from bisect import bisect_left + + +############################################################################### +# COSET TABLE # +############################################################################### + +class CosetTable(DefaultPrinting): + # coset_table: Mathematically a coset table + # represented using a list of lists + # alpha: Mathematically a coset (precisely, a live coset) + # represented by an integer between i with 1 <= i <= n + # alpha in c + # x: Mathematically an element of "A" (set of generators and + # their inverses), represented using "FpGroupElement" + # fp_grp: Finitely Presented Group with < X|R > as presentation. + # H: subgroup of fp_grp. + # NOTE: We start with H as being only a list of words in generators + # of "fp_grp". Since `.subgroup` method has not been implemented. + + r""" + + Properties + ========== + + [1] `0 \in \Omega` and `\tau(1) = \epsilon` + [2] `\alpha^x = \beta \Leftrightarrow \beta^{x^{-1}} = \alpha` + [3] If `\alpha^x = \beta`, then `H \tau(\alpha)x = H \tau(\beta)` + [4] `\forall \alpha \in \Omega, 1^{\tau(\alpha)} = \alpha` + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of Computational Group Theory" + + .. [2] John J. Cannon; Lucien A. Dimino; George Havas; Jane M. Watson + Mathematics of Computation, Vol. 27, No. 123. (Jul., 1973), pp. 463-490. + "Implementation and Analysis of the Todd-Coxeter Algorithm" + + """ + # default limit for the number of cosets allowed in a + # coset enumeration. + coset_table_max_limit = 4096000 + # limit for the current instance + coset_table_limit = None + # maximum size of deduction stack above or equal to + # which it is emptied + max_stack_size = 100 + + def __init__(self, fp_grp, subgroup, max_cosets=None): + if not max_cosets: + max_cosets = CosetTable.coset_table_max_limit + self.fp_group = fp_grp + self.subgroup = subgroup + self.coset_table_limit = max_cosets + # "p" is setup independent of Omega and n + self.p = [0] + # a list of the form `[gen_1, gen_1^{-1}, ... , gen_k, gen_k^{-1}]` + self.A = list(chain.from_iterable((gen, gen**-1) \ + for gen in self.fp_group.generators)) + #P[alpha, x] Only defined when alpha^x is defined. + self.P = [[None]*len(self.A)] + # the mathematical coset table which is a list of lists + self.table = [[None]*len(self.A)] + self.A_dict = {x: self.A.index(x) for x in self.A} + self.A_dict_inv = {} + for x, index in self.A_dict.items(): + if index % 2 == 0: + self.A_dict_inv[x] = self.A_dict[x] + 1 + else: + self.A_dict_inv[x] = self.A_dict[x] - 1 + # used in the coset-table based method of coset enumeration. Each of + # the element is called a "deduction" which is the form (alpha, x) whenever + # a value is assigned to alpha^x during a definition or "deduction process" + self.deduction_stack = [] + # Attributes for modified methods. + H = self.subgroup + self._grp = free_group(', ' .join(["a_%d" % i for i in range(len(H))]))[0] + self.P = [[None]*len(self.A)] + self.p_p = {} + + @property + def omega(self): + """Set of live cosets. """ + return [coset for coset in range(len(self.p)) if self.p[coset] == coset] + + def copy(self): + """ + Return a shallow copy of Coset Table instance ``self``. + + """ + self_copy = self.__class__(self.fp_group, self.subgroup) + self_copy.table = [list(perm_rep) for perm_rep in self.table] + self_copy.p = list(self.p) + self_copy.deduction_stack = list(self.deduction_stack) + return self_copy + + def __str__(self): + return "Coset Table on %s with %s as subgroup generators" \ + % (self.fp_group, self.subgroup) + + __repr__ = __str__ + + @property + def n(self): + """The number `n` represents the length of the sublist containing the + live cosets. + + """ + if not self.table: + return 0 + return max(self.omega) + 1 + + # Pg. 152 [1] + def is_complete(self): + r""" + The coset table is called complete if it has no undefined entries + on the live cosets; that is, `\alpha^x` is defined for all + `\alpha \in \Omega` and `x \in A`. + + """ + return not any(None in self.table[coset] for coset in self.omega) + + # Pg. 153 [1] + def define(self, alpha, x, modified=False): + r""" + This routine is used in the relator-based strategy of Todd-Coxeter + algorithm if some `\alpha^x` is undefined. We check whether there is + space available for defining a new coset. If there is enough space + then we remedy this by adjoining a new coset `\beta` to `\Omega` + (i.e to set of live cosets) and put that equal to `\alpha^x`, then + make an assignment satisfying Property[1]. If there is not enough space + then we halt the Coset Table creation. The maximum amount of space that + can be used by Coset Table can be manipulated using the class variable + ``CosetTable.coset_table_max_limit``. + + See Also + ======== + + define_c + + """ + A = self.A + table = self.table + len_table = len(table) + if len_table >= self.coset_table_limit: + # abort the further generation of cosets + raise ValueError("the coset enumeration has defined more than " + "%s cosets. Try with a greater value max number of cosets " + % self.coset_table_limit) + table.append([None]*len(A)) + self.P.append([None]*len(self.A)) + # beta is the new coset generated + beta = len_table + self.p.append(beta) + table[alpha][self.A_dict[x]] = beta + table[beta][self.A_dict_inv[x]] = alpha + # P[alpha][x] = epsilon, P[beta][x**-1] = epsilon + if modified: + self.P[alpha][self.A_dict[x]] = self._grp.identity + self.P[beta][self.A_dict_inv[x]] = self._grp.identity + self.p_p[beta] = self._grp.identity + + def define_c(self, alpha, x): + r""" + A variation of ``define`` routine, described on Pg. 165 [1], used in + the coset table-based strategy of Todd-Coxeter algorithm. It differs + from ``define`` routine in that for each definition it also adds the + tuple `(\alpha, x)` to the deduction stack. + + See Also + ======== + + define + + """ + A = self.A + table = self.table + len_table = len(table) + if len_table >= self.coset_table_limit: + # abort the further generation of cosets + raise ValueError("the coset enumeration has defined more than " + "%s cosets. Try with a greater value max number of cosets " + % self.coset_table_limit) + table.append([None]*len(A)) + # beta is the new coset generated + beta = len_table + self.p.append(beta) + table[alpha][self.A_dict[x]] = beta + table[beta][self.A_dict_inv[x]] = alpha + # append to deduction stack + self.deduction_stack.append((alpha, x)) + + def scan_c(self, alpha, word): + """ + A variation of ``scan`` routine, described on pg. 165 of [1], which + puts at tuple, whenever a deduction occurs, to deduction stack. + + See Also + ======== + + scan, scan_check, scan_and_fill, scan_and_fill_c + + """ + # alpha is an integer representing a "coset" + # since scanning can be in two cases + # 1. for alpha=0 and w in Y (i.e generating set of H) + # 2. alpha in Omega (set of live cosets), w in R (relators) + A_dict = self.A_dict + A_dict_inv = self.A_dict_inv + table = self.table + f = alpha + i = 0 + r = len(word) + b = alpha + j = r - 1 + # list of union of generators and their inverses + while i <= j and table[f][A_dict[word[i]]] is not None: + f = table[f][A_dict[word[i]]] + i += 1 + if i > j: + if f != b: + self.coincidence_c(f, b) + return + while j >= i and table[b][A_dict_inv[word[j]]] is not None: + b = table[b][A_dict_inv[word[j]]] + j -= 1 + if j < i: + # we have an incorrect completed scan with coincidence f ~ b + # run the "coincidence" routine + self.coincidence_c(f, b) + elif j == i: + # deduction process + table[f][A_dict[word[i]]] = b + table[b][A_dict_inv[word[i]]] = f + self.deduction_stack.append((f, word[i])) + # otherwise scan is incomplete and yields no information + + # alpha, beta coincide, i.e. alpha, beta represent the pair of cosets where + # coincidence occurs + def coincidence_c(self, alpha, beta): + """ + A variation of ``coincidence`` routine used in the coset-table based + method of coset enumeration. The only difference being on addition of + a new coset in coset table(i.e new coset introduction), then it is + appended to ``deduction_stack``. + + See Also + ======== + + coincidence + + """ + A_dict = self.A_dict + A_dict_inv = self.A_dict_inv + table = self.table + # behaves as a queue + q = [] + self.merge(alpha, beta, q) + while len(q) > 0: + gamma = q.pop(0) + for x in A_dict: + delta = table[gamma][A_dict[x]] + if delta is not None: + table[delta][A_dict_inv[x]] = None + # only line of difference from ``coincidence`` routine + self.deduction_stack.append((delta, x**-1)) + mu = self.rep(gamma) + nu = self.rep(delta) + if table[mu][A_dict[x]] is not None: + self.merge(nu, table[mu][A_dict[x]], q) + elif table[nu][A_dict_inv[x]] is not None: + self.merge(mu, table[nu][A_dict_inv[x]], q) + else: + table[mu][A_dict[x]] = nu + table[nu][A_dict_inv[x]] = mu + + def scan(self, alpha, word, y=None, fill=False, modified=False): + r""" + ``scan`` performs a scanning process on the input ``word``. + It first locates the largest prefix ``s`` of ``word`` for which + `\alpha^s` is defined (i.e is not ``None``), ``s`` may be empty. Let + ``word=sv``, let ``t`` be the longest suffix of ``v`` for which + `\alpha^{t^{-1}}` is defined, and let ``v=ut``. Then three + possibilities are there: + + 1. If ``t=v``, then we say that the scan completes, and if, in addition + `\alpha^s = \alpha^{t^{-1}}`, then we say that the scan completes + correctly. + + 2. It can also happen that scan does not complete, but `|u|=1`; that + is, the word ``u`` consists of a single generator `x \in A`. In that + case, if `\alpha^s = \beta` and `\alpha^{t^{-1}} = \gamma`, then we can + set `\beta^x = \gamma` and `\gamma^{x^{-1}} = \beta`. These assignments + are known as deductions and enable the scan to complete correctly. + + 3. See ``coicidence`` routine for explanation of third condition. + + Notes + ===== + + The code for the procedure of scanning `\alpha \in \Omega` + under `w \in A*` is defined on pg. 155 [1] + + See Also + ======== + + scan_c, scan_check, scan_and_fill, scan_and_fill_c + + Scan and Fill + ============= + + Performed when the default argument fill=True. + + Modified Scan + ============= + + Performed when the default argument modified=True + + """ + # alpha is an integer representing a "coset" + # since scanning can be in two cases + # 1. for alpha=0 and w in Y (i.e generating set of H) + # 2. alpha in Omega (set of live cosets), w in R (relators) + A_dict = self.A_dict + A_dict_inv = self.A_dict_inv + table = self.table + f = alpha + i = 0 + r = len(word) + b = alpha + j = r - 1 + b_p = y + if modified: + f_p = self._grp.identity + flag = 0 + while fill or flag == 0: + flag = 1 + while i <= j and table[f][A_dict[word[i]]] is not None: + if modified: + f_p = f_p*self.P[f][A_dict[word[i]]] + f = table[f][A_dict[word[i]]] + i += 1 + if i > j: + if f != b: + if modified: + self.modified_coincidence(f, b, f_p**-1*y) + else: + self.coincidence(f, b) + return + while j >= i and table[b][A_dict_inv[word[j]]] is not None: + if modified: + b_p = b_p*self.P[b][self.A_dict_inv[word[j]]] + b = table[b][A_dict_inv[word[j]]] + j -= 1 + if j < i: + # we have an incorrect completed scan with coincidence f ~ b + # run the "coincidence" routine + if modified: + self.modified_coincidence(f, b, f_p**-1*b_p) + else: + self.coincidence(f, b) + elif j == i: + # deduction process + table[f][A_dict[word[i]]] = b + table[b][A_dict_inv[word[i]]] = f + if modified: + self.P[f][self.A_dict[word[i]]] = f_p**-1*b_p + self.P[b][self.A_dict_inv[word[i]]] = b_p**-1*f_p + return + elif fill: + self.define(f, word[i], modified=modified) + # otherwise scan is incomplete and yields no information + + # used in the low-index subgroups algorithm + def scan_check(self, alpha, word): + r""" + Another version of ``scan`` routine, described on, it checks whether + `\alpha` scans correctly under `word`, it is a straightforward + modification of ``scan``. ``scan_check`` returns ``False`` (rather than + calling ``coincidence``) if the scan completes incorrectly; otherwise + it returns ``True``. + + See Also + ======== + + scan, scan_c, scan_and_fill, scan_and_fill_c + + """ + # alpha is an integer representing a "coset" + # since scanning can be in two cases + # 1. for alpha=0 and w in Y (i.e generating set of H) + # 2. alpha in Omega (set of live cosets), w in R (relators) + A_dict = self.A_dict + A_dict_inv = self.A_dict_inv + table = self.table + f = alpha + i = 0 + r = len(word) + b = alpha + j = r - 1 + while i <= j and table[f][A_dict[word[i]]] is not None: + f = table[f][A_dict[word[i]]] + i += 1 + if i > j: + return f == b + while j >= i and table[b][A_dict_inv[word[j]]] is not None: + b = table[b][A_dict_inv[word[j]]] + j -= 1 + if j < i: + # we have an incorrect completed scan with coincidence f ~ b + # return False, instead of calling coincidence routine + return False + elif j == i: + # deduction process + table[f][A_dict[word[i]]] = b + table[b][A_dict_inv[word[i]]] = f + return True + + def merge(self, k, lamda, q, w=None, modified=False): + """ + Merge two classes with representatives ``k`` and ``lamda``, described + on Pg. 157 [1] (for pseudocode), start by putting ``p[k] = lamda``. + It is more efficient to choose the new representative from the larger + of the two classes being merged, i.e larger among ``k`` and ``lamda``. + procedure ``merge`` performs the merging operation, adds the deleted + class representative to the queue ``q``. + + Parameters + ========== + + 'k', 'lamda' being the two class representatives to be merged. + + Notes + ===== + + Pg. 86-87 [1] contains a description of this method. + + See Also + ======== + + coincidence, rep + + """ + p = self.p + rep = self.rep + phi = rep(k, modified=modified) + psi = rep(lamda, modified=modified) + if phi != psi: + mu = min(phi, psi) + v = max(phi, psi) + p[v] = mu + if modified: + if v == phi: + self.p_p[phi] = self.p_p[k]**-1*w*self.p_p[lamda] + else: + self.p_p[psi] = self.p_p[lamda]**-1*w**-1*self.p_p[k] + q.append(v) + + def rep(self, k, modified=False): + r""" + Parameters + ========== + + `k \in [0 \ldots n-1]`, as for ``self`` only array ``p`` is used + + Returns + ======= + + Representative of the class containing ``k``. + + Returns the representative of `\sim` class containing ``k``, it also + makes some modification to array ``p`` of ``self`` to ease further + computations, described on Pg. 157 [1]. + + The information on classes under `\sim` is stored in array `p` of + ``self`` argument, which will always satisfy the property: + + `p[\alpha] \sim \alpha` and `p[\alpha]=\alpha \iff \alpha=rep(\alpha)` + `\forall \in [0 \ldots n-1]`. + + So, for `\alpha \in [0 \ldots n-1]`, we find `rep(self, \alpha)` by + continually replacing `\alpha` by `p[\alpha]` until it becomes + constant (i.e satisfies `p[\alpha] = \alpha`):w + + To increase the efficiency of later ``rep`` calculations, whenever we + find `rep(self, \alpha)=\beta`, we set + `p[\gamma] = \beta \forall \gamma \in p-chain` from `\alpha` to `\beta` + + Notes + ===== + + ``rep`` routine is also described on Pg. 85-87 [1] in Atkinson's + algorithm, this results from the fact that ``coincidence`` routine + introduces functionality similar to that introduced by the + ``minimal_block`` routine on Pg. 85-87 [1]. + + See Also + ======== + + coincidence, merge + + """ + p = self.p + lamda = k + rho = p[lamda] + if modified: + s = p[:] + while rho != lamda: + if modified: + s[rho] = lamda + lamda = rho + rho = p[lamda] + if modified: + rho = s[lamda] + while rho != k: + mu = rho + rho = s[mu] + p[rho] = lamda + self.p_p[rho] = self.p_p[rho]*self.p_p[mu] + else: + mu = k + rho = p[mu] + while rho != lamda: + p[mu] = lamda + mu = rho + rho = p[mu] + return lamda + + # alpha, beta coincide, i.e. alpha, beta represent the pair of cosets + # where coincidence occurs + def coincidence(self, alpha, beta, w=None, modified=False): + r""" + The third situation described in ``scan`` routine is handled by this + routine, described on Pg. 156-161 [1]. + + The unfortunate situation when the scan completes but not correctly, + then ``coincidence`` routine is run. i.e when for some `i` with + `1 \le i \le r+1`, we have `w=st` with `s = x_1 x_2 \dots x_{i-1}`, + `t = x_i x_{i+1} \dots x_r`, and `\beta = \alpha^s` and + `\gamma = \alpha^{t-1}` are defined but unequal. This means that + `\beta` and `\gamma` represent the same coset of `H` in `G`. Described + on Pg. 156 [1]. ``rep`` + + See Also + ======== + + scan + + """ + A_dict = self.A_dict + A_dict_inv = self.A_dict_inv + table = self.table + # behaves as a queue + q = [] + if modified: + self.modified_merge(alpha, beta, w, q) + else: + self.merge(alpha, beta, q) + while len(q) > 0: + gamma = q.pop(0) + for x in A_dict: + delta = table[gamma][A_dict[x]] + if delta is not None: + table[delta][A_dict_inv[x]] = None + mu = self.rep(gamma, modified=modified) + nu = self.rep(delta, modified=modified) + if table[mu][A_dict[x]] is not None: + if modified: + v = self.p_p[delta]**-1*self.P[gamma][self.A_dict[x]]**-1 + v = v*self.p_p[gamma]*self.P[mu][self.A_dict[x]] + self.modified_merge(nu, table[mu][self.A_dict[x]], v, q) + else: + self.merge(nu, table[mu][A_dict[x]], q) + elif table[nu][A_dict_inv[x]] is not None: + if modified: + v = self.p_p[gamma]**-1*self.P[gamma][self.A_dict[x]] + v = v*self.p_p[delta]*self.P[mu][self.A_dict_inv[x]] + self.modified_merge(mu, table[nu][self.A_dict_inv[x]], v, q) + else: + self.merge(mu, table[nu][A_dict_inv[x]], q) + else: + table[mu][A_dict[x]] = nu + table[nu][A_dict_inv[x]] = mu + if modified: + v = self.p_p[gamma]**-1*self.P[gamma][self.A_dict[x]]*self.p_p[delta] + self.P[mu][self.A_dict[x]] = v + self.P[nu][self.A_dict_inv[x]] = v**-1 + + # method used in the HLT strategy + def scan_and_fill(self, alpha, word): + """ + A modified version of ``scan`` routine used in the relator-based + method of coset enumeration, described on pg. 162-163 [1], which + follows the idea that whenever the procedure is called and the scan + is incomplete then it makes new definitions to enable the scan to + complete; i.e it fills in the gaps in the scan of the relator or + subgroup generator. + + """ + self.scan(alpha, word, fill=True) + + def scan_and_fill_c(self, alpha, word): + """ + A modified version of ``scan`` routine, described on Pg. 165 second + para. [1], with modification similar to that of ``scan_anf_fill`` the + only difference being it calls the coincidence procedure used in the + coset-table based method i.e. the routine ``coincidence_c`` is used. + + See Also + ======== + + scan, scan_and_fill + + """ + A_dict = self.A_dict + A_dict_inv = self.A_dict_inv + table = self.table + r = len(word) + f = alpha + i = 0 + b = alpha + j = r - 1 + # loop until it has filled the alpha row in the table. + while True: + # do the forward scanning + while i <= j and table[f][A_dict[word[i]]] is not None: + f = table[f][A_dict[word[i]]] + i += 1 + if i > j: + if f != b: + self.coincidence_c(f, b) + return + # forward scan was incomplete, scan backwards + while j >= i and table[b][A_dict_inv[word[j]]] is not None: + b = table[b][A_dict_inv[word[j]]] + j -= 1 + if j < i: + self.coincidence_c(f, b) + elif j == i: + table[f][A_dict[word[i]]] = b + table[b][A_dict_inv[word[i]]] = f + self.deduction_stack.append((f, word[i])) + else: + self.define_c(f, word[i]) + + # method used in the HLT strategy + def look_ahead(self): + """ + When combined with the HLT method this is known as HLT+Lookahead + method of coset enumeration, described on pg. 164 [1]. Whenever + ``define`` aborts due to lack of space available this procedure is + executed. This routine helps in recovering space resulting from + "coincidence" of cosets. + + """ + R = self.fp_group.relators + p = self.p + # complete scan all relators under all cosets(obviously live) + # without making new definitions + for beta in self.omega: + for w in R: + self.scan(beta, w) + if p[beta] < beta: + break + + # Pg. 166 + def process_deductions(self, R_c_x, R_c_x_inv): + """ + Processes the deductions that have been pushed onto ``deduction_stack``, + described on Pg. 166 [1] and is used in coset-table based enumeration. + + See Also + ======== + + deduction_stack + + """ + p = self.p + table = self.table + while len(self.deduction_stack) > 0: + if len(self.deduction_stack) >= CosetTable.max_stack_size: + self.look_ahead() + del self.deduction_stack[:] + continue + else: + alpha, x = self.deduction_stack.pop() + if p[alpha] == alpha: + for w in R_c_x: + self.scan_c(alpha, w) + if p[alpha] < alpha: + break + beta = table[alpha][self.A_dict[x]] + if beta is not None and p[beta] == beta: + for w in R_c_x_inv: + self.scan_c(beta, w) + if p[beta] < beta: + break + + def process_deductions_check(self, R_c_x, R_c_x_inv): + """ + A variation of ``process_deductions``, this calls ``scan_check`` + wherever ``process_deductions`` calls ``scan``, described on Pg. [1]. + + See Also + ======== + + process_deductions + + """ + table = self.table + while len(self.deduction_stack) > 0: + alpha, x = self.deduction_stack.pop() + for w in R_c_x: + if not self.scan_check(alpha, w): + return False + beta = table[alpha][self.A_dict[x]] + if beta is not None: + for w in R_c_x_inv: + if not self.scan_check(beta, w): + return False + return True + + def switch(self, beta, gamma): + r"""Switch the elements `\beta, \gamma \in \Omega` of ``self``, used + by the ``standardize`` procedure, described on Pg. 167 [1]. + + See Also + ======== + + standardize + + """ + A = self.A + A_dict = self.A_dict + table = self.table + for x in A: + z = table[gamma][A_dict[x]] + table[gamma][A_dict[x]] = table[beta][A_dict[x]] + table[beta][A_dict[x]] = z + for alpha in range(len(self.p)): + if self.p[alpha] == alpha: + if table[alpha][A_dict[x]] == beta: + table[alpha][A_dict[x]] = gamma + elif table[alpha][A_dict[x]] == gamma: + table[alpha][A_dict[x]] = beta + + def standardize(self): + r""" + A coset table is standardized if when running through the cosets and + within each coset through the generator images (ignoring generator + inverses), the cosets appear in order of the integers + `0, 1, \dots, n`. "Standardize" reorders the elements of `\Omega` + such that, if we scan the coset table first by elements of `\Omega` + and then by elements of A, then the cosets occur in ascending order. + ``standardize()`` is used at the end of an enumeration to permute the + cosets so that they occur in some sort of standard order. + + Notes + ===== + + procedure is described on pg. 167-168 [1], it also makes use of the + ``switch`` routine to replace by smaller integer value. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, coset_enumeration_r + >>> F, x, y = free_group("x, y") + + # Example 5.3 from [1] + >>> f = FpGroup(F, [x**2*y**2, x**3*y**5]) + >>> C = coset_enumeration_r(f, []) + >>> C.compress() + >>> C.table + [[1, 3, 1, 3], [2, 0, 2, 0], [3, 1, 3, 1], [0, 2, 0, 2]] + >>> C.standardize() + >>> C.table + [[1, 2, 1, 2], [3, 0, 3, 0], [0, 3, 0, 3], [2, 1, 2, 1]] + + """ + A = self.A + A_dict = self.A_dict + gamma = 1 + for alpha, x in product(range(self.n), A): + beta = self.table[alpha][A_dict[x]] + if beta >= gamma: + if beta > gamma: + self.switch(gamma, beta) + gamma += 1 + if gamma == self.n: + return + + # Compression of a Coset Table + def compress(self): + """Removes the non-live cosets from the coset table, described on + pg. 167 [1]. + + """ + gamma = -1 + A = self.A + A_dict = self.A_dict + A_dict_inv = self.A_dict_inv + table = self.table + chi = tuple([i for i in range(len(self.p)) if self.p[i] != i]) + for alpha in self.omega: + gamma += 1 + if gamma != alpha: + # replace alpha by gamma in coset table + for x in A: + beta = table[alpha][A_dict[x]] + table[gamma][A_dict[x]] = beta + table[beta][A_dict_inv[x]] == gamma + # all the cosets in the table are live cosets + self.p = list(range(gamma + 1)) + # delete the useless columns + del table[len(self.p):] + # re-define values + for row in table: + for j in range(len(self.A)): + row[j] -= bisect_left(chi, row[j]) + + def conjugates(self, R): + R_c = list(chain.from_iterable((rel.cyclic_conjugates(), \ + (rel**-1).cyclic_conjugates()) for rel in R)) + R_set = set() + for conjugate in R_c: + R_set = R_set.union(conjugate) + R_c_list = [] + for x in self.A: + r = {word for word in R_set if word[0] == x} + R_c_list.append(r) + R_set.difference_update(r) + return R_c_list + + def coset_representative(self, coset): + ''' + Compute the coset representative of a given coset. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, coset_enumeration_r + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**3, y**3, x**-1*y**-1*x*y]) + >>> C = coset_enumeration_r(f, [x]) + >>> C.compress() + >>> C.table + [[0, 0, 1, 2], [1, 1, 2, 0], [2, 2, 0, 1]] + >>> C.coset_representative(0) + + >>> C.coset_representative(1) + y + >>> C.coset_representative(2) + y**-1 + + ''' + for x in self.A: + gamma = self.table[coset][self.A_dict[x]] + if coset == 0: + return self.fp_group.identity + if gamma < coset: + return self.coset_representative(gamma)*x**-1 + + ############################## + # Modified Methods # + ############################## + + def modified_define(self, alpha, x): + r""" + Define a function p_p from from [1..n] to A* as + an additional component of the modified coset table. + + Parameters + ========== + + \alpha \in \Omega + x \in A* + + See Also + ======== + + define + + """ + self.define(alpha, x, modified=True) + + def modified_scan(self, alpha, w, y, fill=False): + r""" + Parameters + ========== + \alpha \in \Omega + w \in A* + y \in (YUY^-1) + fill -- `modified_scan_and_fill` when set to True. + + See Also + ======== + + scan + """ + self.scan(alpha, w, y=y, fill=fill, modified=True) + + def modified_scan_and_fill(self, alpha, w, y): + self.modified_scan(alpha, w, y, fill=True) + + def modified_merge(self, k, lamda, w, q): + r""" + Parameters + ========== + + 'k', 'lamda' -- the two class representatives to be merged. + q -- queue of length l of elements to be deleted from `\Omega` *. + w -- Word in (YUY^-1) + + See Also + ======== + + merge + """ + self.merge(k, lamda, q, w=w, modified=True) + + def modified_rep(self, k): + r""" + Parameters + ========== + + `k \in [0 \ldots n-1]` + + See Also + ======== + + rep + """ + self.rep(k, modified=True) + + def modified_coincidence(self, alpha, beta, w): + r""" + Parameters + ========== + + A coincident pair `\alpha, \beta \in \Omega, w \in Y \cup Y^{-1}` + + See Also + ======== + + coincidence + + """ + self.coincidence(alpha, beta, w=w, modified=True) + +############################################################################### +# COSET ENUMERATION # +############################################################################### + +# relator-based method +def coset_enumeration_r(fp_grp, Y, max_cosets=None, draft=None, + incomplete=False, modified=False): + """ + This is easier of the two implemented methods of coset enumeration. + and is often called the HLT method, after Hazelgrove, Leech, Trotter + The idea is that we make use of ``scan_and_fill`` makes new definitions + whenever the scan is incomplete to enable the scan to complete; this way + we fill in the gaps in the scan of the relator or subgroup generator, + that's why the name relator-based method. + + An instance of `CosetTable` for `fp_grp` can be passed as the keyword + argument `draft` in which case the coset enumeration will start with + that instance and attempt to complete it. + + When `incomplete` is `True` and the function is unable to complete for + some reason, the partially complete table will be returned. + + # TODO: complete the docstring + + See Also + ======== + + scan_and_fill, + + Examples + ======== + + >>> from sympy.combinatorics.free_groups import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, coset_enumeration_r + >>> F, x, y = free_group("x, y") + + # Example 5.1 from [1] + >>> f = FpGroup(F, [x**3, y**3, x**-1*y**-1*x*y]) + >>> C = coset_enumeration_r(f, [x]) + >>> for i in range(len(C.p)): + ... if C.p[i] == i: + ... print(C.table[i]) + [0, 0, 1, 2] + [1, 1, 2, 0] + [2, 2, 0, 1] + >>> C.p + [0, 1, 2, 1, 1] + + # Example from exercises Q2 [1] + >>> f = FpGroup(F, [x**2*y**2, y**-1*x*y*x**-3]) + >>> C = coset_enumeration_r(f, []) + >>> C.compress(); C.standardize() + >>> C.table + [[1, 2, 3, 4], + [5, 0, 6, 7], + [0, 5, 7, 6], + [7, 6, 5, 0], + [6, 7, 0, 5], + [2, 1, 4, 3], + [3, 4, 2, 1], + [4, 3, 1, 2]] + + # Example 5.2 + >>> f = FpGroup(F, [x**2, y**3, (x*y)**3]) + >>> Y = [x*y] + >>> C = coset_enumeration_r(f, Y) + >>> for i in range(len(C.p)): + ... if C.p[i] == i: + ... print(C.table[i]) + [1, 1, 2, 1] + [0, 0, 0, 2] + [3, 3, 1, 0] + [2, 2, 3, 3] + + # Example 5.3 + >>> f = FpGroup(F, [x**2*y**2, x**3*y**5]) + >>> Y = [] + >>> C = coset_enumeration_r(f, Y) + >>> for i in range(len(C.p)): + ... if C.p[i] == i: + ... print(C.table[i]) + [1, 3, 1, 3] + [2, 0, 2, 0] + [3, 1, 3, 1] + [0, 2, 0, 2] + + # Example 5.4 + >>> F, a, b, c, d, e = free_group("a, b, c, d, e") + >>> f = FpGroup(F, [a*b*c**-1, b*c*d**-1, c*d*e**-1, d*e*a**-1, e*a*b**-1]) + >>> Y = [a] + >>> C = coset_enumeration_r(f, Y) + >>> for i in range(len(C.p)): + ... if C.p[i] == i: + ... print(C.table[i]) + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] + + # example of "compress" method + >>> C.compress() + >>> C.table + [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] + + # Exercises Pg. 161, Q2. + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**2*y**2, y**-1*x*y*x**-3]) + >>> Y = [] + >>> C = coset_enumeration_r(f, Y) + >>> C.compress() + >>> C.standardize() + >>> C.table + [[1, 2, 3, 4], + [5, 0, 6, 7], + [0, 5, 7, 6], + [7, 6, 5, 0], + [6, 7, 0, 5], + [2, 1, 4, 3], + [3, 4, 2, 1], + [4, 3, 1, 2]] + + # John J. Cannon; Lucien A. Dimino; George Havas; Jane M. Watson + # Mathematics of Computation, Vol. 27, No. 123. (Jul., 1973), pp. 463-490 + # from 1973chwd.pdf + # Table 1. Ex. 1 + >>> F, r, s, t = free_group("r, s, t") + >>> E1 = FpGroup(F, [t**-1*r*t*r**-2, r**-1*s*r*s**-2, s**-1*t*s*t**-2]) + >>> C = coset_enumeration_r(E1, [r]) + >>> for i in range(len(C.p)): + ... if C.p[i] == i: + ... print(C.table[i]) + [0, 0, 0, 0, 0, 0] + + Ex. 2 + >>> F, a, b = free_group("a, b") + >>> Cox = FpGroup(F, [a**6, b**6, (a*b)**2, (a**2*b**2)**2, (a**3*b**3)**5]) + >>> C = coset_enumeration_r(Cox, [a]) + >>> index = 0 + >>> for i in range(len(C.p)): + ... if C.p[i] == i: + ... index += 1 + >>> index + 500 + + # Ex. 3 + >>> F, a, b = free_group("a, b") + >>> B_2_4 = FpGroup(F, [a**4, b**4, (a*b)**4, (a**-1*b)**4, (a**2*b)**4, \ + (a*b**2)**4, (a**2*b**2)**4, (a**-1*b*a*b)**4, (a*b**-1*a*b)**4]) + >>> C = coset_enumeration_r(B_2_4, [a]) + >>> index = 0 + >>> for i in range(len(C.p)): + ... if C.p[i] == i: + ... index += 1 + >>> index + 1024 + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of computational group theory" + + """ + # 1. Initialize a coset table C for < X|R > + C = CosetTable(fp_grp, Y, max_cosets=max_cosets) + # Define coset table methods. + if modified: + _scan_and_fill = C.modified_scan_and_fill + _define = C.modified_define + else: + _scan_and_fill = C.scan_and_fill + _define = C.define + if draft: + C.table = draft.table[:] + C.p = draft.p[:] + R = fp_grp.relators + A_dict = C.A_dict + p = C.p + for i in range(len(Y)): + if modified: + _scan_and_fill(0, Y[i], C._grp.generators[i]) + else: + _scan_and_fill(0, Y[i]) + alpha = 0 + while alpha < C.n: + if p[alpha] == alpha: + try: + for w in R: + if modified: + _scan_and_fill(alpha, w, C._grp.identity) + else: + _scan_and_fill(alpha, w) + # if alpha was eliminated during the scan then break + if p[alpha] < alpha: + break + if p[alpha] == alpha: + for x in A_dict: + if C.table[alpha][A_dict[x]] is None: + _define(alpha, x) + except ValueError as e: + if incomplete: + return C + raise e + alpha += 1 + return C + +def modified_coset_enumeration_r(fp_grp, Y, max_cosets=None, draft=None, + incomplete=False): + r""" + Introduce a new set of symbols y \in Y that correspond to the + generators of the subgroup. Store the elements of Y as a + word P[\alpha, x] and compute the coset table similar to that of + the regular coset enumeration methods. + + Examples + ======== + + >>> from sympy.combinatorics.free_groups import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup + >>> from sympy.combinatorics.coset_table import modified_coset_enumeration_r + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**3, y**3, x**-1*y**-1*x*y]) + >>> C = modified_coset_enumeration_r(f, [x]) + >>> C.table + [[0, 0, 1, 2], [1, 1, 2, 0], [2, 2, 0, 1], [None, 1, None, None], [1, 3, None, None]] + + See Also + ======== + + coset_enumertation_r + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E., + "Handbook of Computational Group Theory", + Section 5.3.2 + """ + return coset_enumeration_r(fp_grp, Y, max_cosets=max_cosets, draft=draft, + incomplete=incomplete, modified=True) + +# Pg. 166 +# coset-table based method +def coset_enumeration_c(fp_grp, Y, max_cosets=None, draft=None, + incomplete=False): + """ + >>> from sympy.combinatorics.free_groups import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, coset_enumeration_c + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**3, y**3, x**-1*y**-1*x*y]) + >>> C = coset_enumeration_c(f, [x]) + >>> C.table + [[0, 0, 1, 2], [1, 1, 2, 0], [2, 2, 0, 1]] + + """ + # Initialize a coset table C for < X|R > + X = fp_grp.generators + R = fp_grp.relators + C = CosetTable(fp_grp, Y, max_cosets=max_cosets) + if draft: + C.table = draft.table[:] + C.p = draft.p[:] + C.deduction_stack = draft.deduction_stack + for alpha, x in product(range(len(C.table)), X): + if C.table[alpha][C.A_dict[x]] is not None: + C.deduction_stack.append((alpha, x)) + A = C.A + # replace all the elements by cyclic reductions + R_cyc_red = [rel.identity_cyclic_reduction() for rel in R] + R_c = list(chain.from_iterable((rel.cyclic_conjugates(), (rel**-1).cyclic_conjugates()) \ + for rel in R_cyc_red)) + R_set = set() + for conjugate in R_c: + R_set = R_set.union(conjugate) + # a list of subsets of R_c whose words start with "x". + R_c_list = [] + for x in C.A: + r = {word for word in R_set if word[0] == x} + R_c_list.append(r) + R_set.difference_update(r) + for w in Y: + C.scan_and_fill_c(0, w) + for x in A: + C.process_deductions(R_c_list[C.A_dict[x]], R_c_list[C.A_dict_inv[x]]) + alpha = 0 + while alpha < len(C.table): + if C.p[alpha] == alpha: + try: + for x in C.A: + if C.p[alpha] != alpha: + break + if C.table[alpha][C.A_dict[x]] is None: + C.define_c(alpha, x) + C.process_deductions(R_c_list[C.A_dict[x]], R_c_list[C.A_dict_inv[x]]) + except ValueError as e: + if incomplete: + return C + raise e + alpha += 1 + return C diff --git a/lib/python3.12/site-packages/sympy/combinatorics/fp_groups.py b/lib/python3.12/site-packages/sympy/combinatorics/fp_groups.py new file mode 100644 index 0000000000000000000000000000000000000000..0e9858683750ef0f7a0f11b1cc7daec2b6a8051d --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/fp_groups.py @@ -0,0 +1,1354 @@ +"""Finitely Presented Groups and its algorithms. """ + +from sympy.core.singleton import S +from sympy.core.symbol import symbols +from sympy.combinatorics.free_groups import (FreeGroup, FreeGroupElement, + free_group) +from sympy.combinatorics.rewritingsystem import RewritingSystem +from sympy.combinatorics.coset_table import (CosetTable, + coset_enumeration_r, + coset_enumeration_c) +from sympy.combinatorics import PermutationGroup +from sympy.matrices.normalforms import invariant_factors +from sympy.matrices import Matrix +from sympy.polys.polytools import gcd +from sympy.printing.defaults import DefaultPrinting +from sympy.utilities import public +from sympy.utilities.magic import pollute + +from itertools import product + + +@public +def fp_group(fr_grp, relators=()): + _fp_group = FpGroup(fr_grp, relators) + return (_fp_group,) + tuple(_fp_group._generators) + +@public +def xfp_group(fr_grp, relators=()): + _fp_group = FpGroup(fr_grp, relators) + return (_fp_group, _fp_group._generators) + +# Does not work. Both symbols and pollute are undefined. Never tested. +@public +def vfp_group(fr_grpm, relators): + _fp_group = FpGroup(symbols, relators) + pollute([sym.name for sym in _fp_group.symbols], _fp_group.generators) + return _fp_group + + +def _parse_relators(rels): + """Parse the passed relators.""" + return rels + + +############################################################################### +# FINITELY PRESENTED GROUPS # +############################################################################### + + +class FpGroup(DefaultPrinting): + """ + The FpGroup would take a FreeGroup and a list/tuple of relators, the + relators would be specified in such a way that each of them be equal to the + identity of the provided free group. + + """ + is_group = True + is_FpGroup = True + is_PermutationGroup = False + + def __init__(self, fr_grp, relators): + relators = _parse_relators(relators) + self.free_group = fr_grp + self.relators = relators + self.generators = self._generators() + self.dtype = type("FpGroupElement", (FpGroupElement,), {"group": self}) + + # CosetTable instance on identity subgroup + self._coset_table = None + # returns whether coset table on identity subgroup + # has been standardized + self._is_standardized = False + + self._order = None + self._center = None + + self._rewriting_system = RewritingSystem(self) + self._perm_isomorphism = None + return + + def _generators(self): + return self.free_group.generators + + def make_confluent(self): + ''' + Try to make the group's rewriting system confluent + + ''' + self._rewriting_system.make_confluent() + return + + def reduce(self, word): + ''' + Return the reduced form of `word` in `self` according to the group's + rewriting system. If it's confluent, the reduced form is the unique normal + form of the word in the group. + + ''' + return self._rewriting_system.reduce(word) + + def equals(self, word1, word2): + ''' + Compare `word1` and `word2` for equality in the group + using the group's rewriting system. If the system is + confluent, the returned answer is necessarily correct. + (If it is not, `False` could be returned in some cases + where in fact `word1 == word2`) + + ''' + if self.reduce(word1*word2**-1) == self.identity: + return True + elif self._rewriting_system.is_confluent: + return False + return None + + @property + def identity(self): + return self.free_group.identity + + def __contains__(self, g): + return g in self.free_group + + def subgroup(self, gens, C=None, homomorphism=False): + ''' + Return the subgroup generated by `gens` using the + Reidemeister-Schreier algorithm + homomorphism -- When set to True, return a dictionary containing the images + of the presentation generators in the original group. + + Examples + ======== + + >>> from sympy.combinatorics.fp_groups import FpGroup + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**3, y**5, (x*y)**2]) + >>> H = [x*y, x**-1*y**-1*x*y*x] + >>> K, T = f.subgroup(H, homomorphism=True) + >>> T(K.generators) + [x*y, x**-1*y**2*x**-1] + + ''' + + if not all(isinstance(g, FreeGroupElement) for g in gens): + raise ValueError("Generators must be `FreeGroupElement`s") + if not all(g.group == self.free_group for g in gens): + raise ValueError("Given generators are not members of the group") + if homomorphism: + g, rels, _gens = reidemeister_presentation(self, gens, C=C, homomorphism=True) + else: + g, rels = reidemeister_presentation(self, gens, C=C) + if g: + g = FpGroup(g[0].group, rels) + else: + g = FpGroup(free_group('')[0], []) + if homomorphism: + from sympy.combinatorics.homomorphisms import homomorphism + return g, homomorphism(g, self, g.generators, _gens, check=False) + return g + + def coset_enumeration(self, H, strategy="relator_based", max_cosets=None, + draft=None, incomplete=False): + """ + Return an instance of ``coset table``, when Todd-Coxeter algorithm is + run over the ``self`` with ``H`` as subgroup, using ``strategy`` + argument as strategy. The returned coset table is compressed but not + standardized. + + An instance of `CosetTable` for `fp_grp` can be passed as the keyword + argument `draft` in which case the coset enumeration will start with + that instance and attempt to complete it. + + When `incomplete` is `True` and the function is unable to complete for + some reason, the partially complete table will be returned. + + """ + if not max_cosets: + max_cosets = CosetTable.coset_table_max_limit + if strategy == 'relator_based': + C = coset_enumeration_r(self, H, max_cosets=max_cosets, + draft=draft, incomplete=incomplete) + else: + C = coset_enumeration_c(self, H, max_cosets=max_cosets, + draft=draft, incomplete=incomplete) + if C.is_complete(): + C.compress() + return C + + def standardize_coset_table(self): + """ + Standardized the coset table ``self`` and makes the internal variable + ``_is_standardized`` equal to ``True``. + + """ + self._coset_table.standardize() + self._is_standardized = True + + def coset_table(self, H, strategy="relator_based", max_cosets=None, + draft=None, incomplete=False): + """ + Return the mathematical coset table of ``self`` in ``H``. + + """ + if not H: + if self._coset_table is not None: + if not self._is_standardized: + self.standardize_coset_table() + else: + C = self.coset_enumeration([], strategy, max_cosets=max_cosets, + draft=draft, incomplete=incomplete) + self._coset_table = C + self.standardize_coset_table() + return self._coset_table.table + else: + C = self.coset_enumeration(H, strategy, max_cosets=max_cosets, + draft=draft, incomplete=incomplete) + C.standardize() + return C.table + + def order(self, strategy="relator_based"): + """ + Returns the order of the finitely presented group ``self``. It uses + the coset enumeration with identity group as subgroup, i.e ``H=[]``. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x, y**2]) + >>> f.order(strategy="coset_table_based") + 2 + + """ + if self._order is not None: + return self._order + if self._coset_table is not None: + self._order = len(self._coset_table.table) + elif len(self.relators) == 0: + self._order = self.free_group.order() + elif len(self.generators) == 1: + self._order = abs(gcd([r.array_form[0][1] for r in self.relators])) + elif self._is_infinite(): + self._order = S.Infinity + else: + gens, C = self._finite_index_subgroup() + if C: + ind = len(C.table) + self._order = ind*self.subgroup(gens, C=C).order() + else: + self._order = self.index([]) + return self._order + + def _is_infinite(self): + ''' + Test if the group is infinite. Return `True` if the test succeeds + and `None` otherwise + + ''' + used_gens = set() + for r in self.relators: + used_gens.update(r.contains_generators()) + if not set(self.generators) <= used_gens: + return True + # Abelianisation test: check is the abelianisation is infinite + abelian_rels = [] + for rel in self.relators: + abelian_rels.append([rel.exponent_sum(g) for g in self.generators]) + m = Matrix(Matrix(abelian_rels)) + if 0 in invariant_factors(m): + return True + else: + return None + + + def _finite_index_subgroup(self, s=None): + ''' + Find the elements of `self` that generate a finite index subgroup + and, if found, return the list of elements and the coset table of `self` by + the subgroup, otherwise return `(None, None)` + + ''' + gen = self.most_frequent_generator() + rels = list(self.generators) + rels.extend(self.relators) + if not s: + if len(self.generators) == 2: + s = [gen] + [g for g in self.generators if g != gen] + else: + rand = self.free_group.identity + i = 0 + while ((rand in rels or rand**-1 in rels or rand.is_identity) + and i<10): + rand = self.random() + i += 1 + s = [gen, rand] + [g for g in self.generators if g != gen] + mid = (len(s)+1)//2 + half1 = s[:mid] + half2 = s[mid:] + draft1 = None + draft2 = None + m = 200 + C = None + while not C and (m/2 < CosetTable.coset_table_max_limit): + m = min(m, CosetTable.coset_table_max_limit) + draft1 = self.coset_enumeration(half1, max_cosets=m, + draft=draft1, incomplete=True) + if draft1.is_complete(): + C = draft1 + half = half1 + else: + draft2 = self.coset_enumeration(half2, max_cosets=m, + draft=draft2, incomplete=True) + if draft2.is_complete(): + C = draft2 + half = half2 + if not C: + m *= 2 + if not C: + return None, None + C.compress() + return half, C + + def most_frequent_generator(self): + gens = self.generators + rels = self.relators + freqs = [sum(r.generator_count(g) for r in rels) for g in gens] + return gens[freqs.index(max(freqs))] + + def random(self): + import random + r = self.free_group.identity + for i in range(random.randint(2,3)): + r = r*random.choice(self.generators)**random.choice([1,-1]) + return r + + def index(self, H, strategy="relator_based"): + """ + Return the index of subgroup ``H`` in group ``self``. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**5, y**4, y*x*y**3*x**3]) + >>> f.index([x]) + 4 + + """ + # TODO: use |G:H| = |G|/|H| (currently H can't be made into a group) + # when we know |G| and |H| + + if H == []: + return self.order() + else: + C = self.coset_enumeration(H, strategy) + return len(C.table) + + def __str__(self): + if self.free_group.rank > 30: + str_form = "" % self.free_group.rank + else: + str_form = "" % str(self.generators) + return str_form + + __repr__ = __str__ + +#============================================================================== +# PERMUTATION GROUP METHODS +#============================================================================== + + def _to_perm_group(self): + ''' + Return an isomorphic permutation group and the isomorphism. + The implementation is dependent on coset enumeration so + will only terminate for finite groups. + + ''' + from sympy.combinatorics import Permutation + from sympy.combinatorics.homomorphisms import homomorphism + if self.order() is S.Infinity: + raise NotImplementedError("Permutation presentation of infinite " + "groups is not implemented") + if self._perm_isomorphism: + T = self._perm_isomorphism + P = T.image() + else: + C = self.coset_table([]) + gens = self.generators + images = [[C[i][2*gens.index(g)] for i in range(len(C))] for g in gens] + images = [Permutation(i) for i in images] + P = PermutationGroup(images) + T = homomorphism(self, P, gens, images, check=False) + self._perm_isomorphism = T + return P, T + + def _perm_group_list(self, method_name, *args): + ''' + Given the name of a `PermutationGroup` method (returning a subgroup + or a list of subgroups) and (optionally) additional arguments it takes, + return a list or a list of lists containing the generators of this (or + these) subgroups in terms of the generators of `self`. + + ''' + P, T = self._to_perm_group() + perm_result = getattr(P, method_name)(*args) + single = False + if isinstance(perm_result, PermutationGroup): + perm_result, single = [perm_result], True + result = [] + for group in perm_result: + gens = group.generators + result.append(T.invert(gens)) + return result[0] if single else result + + def derived_series(self): + ''' + Return the list of lists containing the generators + of the subgroups in the derived series of `self`. + + ''' + return self._perm_group_list('derived_series') + + def lower_central_series(self): + ''' + Return the list of lists containing the generators + of the subgroups in the lower central series of `self`. + + ''' + return self._perm_group_list('lower_central_series') + + def center(self): + ''' + Return the list of generators of the center of `self`. + + ''' + return self._perm_group_list('center') + + + def derived_subgroup(self): + ''' + Return the list of generators of the derived subgroup of `self`. + + ''' + return self._perm_group_list('derived_subgroup') + + + def centralizer(self, other): + ''' + Return the list of generators of the centralizer of `other` + (a list of elements of `self`) in `self`. + + ''' + T = self._to_perm_group()[1] + other = T(other) + return self._perm_group_list('centralizer', other) + + def normal_closure(self, other): + ''' + Return the list of generators of the normal closure of `other` + (a list of elements of `self`) in `self`. + + ''' + T = self._to_perm_group()[1] + other = T(other) + return self._perm_group_list('normal_closure', other) + + def _perm_property(self, attr): + ''' + Given an attribute of a `PermutationGroup`, return + its value for a permutation group isomorphic to `self`. + + ''' + P = self._to_perm_group()[0] + return getattr(P, attr) + + @property + def is_abelian(self): + ''' + Check if `self` is abelian. + + ''' + return self._perm_property("is_abelian") + + @property + def is_nilpotent(self): + ''' + Check if `self` is nilpotent. + + ''' + return self._perm_property("is_nilpotent") + + @property + def is_solvable(self): + ''' + Check if `self` is solvable. + + ''' + return self._perm_property("is_solvable") + + @property + def elements(self): + ''' + List the elements of `self`. + + ''' + P, T = self._to_perm_group() + return T.invert(P.elements) + + @property + def is_cyclic(self): + """ + Return ``True`` if group is Cyclic. + + """ + if len(self.generators) <= 1: + return True + try: + P, T = self._to_perm_group() + except NotImplementedError: + raise NotImplementedError("Check for infinite Cyclic group " + "is not implemented") + return P.is_cyclic + + def abelian_invariants(self): + """ + Return Abelian Invariants of a group. + """ + try: + P, T = self._to_perm_group() + except NotImplementedError: + raise NotImplementedError("abelian invariants is not implemented" + "for infinite group") + return P.abelian_invariants() + + def composition_series(self): + """ + Return subnormal series of maximum length for a group. + """ + try: + P, T = self._to_perm_group() + except NotImplementedError: + raise NotImplementedError("composition series is not implemented" + "for infinite group") + return P.composition_series() + + +class FpSubgroup(DefaultPrinting): + ''' + The class implementing a subgroup of an FpGroup or a FreeGroup + (only finite index subgroups are supported at this point). This + is to be used if one wishes to check if an element of the original + group belongs to the subgroup + + ''' + def __init__(self, G, gens, normal=False): + super().__init__() + self.parent = G + self.generators = list({g for g in gens if g != G.identity}) + self._min_words = None #for use in __contains__ + self.C = None + self.normal = normal + + def __contains__(self, g): + + if isinstance(self.parent, FreeGroup): + if self._min_words is None: + # make _min_words - a list of subwords such that + # g is in the subgroup if and only if it can be + # partitioned into these subwords. Infinite families of + # subwords are presented by tuples, e.g. (r, w) + # stands for the family of subwords r*w**n*r**-1 + + def _process(w): + # this is to be used before adding new words + # into _min_words; if the word w is not cyclically + # reduced, it will generate an infinite family of + # subwords so should be written as a tuple; + # if it is, w**-1 should be added to the list + # as well + p, r = w.cyclic_reduction(removed=True) + if not r.is_identity: + return [(r, p)] + else: + return [w, w**-1] + + # make the initial list + gens = [] + for w in self.generators: + if self.normal: + w = w.cyclic_reduction() + gens.extend(_process(w)) + + for w1 in gens: + for w2 in gens: + # if w1 and w2 are equal or are inverses, continue + if w1 == w2 or (not isinstance(w1, tuple) + and w1**-1 == w2): + continue + + # if the start of one word is the inverse of the + # end of the other, their multiple should be added + # to _min_words because of cancellation + if isinstance(w1, tuple): + # start, end + s1, s2 = w1[0][0], w1[0][0]**-1 + else: + s1, s2 = w1[0], w1[len(w1)-1] + + if isinstance(w2, tuple): + # start, end + r1, r2 = w2[0][0], w2[0][0]**-1 + else: + r1, r2 = w2[0], w2[len(w1)-1] + + # p1 and p2 are w1 and w2 or, in case when + # w1 or w2 is an infinite family, a representative + p1, p2 = w1, w2 + if isinstance(w1, tuple): + p1 = w1[0]*w1[1]*w1[0]**-1 + if isinstance(w2, tuple): + p2 = w2[0]*w2[1]*w2[0]**-1 + + # add the product of the words to the list is necessary + if r1**-1 == s2 and not (p1*p2).is_identity: + new = _process(p1*p2) + if new not in gens: + gens.extend(new) + + if r2**-1 == s1 and not (p2*p1).is_identity: + new = _process(p2*p1) + if new not in gens: + gens.extend(new) + + self._min_words = gens + + min_words = self._min_words + + def _is_subword(w): + # check if w is a word in _min_words or one of + # the infinite families in it + w, r = w.cyclic_reduction(removed=True) + if r.is_identity or self.normal: + return w in min_words + else: + t = [s[1] for s in min_words if isinstance(s, tuple) + and s[0] == r] + return [s for s in t if w.power_of(s)] != [] + + # store the solution of words for which the result of + # _word_break (below) is known + known = {} + + def _word_break(w): + # check if w can be written as a product of words + # in min_words + if len(w) == 0: + return True + i = 0 + while i < len(w): + i += 1 + prefix = w.subword(0, i) + if not _is_subword(prefix): + continue + rest = w.subword(i, len(w)) + if rest not in known: + known[rest] = _word_break(rest) + if known[rest]: + return True + return False + + if self.normal: + g = g.cyclic_reduction() + return _word_break(g) + else: + if self.C is None: + C = self.parent.coset_enumeration(self.generators) + self.C = C + i = 0 + C = self.C + for j in range(len(g)): + i = C.table[i][C.A_dict[g[j]]] + return i == 0 + + def order(self): + if not self.generators: + return S.One + if isinstance(self.parent, FreeGroup): + return S.Infinity + if self.C is None: + C = self.parent.coset_enumeration(self.generators) + self.C = C + # This is valid because `len(self.C.table)` (the index of the subgroup) + # will always be finite - otherwise coset enumeration doesn't terminate + return self.parent.order()/len(self.C.table) + + def to_FpGroup(self): + if isinstance(self.parent, FreeGroup): + gen_syms = [('x_%d'%i) for i in range(len(self.generators))] + return free_group(', '.join(gen_syms))[0] + return self.parent.subgroup(C=self.C) + + def __str__(self): + if len(self.generators) > 30: + str_form = "" % len(self.generators) + else: + str_form = "" % str(self.generators) + return str_form + + __repr__ = __str__ + + +############################################################################### +# LOW INDEX SUBGROUPS # +############################################################################### + +def low_index_subgroups(G, N, Y=()): + """ + Implements the Low Index Subgroups algorithm, i.e find all subgroups of + ``G`` upto a given index ``N``. This implements the method described in + [Sim94]. This procedure involves a backtrack search over incomplete Coset + Tables, rather than over forced coincidences. + + Parameters + ========== + + G: An FpGroup < X|R > + N: positive integer, representing the maximum index value for subgroups + Y: (an optional argument) specifying a list of subgroup generators, such + that each of the resulting subgroup contains the subgroup generated by Y. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, low_index_subgroups + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**2, y**3, (x*y)**4]) + >>> L = low_index_subgroups(f, 4) + >>> for coset_table in L: + ... print(coset_table.table) + [[0, 0, 0, 0]] + [[0, 0, 1, 2], [1, 1, 2, 0], [3, 3, 0, 1], [2, 2, 3, 3]] + [[0, 0, 1, 2], [2, 2, 2, 0], [1, 1, 0, 1]] + [[1, 1, 0, 0], [0, 0, 1, 1]] + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of Computational Group Theory" + Section 5.4 + + .. [2] Marston Conder and Peter Dobcsanyi + "Applications and Adaptions of the Low Index Subgroups Procedure" + + """ + C = CosetTable(G, []) + R = G.relators + # length chosen for the length of the short relators + len_short_rel = 5 + # elements of R2 only checked at the last step for complete + # coset tables + R2 = {rel for rel in R if len(rel) > len_short_rel} + # elements of R1 are used in inner parts of the process to prune + # branches of the search tree, + R1 = {rel.identity_cyclic_reduction() for rel in set(R) - R2} + R1_c_list = C.conjugates(R1) + S = [] + descendant_subgroups(S, C, R1_c_list, C.A[0], R2, N, Y) + return S + + +def descendant_subgroups(S, C, R1_c_list, x, R2, N, Y): + A_dict = C.A_dict + A_dict_inv = C.A_dict_inv + if C.is_complete(): + # if C is complete then it only needs to test + # whether the relators in R2 are satisfied + for w, alpha in product(R2, C.omega): + if not C.scan_check(alpha, w): + return + # relators in R2 are satisfied, append the table to list + S.append(C) + else: + # find the first undefined entry in Coset Table + for alpha, x in product(range(len(C.table)), C.A): + if C.table[alpha][A_dict[x]] is None: + # this is "x" in pseudo-code (using "y" makes it clear) + undefined_coset, undefined_gen = alpha, x + break + # for filling up the undefine entry we try all possible values + # of beta in Omega or beta = n where beta^(undefined_gen^-1) is undefined + reach = C.omega + [C.n] + for beta in reach: + if beta < N: + if beta == C.n or C.table[beta][A_dict_inv[undefined_gen]] is None: + try_descendant(S, C, R1_c_list, R2, N, undefined_coset, \ + undefined_gen, beta, Y) + + +def try_descendant(S, C, R1_c_list, R2, N, alpha, x, beta, Y): + r""" + Solves the problem of trying out each individual possibility + for `\alpha^x. + + """ + D = C.copy() + if beta == D.n and beta < N: + D.table.append([None]*len(D.A)) + D.p.append(beta) + D.table[alpha][D.A_dict[x]] = beta + D.table[beta][D.A_dict_inv[x]] = alpha + D.deduction_stack.append((alpha, x)) + if not D.process_deductions_check(R1_c_list[D.A_dict[x]], \ + R1_c_list[D.A_dict_inv[x]]): + return + for w in Y: + if not D.scan_check(0, w): + return + if first_in_class(D, Y): + descendant_subgroups(S, D, R1_c_list, x, R2, N, Y) + + +def first_in_class(C, Y=()): + """ + Checks whether the subgroup ``H=G1`` corresponding to the Coset Table + could possibly be the canonical representative of its conjugacy class. + + Parameters + ========== + + C: CosetTable + + Returns + ======= + + bool: True/False + + If this returns False, then no descendant of C can have that property, and + so we can abandon C. If it returns True, then we need to process further + the node of the search tree corresponding to C, and so we call + ``descendant_subgroups`` recursively on C. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, CosetTable, first_in_class + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**2, y**3, (x*y)**4]) + >>> C = CosetTable(f, []) + >>> C.table = [[0, 0, None, None]] + >>> first_in_class(C) + True + >>> C.table = [[1, 1, 1, None], [0, 0, None, 1]]; C.p = [0, 1] + >>> first_in_class(C) + True + >>> C.table = [[1, 1, 2, 1], [0, 0, 0, None], [None, None, None, 0]] + >>> C.p = [0, 1, 2] + >>> first_in_class(C) + False + >>> C.table = [[1, 1, 1, 2], [0, 0, 2, 0], [2, None, 0, 1]] + >>> first_in_class(C) + False + + # TODO:: Sims points out in [Sim94] that performance can be improved by + # remembering some of the information computed by ``first_in_class``. If + # the ``continue alpha`` statement is executed at line 14, then the same thing + # will happen for that value of alpha in any descendant of the table C, and so + # the values the values of alpha for which this occurs could profitably be + # stored and passed through to the descendants of C. Of course this would + # make the code more complicated. + + # The code below is taken directly from the function on page 208 of [Sim94] + # nu[alpha] + + """ + n = C.n + # lamda is the largest numbered point in Omega_c_alpha which is currently defined + lamda = -1 + # for alpha in Omega_c, nu[alpha] is the point in Omega_c_alpha corresponding to alpha + nu = [None]*n + # for alpha in Omega_c_alpha, mu[alpha] is the point in Omega_c corresponding to alpha + mu = [None]*n + # mutually nu and mu are the mutually-inverse equivalence maps between + # Omega_c_alpha and Omega_c + next_alpha = False + # For each 0!=alpha in [0 .. nc-1], we start by constructing the equivalent + # standardized coset table C_alpha corresponding to H_alpha + for alpha in range(1, n): + # reset nu to "None" after previous value of alpha + for beta in range(lamda+1): + nu[mu[beta]] = None + # we only want to reject our current table in favour of a preceding + # table in the ordering in which 1 is replaced by alpha, if the subgroup + # G_alpha corresponding to this preceding table definitely contains the + # given subgroup + for w in Y: + # TODO: this should support input of a list of general words + # not just the words which are in "A" (i.e gen and gen^-1) + if C.table[alpha][C.A_dict[w]] != alpha: + # continue with alpha + next_alpha = True + break + if next_alpha: + next_alpha = False + continue + # try alpha as the new point 0 in Omega_C_alpha + mu[0] = alpha + nu[alpha] = 0 + # compare corresponding entries in C and C_alpha + lamda = 0 + for beta in range(n): + for x in C.A: + gamma = C.table[beta][C.A_dict[x]] + delta = C.table[mu[beta]][C.A_dict[x]] + # if either of the entries is undefined, + # we move with next alpha + if gamma is None or delta is None: + # continue with alpha + next_alpha = True + break + if nu[delta] is None: + # delta becomes the next point in Omega_C_alpha + lamda += 1 + nu[delta] = lamda + mu[lamda] = delta + if nu[delta] < gamma: + return False + if nu[delta] > gamma: + # continue with alpha + next_alpha = True + break + if next_alpha: + next_alpha = False + break + return True + +#======================================================================== +# Simplifying Presentation +#======================================================================== + +def simplify_presentation(*args, change_gens=False): + ''' + For an instance of `FpGroup`, return a simplified isomorphic copy of + the group (e.g. remove redundant generators or relators). Alternatively, + a list of generators and relators can be passed in which case the + simplified lists will be returned. + + By default, the generators of the group are unchanged. If you would + like to remove redundant generators, set the keyword argument + `change_gens = True`. + + ''' + if len(args) == 1: + if not isinstance(args[0], FpGroup): + raise TypeError("The argument must be an instance of FpGroup") + G = args[0] + gens, rels = simplify_presentation(G.generators, G.relators, + change_gens=change_gens) + if gens: + return FpGroup(gens[0].group, rels) + return FpGroup(FreeGroup([]), []) + elif len(args) == 2: + gens, rels = args[0][:], args[1][:] + if not gens: + return gens, rels + identity = gens[0].group.identity + else: + if len(args) == 0: + m = "Not enough arguments" + else: + m = "Too many arguments" + raise RuntimeError(m) + + prev_gens = [] + prev_rels = [] + while not set(prev_rels) == set(rels): + prev_rels = rels + while change_gens and not set(prev_gens) == set(gens): + prev_gens = gens + gens, rels = elimination_technique_1(gens, rels, identity) + rels = _simplify_relators(rels) + + if change_gens: + syms = [g.array_form[0][0] for g in gens] + F = free_group(syms)[0] + identity = F.identity + gens = F.generators + subs = dict(zip(syms, gens)) + for j, r in enumerate(rels): + a = r.array_form + rel = identity + for sym, p in a: + rel = rel*subs[sym]**p + rels[j] = rel + return gens, rels + +def _simplify_relators(rels): + """ + Simplifies a set of relators. All relators are checked to see if they are + of the form `gen^n`. If any such relators are found then all other relators + are processed for strings in the `gen` known order. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import _simplify_relators + >>> F, x, y = free_group("x, y") + >>> w1 = [x**2*y**4, x**3] + >>> _simplify_relators(w1) + [x**3, x**-1*y**4] + + >>> w2 = [x**2*y**-4*x**5, x**3, x**2*y**8, y**5] + >>> _simplify_relators(w2) + [x**-1*y**-2, x**-1*y*x**-1, x**3, y**5] + + >>> w3 = [x**6*y**4, x**4] + >>> _simplify_relators(w3) + [x**4, x**2*y**4] + + >>> w4 = [x**2, x**5, y**3] + >>> _simplify_relators(w4) + [x, y**3] + + """ + rels = rels[:] + + if not rels: + return [] + + identity = rels[0].group.identity + + # build dictionary with "gen: n" where gen^n is one of the relators + exps = {} + for i in range(len(rels)): + rel = rels[i] + if rel.number_syllables() == 1: + g = rel[0] + exp = abs(rel.array_form[0][1]) + if rel.array_form[0][1] < 0: + rels[i] = rels[i]**-1 + g = g**-1 + if g in exps: + exp = gcd(exp, exps[g].array_form[0][1]) + exps[g] = g**exp + + one_syllables_words = list(exps.values()) + # decrease some of the exponents in relators, making use of the single + # syllable relators + for i, rel in enumerate(rels): + if rel in one_syllables_words: + continue + rel = rel.eliminate_words(one_syllables_words, _all = True) + # if rels[i] contains g**n where abs(n) is greater than half of the power p + # of g in exps, g**n can be replaced by g**(n-p) (or g**(p-n) if n<0) + for g in rel.contains_generators(): + if g in exps: + exp = exps[g].array_form[0][1] + max_exp = (exp + 1)//2 + rel = rel.eliminate_word(g**(max_exp), g**(max_exp-exp), _all = True) + rel = rel.eliminate_word(g**(-max_exp), g**(-(max_exp-exp)), _all = True) + rels[i] = rel + + rels = [r.identity_cyclic_reduction() for r in rels] + + rels += one_syllables_words # include one_syllable_words in the list of relators + rels = list(set(rels)) # get unique values in rels + rels.sort() + + # remove entries in rels + try: + rels.remove(identity) + except ValueError: + pass + return rels + +# Pg 350, section 2.5.1 from [2] +def elimination_technique_1(gens, rels, identity): + rels = rels[:] + # the shorter relators are examined first so that generators selected for + # elimination will have shorter strings as equivalent + rels.sort() + gens = gens[:] + redundant_gens = {} + redundant_rels = [] + used_gens = set() + # examine each relator in relator list for any generator occurring exactly + # once + for rel in rels: + # don't look for a redundant generator in a relator which + # depends on previously found ones + contained_gens = rel.contains_generators() + if any(g in contained_gens for g in redundant_gens): + continue + contained_gens = list(contained_gens) + contained_gens.sort(reverse = True) + for gen in contained_gens: + if rel.generator_count(gen) == 1 and gen not in used_gens: + k = rel.exponent_sum(gen) + gen_index = rel.index(gen**k) + bk = rel.subword(gen_index + 1, len(rel)) + fw = rel.subword(0, gen_index) + chi = bk*fw + redundant_gens[gen] = chi**(-1*k) + used_gens.update(chi.contains_generators()) + redundant_rels.append(rel) + break + rels = [r for r in rels if r not in redundant_rels] + # eliminate the redundant generators from remaining relators + rels = [r.eliminate_words(redundant_gens, _all = True).identity_cyclic_reduction() for r in rels] + rels = list(set(rels)) + try: + rels.remove(identity) + except ValueError: + pass + gens = [g for g in gens if g not in redundant_gens] + return gens, rels + +############################################################################### +# SUBGROUP PRESENTATIONS # +############################################################################### + +# Pg 175 [1] +def define_schreier_generators(C, homomorphism=False): + ''' + Parameters + ========== + + C -- Coset table. + homomorphism -- When set to True, return a dictionary containing the images + of the presentation generators in the original group. + ''' + y = [] + gamma = 1 + f = C.fp_group + X = f.generators + if homomorphism: + # `_gens` stores the elements of the parent group to + # to which the schreier generators correspond to. + _gens = {} + # compute the schreier Traversal + tau = {} + tau[0] = f.identity + C.P = [[None]*len(C.A) for i in range(C.n)] + for alpha, x in product(C.omega, C.A): + beta = C.table[alpha][C.A_dict[x]] + if beta == gamma: + C.P[alpha][C.A_dict[x]] = "" + C.P[beta][C.A_dict_inv[x]] = "" + gamma += 1 + if homomorphism: + tau[beta] = tau[alpha]*x + elif x in X and C.P[alpha][C.A_dict[x]] is None: + y_alpha_x = '%s_%s' % (x, alpha) + y.append(y_alpha_x) + C.P[alpha][C.A_dict[x]] = y_alpha_x + if homomorphism: + _gens[y_alpha_x] = tau[alpha]*x*tau[beta]**-1 + grp_gens = list(free_group(', '.join(y))) + C._schreier_free_group = grp_gens.pop(0) + C._schreier_generators = grp_gens + if homomorphism: + C._schreier_gen_elem = _gens + # replace all elements of P by, free group elements + for i, j in product(range(len(C.P)), range(len(C.A))): + # if equals "", replace by identity element + if C.P[i][j] == "": + C.P[i][j] = C._schreier_free_group.identity + elif isinstance(C.P[i][j], str): + r = C._schreier_generators[y.index(C.P[i][j])] + C.P[i][j] = r + beta = C.table[i][j] + C.P[beta][j + 1] = r**-1 + +def reidemeister_relators(C): + R = C.fp_group.relators + rels = [rewrite(C, coset, word) for word in R for coset in range(C.n)] + order_1_gens = {i for i in rels if len(i) == 1} + + # remove all the order 1 generators from relators + rels = list(filter(lambda rel: rel not in order_1_gens, rels)) + + # replace order 1 generators by identity element in reidemeister relators + for i in range(len(rels)): + w = rels[i] + w = w.eliminate_words(order_1_gens, _all=True) + rels[i] = w + + C._schreier_generators = [i for i in C._schreier_generators + if not (i in order_1_gens or i**-1 in order_1_gens)] + + # Tietze transformation 1 i.e TT_1 + # remove cyclic conjugate elements from relators + i = 0 + while i < len(rels): + w = rels[i] + j = i + 1 + while j < len(rels): + if w.is_cyclic_conjugate(rels[j]): + del rels[j] + else: + j += 1 + i += 1 + + C._reidemeister_relators = rels + + +def rewrite(C, alpha, w): + """ + Parameters + ========== + + C: CosetTable + alpha: A live coset + w: A word in `A*` + + Returns + ======= + + rho(tau(alpha), w) + + Examples + ======== + + >>> from sympy.combinatorics.fp_groups import FpGroup, CosetTable, define_schreier_generators, rewrite + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**2, y**3, (x*y)**6]) + >>> C = CosetTable(f, []) + >>> C.table = [[1, 1, 2, 3], [0, 0, 4, 5], [4, 4, 3, 0], [5, 5, 0, 2], [2, 2, 5, 1], [3, 3, 1, 4]] + >>> C.p = [0, 1, 2, 3, 4, 5] + >>> define_schreier_generators(C) + >>> rewrite(C, 0, (x*y)**6) + x_4*y_2*x_3*x_1*x_2*y_4*x_5 + + """ + v = C._schreier_free_group.identity + for i in range(len(w)): + x_i = w[i] + v = v*C.P[alpha][C.A_dict[x_i]] + alpha = C.table[alpha][C.A_dict[x_i]] + return v + +# Pg 350, section 2.5.2 from [2] +def elimination_technique_2(C): + """ + This technique eliminates one generator at a time. Heuristically this + seems superior in that we may select for elimination the generator with + shortest equivalent string at each stage. + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, coset_enumeration_r, \ + reidemeister_relators, define_schreier_generators, elimination_technique_2 + >>> F, x, y = free_group("x, y") + >>> f = FpGroup(F, [x**3, y**5, (x*y)**2]); H = [x*y, x**-1*y**-1*x*y*x] + >>> C = coset_enumeration_r(f, H) + >>> C.compress(); C.standardize() + >>> define_schreier_generators(C) + >>> reidemeister_relators(C) + >>> elimination_technique_2(C) + ([y_1, y_2], [y_2**-3, y_2*y_1*y_2*y_1*y_2*y_1, y_1**2]) + + """ + rels = C._reidemeister_relators + rels.sort(reverse=True) + gens = C._schreier_generators + for i in range(len(gens) - 1, -1, -1): + rel = rels[i] + for j in range(len(gens) - 1, -1, -1): + gen = gens[j] + if rel.generator_count(gen) == 1: + k = rel.exponent_sum(gen) + gen_index = rel.index(gen**k) + bk = rel.subword(gen_index + 1, len(rel)) + fw = rel.subword(0, gen_index) + rep_by = (bk*fw)**(-1*k) + del rels[i]; del gens[j] + for l in range(len(rels)): + rels[l] = rels[l].eliminate_word(gen, rep_by) + break + C._reidemeister_relators = rels + C._schreier_generators = gens + return C._schreier_generators, C._reidemeister_relators + +def reidemeister_presentation(fp_grp, H, C=None, homomorphism=False): + """ + Parameters + ========== + + fp_group: A finitely presented group, an instance of FpGroup + H: A subgroup whose presentation is to be found, given as a list + of words in generators of `fp_grp` + homomorphism: When set to True, return a homomorphism from the subgroup + to the parent group + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> from sympy.combinatorics.fp_groups import FpGroup, reidemeister_presentation + >>> F, x, y = free_group("x, y") + + Example 5.6 Pg. 177 from [1] + >>> f = FpGroup(F, [x**3, y**5, (x*y)**2]) + >>> H = [x*y, x**-1*y**-1*x*y*x] + >>> reidemeister_presentation(f, H) + ((y_1, y_2), (y_1**2, y_2**3, y_2*y_1*y_2*y_1*y_2*y_1)) + + Example 5.8 Pg. 183 from [1] + >>> f = FpGroup(F, [x**3, y**3, (x*y)**3]) + >>> H = [x*y, x*y**-1] + >>> reidemeister_presentation(f, H) + ((x_0, y_0), (x_0**3, y_0**3, x_0*y_0*x_0*y_0*x_0*y_0)) + + Exercises Q2. Pg 187 from [1] + >>> f = FpGroup(F, [x**2*y**2, y**-1*x*y*x**-3]) + >>> H = [x] + >>> reidemeister_presentation(f, H) + ((x_0,), (x_0**4,)) + + Example 5.9 Pg. 183 from [1] + >>> f = FpGroup(F, [x**3*y**-3, (x*y)**3, (x*y**-1)**2]) + >>> H = [x] + >>> reidemeister_presentation(f, H) + ((x_0,), (x_0**6,)) + + """ + if not C: + C = coset_enumeration_r(fp_grp, H) + C.compress(); C.standardize() + define_schreier_generators(C, homomorphism=homomorphism) + reidemeister_relators(C) + gens, rels = C._schreier_generators, C._reidemeister_relators + gens, rels = simplify_presentation(gens, rels, change_gens=True) + + C.schreier_generators = tuple(gens) + C.reidemeister_relators = tuple(rels) + + if homomorphism: + _gens = [] + for gen in gens: + _gens.append(C._schreier_gen_elem[str(gen)]) + return C.schreier_generators, C.reidemeister_relators, _gens + + return C.schreier_generators, C.reidemeister_relators + + +FpGroupElement = FreeGroupElement diff --git a/lib/python3.12/site-packages/sympy/combinatorics/free_groups.py b/lib/python3.12/site-packages/sympy/combinatorics/free_groups.py new file mode 100644 index 0000000000000000000000000000000000000000..53bd0f4d75a0dc5987cf91706390cdfa0bc048ed --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/free_groups.py @@ -0,0 +1,1354 @@ +from __future__ import annotations + +from sympy.core import S +from sympy.core.expr import Expr +from sympy.core.symbol import Symbol, symbols as _symbols +from sympy.core.sympify import CantSympify +from sympy.printing.defaults import DefaultPrinting +from sympy.utilities import public +from sympy.utilities.iterables import flatten, is_sequence +from sympy.utilities.magic import pollute +from sympy.utilities.misc import as_int + + +@public +def free_group(symbols): + """Construct a free group returning ``(FreeGroup, (f_0, f_1, ..., f_(n-1))``. + + Parameters + ========== + + symbols : str, Symbol/Expr or sequence of str, Symbol/Expr (may be empty) + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y, z = free_group("x, y, z") + >>> F + + >>> x**2*y**-1 + x**2*y**-1 + >>> type(_) + + + """ + _free_group = FreeGroup(symbols) + return (_free_group,) + tuple(_free_group.generators) + +@public +def xfree_group(symbols): + """Construct a free group returning ``(FreeGroup, (f_0, f_1, ..., f_(n-1)))``. + + Parameters + ========== + + symbols : str, Symbol/Expr or sequence of str, Symbol/Expr (may be empty) + + Examples + ======== + + >>> from sympy.combinatorics.free_groups import xfree_group + >>> F, (x, y, z) = xfree_group("x, y, z") + >>> F + + >>> y**2*x**-2*z**-1 + y**2*x**-2*z**-1 + >>> type(_) + + + """ + _free_group = FreeGroup(symbols) + return (_free_group, _free_group.generators) + +@public +def vfree_group(symbols): + """Construct a free group and inject ``f_0, f_1, ..., f_(n-1)`` as symbols + into the global namespace. + + Parameters + ========== + + symbols : str, Symbol/Expr or sequence of str, Symbol/Expr (may be empty) + + Examples + ======== + + >>> from sympy.combinatorics.free_groups import vfree_group + >>> vfree_group("x, y, z") + + >>> x**2*y**-2*z # noqa: F821 + x**2*y**-2*z + >>> type(_) + + + """ + _free_group = FreeGroup(symbols) + pollute([sym.name for sym in _free_group.symbols], _free_group.generators) + return _free_group + + +def _parse_symbols(symbols): + if not symbols: + return () + if isinstance(symbols, str): + return _symbols(symbols, seq=True) + elif isinstance(symbols, (Expr, FreeGroupElement)): + return (symbols,) + elif is_sequence(symbols): + if all(isinstance(s, str) for s in symbols): + return _symbols(symbols) + elif all(isinstance(s, Expr) for s in symbols): + return symbols + raise ValueError("The type of `symbols` must be one of the following: " + "a str, Symbol/Expr or a sequence of " + "one of these types") + + +############################################################################## +# FREE GROUP # +############################################################################## + +_free_group_cache: dict[int, FreeGroup] = {} + +class FreeGroup(DefaultPrinting): + """ + Free group with finite or infinite number of generators. Its input API + is that of a str, Symbol/Expr or a sequence of one of + these types (which may be empty) + + See Also + ======== + + sympy.polys.rings.PolyRing + + References + ========== + + .. [1] https://www.gap-system.org/Manuals/doc/ref/chap37.html + + .. [2] https://en.wikipedia.org/wiki/Free_group + + """ + is_associative = True + is_group = True + is_FreeGroup = True + is_PermutationGroup = False + relators: list[Expr] = [] + + def __new__(cls, symbols): + symbols = tuple(_parse_symbols(symbols)) + rank = len(symbols) + _hash = hash((cls.__name__, symbols, rank)) + obj = _free_group_cache.get(_hash) + + if obj is None: + obj = object.__new__(cls) + obj._hash = _hash + obj._rank = rank + # dtype method is used to create new instances of FreeGroupElement + obj.dtype = type("FreeGroupElement", (FreeGroupElement,), {"group": obj}) + obj.symbols = symbols + obj.generators = obj._generators() + obj._gens_set = set(obj.generators) + for symbol, generator in zip(obj.symbols, obj.generators): + if isinstance(symbol, Symbol): + name = symbol.name + if hasattr(obj, name): + setattr(obj, name, generator) + + _free_group_cache[_hash] = obj + + return obj + + def _generators(group): + """Returns the generators of the FreeGroup. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y, z = free_group("x, y, z") + >>> F.generators + (x, y, z) + + """ + gens = [] + for sym in group.symbols: + elm = ((sym, 1),) + gens.append(group.dtype(elm)) + return tuple(gens) + + def clone(self, symbols=None): + return self.__class__(symbols or self.symbols) + + def __contains__(self, i): + """Return True if ``i`` is contained in FreeGroup.""" + if not isinstance(i, FreeGroupElement): + return False + group = i.group + return self == group + + def __hash__(self): + return self._hash + + def __len__(self): + return self.rank + + def __str__(self): + if self.rank > 30: + str_form = "" % self.rank + else: + str_form = "" + return str_form + + __repr__ = __str__ + + def __getitem__(self, index): + symbols = self.symbols[index] + return self.clone(symbols=symbols) + + def __eq__(self, other): + """No ``FreeGroup`` is equal to any "other" ``FreeGroup``. + """ + return self is other + + def index(self, gen): + """Return the index of the generator `gen` from ``(f_0, ..., f_(n-1))``. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> F.index(y) + 1 + >>> F.index(x) + 0 + + """ + if isinstance(gen, self.dtype): + return self.generators.index(gen) + else: + raise ValueError("expected a generator of Free Group %s, got %s" % (self, gen)) + + def order(self): + """Return the order of the free group. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> F.order() + oo + + >>> free_group("")[0].order() + 1 + + """ + if self.rank == 0: + return S.One + else: + return S.Infinity + + @property + def elements(self): + """ + Return the elements of the free group. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> (z,) = free_group("") + >>> z.elements + {} + + """ + if self.rank == 0: + # A set containing Identity element of `FreeGroup` self is returned + return {self.identity} + else: + raise ValueError("Group contains infinitely many elements" + ", hence cannot be represented") + + @property + def rank(self): + r""" + In group theory, the `rank` of a group `G`, denoted `G.rank`, + can refer to the smallest cardinality of a generating set + for G, that is + + \operatorname{rank}(G)=\min\{ |X|: X\subseteq G, \left\langle X\right\rangle =G\}. + + """ + return self._rank + + @property + def is_abelian(self): + """Returns if the group is Abelian. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y, z = free_group("x y z") + >>> f.is_abelian + False + + """ + return self.rank in (0, 1) + + @property + def identity(self): + """Returns the identity element of free group.""" + return self.dtype() + + def contains(self, g): + """Tests if Free Group element ``g`` belong to self, ``G``. + + In mathematical terms any linear combination of generators + of a Free Group is contained in it. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y, z = free_group("x y z") + >>> f.contains(x**3*y**2) + True + + """ + if not isinstance(g, FreeGroupElement): + return False + elif self != g.group: + return False + else: + return True + + def center(self): + """Returns the center of the free group `self`.""" + return {self.identity} + + +############################################################################ +# FreeGroupElement # +############################################################################ + + +class FreeGroupElement(CantSympify, DefaultPrinting, tuple): + """Used to create elements of FreeGroup. It cannot be used directly to + create a free group element. It is called by the `dtype` method of the + `FreeGroup` class. + + """ + is_assoc_word = True + + def new(self, init): + return self.__class__(init) + + _hash = None + + def __hash__(self): + _hash = self._hash + if _hash is None: + self._hash = _hash = hash((self.group, frozenset(tuple(self)))) + return _hash + + def copy(self): + return self.new(self) + + @property + def is_identity(self): + if self.array_form == (): + return True + else: + return False + + @property + def array_form(self): + """ + SymPy provides two different internal kinds of representation + of associative words. The first one is called the `array_form` + which is a tuple containing `tuples` as its elements, where the + size of each tuple is two. At the first position the tuple + contains the `symbol-generator`, while at the second position + of tuple contains the exponent of that generator at the position. + Since elements (i.e. words) do not commute, the indexing of tuple + makes that property to stay. + + The structure in ``array_form`` of ``FreeGroupElement`` is of form: + + ``( ( symbol_of_gen, exponent ), ( , ), ... ( , ) )`` + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y, z = free_group("x y z") + >>> (x*z).array_form + ((x, 1), (z, 1)) + >>> (x**2*z*y*x**2).array_form + ((x, 2), (z, 1), (y, 1), (x, 2)) + + See Also + ======== + + letter_repr + + """ + return tuple(self) + + @property + def letter_form(self): + """ + The letter representation of a ``FreeGroupElement`` is a tuple + of generator symbols, with each entry corresponding to a group + generator. Inverses of the generators are represented by + negative generator symbols. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b, c, d = free_group("a b c d") + >>> (a**3).letter_form + (a, a, a) + >>> (a**2*d**-2*a*b**-4).letter_form + (a, a, -d, -d, a, -b, -b, -b, -b) + >>> (a**-2*b**3*d).letter_form + (-a, -a, b, b, b, d) + + See Also + ======== + + array_form + + """ + return tuple(flatten([(i,)*j if j > 0 else (-i,)*(-j) + for i, j in self.array_form])) + + def __getitem__(self, i): + group = self.group + r = self.letter_form[i] + if r.is_Symbol: + return group.dtype(((r, 1),)) + else: + return group.dtype(((-r, -1),)) + + def index(self, gen): + if len(gen) != 1: + raise ValueError() + return (self.letter_form).index(gen.letter_form[0]) + + @property + def letter_form_elm(self): + """ + """ + group = self.group + r = self.letter_form + return [group.dtype(((elm,1),)) if elm.is_Symbol \ + else group.dtype(((-elm,-1),)) for elm in r] + + @property + def ext_rep(self): + """This is called the External Representation of ``FreeGroupElement`` + """ + return tuple(flatten(self.array_form)) + + def __contains__(self, gen): + return gen.array_form[0][0] in tuple([r[0] for r in self.array_form]) + + def __str__(self): + if self.is_identity: + return "" + + str_form = "" + array_form = self.array_form + for i in range(len(array_form)): + if i == len(array_form) - 1: + if array_form[i][1] == 1: + str_form += str(array_form[i][0]) + else: + str_form += str(array_form[i][0]) + \ + "**" + str(array_form[i][1]) + else: + if array_form[i][1] == 1: + str_form += str(array_form[i][0]) + "*" + else: + str_form += str(array_form[i][0]) + \ + "**" + str(array_form[i][1]) + "*" + return str_form + + __repr__ = __str__ + + def __pow__(self, n): + n = as_int(n) + result = self.group.identity + if n == 0: + return result + if n < 0: + n = -n + x = self.inverse() + else: + x = self + while True: + if n % 2: + result *= x + n >>= 1 + if not n: + break + x *= x + return result + + def __mul__(self, other): + """Returns the product of elements belonging to the same ``FreeGroup``. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y, z = free_group("x y z") + >>> x*y**2*y**-4 + x*y**-2 + >>> z*y**-2 + z*y**-2 + >>> x**2*y*y**-1*x**-2 + + + """ + group = self.group + if not isinstance(other, group.dtype): + raise TypeError("only FreeGroup elements of same FreeGroup can " + "be multiplied") + if self.is_identity: + return other + if other.is_identity: + return self + r = list(self.array_form + other.array_form) + zero_mul_simp(r, len(self.array_form) - 1) + return group.dtype(tuple(r)) + + def __truediv__(self, other): + group = self.group + if not isinstance(other, group.dtype): + raise TypeError("only FreeGroup elements of same FreeGroup can " + "be multiplied") + return self*(other.inverse()) + + def __rtruediv__(self, other): + group = self.group + if not isinstance(other, group.dtype): + raise TypeError("only FreeGroup elements of same FreeGroup can " + "be multiplied") + return other*(self.inverse()) + + def __add__(self, other): + return NotImplemented + + def inverse(self): + """ + Returns the inverse of a ``FreeGroupElement`` element + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y, z = free_group("x y z") + >>> x.inverse() + x**-1 + >>> (x*y).inverse() + y**-1*x**-1 + + """ + group = self.group + r = tuple([(i, -j) for i, j in self.array_form[::-1]]) + return group.dtype(r) + + def order(self): + """Find the order of a ``FreeGroupElement``. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y = free_group("x y") + >>> (x**2*y*y**-1*x**-2).order() + 1 + + """ + if self.is_identity: + return S.One + else: + return S.Infinity + + def commutator(self, other): + """ + Return the commutator of `self` and `x`: ``~x*~self*x*self`` + + """ + group = self.group + if not isinstance(other, group.dtype): + raise ValueError("commutator of only FreeGroupElement of the same " + "FreeGroup exists") + else: + return self.inverse()*other.inverse()*self*other + + def eliminate_words(self, words, _all=False, inverse=True): + ''' + Replace each subword from the dictionary `words` by words[subword]. + If words is a list, replace the words by the identity. + + ''' + again = True + new = self + if isinstance(words, dict): + while again: + again = False + for sub in words: + prev = new + new = new.eliminate_word(sub, words[sub], _all=_all, inverse=inverse) + if new != prev: + again = True + else: + while again: + again = False + for sub in words: + prev = new + new = new.eliminate_word(sub, _all=_all, inverse=inverse) + if new != prev: + again = True + return new + + def eliminate_word(self, gen, by=None, _all=False, inverse=True): + """ + For an associative word `self`, a subword `gen`, and an associative + word `by` (identity by default), return the associative word obtained by + replacing each occurrence of `gen` in `self` by `by`. If `_all = True`, + the occurrences of `gen` that may appear after the first substitution will + also be replaced and so on until no occurrences are found. This might not + always terminate (e.g. `(x).eliminate_word(x, x**2, _all=True)`). + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y = free_group("x y") + >>> w = x**5*y*x**2*y**-4*x + >>> w.eliminate_word( x, x**2 ) + x**10*y*x**4*y**-4*x**2 + >>> w.eliminate_word( x, y**-1 ) + y**-11 + >>> w.eliminate_word(x**5) + y*x**2*y**-4*x + >>> w.eliminate_word(x*y, y) + x**4*y*x**2*y**-4*x + + See Also + ======== + substituted_word + + """ + if by is None: + by = self.group.identity + if self.is_independent(gen) or gen == by: + return self + if gen == self: + return by + if gen**-1 == by: + _all = False + word = self + l = len(gen) + + try: + i = word.subword_index(gen) + k = 1 + except ValueError: + if not inverse: + return word + try: + i = word.subword_index(gen**-1) + k = -1 + except ValueError: + return word + + word = word.subword(0, i)*by**k*word.subword(i+l, len(word)).eliminate_word(gen, by) + + if _all: + return word.eliminate_word(gen, by, _all=True, inverse=inverse) + else: + return word + + def __len__(self): + """ + For an associative word `self`, returns the number of letters in it. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b = free_group("a b") + >>> w = a**5*b*a**2*b**-4*a + >>> len(w) + 13 + >>> len(a**17) + 17 + >>> len(w**0) + 0 + + """ + return sum(abs(j) for (i, j) in self) + + def __eq__(self, other): + """ + Two associative words are equal if they are words over the + same alphabet and if they are sequences of the same letters. + This is equivalent to saying that the external representations + of the words are equal. + There is no "universal" empty word, every alphabet has its own + empty word. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, swapnil0, swapnil1 = free_group("swapnil0 swapnil1") + >>> f + + >>> g, swap0, swap1 = free_group("swap0 swap1") + >>> g + + + >>> swapnil0 == swapnil1 + False + >>> swapnil0*swapnil1 == swapnil1/swapnil1*swapnil0*swapnil1 + True + >>> swapnil0*swapnil1 == swapnil1*swapnil0 + False + >>> swapnil1**0 == swap0**0 + False + + """ + group = self.group + if not isinstance(other, group.dtype): + return False + return tuple.__eq__(self, other) + + def __lt__(self, other): + """ + The ordering of associative words is defined by length and + lexicography (this ordering is called short-lex ordering), that + is, shorter words are smaller than longer words, and words of the + same length are compared w.r.t. the lexicographical ordering induced + by the ordering of generators. Generators are sorted according + to the order in which they were created. If the generators are + invertible then each generator `g` is larger than its inverse `g^{-1}`, + and `g^{-1}` is larger than every generator that is smaller than `g`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b = free_group("a b") + >>> b < a + False + >>> a < a.inverse() + False + + """ + group = self.group + if not isinstance(other, group.dtype): + raise TypeError("only FreeGroup elements of same FreeGroup can " + "be compared") + l = len(self) + m = len(other) + # implement lenlex order + if l < m: + return True + elif l > m: + return False + for i in range(l): + a = self[i].array_form[0] + b = other[i].array_form[0] + p = group.symbols.index(a[0]) + q = group.symbols.index(b[0]) + if p < q: + return True + elif p > q: + return False + elif a[1] < b[1]: + return True + elif a[1] > b[1]: + return False + return False + + def __le__(self, other): + return (self == other or self < other) + + def __gt__(self, other): + """ + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, x, y, z = free_group("x y z") + >>> y**2 > x**2 + True + >>> y*z > z*y + False + >>> x > x.inverse() + True + + """ + group = self.group + if not isinstance(other, group.dtype): + raise TypeError("only FreeGroup elements of same FreeGroup can " + "be compared") + return not self <= other + + def __ge__(self, other): + return not self < other + + def exponent_sum(self, gen): + """ + For an associative word `self` and a generator or inverse of generator + `gen`, ``exponent_sum`` returns the number of times `gen` appears in + `self` minus the number of times its inverse appears in `self`. If + neither `gen` nor its inverse occur in `self` then 0 is returned. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> w = x**2*y**3 + >>> w.exponent_sum(x) + 2 + >>> w.exponent_sum(x**-1) + -2 + >>> w = x**2*y**4*x**-3 + >>> w.exponent_sum(x) + -1 + + See Also + ======== + + generator_count + + """ + if len(gen) != 1: + raise ValueError("gen must be a generator or inverse of a generator") + s = gen.array_form[0] + return s[1]*sum(i[1] for i in self.array_form if i[0] == s[0]) + + def generator_count(self, gen): + """ + For an associative word `self` and a generator `gen`, + ``generator_count`` returns the multiplicity of generator + `gen` in `self`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> w = x**2*y**3 + >>> w.generator_count(x) + 2 + >>> w = x**2*y**4*x**-3 + >>> w.generator_count(x) + 5 + + See Also + ======== + + exponent_sum + + """ + if len(gen) != 1 or gen.array_form[0][1] < 0: + raise ValueError("gen must be a generator") + s = gen.array_form[0] + return s[1]*sum(abs(i[1]) for i in self.array_form if i[0] == s[0]) + + def subword(self, from_i, to_j, strict=True): + """ + For an associative word `self` and two positive integers `from_i` and + `to_j`, `subword` returns the subword of `self` that begins at position + `from_i` and ends at `to_j - 1`, indexing is done with origin 0. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b = free_group("a b") + >>> w = a**5*b*a**2*b**-4*a + >>> w.subword(2, 6) + a**3*b + + """ + group = self.group + if not strict: + from_i = max(from_i, 0) + to_j = min(len(self), to_j) + if from_i < 0 or to_j > len(self): + raise ValueError("`from_i`, `to_j` must be positive and no greater than " + "the length of associative word") + if to_j <= from_i: + return group.identity + else: + letter_form = self.letter_form[from_i: to_j] + array_form = letter_form_to_array_form(letter_form, group) + return group.dtype(array_form) + + def subword_index(self, word, start = 0): + ''' + Find the index of `word` in `self`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b = free_group("a b") + >>> w = a**2*b*a*b**3 + >>> w.subword_index(a*b*a*b) + 1 + + ''' + l = len(word) + self_lf = self.letter_form + word_lf = word.letter_form + index = None + for i in range(start,len(self_lf)-l+1): + if self_lf[i:i+l] == word_lf: + index = i + break + if index is not None: + return index + else: + raise ValueError("The given word is not a subword of self") + + def is_dependent(self, word): + """ + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> (x**4*y**-3).is_dependent(x**4*y**-2) + True + >>> (x**2*y**-1).is_dependent(x*y) + False + >>> (x*y**2*x*y**2).is_dependent(x*y**2) + True + >>> (x**12).is_dependent(x**-4) + True + + See Also + ======== + + is_independent + + """ + try: + return self.subword_index(word) is not None + except ValueError: + pass + try: + return self.subword_index(word**-1) is not None + except ValueError: + return False + + def is_independent(self, word): + """ + + See Also + ======== + + is_dependent + + """ + return not self.is_dependent(word) + + def contains_generators(self): + """ + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y, z = free_group("x, y, z") + >>> (x**2*y**-1).contains_generators() + {x, y} + >>> (x**3*z).contains_generators() + {x, z} + + """ + group = self.group + gens = {group.dtype(((syllable[0], 1),)) for syllable in self.array_form} + return gens + + def cyclic_subword(self, from_i, to_j): + group = self.group + l = len(self) + letter_form = self.letter_form + period1 = int(from_i/l) + if from_i >= l: + from_i -= l*period1 + to_j -= l*period1 + diff = to_j - from_i + word = letter_form[from_i: to_j] + period2 = int(to_j/l) - 1 + word += letter_form*period2 + letter_form[:diff-l+from_i-l*period2] + word = letter_form_to_array_form(word, group) + return group.dtype(word) + + def cyclic_conjugates(self): + """Returns a words which are cyclic to the word `self`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> w = x*y*x*y*x + >>> w.cyclic_conjugates() + {x*y*x**2*y, x**2*y*x*y, y*x*y*x**2, y*x**2*y*x, x*y*x*y*x} + >>> s = x*y*x**2*y*x + >>> s.cyclic_conjugates() + {x**2*y*x**2*y, y*x**2*y*x**2, x*y*x**2*y*x} + + References + ========== + + .. [1] https://planetmath.org/cyclicpermutation + + """ + return {self.cyclic_subword(i, i+len(self)) for i in range(len(self))} + + def is_cyclic_conjugate(self, w): + """ + Checks whether words ``self``, ``w`` are cyclic conjugates. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> w1 = x**2*y**5 + >>> w2 = x*y**5*x + >>> w1.is_cyclic_conjugate(w2) + True + >>> w3 = x**-1*y**5*x**-1 + >>> w3.is_cyclic_conjugate(w2) + False + + """ + l1 = len(self) + l2 = len(w) + if l1 != l2: + return False + w1 = self.identity_cyclic_reduction() + w2 = w.identity_cyclic_reduction() + letter1 = w1.letter_form + letter2 = w2.letter_form + str1 = ' '.join(map(str, letter1)) + str2 = ' '.join(map(str, letter2)) + if len(str1) != len(str2): + return False + + return str1 in str2 + ' ' + str2 + + def number_syllables(self): + """Returns the number of syllables of the associative word `self`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, swapnil0, swapnil1 = free_group("swapnil0 swapnil1") + >>> (swapnil1**3*swapnil0*swapnil1**-1).number_syllables() + 3 + + """ + return len(self.array_form) + + def exponent_syllable(self, i): + """ + Returns the exponent of the `i`-th syllable of the associative word + `self`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b = free_group("a b") + >>> w = a**5*b*a**2*b**-4*a + >>> w.exponent_syllable( 2 ) + 2 + + """ + return self.array_form[i][1] + + def generator_syllable(self, i): + """ + Returns the symbol of the generator that is involved in the + i-th syllable of the associative word `self`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b = free_group("a b") + >>> w = a**5*b*a**2*b**-4*a + >>> w.generator_syllable( 3 ) + b + + """ + return self.array_form[i][0] + + def sub_syllables(self, from_i, to_j): + """ + `sub_syllables` returns the subword of the associative word `self` that + consists of syllables from positions `from_to` to `to_j`, where + `from_to` and `to_j` must be positive integers and indexing is done + with origin 0. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> f, a, b = free_group("a, b") + >>> w = a**5*b*a**2*b**-4*a + >>> w.sub_syllables(1, 2) + b + >>> w.sub_syllables(3, 3) + + + """ + if not isinstance(from_i, int) or not isinstance(to_j, int): + raise ValueError("both arguments should be integers") + group = self.group + if to_j <= from_i: + return group.identity + else: + r = tuple(self.array_form[from_i: to_j]) + return group.dtype(r) + + def substituted_word(self, from_i, to_j, by): + """ + Returns the associative word obtained by replacing the subword of + `self` that begins at position `from_i` and ends at position `to_j - 1` + by the associative word `by`. `from_i` and `to_j` must be positive + integers, indexing is done with origin 0. In other words, + `w.substituted_word(w, from_i, to_j, by)` is the product of the three + words: `w.subword(0, from_i)`, `by`, and + `w.subword(to_j len(w))`. + + See Also + ======== + + eliminate_word + + """ + lw = len(self) + if from_i >= to_j or from_i > lw or to_j > lw: + raise ValueError("values should be within bounds") + + # otherwise there are four possibilities + + # first if from=1 and to=lw then + if from_i == 0 and to_j == lw: + return by + elif from_i == 0: # second if from_i=1 (and to_j < lw) then + return by*self.subword(to_j, lw) + elif to_j == lw: # third if to_j=1 (and from_i > 1) then + return self.subword(0, from_i)*by + else: # finally + return self.subword(0, from_i)*by*self.subword(to_j, lw) + + def is_cyclically_reduced(self): + r"""Returns whether the word is cyclically reduced or not. + A word is cyclically reduced if by forming the cycle of the + word, the word is not reduced, i.e a word w = `a_1 ... a_n` + is called cyclically reduced if `a_1 \ne a_n^{-1}`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> (x**2*y**-1*x**-1).is_cyclically_reduced() + False + >>> (y*x**2*y**2).is_cyclically_reduced() + True + + """ + if not self: + return True + return self[0] != self[-1]**-1 + + def identity_cyclic_reduction(self): + """Return a unique cyclically reduced version of the word. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> (x**2*y**2*x**-1).identity_cyclic_reduction() + x*y**2 + >>> (x**-3*y**-1*x**5).identity_cyclic_reduction() + x**2*y**-1 + + References + ========== + + .. [1] https://planetmath.org/cyclicallyreduced + + """ + word = self.copy() + group = self.group + while not word.is_cyclically_reduced(): + exp1 = word.exponent_syllable(0) + exp2 = word.exponent_syllable(-1) + r = exp1 + exp2 + if r == 0: + rep = word.array_form[1: word.number_syllables() - 1] + else: + rep = ((word.generator_syllable(0), exp1 + exp2),) + \ + word.array_form[1: word.number_syllables() - 1] + word = group.dtype(rep) + return word + + def cyclic_reduction(self, removed=False): + """Return a cyclically reduced version of the word. Unlike + `identity_cyclic_reduction`, this will not cyclically permute + the reduced word - just remove the "unreduced" bits on either + side of it. Compare the examples with those of + `identity_cyclic_reduction`. + + When `removed` is `True`, return a tuple `(word, r)` where + self `r` is such that before the reduction the word was either + `r*word*r**-1`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> (x**2*y**2*x**-1).cyclic_reduction() + x*y**2 + >>> (x**-3*y**-1*x**5).cyclic_reduction() + y**-1*x**2 + >>> (x**-3*y**-1*x**5).cyclic_reduction(removed=True) + (y**-1*x**2, x**-3) + + """ + word = self.copy() + g = self.group.identity + while not word.is_cyclically_reduced(): + exp1 = abs(word.exponent_syllable(0)) + exp2 = abs(word.exponent_syllable(-1)) + exp = min(exp1, exp2) + start = word[0]**abs(exp) + end = word[-1]**abs(exp) + word = start**-1*word*end**-1 + g = g*start + if removed: + return word, g + return word + + def power_of(self, other): + ''' + Check if `self == other**n` for some integer n. + + Examples + ======== + + >>> from sympy.combinatorics import free_group + >>> F, x, y = free_group("x, y") + >>> ((x*y)**2).power_of(x*y) + True + >>> (x**-3*y**-2*x**3).power_of(x**-3*y*x**3) + True + + ''' + if self.is_identity: + return True + + l = len(other) + if l == 1: + # self has to be a power of one generator + gens = self.contains_generators() + s = other in gens or other**-1 in gens + return len(gens) == 1 and s + + # if self is not cyclically reduced and it is a power of other, + # other isn't cyclically reduced and the parts removed during + # their reduction must be equal + reduced, r1 = self.cyclic_reduction(removed=True) + if not r1.is_identity: + other, r2 = other.cyclic_reduction(removed=True) + if r1 == r2: + return reduced.power_of(other) + return False + + if len(self) < l or len(self) % l: + return False + + prefix = self.subword(0, l) + if prefix == other or prefix**-1 == other: + rest = self.subword(l, len(self)) + return rest.power_of(other) + return False + + +def letter_form_to_array_form(array_form, group): + """ + This method converts a list given with possible repetitions of elements in + it. It returns a new list such that repetitions of consecutive elements is + removed and replace with a tuple element of size two such that the first + index contains `value` and the second index contains the number of + consecutive repetitions of `value`. + + """ + a = list(array_form[:]) + new_array = [] + n = 1 + symbols = group.symbols + for i in range(len(a)): + if i == len(a) - 1: + if a[i] == a[i - 1]: + if (-a[i]) in symbols: + new_array.append((-a[i], -n)) + else: + new_array.append((a[i], n)) + else: + if (-a[i]) in symbols: + new_array.append((-a[i], -1)) + else: + new_array.append((a[i], 1)) + return new_array + elif a[i] == a[i + 1]: + n += 1 + else: + if (-a[i]) in symbols: + new_array.append((-a[i], -n)) + else: + new_array.append((a[i], n)) + n = 1 + + +def zero_mul_simp(l, index): + """Used to combine two reduced words.""" + while index >=0 and index < len(l) - 1 and l[index][0] == l[index + 1][0]: + exp = l[index][1] + l[index + 1][1] + base = l[index][0] + l[index] = (base, exp) + del l[index + 1] + if l[index][1] == 0: + del l[index] + index -= 1 diff --git a/lib/python3.12/site-packages/sympy/combinatorics/galois.py b/lib/python3.12/site-packages/sympy/combinatorics/galois.py new file mode 100644 index 0000000000000000000000000000000000000000..f8ff89886283903e116bf40e1be6f6131386e802 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/galois.py @@ -0,0 +1,611 @@ +r""" +Construct transitive subgroups of symmetric groups, useful in Galois theory. + +Besides constructing instances of the :py:class:`~.PermutationGroup` class to +represent the transitive subgroups of $S_n$ for small $n$, this module provides +*names* for these groups. + +In some applications, it may be preferable to know the name of a group, +rather than receive an instance of the :py:class:`~.PermutationGroup` +class, and then have to do extra work to determine which group it is, by +checking various properties. + +Names are instances of ``Enum`` classes defined in this module. With a name in +hand, the name's ``get_perm_group`` method can then be used to retrieve a +:py:class:`~.PermutationGroup`. + +The names used for groups in this module are taken from [1]. + +References +========== + +.. [1] Cohen, H. *A Course in Computational Algebraic Number Theory*. + +""" + +from collections import defaultdict +from enum import Enum +import itertools + +from sympy.combinatorics.named_groups import ( + SymmetricGroup, AlternatingGroup, CyclicGroup, DihedralGroup, + set_symmetric_group_properties, set_alternating_group_properties, +) +from sympy.combinatorics.perm_groups import PermutationGroup +from sympy.combinatorics.permutations import Permutation + + +class S1TransitiveSubgroups(Enum): + """ + Names for the transitive subgroups of S1. + """ + S1 = "S1" + + def get_perm_group(self): + return SymmetricGroup(1) + + +class S2TransitiveSubgroups(Enum): + """ + Names for the transitive subgroups of S2. + """ + S2 = "S2" + + def get_perm_group(self): + return SymmetricGroup(2) + + +class S3TransitiveSubgroups(Enum): + """ + Names for the transitive subgroups of S3. + """ + A3 = "A3" + S3 = "S3" + + def get_perm_group(self): + if self == S3TransitiveSubgroups.A3: + return AlternatingGroup(3) + elif self == S3TransitiveSubgroups.S3: + return SymmetricGroup(3) + + +class S4TransitiveSubgroups(Enum): + """ + Names for the transitive subgroups of S4. + """ + C4 = "C4" + V = "V" + D4 = "D4" + A4 = "A4" + S4 = "S4" + + def get_perm_group(self): + if self == S4TransitiveSubgroups.C4: + return CyclicGroup(4) + elif self == S4TransitiveSubgroups.V: + return four_group() + elif self == S4TransitiveSubgroups.D4: + return DihedralGroup(4) + elif self == S4TransitiveSubgroups.A4: + return AlternatingGroup(4) + elif self == S4TransitiveSubgroups.S4: + return SymmetricGroup(4) + + +class S5TransitiveSubgroups(Enum): + """ + Names for the transitive subgroups of S5. + """ + C5 = "C5" + D5 = "D5" + M20 = "M20" + A5 = "A5" + S5 = "S5" + + def get_perm_group(self): + if self == S5TransitiveSubgroups.C5: + return CyclicGroup(5) + elif self == S5TransitiveSubgroups.D5: + return DihedralGroup(5) + elif self == S5TransitiveSubgroups.M20: + return M20() + elif self == S5TransitiveSubgroups.A5: + return AlternatingGroup(5) + elif self == S5TransitiveSubgroups.S5: + return SymmetricGroup(5) + + +class S6TransitiveSubgroups(Enum): + """ + Names for the transitive subgroups of S6. + """ + C6 = "C6" + S3 = "S3" + D6 = "D6" + A4 = "A4" + G18 = "G18" + A4xC2 = "A4 x C2" + S4m = "S4-" + S4p = "S4+" + G36m = "G36-" + G36p = "G36+" + S4xC2 = "S4 x C2" + PSL2F5 = "PSL2(F5)" + G72 = "G72" + PGL2F5 = "PGL2(F5)" + A6 = "A6" + S6 = "S6" + + def get_perm_group(self): + if self == S6TransitiveSubgroups.C6: + return CyclicGroup(6) + elif self == S6TransitiveSubgroups.S3: + return S3_in_S6() + elif self == S6TransitiveSubgroups.D6: + return DihedralGroup(6) + elif self == S6TransitiveSubgroups.A4: + return A4_in_S6() + elif self == S6TransitiveSubgroups.G18: + return G18() + elif self == S6TransitiveSubgroups.A4xC2: + return A4xC2() + elif self == S6TransitiveSubgroups.S4m: + return S4m() + elif self == S6TransitiveSubgroups.S4p: + return S4p() + elif self == S6TransitiveSubgroups.G36m: + return G36m() + elif self == S6TransitiveSubgroups.G36p: + return G36p() + elif self == S6TransitiveSubgroups.S4xC2: + return S4xC2() + elif self == S6TransitiveSubgroups.PSL2F5: + return PSL2F5() + elif self == S6TransitiveSubgroups.G72: + return G72() + elif self == S6TransitiveSubgroups.PGL2F5: + return PGL2F5() + elif self == S6TransitiveSubgroups.A6: + return AlternatingGroup(6) + elif self == S6TransitiveSubgroups.S6: + return SymmetricGroup(6) + + +def four_group(): + """ + Return a representation of the Klein four-group as a transitive subgroup + of S4. + """ + return PermutationGroup( + Permutation(0, 1)(2, 3), + Permutation(0, 2)(1, 3) + ) + + +def M20(): + """ + Return a representation of the metacyclic group M20, a transitive subgroup + of S5 that is one of the possible Galois groups for polys of degree 5. + + Notes + ===== + + See [1], Page 323. + + """ + G = PermutationGroup(Permutation(0, 1, 2, 3, 4), Permutation(1, 2, 4, 3)) + G._degree = 5 + G._order = 20 + G._is_transitive = True + G._is_sym = False + G._is_alt = False + G._is_cyclic = False + G._is_dihedral = False + return G + + +def S3_in_S6(): + """ + Return a representation of S3 as a transitive subgroup of S6. + + Notes + ===== + + The representation is found by viewing the group as the symmetries of a + triangular prism. + + """ + G = PermutationGroup(Permutation(0, 1, 2)(3, 4, 5), Permutation(0, 3)(2, 4)(1, 5)) + set_symmetric_group_properties(G, 3, 6) + return G + + +def A4_in_S6(): + """ + Return a representation of A4 as a transitive subgroup of S6. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + G = PermutationGroup(Permutation(0, 4, 5)(1, 3, 2), Permutation(0, 1, 2)(3, 5, 4)) + set_alternating_group_properties(G, 4, 6) + return G + + +def S4m(): + """ + Return a representation of the S4- transitive subgroup of S6. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + G = PermutationGroup(Permutation(1, 4, 5, 3), Permutation(0, 4)(1, 5)(2, 3)) + set_symmetric_group_properties(G, 4, 6) + return G + + +def S4p(): + """ + Return a representation of the S4+ transitive subgroup of S6. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + G = PermutationGroup(Permutation(0, 2, 4, 1)(3, 5), Permutation(0, 3)(4, 5)) + set_symmetric_group_properties(G, 4, 6) + return G + + +def A4xC2(): + """ + Return a representation of the (A4 x C2) transitive subgroup of S6. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + return PermutationGroup( + Permutation(0, 4, 5)(1, 3, 2), Permutation(0, 1, 2)(3, 5, 4), + Permutation(5)(2, 4)) + + +def S4xC2(): + """ + Return a representation of the (S4 x C2) transitive subgroup of S6. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + return PermutationGroup( + Permutation(1, 4, 5, 3), Permutation(0, 4)(1, 5)(2, 3), + Permutation(1, 4)(3, 5)) + + +def G18(): + """ + Return a representation of the group G18, a transitive subgroup of S6 + isomorphic to the semidirect product of C3^2 with C2. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + return PermutationGroup( + Permutation(5)(0, 1, 2), Permutation(3, 4, 5), + Permutation(0, 4)(1, 5)(2, 3)) + + +def G36m(): + """ + Return a representation of the group G36-, a transitive subgroup of S6 + isomorphic to the semidirect product of C3^2 with C2^2. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + return PermutationGroup( + Permutation(5)(0, 1, 2), Permutation(3, 4, 5), + Permutation(1, 2)(3, 5), Permutation(0, 4)(1, 5)(2, 3)) + + +def G36p(): + """ + Return a representation of the group G36+, a transitive subgroup of S6 + isomorphic to the semidirect product of C3^2 with C4. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + return PermutationGroup( + Permutation(5)(0, 1, 2), Permutation(3, 4, 5), + Permutation(0, 5, 2, 3)(1, 4)) + + +def G72(): + """ + Return a representation of the group G72, a transitive subgroup of S6 + isomorphic to the semidirect product of C3^2 with D4. + + Notes + ===== + + See [1], Page 325. + + """ + return PermutationGroup( + Permutation(5)(0, 1, 2), + Permutation(0, 4, 1, 3)(2, 5), Permutation(0, 3)(1, 4)(2, 5)) + + +def PSL2F5(): + r""" + Return a representation of the group $PSL_2(\mathbb{F}_5)$, as a transitive + subgroup of S6, isomorphic to $A_5$. + + Notes + ===== + + This was computed using :py:func:`~.find_transitive_subgroups_of_S6`. + + """ + G = PermutationGroup( + Permutation(0, 4, 5)(1, 3, 2), Permutation(0, 4, 3, 1, 5)) + set_alternating_group_properties(G, 5, 6) + return G + + +def PGL2F5(): + r""" + Return a representation of the group $PGL_2(\mathbb{F}_5)$, as a transitive + subgroup of S6, isomorphic to $S_5$. + + Notes + ===== + + See [1], Page 325. + + """ + G = PermutationGroup( + Permutation(0, 1, 2, 3, 4), Permutation(0, 5)(1, 2)(3, 4)) + set_symmetric_group_properties(G, 5, 6) + return G + + +def find_transitive_subgroups_of_S6(*targets, print_report=False): + r""" + Search for certain transitive subgroups of $S_6$. + + The symmetric group $S_6$ has 16 different transitive subgroups, up to + conjugacy. Some are more easily constructed than others. For example, the + dihedral group $D_6$ is immediately found, but it is not at all obvious how + to realize $S_4$ or $S_5$ *transitively* within $S_6$. + + In some cases there are well-known constructions that can be used. For + example, $S_5$ is isomorphic to $PGL_2(\mathbb{F}_5)$, which acts in a + natural way on the projective line $P^1(\mathbb{F}_5)$, a set of order 6. + + In absence of such special constructions however, we can simply search for + generators. For example, transitive instances of $A_4$ and $S_4$ can be + found within $S_6$ in this way. + + Once we are engaged in such searches, it may then be easier (if less + elegant) to find even those groups like $S_5$ that do have special + constructions, by mere search. + + This function locates generators for transitive instances in $S_6$ of the + following subgroups: + + * $A_4$ + * $S_4^-$ ($S_4$ not contained within $A_6$) + * $S_4^+$ ($S_4$ contained within $A_6$) + * $A_4 \times C_2$ + * $S_4 \times C_2$ + * $G_{18} = C_3^2 \rtimes C_2$ + * $G_{36}^- = C_3^2 \rtimes C_2^2$ + * $G_{36}^+ = C_3^2 \rtimes C_4$ + * $G_{72} = C_3^2 \rtimes D_4$ + * $A_5$ + * $S_5$ + + Note: Each of these groups also has a dedicated function in this module + that returns the group immediately, using generators that were found by + this search procedure. + + The search procedure serves as a record of how these generators were + found. Also, due to randomness in the generation of the elements of + permutation groups, it can be called again, in order to (probably) get + different generators for the same groups. + + Parameters + ========== + + targets : list of :py:class:`~.S6TransitiveSubgroups` values + The groups you want to find. + + print_report : bool (default False) + If True, print to stdout the generators found for each group. + + Returns + ======= + + dict + mapping each name in *targets* to the :py:class:`~.PermutationGroup` + that was found + + References + ========== + + .. [2] https://en.wikipedia.org/wiki/Projective_linear_group#Exceptional_isomorphisms + .. [3] https://en.wikipedia.org/wiki/Automorphisms_of_the_symmetric_and_alternating_groups#PGL%282,5%29 + + """ + def elts_by_order(G): + """Sort the elements of a group by their order. """ + elts = defaultdict(list) + for g in G.elements: + elts[g.order()].append(g) + return elts + + def order_profile(G, name=None): + """Determine how many elements a group has, of each order. """ + elts = elts_by_order(G) + profile = {o:len(e) for o, e in elts.items()} + if name: + print(f'{name}: ' + ' '.join(f'{len(profile[r])}@{r}' for r in sorted(profile.keys()))) + return profile + + S6 = SymmetricGroup(6) + A6 = AlternatingGroup(6) + S6_by_order = elts_by_order(S6) + + def search(existing_gens, needed_gen_orders, order, alt=None, profile=None, anti_profile=None): + """ + Find a transitive subgroup of S6. + + Parameters + ========== + + existing_gens : list of Permutation + Optionally empty list of generators that must be in the group. + + needed_gen_orders : list of positive int + Nonempty list of the orders of the additional generators that are + to be found. + + order: int + The order of the group being sought. + + alt: bool, None + If True, require the group to be contained in A6. + If False, require the group not to be contained in A6. + + profile : dict + If given, the group's order profile must equal this. + + anti_profile : dict + If given, the group's order profile must *not* equal this. + + """ + for gens in itertools.product(*[S6_by_order[n] for n in needed_gen_orders]): + if len(set(gens)) < len(gens): + continue + G = PermutationGroup(existing_gens + list(gens)) + if G.order() == order and G.is_transitive(): + if alt is not None and G.is_subgroup(A6) != alt: + continue + if profile and order_profile(G) != profile: + continue + if anti_profile and order_profile(G) == anti_profile: + continue + return G + + def match_known_group(G, alt=None): + needed = [g.order() for g in G.generators] + return search([], needed, G.order(), alt=alt, profile=order_profile(G)) + + found = {} + + def finish_up(name, G): + found[name] = G + if print_report: + print("=" * 40) + print(f"{name}:") + print(G.generators) + + if S6TransitiveSubgroups.A4 in targets or S6TransitiveSubgroups.A4xC2 in targets: + A4_in_S6 = match_known_group(AlternatingGroup(4)) + finish_up(S6TransitiveSubgroups.A4, A4_in_S6) + + if S6TransitiveSubgroups.S4m in targets or S6TransitiveSubgroups.S4xC2 in targets: + S4m_in_S6 = match_known_group(SymmetricGroup(4), alt=False) + finish_up(S6TransitiveSubgroups.S4m, S4m_in_S6) + + if S6TransitiveSubgroups.S4p in targets: + S4p_in_S6 = match_known_group(SymmetricGroup(4), alt=True) + finish_up(S6TransitiveSubgroups.S4p, S4p_in_S6) + + if S6TransitiveSubgroups.A4xC2 in targets: + A4xC2_in_S6 = search(A4_in_S6.generators, [2], 24, anti_profile=order_profile(SymmetricGroup(4))) + finish_up(S6TransitiveSubgroups.A4xC2, A4xC2_in_S6) + + if S6TransitiveSubgroups.S4xC2 in targets: + S4xC2_in_S6 = search(S4m_in_S6.generators, [2], 48) + finish_up(S6TransitiveSubgroups.S4xC2, S4xC2_in_S6) + + # For the normal factor N = C3^2 in any of the G_n subgroups, we take one + # obvious instance of C3^2 in S6: + N_gens = [Permutation(5)(0, 1, 2), Permutation(5)(3, 4, 5)] + + if S6TransitiveSubgroups.G18 in targets: + G18_in_S6 = search(N_gens, [2], 18) + finish_up(S6TransitiveSubgroups.G18, G18_in_S6) + + if S6TransitiveSubgroups.G36m in targets: + G36m_in_S6 = search(N_gens, [2, 2], 36, alt=False) + finish_up(S6TransitiveSubgroups.G36m, G36m_in_S6) + + if S6TransitiveSubgroups.G36p in targets: + G36p_in_S6 = search(N_gens, [4], 36, alt=True) + finish_up(S6TransitiveSubgroups.G36p, G36p_in_S6) + + if S6TransitiveSubgroups.G72 in targets: + G72_in_S6 = search(N_gens, [4, 2], 72) + finish_up(S6TransitiveSubgroups.G72, G72_in_S6) + + # The PSL2(F5) and PGL2(F5) subgroups are isomorphic to A5 and S5, resp. + + if S6TransitiveSubgroups.PSL2F5 in targets: + PSL2F5_in_S6 = match_known_group(AlternatingGroup(5)) + finish_up(S6TransitiveSubgroups.PSL2F5, PSL2F5_in_S6) + + if S6TransitiveSubgroups.PGL2F5 in targets: + PGL2F5_in_S6 = match_known_group(SymmetricGroup(5)) + finish_up(S6TransitiveSubgroups.PGL2F5, PGL2F5_in_S6) + + # There is little need to "search" for any of the groups C6, S3, D6, A6, + # or S6, since they all have obvious realizations within S6. However, we + # support them here just in case a random representation is desired. + + if S6TransitiveSubgroups.C6 in targets: + C6 = match_known_group(CyclicGroup(6)) + finish_up(S6TransitiveSubgroups.C6, C6) + + if S6TransitiveSubgroups.S3 in targets: + S3 = match_known_group(SymmetricGroup(3)) + finish_up(S6TransitiveSubgroups.S3, S3) + + if S6TransitiveSubgroups.D6 in targets: + D6 = match_known_group(DihedralGroup(6)) + finish_up(S6TransitiveSubgroups.D6, D6) + + if S6TransitiveSubgroups.A6 in targets: + A6 = match_known_group(A6) + finish_up(S6TransitiveSubgroups.A6, A6) + + if S6TransitiveSubgroups.S6 in targets: + S6 = match_known_group(S6) + finish_up(S6TransitiveSubgroups.S6, S6) + + return found diff --git a/lib/python3.12/site-packages/sympy/combinatorics/generators.py b/lib/python3.12/site-packages/sympy/combinatorics/generators.py new file mode 100644 index 0000000000000000000000000000000000000000..9f136502d4e082e6c2554e7fb294d0036c5b0034 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/generators.py @@ -0,0 +1,302 @@ +from sympy.combinatorics.permutations import Permutation +from sympy.core.symbol import symbols +from sympy.matrices import Matrix +from sympy.utilities.iterables import variations, rotate_left + + +def symmetric(n): + """ + Generates the symmetric group of order n, Sn. + + Examples + ======== + + >>> from sympy.combinatorics.generators import symmetric + >>> list(symmetric(3)) + [(2), (1 2), (2)(0 1), (0 1 2), (0 2 1), (0 2)] + """ + for perm in variations(range(n), n): + yield Permutation(perm) + + +def cyclic(n): + """ + Generates the cyclic group of order n, Cn. + + Examples + ======== + + >>> from sympy.combinatorics.generators import cyclic + >>> list(cyclic(5)) + [(4), (0 1 2 3 4), (0 2 4 1 3), + (0 3 1 4 2), (0 4 3 2 1)] + + See Also + ======== + + dihedral + """ + gen = list(range(n)) + for i in range(n): + yield Permutation(gen) + gen = rotate_left(gen, 1) + + +def alternating(n): + """ + Generates the alternating group of order n, An. + + Examples + ======== + + >>> from sympy.combinatorics.generators import alternating + >>> list(alternating(3)) + [(2), (0 1 2), (0 2 1)] + """ + for perm in variations(range(n), n): + p = Permutation(perm) + if p.is_even: + yield p + + +def dihedral(n): + """ + Generates the dihedral group of order 2n, Dn. + + The result is given as a subgroup of Sn, except for the special cases n=1 + (the group S2) and n=2 (the Klein 4-group) where that's not possible + and embeddings in S2 and S4 respectively are given. + + Examples + ======== + + >>> from sympy.combinatorics.generators import dihedral + >>> list(dihedral(3)) + [(2), (0 2), (0 1 2), (1 2), (0 2 1), (2)(0 1)] + + See Also + ======== + + cyclic + """ + if n == 1: + yield Permutation([0, 1]) + yield Permutation([1, 0]) + elif n == 2: + yield Permutation([0, 1, 2, 3]) + yield Permutation([1, 0, 3, 2]) + yield Permutation([2, 3, 0, 1]) + yield Permutation([3, 2, 1, 0]) + else: + gen = list(range(n)) + for i in range(n): + yield Permutation(gen) + yield Permutation(gen[::-1]) + gen = rotate_left(gen, 1) + + +def rubik_cube_generators(): + """Return the permutations of the 3x3 Rubik's cube, see + https://www.gap-system.org/Doc/Examples/rubik.html + """ + a = [ + [(1, 3, 8, 6), (2, 5, 7, 4), (9, 33, 25, 17), (10, 34, 26, 18), + (11, 35, 27, 19)], + [(9, 11, 16, 14), (10, 13, 15, 12), (1, 17, 41, 40), (4, 20, 44, 37), + (6, 22, 46, 35)], + [(17, 19, 24, 22), (18, 21, 23, 20), (6, 25, 43, 16), (7, 28, 42, 13), + (8, 30, 41, 11)], + [(25, 27, 32, 30), (26, 29, 31, 28), (3, 38, 43, 19), (5, 36, 45, 21), + (8, 33, 48, 24)], + [(33, 35, 40, 38), (34, 37, 39, 36), (3, 9, 46, 32), (2, 12, 47, 29), + (1, 14, 48, 27)], + [(41, 43, 48, 46), (42, 45, 47, 44), (14, 22, 30, 38), + (15, 23, 31, 39), (16, 24, 32, 40)] + ] + return [Permutation([[i - 1 for i in xi] for xi in x], size=48) for x in a] + + +def rubik(n): + """Return permutations for an nxn Rubik's cube. + + Permutations returned are for rotation of each of the slice + from the face up to the last face for each of the 3 sides (in this order): + front, right and bottom. Hence, the first n - 1 permutations are for the + slices from the front. + """ + + if n < 2: + raise ValueError('dimension of cube must be > 1') + + # 1-based reference to rows and columns in Matrix + def getr(f, i): + return faces[f].col(n - i) + + def getl(f, i): + return faces[f].col(i - 1) + + def getu(f, i): + return faces[f].row(i - 1) + + def getd(f, i): + return faces[f].row(n - i) + + def setr(f, i, s): + faces[f][:, n - i] = Matrix(n, 1, s) + + def setl(f, i, s): + faces[f][:, i - 1] = Matrix(n, 1, s) + + def setu(f, i, s): + faces[f][i - 1, :] = Matrix(1, n, s) + + def setd(f, i, s): + faces[f][n - i, :] = Matrix(1, n, s) + + # motion of a single face + def cw(F, r=1): + for _ in range(r): + face = faces[F] + rv = [] + for c in range(n): + for r in range(n - 1, -1, -1): + rv.append(face[r, c]) + faces[F] = Matrix(n, n, rv) + + def ccw(F): + cw(F, 3) + + # motion of plane i from the F side; + # fcw(0) moves the F face, fcw(1) moves the plane + # just behind the front face, etc... + def fcw(i, r=1): + for _ in range(r): + if i == 0: + cw(F) + i += 1 + temp = getr(L, i) + setr(L, i, list(getu(D, i))) + setu(D, i, list(reversed(getl(R, i)))) + setl(R, i, list(getd(U, i))) + setd(U, i, list(reversed(temp))) + i -= 1 + + def fccw(i): + fcw(i, 3) + + # motion of the entire cube from the F side + def FCW(r=1): + for _ in range(r): + cw(F) + ccw(B) + cw(U) + t = faces[U] + cw(L) + faces[U] = faces[L] + cw(D) + faces[L] = faces[D] + cw(R) + faces[D] = faces[R] + faces[R] = t + + def FCCW(): + FCW(3) + + # motion of the entire cube from the U side + def UCW(r=1): + for _ in range(r): + cw(U) + ccw(D) + t = faces[F] + faces[F] = faces[R] + faces[R] = faces[B] + faces[B] = faces[L] + faces[L] = t + + def UCCW(): + UCW(3) + + # defining the permutations for the cube + + U, F, R, B, L, D = names = symbols('U, F, R, B, L, D') + + # the faces are represented by nxn matrices + faces = {} + count = 0 + for fi in range(6): + f = [] + for a in range(n**2): + f.append(count) + count += 1 + faces[names[fi]] = Matrix(n, n, f) + + # this will either return the value of the current permutation + # (show != 1) or else append the permutation to the group, g + def perm(show=0): + # add perm to the list of perms + p = [] + for f in names: + p.extend(faces[f]) + if show: + return p + g.append(Permutation(p)) + + g = [] # container for the group's permutations + I = list(range(6*n**2)) # the identity permutation used for checking + + # define permutations corresponding to cw rotations of the planes + # up TO the last plane from that direction; by not including the + # last plane, the orientation of the cube is maintained. + + # F slices + for i in range(n - 1): + fcw(i) + perm() + fccw(i) # restore + assert perm(1) == I + + # R slices + # bring R to front + UCW() + for i in range(n - 1): + fcw(i) + # put it back in place + UCCW() + # record + perm() + # restore + # bring face to front + UCW() + fccw(i) + # restore + UCCW() + assert perm(1) == I + + # D slices + # bring up bottom + FCW() + UCCW() + FCCW() + for i in range(n - 1): + # turn strip + fcw(i) + # put bottom back on the bottom + FCW() + UCW() + FCCW() + # record + perm() + # restore + # bring up bottom + FCW() + UCCW() + FCCW() + # turn strip + fccw(i) + # put bottom back on the bottom + FCW() + UCW() + FCCW() + assert perm(1) == I + + return g diff --git a/lib/python3.12/site-packages/sympy/combinatorics/graycode.py b/lib/python3.12/site-packages/sympy/combinatorics/graycode.py new file mode 100644 index 0000000000000000000000000000000000000000..930fd337862a70e920a985947d74375b27741293 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/graycode.py @@ -0,0 +1,430 @@ +from sympy.core import Basic, Integer + +import random + + +class GrayCode(Basic): + """ + A Gray code is essentially a Hamiltonian walk on + a n-dimensional cube with edge length of one. + The vertices of the cube are represented by vectors + whose values are binary. The Hamilton walk visits + each vertex exactly once. The Gray code for a 3d + cube is ['000','100','110','010','011','111','101', + '001']. + + A Gray code solves the problem of sequentially + generating all possible subsets of n objects in such + a way that each subset is obtained from the previous + one by either deleting or adding a single object. + In the above example, 1 indicates that the object is + present, and 0 indicates that its absent. + + Gray codes have applications in statistics as well when + we want to compute various statistics related to subsets + in an efficient manner. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(3) + >>> list(a.generate_gray()) + ['000', '001', '011', '010', '110', '111', '101', '100'] + >>> a = GrayCode(4) + >>> list(a.generate_gray()) + ['0000', '0001', '0011', '0010', '0110', '0111', '0101', '0100', \ + '1100', '1101', '1111', '1110', '1010', '1011', '1001', '1000'] + + References + ========== + + .. [1] Nijenhuis,A. and Wilf,H.S.(1978). + Combinatorial Algorithms. Academic Press. + .. [2] Knuth, D. (2011). The Art of Computer Programming, Vol 4 + Addison Wesley + + + """ + + _skip = False + _current = 0 + _rank = None + + def __new__(cls, n, *args, **kw_args): + """ + Default constructor. + + It takes a single argument ``n`` which gives the dimension of the Gray + code. The starting Gray code string (``start``) or the starting ``rank`` + may also be given; the default is to start at rank = 0 ('0...0'). + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(3) + >>> a + GrayCode(3) + >>> a.n + 3 + + >>> a = GrayCode(3, start='100') + >>> a.current + '100' + + >>> a = GrayCode(4, rank=4) + >>> a.current + '0110' + >>> a.rank + 4 + + """ + if n < 1 or int(n) != n: + raise ValueError( + 'Gray code dimension must be a positive integer, not %i' % n) + n = Integer(n) + args = (n,) + args + obj = Basic.__new__(cls, *args) + if 'start' in kw_args: + obj._current = kw_args["start"] + if len(obj._current) > n: + raise ValueError('Gray code start has length %i but ' + 'should not be greater than %i' % (len(obj._current), n)) + elif 'rank' in kw_args: + if int(kw_args["rank"]) != kw_args["rank"]: + raise ValueError('Gray code rank must be a positive integer, ' + 'not %i' % kw_args["rank"]) + obj._rank = int(kw_args["rank"]) % obj.selections + obj._current = obj.unrank(n, obj._rank) + return obj + + def next(self, delta=1): + """ + Returns the Gray code a distance ``delta`` (default = 1) from the + current value in canonical order. + + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(3, start='110') + >>> a.next().current + '111' + >>> a.next(-1).current + '010' + """ + return GrayCode(self.n, rank=(self.rank + delta) % self.selections) + + @property + def selections(self): + """ + Returns the number of bit vectors in the Gray code. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(3) + >>> a.selections + 8 + """ + return 2**self.n + + @property + def n(self): + """ + Returns the dimension of the Gray code. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(5) + >>> a.n + 5 + """ + return self.args[0] + + def generate_gray(self, **hints): + """ + Generates the sequence of bit vectors of a Gray Code. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(3) + >>> list(a.generate_gray()) + ['000', '001', '011', '010', '110', '111', '101', '100'] + >>> list(a.generate_gray(start='011')) + ['011', '010', '110', '111', '101', '100'] + >>> list(a.generate_gray(rank=4)) + ['110', '111', '101', '100'] + + See Also + ======== + + skip + + References + ========== + + .. [1] Knuth, D. (2011). The Art of Computer Programming, + Vol 4, Addison Wesley + + """ + bits = self.n + start = None + if "start" in hints: + start = hints["start"] + elif "rank" in hints: + start = GrayCode.unrank(self.n, hints["rank"]) + if start is not None: + self._current = start + current = self.current + graycode_bin = gray_to_bin(current) + if len(graycode_bin) > self.n: + raise ValueError('Gray code start has length %i but should ' + 'not be greater than %i' % (len(graycode_bin), bits)) + self._current = int(current, 2) + graycode_int = int(''.join(graycode_bin), 2) + for i in range(graycode_int, 1 << bits): + if self._skip: + self._skip = False + else: + yield self.current + bbtc = (i ^ (i + 1)) + gbtc = (bbtc ^ (bbtc >> 1)) + self._current = (self._current ^ gbtc) + self._current = 0 + + def skip(self): + """ + Skips the bit generation. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(3) + >>> for i in a.generate_gray(): + ... if i == '010': + ... a.skip() + ... print(i) + ... + 000 + 001 + 011 + 010 + 111 + 101 + 100 + + See Also + ======== + + generate_gray + """ + self._skip = True + + @property + def rank(self): + """ + Ranks the Gray code. + + A ranking algorithm determines the position (or rank) + of a combinatorial object among all the objects w.r.t. + a given order. For example, the 4 bit binary reflected + Gray code (BRGC) '0101' has a rank of 6 as it appears in + the 6th position in the canonical ordering of the family + of 4 bit Gray codes. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> a = GrayCode(3) + >>> list(a.generate_gray()) + ['000', '001', '011', '010', '110', '111', '101', '100'] + >>> GrayCode(3, start='100').rank + 7 + >>> GrayCode(3, rank=7).current + '100' + + See Also + ======== + + unrank + + References + ========== + + .. [1] https://web.archive.org/web/20200224064753/http://statweb.stanford.edu/~susan/courses/s208/node12.html + + """ + if self._rank is None: + self._rank = int(gray_to_bin(self.current), 2) + return self._rank + + @property + def current(self): + """ + Returns the currently referenced Gray code as a bit string. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> GrayCode(3, start='100').current + '100' + """ + rv = self._current or '0' + if not isinstance(rv, str): + rv = bin(rv)[2:] + return rv.rjust(self.n, '0') + + @classmethod + def unrank(self, n, rank): + """ + Unranks an n-bit sized Gray code of rank k. This method exists + so that a derivative GrayCode class can define its own code of + a given rank. + + The string here is generated in reverse order to allow for tail-call + optimization. + + Examples + ======== + + >>> from sympy.combinatorics import GrayCode + >>> GrayCode(5, rank=3).current + '00010' + >>> GrayCode.unrank(5, 3) + '00010' + + See Also + ======== + + rank + """ + def _unrank(k, n): + if n == 1: + return str(k % 2) + m = 2**(n - 1) + if k < m: + return '0' + _unrank(k, n - 1) + return '1' + _unrank(m - (k % m) - 1, n - 1) + return _unrank(rank, n) + + +def random_bitstring(n): + """ + Generates a random bitlist of length n. + + Examples + ======== + + >>> from sympy.combinatorics.graycode import random_bitstring + >>> random_bitstring(3) # doctest: +SKIP + 100 + """ + return ''.join([random.choice('01') for i in range(n)]) + + +def gray_to_bin(bin_list): + """ + Convert from Gray coding to binary coding. + + We assume big endian encoding. + + Examples + ======== + + >>> from sympy.combinatorics.graycode import gray_to_bin + >>> gray_to_bin('100') + '111' + + See Also + ======== + + bin_to_gray + """ + b = [bin_list[0]] + for i in range(1, len(bin_list)): + b += str(int(b[i - 1] != bin_list[i])) + return ''.join(b) + + +def bin_to_gray(bin_list): + """ + Convert from binary coding to gray coding. + + We assume big endian encoding. + + Examples + ======== + + >>> from sympy.combinatorics.graycode import bin_to_gray + >>> bin_to_gray('111') + '100' + + See Also + ======== + + gray_to_bin + """ + b = [bin_list[0]] + for i in range(1, len(bin_list)): + b += str(int(bin_list[i]) ^ int(bin_list[i - 1])) + return ''.join(b) + + +def get_subset_from_bitstring(super_set, bitstring): + """ + Gets the subset defined by the bitstring. + + Examples + ======== + + >>> from sympy.combinatorics.graycode import get_subset_from_bitstring + >>> get_subset_from_bitstring(['a', 'b', 'c', 'd'], '0011') + ['c', 'd'] + >>> get_subset_from_bitstring(['c', 'a', 'c', 'c'], '1100') + ['c', 'a'] + + See Also + ======== + + graycode_subsets + """ + if len(super_set) != len(bitstring): + raise ValueError("The sizes of the lists are not equal") + return [super_set[i] for i, j in enumerate(bitstring) + if bitstring[i] == '1'] + + +def graycode_subsets(gray_code_set): + """ + Generates the subsets as enumerated by a Gray code. + + Examples + ======== + + >>> from sympy.combinatorics.graycode import graycode_subsets + >>> list(graycode_subsets(['a', 'b', 'c'])) + [[], ['c'], ['b', 'c'], ['b'], ['a', 'b'], ['a', 'b', 'c'], \ + ['a', 'c'], ['a']] + >>> list(graycode_subsets(['a', 'b', 'c', 'c'])) + [[], ['c'], ['c', 'c'], ['c'], ['b', 'c'], ['b', 'c', 'c'], \ + ['b', 'c'], ['b'], ['a', 'b'], ['a', 'b', 'c'], ['a', 'b', 'c', 'c'], \ + ['a', 'b', 'c'], ['a', 'c'], ['a', 'c', 'c'], ['a', 'c'], ['a']] + + See Also + ======== + + get_subset_from_bitstring + """ + for bitstring in list(GrayCode(len(gray_code_set)).generate_gray()): + yield get_subset_from_bitstring(gray_code_set, bitstring) diff --git a/lib/python3.12/site-packages/sympy/combinatorics/group_constructs.py b/lib/python3.12/site-packages/sympy/combinatorics/group_constructs.py new file mode 100644 index 0000000000000000000000000000000000000000..a5c16ec254191646b26eee869763e2926e187da5 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/group_constructs.py @@ -0,0 +1,61 @@ +from sympy.combinatorics.perm_groups import PermutationGroup +from sympy.combinatorics.permutations import Permutation +from sympy.utilities.iterables import uniq + +_af_new = Permutation._af_new + + +def DirectProduct(*groups): + """ + Returns the direct product of several groups as a permutation group. + + Explanation + =========== + + This is implemented much like the __mul__ procedure for taking the direct + product of two permutation groups, but the idea of shifting the + generators is realized in the case of an arbitrary number of groups. + A call to DirectProduct(G1, G2, ..., Gn) is generally expected to be faster + than a call to G1*G2*...*Gn (and thus the need for this algorithm). + + Examples + ======== + + >>> from sympy.combinatorics.group_constructs import DirectProduct + >>> from sympy.combinatorics.named_groups import CyclicGroup + >>> C = CyclicGroup(4) + >>> G = DirectProduct(C, C, C) + >>> G.order() + 64 + + See Also + ======== + + sympy.combinatorics.perm_groups.PermutationGroup.__mul__ + + """ + degrees = [] + gens_count = [] + total_degree = 0 + total_gens = 0 + for group in groups: + current_deg = group.degree + current_num_gens = len(group.generators) + degrees.append(current_deg) + total_degree += current_deg + gens_count.append(current_num_gens) + total_gens += current_num_gens + array_gens = [] + for i in range(total_gens): + array_gens.append(list(range(total_degree))) + current_gen = 0 + current_deg = 0 + for i in range(len(gens_count)): + for j in range(current_gen, current_gen + gens_count[i]): + gen = ((groups[i].generators)[j - current_gen]).array_form + array_gens[j][current_deg:current_deg + degrees[i]] = \ + [x + current_deg for x in gen] + current_gen += gens_count[i] + current_deg += degrees[i] + perm_gens = list(uniq([_af_new(list(a)) for a in array_gens])) + return PermutationGroup(perm_gens, dups=False) diff --git a/lib/python3.12/site-packages/sympy/combinatorics/homomorphisms.py b/lib/python3.12/site-packages/sympy/combinatorics/homomorphisms.py new file mode 100644 index 0000000000000000000000000000000000000000..256f56b3aa7c5404d332f42e37d4f1117ea81db7 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/homomorphisms.py @@ -0,0 +1,549 @@ +import itertools +from sympy.combinatorics.fp_groups import FpGroup, FpSubgroup, simplify_presentation +from sympy.combinatorics.free_groups import FreeGroup +from sympy.combinatorics.perm_groups import PermutationGroup +from sympy.core.intfunc import igcd +from sympy.functions.combinatorial.numbers import totient +from sympy.core.singleton import S + +class GroupHomomorphism: + ''' + A class representing group homomorphisms. Instantiate using `homomorphism()`. + + References + ========== + + .. [1] Holt, D., Eick, B. and O'Brien, E. (2005). Handbook of computational group theory. + + ''' + + def __init__(self, domain, codomain, images): + self.domain = domain + self.codomain = codomain + self.images = images + self._inverses = None + self._kernel = None + self._image = None + + def _invs(self): + ''' + Return a dictionary with `{gen: inverse}` where `gen` is a rewriting + generator of `codomain` (e.g. strong generator for permutation groups) + and `inverse` is an element of its preimage + + ''' + image = self.image() + inverses = {} + for k in list(self.images.keys()): + v = self.images[k] + if not (v in inverses + or v.is_identity): + inverses[v] = k + if isinstance(self.codomain, PermutationGroup): + gens = image.strong_gens + else: + gens = image.generators + for g in gens: + if g in inverses or g.is_identity: + continue + w = self.domain.identity + if isinstance(self.codomain, PermutationGroup): + parts = image._strong_gens_slp[g][::-1] + else: + parts = g + for s in parts: + if s in inverses: + w = w*inverses[s] + else: + w = w*inverses[s**-1]**-1 + inverses[g] = w + + return inverses + + def invert(self, g): + ''' + Return an element of the preimage of ``g`` or of each element + of ``g`` if ``g`` is a list. + + Explanation + =========== + + If the codomain is an FpGroup, the inverse for equal + elements might not always be the same unless the FpGroup's + rewriting system is confluent. However, making a system + confluent can be time-consuming. If it's important, try + `self.codomain.make_confluent()` first. + + ''' + from sympy.combinatorics import Permutation + from sympy.combinatorics.free_groups import FreeGroupElement + if isinstance(g, (Permutation, FreeGroupElement)): + if isinstance(self.codomain, FpGroup): + g = self.codomain.reduce(g) + if self._inverses is None: + self._inverses = self._invs() + image = self.image() + w = self.domain.identity + if isinstance(self.codomain, PermutationGroup): + gens = image.generator_product(g)[::-1] + else: + gens = g + # the following can't be "for s in gens:" + # because that would be equivalent to + # "for s in gens.array_form:" when g is + # a FreeGroupElement. On the other hand, + # when you call gens by index, the generator + # (or inverse) at position i is returned. + for i in range(len(gens)): + s = gens[i] + if s.is_identity: + continue + if s in self._inverses: + w = w*self._inverses[s] + else: + w = w*self._inverses[s**-1]**-1 + return w + elif isinstance(g, list): + return [self.invert(e) for e in g] + + def kernel(self): + ''' + Compute the kernel of `self`. + + ''' + if self._kernel is None: + self._kernel = self._compute_kernel() + return self._kernel + + def _compute_kernel(self): + G = self.domain + G_order = G.order() + if G_order is S.Infinity: + raise NotImplementedError( + "Kernel computation is not implemented for infinite groups") + gens = [] + if isinstance(G, PermutationGroup): + K = PermutationGroup(G.identity) + else: + K = FpSubgroup(G, gens, normal=True) + i = self.image().order() + while K.order()*i != G_order: + r = G.random() + k = r*self.invert(self(r))**-1 + if k not in K: + gens.append(k) + if isinstance(G, PermutationGroup): + K = PermutationGroup(gens) + else: + K = FpSubgroup(G, gens, normal=True) + return K + + def image(self): + ''' + Compute the image of `self`. + + ''' + if self._image is None: + values = list(set(self.images.values())) + if isinstance(self.codomain, PermutationGroup): + self._image = self.codomain.subgroup(values) + else: + self._image = FpSubgroup(self.codomain, values) + return self._image + + def _apply(self, elem): + ''' + Apply `self` to `elem`. + + ''' + if elem not in self.domain: + if isinstance(elem, (list, tuple)): + return [self._apply(e) for e in elem] + raise ValueError("The supplied element does not belong to the domain") + if elem.is_identity: + return self.codomain.identity + else: + images = self.images + value = self.codomain.identity + if isinstance(self.domain, PermutationGroup): + gens = self.domain.generator_product(elem, original=True) + for g in gens: + if g in self.images: + value = images[g]*value + else: + value = images[g**-1]**-1*value + else: + i = 0 + for _, p in elem.array_form: + if p < 0: + g = elem[i]**-1 + else: + g = elem[i] + value = value*images[g]**p + i += abs(p) + return value + + def __call__(self, elem): + return self._apply(elem) + + def is_injective(self): + ''' + Check if the homomorphism is injective + + ''' + return self.kernel().order() == 1 + + def is_surjective(self): + ''' + Check if the homomorphism is surjective + + ''' + im = self.image().order() + oth = self.codomain.order() + if im is S.Infinity and oth is S.Infinity: + return None + else: + return im == oth + + def is_isomorphism(self): + ''' + Check if `self` is an isomorphism. + + ''' + return self.is_injective() and self.is_surjective() + + def is_trivial(self): + ''' + Check is `self` is a trivial homomorphism, i.e. all elements + are mapped to the identity. + + ''' + return self.image().order() == 1 + + def compose(self, other): + ''' + Return the composition of `self` and `other`, i.e. + the homomorphism phi such that for all g in the domain + of `other`, phi(g) = self(other(g)) + + ''' + if not other.image().is_subgroup(self.domain): + raise ValueError("The image of `other` must be a subgroup of " + "the domain of `self`") + images = {g: self(other(g)) for g in other.images} + return GroupHomomorphism(other.domain, self.codomain, images) + + def restrict_to(self, H): + ''' + Return the restriction of the homomorphism to the subgroup `H` + of the domain. + + ''' + if not isinstance(H, PermutationGroup) or not H.is_subgroup(self.domain): + raise ValueError("Given H is not a subgroup of the domain") + domain = H + images = {g: self(g) for g in H.generators} + return GroupHomomorphism(domain, self.codomain, images) + + def invert_subgroup(self, H): + ''' + Return the subgroup of the domain that is the inverse image + of the subgroup ``H`` of the homomorphism image + + ''' + if not H.is_subgroup(self.image()): + raise ValueError("Given H is not a subgroup of the image") + gens = [] + P = PermutationGroup(self.image().identity) + for h in H.generators: + h_i = self.invert(h) + if h_i not in P: + gens.append(h_i) + P = PermutationGroup(gens) + for k in self.kernel().generators: + if k*h_i not in P: + gens.append(k*h_i) + P = PermutationGroup(gens) + return P + +def homomorphism(domain, codomain, gens, images=(), check=True): + ''' + Create (if possible) a group homomorphism from the group ``domain`` + to the group ``codomain`` defined by the images of the domain's + generators ``gens``. ``gens`` and ``images`` can be either lists or tuples + of equal sizes. If ``gens`` is a proper subset of the group's generators, + the unspecified generators will be mapped to the identity. If the + images are not specified, a trivial homomorphism will be created. + + If the given images of the generators do not define a homomorphism, + an exception is raised. + + If ``check`` is ``False``, do not check whether the given images actually + define a homomorphism. + + ''' + if not isinstance(domain, (PermutationGroup, FpGroup, FreeGroup)): + raise TypeError("The domain must be a group") + if not isinstance(codomain, (PermutationGroup, FpGroup, FreeGroup)): + raise TypeError("The codomain must be a group") + + generators = domain.generators + if not all(g in generators for g in gens): + raise ValueError("The supplied generators must be a subset of the domain's generators") + if not all(g in codomain for g in images): + raise ValueError("The images must be elements of the codomain") + + if images and len(images) != len(gens): + raise ValueError("The number of images must be equal to the number of generators") + + gens = list(gens) + images = list(images) + + images.extend([codomain.identity]*(len(generators)-len(images))) + gens.extend([g for g in generators if g not in gens]) + images = dict(zip(gens,images)) + + if check and not _check_homomorphism(domain, codomain, images): + raise ValueError("The given images do not define a homomorphism") + return GroupHomomorphism(domain, codomain, images) + +def _check_homomorphism(domain, codomain, images): + """ + Check that a given mapping of generators to images defines a homomorphism. + + Parameters + ========== + domain : PermutationGroup, FpGroup, FreeGroup + codomain : PermutationGroup, FpGroup, FreeGroup + images : dict + The set of keys must be equal to domain.generators. + The values must be elements of the codomain. + + """ + pres = domain if hasattr(domain, 'relators') else domain.presentation() + rels = pres.relators + gens = pres.generators + symbols = [g.ext_rep[0] for g in gens] + symbols_to_domain_generators = dict(zip(symbols, domain.generators)) + identity = codomain.identity + + def _image(r): + w = identity + for symbol, power in r.array_form: + g = symbols_to_domain_generators[symbol] + w *= images[g]**power + return w + + for r in rels: + if isinstance(codomain, FpGroup): + s = codomain.equals(_image(r), identity) + if s is None: + # only try to make the rewriting system + # confluent when it can't determine the + # truth of equality otherwise + success = codomain.make_confluent() + s = codomain.equals(_image(r), identity) + if s is None and not success: + raise RuntimeError("Can't determine if the images " + "define a homomorphism. Try increasing " + "the maximum number of rewriting rules " + "(group._rewriting_system.set_max(new_value); " + "the current value is stored in group._rewriting" + "_system.maxeqns)") + else: + s = _image(r).is_identity + if not s: + return False + return True + +def orbit_homomorphism(group, omega): + ''' + Return the homomorphism induced by the action of the permutation + group ``group`` on the set ``omega`` that is closed under the action. + + ''' + from sympy.combinatorics import Permutation + from sympy.combinatorics.named_groups import SymmetricGroup + codomain = SymmetricGroup(len(omega)) + identity = codomain.identity + omega = list(omega) + images = {g: identity*Permutation([omega.index(o^g) for o in omega]) for g in group.generators} + group._schreier_sims(base=omega) + H = GroupHomomorphism(group, codomain, images) + if len(group.basic_stabilizers) > len(omega): + H._kernel = group.basic_stabilizers[len(omega)] + else: + H._kernel = PermutationGroup([group.identity]) + return H + +def block_homomorphism(group, blocks): + ''' + Return the homomorphism induced by the action of the permutation + group ``group`` on the block system ``blocks``. The latter should be + of the same form as returned by the ``minimal_block`` method for + permutation groups, namely a list of length ``group.degree`` where + the i-th entry is a representative of the block i belongs to. + + ''' + from sympy.combinatorics import Permutation + from sympy.combinatorics.named_groups import SymmetricGroup + + n = len(blocks) + + # number the blocks; m is the total number, + # b is such that b[i] is the number of the block i belongs to, + # p is the list of length m such that p[i] is the representative + # of the i-th block + m = 0 + p = [] + b = [None]*n + for i in range(n): + if blocks[i] == i: + p.append(i) + b[i] = m + m += 1 + for i in range(n): + b[i] = b[blocks[i]] + + codomain = SymmetricGroup(m) + # the list corresponding to the identity permutation in codomain + identity = range(m) + images = {g: Permutation([b[p[i]^g] for i in identity]) for g in group.generators} + H = GroupHomomorphism(group, codomain, images) + return H + +def group_isomorphism(G, H, isomorphism=True): + ''' + Compute an isomorphism between 2 given groups. + + Parameters + ========== + + G : A finite ``FpGroup`` or a ``PermutationGroup``. + First group. + + H : A finite ``FpGroup`` or a ``PermutationGroup`` + Second group. + + isomorphism : bool + This is used to avoid the computation of homomorphism + when the user only wants to check if there exists + an isomorphism between the groups. + + Returns + ======= + + If isomorphism = False -- Returns a boolean. + If isomorphism = True -- Returns a boolean and an isomorphism between `G` and `H`. + + Examples + ======== + + >>> from sympy.combinatorics import free_group, Permutation + >>> from sympy.combinatorics.perm_groups import PermutationGroup + >>> from sympy.combinatorics.fp_groups import FpGroup + >>> from sympy.combinatorics.homomorphisms import group_isomorphism + >>> from sympy.combinatorics.named_groups import DihedralGroup, AlternatingGroup + + >>> D = DihedralGroup(8) + >>> p = Permutation(0, 1, 2, 3, 4, 5, 6, 7) + >>> P = PermutationGroup(p) + >>> group_isomorphism(D, P) + (False, None) + + >>> F, a, b = free_group("a, b") + >>> G = FpGroup(F, [a**3, b**3, (a*b)**2]) + >>> H = AlternatingGroup(4) + >>> (check, T) = group_isomorphism(G, H) + >>> check + True + >>> T(b*a*b**-1*a**-1*b**-1) + (0 2 3) + + Notes + ===== + + Uses the approach suggested by Robert Tarjan to compute the isomorphism between two groups. + First, the generators of ``G`` are mapped to the elements of ``H`` and + we check if the mapping induces an isomorphism. + + ''' + if not isinstance(G, (PermutationGroup, FpGroup)): + raise TypeError("The group must be a PermutationGroup or an FpGroup") + if not isinstance(H, (PermutationGroup, FpGroup)): + raise TypeError("The group must be a PermutationGroup or an FpGroup") + + if isinstance(G, FpGroup) and isinstance(H, FpGroup): + G = simplify_presentation(G) + H = simplify_presentation(H) + # Two infinite FpGroups with the same generators are isomorphic + # when the relators are same but are ordered differently. + if G.generators == H.generators and (G.relators).sort() == (H.relators).sort(): + if not isomorphism: + return True + return (True, homomorphism(G, H, G.generators, H.generators)) + + # `_H` is the permutation group isomorphic to `H`. + _H = H + g_order = G.order() + h_order = H.order() + + if g_order is S.Infinity: + raise NotImplementedError("Isomorphism methods are not implemented for infinite groups.") + + if isinstance(H, FpGroup): + if h_order is S.Infinity: + raise NotImplementedError("Isomorphism methods are not implemented for infinite groups.") + _H, h_isomorphism = H._to_perm_group() + + if (g_order != h_order) or (G.is_abelian != H.is_abelian): + if not isomorphism: + return False + return (False, None) + + if not isomorphism: + # Two groups of the same cyclic numbered order + # are isomorphic to each other. + n = g_order + if (igcd(n, totient(n))) == 1: + return True + + # Match the generators of `G` with subsets of `_H` + gens = list(G.generators) + for subset in itertools.permutations(_H, len(gens)): + images = list(subset) + images.extend([_H.identity]*(len(G.generators)-len(images))) + _images = dict(zip(gens,images)) + if _check_homomorphism(G, _H, _images): + if isinstance(H, FpGroup): + images = h_isomorphism.invert(images) + T = homomorphism(G, H, G.generators, images, check=False) + if T.is_isomorphism(): + # It is a valid isomorphism + if not isomorphism: + return True + return (True, T) + + if not isomorphism: + return False + return (False, None) + +def is_isomorphic(G, H): + ''' + Check if the groups are isomorphic to each other + + Parameters + ========== + + G : A finite ``FpGroup`` or a ``PermutationGroup`` + First group. + + H : A finite ``FpGroup`` or a ``PermutationGroup`` + Second group. + + Returns + ======= + + boolean + ''' + return group_isomorphism(G, H, isomorphism=False) diff --git a/lib/python3.12/site-packages/sympy/combinatorics/named_groups.py b/lib/python3.12/site-packages/sympy/combinatorics/named_groups.py new file mode 100644 index 0000000000000000000000000000000000000000..59f10c40ef716e3b644e00f936323e9f6936eb88 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/named_groups.py @@ -0,0 +1,332 @@ +from sympy.combinatorics.group_constructs import DirectProduct +from sympy.combinatorics.perm_groups import PermutationGroup +from sympy.combinatorics.permutations import Permutation + +_af_new = Permutation._af_new + + +def AbelianGroup(*cyclic_orders): + """ + Returns the direct product of cyclic groups with the given orders. + + Explanation + =========== + + According to the structure theorem for finite abelian groups ([1]), + every finite abelian group can be written as the direct product of + finitely many cyclic groups. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AbelianGroup + >>> AbelianGroup(3, 4) + PermutationGroup([ + (6)(0 1 2), + (3 4 5 6)]) + >>> _.is_group + True + + See Also + ======== + + DirectProduct + + References + ========== + + .. [1] https://groupprops.subwiki.org/wiki/Structure_theorem_for_finitely_generated_abelian_groups + + """ + groups = [] + degree = 0 + order = 1 + for size in cyclic_orders: + degree += size + order *= size + groups.append(CyclicGroup(size)) + G = DirectProduct(*groups) + G._is_abelian = True + G._degree = degree + G._order = order + + return G + + +def AlternatingGroup(n): + """ + Generates the alternating group on ``n`` elements as a permutation group. + + Explanation + =========== + + For ``n > 2``, the generators taken are ``(0 1 2), (0 1 2 ... n-1)`` for + ``n`` odd + and ``(0 1 2), (1 2 ... n-1)`` for ``n`` even (See [1], p.31, ex.6.9.). + After the group is generated, some of its basic properties are set. + The cases ``n = 1, 2`` are handled separately. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AlternatingGroup + >>> G = AlternatingGroup(4) + >>> G.is_group + True + >>> a = list(G.generate_dimino()) + >>> len(a) + 12 + >>> all(perm.is_even for perm in a) + True + + See Also + ======== + + SymmetricGroup, CyclicGroup, DihedralGroup + + References + ========== + + .. [1] Armstrong, M. "Groups and Symmetry" + + """ + # small cases are special + if n in (1, 2): + return PermutationGroup([Permutation([0])]) + + a = list(range(n)) + a[0], a[1], a[2] = a[1], a[2], a[0] + gen1 = a + if n % 2: + a = list(range(1, n)) + a.append(0) + gen2 = a + else: + a = list(range(2, n)) + a.append(1) + a.insert(0, 0) + gen2 = a + gens = [gen1, gen2] + if gen1 == gen2: + gens = gens[:1] + G = PermutationGroup([_af_new(a) for a in gens], dups=False) + + set_alternating_group_properties(G, n, n) + G._is_alt = True + return G + + +def set_alternating_group_properties(G, n, degree): + """Set known properties of an alternating group. """ + if n < 4: + G._is_abelian = True + G._is_nilpotent = True + else: + G._is_abelian = False + G._is_nilpotent = False + if n < 5: + G._is_solvable = True + else: + G._is_solvable = False + G._degree = degree + G._is_transitive = True + G._is_dihedral = False + + +def CyclicGroup(n): + """ + Generates the cyclic group of order ``n`` as a permutation group. + + Explanation + =========== + + The generator taken is the ``n``-cycle ``(0 1 2 ... n-1)`` + (in cycle notation). After the group is generated, some of its basic + properties are set. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import CyclicGroup + >>> G = CyclicGroup(6) + >>> G.is_group + True + >>> G.order() + 6 + >>> list(G.generate_schreier_sims(af=True)) + [[0, 1, 2, 3, 4, 5], [1, 2, 3, 4, 5, 0], [2, 3, 4, 5, 0, 1], + [3, 4, 5, 0, 1, 2], [4, 5, 0, 1, 2, 3], [5, 0, 1, 2, 3, 4]] + + See Also + ======== + + SymmetricGroup, DihedralGroup, AlternatingGroup + + """ + a = list(range(1, n)) + a.append(0) + gen = _af_new(a) + G = PermutationGroup([gen]) + + G._is_abelian = True + G._is_nilpotent = True + G._is_solvable = True + G._degree = n + G._is_transitive = True + G._order = n + G._is_dihedral = (n == 2) + return G + + +def DihedralGroup(n): + r""" + Generates the dihedral group `D_n` as a permutation group. + + Explanation + =========== + + The dihedral group `D_n` is the group of symmetries of the regular + ``n``-gon. The generators taken are the ``n``-cycle ``a = (0 1 2 ... n-1)`` + (a rotation of the ``n``-gon) and ``b = (0 n-1)(1 n-2)...`` + (a reflection of the ``n``-gon) in cycle rotation. It is easy to see that + these satisfy ``a**n = b**2 = 1`` and ``bab = ~a`` so they indeed generate + `D_n` (See [1]). After the group is generated, some of its basic properties + are set. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> G = DihedralGroup(5) + >>> G.is_group + True + >>> a = list(G.generate_dimino()) + >>> [perm.cyclic_form for perm in a] + [[], [[0, 1, 2, 3, 4]], [[0, 2, 4, 1, 3]], + [[0, 3, 1, 4, 2]], [[0, 4, 3, 2, 1]], [[0, 4], [1, 3]], + [[1, 4], [2, 3]], [[0, 1], [2, 4]], [[0, 2], [3, 4]], + [[0, 3], [1, 2]]] + + See Also + ======== + + SymmetricGroup, CyclicGroup, AlternatingGroup + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Dihedral_group + + """ + # small cases are special + if n == 1: + return PermutationGroup([Permutation([1, 0])]) + if n == 2: + return PermutationGroup([Permutation([1, 0, 3, 2]), + Permutation([2, 3, 0, 1]), Permutation([3, 2, 1, 0])]) + + a = list(range(1, n)) + a.append(0) + gen1 = _af_new(a) + a = list(range(n)) + a.reverse() + gen2 = _af_new(a) + G = PermutationGroup([gen1, gen2]) + # if n is a power of 2, group is nilpotent + if n & (n-1) == 0: + G._is_nilpotent = True + else: + G._is_nilpotent = False + G._is_dihedral = True + G._is_abelian = False + G._is_solvable = True + G._degree = n + G._is_transitive = True + G._order = 2*n + return G + + +def SymmetricGroup(n): + """ + Generates the symmetric group on ``n`` elements as a permutation group. + + Explanation + =========== + + The generators taken are the ``n``-cycle + ``(0 1 2 ... n-1)`` and the transposition ``(0 1)`` (in cycle notation). + (See [1]). After the group is generated, some of its basic properties + are set. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> G = SymmetricGroup(4) + >>> G.is_group + True + >>> G.order() + 24 + >>> list(G.generate_schreier_sims(af=True)) + [[0, 1, 2, 3], [1, 2, 3, 0], [2, 3, 0, 1], [3, 1, 2, 0], [0, 2, 3, 1], + [1, 3, 0, 2], [2, 0, 1, 3], [3, 2, 0, 1], [0, 3, 1, 2], [1, 0, 2, 3], + [2, 1, 3, 0], [3, 0, 1, 2], [0, 1, 3, 2], [1, 2, 0, 3], [2, 3, 1, 0], + [3, 1, 0, 2], [0, 2, 1, 3], [1, 3, 2, 0], [2, 0, 3, 1], [3, 2, 1, 0], + [0, 3, 2, 1], [1, 0, 3, 2], [2, 1, 0, 3], [3, 0, 2, 1]] + + See Also + ======== + + CyclicGroup, DihedralGroup, AlternatingGroup + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Symmetric_group#Generators_and_relations + + """ + if n == 1: + G = PermutationGroup([Permutation([0])]) + elif n == 2: + G = PermutationGroup([Permutation([1, 0])]) + else: + a = list(range(1, n)) + a.append(0) + gen1 = _af_new(a) + a = list(range(n)) + a[0], a[1] = a[1], a[0] + gen2 = _af_new(a) + G = PermutationGroup([gen1, gen2]) + set_symmetric_group_properties(G, n, n) + G._is_sym = True + return G + + +def set_symmetric_group_properties(G, n, degree): + """Set known properties of a symmetric group. """ + if n < 3: + G._is_abelian = True + G._is_nilpotent = True + else: + G._is_abelian = False + G._is_nilpotent = False + if n < 5: + G._is_solvable = True + else: + G._is_solvable = False + G._degree = degree + G._is_transitive = True + G._is_dihedral = (n in [2, 3]) # cf Landau's func and Stirling's approx + + +def RubikGroup(n): + """Return a group of Rubik's cube generators + + >>> from sympy.combinatorics.named_groups import RubikGroup + >>> RubikGroup(2).is_group + True + """ + from sympy.combinatorics.generators import rubik + if n <= 1: + raise ValueError("Invalid cube. n has to be greater than 1") + return PermutationGroup(rubik(n)) diff --git a/lib/python3.12/site-packages/sympy/combinatorics/pc_groups.py b/lib/python3.12/site-packages/sympy/combinatorics/pc_groups.py new file mode 100644 index 0000000000000000000000000000000000000000..dbb4b0e442ec70d4c088fb51924fadc30cdf2fbf --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/pc_groups.py @@ -0,0 +1,709 @@ +from sympy.ntheory.primetest import isprime +from sympy.combinatorics.perm_groups import PermutationGroup +from sympy.printing.defaults import DefaultPrinting +from sympy.combinatorics.free_groups import free_group + + +class PolycyclicGroup(DefaultPrinting): + + is_group = True + is_solvable = True + + def __init__(self, pc_sequence, pc_series, relative_order, collector=None): + """ + + Parameters + ========== + + pc_sequence : list + A sequence of elements whose classes generate the cyclic factor + groups of pc_series. + pc_series : list + A subnormal sequence of subgroups where each factor group is cyclic. + relative_order : list + The orders of factor groups of pc_series. + collector : Collector + By default, it is None. Collector class provides the + polycyclic presentation with various other functionalities. + + """ + self.pcgs = pc_sequence + self.pc_series = pc_series + self.relative_order = relative_order + self.collector = Collector(self.pcgs, pc_series, relative_order) if not collector else collector + + def is_prime_order(self): + return all(isprime(order) for order in self.relative_order) + + def length(self): + return len(self.pcgs) + + +class Collector(DefaultPrinting): + + """ + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of Computational Group Theory" + Section 8.1.3 + """ + + def __init__(self, pcgs, pc_series, relative_order, free_group_=None, pc_presentation=None): + """ + + Most of the parameters for the Collector class are the same as for PolycyclicGroup. + Others are described below. + + Parameters + ========== + + free_group_ : tuple + free_group_ provides the mapping of polycyclic generating + sequence with the free group elements. + pc_presentation : dict + Provides the presentation of polycyclic groups with the + help of power and conjugate relators. + + See Also + ======== + + PolycyclicGroup + + """ + self.pcgs = pcgs + self.pc_series = pc_series + self.relative_order = relative_order + self.free_group = free_group('x:{}'.format(len(pcgs)))[0] if not free_group_ else free_group_ + self.index = {s: i for i, s in enumerate(self.free_group.symbols)} + self.pc_presentation = self.pc_relators() + + def minimal_uncollected_subword(self, word): + r""" + Returns the minimal uncollected subwords. + + Explanation + =========== + + A word ``v`` defined on generators in ``X`` is a minimal + uncollected subword of the word ``w`` if ``v`` is a subword + of ``w`` and it has one of the following form + + * `v = {x_{i+1}}^{a_j}x_i` + + * `v = {x_{i+1}}^{a_j}{x_i}^{-1}` + + * `v = {x_i}^{a_j}` + + for `a_j` not in `\{1, \ldots, s-1\}`. Where, ``s`` is the power + exponent of the corresponding generator. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics import free_group + >>> G = SymmetricGroup(4) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> F, x1, x2 = free_group("x1, x2") + >>> word = x2**2*x1**7 + >>> collector.minimal_uncollected_subword(word) + ((x2, 2),) + + """ + # To handle the case word = + if not word: + return None + + array = word.array_form + re = self.relative_order + index = self.index + + for i in range(len(array)): + s1, e1 = array[i] + + if re[index[s1]] and (e1 < 0 or e1 > re[index[s1]]-1): + return ((s1, e1), ) + + for i in range(len(array)-1): + s1, e1 = array[i] + s2, e2 = array[i+1] + + if index[s1] > index[s2]: + e = 1 if e2 > 0 else -1 + return ((s1, e1), (s2, e)) + + return None + + def relations(self): + """ + Separates the given relators of pc presentation in power and + conjugate relations. + + Returns + ======= + + (power_rel, conj_rel) + Separates pc presentation into power and conjugate relations. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> G = SymmetricGroup(3) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> power_rel, conj_rel = collector.relations() + >>> power_rel + {x0**2: (), x1**3: ()} + >>> conj_rel + {x0**-1*x1*x0: x1**2} + + See Also + ======== + + pc_relators + + """ + power_relators = {} + conjugate_relators = {} + for key, value in self.pc_presentation.items(): + if len(key.array_form) == 1: + power_relators[key] = value + else: + conjugate_relators[key] = value + return power_relators, conjugate_relators + + def subword_index(self, word, w): + """ + Returns the start and ending index of a given + subword in a word. + + Parameters + ========== + + word : FreeGroupElement + word defined on free group elements for a + polycyclic group. + w : FreeGroupElement + subword of a given word, whose starting and + ending index to be computed. + + Returns + ======= + + (i, j) + A tuple containing starting and ending index of ``w`` + in the given word. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics import free_group + >>> G = SymmetricGroup(4) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> F, x1, x2 = free_group("x1, x2") + >>> word = x2**2*x1**7 + >>> w = x2**2*x1 + >>> collector.subword_index(word, w) + (0, 3) + >>> w = x1**7 + >>> collector.subword_index(word, w) + (2, 9) + + """ + low = -1 + high = -1 + for i in range(len(word)-len(w)+1): + if word.subword(i, i+len(w)) == w: + low = i + high = i+len(w) + break + if low == high == -1: + return -1, -1 + return low, high + + def map_relation(self, w): + """ + Return a conjugate relation. + + Explanation + =========== + + Given a word formed by two free group elements, the + corresponding conjugate relation with those free + group elements is formed and mapped with the collected + word in the polycyclic presentation. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics import free_group + >>> G = SymmetricGroup(3) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> F, x0, x1 = free_group("x0, x1") + >>> w = x1*x0 + >>> collector.map_relation(w) + x1**2 + + See Also + ======== + + pc_presentation + + """ + array = w.array_form + s1 = array[0][0] + s2 = array[1][0] + key = ((s2, -1), (s1, 1), (s2, 1)) + key = self.free_group.dtype(key) + return self.pc_presentation[key] + + + def collected_word(self, word): + r""" + Return the collected form of a word. + + Explanation + =========== + + A word ``w`` is called collected, if `w = {x_{i_1}}^{a_1} * \ldots * + {x_{i_r}}^{a_r}` with `i_1 < i_2< \ldots < i_r` and `a_j` is in + `\{1, \ldots, {s_j}-1\}`. + + Otherwise w is uncollected. + + Parameters + ========== + + word : FreeGroupElement + An uncollected word. + + Returns + ======= + + word + A collected word of form `w = {x_{i_1}}^{a_1}, \ldots, + {x_{i_r}}^{a_r}` with `i_1, i_2, \ldots, i_r` and `a_j \in + \{1, \ldots, {s_j}-1\}`. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics.perm_groups import PermutationGroup + >>> from sympy.combinatorics import free_group + >>> G = SymmetricGroup(4) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> F, x0, x1, x2, x3 = free_group("x0, x1, x2, x3") + >>> word = x3*x2*x1*x0 + >>> collected_word = collector.collected_word(word) + >>> free_to_perm = {} + >>> free_group = collector.free_group + >>> for sym, gen in zip(free_group.symbols, collector.pcgs): + ... free_to_perm[sym] = gen + >>> G1 = PermutationGroup() + >>> for w in word: + ... sym = w[0] + ... perm = free_to_perm[sym] + ... G1 = PermutationGroup([perm] + G1.generators) + >>> G2 = PermutationGroup() + >>> for w in collected_word: + ... sym = w[0] + ... perm = free_to_perm[sym] + ... G2 = PermutationGroup([perm] + G2.generators) + + The two are not identical, but they are equivalent: + + >>> G1.equals(G2), G1 == G2 + (True, False) + + See Also + ======== + + minimal_uncollected_subword + + """ + free_group = self.free_group + while True: + w = self.minimal_uncollected_subword(word) + if not w: + break + + low, high = self.subword_index(word, free_group.dtype(w)) + if low == -1: + continue + + s1, e1 = w[0] + if len(w) == 1: + re = self.relative_order[self.index[s1]] + q = e1 // re + r = e1-q*re + + key = ((w[0][0], re), ) + key = free_group.dtype(key) + if self.pc_presentation[key]: + presentation = self.pc_presentation[key].array_form + sym, exp = presentation[0] + word_ = ((w[0][0], r), (sym, q*exp)) + word_ = free_group.dtype(word_) + else: + if r != 0: + word_ = ((w[0][0], r), ) + word_ = free_group.dtype(word_) + else: + word_ = None + word = word.eliminate_word(free_group.dtype(w), word_) + + if len(w) == 2 and w[1][1] > 0: + s2, e2 = w[1] + s2 = ((s2, 1), ) + s2 = free_group.dtype(s2) + word_ = self.map_relation(free_group.dtype(w)) + word_ = s2*word_**e1 + word_ = free_group.dtype(word_) + word = word.substituted_word(low, high, word_) + + elif len(w) == 2 and w[1][1] < 0: + s2, e2 = w[1] + s2 = ((s2, 1), ) + s2 = free_group.dtype(s2) + word_ = self.map_relation(free_group.dtype(w)) + word_ = s2**-1*word_**e1 + word_ = free_group.dtype(word_) + word = word.substituted_word(low, high, word_) + + return word + + + def pc_relators(self): + r""" + Return the polycyclic presentation. + + Explanation + =========== + + There are two types of relations used in polycyclic + presentation. + + * Power relations : Power relators are of the form `x_i^{re_i}`, + where `i \in \{0, \ldots, \mathrm{len(pcgs)}\}`, ``x`` represents polycyclic + generator and ``re`` is the corresponding relative order. + + * Conjugate relations : Conjugate relators are of the form `x_j^-1x_ix_j`, + where `j < i \in \{0, \ldots, \mathrm{len(pcgs)}\}`. + + Returns + ======= + + A dictionary with power and conjugate relations as key and + their collected form as corresponding values. + + Notes + ===== + + Identity Permutation is mapped with empty ``()``. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics.permutations import Permutation + >>> S = SymmetricGroup(49).sylow_subgroup(7) + >>> der = S.derived_series() + >>> G = der[len(der)-2] + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> pcgs = PcGroup.pcgs + >>> len(pcgs) + 6 + >>> free_group = collector.free_group + >>> pc_resentation = collector.pc_presentation + >>> free_to_perm = {} + >>> for s, g in zip(free_group.symbols, pcgs): + ... free_to_perm[s] = g + + >>> for k, v in pc_resentation.items(): + ... k_array = k.array_form + ... if v != (): + ... v_array = v.array_form + ... lhs = Permutation() + ... for gen in k_array: + ... s = gen[0] + ... e = gen[1] + ... lhs = lhs*free_to_perm[s]**e + ... if v == (): + ... assert lhs.is_identity + ... continue + ... rhs = Permutation() + ... for gen in v_array: + ... s = gen[0] + ... e = gen[1] + ... rhs = rhs*free_to_perm[s]**e + ... assert lhs == rhs + + """ + free_group = self.free_group + rel_order = self.relative_order + pc_relators = {} + perm_to_free = {} + pcgs = self.pcgs + + for gen, s in zip(pcgs, free_group.generators): + perm_to_free[gen**-1] = s**-1 + perm_to_free[gen] = s + + pcgs = pcgs[::-1] + series = self.pc_series[::-1] + rel_order = rel_order[::-1] + collected_gens = [] + + for i, gen in enumerate(pcgs): + re = rel_order[i] + relation = perm_to_free[gen]**re + G = series[i] + + l = G.generator_product(gen**re, original = True) + l.reverse() + + word = free_group.identity + for g in l: + word = word*perm_to_free[g] + + word = self.collected_word(word) + pc_relators[relation] = word if word else () + self.pc_presentation = pc_relators + + collected_gens.append(gen) + if len(collected_gens) > 1: + conj = collected_gens[len(collected_gens)-1] + conjugator = perm_to_free[conj] + + for j in range(len(collected_gens)-1): + conjugated = perm_to_free[collected_gens[j]] + + relation = conjugator**-1*conjugated*conjugator + gens = conj**-1*collected_gens[j]*conj + + l = G.generator_product(gens, original = True) + l.reverse() + word = free_group.identity + for g in l: + word = word*perm_to_free[g] + + word = self.collected_word(word) + pc_relators[relation] = word if word else () + self.pc_presentation = pc_relators + + return pc_relators + + def exponent_vector(self, element): + r""" + Return the exponent vector of length equal to the + length of polycyclic generating sequence. + + Explanation + =========== + + For a given generator/element ``g`` of the polycyclic group, + it can be represented as `g = {x_1}^{e_1}, \ldots, {x_n}^{e_n}`, + where `x_i` represents polycyclic generators and ``n`` is + the number of generators in the free_group equal to the length + of pcgs. + + Parameters + ========== + + element : Permutation + Generator of a polycyclic group. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics.permutations import Permutation + >>> G = SymmetricGroup(4) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> pcgs = PcGroup.pcgs + >>> collector.exponent_vector(G[0]) + [1, 0, 0, 0] + >>> exp = collector.exponent_vector(G[1]) + >>> g = Permutation() + >>> for i in range(len(exp)): + ... g = g*pcgs[i]**exp[i] if exp[i] else g + >>> assert g == G[1] + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of Computational Group Theory" + Section 8.1.1, Definition 8.4 + + """ + free_group = self.free_group + G = PermutationGroup() + for g in self.pcgs: + G = PermutationGroup([g] + G.generators) + gens = G.generator_product(element, original = True) + gens.reverse() + + perm_to_free = {} + for sym, g in zip(free_group.generators, self.pcgs): + perm_to_free[g**-1] = sym**-1 + perm_to_free[g] = sym + w = free_group.identity + for g in gens: + w = w*perm_to_free[g] + + word = self.collected_word(w) + + index = self.index + exp_vector = [0]*len(free_group) + word = word.array_form + for t in word: + exp_vector[index[t[0]]] = t[1] + return exp_vector + + def depth(self, element): + r""" + Return the depth of a given element. + + Explanation + =========== + + The depth of a given element ``g`` is defined by + `\mathrm{dep}[g] = i` if `e_1 = e_2 = \ldots = e_{i-1} = 0` + and `e_i != 0`, where ``e`` represents the exponent-vector. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> G = SymmetricGroup(3) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> collector.depth(G[0]) + 2 + >>> collector.depth(G[1]) + 1 + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of Computational Group Theory" + Section 8.1.1, Definition 8.5 + + """ + exp_vector = self.exponent_vector(element) + return next((i+1 for i, x in enumerate(exp_vector) if x), len(self.pcgs)+1) + + def leading_exponent(self, element): + r""" + Return the leading non-zero exponent. + + Explanation + =========== + + The leading exponent for a given element `g` is defined + by `\mathrm{leading\_exponent}[g]` `= e_i`, if `\mathrm{depth}[g] = i`. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> G = SymmetricGroup(3) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> collector.leading_exponent(G[1]) + 1 + + """ + exp_vector = self.exponent_vector(element) + depth = self.depth(element) + if depth != len(self.pcgs)+1: + return exp_vector[depth-1] + return None + + def _sift(self, z, g): + h = g + d = self.depth(h) + while d < len(self.pcgs) and z[d-1] != 1: + k = z[d-1] + e = self.leading_exponent(h)*(self.leading_exponent(k))**-1 + e = e % self.relative_order[d-1] + h = k**-e*h + d = self.depth(h) + return h + + def induced_pcgs(self, gens): + """ + + Parameters + ========== + + gens : list + A list of generators on which polycyclic subgroup + is to be defined. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> S = SymmetricGroup(8) + >>> G = S.sylow_subgroup(2) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> gens = [G[0], G[1]] + >>> ipcgs = collector.induced_pcgs(gens) + >>> [gen.order() for gen in ipcgs] + [2, 2, 2] + >>> G = S.sylow_subgroup(3) + >>> PcGroup = G.polycyclic_group() + >>> collector = PcGroup.collector + >>> gens = [G[0], G[1]] + >>> ipcgs = collector.induced_pcgs(gens) + >>> [gen.order() for gen in ipcgs] + [3] + + """ + z = [1]*len(self.pcgs) + G = gens + while G: + g = G.pop(0) + h = self._sift(z, g) + d = self.depth(h) + if d < len(self.pcgs): + for gen in z: + if gen != 1: + G.append(h**-1*gen**-1*h*gen) + z[d-1] = h; + z = [gen for gen in z if gen != 1] + return z + + def constructive_membership_test(self, ipcgs, g): + """ + Return the exponent vector for induced pcgs. + """ + e = [0]*len(ipcgs) + h = g + d = self.depth(h) + for i, gen in enumerate(ipcgs): + while self.depth(gen) == d: + f = self.leading_exponent(h)*self.leading_exponent(gen) + f = f % self.relative_order[d-1] + h = gen**(-f)*h + e[i] = f + d = self.depth(h) + if h == 1: + return e + return False diff --git a/lib/python3.12/site-packages/sympy/combinatorics/perm_groups.py b/lib/python3.12/site-packages/sympy/combinatorics/perm_groups.py new file mode 100644 index 0000000000000000000000000000000000000000..1a72aea90b2c65eac42e5f62316b86c94f9eebad --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/perm_groups.py @@ -0,0 +1,5463 @@ +from math import factorial as _factorial, log, prod +from itertools import chain, product + + +from sympy.combinatorics import Permutation +from sympy.combinatorics.permutations import (_af_commutes_with, _af_invert, + _af_rmul, _af_rmuln, _af_pow, Cycle) +from sympy.combinatorics.util import (_check_cycles_alt_sym, + _distribute_gens_by_base, _orbits_transversals_from_bsgs, + _handle_precomputed_bsgs, _base_ordering, _strong_gens_from_distr, + _strip, _strip_af) +from sympy.core import Basic +from sympy.core.random import _randrange, randrange, choice +from sympy.core.symbol import Symbol +from sympy.core.sympify import _sympify +from sympy.functions.combinatorial.factorials import factorial +from sympy.ntheory import primefactors, sieve +from sympy.ntheory.factor_ import (factorint, multiplicity) +from sympy.ntheory.primetest import isprime +from sympy.utilities.iterables import has_variety, is_sequence, uniq + +rmul = Permutation.rmul_with_af +_af_new = Permutation._af_new + + +class PermutationGroup(Basic): + r"""The class defining a Permutation group. + + Explanation + =========== + + ``PermutationGroup([p1, p2, ..., pn])`` returns the permutation group + generated by the list of permutations. This group can be supplied + to Polyhedron if one desires to decorate the elements to which the + indices of the permutation refer. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> from sympy.combinatorics import Polyhedron + + The permutations corresponding to motion of the front, right and + bottom face of a $2 \times 2$ Rubik's cube are defined: + + >>> F = Permutation(2, 19, 21, 8)(3, 17, 20, 10)(4, 6, 7, 5) + >>> R = Permutation(1, 5, 21, 14)(3, 7, 23, 12)(8, 10, 11, 9) + >>> D = Permutation(6, 18, 14, 10)(7, 19, 15, 11)(20, 22, 23, 21) + + These are passed as permutations to PermutationGroup: + + >>> G = PermutationGroup(F, R, D) + >>> G.order() + 3674160 + + The group can be supplied to a Polyhedron in order to track the + objects being moved. An example involving the $2 \times 2$ Rubik's cube is + given there, but here is a simple demonstration: + + >>> a = Permutation(2, 1) + >>> b = Permutation(1, 0) + >>> G = PermutationGroup(a, b) + >>> P = Polyhedron(list('ABC'), pgroup=G) + >>> P.corners + (A, B, C) + >>> P.rotate(0) # apply permutation 0 + >>> P.corners + (A, C, B) + >>> P.reset() + >>> P.corners + (A, B, C) + + Or one can make a permutation as a product of selected permutations + and apply them to an iterable directly: + + >>> P10 = G.make_perm([0, 1]) + >>> P10('ABC') + ['C', 'A', 'B'] + + See Also + ======== + + sympy.combinatorics.polyhedron.Polyhedron, + sympy.combinatorics.permutations.Permutation + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of Computational Group Theory" + + .. [2] Seress, A. + "Permutation Group Algorithms" + + .. [3] https://en.wikipedia.org/wiki/Schreier_vector + + .. [4] https://en.wikipedia.org/wiki/Nielsen_transformation#Product_replacement_algorithm + + .. [5] Frank Celler, Charles R.Leedham-Green, Scott H.Murray, + Alice C.Niemeyer, and E.A.O'Brien. "Generating Random + Elements of a Finite Group" + + .. [6] https://en.wikipedia.org/wiki/Block_%28permutation_group_theory%29 + + .. [7] https://algorithmist.com/wiki/Union_find + + .. [8] https://en.wikipedia.org/wiki/Multiply_transitive_group#Multiply_transitive_groups + + .. [9] https://en.wikipedia.org/wiki/Center_%28group_theory%29 + + .. [10] https://en.wikipedia.org/wiki/Centralizer_and_normalizer + + .. [11] https://groupprops.subwiki.org/wiki/Derived_subgroup + + .. [12] https://en.wikipedia.org/wiki/Nilpotent_group + + .. [13] https://www.math.colostate.edu/~hulpke/CGT/cgtnotes.pdf + + .. [14] https://docs.gap-system.org/doc/ref/manual.pdf + + """ + is_group = True + + def __new__(cls, *args, dups=True, **kwargs): + """The default constructor. Accepts Cycle and Permutation forms. + Removes duplicates unless ``dups`` keyword is ``False``. + """ + if not args: + args = [Permutation()] + else: + args = list(args[0] if is_sequence(args[0]) else args) + if not args: + args = [Permutation()] + if any(isinstance(a, Cycle) for a in args): + args = [Permutation(a) for a in args] + if has_variety(a.size for a in args): + degree = kwargs.pop('degree', None) + if degree is None: + degree = max(a.size for a in args) + for i in range(len(args)): + if args[i].size != degree: + args[i] = Permutation(args[i], size=degree) + if dups: + args = list(uniq([_af_new(list(a)) for a in args])) + if len(args) > 1: + args = [g for g in args if not g.is_identity] + return Basic.__new__(cls, *args, **kwargs) + + def __init__(self, *args, **kwargs): + self._generators = list(self.args) + self._order = None + self._elements = [] + self._center = None + self._is_abelian = None + self._is_transitive = None + self._is_sym = None + self._is_alt = None + self._is_primitive = None + self._is_nilpotent = None + self._is_solvable = None + self._is_trivial = None + self._transitivity_degree = None + self._max_div = None + self._is_perfect = None + self._is_cyclic = None + self._is_dihedral = None + self._r = len(self._generators) + self._degree = self._generators[0].size + + # these attributes are assigned after running schreier_sims + self._base = [] + self._strong_gens = [] + self._strong_gens_slp = [] + self._basic_orbits = [] + self._transversals = [] + self._transversal_slp = [] + + # these attributes are assigned after running _random_pr_init + self._random_gens = [] + + # finite presentation of the group as an instance of `FpGroup` + self._fp_presentation = None + + def __getitem__(self, i): + return self._generators[i] + + def __contains__(self, i): + """Return ``True`` if *i* is contained in PermutationGroup. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> p = Permutation(1, 2, 3) + >>> Permutation(3) in PermutationGroup(p) + True + + """ + if not isinstance(i, Permutation): + raise TypeError("A PermutationGroup contains only Permutations as " + "elements, not elements of type %s" % type(i)) + return self.contains(i) + + def __len__(self): + return len(self._generators) + + def equals(self, other): + """Return ``True`` if PermutationGroup generated by elements in the + group are same i.e they represent the same PermutationGroup. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> p = Permutation(0, 1, 2, 3, 4, 5) + >>> G = PermutationGroup([p, p**2]) + >>> H = PermutationGroup([p**2, p]) + >>> G.generators == H.generators + False + >>> G.equals(H) + True + + """ + if not isinstance(other, PermutationGroup): + return False + + set_self_gens = set(self.generators) + set_other_gens = set(other.generators) + + # before reaching the general case there are also certain + # optimisation and obvious cases requiring less or no actual + # computation. + if set_self_gens == set_other_gens: + return True + + # in the most general case it will check that each generator of + # one group belongs to the other PermutationGroup and vice-versa + for gen1 in set_self_gens: + if not other.contains(gen1): + return False + for gen2 in set_other_gens: + if not self.contains(gen2): + return False + return True + + def __mul__(self, other): + """ + Return the direct product of two permutation groups as a permutation + group. + + Explanation + =========== + + This implementation realizes the direct product by shifting the index + set for the generators of the second group: so if we have ``G`` acting + on ``n1`` points and ``H`` acting on ``n2`` points, ``G*H`` acts on + ``n1 + n2`` points. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import CyclicGroup + >>> G = CyclicGroup(5) + >>> H = G*G + >>> H + PermutationGroup([ + (9)(0 1 2 3 4), + (5 6 7 8 9)]) + >>> H.order() + 25 + + """ + if isinstance(other, Permutation): + return Coset(other, self, dir='+') + gens1 = [perm._array_form for perm in self.generators] + gens2 = [perm._array_form for perm in other.generators] + n1 = self._degree + n2 = other._degree + start = list(range(n1)) + end = list(range(n1, n1 + n2)) + for i in range(len(gens2)): + gens2[i] = [x + n1 for x in gens2[i]] + gens2 = [start + gen for gen in gens2] + gens1 = [gen + end for gen in gens1] + together = gens1 + gens2 + gens = [_af_new(x) for x in together] + return PermutationGroup(gens) + + def _random_pr_init(self, r, n, _random_prec_n=None): + r"""Initialize random generators for the product replacement algorithm. + + Explanation + =========== + + The implementation uses a modification of the original product + replacement algorithm due to Leedham-Green, as described in [1], + pp. 69-71; also, see [2], pp. 27-29 for a detailed theoretical + analysis of the original product replacement algorithm, and [4]. + + The product replacement algorithm is used for producing random, + uniformly distributed elements of a group `G` with a set of generators + `S`. For the initialization ``_random_pr_init``, a list ``R`` of + `\max\{r, |S|\}` group generators is created as the attribute + ``G._random_gens``, repeating elements of `S` if necessary, and the + identity element of `G` is appended to ``R`` - we shall refer to this + last element as the accumulator. Then the function ``random_pr()`` + is called ``n`` times, randomizing the list ``R`` while preserving + the generation of `G` by ``R``. The function ``random_pr()`` itself + takes two random elements ``g, h`` among all elements of ``R`` but + the accumulator and replaces ``g`` with a randomly chosen element + from `\{gh, g(~h), hg, (~h)g\}`. Then the accumulator is multiplied + by whatever ``g`` was replaced by. The new value of the accumulator is + then returned by ``random_pr()``. + + The elements returned will eventually (for ``n`` large enough) become + uniformly distributed across `G` ([5]). For practical purposes however, + the values ``n = 50, r = 11`` are suggested in [1]. + + Notes + ===== + + THIS FUNCTION HAS SIDE EFFECTS: it changes the attribute + self._random_gens + + See Also + ======== + + random_pr + + """ + deg = self.degree + random_gens = [x._array_form for x in self.generators] + k = len(random_gens) + if k < r: + for i in range(k, r): + random_gens.append(random_gens[i - k]) + acc = list(range(deg)) + random_gens.append(acc) + self._random_gens = random_gens + + # handle randomized input for testing purposes + if _random_prec_n is None: + for i in range(n): + self.random_pr() + else: + for i in range(n): + self.random_pr(_random_prec=_random_prec_n[i]) + + def _union_find_merge(self, first, second, ranks, parents, not_rep): + """Merges two classes in a union-find data structure. + + Explanation + =========== + + Used in the implementation of Atkinson's algorithm as suggested in [1], + pp. 83-87. The class merging process uses union by rank as an + optimization. ([7]) + + Notes + ===== + + THIS FUNCTION HAS SIDE EFFECTS: the list of class representatives, + ``parents``, the list of class sizes, ``ranks``, and the list of + elements that are not representatives, ``not_rep``, are changed due to + class merging. + + See Also + ======== + + minimal_block, _union_find_rep + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of computational group theory" + + .. [7] https://algorithmist.com/wiki/Union_find + + """ + rep_first = self._union_find_rep(first, parents) + rep_second = self._union_find_rep(second, parents) + if rep_first != rep_second: + # union by rank + if ranks[rep_first] >= ranks[rep_second]: + new_1, new_2 = rep_first, rep_second + else: + new_1, new_2 = rep_second, rep_first + total_rank = ranks[new_1] + ranks[new_2] + if total_rank > self.max_div: + return -1 + parents[new_2] = new_1 + ranks[new_1] = total_rank + not_rep.append(new_2) + return 1 + return 0 + + def _union_find_rep(self, num, parents): + """Find representative of a class in a union-find data structure. + + Explanation + =========== + + Used in the implementation of Atkinson's algorithm as suggested in [1], + pp. 83-87. After the representative of the class to which ``num`` + belongs is found, path compression is performed as an optimization + ([7]). + + Notes + ===== + + THIS FUNCTION HAS SIDE EFFECTS: the list of class representatives, + ``parents``, is altered due to path compression. + + See Also + ======== + + minimal_block, _union_find_merge + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of computational group theory" + + .. [7] https://algorithmist.com/wiki/Union_find + + """ + rep, parent = num, parents[num] + while parent != rep: + rep = parent + parent = parents[rep] + # path compression + temp, parent = num, parents[num] + while parent != rep: + parents[temp] = rep + temp = parent + parent = parents[temp] + return rep + + @property + def base(self): + r"""Return a base from the Schreier-Sims algorithm. + + Explanation + =========== + + For a permutation group `G`, a base is a sequence of points + `B = (b_1, b_2, \dots, b_k)` such that no element of `G` apart + from the identity fixes all the points in `B`. The concepts of + a base and strong generating set and their applications are + discussed in depth in [1], pp. 87-89 and [2], pp. 55-57. + + An alternative way to think of `B` is that it gives the + indices of the stabilizer cosets that contain more than the + identity permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> G = PermutationGroup([Permutation(0, 1, 3)(2, 4)]) + >>> G.base + [0, 2] + + See Also + ======== + + strong_gens, basic_transversals, basic_orbits, basic_stabilizers + + """ + if self._base == []: + self.schreier_sims() + return self._base + + def baseswap(self, base, strong_gens, pos, randomized=False, + transversals=None, basic_orbits=None, strong_gens_distr=None): + r"""Swap two consecutive base points in base and strong generating set. + + Explanation + =========== + + If a base for a group `G` is given by `(b_1, b_2, \dots, b_k)`, this + function returns a base `(b_1, b_2, \dots, b_{i+1}, b_i, \dots, b_k)`, + where `i` is given by ``pos``, and a strong generating set relative + to that base. The original base and strong generating set are not + modified. + + The randomized version (default) is of Las Vegas type. + + Parameters + ========== + + base, strong_gens + The base and strong generating set. + pos + The position at which swapping is performed. + randomized + A switch between randomized and deterministic version. + transversals + The transversals for the basic orbits, if known. + basic_orbits + The basic orbits, if known. + strong_gens_distr + The strong generators distributed by basic stabilizers, if known. + + Returns + ======= + + (base, strong_gens) + ``base`` is the new base, and ``strong_gens`` is a generating set + relative to it. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics.testutil import _verify_bsgs + >>> from sympy.combinatorics.perm_groups import PermutationGroup + >>> S = SymmetricGroup(4) + >>> S.schreier_sims() + >>> S.base + [0, 1, 2] + >>> base, gens = S.baseswap(S.base, S.strong_gens, 1, randomized=False) + >>> base, gens + ([0, 2, 1], + [(0 1 2 3), (3)(0 1), (1 3 2), + (2 3), (1 3)]) + + check that base, gens is a BSGS + + >>> S1 = PermutationGroup(gens) + >>> _verify_bsgs(S1, base, gens) + True + + See Also + ======== + + schreier_sims + + Notes + ===== + + The deterministic version of the algorithm is discussed in + [1], pp. 102-103; the randomized version is discussed in [1], p.103, and + [2], p.98. It is of Las Vegas type. + Notice that [1] contains a mistake in the pseudocode and + discussion of BASESWAP: on line 3 of the pseudocode, + `|\beta_{i+1}^{\left\langle T\right\rangle}|` should be replaced by + `|\beta_{i}^{\left\langle T\right\rangle}|`, and the same for the + discussion of the algorithm. + + """ + # construct the basic orbits, generators for the stabilizer chain + # and transversal elements from whatever was provided + transversals, basic_orbits, strong_gens_distr = \ + _handle_precomputed_bsgs(base, strong_gens, transversals, + basic_orbits, strong_gens_distr) + base_len = len(base) + degree = self.degree + # size of orbit of base[pos] under the stabilizer we seek to insert + # in the stabilizer chain at position pos + 1 + size = len(basic_orbits[pos])*len(basic_orbits[pos + 1]) \ + //len(_orbit(degree, strong_gens_distr[pos], base[pos + 1])) + # initialize the wanted stabilizer by a subgroup + if pos + 2 > base_len - 1: + T = [] + else: + T = strong_gens_distr[pos + 2][:] + # randomized version + if randomized is True: + stab_pos = PermutationGroup(strong_gens_distr[pos]) + schreier_vector = stab_pos.schreier_vector(base[pos + 1]) + # add random elements of the stabilizer until they generate it + while len(_orbit(degree, T, base[pos])) != size: + new = stab_pos.random_stab(base[pos + 1], + schreier_vector=schreier_vector) + T.append(new) + # deterministic version + else: + Gamma = set(basic_orbits[pos]) + Gamma.remove(base[pos]) + if base[pos + 1] in Gamma: + Gamma.remove(base[pos + 1]) + # add elements of the stabilizer until they generate it by + # ruling out member of the basic orbit of base[pos] along the way + while len(_orbit(degree, T, base[pos])) != size: + gamma = next(iter(Gamma)) + x = transversals[pos][gamma] + temp = x._array_form.index(base[pos + 1]) # (~x)(base[pos + 1]) + if temp not in basic_orbits[pos + 1]: + Gamma = Gamma - _orbit(degree, T, gamma) + else: + y = transversals[pos + 1][temp] + el = rmul(x, y) + if el(base[pos]) not in _orbit(degree, T, base[pos]): + T.append(el) + Gamma = Gamma - _orbit(degree, T, base[pos]) + # build the new base and strong generating set + strong_gens_new_distr = strong_gens_distr[:] + strong_gens_new_distr[pos + 1] = T + base_new = base[:] + base_new[pos], base_new[pos + 1] = base_new[pos + 1], base_new[pos] + strong_gens_new = _strong_gens_from_distr(strong_gens_new_distr) + for gen in T: + if gen not in strong_gens_new: + strong_gens_new.append(gen) + return base_new, strong_gens_new + + @property + def basic_orbits(self): + r""" + Return the basic orbits relative to a base and strong generating set. + + Explanation + =========== + + If `(b_1, b_2, \dots, b_k)` is a base for a group `G`, and + `G^{(i)} = G_{b_1, b_2, \dots, b_{i-1}}` is the ``i``-th basic stabilizer + (so that `G^{(1)} = G`), the ``i``-th basic orbit relative to this base + is the orbit of `b_i` under `G^{(i)}`. See [1], pp. 87-89 for more + information. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> S = SymmetricGroup(4) + >>> S.basic_orbits + [[0, 1, 2, 3], [1, 2, 3], [2, 3]] + + See Also + ======== + + base, strong_gens, basic_transversals, basic_stabilizers + + """ + if self._basic_orbits == []: + self.schreier_sims() + return self._basic_orbits + + @property + def basic_stabilizers(self): + r""" + Return a chain of stabilizers relative to a base and strong generating + set. + + Explanation + =========== + + The ``i``-th basic stabilizer `G^{(i)}` relative to a base + `(b_1, b_2, \dots, b_k)` is `G_{b_1, b_2, \dots, b_{i-1}}`. For more + information, see [1], pp. 87-89. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AlternatingGroup + >>> A = AlternatingGroup(4) + >>> A.schreier_sims() + >>> A.base + [0, 1] + >>> for g in A.basic_stabilizers: + ... print(g) + ... + PermutationGroup([ + (3)(0 1 2), + (1 2 3)]) + PermutationGroup([ + (1 2 3)]) + + See Also + ======== + + base, strong_gens, basic_orbits, basic_transversals + + """ + + if self._transversals == []: + self.schreier_sims() + strong_gens = self._strong_gens + base = self._base + if not base: # e.g. if self is trivial + return [] + strong_gens_distr = _distribute_gens_by_base(base, strong_gens) + basic_stabilizers = [] + for gens in strong_gens_distr: + basic_stabilizers.append(PermutationGroup(gens)) + return basic_stabilizers + + @property + def basic_transversals(self): + """ + Return basic transversals relative to a base and strong generating set. + + Explanation + =========== + + The basic transversals are transversals of the basic orbits. They + are provided as a list of dictionaries, each dictionary having + keys - the elements of one of the basic orbits, and values - the + corresponding transversal elements. See [1], pp. 87-89 for more + information. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AlternatingGroup + >>> A = AlternatingGroup(4) + >>> A.basic_transversals + [{0: (3), 1: (3)(0 1 2), 2: (3)(0 2 1), 3: (0 3 1)}, {1: (3), 2: (1 2 3), 3: (1 3 2)}] + + See Also + ======== + + strong_gens, base, basic_orbits, basic_stabilizers + + """ + + if self._transversals == []: + self.schreier_sims() + return self._transversals + + def composition_series(self): + r""" + Return the composition series for a group as a list + of permutation groups. + + Explanation + =========== + + The composition series for a group `G` is defined as a + subnormal series `G = H_0 > H_1 > H_2 \ldots` A composition + series is a subnormal series such that each factor group + `H(i+1) / H(i)` is simple. + A subnormal series is a composition series only if it is of + maximum length. + + The algorithm works as follows: + Starting with the derived series the idea is to fill + the gap between `G = der[i]` and `H = der[i+1]` for each + `i` independently. Since, all subgroups of the abelian group + `G/H` are normal so, first step is to take the generators + `g` of `G` and add them to generators of `H` one by one. + + The factor groups formed are not simple in general. Each + group is obtained from the previous one by adding one + generator `g`, if the previous group is denoted by `H` + then the next group `K` is generated by `g` and `H`. + The factor group `K/H` is cyclic and it's order is + `K.order()//G.order()`. The series is then extended between + `K` and `H` by groups generated by powers of `g` and `H`. + The series formed is then prepended to the already existing + series. + + Examples + ======== + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics.named_groups import CyclicGroup + >>> S = SymmetricGroup(12) + >>> G = S.sylow_subgroup(2) + >>> C = G.composition_series() + >>> [H.order() for H in C] + [1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] + >>> G = S.sylow_subgroup(3) + >>> C = G.composition_series() + >>> [H.order() for H in C] + [243, 81, 27, 9, 3, 1] + >>> G = CyclicGroup(12) + >>> C = G.composition_series() + >>> [H.order() for H in C] + [12, 6, 3, 1] + + """ + der = self.derived_series() + if not all(g.is_identity for g in der[-1].generators): + raise NotImplementedError('Group should be solvable') + series = [] + + for i in range(len(der)-1): + H = der[i+1] + up_seg = [] + for g in der[i].generators: + K = PermutationGroup([g] + H.generators) + order = K.order() // H.order() + down_seg = [] + for p, e in factorint(order).items(): + for _ in range(e): + down_seg.append(PermutationGroup([g] + H.generators)) + g = g**p + up_seg = down_seg + up_seg + H = K + up_seg[0] = der[i] + series.extend(up_seg) + series.append(der[-1]) + return series + + def coset_transversal(self, H): + """Return a transversal of the right cosets of self by its subgroup H + using the second method described in [1], Subsection 4.6.7 + + """ + + if not H.is_subgroup(self): + raise ValueError("The argument must be a subgroup") + + if H.order() == 1: + return self.elements + + self._schreier_sims(base=H.base) # make G.base an extension of H.base + + base = self.base + base_ordering = _base_ordering(base, self.degree) + identity = Permutation(self.degree - 1) + + transversals = self.basic_transversals[:] + # transversals is a list of dictionaries. Get rid of the keys + # so that it is a list of lists and sort each list in + # the increasing order of base[l]^x + for l, t in enumerate(transversals): + transversals[l] = sorted(t.values(), + key = lambda x: base_ordering[base[l]^x]) + + orbits = H.basic_orbits + h_stabs = H.basic_stabilizers + g_stabs = self.basic_stabilizers + + indices = [x.order()//y.order() for x, y in zip(g_stabs, h_stabs)] + + # T^(l) should be a right transversal of H^(l) in G^(l) for + # 1<=l<=len(base). While H^(l) is the trivial group, T^(l) + # contains all the elements of G^(l) so we might just as well + # start with l = len(h_stabs)-1 + if len(g_stabs) > len(h_stabs): + T = g_stabs[len(h_stabs)].elements + else: + T = [identity] + l = len(h_stabs)-1 + t_len = len(T) + while l > -1: + T_next = [] + for u in transversals[l]: + if u == identity: + continue + b = base_ordering[base[l]^u] + for t in T: + p = t*u + if all(base_ordering[h^p] >= b for h in orbits[l]): + T_next.append(p) + if t_len + len(T_next) == indices[l]: + break + if t_len + len(T_next) == indices[l]: + break + T += T_next + t_len += len(T_next) + l -= 1 + T.remove(identity) + T = [identity] + T + return T + + def _coset_representative(self, g, H): + """Return the representative of Hg from the transversal that + would be computed by ``self.coset_transversal(H)``. + + """ + if H.order() == 1: + return g + # The base of self must be an extension of H.base. + if not(self.base[:len(H.base)] == H.base): + self._schreier_sims(base=H.base) + orbits = H.basic_orbits[:] + h_transversals = [list(_.values()) for _ in H.basic_transversals] + transversals = [list(_.values()) for _ in self.basic_transversals] + base = self.base + base_ordering = _base_ordering(base, self.degree) + def step(l, x): + gamma = min(orbits[l], key = lambda y: base_ordering[y^x]) + i = [base[l]^h for h in h_transversals[l]].index(gamma) + x = h_transversals[l][i]*x + if l < len(orbits)-1: + for u in transversals[l]: + if base[l]^u == base[l]^x: + break + x = step(l+1, x*u**-1)*u + return x + return step(0, g) + + def coset_table(self, H): + """Return the standardised (right) coset table of self in H as + a list of lists. + """ + # Maybe this should be made to return an instance of CosetTable + # from fp_groups.py but the class would need to be changed first + # to be compatible with PermutationGroups + + if not H.is_subgroup(self): + raise ValueError("The argument must be a subgroup") + T = self.coset_transversal(H) + n = len(T) + + A = list(chain.from_iterable((gen, gen**-1) + for gen in self.generators)) + + table = [] + for i in range(n): + row = [self._coset_representative(T[i]*x, H) for x in A] + row = [T.index(r) for r in row] + table.append(row) + + # standardize (this is the same as the algorithm used in coset_table) + # If CosetTable is made compatible with PermutationGroups, this + # should be replaced by table.standardize() + A = range(len(A)) + gamma = 1 + for alpha, a in product(range(n), A): + beta = table[alpha][a] + if beta >= gamma: + if beta > gamma: + for x in A: + z = table[gamma][x] + table[gamma][x] = table[beta][x] + table[beta][x] = z + for i in range(n): + if table[i][x] == beta: + table[i][x] = gamma + elif table[i][x] == gamma: + table[i][x] = beta + gamma += 1 + if gamma >= n-1: + return table + + def center(self): + r""" + Return the center of a permutation group. + + Explanation + =========== + + The center for a group `G` is defined as + `Z(G) = \{z\in G | \forall g\in G, zg = gz \}`, + the set of elements of `G` that commute with all elements of `G`. + It is equal to the centralizer of `G` inside `G`, and is naturally a + subgroup of `G` ([9]). + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> D = DihedralGroup(4) + >>> G = D.center() + >>> G.order() + 2 + + See Also + ======== + + centralizer + + Notes + ===== + + This is a naive implementation that is a straightforward application + of ``.centralizer()`` + + """ + if not self._center: + self._center = self.centralizer(self) + return self._center + + def centralizer(self, other): + r""" + Return the centralizer of a group/set/element. + + Explanation + =========== + + The centralizer of a set of permutations ``S`` inside + a group ``G`` is the set of elements of ``G`` that commute with all + elements of ``S``:: + + `C_G(S) = \{ g \in G | gs = sg \forall s \in S\}` ([10]) + + Usually, ``S`` is a subset of ``G``, but if ``G`` is a proper subgroup of + the full symmetric group, we allow for ``S`` to have elements outside + ``G``. + + It is naturally a subgroup of ``G``; the centralizer of a permutation + group is equal to the centralizer of any set of generators for that + group, since any element commuting with the generators commutes with + any product of the generators. + + Parameters + ========== + + other + a permutation group/list of permutations/single permutation + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... CyclicGroup) + >>> S = SymmetricGroup(6) + >>> C = CyclicGroup(6) + >>> H = S.centralizer(C) + >>> H.is_subgroup(C) + True + + See Also + ======== + + subgroup_search + + Notes + ===== + + The implementation is an application of ``.subgroup_search()`` with + tests using a specific base for the group ``G``. + + """ + if hasattr(other, 'generators'): + if other.is_trivial or self.is_trivial: + return self + degree = self.degree + identity = _af_new(list(range(degree))) + orbits = other.orbits() + num_orbits = len(orbits) + orbits.sort(key=lambda x: -len(x)) + long_base = [] + orbit_reps = [None]*num_orbits + orbit_reps_indices = [None]*num_orbits + orbit_descr = [None]*degree + for i in range(num_orbits): + orbit = list(orbits[i]) + orbit_reps[i] = orbit[0] + orbit_reps_indices[i] = len(long_base) + for point in orbit: + orbit_descr[point] = i + long_base = long_base + orbit + base, strong_gens = self.schreier_sims_incremental(base=long_base) + strong_gens_distr = _distribute_gens_by_base(base, strong_gens) + i = 0 + for i in range(len(base)): + if strong_gens_distr[i] == [identity]: + break + base = base[:i] + base_len = i + for j in range(num_orbits): + if base[base_len - 1] in orbits[j]: + break + rel_orbits = orbits[: j + 1] + num_rel_orbits = len(rel_orbits) + transversals = [None]*num_rel_orbits + for j in range(num_rel_orbits): + rep = orbit_reps[j] + transversals[j] = dict( + other.orbit_transversal(rep, pairs=True)) + trivial_test = lambda x: True + tests = [None]*base_len + for l in range(base_len): + if base[l] in orbit_reps: + tests[l] = trivial_test + else: + def test(computed_words, l=l): + g = computed_words[l] + rep_orb_index = orbit_descr[base[l]] + rep = orbit_reps[rep_orb_index] + im = g._array_form[base[l]] + im_rep = g._array_form[rep] + tr_el = transversals[rep_orb_index][base[l]] + # using the definition of transversal, + # base[l]^g = rep^(tr_el*g); + # if g belongs to the centralizer, then + # base[l]^g = (rep^g)^tr_el + return im == tr_el._array_form[im_rep] + tests[l] = test + + def prop(g): + return [rmul(g, gen) for gen in other.generators] == \ + [rmul(gen, g) for gen in other.generators] + return self.subgroup_search(prop, base=base, + strong_gens=strong_gens, tests=tests) + elif hasattr(other, '__getitem__'): + gens = list(other) + return self.centralizer(PermutationGroup(gens)) + elif hasattr(other, 'array_form'): + return self.centralizer(PermutationGroup([other])) + + def commutator(self, G, H): + """ + Return the commutator of two subgroups. + + Explanation + =========== + + For a permutation group ``K`` and subgroups ``G``, ``H``, the + commutator of ``G`` and ``H`` is defined as the group generated + by all the commutators `[g, h] = hgh^{-1}g^{-1}` for ``g`` in ``G`` and + ``h`` in ``H``. It is naturally a subgroup of ``K`` ([1], p.27). + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... AlternatingGroup) + >>> S = SymmetricGroup(5) + >>> A = AlternatingGroup(5) + >>> G = S.commutator(S, A) + >>> G.is_subgroup(A) + True + + See Also + ======== + + derived_subgroup + + Notes + ===== + + The commutator of two subgroups `H, G` is equal to the normal closure + of the commutators of all the generators, i.e. `hgh^{-1}g^{-1}` for `h` + a generator of `H` and `g` a generator of `G` ([1], p.28) + + """ + ggens = G.generators + hgens = H.generators + commutators = [] + for ggen in ggens: + for hgen in hgens: + commutator = rmul(hgen, ggen, ~hgen, ~ggen) + if commutator not in commutators: + commutators.append(commutator) + res = self.normal_closure(commutators) + return res + + def coset_factor(self, g, factor_index=False): + """Return ``G``'s (self's) coset factorization of ``g`` + + Explanation + =========== + + If ``g`` is an element of ``G`` then it can be written as the product + of permutations drawn from the Schreier-Sims coset decomposition, + + The permutations returned in ``f`` are those for which + the product gives ``g``: ``g = f[n]*...f[1]*f[0]`` where ``n = len(B)`` + and ``B = G.base``. f[i] is one of the permutations in + ``self._basic_orbits[i]``. + + If factor_index==True, + returns a tuple ``[b[0],..,b[n]]``, where ``b[i]`` + belongs to ``self._basic_orbits[i]`` + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation(0, 1, 3, 7, 6, 4)(2, 5) + >>> b = Permutation(0, 1, 3, 2)(4, 5, 7, 6) + >>> G = PermutationGroup([a, b]) + + Define g: + + >>> g = Permutation(7)(1, 2, 4)(3, 6, 5) + + Confirm that it is an element of G: + + >>> G.contains(g) + True + + Thus, it can be written as a product of factors (up to + 3) drawn from u. See below that a factor from u1 and u2 + and the Identity permutation have been used: + + >>> f = G.coset_factor(g) + >>> f[2]*f[1]*f[0] == g + True + >>> f1 = G.coset_factor(g, True); f1 + [0, 4, 4] + >>> tr = G.basic_transversals + >>> f[0] == tr[0][f1[0]] + True + + If g is not an element of G then [] is returned: + + >>> c = Permutation(5, 6, 7) + >>> G.coset_factor(c) + [] + + See Also + ======== + + sympy.combinatorics.util._strip + + """ + if isinstance(g, (Cycle, Permutation)): + g = g.list() + if len(g) != self._degree: + # this could either adjust the size or return [] immediately + # but we don't choose between the two and just signal a possible + # error + raise ValueError('g should be the same size as permutations of G') + I = list(range(self._degree)) + basic_orbits = self.basic_orbits + transversals = self._transversals + factors = [] + base = self.base + h = g + for i in range(len(base)): + beta = h[base[i]] + if beta == base[i]: + factors.append(beta) + continue + if beta not in basic_orbits[i]: + return [] + u = transversals[i][beta]._array_form + h = _af_rmul(_af_invert(u), h) + factors.append(beta) + if h != I: + return [] + if factor_index: + return factors + tr = self.basic_transversals + factors = [tr[i][factors[i]] for i in range(len(base))] + return factors + + def generator_product(self, g, original=False): + r''' + Return a list of strong generators `[s1, \dots, sn]` + s.t `g = sn \times \dots \times s1`. If ``original=True``, make the + list contain only the original group generators + + ''' + product = [] + if g.is_identity: + return [] + if g in self.strong_gens: + if not original or g in self.generators: + return [g] + else: + slp = self._strong_gens_slp[g] + for s in slp: + product.extend(self.generator_product(s, original=True)) + return product + elif g**-1 in self.strong_gens: + g = g**-1 + if not original or g in self.generators: + return [g**-1] + else: + slp = self._strong_gens_slp[g] + for s in slp: + product.extend(self.generator_product(s, original=True)) + l = len(product) + product = [product[l-i-1]**-1 for i in range(l)] + return product + + f = self.coset_factor(g, True) + for i, j in enumerate(f): + slp = self._transversal_slp[i][j] + for s in slp: + if not original: + product.append(self.strong_gens[s]) + else: + s = self.strong_gens[s] + product.extend(self.generator_product(s, original=True)) + return product + + def coset_rank(self, g): + """rank using Schreier-Sims representation. + + Explanation + =========== + + The coset rank of ``g`` is the ordering number in which + it appears in the lexicographic listing according to the + coset decomposition + + The ordering is the same as in G.generate(method='coset'). + If ``g`` does not belong to the group it returns None. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation(0, 1, 3, 7, 6, 4)(2, 5) + >>> b = Permutation(0, 1, 3, 2)(4, 5, 7, 6) + >>> G = PermutationGroup([a, b]) + >>> c = Permutation(7)(2, 4)(3, 5) + >>> G.coset_rank(c) + 16 + >>> G.coset_unrank(16) + (7)(2 4)(3 5) + + See Also + ======== + + coset_factor + + """ + factors = self.coset_factor(g, True) + if not factors: + return None + rank = 0 + b = 1 + transversals = self._transversals + base = self._base + basic_orbits = self._basic_orbits + for i in range(len(base)): + k = factors[i] + j = basic_orbits[i].index(k) + rank += b*j + b = b*len(transversals[i]) + return rank + + def coset_unrank(self, rank, af=False): + """unrank using Schreier-Sims representation + + coset_unrank is the inverse operation of coset_rank + if 0 <= rank < order; otherwise it returns None. + + """ + if rank < 0 or rank >= self.order(): + return None + base = self.base + transversals = self.basic_transversals + basic_orbits = self.basic_orbits + m = len(base) + v = [0]*m + for i in range(m): + rank, c = divmod(rank, len(transversals[i])) + v[i] = basic_orbits[i][c] + a = [transversals[i][v[i]]._array_form for i in range(m)] + h = _af_rmuln(*a) + if af: + return h + else: + return _af_new(h) + + @property + def degree(self): + """Returns the size of the permutations in the group. + + Explanation + =========== + + The number of permutations comprising the group is given by + ``len(group)``; the number of permutations that can be generated + by the group is given by ``group.order()``. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a]) + >>> G.degree + 3 + >>> len(G) + 1 + >>> G.order() + 2 + >>> list(G.generate()) + [(2), (2)(0 1)] + + See Also + ======== + + order + """ + return self._degree + + @property + def identity(self): + ''' + Return the identity element of the permutation group. + + ''' + return _af_new(list(range(self.degree))) + + @property + def elements(self): + """Returns all the elements of the permutation group as a list + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> p = PermutationGroup(Permutation(1, 3), Permutation(1, 2)) + >>> p.elements + [(3), (3)(1 2), (1 3), (2 3), (1 2 3), (1 3 2)] + + """ + if not self._elements: + self._elements = list(self.generate()) + + return self._elements + + def derived_series(self): + r"""Return the derived series for the group. + + Explanation + =========== + + The derived series for a group `G` is defined as + `G = G_0 > G_1 > G_2 > \ldots` where `G_i = [G_{i-1}, G_{i-1}]`, + i.e. `G_i` is the derived subgroup of `G_{i-1}`, for + `i\in\mathbb{N}`. When we have `G_k = G_{k-1}` for some + `k\in\mathbb{N}`, the series terminates. + + Returns + ======= + + A list of permutation groups containing the members of the derived + series in the order `G = G_0, G_1, G_2, \ldots`. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... AlternatingGroup, DihedralGroup) + >>> A = AlternatingGroup(5) + >>> len(A.derived_series()) + 1 + >>> S = SymmetricGroup(4) + >>> len(S.derived_series()) + 4 + >>> S.derived_series()[1].is_subgroup(AlternatingGroup(4)) + True + >>> S.derived_series()[2].is_subgroup(DihedralGroup(2)) + True + + See Also + ======== + + derived_subgroup + + """ + res = [self] + current = self + nxt = self.derived_subgroup() + while not current.is_subgroup(nxt): + res.append(nxt) + current = nxt + nxt = nxt.derived_subgroup() + return res + + def derived_subgroup(self): + r"""Compute the derived subgroup. + + Explanation + =========== + + The derived subgroup, or commutator subgroup is the subgroup generated + by all commutators `[g, h] = hgh^{-1}g^{-1}` for `g, h\in G` ; it is + equal to the normal closure of the set of commutators of the generators + ([1], p.28, [11]). + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([1, 0, 2, 4, 3]) + >>> b = Permutation([0, 1, 3, 2, 4]) + >>> G = PermutationGroup([a, b]) + >>> C = G.derived_subgroup() + >>> list(C.generate(af=True)) + [[0, 1, 2, 3, 4], [0, 1, 3, 4, 2], [0, 1, 4, 2, 3]] + + See Also + ======== + + derived_series + + """ + r = self._r + gens = [p._array_form for p in self.generators] + set_commutators = set() + degree = self._degree + rng = list(range(degree)) + for i in range(r): + for j in range(r): + p1 = gens[i] + p2 = gens[j] + c = list(range(degree)) + for k in rng: + c[p2[p1[k]]] = p1[p2[k]] + ct = tuple(c) + if ct not in set_commutators: + set_commutators.add(ct) + cms = [_af_new(p) for p in set_commutators] + G2 = self.normal_closure(cms) + return G2 + + def generate(self, method="coset", af=False): + """Return iterator to generate the elements of the group. + + Explanation + =========== + + Iteration is done with one of these methods:: + + method='coset' using the Schreier-Sims coset representation + method='dimino' using the Dimino method + + If ``af = True`` it yields the array form of the permutations + + Examples + ======== + + >>> from sympy.combinatorics import PermutationGroup + >>> from sympy.combinatorics.polyhedron import tetrahedron + + The permutation group given in the tetrahedron object is also + true groups: + + >>> G = tetrahedron.pgroup + >>> G.is_group + True + + Also the group generated by the permutations in the tetrahedron + pgroup -- even the first two -- is a proper group: + + >>> H = PermutationGroup(G[0], G[1]) + >>> J = PermutationGroup(list(H.generate())); J + PermutationGroup([ + (0 1)(2 3), + (1 2 3), + (1 3 2), + (0 3 1), + (0 2 3), + (0 3)(1 2), + (0 1 3), + (3)(0 2 1), + (0 3 2), + (3)(0 1 2), + (0 2)(1 3)]) + >>> _.is_group + True + """ + if method == "coset": + return self.generate_schreier_sims(af) + elif method == "dimino": + return self.generate_dimino(af) + else: + raise NotImplementedError('No generation defined for %s' % method) + + def generate_dimino(self, af=False): + """Yield group elements using Dimino's algorithm. + + If ``af == True`` it yields the array form of the permutations. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1, 3]) + >>> b = Permutation([0, 2, 3, 1]) + >>> g = PermutationGroup([a, b]) + >>> list(g.generate_dimino(af=True)) + [[0, 1, 2, 3], [0, 2, 1, 3], [0, 2, 3, 1], + [0, 1, 3, 2], [0, 3, 2, 1], [0, 3, 1, 2]] + + References + ========== + + .. [1] The Implementation of Various Algorithms for Permutation Groups in + the Computer Algebra System: AXIOM, N.J. Doye, M.Sc. Thesis + + """ + idn = list(range(self.degree)) + order = 0 + element_list = [idn] + set_element_list = {tuple(idn)} + if af: + yield idn + else: + yield _af_new(idn) + gens = [p._array_form for p in self.generators] + + for i in range(len(gens)): + # D elements of the subgroup G_i generated by gens[:i] + D = element_list[:] + N = [idn] + while N: + A = N + N = [] + for a in A: + for g in gens[:i + 1]: + ag = _af_rmul(a, g) + if tuple(ag) not in set_element_list: + # produce G_i*g + for d in D: + order += 1 + ap = _af_rmul(d, ag) + if af: + yield ap + else: + p = _af_new(ap) + yield p + element_list.append(ap) + set_element_list.add(tuple(ap)) + N.append(ap) + self._order = len(element_list) + + def generate_schreier_sims(self, af=False): + """Yield group elements using the Schreier-Sims representation + in coset_rank order + + If ``af = True`` it yields the array form of the permutations + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1, 3]) + >>> b = Permutation([0, 2, 3, 1]) + >>> g = PermutationGroup([a, b]) + >>> list(g.generate_schreier_sims(af=True)) + [[0, 1, 2, 3], [0, 2, 1, 3], [0, 3, 2, 1], + [0, 1, 3, 2], [0, 2, 3, 1], [0, 3, 1, 2]] + """ + + n = self._degree + u = self.basic_transversals + basic_orbits = self._basic_orbits + if len(u) == 0: + for x in self.generators: + if af: + yield x._array_form + else: + yield x + return + if len(u) == 1: + for i in basic_orbits[0]: + if af: + yield u[0][i]._array_form + else: + yield u[0][i] + return + + u = list(reversed(u)) + basic_orbits = basic_orbits[::-1] + # stg stack of group elements + stg = [list(range(n))] + posmax = [len(x) for x in u] + n1 = len(posmax) - 1 + pos = [0]*n1 + h = 0 + while 1: + # backtrack when finished iterating over coset + if pos[h] >= posmax[h]: + if h == 0: + return + pos[h] = 0 + h -= 1 + stg.pop() + continue + p = _af_rmul(u[h][basic_orbits[h][pos[h]]]._array_form, stg[-1]) + pos[h] += 1 + stg.append(p) + h += 1 + if h == n1: + if af: + for i in basic_orbits[-1]: + p = _af_rmul(u[-1][i]._array_form, stg[-1]) + yield p + else: + for i in basic_orbits[-1]: + p = _af_rmul(u[-1][i]._array_form, stg[-1]) + p1 = _af_new(p) + yield p1 + stg.pop() + h -= 1 + + @property + def generators(self): + """Returns the generators of the group. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1]) + >>> b = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a, b]) + >>> G.generators + [(1 2), (2)(0 1)] + + """ + return self._generators + + def contains(self, g, strict=True): + """Test if permutation ``g`` belong to self, ``G``. + + Explanation + =========== + + If ``g`` is an element of ``G`` it can be written as a product + of factors drawn from the cosets of ``G``'s stabilizers. To see + if ``g`` is one of the actual generators defining the group use + ``G.has(g)``. + + If ``strict`` is not ``True``, ``g`` will be resized, if necessary, + to match the size of permutations in ``self``. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + + >>> a = Permutation(1, 2) + >>> b = Permutation(2, 3, 1) + >>> G = PermutationGroup(a, b, degree=5) + >>> G.contains(G[0]) # trivial check + True + >>> elem = Permutation([[2, 3]], size=5) + >>> G.contains(elem) + True + >>> G.contains(Permutation(4)(0, 1, 2, 3)) + False + + If strict is False, a permutation will be resized, if + necessary: + + >>> H = PermutationGroup(Permutation(5)) + >>> H.contains(Permutation(3)) + False + >>> H.contains(Permutation(3), strict=False) + True + + To test if a given permutation is present in the group: + + >>> elem in G.generators + False + >>> G.has(elem) + False + + See Also + ======== + + coset_factor, sympy.core.basic.Basic.has, __contains__ + + """ + if not isinstance(g, Permutation): + return False + if g.size != self.degree: + if strict: + return False + g = Permutation(g, size=self.degree) + if g in self.generators: + return True + return bool(self.coset_factor(g.array_form, True)) + + @property + def is_perfect(self): + """Return ``True`` if the group is perfect. + A group is perfect if it equals to its derived subgroup. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation(1,2,3)(4,5) + >>> b = Permutation(1,2,3,4,5) + >>> G = PermutationGroup([a, b]) + >>> G.is_perfect + False + + """ + if self._is_perfect is None: + self._is_perfect = self.equals(self.derived_subgroup()) + return self._is_perfect + + @property + def is_abelian(self): + """Test if the group is Abelian. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1]) + >>> b = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a, b]) + >>> G.is_abelian + False + >>> a = Permutation([0, 2, 1]) + >>> G = PermutationGroup([a]) + >>> G.is_abelian + True + + """ + if self._is_abelian is not None: + return self._is_abelian + + self._is_abelian = True + gens = [p._array_form for p in self.generators] + for x in gens: + for y in gens: + if y <= x: + continue + if not _af_commutes_with(x, y): + self._is_abelian = False + return False + return True + + def abelian_invariants(self): + """ + Returns the abelian invariants for the given group. + Let ``G`` be a nontrivial finite abelian group. Then G is isomorphic to + the direct product of finitely many nontrivial cyclic groups of + prime-power order. + + Explanation + =========== + + The prime-powers that occur as the orders of the factors are uniquely + determined by G. More precisely, the primes that occur in the orders of the + factors in any such decomposition of ``G`` are exactly the primes that divide + ``|G|`` and for any such prime ``p``, if the orders of the factors that are + p-groups in one such decomposition of ``G`` are ``p^{t_1} >= p^{t_2} >= ... p^{t_r}``, + then the orders of the factors that are p-groups in any such decomposition of ``G`` + are ``p^{t_1} >= p^{t_2} >= ... p^{t_r}``. + + The uniquely determined integers ``p^{t_1} >= p^{t_2} >= ... p^{t_r}``, taken + for all primes that divide ``|G|`` are called the invariants of the nontrivial + group ``G`` as suggested in ([14], p. 542). + + Notes + ===== + + We adopt the convention that the invariants of a trivial group are []. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1]) + >>> b = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a, b]) + >>> G.abelian_invariants() + [2] + >>> from sympy.combinatorics import CyclicGroup + >>> G = CyclicGroup(7) + >>> G.abelian_invariants() + [7] + + """ + if self.is_trivial: + return [] + gns = self.generators + inv = [] + G = self + H = G.derived_subgroup() + Hgens = H.generators + for p in primefactors(G.order()): + ranks = [] + while True: + pows = [] + for g in gns: + elm = g**p + if not H.contains(elm): + pows.append(elm) + K = PermutationGroup(Hgens + pows) if pows else H + r = G.order()//K.order() + G = K + gns = pows + if r == 1: + break + ranks.append(multiplicity(p, r)) + + if ranks: + pows = [1]*ranks[0] + for i in ranks: + for j in range(i): + pows[j] = pows[j]*p + inv.extend(pows) + inv.sort() + return inv + + def is_elementary(self, p): + """Return ``True`` if the group is elementary abelian. An elementary + abelian group is a finite abelian group, where every nontrivial + element has order `p`, where `p` is a prime. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1]) + >>> G = PermutationGroup([a]) + >>> G.is_elementary(2) + True + >>> a = Permutation([0, 2, 1, 3]) + >>> b = Permutation([3, 1, 2, 0]) + >>> G = PermutationGroup([a, b]) + >>> G.is_elementary(2) + True + >>> G.is_elementary(3) + False + + """ + return self.is_abelian and all(g.order() == p for g in self.generators) + + def _eval_is_alt_sym_naive(self, only_sym=False, only_alt=False): + """A naive test using the group order.""" + if only_sym and only_alt: + raise ValueError( + "Both {} and {} cannot be set to True" + .format(only_sym, only_alt)) + + n = self.degree + sym_order = _factorial(n) + order = self.order() + + if order == sym_order: + self._is_sym = True + self._is_alt = False + if only_alt: + return False + return True + + elif 2*order == sym_order: + self._is_sym = False + self._is_alt = True + if only_sym: + return False + return True + + return False + + def _eval_is_alt_sym_monte_carlo(self, eps=0.05, perms=None): + """A test using monte-carlo algorithm. + + Parameters + ========== + + eps : float, optional + The criterion for the incorrect ``False`` return. + + perms : list[Permutation], optional + If explicitly given, it tests over the given candidates + for testing. + + If ``None``, it randomly computes ``N_eps`` and chooses + ``N_eps`` sample of the permutation from the group. + + See Also + ======== + + _check_cycles_alt_sym + """ + if perms is None: + n = self.degree + if n < 17: + c_n = 0.34 + else: + c_n = 0.57 + d_n = (c_n*log(2))/log(n) + N_eps = int(-log(eps)/d_n) + + perms = (self.random_pr() for i in range(N_eps)) + return self._eval_is_alt_sym_monte_carlo(perms=perms) + + for perm in perms: + if _check_cycles_alt_sym(perm): + return True + return False + + def is_alt_sym(self, eps=0.05, _random_prec=None): + r"""Monte Carlo test for the symmetric/alternating group for degrees + >= 8. + + Explanation + =========== + + More specifically, it is one-sided Monte Carlo with the + answer True (i.e., G is symmetric/alternating) guaranteed to be + correct, and the answer False being incorrect with probability eps. + + For degree < 8, the order of the group is checked so the test + is deterministic. + + Notes + ===== + + The algorithm itself uses some nontrivial results from group theory and + number theory: + 1) If a transitive group ``G`` of degree ``n`` contains an element + with a cycle of length ``n/2 < p < n-2`` for ``p`` a prime, ``G`` is the + symmetric or alternating group ([1], pp. 81-82) + 2) The proportion of elements in the symmetric/alternating group having + the property described in 1) is approximately `\log(2)/\log(n)` + ([1], p.82; [2], pp. 226-227). + The helper function ``_check_cycles_alt_sym`` is used to + go over the cycles in a permutation and look for ones satisfying 1). + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> D = DihedralGroup(10) + >>> D.is_alt_sym() + False + + See Also + ======== + + _check_cycles_alt_sym + + """ + if _random_prec is not None: + N_eps = _random_prec['N_eps'] + perms= (_random_prec[i] for i in range(N_eps)) + return self._eval_is_alt_sym_monte_carlo(perms=perms) + + if self._is_sym or self._is_alt: + return True + if self._is_sym is False and self._is_alt is False: + return False + + n = self.degree + if n < 8: + return self._eval_is_alt_sym_naive() + elif self.is_transitive(): + return self._eval_is_alt_sym_monte_carlo(eps=eps) + + self._is_sym, self._is_alt = False, False + return False + + @property + def is_nilpotent(self): + """Test if the group is nilpotent. + + Explanation + =========== + + A group `G` is nilpotent if it has a central series of finite length. + Alternatively, `G` is nilpotent if its lower central series terminates + with the trivial group. Every nilpotent group is also solvable + ([1], p.29, [12]). + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... CyclicGroup) + >>> C = CyclicGroup(6) + >>> C.is_nilpotent + True + >>> S = SymmetricGroup(5) + >>> S.is_nilpotent + False + + See Also + ======== + + lower_central_series, is_solvable + + """ + if self._is_nilpotent is None: + lcs = self.lower_central_series() + terminator = lcs[len(lcs) - 1] + gens = terminator.generators + degree = self.degree + identity = _af_new(list(range(degree))) + if all(g == identity for g in gens): + self._is_solvable = True + self._is_nilpotent = True + return True + else: + self._is_nilpotent = False + return False + else: + return self._is_nilpotent + + def is_normal(self, gr, strict=True): + """Test if ``G=self`` is a normal subgroup of ``gr``. + + Explanation + =========== + + G is normal in gr if + for each g2 in G, g1 in gr, ``g = g1*g2*g1**-1`` belongs to G + It is sufficient to check this for each g1 in gr.generators and + g2 in G.generators. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([1, 2, 0]) + >>> b = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a, b]) + >>> G1 = PermutationGroup([a, Permutation([2, 0, 1])]) + >>> G1.is_normal(G) + True + + """ + if not self.is_subgroup(gr, strict=strict): + return False + d_self = self.degree + d_gr = gr.degree + if self.is_trivial and (d_self == d_gr or not strict): + return True + if self._is_abelian: + return True + new_self = self.copy() + if not strict and d_self != d_gr: + if d_self < d_gr: + new_self = PermGroup(new_self.generators + [Permutation(d_gr - 1)]) + else: + gr = PermGroup(gr.generators + [Permutation(d_self - 1)]) + gens2 = [p._array_form for p in new_self.generators] + gens1 = [p._array_form for p in gr.generators] + for g1 in gens1: + for g2 in gens2: + p = _af_rmuln(g1, g2, _af_invert(g1)) + if not new_self.coset_factor(p, True): + return False + return True + + def is_primitive(self, randomized=True): + r"""Test if a group is primitive. + + Explanation + =========== + + A permutation group ``G`` acting on a set ``S`` is called primitive if + ``S`` contains no nontrivial block under the action of ``G`` + (a block is nontrivial if its cardinality is more than ``1``). + + Notes + ===== + + The algorithm is described in [1], p.83, and uses the function + minimal_block to search for blocks of the form `\{0, k\}` for ``k`` + ranging over representatives for the orbits of `G_0`, the stabilizer of + ``0``. This algorithm has complexity `O(n^2)` where ``n`` is the degree + of the group, and will perform badly if `G_0` is small. + + There are two implementations offered: one finds `G_0` + deterministically using the function ``stabilizer``, and the other + (default) produces random elements of `G_0` using ``random_stab``, + hoping that they generate a subgroup of `G_0` with not too many more + orbits than `G_0` (this is suggested in [1], p.83). Behavior is changed + by the ``randomized`` flag. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> D = DihedralGroup(10) + >>> D.is_primitive() + False + + See Also + ======== + + minimal_block, random_stab + + """ + if self._is_primitive is not None: + return self._is_primitive + + if self.is_transitive() is False: + return False + + if randomized: + random_stab_gens = [] + v = self.schreier_vector(0) + for _ in range(len(self)): + random_stab_gens.append(self.random_stab(0, v)) + stab = PermutationGroup(random_stab_gens) + else: + stab = self.stabilizer(0) + orbits = stab.orbits() + for orb in orbits: + x = orb.pop() + if x != 0 and any(e != 0 for e in self.minimal_block([0, x])): + self._is_primitive = False + return False + self._is_primitive = True + return True + + def minimal_blocks(self, randomized=True): + ''' + For a transitive group, return the list of all minimal + block systems. If a group is intransitive, return `False`. + + Examples + ======== + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> DihedralGroup(6).minimal_blocks() + [[0, 1, 0, 1, 0, 1], [0, 1, 2, 0, 1, 2]] + >>> G = PermutationGroup(Permutation(1,2,5)) + >>> G.minimal_blocks() + False + + See Also + ======== + + minimal_block, is_transitive, is_primitive + + ''' + def _number_blocks(blocks): + # number the blocks of a block system + # in order and return the number of + # blocks and the tuple with the + # reordering + n = len(blocks) + appeared = {} + m = 0 + b = [None]*n + for i in range(n): + if blocks[i] not in appeared: + appeared[blocks[i]] = m + b[i] = m + m += 1 + else: + b[i] = appeared[blocks[i]] + return tuple(b), m + + if not self.is_transitive(): + return False + blocks = [] + num_blocks = [] + rep_blocks = [] + if randomized: + random_stab_gens = [] + v = self.schreier_vector(0) + for i in range(len(self)): + random_stab_gens.append(self.random_stab(0, v)) + stab = PermutationGroup(random_stab_gens) + else: + stab = self.stabilizer(0) + orbits = stab.orbits() + for orb in orbits: + x = orb.pop() + if x != 0: + block = self.minimal_block([0, x]) + num_block, _ = _number_blocks(block) + # a representative block (containing 0) + rep = {j for j in range(self.degree) if num_block[j] == 0} + # check if the system is minimal with + # respect to the already discovere ones + minimal = True + blocks_remove_mask = [False] * len(blocks) + for i, r in enumerate(rep_blocks): + if len(r) > len(rep) and rep.issubset(r): + # i-th block system is not minimal + blocks_remove_mask[i] = True + elif len(r) < len(rep) and r.issubset(rep): + # the system being checked is not minimal + minimal = False + break + # remove non-minimal representative blocks + blocks = [b for i, b in enumerate(blocks) if not blocks_remove_mask[i]] + num_blocks = [n for i, n in enumerate(num_blocks) if not blocks_remove_mask[i]] + rep_blocks = [r for i, r in enumerate(rep_blocks) if not blocks_remove_mask[i]] + + if minimal and num_block not in num_blocks: + blocks.append(block) + num_blocks.append(num_block) + rep_blocks.append(rep) + return blocks + + @property + def is_solvable(self): + """Test if the group is solvable. + + ``G`` is solvable if its derived series terminates with the trivial + group ([1], p.29). + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> S = SymmetricGroup(3) + >>> S.is_solvable + True + + See Also + ======== + + is_nilpotent, derived_series + + """ + if self._is_solvable is None: + if self.order() % 2 != 0: + return True + ds = self.derived_series() + terminator = ds[len(ds) - 1] + gens = terminator.generators + degree = self.degree + identity = _af_new(list(range(degree))) + if all(g == identity for g in gens): + self._is_solvable = True + return True + else: + self._is_solvable = False + return False + else: + return self._is_solvable + + def is_subgroup(self, G, strict=True): + """Return ``True`` if all elements of ``self`` belong to ``G``. + + If ``strict`` is ``False`` then if ``self``'s degree is smaller + than ``G``'s, the elements will be resized to have the same degree. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> from sympy.combinatorics import SymmetricGroup, CyclicGroup + + Testing is strict by default: the degree of each group must be the + same: + + >>> p = Permutation(0, 1, 2, 3, 4, 5) + >>> G1 = PermutationGroup([Permutation(0, 1, 2), Permutation(0, 1)]) + >>> G2 = PermutationGroup([Permutation(0, 2), Permutation(0, 1, 2)]) + >>> G3 = PermutationGroup([p, p**2]) + >>> assert G1.order() == G2.order() == G3.order() == 6 + >>> G1.is_subgroup(G2) + True + >>> G1.is_subgroup(G3) + False + >>> G3.is_subgroup(PermutationGroup(G3[1])) + False + >>> G3.is_subgroup(PermutationGroup(G3[0])) + True + + To ignore the size, set ``strict`` to ``False``: + + >>> S3 = SymmetricGroup(3) + >>> S5 = SymmetricGroup(5) + >>> S3.is_subgroup(S5, strict=False) + True + >>> C7 = CyclicGroup(7) + >>> G = S5*C7 + >>> S5.is_subgroup(G, False) + True + >>> C7.is_subgroup(G, 0) + False + + """ + if isinstance(G, SymmetricPermutationGroup): + if self.degree != G.degree: + return False + return True + if not isinstance(G, PermutationGroup): + return False + if self == G or self.generators[0]==Permutation(): + return True + if G.order() % self.order() != 0: + return False + if self.degree == G.degree or \ + (self.degree < G.degree and not strict): + gens = self.generators + else: + return False + return all(G.contains(g, strict=strict) for g in gens) + + @property + def is_polycyclic(self): + """Return ``True`` if a group is polycyclic. A group is polycyclic if + it has a subnormal series with cyclic factors. For finite groups, + this is the same as if the group is solvable. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1, 3]) + >>> b = Permutation([2, 0, 1, 3]) + >>> G = PermutationGroup([a, b]) + >>> G.is_polycyclic + True + + """ + return self.is_solvable + + def is_transitive(self, strict=True): + """Test if the group is transitive. + + Explanation + =========== + + A group is transitive if it has a single orbit. + + If ``strict`` is ``False`` the group is transitive if it has + a single orbit of length different from 1. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1, 3]) + >>> b = Permutation([2, 0, 1, 3]) + >>> G1 = PermutationGroup([a, b]) + >>> G1.is_transitive() + False + >>> G1.is_transitive(strict=False) + True + >>> c = Permutation([2, 3, 0, 1]) + >>> G2 = PermutationGroup([a, c]) + >>> G2.is_transitive() + True + >>> d = Permutation([1, 0, 2, 3]) + >>> e = Permutation([0, 1, 3, 2]) + >>> G3 = PermutationGroup([d, e]) + >>> G3.is_transitive() or G3.is_transitive(strict=False) + False + + """ + if self._is_transitive: # strict or not, if True then True + return self._is_transitive + if strict: + if self._is_transitive is not None: # we only store strict=True + return self._is_transitive + + ans = len(self.orbit(0)) == self.degree + self._is_transitive = ans + return ans + + got_orb = False + for x in self.orbits(): + if len(x) > 1: + if got_orb: + return False + got_orb = True + return got_orb + + @property + def is_trivial(self): + """Test if the group is the trivial group. + + This is true if the group contains only the identity permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> G = PermutationGroup([Permutation([0, 1, 2])]) + >>> G.is_trivial + True + + """ + if self._is_trivial is None: + self._is_trivial = len(self) == 1 and self[0].is_Identity + return self._is_trivial + + def lower_central_series(self): + r"""Return the lower central series for the group. + + The lower central series for a group `G` is the series + `G = G_0 > G_1 > G_2 > \ldots` where + `G_k = [G, G_{k-1}]`, i.e. every term after the first is equal to the + commutator of `G` and the previous term in `G1` ([1], p.29). + + Returns + ======= + + A list of permutation groups in the order `G = G_0, G_1, G_2, \ldots` + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (AlternatingGroup, + ... DihedralGroup) + >>> A = AlternatingGroup(4) + >>> len(A.lower_central_series()) + 2 + >>> A.lower_central_series()[1].is_subgroup(DihedralGroup(2)) + True + + See Also + ======== + + commutator, derived_series + + """ + res = [self] + current = self + nxt = self.commutator(self, current) + while not current.is_subgroup(nxt): + res.append(nxt) + current = nxt + nxt = self.commutator(self, current) + return res + + @property + def max_div(self): + """Maximum proper divisor of the degree of a permutation group. + + Explanation + =========== + + Obviously, this is the degree divided by its minimal proper divisor + (larger than ``1``, if one exists). As it is guaranteed to be prime, + the ``sieve`` from ``sympy.ntheory`` is used. + This function is also used as an optimization tool for the functions + ``minimal_block`` and ``_union_find_merge``. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> G = PermutationGroup([Permutation([0, 2, 1, 3])]) + >>> G.max_div + 2 + + See Also + ======== + + minimal_block, _union_find_merge + + """ + if self._max_div is not None: + return self._max_div + n = self.degree + if n == 1: + return 1 + for x in sieve: + if n % x == 0: + d = n//x + self._max_div = d + return d + + def minimal_block(self, points): + r"""For a transitive group, finds the block system generated by + ``points``. + + Explanation + =========== + + If a group ``G`` acts on a set ``S``, a nonempty subset ``B`` of ``S`` + is called a block under the action of ``G`` if for all ``g`` in ``G`` + we have ``gB = B`` (``g`` fixes ``B``) or ``gB`` and ``B`` have no + common points (``g`` moves ``B`` entirely). ([1], p.23; [6]). + + The distinct translates ``gB`` of a block ``B`` for ``g`` in ``G`` + partition the set ``S`` and this set of translates is known as a block + system. Moreover, we obviously have that all blocks in the partition + have the same size, hence the block size divides ``|S|`` ([1], p.23). + A ``G``-congruence is an equivalence relation ``~`` on the set ``S`` + such that ``a ~ b`` implies ``g(a) ~ g(b)`` for all ``g`` in ``G``. + For a transitive group, the equivalence classes of a ``G``-congruence + and the blocks of a block system are the same thing ([1], p.23). + + The algorithm below checks the group for transitivity, and then finds + the ``G``-congruence generated by the pairs ``(p_0, p_1), (p_0, p_2), + ..., (p_0,p_{k-1})`` which is the same as finding the maximal block + system (i.e., the one with minimum block size) such that + ``p_0, ..., p_{k-1}`` are in the same block ([1], p.83). + + It is an implementation of Atkinson's algorithm, as suggested in [1], + and manipulates an equivalence relation on the set ``S`` using a + union-find data structure. The running time is just above + `O(|points||S|)`. ([1], pp. 83-87; [7]). + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> D = DihedralGroup(10) + >>> D.minimal_block([0, 5]) + [0, 1, 2, 3, 4, 0, 1, 2, 3, 4] + >>> D.minimal_block([0, 1]) + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] + + See Also + ======== + + _union_find_rep, _union_find_merge, is_transitive, is_primitive + + """ + if not self.is_transitive(): + return False + n = self.degree + gens = self.generators + # initialize the list of equivalence class representatives + parents = list(range(n)) + ranks = [1]*n + not_rep = [] + k = len(points) + # the block size must divide the degree of the group + if k > self.max_div: + return [0]*n + for i in range(k - 1): + parents[points[i + 1]] = points[0] + not_rep.append(points[i + 1]) + ranks[points[0]] = k + i = 0 + len_not_rep = k - 1 + while i < len_not_rep: + gamma = not_rep[i] + i += 1 + for gen in gens: + # find has side effects: performs path compression on the list + # of representatives + delta = self._union_find_rep(gamma, parents) + # union has side effects: performs union by rank on the list + # of representatives + temp = self._union_find_merge(gen(gamma), gen(delta), ranks, + parents, not_rep) + if temp == -1: + return [0]*n + len_not_rep += temp + for i in range(n): + # force path compression to get the final state of the equivalence + # relation + self._union_find_rep(i, parents) + + # rewrite result so that block representatives are minimal + new_reps = {} + return [new_reps.setdefault(r, i) for i, r in enumerate(parents)] + + def conjugacy_class(self, x): + r"""Return the conjugacy class of an element in the group. + + Explanation + =========== + + The conjugacy class of an element ``g`` in a group ``G`` is the set of + elements ``x`` in ``G`` that are conjugate with ``g``, i.e. for which + + ``g = xax^{-1}`` + + for some ``a`` in ``G``. + + Note that conjugacy is an equivalence relation, and therefore that + conjugacy classes are partitions of ``G``. For a list of all the + conjugacy classes of the group, use the conjugacy_classes() method. + + In a permutation group, each conjugacy class corresponds to a particular + `cycle structure': for example, in ``S_3``, the conjugacy classes are: + + * the identity class, ``{()}`` + * all transpositions, ``{(1 2), (1 3), (2 3)}`` + * all 3-cycles, ``{(1 2 3), (1 3 2)}`` + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, SymmetricGroup + >>> S3 = SymmetricGroup(3) + >>> S3.conjugacy_class(Permutation(0, 1, 2)) + {(0 1 2), (0 2 1)} + + Notes + ===== + + This procedure computes the conjugacy class directly by finding the + orbit of the element under conjugation in G. This algorithm is only + feasible for permutation groups of relatively small order, but is like + the orbit() function itself in that respect. + """ + # Ref: "Computing the conjugacy classes of finite groups"; Butler, G. + # Groups '93 Galway/St Andrews; edited by Campbell, C. M. + new_class = {x} + last_iteration = new_class + + while len(last_iteration) > 0: + this_iteration = set() + + for y in last_iteration: + for s in self.generators: + conjugated = s * y * (~s) + if conjugated not in new_class: + this_iteration.add(conjugated) + + new_class.update(last_iteration) + last_iteration = this_iteration + + return new_class + + + def conjugacy_classes(self): + r"""Return the conjugacy classes of the group. + + Explanation + =========== + + As described in the documentation for the .conjugacy_class() function, + conjugacy is an equivalence relation on a group G which partitions the + set of elements. This method returns a list of all these conjugacy + classes of G. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricGroup + >>> SymmetricGroup(3).conjugacy_classes() + [{(2)}, {(0 1 2), (0 2 1)}, {(0 2), (1 2), (2)(0 1)}] + + """ + identity = _af_new(list(range(self.degree))) + known_elements = {identity} + classes = [known_elements.copy()] + + for x in self.generate(): + if x not in known_elements: + new_class = self.conjugacy_class(x) + classes.append(new_class) + known_elements.update(new_class) + + return classes + + def normal_closure(self, other, k=10): + r"""Return the normal closure of a subgroup/set of permutations. + + Explanation + =========== + + If ``S`` is a subset of a group ``G``, the normal closure of ``A`` in ``G`` + is defined as the intersection of all normal subgroups of ``G`` that + contain ``A`` ([1], p.14). Alternatively, it is the group generated by + the conjugates ``x^{-1}yx`` for ``x`` a generator of ``G`` and ``y`` a + generator of the subgroup ``\left\langle S\right\rangle`` generated by + ``S`` (for some chosen generating set for ``\left\langle S\right\rangle``) + ([1], p.73). + + Parameters + ========== + + other + a subgroup/list of permutations/single permutation + k + an implementation-specific parameter that determines the number + of conjugates that are adjoined to ``other`` at once + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... CyclicGroup, AlternatingGroup) + >>> S = SymmetricGroup(5) + >>> C = CyclicGroup(5) + >>> G = S.normal_closure(C) + >>> G.order() + 60 + >>> G.is_subgroup(AlternatingGroup(5)) + True + + See Also + ======== + + commutator, derived_subgroup, random_pr + + Notes + ===== + + The algorithm is described in [1], pp. 73-74; it makes use of the + generation of random elements for permutation groups by the product + replacement algorithm. + + """ + if hasattr(other, 'generators'): + degree = self.degree + identity = _af_new(list(range(degree))) + + if all(g == identity for g in other.generators): + return other + Z = PermutationGroup(other.generators[:]) + base, strong_gens = Z.schreier_sims_incremental() + strong_gens_distr = _distribute_gens_by_base(base, strong_gens) + basic_orbits, basic_transversals = \ + _orbits_transversals_from_bsgs(base, strong_gens_distr) + + self._random_pr_init(r=10, n=20) + + _loop = True + while _loop: + Z._random_pr_init(r=10, n=10) + for _ in range(k): + g = self.random_pr() + h = Z.random_pr() + conj = h^g + res = _strip(conj, base, basic_orbits, basic_transversals) + if res[0] != identity or res[1] != len(base) + 1: + gens = Z.generators + gens.append(conj) + Z = PermutationGroup(gens) + strong_gens.append(conj) + temp_base, temp_strong_gens = \ + Z.schreier_sims_incremental(base, strong_gens) + base, strong_gens = temp_base, temp_strong_gens + strong_gens_distr = \ + _distribute_gens_by_base(base, strong_gens) + basic_orbits, basic_transversals = \ + _orbits_transversals_from_bsgs(base, + strong_gens_distr) + _loop = False + for g in self.generators: + for h in Z.generators: + conj = h^g + res = _strip(conj, base, basic_orbits, + basic_transversals) + if res[0] != identity or res[1] != len(base) + 1: + _loop = True + break + if _loop: + break + return Z + elif hasattr(other, '__getitem__'): + return self.normal_closure(PermutationGroup(other)) + elif hasattr(other, 'array_form'): + return self.normal_closure(PermutationGroup([other])) + + def orbit(self, alpha, action='tuples'): + r"""Compute the orbit of alpha `\{g(\alpha) | g \in G\}` as a set. + + Explanation + =========== + + The time complexity of the algorithm used here is `O(|Orb|*r)` where + `|Orb|` is the size of the orbit and ``r`` is the number of generators of + the group. For a more detailed analysis, see [1], p.78, [2], pp. 19-21. + Here alpha can be a single point, or a list of points. + + If alpha is a single point, the ordinary orbit is computed. + if alpha is a list of points, there are three available options: + + 'union' - computes the union of the orbits of the points in the list + 'tuples' - computes the orbit of the list interpreted as an ordered + tuple under the group action ( i.e., g((1,2,3)) = (g(1), g(2), g(3)) ) + 'sets' - computes the orbit of the list interpreted as a sets + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([1, 2, 0, 4, 5, 6, 3]) + >>> G = PermutationGroup([a]) + >>> G.orbit(0) + {0, 1, 2} + >>> G.orbit([0, 4], 'union') + {0, 1, 2, 3, 4, 5, 6} + + See Also + ======== + + orbit_transversal + + """ + return _orbit(self.degree, self.generators, alpha, action) + + def orbit_rep(self, alpha, beta, schreier_vector=None): + """Return a group element which sends ``alpha`` to ``beta``. + + Explanation + =========== + + If ``beta`` is not in the orbit of ``alpha``, the function returns + ``False``. This implementation makes use of the schreier vector. + For a proof of correctness, see [1], p.80 + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AlternatingGroup + >>> G = AlternatingGroup(5) + >>> G.orbit_rep(0, 4) + (0 4 1 2 3) + + See Also + ======== + + schreier_vector + + """ + if schreier_vector is None: + schreier_vector = self.schreier_vector(alpha) + if schreier_vector[beta] is None: + return False + k = schreier_vector[beta] + gens = [x._array_form for x in self.generators] + a = [] + while k != -1: + a.append(gens[k]) + beta = gens[k].index(beta) # beta = (~gens[k])(beta) + k = schreier_vector[beta] + if a: + return _af_new(_af_rmuln(*a)) + else: + return _af_new(list(range(self._degree))) + + def orbit_transversal(self, alpha, pairs=False): + r"""Computes a transversal for the orbit of ``alpha`` as a set. + + Explanation + =========== + + For a permutation group `G`, a transversal for the orbit + `Orb = \{g(\alpha) | g \in G\}` is a set + `\{g_\beta | g_\beta(\alpha) = \beta\}` for `\beta \in Orb`. + Note that there may be more than one possible transversal. + If ``pairs`` is set to ``True``, it returns the list of pairs + `(\beta, g_\beta)`. For a proof of correctness, see [1], p.79 + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> G = DihedralGroup(6) + >>> G.orbit_transversal(0) + [(5), (0 1 2 3 4 5), (0 5)(1 4)(2 3), (0 2 4)(1 3 5), (5)(0 4)(1 3), (0 3)(1 4)(2 5)] + + See Also + ======== + + orbit + + """ + return _orbit_transversal(self._degree, self.generators, alpha, pairs) + + def orbits(self, rep=False): + """Return the orbits of ``self``, ordered according to lowest element + in each orbit. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation(1, 5)(2, 3)(4, 0, 6) + >>> b = Permutation(1, 5)(3, 4)(2, 6, 0) + >>> G = PermutationGroup([a, b]) + >>> G.orbits() + [{0, 2, 3, 4, 6}, {1, 5}] + """ + return _orbits(self._degree, self._generators) + + def order(self): + """Return the order of the group: the number of permutations that + can be generated from elements of the group. + + The number of permutations comprising the group is given by + ``len(group)``; the length of each permutation in the group is + given by ``group.size``. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + + >>> a = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a]) + >>> G.degree + 3 + >>> len(G) + 1 + >>> G.order() + 2 + >>> list(G.generate()) + [(2), (2)(0 1)] + + >>> a = Permutation([0, 2, 1]) + >>> b = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a, b]) + >>> G.order() + 6 + + See Also + ======== + + degree + + """ + if self._order is not None: + return self._order + if self._is_sym: + n = self._degree + self._order = factorial(n) + return self._order + if self._is_alt: + n = self._degree + self._order = factorial(n)/2 + return self._order + + m = prod([len(x) for x in self.basic_transversals]) + self._order = m + return m + + def index(self, H): + """ + Returns the index of a permutation group. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation(1,2,3) + >>> b =Permutation(3) + >>> G = PermutationGroup([a]) + >>> H = PermutationGroup([b]) + >>> G.index(H) + 3 + + """ + if H.is_subgroup(self): + return self.order()//H.order() + + @property + def is_symmetric(self): + """Return ``True`` if the group is symmetric. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricGroup + >>> g = SymmetricGroup(5) + >>> g.is_symmetric + True + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> g = PermutationGroup( + ... Permutation(0, 1, 2, 3, 4), + ... Permutation(2, 3)) + >>> g.is_symmetric + True + + Notes + ===== + + This uses a naive test involving the computation of the full + group order. + If you need more quicker taxonomy for large groups, you can use + :meth:`PermutationGroup.is_alt_sym`. + However, :meth:`PermutationGroup.is_alt_sym` may not be accurate + and is not able to distinguish between an alternating group and + a symmetric group. + + See Also + ======== + + is_alt_sym + """ + _is_sym = self._is_sym + if _is_sym is not None: + return _is_sym + + n = self.degree + if n >= 8: + if self.is_transitive(): + _is_alt_sym = self._eval_is_alt_sym_monte_carlo() + if _is_alt_sym: + if any(g.is_odd for g in self.generators): + self._is_sym, self._is_alt = True, False + return True + + self._is_sym, self._is_alt = False, True + return False + + return self._eval_is_alt_sym_naive(only_sym=True) + + self._is_sym, self._is_alt = False, False + return False + + return self._eval_is_alt_sym_naive(only_sym=True) + + + @property + def is_alternating(self): + """Return ``True`` if the group is alternating. + + Examples + ======== + + >>> from sympy.combinatorics import AlternatingGroup + >>> g = AlternatingGroup(5) + >>> g.is_alternating + True + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> g = PermutationGroup( + ... Permutation(0, 1, 2, 3, 4), + ... Permutation(2, 3, 4)) + >>> g.is_alternating + True + + Notes + ===== + + This uses a naive test involving the computation of the full + group order. + If you need more quicker taxonomy for large groups, you can use + :meth:`PermutationGroup.is_alt_sym`. + However, :meth:`PermutationGroup.is_alt_sym` may not be accurate + and is not able to distinguish between an alternating group and + a symmetric group. + + See Also + ======== + + is_alt_sym + """ + _is_alt = self._is_alt + if _is_alt is not None: + return _is_alt + + n = self.degree + if n >= 8: + if self.is_transitive(): + _is_alt_sym = self._eval_is_alt_sym_monte_carlo() + if _is_alt_sym: + if all(g.is_even for g in self.generators): + self._is_sym, self._is_alt = False, True + return True + + self._is_sym, self._is_alt = True, False + return False + + return self._eval_is_alt_sym_naive(only_alt=True) + + self._is_sym, self._is_alt = False, False + return False + + return self._eval_is_alt_sym_naive(only_alt=True) + + @classmethod + def _distinct_primes_lemma(cls, primes): + """Subroutine to test if there is only one cyclic group for the + order.""" + primes = sorted(primes) + l = len(primes) + for i in range(l): + for j in range(i+1, l): + if primes[j] % primes[i] == 1: + return None + return True + + @property + def is_cyclic(self): + r""" + Return ``True`` if the group is Cyclic. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AbelianGroup + >>> G = AbelianGroup(3, 4) + >>> G.is_cyclic + True + >>> G = AbelianGroup(4, 4) + >>> G.is_cyclic + False + + Notes + ===== + + If the order of a group $n$ can be factored into the distinct + primes $p_1, p_2, \dots , p_s$ and if + + .. math:: + \forall i, j \in \{1, 2, \dots, s \}: + p_i \not \equiv 1 \pmod {p_j} + + holds true, there is only one group of the order $n$ which + is a cyclic group [1]_. This is a generalization of the lemma + that the group of order $15, 35, \dots$ are cyclic. + + And also, these additional lemmas can be used to test if a + group is cyclic if the order of the group is already found. + + - If the group is abelian and the order of the group is + square-free, the group is cyclic. + - If the order of the group is less than $6$ and is not $4$, the + group is cyclic. + - If the order of the group is prime, the group is cyclic. + + References + ========== + + .. [1] 1978: John S. Rose: A Course on Group Theory, + Introduction to Finite Group Theory: 1.4 + """ + if self._is_cyclic is not None: + return self._is_cyclic + + if len(self.generators) == 1: + self._is_cyclic = True + self._is_abelian = True + return True + + if self._is_abelian is False: + self._is_cyclic = False + return False + + order = self.order() + + if order < 6: + self._is_abelian = True + if order != 4: + self._is_cyclic = True + return True + + factors = factorint(order) + if all(v == 1 for v in factors.values()): + if self._is_abelian: + self._is_cyclic = True + return True + + primes = list(factors.keys()) + if PermutationGroup._distinct_primes_lemma(primes) is True: + self._is_cyclic = True + self._is_abelian = True + return True + + if not self.is_abelian: + self._is_cyclic = False + return False + + self._is_cyclic = all( + any(g**(order//p) != self.identity for g in self.generators) + for p, e in factors.items() if e > 1 + ) + return self._is_cyclic + + @property + def is_dihedral(self): + r""" + Return ``True`` if the group is dihedral. + + Examples + ======== + + >>> from sympy.combinatorics.perm_groups import PermutationGroup + >>> from sympy.combinatorics.permutations import Permutation + >>> from sympy.combinatorics.named_groups import SymmetricGroup, CyclicGroup + >>> G = PermutationGroup(Permutation(1, 6)(2, 5)(3, 4), Permutation(0, 1, 2, 3, 4, 5, 6)) + >>> G.is_dihedral + True + >>> G = SymmetricGroup(3) + >>> G.is_dihedral + True + >>> G = CyclicGroup(6) + >>> G.is_dihedral + False + + References + ========== + + .. [Di1] https://math.stackexchange.com/questions/827230/given-a-cayley-table-is-there-an-algorithm-to-determine-if-it-is-a-dihedral-gro/827273#827273 + .. [Di2] https://kconrad.math.uconn.edu/blurbs/grouptheory/dihedral.pdf + .. [Di3] https://kconrad.math.uconn.edu/blurbs/grouptheory/dihedral2.pdf + .. [Di4] https://en.wikipedia.org/wiki/Dihedral_group + """ + if self._is_dihedral is not None: + return self._is_dihedral + + order = self.order() + + if order % 2 == 1: + self._is_dihedral = False + return False + if order == 2: + self._is_dihedral = True + return True + if order == 4: + # The dihedral group of order 4 is the Klein 4-group. + self._is_dihedral = not self.is_cyclic + return self._is_dihedral + if self.is_abelian: + # The only abelian dihedral groups are the ones of orders 2 and 4. + self._is_dihedral = False + return False + + # Now we know the group is of even order >= 6, and nonabelian. + n = order // 2 + + # Handle special cases where there are exactly two generators. + gens = self.generators + if len(gens) == 2: + x, y = gens + a, b = x.order(), y.order() + # Make a >= b + if a < b: + x, y, a, b = y, x, b, a + # Using Theorem 2.1 of [Di3]: + if a == 2 == b: + self._is_dihedral = True + return True + # Using Theorem 1.1 of [Di3]: + if a == n and b == 2 and y*x*y == ~x: + self._is_dihedral = True + return True + + # Proceed with algorithm of [Di1] + # Find elements of orders 2 and n + order_2, order_n = [], [] + for p in self.elements: + k = p.order() + if k == 2: + order_2.append(p) + elif k == n: + order_n.append(p) + + if len(order_2) != n + 1 - (n % 2): + self._is_dihedral = False + return False + + if not order_n: + self._is_dihedral = False + return False + + x = order_n[0] + # Want an element y of order 2 that is not a power of x + # (i.e. that is not the 180-deg rotation, when n is even). + y = order_2[0] + if n % 2 == 0 and y == x**(n//2): + y = order_2[1] + + self._is_dihedral = (y*x*y == ~x) + return self._is_dihedral + + def pointwise_stabilizer(self, points, incremental=True): + r"""Return the pointwise stabilizer for a set of points. + + Explanation + =========== + + For a permutation group `G` and a set of points + `\{p_1, p_2,\ldots, p_k\}`, the pointwise stabilizer of + `p_1, p_2, \ldots, p_k` is defined as + `G_{p_1,\ldots, p_k} = + \{g\in G | g(p_i) = p_i \forall i\in\{1, 2,\ldots,k\}\}` ([1],p20). + It is a subgroup of `G`. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> S = SymmetricGroup(7) + >>> Stab = S.pointwise_stabilizer([2, 3, 5]) + >>> Stab.is_subgroup(S.stabilizer(2).stabilizer(3).stabilizer(5)) + True + + See Also + ======== + + stabilizer, schreier_sims_incremental + + Notes + ===== + + When incremental == True, + rather than the obvious implementation using successive calls to + ``.stabilizer()``, this uses the incremental Schreier-Sims algorithm + to obtain a base with starting segment - the given points. + + """ + if incremental: + base, strong_gens = self.schreier_sims_incremental(base=points) + stab_gens = [] + degree = self.degree + for gen in strong_gens: + if [gen(point) for point in points] == points: + stab_gens.append(gen) + if not stab_gens: + stab_gens = _af_new(list(range(degree))) + return PermutationGroup(stab_gens) + else: + gens = self._generators + degree = self.degree + for x in points: + gens = _stabilizer(degree, gens, x) + return PermutationGroup(gens) + + def make_perm(self, n, seed=None): + """ + Multiply ``n`` randomly selected permutations from + pgroup together, starting with the identity + permutation. If ``n`` is a list of integers, those + integers will be used to select the permutations and they + will be applied in L to R order: make_perm((A, B, C)) will + give CBA(I) where I is the identity permutation. + + ``seed`` is used to set the seed for the random selection + of permutations from pgroup. If this is a list of integers, + the corresponding permutations from pgroup will be selected + in the order give. This is mainly used for testing purposes. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a, b = [Permutation([1, 0, 3, 2]), Permutation([1, 3, 0, 2])] + >>> G = PermutationGroup([a, b]) + >>> G.make_perm(1, [0]) + (0 1)(2 3) + >>> G.make_perm(3, [0, 1, 0]) + (0 2 3 1) + >>> G.make_perm([0, 1, 0]) + (0 2 3 1) + + See Also + ======== + + random + """ + if is_sequence(n): + if seed is not None: + raise ValueError('If n is a sequence, seed should be None') + n, seed = len(n), n + else: + try: + n = int(n) + except TypeError: + raise ValueError('n must be an integer or a sequence.') + randomrange = _randrange(seed) + + # start with the identity permutation + result = Permutation(list(range(self.degree))) + m = len(self) + for _ in range(n): + p = self[randomrange(m)] + result = rmul(result, p) + return result + + def random(self, af=False): + """Return a random group element + """ + rank = randrange(self.order()) + return self.coset_unrank(rank, af) + + def random_pr(self, gen_count=11, iterations=50, _random_prec=None): + """Return a random group element using product replacement. + + Explanation + =========== + + For the details of the product replacement algorithm, see + ``_random_pr_init`` In ``random_pr`` the actual 'product replacement' + is performed. Notice that if the attribute ``_random_gens`` + is empty, it needs to be initialized by ``_random_pr_init``. + + See Also + ======== + + _random_pr_init + + """ + if self._random_gens == []: + self._random_pr_init(gen_count, iterations) + random_gens = self._random_gens + r = len(random_gens) - 1 + + # handle randomized input for testing purposes + if _random_prec is None: + s = randrange(r) + t = randrange(r - 1) + if t == s: + t = r - 1 + x = choice([1, 2]) + e = choice([-1, 1]) + else: + s = _random_prec['s'] + t = _random_prec['t'] + if t == s: + t = r - 1 + x = _random_prec['x'] + e = _random_prec['e'] + + if x == 1: + random_gens[s] = _af_rmul(random_gens[s], _af_pow(random_gens[t], e)) + random_gens[r] = _af_rmul(random_gens[r], random_gens[s]) + else: + random_gens[s] = _af_rmul(_af_pow(random_gens[t], e), random_gens[s]) + random_gens[r] = _af_rmul(random_gens[s], random_gens[r]) + return _af_new(random_gens[r]) + + def random_stab(self, alpha, schreier_vector=None, _random_prec=None): + """Random element from the stabilizer of ``alpha``. + + The schreier vector for ``alpha`` is an optional argument used + for speeding up repeated calls. The algorithm is described in [1], p.81 + + See Also + ======== + + random_pr, orbit_rep + + """ + if schreier_vector is None: + schreier_vector = self.schreier_vector(alpha) + if _random_prec is None: + rand = self.random_pr() + else: + rand = _random_prec['rand'] + beta = rand(alpha) + h = self.orbit_rep(alpha, beta, schreier_vector) + return rmul(~h, rand) + + def schreier_sims(self): + """Schreier-Sims algorithm. + + Explanation + =========== + + It computes the generators of the chain of stabilizers + `G > G_{b_1} > .. > G_{b1,..,b_r} > 1` + in which `G_{b_1,..,b_i}` stabilizes `b_1,..,b_i`, + and the corresponding ``s`` cosets. + An element of the group can be written as the product + `h_1*..*h_s`. + + We use the incremental Schreier-Sims algorithm. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([0, 2, 1]) + >>> b = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a, b]) + >>> G.schreier_sims() + >>> G.basic_transversals + [{0: (2)(0 1), 1: (2), 2: (1 2)}, + {0: (2), 2: (0 2)}] + """ + if self._transversals: + return + self._schreier_sims() + return + + def _schreier_sims(self, base=None): + schreier = self.schreier_sims_incremental(base=base, slp_dict=True) + base, strong_gens = schreier[:2] + self._base = base + self._strong_gens = strong_gens + self._strong_gens_slp = schreier[2] + if not base: + self._transversals = [] + self._basic_orbits = [] + return + + strong_gens_distr = _distribute_gens_by_base(base, strong_gens) + basic_orbits, transversals, slps = _orbits_transversals_from_bsgs(base,\ + strong_gens_distr, slp=True) + + # rewrite the indices stored in slps in terms of strong_gens + for i, slp in enumerate(slps): + gens = strong_gens_distr[i] + for k in slp: + slp[k] = [strong_gens.index(gens[s]) for s in slp[k]] + + self._transversals = transversals + self._basic_orbits = [sorted(x) for x in basic_orbits] + self._transversal_slp = slps + + def schreier_sims_incremental(self, base=None, gens=None, slp_dict=False): + """Extend a sequence of points and generating set to a base and strong + generating set. + + Parameters + ========== + + base + The sequence of points to be extended to a base. Optional + parameter with default value ``[]``. + gens + The generating set to be extended to a strong generating set + relative to the base obtained. Optional parameter with default + value ``self.generators``. + + slp_dict + If `True`, return a dictionary `{g: gens}` for each strong + generator `g` where `gens` is a list of strong generators + coming before `g` in `strong_gens`, such that the product + of the elements of `gens` is equal to `g`. + + Returns + ======= + + (base, strong_gens) + ``base`` is the base obtained, and ``strong_gens`` is the strong + generating set relative to it. The original parameters ``base``, + ``gens`` remain unchanged. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AlternatingGroup + >>> from sympy.combinatorics.testutil import _verify_bsgs + >>> A = AlternatingGroup(7) + >>> base = [2, 3] + >>> seq = [2, 3] + >>> base, strong_gens = A.schreier_sims_incremental(base=seq) + >>> _verify_bsgs(A, base, strong_gens) + True + >>> base[:2] + [2, 3] + + Notes + ===== + + This version of the Schreier-Sims algorithm runs in polynomial time. + There are certain assumptions in the implementation - if the trivial + group is provided, ``base`` and ``gens`` are returned immediately, + as any sequence of points is a base for the trivial group. If the + identity is present in the generators ``gens``, it is removed as + it is a redundant generator. + The implementation is described in [1], pp. 90-93. + + See Also + ======== + + schreier_sims, schreier_sims_random + + """ + if base is None: + base = [] + if gens is None: + gens = self.generators[:] + degree = self.degree + id_af = list(range(degree)) + # handle the trivial group + if len(gens) == 1 and gens[0].is_Identity: + if slp_dict: + return base, gens, {gens[0]: [gens[0]]} + return base, gens + # prevent side effects + _base, _gens = base[:], gens[:] + # remove the identity as a generator + _gens = [x for x in _gens if not x.is_Identity] + # make sure no generator fixes all base points + for gen in _gens: + if all(x == gen._array_form[x] for x in _base): + for new in id_af: + if gen._array_form[new] != new: + break + else: + assert None # can this ever happen? + _base.append(new) + # distribute generators according to basic stabilizers + strong_gens_distr = _distribute_gens_by_base(_base, _gens) + strong_gens_slp = [] + # initialize the basic stabilizers, basic orbits and basic transversals + orbs = {} + transversals = {} + slps = {} + base_len = len(_base) + for i in range(base_len): + transversals[i], slps[i] = _orbit_transversal(degree, strong_gens_distr[i], + _base[i], pairs=True, af=True, slp=True) + transversals[i] = dict(transversals[i]) + orbs[i] = list(transversals[i].keys()) + # main loop: amend the stabilizer chain until we have generators + # for all stabilizers + i = base_len - 1 + while i >= 0: + # this flag is used to continue with the main loop from inside + # a nested loop + continue_i = False + # test the generators for being a strong generating set + db = {} + for beta, u_beta in list(transversals[i].items()): + for j, gen in enumerate(strong_gens_distr[i]): + gb = gen._array_form[beta] + u1 = transversals[i][gb] + g1 = _af_rmul(gen._array_form, u_beta) + slp = [(i, g) for g in slps[i][beta]] + slp = [(i, j)] + slp + if g1 != u1: + # test if the schreier generator is in the i+1-th + # would-be basic stabilizer + y = True + try: + u1_inv = db[gb] + except KeyError: + u1_inv = db[gb] = _af_invert(u1) + schreier_gen = _af_rmul(u1_inv, g1) + u1_inv_slp = slps[i][gb][:] + u1_inv_slp.reverse() + u1_inv_slp = [(i, (g,)) for g in u1_inv_slp] + slp = u1_inv_slp + slp + h, j, slp = _strip_af(schreier_gen, _base, orbs, transversals, i, slp=slp, slps=slps) + if j <= base_len: + # new strong generator h at level j + y = False + elif h: + # h fixes all base points + y = False + moved = 0 + while h[moved] == moved: + moved += 1 + _base.append(moved) + base_len += 1 + strong_gens_distr.append([]) + if y is False: + # if a new strong generator is found, update the + # data structures and start over + h = _af_new(h) + strong_gens_slp.append((h, slp)) + for l in range(i + 1, j): + strong_gens_distr[l].append(h) + transversals[l], slps[l] =\ + _orbit_transversal(degree, strong_gens_distr[l], + _base[l], pairs=True, af=True, slp=True) + transversals[l] = dict(transversals[l]) + orbs[l] = list(transversals[l].keys()) + i = j - 1 + # continue main loop using the flag + continue_i = True + if continue_i is True: + break + if continue_i is True: + break + if continue_i is True: + continue + i -= 1 + + strong_gens = _gens[:] + + if slp_dict: + # create the list of the strong generators strong_gens and + # rewrite the indices of strong_gens_slp in terms of the + # elements of strong_gens + for k, slp in strong_gens_slp: + strong_gens.append(k) + for i in range(len(slp)): + s = slp[i] + if isinstance(s[1], tuple): + slp[i] = strong_gens_distr[s[0]][s[1][0]]**-1 + else: + slp[i] = strong_gens_distr[s[0]][s[1]] + strong_gens_slp = dict(strong_gens_slp) + # add the original generators + for g in _gens: + strong_gens_slp[g] = [g] + return (_base, strong_gens, strong_gens_slp) + + strong_gens.extend([k for k, _ in strong_gens_slp]) + return _base, strong_gens + + def schreier_sims_random(self, base=None, gens=None, consec_succ=10, + _random_prec=None): + r"""Randomized Schreier-Sims algorithm. + + Explanation + =========== + + The randomized Schreier-Sims algorithm takes the sequence ``base`` + and the generating set ``gens``, and extends ``base`` to a base, and + ``gens`` to a strong generating set relative to that base with + probability of a wrong answer at most `2^{-consec\_succ}`, + provided the random generators are sufficiently random. + + Parameters + ========== + + base + The sequence to be extended to a base. + gens + The generating set to be extended to a strong generating set. + consec_succ + The parameter defining the probability of a wrong answer. + _random_prec + An internal parameter used for testing purposes. + + Returns + ======= + + (base, strong_gens) + ``base`` is the base and ``strong_gens`` is the strong generating + set relative to it. + + Examples + ======== + + >>> from sympy.combinatorics.testutil import _verify_bsgs + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> S = SymmetricGroup(5) + >>> base, strong_gens = S.schreier_sims_random(consec_succ=5) + >>> _verify_bsgs(S, base, strong_gens) #doctest: +SKIP + True + + Notes + ===== + + The algorithm is described in detail in [1], pp. 97-98. It extends + the orbits ``orbs`` and the permutation groups ``stabs`` to + basic orbits and basic stabilizers for the base and strong generating + set produced in the end. + The idea of the extension process + is to "sift" random group elements through the stabilizer chain + and amend the stabilizers/orbits along the way when a sift + is not successful. + The helper function ``_strip`` is used to attempt + to decompose a random group element according to the current + state of the stabilizer chain and report whether the element was + fully decomposed (successful sift) or not (unsuccessful sift). In + the latter case, the level at which the sift failed is reported and + used to amend ``stabs``, ``base``, ``gens`` and ``orbs`` accordingly. + The halting condition is for ``consec_succ`` consecutive successful + sifts to pass. This makes sure that the current ``base`` and ``gens`` + form a BSGS with probability at least `1 - 1/\text{consec\_succ}`. + + See Also + ======== + + schreier_sims + + """ + if base is None: + base = [] + if gens is None: + gens = self.generators + base_len = len(base) + n = self.degree + # make sure no generator fixes all base points + for gen in gens: + if all(gen(x) == x for x in base): + new = 0 + while gen._array_form[new] == new: + new += 1 + base.append(new) + base_len += 1 + # distribute generators according to basic stabilizers + strong_gens_distr = _distribute_gens_by_base(base, gens) + # initialize the basic stabilizers, basic transversals and basic orbits + transversals = {} + orbs = {} + for i in range(base_len): + transversals[i] = dict(_orbit_transversal(n, strong_gens_distr[i], + base[i], pairs=True)) + orbs[i] = list(transversals[i].keys()) + # initialize the number of consecutive elements sifted + c = 0 + # start sifting random elements while the number of consecutive sifts + # is less than consec_succ + while c < consec_succ: + if _random_prec is None: + g = self.random_pr() + else: + g = _random_prec['g'].pop() + h, j = _strip(g, base, orbs, transversals) + y = True + # determine whether a new base point is needed + if j <= base_len: + y = False + elif not h.is_Identity: + y = False + moved = 0 + while h(moved) == moved: + moved += 1 + base.append(moved) + base_len += 1 + strong_gens_distr.append([]) + # if the element doesn't sift, amend the strong generators and + # associated stabilizers and orbits + if y is False: + for l in range(1, j): + strong_gens_distr[l].append(h) + transversals[l] = dict(_orbit_transversal(n, + strong_gens_distr[l], base[l], pairs=True)) + orbs[l] = list(transversals[l].keys()) + c = 0 + else: + c += 1 + # build the strong generating set + strong_gens = strong_gens_distr[0][:] + for gen in strong_gens_distr[1]: + if gen not in strong_gens: + strong_gens.append(gen) + return base, strong_gens + + def schreier_vector(self, alpha): + """Computes the schreier vector for ``alpha``. + + Explanation + =========== + + The Schreier vector efficiently stores information + about the orbit of ``alpha``. It can later be used to quickly obtain + elements of the group that send ``alpha`` to a particular element + in the orbit. Notice that the Schreier vector depends on the order + in which the group generators are listed. For a definition, see [3]. + Since list indices start from zero, we adopt the convention to use + "None" instead of 0 to signify that an element does not belong + to the orbit. + For the algorithm and its correctness, see [2], pp.78-80. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([2, 4, 6, 3, 1, 5, 0]) + >>> b = Permutation([0, 1, 3, 5, 4, 6, 2]) + >>> G = PermutationGroup([a, b]) + >>> G.schreier_vector(0) + [-1, None, 0, 1, None, 1, 0] + + See Also + ======== + + orbit + + """ + n = self.degree + v = [None]*n + v[alpha] = -1 + orb = [alpha] + used = [False]*n + used[alpha] = True + gens = self.generators + r = len(gens) + for b in orb: + for i in range(r): + temp = gens[i]._array_form[b] + if used[temp] is False: + orb.append(temp) + used[temp] = True + v[temp] = i + return v + + def stabilizer(self, alpha): + r"""Return the stabilizer subgroup of ``alpha``. + + Explanation + =========== + + The stabilizer of `\alpha` is the group `G_\alpha = + \{g \in G | g(\alpha) = \alpha\}`. + For a proof of correctness, see [1], p.79. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> G = DihedralGroup(6) + >>> G.stabilizer(5) + PermutationGroup([ + (5)(0 4)(1 3)]) + + See Also + ======== + + orbit + + """ + return PermGroup(_stabilizer(self._degree, self._generators, alpha)) + + @property + def strong_gens(self): + r"""Return a strong generating set from the Schreier-Sims algorithm. + + Explanation + =========== + + A generating set `S = \{g_1, g_2, \dots, g_t\}` for a permutation group + `G` is a strong generating set relative to the sequence of points + (referred to as a "base") `(b_1, b_2, \dots, b_k)` if, for + `1 \leq i \leq k` we have that the intersection of the pointwise + stabilizer `G^{(i+1)} := G_{b_1, b_2, \dots, b_i}` with `S` generates + the pointwise stabilizer `G^{(i+1)}`. The concepts of a base and + strong generating set and their applications are discussed in depth + in [1], pp. 87-89 and [2], pp. 55-57. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> D = DihedralGroup(4) + >>> D.strong_gens + [(0 1 2 3), (0 3)(1 2), (1 3)] + >>> D.base + [0, 1] + + See Also + ======== + + base, basic_transversals, basic_orbits, basic_stabilizers + + """ + if self._strong_gens == []: + self.schreier_sims() + return self._strong_gens + + def subgroup(self, gens): + """ + Return the subgroup generated by `gens` which is a list of + elements of the group + """ + + if not all(g in self for g in gens): + raise ValueError("The group does not contain the supplied generators") + + G = PermutationGroup(gens) + return G + + def subgroup_search(self, prop, base=None, strong_gens=None, tests=None, + init_subgroup=None): + """Find the subgroup of all elements satisfying the property ``prop``. + + Explanation + =========== + + This is done by a depth-first search with respect to base images that + uses several tests to prune the search tree. + + Parameters + ========== + + prop + The property to be used. Has to be callable on group elements + and always return ``True`` or ``False``. It is assumed that + all group elements satisfying ``prop`` indeed form a subgroup. + base + A base for the supergroup. + strong_gens + A strong generating set for the supergroup. + tests + A list of callables of length equal to the length of ``base``. + These are used to rule out group elements by partial base images, + so that ``tests[l](g)`` returns False if the element ``g`` is known + not to satisfy prop base on where g sends the first ``l + 1`` base + points. + init_subgroup + if a subgroup of the sought group is + known in advance, it can be passed to the function as this + parameter. + + Returns + ======= + + res + The subgroup of all elements satisfying ``prop``. The generating + set for this group is guaranteed to be a strong generating set + relative to the base ``base``. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... AlternatingGroup) + >>> from sympy.combinatorics.testutil import _verify_bsgs + >>> S = SymmetricGroup(7) + >>> prop_even = lambda x: x.is_even + >>> base, strong_gens = S.schreier_sims_incremental() + >>> G = S.subgroup_search(prop_even, base=base, strong_gens=strong_gens) + >>> G.is_subgroup(AlternatingGroup(7)) + True + >>> _verify_bsgs(G, base, G.generators) + True + + Notes + ===== + + This function is extremely lengthy and complicated and will require + some careful attention. The implementation is described in + [1], pp. 114-117, and the comments for the code here follow the lines + of the pseudocode in the book for clarity. + + The complexity is exponential in general, since the search process by + itself visits all members of the supergroup. However, there are a lot + of tests which are used to prune the search tree, and users can define + their own tests via the ``tests`` parameter, so in practice, and for + some computations, it's not terrible. + + A crucial part in the procedure is the frequent base change performed + (this is line 11 in the pseudocode) in order to obtain a new basic + stabilizer. The book mentiones that this can be done by using + ``.baseswap(...)``, however the current implementation uses a more + straightforward way to find the next basic stabilizer - calling the + function ``.stabilizer(...)`` on the previous basic stabilizer. + + """ + # initialize BSGS and basic group properties + def get_reps(orbits): + # get the minimal element in the base ordering + return [min(orbit, key = lambda x: base_ordering[x]) \ + for orbit in orbits] + + def update_nu(l): + temp_index = len(basic_orbits[l]) + 1 -\ + len(res_basic_orbits_init_base[l]) + # this corresponds to the element larger than all points + if temp_index >= len(sorted_orbits[l]): + nu[l] = base_ordering[degree] + else: + nu[l] = sorted_orbits[l][temp_index] + + if base is None: + base, strong_gens = self.schreier_sims_incremental() + base_len = len(base) + degree = self.degree + identity = _af_new(list(range(degree))) + base_ordering = _base_ordering(base, degree) + # add an element larger than all points + base_ordering.append(degree) + # add an element smaller than all points + base_ordering.append(-1) + # compute BSGS-related structures + strong_gens_distr = _distribute_gens_by_base(base, strong_gens) + basic_orbits, transversals = _orbits_transversals_from_bsgs(base, + strong_gens_distr) + # handle subgroup initialization and tests + if init_subgroup is None: + init_subgroup = PermutationGroup([identity]) + if tests is None: + trivial_test = lambda x: True + tests = [] + for i in range(base_len): + tests.append(trivial_test) + # line 1: more initializations. + res = init_subgroup + f = base_len - 1 + l = base_len - 1 + # line 2: set the base for K to the base for G + res_base = base[:] + # line 3: compute BSGS and related structures for K + res_base, res_strong_gens = res.schreier_sims_incremental( + base=res_base) + res_strong_gens_distr = _distribute_gens_by_base(res_base, + res_strong_gens) + res_generators = res.generators + res_basic_orbits_init_base = \ + [_orbit(degree, res_strong_gens_distr[i], res_base[i])\ + for i in range(base_len)] + # initialize orbit representatives + orbit_reps = [None]*base_len + # line 4: orbit representatives for f-th basic stabilizer of K + orbits = _orbits(degree, res_strong_gens_distr[f]) + orbit_reps[f] = get_reps(orbits) + # line 5: remove the base point from the representatives to avoid + # getting the identity element as a generator for K + orbit_reps[f].remove(base[f]) + # line 6: more initializations + c = [0]*base_len + u = [identity]*base_len + sorted_orbits = [None]*base_len + for i in range(base_len): + sorted_orbits[i] = basic_orbits[i][:] + sorted_orbits[i].sort(key=lambda point: base_ordering[point]) + # line 7: initializations + mu = [None]*base_len + nu = [None]*base_len + # this corresponds to the element smaller than all points + mu[l] = degree + 1 + update_nu(l) + # initialize computed words + computed_words = [identity]*base_len + # line 8: main loop + while True: + # apply all the tests + while l < base_len - 1 and \ + computed_words[l](base[l]) in orbit_reps[l] and \ + base_ordering[mu[l]] < \ + base_ordering[computed_words[l](base[l])] < \ + base_ordering[nu[l]] and \ + tests[l](computed_words): + # line 11: change the (partial) base of K + new_point = computed_words[l](base[l]) + res_base[l] = new_point + new_stab_gens = _stabilizer(degree, res_strong_gens_distr[l], + new_point) + res_strong_gens_distr[l + 1] = new_stab_gens + # line 12: calculate minimal orbit representatives for the + # l+1-th basic stabilizer + orbits = _orbits(degree, new_stab_gens) + orbit_reps[l + 1] = get_reps(orbits) + # line 13: amend sorted orbits + l += 1 + temp_orbit = [computed_words[l - 1](point) for point + in basic_orbits[l]] + temp_orbit.sort(key=lambda point: base_ordering[point]) + sorted_orbits[l] = temp_orbit + # lines 14 and 15: update variables used minimality tests + new_mu = degree + 1 + for i in range(l): + if base[l] in res_basic_orbits_init_base[i]: + candidate = computed_words[i](base[i]) + if base_ordering[candidate] > base_ordering[new_mu]: + new_mu = candidate + mu[l] = new_mu + update_nu(l) + # line 16: determine the new transversal element + c[l] = 0 + temp_point = sorted_orbits[l][c[l]] + gamma = computed_words[l - 1]._array_form.index(temp_point) + u[l] = transversals[l][gamma] + # update computed words + computed_words[l] = rmul(computed_words[l - 1], u[l]) + # lines 17 & 18: apply the tests to the group element found + g = computed_words[l] + temp_point = g(base[l]) + if l == base_len - 1 and \ + base_ordering[mu[l]] < \ + base_ordering[temp_point] < base_ordering[nu[l]] and \ + temp_point in orbit_reps[l] and \ + tests[l](computed_words) and \ + prop(g): + # line 19: reset the base of K + res_generators.append(g) + res_base = base[:] + # line 20: recalculate basic orbits (and transversals) + res_strong_gens.append(g) + res_strong_gens_distr = _distribute_gens_by_base(res_base, + res_strong_gens) + res_basic_orbits_init_base = \ + [_orbit(degree, res_strong_gens_distr[i], res_base[i]) \ + for i in range(base_len)] + # line 21: recalculate orbit representatives + # line 22: reset the search depth + orbit_reps[f] = get_reps(orbits) + l = f + # line 23: go up the tree until in the first branch not fully + # searched + while l >= 0 and c[l] == len(basic_orbits[l]) - 1: + l = l - 1 + # line 24: if the entire tree is traversed, return K + if l == -1: + return PermutationGroup(res_generators) + # lines 25-27: update orbit representatives + if l < f: + # line 26 + f = l + c[l] = 0 + # line 27 + temp_orbits = _orbits(degree, res_strong_gens_distr[f]) + orbit_reps[f] = get_reps(temp_orbits) + # line 28: update variables used for minimality testing + mu[l] = degree + 1 + temp_index = len(basic_orbits[l]) + 1 - \ + len(res_basic_orbits_init_base[l]) + if temp_index >= len(sorted_orbits[l]): + nu[l] = base_ordering[degree] + else: + nu[l] = sorted_orbits[l][temp_index] + # line 29: set the next element from the current branch and update + # accordingly + c[l] += 1 + if l == 0: + gamma = sorted_orbits[l][c[l]] + else: + gamma = computed_words[l - 1]._array_form.index(sorted_orbits[l][c[l]]) + + u[l] = transversals[l][gamma] + if l == 0: + computed_words[l] = u[l] + else: + computed_words[l] = rmul(computed_words[l - 1], u[l]) + + @property + def transitivity_degree(self): + r"""Compute the degree of transitivity of the group. + + Explanation + =========== + + A permutation group `G` acting on `\Omega = \{0, 1, \dots, n-1\}` is + ``k``-fold transitive, if, for any `k` points + `(a_1, a_2, \dots, a_k) \in \Omega` and any `k` points + `(b_1, b_2, \dots, b_k) \in \Omega` there exists `g \in G` such that + `g(a_1) = b_1, g(a_2) = b_2, \dots, g(a_k) = b_k` + The degree of transitivity of `G` is the maximum ``k`` such that + `G` is ``k``-fold transitive. ([8]) + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> a = Permutation([1, 2, 0]) + >>> b = Permutation([1, 0, 2]) + >>> G = PermutationGroup([a, b]) + >>> G.transitivity_degree + 3 + + See Also + ======== + + is_transitive, orbit + + """ + if self._transitivity_degree is None: + n = self.degree + G = self + # if G is k-transitive, a tuple (a_0,..,a_k) + # can be brought to (b_0,...,b_(k-1), b_k) + # where b_0,...,b_(k-1) are fixed points; + # consider the group G_k which stabilizes b_0,...,b_(k-1) + # if G_k is transitive on the subset excluding b_0,...,b_(k-1) + # then G is (k+1)-transitive + for i in range(n): + orb = G.orbit(i) + if len(orb) != n - i: + self._transitivity_degree = i + return i + G = G.stabilizer(i) + self._transitivity_degree = n + return n + else: + return self._transitivity_degree + + def _p_elements_group(self, p): + ''' + For an abelian p-group, return the subgroup consisting of + all elements of order p (and the identity) + + ''' + gens = self.generators[:] + gens = sorted(gens, key=lambda x: x.order(), reverse=True) + gens_p = [g**(g.order()/p) for g in gens] + gens_r = [] + for i in range(len(gens)): + x = gens[i] + x_order = x.order() + # x_p has order p + x_p = x**(x_order/p) + if i > 0: + P = PermutationGroup(gens_p[:i]) + else: + P = PermutationGroup(self.identity) + if x**(x_order/p) not in P: + gens_r.append(x**(x_order/p)) + else: + # replace x by an element of order (x.order()/p) + # so that gens still generates G + g = P.generator_product(x_p, original=True) + for s in g: + x = x*s**-1 + x_order = x_order/p + # insert x to gens so that the sorting is preserved + del gens[i] + del gens_p[i] + j = i - 1 + while j < len(gens) and gens[j].order() >= x_order: + j += 1 + gens = gens[:j] + [x] + gens[j:] + gens_p = gens_p[:j] + [x] + gens_p[j:] + return PermutationGroup(gens_r) + + def _sylow_alt_sym(self, p): + ''' + Return a p-Sylow subgroup of a symmetric or an + alternating group. + + Explanation + =========== + + The algorithm for this is hinted at in [1], Chapter 4, + Exercise 4. + + For Sym(n) with n = p^i, the idea is as follows. Partition + the interval [0..n-1] into p equal parts, each of length p^(i-1): + [0..p^(i-1)-1], [p^(i-1)..2*p^(i-1)-1]...[(p-1)*p^(i-1)..p^i-1]. + Find a p-Sylow subgroup of Sym(p^(i-1)) (treated as a subgroup + of ``self``) acting on each of the parts. Call the subgroups + P_1, P_2...P_p. The generators for the subgroups P_2...P_p + can be obtained from those of P_1 by applying a "shifting" + permutation to them, that is, a permutation mapping [0..p^(i-1)-1] + to the second part (the other parts are obtained by using the shift + multiple times). The union of this permutation and the generators + of P_1 is a p-Sylow subgroup of ``self``. + + For n not equal to a power of p, partition + [0..n-1] in accordance with how n would be written in base p. + E.g. for p=2 and n=11, 11 = 2^3 + 2^2 + 1 so the partition + is [[0..7], [8..9], {10}]. To generate a p-Sylow subgroup, + take the union of the generators for each of the parts. + For the above example, {(0 1), (0 2)(1 3), (0 4), (1 5)(2 7)} + from the first part, {(8 9)} from the second part and + nothing from the third. This gives 4 generators in total, and + the subgroup they generate is p-Sylow. + + Alternating groups are treated the same except when p=2. In this + case, (0 1)(s s+1) should be added for an appropriate s (the start + of a part) for each part in the partitions. + + See Also + ======== + + sylow_subgroup, is_alt_sym + + ''' + n = self.degree + gens = [] + identity = Permutation(n-1) + # the case of 2-sylow subgroups of alternating groups + # needs special treatment + alt = p == 2 and all(g.is_even for g in self.generators) + + # find the presentation of n in base p + coeffs = [] + m = n + while m > 0: + coeffs.append(m % p) + m = m // p + + power = len(coeffs)-1 + # for a symmetric group, gens[:i] is the generating + # set for a p-Sylow subgroup on [0..p**(i-1)-1]. For + # alternating groups, the same is given by gens[:2*(i-1)] + for i in range(1, power+1): + if i == 1 and alt: + # (0 1) shouldn't be added for alternating groups + continue + gen = Permutation([(j + p**(i-1)) % p**i for j in range(p**i)]) + gens.append(identity*gen) + if alt: + gen = Permutation(0, 1)*gen*Permutation(0, 1)*gen + gens.append(gen) + + # the first point in the current part (see the algorithm + # description in the docstring) + start = 0 + + while power > 0: + a = coeffs[power] + + # make the permutation shifting the start of the first + # part ([0..p^i-1] for some i) to the current one + for _ in range(a): + shift = Permutation() + if start > 0: + for i in range(p**power): + shift = shift(i, start + i) + + if alt: + gen = Permutation(0, 1)*shift*Permutation(0, 1)*shift + gens.append(gen) + j = 2*(power - 1) + else: + j = power + + for i, gen in enumerate(gens[:j]): + if alt and i % 2 == 1: + continue + # shift the generator to the start of the + # partition part + gen = shift*gen*shift + gens.append(gen) + + start += p**power + power = power-1 + + return gens + + def sylow_subgroup(self, p): + ''' + Return a p-Sylow subgroup of the group. + + The algorithm is described in [1], Chapter 4, Section 7 + + Examples + ======== + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> from sympy.combinatorics.named_groups import SymmetricGroup + >>> from sympy.combinatorics.named_groups import AlternatingGroup + + >>> D = DihedralGroup(6) + >>> S = D.sylow_subgroup(2) + >>> S.order() + 4 + >>> G = SymmetricGroup(6) + >>> S = G.sylow_subgroup(5) + >>> S.order() + 5 + + >>> G1 = AlternatingGroup(3) + >>> G2 = AlternatingGroup(5) + >>> G3 = AlternatingGroup(9) + + >>> S1 = G1.sylow_subgroup(3) + >>> S2 = G2.sylow_subgroup(3) + >>> S3 = G3.sylow_subgroup(3) + + >>> len1 = len(S1.lower_central_series()) + >>> len2 = len(S2.lower_central_series()) + >>> len3 = len(S3.lower_central_series()) + + >>> len1 == len2 + True + >>> len1 < len3 + True + + ''' + from sympy.combinatorics.homomorphisms import ( + orbit_homomorphism, block_homomorphism) + + if not isprime(p): + raise ValueError("p must be a prime") + + def is_p_group(G): + # check if the order of G is a power of p + # and return the power + m = G.order() + n = 0 + while m % p == 0: + m = m/p + n += 1 + if m == 1: + return True, n + return False, n + + def _sylow_reduce(mu, nu): + # reduction based on two homomorphisms + # mu and nu with trivially intersecting + # kernels + Q = mu.image().sylow_subgroup(p) + Q = mu.invert_subgroup(Q) + nu = nu.restrict_to(Q) + R = nu.image().sylow_subgroup(p) + return nu.invert_subgroup(R) + + order = self.order() + if order % p != 0: + return PermutationGroup([self.identity]) + p_group, n = is_p_group(self) + if p_group: + return self + + if self.is_alt_sym(): + return PermutationGroup(self._sylow_alt_sym(p)) + + # if there is a non-trivial orbit with size not divisible + # by p, the sylow subgroup is contained in its stabilizer + # (by orbit-stabilizer theorem) + orbits = self.orbits() + non_p_orbits = [o for o in orbits if len(o) % p != 0 and len(o) != 1] + if non_p_orbits: + G = self.stabilizer(list(non_p_orbits[0]).pop()) + return G.sylow_subgroup(p) + + if not self.is_transitive(): + # apply _sylow_reduce to orbit actions + orbits = sorted(orbits, key=len) + omega1 = orbits.pop() + omega2 = orbits[0].union(*orbits) + mu = orbit_homomorphism(self, omega1) + nu = orbit_homomorphism(self, omega2) + return _sylow_reduce(mu, nu) + + blocks = self.minimal_blocks() + if len(blocks) > 1: + # apply _sylow_reduce to block system actions + mu = block_homomorphism(self, blocks[0]) + nu = block_homomorphism(self, blocks[1]) + return _sylow_reduce(mu, nu) + elif len(blocks) == 1: + block = list(blocks)[0] + if any(e != 0 for e in block): + # self is imprimitive + mu = block_homomorphism(self, block) + if not is_p_group(mu.image())[0]: + S = mu.image().sylow_subgroup(p) + return mu.invert_subgroup(S).sylow_subgroup(p) + + # find an element of order p + g = self.random() + g_order = g.order() + while g_order % p != 0 or g_order == 0: + g = self.random() + g_order = g.order() + g = g**(g_order // p) + if order % p**2 != 0: + return PermutationGroup(g) + + C = self.centralizer(g) + while C.order() % p**n != 0: + S = C.sylow_subgroup(p) + s_order = S.order() + Z = S.center() + P = Z._p_elements_group(p) + h = P.random() + C_h = self.centralizer(h) + while C_h.order() % p*s_order != 0: + h = P.random() + C_h = self.centralizer(h) + C = C_h + + return C.sylow_subgroup(p) + + def _block_verify(self, L, alpha): + delta = sorted(self.orbit(alpha)) + # p[i] will be the number of the block + # delta[i] belongs to + p = [-1]*len(delta) + blocks = [-1]*len(delta) + + B = [[]] # future list of blocks + u = [0]*len(delta) # u[i] in L s.t. alpha^u[i] = B[0][i] + + t = L.orbit_transversal(alpha, pairs=True) + for a, beta in t: + B[0].append(a) + i_a = delta.index(a) + p[i_a] = 0 + blocks[i_a] = alpha + u[i_a] = beta + + rho = 0 + m = 0 # number of blocks - 1 + + while rho <= m: + beta = B[rho][0] + for g in self.generators: + d = beta^g + i_d = delta.index(d) + sigma = p[i_d] + if sigma < 0: + # define a new block + m += 1 + sigma = m + u[i_d] = u[delta.index(beta)]*g + p[i_d] = sigma + rep = d + blocks[i_d] = rep + newb = [rep] + for gamma in B[rho][1:]: + i_gamma = delta.index(gamma) + d = gamma^g + i_d = delta.index(d) + if p[i_d] < 0: + u[i_d] = u[i_gamma]*g + p[i_d] = sigma + blocks[i_d] = rep + newb.append(d) + else: + # B[rho] is not a block + s = u[i_gamma]*g*u[i_d]**(-1) + return False, s + + B.append(newb) + else: + for h in B[rho][1:]: + if h^g not in B[sigma]: + # B[rho] is not a block + s = u[delta.index(beta)]*g*u[i_d]**(-1) + return False, s + rho += 1 + + return True, blocks + + def _verify(H, K, phi, z, alpha): + ''' + Return a list of relators ``rels`` in generators ``gens`_h` that + are mapped to ``H.generators`` by ``phi`` so that given a finite + presentation of ``K`` on a subset of ``gens_h`` + is a finite presentation of ``H``. + + Explanation + =========== + + ``H`` should be generated by the union of ``K.generators`` and ``z`` + (a single generator), and ``H.stabilizer(alpha) == K``; ``phi`` is a + canonical injection from a free group into a permutation group + containing ``H``. + + The algorithm is described in [1], Chapter 6. + + Examples + ======== + + >>> from sympy.combinatorics import free_group, Permutation, PermutationGroup + >>> from sympy.combinatorics.homomorphisms import homomorphism + >>> from sympy.combinatorics.fp_groups import FpGroup + + >>> H = PermutationGroup(Permutation(0, 2), Permutation (1, 5)) + >>> K = PermutationGroup(Permutation(5)(0, 2)) + >>> F = free_group("x_0 x_1")[0] + >>> gens = F.generators + >>> phi = homomorphism(F, H, F.generators, H.generators) + >>> rels_k = [gens[0]**2] # relators for presentation of K + >>> z= Permutation(1, 5) + >>> check, rels_h = H._verify(K, phi, z, 1) + >>> check + True + >>> rels = rels_k + rels_h + >>> G = FpGroup(F, rels) # presentation of H + >>> G.order() == H.order() + True + + See also + ======== + + strong_presentation, presentation, stabilizer + + ''' + + orbit = H.orbit(alpha) + beta = alpha^(z**-1) + + K_beta = K.stabilizer(beta) + + # orbit representatives of K_beta + gammas = [alpha, beta] + orbits = list({tuple(K_beta.orbit(o)) for o in orbit}) + orbit_reps = [orb[0] for orb in orbits] + for rep in orbit_reps: + if rep not in gammas: + gammas.append(rep) + + # orbit transversal of K + betas = [alpha, beta] + transversal = {alpha: phi.invert(H.identity), beta: phi.invert(z**-1)} + + for s, g in K.orbit_transversal(beta, pairs=True): + if s not in transversal: + transversal[s] = transversal[beta]*phi.invert(g) + + + union = K.orbit(alpha).union(K.orbit(beta)) + while (len(union) < len(orbit)): + for gamma in gammas: + if gamma in union: + r = gamma^z + if r not in union: + betas.append(r) + transversal[r] = transversal[gamma]*phi.invert(z) + for s, g in K.orbit_transversal(r, pairs=True): + if s not in transversal: + transversal[s] = transversal[r]*phi.invert(g) + union = union.union(K.orbit(r)) + break + + # compute relators + rels = [] + + for b in betas: + k_gens = K.stabilizer(b).generators + for y in k_gens: + new_rel = transversal[b] + gens = K.generator_product(y, original=True) + for g in gens[::-1]: + new_rel = new_rel*phi.invert(g) + new_rel = new_rel*transversal[b]**-1 + + perm = phi(new_rel) + try: + gens = K.generator_product(perm, original=True) + except ValueError: + return False, perm + for g in gens: + new_rel = new_rel*phi.invert(g)**-1 + if new_rel not in rels: + rels.append(new_rel) + + for gamma in gammas: + new_rel = transversal[gamma]*phi.invert(z)*transversal[gamma^z]**-1 + perm = phi(new_rel) + try: + gens = K.generator_product(perm, original=True) + except ValueError: + return False, perm + for g in gens: + new_rel = new_rel*phi.invert(g)**-1 + if new_rel not in rels: + rels.append(new_rel) + + return True, rels + + def strong_presentation(self): + ''' + Return a strong finite presentation of group. The generators + of the returned group are in the same order as the strong + generators of group. + + The algorithm is based on Sims' Verify algorithm described + in [1], Chapter 6. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> P = DihedralGroup(4) + >>> G = P.strong_presentation() + >>> P.order() == G.order() + True + + See Also + ======== + + presentation, _verify + + ''' + from sympy.combinatorics.fp_groups import (FpGroup, + simplify_presentation) + from sympy.combinatorics.free_groups import free_group + from sympy.combinatorics.homomorphisms import (block_homomorphism, + homomorphism, GroupHomomorphism) + + strong_gens = self.strong_gens[:] + stabs = self.basic_stabilizers[:] + base = self.base[:] + + # injection from a free group on len(strong_gens) + # generators into G + gen_syms = [('x_%d'%i) for i in range(len(strong_gens))] + F = free_group(', '.join(gen_syms))[0] + phi = homomorphism(F, self, F.generators, strong_gens) + + H = PermutationGroup(self.identity) + while stabs: + alpha = base.pop() + K = H + H = stabs.pop() + new_gens = [g for g in H.generators if g not in K] + + if K.order() == 1: + z = new_gens.pop() + rels = [F.generators[-1]**z.order()] + intermediate_gens = [z] + K = PermutationGroup(intermediate_gens) + + # add generators one at a time building up from K to H + while new_gens: + z = new_gens.pop() + intermediate_gens = [z] + intermediate_gens + K_s = PermutationGroup(intermediate_gens) + orbit = K_s.orbit(alpha) + orbit_k = K.orbit(alpha) + + # split into cases based on the orbit of K_s + if orbit_k == orbit: + if z in K: + rel = phi.invert(z) + perm = z + else: + t = K.orbit_rep(alpha, alpha^z) + rel = phi.invert(z)*phi.invert(t)**-1 + perm = z*t**-1 + for g in K.generator_product(perm, original=True): + rel = rel*phi.invert(g)**-1 + new_rels = [rel] + elif len(orbit_k) == 1: + # `success` is always true because `strong_gens` + # and `base` are already a verified BSGS. Later + # this could be changed to start with a randomly + # generated (potential) BSGS, and then new elements + # would have to be appended to it when `success` + # is false. + success, new_rels = K_s._verify(K, phi, z, alpha) + else: + # K.orbit(alpha) should be a block + # under the action of K_s on K_s.orbit(alpha) + check, block = K_s._block_verify(K, alpha) + if check: + # apply _verify to the action of K_s + # on the block system; for convenience, + # add the blocks as additional points + # that K_s should act on + t = block_homomorphism(K_s, block) + m = t.codomain.degree # number of blocks + d = K_s.degree + + # conjugating with p will shift + # permutations in t.image() to + # higher numbers, e.g. + # p*(0 1)*p = (m m+1) + p = Permutation() + for i in range(m): + p *= Permutation(i, i+d) + + t_img = t.images + # combine generators of K_s with their + # action on the block system + images = {g: g*p*t_img[g]*p for g in t_img} + for g in self.strong_gens[:-len(K_s.generators)]: + images[g] = g + K_s_act = PermutationGroup(list(images.values())) + f = GroupHomomorphism(self, K_s_act, images) + + K_act = PermutationGroup([f(g) for g in K.generators]) + success, new_rels = K_s_act._verify(K_act, f.compose(phi), f(z), d) + + for n in new_rels: + if n not in rels: + rels.append(n) + K = K_s + + group = FpGroup(F, rels) + return simplify_presentation(group) + + def presentation(self, eliminate_gens=True): + ''' + Return an `FpGroup` presentation of the group. + + The algorithm is described in [1], Chapter 6.1. + + ''' + from sympy.combinatorics.fp_groups import (FpGroup, + simplify_presentation) + from sympy.combinatorics.coset_table import CosetTable + from sympy.combinatorics.free_groups import free_group + from sympy.combinatorics.homomorphisms import homomorphism + + if self._fp_presentation: + return self._fp_presentation + + def _factor_group_by_rels(G, rels): + if isinstance(G, FpGroup): + rels.extend(G.relators) + return FpGroup(G.free_group, list(set(rels))) + return FpGroup(G, rels) + + gens = self.generators + len_g = len(gens) + + if len_g == 1: + order = gens[0].order() + # handle the trivial group + if order == 1: + return free_group([])[0] + F, x = free_group('x') + return FpGroup(F, [x**order]) + + if self.order() > 20: + half_gens = self.generators[0:(len_g+1)//2] + else: + half_gens = [] + H = PermutationGroup(half_gens) + H_p = H.presentation() + + len_h = len(H_p.generators) + + C = self.coset_table(H) + n = len(C) # subgroup index + + gen_syms = [('x_%d'%i) for i in range(len(gens))] + F = free_group(', '.join(gen_syms))[0] + + # mapping generators of H_p to those of F + images = [F.generators[i] for i in range(len_h)] + R = homomorphism(H_p, F, H_p.generators, images, check=False) + + # rewrite relators + rels = R(H_p.relators) + G_p = FpGroup(F, rels) + + # injective homomorphism from G_p into self + T = homomorphism(G_p, self, G_p.generators, gens) + + C_p = CosetTable(G_p, []) + + C_p.table = [[None]*(2*len_g) for i in range(n)] + + # initiate the coset transversal + transversal = [None]*n + transversal[0] = G_p.identity + + # fill in the coset table as much as possible + for i in range(2*len_h): + C_p.table[0][i] = 0 + + gamma = 1 + for alpha, x in product(range(n), range(2*len_g)): + beta = C[alpha][x] + if beta == gamma: + gen = G_p.generators[x//2]**((-1)**(x % 2)) + transversal[beta] = transversal[alpha]*gen + C_p.table[alpha][x] = beta + C_p.table[beta][x + (-1)**(x % 2)] = alpha + gamma += 1 + if gamma == n: + break + + C_p.p = list(range(n)) + beta = x = 0 + + while not C_p.is_complete(): + # find the first undefined entry + while C_p.table[beta][x] == C[beta][x]: + x = (x + 1) % (2*len_g) + if x == 0: + beta = (beta + 1) % n + + # define a new relator + gen = G_p.generators[x//2]**((-1)**(x % 2)) + new_rel = transversal[beta]*gen*transversal[C[beta][x]]**-1 + perm = T(new_rel) + nxt = G_p.identity + for s in H.generator_product(perm, original=True): + nxt = nxt*T.invert(s)**-1 + new_rel = new_rel*nxt + + # continue coset enumeration + G_p = _factor_group_by_rels(G_p, [new_rel]) + C_p.scan_and_fill(0, new_rel) + C_p = G_p.coset_enumeration([], strategy="coset_table", + draft=C_p, max_cosets=n, incomplete=True) + + self._fp_presentation = simplify_presentation(G_p) + return self._fp_presentation + + def polycyclic_group(self): + """ + Return the PolycyclicGroup instance with below parameters: + + Explanation + =========== + + * pc_sequence : Polycyclic sequence is formed by collecting all + the missing generators between the adjacent groups in the + derived series of given permutation group. + + * pc_series : Polycyclic series is formed by adding all the missing + generators of ``der[i+1]`` in ``der[i]``, where ``der`` represents + the derived series. + + * relative_order : A list, computed by the ratio of adjacent groups in + pc_series. + + """ + from sympy.combinatorics.pc_groups import PolycyclicGroup + if not self.is_polycyclic: + raise ValueError("The group must be solvable") + + der = self.derived_series() + pc_series = [] + pc_sequence = [] + relative_order = [] + pc_series.append(der[-1]) + der.reverse() + + for i in range(len(der)-1): + H = der[i] + for g in der[i+1].generators: + if g not in H: + H = PermutationGroup([g] + H.generators) + pc_series.insert(0, H) + pc_sequence.insert(0, g) + + G1 = pc_series[0].order() + G2 = pc_series[1].order() + relative_order.insert(0, G1 // G2) + + return PolycyclicGroup(pc_sequence, pc_series, relative_order, collector=None) + + +def _orbit(degree, generators, alpha, action='tuples'): + r"""Compute the orbit of alpha `\{g(\alpha) | g \in G\}` as a set. + + Explanation + =========== + + The time complexity of the algorithm used here is `O(|Orb|*r)` where + `|Orb|` is the size of the orbit and ``r`` is the number of generators of + the group. For a more detailed analysis, see [1], p.78, [2], pp. 19-21. + Here alpha can be a single point, or a list of points. + + If alpha is a single point, the ordinary orbit is computed. + if alpha is a list of points, there are three available options: + + 'union' - computes the union of the orbits of the points in the list + 'tuples' - computes the orbit of the list interpreted as an ordered + tuple under the group action ( i.e., g((1, 2, 3)) = (g(1), g(2), g(3)) ) + 'sets' - computes the orbit of the list interpreted as a sets + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> from sympy.combinatorics.perm_groups import _orbit + >>> a = Permutation([1, 2, 0, 4, 5, 6, 3]) + >>> G = PermutationGroup([a]) + >>> _orbit(G.degree, G.generators, 0) + {0, 1, 2} + >>> _orbit(G.degree, G.generators, [0, 4], 'union') + {0, 1, 2, 3, 4, 5, 6} + + See Also + ======== + + orbit, orbit_transversal + + """ + if not hasattr(alpha, '__getitem__'): + alpha = [alpha] + + gens = [x._array_form for x in generators] + if len(alpha) == 1 or action == 'union': + orb = alpha + used = [False]*degree + for el in alpha: + used[el] = True + for b in orb: + for gen in gens: + temp = gen[b] + if used[temp] == False: + orb.append(temp) + used[temp] = True + return set(orb) + elif action == 'tuples': + alpha = tuple(alpha) + orb = [alpha] + used = {alpha} + for b in orb: + for gen in gens: + temp = tuple([gen[x] for x in b]) + if temp not in used: + orb.append(temp) + used.add(temp) + return set(orb) + elif action == 'sets': + alpha = frozenset(alpha) + orb = [alpha] + used = {alpha} + for b in orb: + for gen in gens: + temp = frozenset([gen[x] for x in b]) + if temp not in used: + orb.append(temp) + used.add(temp) + return {tuple(x) for x in orb} + + +def _orbits(degree, generators): + """Compute the orbits of G. + + If ``rep=False`` it returns a list of sets else it returns a list of + representatives of the orbits + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy.combinatorics.perm_groups import _orbits + >>> a = Permutation([0, 2, 1]) + >>> b = Permutation([1, 0, 2]) + >>> _orbits(a.size, [a, b]) + [{0, 1, 2}] + """ + + orbs = [] + sorted_I = list(range(degree)) + I = set(sorted_I) + while I: + i = sorted_I[0] + orb = _orbit(degree, generators, i) + orbs.append(orb) + # remove all indices that are in this orbit + I -= orb + sorted_I = [i for i in sorted_I if i not in orb] + return orbs + + +def _orbit_transversal(degree, generators, alpha, pairs, af=False, slp=False): + r"""Computes a transversal for the orbit of ``alpha`` as a set. + + Explanation + =========== + + generators generators of the group ``G`` + + For a permutation group ``G``, a transversal for the orbit + `Orb = \{g(\alpha) | g \in G\}` is a set + `\{g_\beta | g_\beta(\alpha) = \beta\}` for `\beta \in Orb`. + Note that there may be more than one possible transversal. + If ``pairs`` is set to ``True``, it returns the list of pairs + `(\beta, g_\beta)`. For a proof of correctness, see [1], p.79 + + if ``af`` is ``True``, the transversal elements are given in + array form. + + If `slp` is `True`, a dictionary `{beta: slp_beta}` is returned + for `\beta \in Orb` where `slp_beta` is a list of indices of the + generators in `generators` s.t. if `slp_beta = [i_1 \dots i_n]` + `g_\beta = generators[i_n] \times \dots \times generators[i_1]`. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> from sympy.combinatorics.perm_groups import _orbit_transversal + >>> G = DihedralGroup(6) + >>> _orbit_transversal(G.degree, G.generators, 0, False) + [(5), (0 1 2 3 4 5), (0 5)(1 4)(2 3), (0 2 4)(1 3 5), (5)(0 4)(1 3), (0 3)(1 4)(2 5)] + """ + + tr = [(alpha, list(range(degree)))] + slp_dict = {alpha: []} + used = [False]*degree + used[alpha] = True + gens = [x._array_form for x in generators] + for x, px in tr: + px_slp = slp_dict[x] + for gen in gens: + temp = gen[x] + if used[temp] == False: + slp_dict[temp] = [gens.index(gen)] + px_slp + tr.append((temp, _af_rmul(gen, px))) + used[temp] = True + if pairs: + if not af: + tr = [(x, _af_new(y)) for x, y in tr] + if not slp: + return tr + return tr, slp_dict + + if af: + tr = [y for _, y in tr] + if not slp: + return tr + return tr, slp_dict + + tr = [_af_new(y) for _, y in tr] + if not slp: + return tr + return tr, slp_dict + + +def _stabilizer(degree, generators, alpha): + r"""Return the stabilizer subgroup of ``alpha``. + + Explanation + =========== + + The stabilizer of `\alpha` is the group `G_\alpha = + \{g \in G | g(\alpha) = \alpha\}`. + For a proof of correctness, see [1], p.79. + + degree : degree of G + generators : generators of G + + Examples + ======== + + >>> from sympy.combinatorics.perm_groups import _stabilizer + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> G = DihedralGroup(6) + >>> _stabilizer(G.degree, G.generators, 5) + [(5)(0 4)(1 3), (5)] + + See Also + ======== + + orbit + + """ + orb = [alpha] + table = {alpha: list(range(degree))} + table_inv = {alpha: list(range(degree))} + used = [False]*degree + used[alpha] = True + gens = [x._array_form for x in generators] + stab_gens = [] + for b in orb: + for gen in gens: + temp = gen[b] + if used[temp] is False: + gen_temp = _af_rmul(gen, table[b]) + orb.append(temp) + table[temp] = gen_temp + table_inv[temp] = _af_invert(gen_temp) + used[temp] = True + else: + schreier_gen = _af_rmuln(table_inv[temp], gen, table[b]) + if schreier_gen not in stab_gens: + stab_gens.append(schreier_gen) + return [_af_new(x) for x in stab_gens] + + +PermGroup = PermutationGroup + + +class SymmetricPermutationGroup(Basic): + """ + The class defining the lazy form of SymmetricGroup. + + deg : int + + """ + def __new__(cls, deg): + deg = _sympify(deg) + obj = Basic.__new__(cls, deg) + return obj + + def __init__(self, *args, **kwargs): + self._deg = self.args[0] + self._order = None + + def __contains__(self, i): + """Return ``True`` if *i* is contained in SymmetricPermutationGroup. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, SymmetricPermutationGroup + >>> G = SymmetricPermutationGroup(4) + >>> Permutation(1, 2, 3) in G + True + + """ + if not isinstance(i, Permutation): + raise TypeError("A SymmetricPermutationGroup contains only Permutations as " + "elements, not elements of type %s" % type(i)) + return i.size == self.degree + + def order(self): + """ + Return the order of the SymmetricPermutationGroup. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricPermutationGroup + >>> G = SymmetricPermutationGroup(4) + >>> G.order() + 24 + """ + if self._order is not None: + return self._order + n = self._deg + self._order = factorial(n) + return self._order + + @property + def degree(self): + """ + Return the degree of the SymmetricPermutationGroup. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricPermutationGroup + >>> G = SymmetricPermutationGroup(4) + >>> G.degree + 4 + + """ + return self._deg + + @property + def identity(self): + ''' + Return the identity element of the SymmetricPermutationGroup. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricPermutationGroup + >>> G = SymmetricPermutationGroup(4) + >>> G.identity() + (3) + + ''' + return _af_new(list(range(self._deg))) + + +class Coset(Basic): + """A left coset of a permutation group with respect to an element. + + Parameters + ========== + + g : Permutation + + H : PermutationGroup + + dir : "+" or "-", If not specified by default it will be "+" + here ``dir`` specified the type of coset "+" represent the + right coset and "-" represent the left coset. + + G : PermutationGroup, optional + The group which contains *H* as its subgroup and *g* as its + element. + + If not specified, it would automatically become a symmetric + group ``SymmetricPermutationGroup(g.size)`` and + ``SymmetricPermutationGroup(H.degree)`` if ``g.size`` and ``H.degree`` + are matching.``SymmetricPermutationGroup`` is a lazy form of SymmetricGroup + used for representation purpose. + + """ + + def __new__(cls, g, H, G=None, dir="+"): + g = _sympify(g) + if not isinstance(g, Permutation): + raise NotImplementedError + + H = _sympify(H) + if not isinstance(H, PermutationGroup): + raise NotImplementedError + + if G is not None: + G = _sympify(G) + if not isinstance(G, (PermutationGroup, SymmetricPermutationGroup)): + raise NotImplementedError + if not H.is_subgroup(G): + raise ValueError("{} must be a subgroup of {}.".format(H, G)) + if g not in G: + raise ValueError("{} must be an element of {}.".format(g, G)) + else: + g_size = g.size + h_degree = H.degree + if g_size != h_degree: + raise ValueError( + "The size of the permutation {} and the degree of " + "the permutation group {} should be matching " + .format(g, H)) + G = SymmetricPermutationGroup(g.size) + + if isinstance(dir, str): + dir = Symbol(dir) + elif not isinstance(dir, Symbol): + raise TypeError("dir must be of type basestring or " + "Symbol, not %s" % type(dir)) + if str(dir) not in ('+', '-'): + raise ValueError("dir must be one of '+' or '-' not %s" % dir) + obj = Basic.__new__(cls, g, H, G, dir) + return obj + + def __init__(self, *args, **kwargs): + self._dir = self.args[3] + + @property + def is_left_coset(self): + """ + Check if the coset is left coset that is ``gH``. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup, Coset + >>> a = Permutation(1, 2) + >>> b = Permutation(0, 1) + >>> G = PermutationGroup([a, b]) + >>> cst = Coset(a, G, dir="-") + >>> cst.is_left_coset + True + + """ + return str(self._dir) == '-' + + @property + def is_right_coset(self): + """ + Check if the coset is right coset that is ``Hg``. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, PermutationGroup, Coset + >>> a = Permutation(1, 2) + >>> b = Permutation(0, 1) + >>> G = PermutationGroup([a, b]) + >>> cst = Coset(a, G, dir="+") + >>> cst.is_right_coset + True + + """ + return str(self._dir) == '+' + + def as_list(self): + """ + Return all the elements of coset in the form of list. + """ + g = self.args[0] + H = self.args[1] + cst = [] + if str(self._dir) == '+': + for h in H.elements: + cst.append(h*g) + else: + for h in H.elements: + cst.append(g*h) + return cst diff --git a/lib/python3.12/site-packages/sympy/combinatorics/permutations.py b/lib/python3.12/site-packages/sympy/combinatorics/permutations.py new file mode 100644 index 0000000000000000000000000000000000000000..21914003b2b95cb3f9f1232a9f0dc012aac0b789 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/permutations.py @@ -0,0 +1,3115 @@ +import random +from collections import defaultdict +from collections.abc import Iterable +from functools import reduce + +from sympy.core.parameters import global_parameters +from sympy.core.basic import Atom +from sympy.core.expr import Expr +from sympy.core.numbers import int_valued +from sympy.core.numbers import Integer +from sympy.core.sympify import _sympify +from sympy.matrices import zeros +from sympy.polys.polytools import lcm +from sympy.printing.repr import srepr +from sympy.utilities.iterables import (flatten, has_variety, minlex, + has_dups, runs, is_sequence) +from sympy.utilities.misc import as_int +from mpmath.libmp.libintmath import ifac +from sympy.multipledispatch import dispatch + +def _af_rmul(a, b): + """ + Return the product b*a; input and output are array forms. The ith value + is a[b[i]]. + + Examples + ======== + + >>> from sympy.combinatorics.permutations import _af_rmul, Permutation + + >>> a, b = [1, 0, 2], [0, 2, 1] + >>> _af_rmul(a, b) + [1, 2, 0] + >>> [a[b[i]] for i in range(3)] + [1, 2, 0] + + This handles the operands in reverse order compared to the ``*`` operator: + + >>> a = Permutation(a) + >>> b = Permutation(b) + >>> list(a*b) + [2, 0, 1] + >>> [b(a(i)) for i in range(3)] + [2, 0, 1] + + See Also + ======== + + rmul, _af_rmuln + """ + return [a[i] for i in b] + + +def _af_rmuln(*abc): + """ + Given [a, b, c, ...] return the product of ...*c*b*a using array forms. + The ith value is a[b[c[i]]]. + + Examples + ======== + + >>> from sympy.combinatorics.permutations import _af_rmul, Permutation + + >>> a, b = [1, 0, 2], [0, 2, 1] + >>> _af_rmul(a, b) + [1, 2, 0] + >>> [a[b[i]] for i in range(3)] + [1, 2, 0] + + This handles the operands in reverse order compared to the ``*`` operator: + + >>> a = Permutation(a); b = Permutation(b) + >>> list(a*b) + [2, 0, 1] + >>> [b(a(i)) for i in range(3)] + [2, 0, 1] + + See Also + ======== + + rmul, _af_rmul + """ + a = abc + m = len(a) + if m == 3: + p0, p1, p2 = a + return [p0[p1[i]] for i in p2] + if m == 4: + p0, p1, p2, p3 = a + return [p0[p1[p2[i]]] for i in p3] + if m == 5: + p0, p1, p2, p3, p4 = a + return [p0[p1[p2[p3[i]]]] for i in p4] + if m == 6: + p0, p1, p2, p3, p4, p5 = a + return [p0[p1[p2[p3[p4[i]]]]] for i in p5] + if m == 7: + p0, p1, p2, p3, p4, p5, p6 = a + return [p0[p1[p2[p3[p4[p5[i]]]]]] for i in p6] + if m == 8: + p0, p1, p2, p3, p4, p5, p6, p7 = a + return [p0[p1[p2[p3[p4[p5[p6[i]]]]]]] for i in p7] + if m == 1: + return a[0][:] + if m == 2: + a, b = a + return [a[i] for i in b] + if m == 0: + raise ValueError("String must not be empty") + p0 = _af_rmuln(*a[:m//2]) + p1 = _af_rmuln(*a[m//2:]) + return [p0[i] for i in p1] + + +def _af_parity(pi): + """ + Computes the parity of a permutation in array form. + + Explanation + =========== + + The parity of a permutation reflects the parity of the + number of inversions in the permutation, i.e., the + number of pairs of x and y such that x > y but p[x] < p[y]. + + Examples + ======== + + >>> from sympy.combinatorics.permutations import _af_parity + >>> _af_parity([0, 1, 2, 3]) + 0 + >>> _af_parity([3, 2, 0, 1]) + 1 + + See Also + ======== + + Permutation + """ + n = len(pi) + a = [0] * n + c = 0 + for j in range(n): + if a[j] == 0: + c += 1 + a[j] = 1 + i = j + while pi[i] != j: + i = pi[i] + a[i] = 1 + return (n - c) % 2 + + +def _af_invert(a): + """ + Finds the inverse, ~A, of a permutation, A, given in array form. + + Examples + ======== + + >>> from sympy.combinatorics.permutations import _af_invert, _af_rmul + >>> A = [1, 2, 0, 3] + >>> _af_invert(A) + [2, 0, 1, 3] + >>> _af_rmul(_, A) + [0, 1, 2, 3] + + See Also + ======== + + Permutation, __invert__ + """ + inv_form = [0] * len(a) + for i, ai in enumerate(a): + inv_form[ai] = i + return inv_form + + +def _af_pow(a, n): + """ + Routine for finding powers of a permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy.combinatorics.permutations import _af_pow + >>> p = Permutation([2, 0, 3, 1]) + >>> p.order() + 4 + >>> _af_pow(p._array_form, 4) + [0, 1, 2, 3] + """ + if n == 0: + return list(range(len(a))) + if n < 0: + return _af_pow(_af_invert(a), -n) + if n == 1: + return a[:] + elif n == 2: + b = [a[i] for i in a] + elif n == 3: + b = [a[a[i]] for i in a] + elif n == 4: + b = [a[a[a[i]]] for i in a] + else: + # use binary multiplication + b = list(range(len(a))) + while 1: + if n & 1: + b = [b[i] for i in a] + n -= 1 + if not n: + break + if n % 4 == 0: + a = [a[a[a[i]]] for i in a] + n = n // 4 + elif n % 2 == 0: + a = [a[i] for i in a] + n = n // 2 + return b + + +def _af_commutes_with(a, b): + """ + Checks if the two permutations with array forms + given by ``a`` and ``b`` commute. + + Examples + ======== + + >>> from sympy.combinatorics.permutations import _af_commutes_with + >>> _af_commutes_with([1, 2, 0], [0, 2, 1]) + False + + See Also + ======== + + Permutation, commutes_with + """ + return not any(a[b[i]] != b[a[i]] for i in range(len(a) - 1)) + + +class Cycle(dict): + """ + Wrapper around dict which provides the functionality of a disjoint cycle. + + Explanation + =========== + + A cycle shows the rule to use to move subsets of elements to obtain + a permutation. The Cycle class is more flexible than Permutation in + that 1) all elements need not be present in order to investigate how + multiple cycles act in sequence and 2) it can contain singletons: + + >>> from sympy.combinatorics.permutations import Perm, Cycle + + A Cycle will automatically parse a cycle given as a tuple on the rhs: + + >>> Cycle(1, 2)(2, 3) + (1 3 2) + + The identity cycle, Cycle(), can be used to start a product: + + >>> Cycle()(1, 2)(2, 3) + (1 3 2) + + The array form of a Cycle can be obtained by calling the list + method (or passing it to the list function) and all elements from + 0 will be shown: + + >>> a = Cycle(1, 2) + >>> a.list() + [0, 2, 1] + >>> list(a) + [0, 2, 1] + + If a larger (or smaller) range is desired use the list method and + provide the desired size -- but the Cycle cannot be truncated to + a size smaller than the largest element that is out of place: + + >>> b = Cycle(2, 4)(1, 2)(3, 1, 4)(1, 3) + >>> b.list() + [0, 2, 1, 3, 4] + >>> b.list(b.size + 1) + [0, 2, 1, 3, 4, 5] + >>> b.list(-1) + [0, 2, 1] + + Singletons are not shown when printing with one exception: the largest + element is always shown -- as a singleton if necessary: + + >>> Cycle(1, 4, 10)(4, 5) + (1 5 4 10) + >>> Cycle(1, 2)(4)(5)(10) + (1 2)(10) + + The array form can be used to instantiate a Permutation so other + properties of the permutation can be investigated: + + >>> Perm(Cycle(1, 2)(3, 4).list()).transpositions() + [(1, 2), (3, 4)] + + Notes + ===== + + The underlying structure of the Cycle is a dictionary and although + the __iter__ method has been redefined to give the array form of the + cycle, the underlying dictionary items are still available with the + such methods as items(): + + >>> list(Cycle(1, 2).items()) + [(1, 2), (2, 1)] + + See Also + ======== + + Permutation + """ + def __missing__(self, arg): + """Enter arg into dictionary and return arg.""" + return as_int(arg) + + def __iter__(self): + yield from self.list() + + def __call__(self, *other): + """Return product of cycles processed from R to L. + + Examples + ======== + + >>> from sympy.combinatorics import Cycle + >>> Cycle(1, 2)(2, 3) + (1 3 2) + + An instance of a Cycle will automatically parse list-like + objects and Permutations that are on the right. It is more + flexible than the Permutation in that all elements need not + be present: + + >>> a = Cycle(1, 2) + >>> a(2, 3) + (1 3 2) + >>> a(2, 3)(4, 5) + (1 3 2)(4 5) + + """ + rv = Cycle(*other) + for k, v in zip(list(self.keys()), [rv[self[k]] for k in self.keys()]): + rv[k] = v + return rv + + def list(self, size=None): + """Return the cycles as an explicit list starting from 0 up + to the greater of the largest value in the cycles and size. + + Truncation of trailing unmoved items will occur when size + is less than the maximum element in the cycle; if this is + desired, setting ``size=-1`` will guarantee such trimming. + + Examples + ======== + + >>> from sympy.combinatorics import Cycle + >>> p = Cycle(2, 3)(4, 5) + >>> p.list() + [0, 1, 3, 2, 5, 4] + >>> p.list(10) + [0, 1, 3, 2, 5, 4, 6, 7, 8, 9] + + Passing a length too small will trim trailing, unchanged elements + in the permutation: + + >>> Cycle(2, 4)(1, 2, 4).list(-1) + [0, 2, 1] + """ + if not self and size is None: + raise ValueError('must give size for empty Cycle') + if size is not None: + big = max([i for i in self.keys() if self[i] != i] + [0]) + size = max(size, big + 1) + else: + size = self.size + return [self[i] for i in range(size)] + + def __repr__(self): + """We want it to print as a Cycle, not as a dict. + + Examples + ======== + + >>> from sympy.combinatorics import Cycle + >>> Cycle(1, 2) + (1 2) + >>> print(_) + (1 2) + >>> list(Cycle(1, 2).items()) + [(1, 2), (2, 1)] + """ + if not self: + return 'Cycle()' + cycles = Permutation(self).cyclic_form + s = ''.join(str(tuple(c)) for c in cycles) + big = self.size - 1 + if not any(i == big for c in cycles for i in c): + s += '(%s)' % big + return 'Cycle%s' % s + + def __str__(self): + """We want it to be printed in a Cycle notation with no + comma in-between. + + Examples + ======== + + >>> from sympy.combinatorics import Cycle + >>> Cycle(1, 2) + (1 2) + >>> Cycle(1, 2, 4)(5, 6) + (1 2 4)(5 6) + """ + if not self: + return '()' + cycles = Permutation(self).cyclic_form + s = ''.join(str(tuple(c)) for c in cycles) + big = self.size - 1 + if not any(i == big for c in cycles for i in c): + s += '(%s)' % big + s = s.replace(',', '') + return s + + def __init__(self, *args): + """Load up a Cycle instance with the values for the cycle. + + Examples + ======== + + >>> from sympy.combinatorics import Cycle + >>> Cycle(1, 2, 6) + (1 2 6) + """ + + if not args: + return + if len(args) == 1: + if isinstance(args[0], Permutation): + for c in args[0].cyclic_form: + self.update(self(*c)) + return + elif isinstance(args[0], Cycle): + for k, v in args[0].items(): + self[k] = v + return + args = [as_int(a) for a in args] + if any(i < 0 for i in args): + raise ValueError('negative integers are not allowed in a cycle.') + if has_dups(args): + raise ValueError('All elements must be unique in a cycle.') + for i in range(-len(args), 0): + self[args[i]] = args[i + 1] + + @property + def size(self): + if not self: + return 0 + return max(self.keys()) + 1 + + def copy(self): + return Cycle(self) + + +class Permutation(Atom): + r""" + A permutation, alternatively known as an 'arrangement number' or 'ordering' + is an arrangement of the elements of an ordered list into a one-to-one + mapping with itself. The permutation of a given arrangement is given by + indicating the positions of the elements after re-arrangement [2]_. For + example, if one started with elements ``[x, y, a, b]`` (in that order) and + they were reordered as ``[x, y, b, a]`` then the permutation would be + ``[0, 1, 3, 2]``. Notice that (in SymPy) the first element is always referred + to as 0 and the permutation uses the indices of the elements in the + original ordering, not the elements ``(a, b, ...)`` themselves. + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + + Permutations Notation + ===================== + + Permutations are commonly represented in disjoint cycle or array forms. + + Array Notation and 2-line Form + ------------------------------------ + + In the 2-line form, the elements and their final positions are shown + as a matrix with 2 rows: + + [0 1 2 ... n-1] + [p(0) p(1) p(2) ... p(n-1)] + + Since the first line is always ``range(n)``, where n is the size of p, + it is sufficient to represent the permutation by the second line, + referred to as the "array form" of the permutation. This is entered + in brackets as the argument to the Permutation class: + + >>> p = Permutation([0, 2, 1]); p + Permutation([0, 2, 1]) + + Given i in range(p.size), the permutation maps i to i^p + + >>> [i^p for i in range(p.size)] + [0, 2, 1] + + The composite of two permutations p*q means first apply p, then q, so + i^(p*q) = (i^p)^q which is i^p^q according to Python precedence rules: + + >>> q = Permutation([2, 1, 0]) + >>> [i^p^q for i in range(3)] + [2, 0, 1] + >>> [i^(p*q) for i in range(3)] + [2, 0, 1] + + One can use also the notation p(i) = i^p, but then the composition + rule is (p*q)(i) = q(p(i)), not p(q(i)): + + >>> [(p*q)(i) for i in range(p.size)] + [2, 0, 1] + >>> [q(p(i)) for i in range(p.size)] + [2, 0, 1] + >>> [p(q(i)) for i in range(p.size)] + [1, 2, 0] + + Disjoint Cycle Notation + ----------------------- + + In disjoint cycle notation, only the elements that have shifted are + indicated. + + For example, [1, 3, 2, 0] can be represented as (0, 1, 3)(2). + This can be understood from the 2 line format of the given permutation. + In the 2-line form, + [0 1 2 3] + [1 3 2 0] + + The element in the 0th position is 1, so 0 -> 1. The element in the 1st + position is three, so 1 -> 3. And the element in the third position is again + 0, so 3 -> 0. Thus, 0 -> 1 -> 3 -> 0, and 2 -> 2. Thus, this can be represented + as 2 cycles: (0, 1, 3)(2). + In common notation, singular cycles are not explicitly written as they can be + inferred implicitly. + + Only the relative ordering of elements in a cycle matter: + + >>> Permutation(1,2,3) == Permutation(2,3,1) == Permutation(3,1,2) + True + + The disjoint cycle notation is convenient when representing + permutations that have several cycles in them: + + >>> Permutation(1, 2)(3, 5) == Permutation([[1, 2], [3, 5]]) + True + + It also provides some economy in entry when computing products of + permutations that are written in disjoint cycle notation: + + >>> Permutation(1, 2)(1, 3)(2, 3) + Permutation([0, 3, 2, 1]) + >>> _ == Permutation([[1, 2]])*Permutation([[1, 3]])*Permutation([[2, 3]]) + True + + Caution: when the cycles have common elements between them then the order + in which the permutations are applied matters. This module applies + the permutations from *left to right*. + + >>> Permutation(1, 2)(2, 3) == Permutation([(1, 2), (2, 3)]) + True + >>> Permutation(1, 2)(2, 3).list() + [0, 3, 1, 2] + + In the above case, (1,2) is computed before (2,3). + As 0 -> 0, 0 -> 0, element in position 0 is 0. + As 1 -> 2, 2 -> 3, element in position 1 is 3. + As 2 -> 1, 1 -> 1, element in position 2 is 1. + As 3 -> 3, 3 -> 2, element in position 3 is 2. + + If the first and second elements had been + swapped first, followed by the swapping of the second + and third, the result would have been [0, 2, 3, 1]. + If, you want to apply the cycles in the conventional + right to left order, call the function with arguments in reverse order + as demonstrated below: + + >>> Permutation([(1, 2), (2, 3)][::-1]).list() + [0, 2, 3, 1] + + Entering a singleton in a permutation is a way to indicate the size of the + permutation. The ``size`` keyword can also be used. + + Array-form entry: + + >>> Permutation([[1, 2], [9]]) + Permutation([0, 2, 1], size=10) + >>> Permutation([[1, 2]], size=10) + Permutation([0, 2, 1], size=10) + + Cyclic-form entry: + + >>> Permutation(1, 2, size=10) + Permutation([0, 2, 1], size=10) + >>> Permutation(9)(1, 2) + Permutation([0, 2, 1], size=10) + + Caution: no singleton containing an element larger than the largest + in any previous cycle can be entered. This is an important difference + in how Permutation and Cycle handle the ``__call__`` syntax. A singleton + argument at the start of a Permutation performs instantiation of the + Permutation and is permitted: + + >>> Permutation(5) + Permutation([], size=6) + + A singleton entered after instantiation is a call to the permutation + -- a function call -- and if the argument is out of range it will + trigger an error. For this reason, it is better to start the cycle + with the singleton: + + The following fails because there is no element 3: + + >>> Permutation(1, 2)(3) + Traceback (most recent call last): + ... + IndexError: list index out of range + + This is ok: only the call to an out of range singleton is prohibited; + otherwise the permutation autosizes: + + >>> Permutation(3)(1, 2) + Permutation([0, 2, 1, 3]) + >>> Permutation(1, 2)(3, 4) == Permutation(3, 4)(1, 2) + True + + + Equality testing + ---------------- + + The array forms must be the same in order for permutations to be equal: + + >>> Permutation([1, 0, 2, 3]) == Permutation([1, 0]) + False + + + Identity Permutation + -------------------- + + The identity permutation is a permutation in which no element is out of + place. It can be entered in a variety of ways. All the following create + an identity permutation of size 4: + + >>> I = Permutation([0, 1, 2, 3]) + >>> all(p == I for p in [ + ... Permutation(3), + ... Permutation(range(4)), + ... Permutation([], size=4), + ... Permutation(size=4)]) + True + + Watch out for entering the range *inside* a set of brackets (which is + cycle notation): + + >>> I == Permutation([range(4)]) + False + + + Permutation Printing + ==================== + + There are a few things to note about how Permutations are printed. + + .. deprecated:: 1.6 + + Configuring Permutation printing by setting + ``Permutation.print_cyclic`` is deprecated. Users should use the + ``perm_cyclic`` flag to the printers, as described below. + + 1) If you prefer one form (array or cycle) over another, you can set + ``init_printing`` with the ``perm_cyclic`` flag. + + >>> from sympy import init_printing + >>> p = Permutation(1, 2)(4, 5)(3, 4) + >>> p + Permutation([0, 2, 1, 4, 5, 3]) + + >>> init_printing(perm_cyclic=True, pretty_print=False) + >>> p + (1 2)(3 4 5) + + 2) Regardless of the setting, a list of elements in the array for cyclic + form can be obtained and either of those can be copied and supplied as + the argument to Permutation: + + >>> p.array_form + [0, 2, 1, 4, 5, 3] + >>> p.cyclic_form + [[1, 2], [3, 4, 5]] + >>> Permutation(_) == p + True + + 3) Printing is economical in that as little as possible is printed while + retaining all information about the size of the permutation: + + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> Permutation([1, 0, 2, 3]) + Permutation([1, 0, 2, 3]) + >>> Permutation([1, 0, 2, 3], size=20) + Permutation([1, 0], size=20) + >>> Permutation([1, 0, 2, 4, 3, 5, 6], size=20) + Permutation([1, 0, 2, 4, 3], size=20) + + >>> p = Permutation([1, 0, 2, 3]) + >>> init_printing(perm_cyclic=True, pretty_print=False) + >>> p + (3)(0 1) + >>> init_printing(perm_cyclic=False, pretty_print=False) + + The 2 was not printed but it is still there as can be seen with the + array_form and size methods: + + >>> p.array_form + [1, 0, 2, 3] + >>> p.size + 4 + + Short introduction to other methods + =================================== + + The permutation can act as a bijective function, telling what element is + located at a given position + + >>> q = Permutation([5, 2, 3, 4, 1, 0]) + >>> q.array_form[1] # the hard way + 2 + >>> q(1) # the easy way + 2 + >>> {i: q(i) for i in range(q.size)} # showing the bijection + {0: 5, 1: 2, 2: 3, 3: 4, 4: 1, 5: 0} + + The full cyclic form (including singletons) can be obtained: + + >>> p.full_cyclic_form + [[0, 1], [2], [3]] + + Any permutation can be factored into transpositions of pairs of elements: + + >>> Permutation([[1, 2], [3, 4, 5]]).transpositions() + [(1, 2), (3, 5), (3, 4)] + >>> Permutation.rmul(*[Permutation([ti], size=6) for ti in _]).cyclic_form + [[1, 2], [3, 4, 5]] + + The number of permutations on a set of n elements is given by n! and is + called the cardinality. + + >>> p.size + 4 + >>> p.cardinality + 24 + + A given permutation has a rank among all the possible permutations of the + same elements, but what that rank is depends on how the permutations are + enumerated. (There are a number of different methods of doing so.) The + lexicographic rank is given by the rank method and this rank is used to + increment a permutation with addition/subtraction: + + >>> p.rank() + 6 + >>> p + 1 + Permutation([1, 0, 3, 2]) + >>> p.next_lex() + Permutation([1, 0, 3, 2]) + >>> _.rank() + 7 + >>> p.unrank_lex(p.size, rank=7) + Permutation([1, 0, 3, 2]) + + The product of two permutations p and q is defined as their composition as + functions, (p*q)(i) = q(p(i)) [6]_. + + >>> p = Permutation([1, 0, 2, 3]) + >>> q = Permutation([2, 3, 1, 0]) + >>> list(q*p) + [2, 3, 0, 1] + >>> list(p*q) + [3, 2, 1, 0] + >>> [q(p(i)) for i in range(p.size)] + [3, 2, 1, 0] + + The permutation can be 'applied' to any list-like object, not only + Permutations: + + >>> p(['zero', 'one', 'four', 'two']) + ['one', 'zero', 'four', 'two'] + >>> p('zo42') + ['o', 'z', '4', '2'] + + If you have a list of arbitrary elements, the corresponding permutation + can be found with the from_sequence method: + + >>> Permutation.from_sequence('SymPy') + Permutation([1, 3, 2, 0, 4]) + + Checking if a Permutation is contained in a Group + ================================================= + + Generally if you have a group of permutations G on n symbols, and + you're checking if a permutation on less than n symbols is part + of that group, the check will fail. + + Here is an example for n=5 and we check if the cycle + (1,2,3) is in G: + + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=True, pretty_print=False) + >>> from sympy.combinatorics import Cycle, Permutation + >>> from sympy.combinatorics.perm_groups import PermutationGroup + >>> G = PermutationGroup(Cycle(2, 3)(4, 5), Cycle(1, 2, 3, 4, 5)) + >>> p1 = Permutation(Cycle(2, 5, 3)) + >>> p2 = Permutation(Cycle(1, 2, 3)) + >>> a1 = Permutation(Cycle(1, 2, 3).list(6)) + >>> a2 = Permutation(Cycle(1, 2, 3)(5)) + >>> a3 = Permutation(Cycle(1, 2, 3),size=6) + >>> for p in [p1,p2,a1,a2,a3]: p, G.contains(p) + ((2 5 3), True) + ((1 2 3), False) + ((5)(1 2 3), True) + ((5)(1 2 3), True) + ((5)(1 2 3), True) + + The check for p2 above will fail. + + Checking if p1 is in G works because SymPy knows + G is a group on 5 symbols, and p1 is also on 5 symbols + (its largest element is 5). + + For ``a1``, the ``.list(6)`` call will extend the permutation to 5 + symbols, so the test will work as well. In the case of ``a2`` the + permutation is being extended to 5 symbols by using a singleton, + and in the case of ``a3`` it's extended through the constructor + argument ``size=6``. + + There is another way to do this, which is to tell the ``contains`` + method that the number of symbols the group is on does not need to + match perfectly the number of symbols for the permutation: + + >>> G.contains(p2,strict=False) + True + + This can be via the ``strict`` argument to the ``contains`` method, + and SymPy will try to extend the permutation on its own and then + perform the containment check. + + See Also + ======== + + Cycle + + References + ========== + + .. [1] Skiena, S. 'Permutations.' 1.1 in Implementing Discrete Mathematics + Combinatorics and Graph Theory with Mathematica. Reading, MA: + Addison-Wesley, pp. 3-16, 1990. + + .. [2] Knuth, D. E. The Art of Computer Programming, Vol. 4: Combinatorial + Algorithms, 1st ed. Reading, MA: Addison-Wesley, 2011. + + .. [3] Wendy Myrvold and Frank Ruskey. 2001. Ranking and unranking + permutations in linear time. Inf. Process. Lett. 79, 6 (September 2001), + 281-284. DOI=10.1016/S0020-0190(01)00141-7 + + .. [4] D. L. Kreher, D. R. Stinson 'Combinatorial Algorithms' + CRC Press, 1999 + + .. [5] Graham, R. L.; Knuth, D. E.; and Patashnik, O. + Concrete Mathematics: A Foundation for Computer Science, 2nd ed. + Reading, MA: Addison-Wesley, 1994. + + .. [6] https://en.wikipedia.org/w/index.php?oldid=499948155#Product_and_inverse + + .. [7] https://en.wikipedia.org/wiki/Lehmer_code + + """ + + is_Permutation = True + + _array_form = None + _cyclic_form = None + _cycle_structure = None + _size = None + _rank = None + + def __new__(cls, *args, size=None, **kwargs): + """ + Constructor for the Permutation object from a list or a + list of lists in which all elements of the permutation may + appear only once. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + + Permutations entered in array-form are left unaltered: + + >>> Permutation([0, 2, 1]) + Permutation([0, 2, 1]) + + Permutations entered in cyclic form are converted to array form; + singletons need not be entered, but can be entered to indicate the + largest element: + + >>> Permutation([[4, 5, 6], [0, 1]]) + Permutation([1, 0, 2, 3, 5, 6, 4]) + >>> Permutation([[4, 5, 6], [0, 1], [19]]) + Permutation([1, 0, 2, 3, 5, 6, 4], size=20) + + All manipulation of permutations assumes that the smallest element + is 0 (in keeping with 0-based indexing in Python) so if the 0 is + missing when entering a permutation in array form, an error will be + raised: + + >>> Permutation([2, 1]) + Traceback (most recent call last): + ... + ValueError: Integers 0 through 2 must be present. + + If a permutation is entered in cyclic form, it can be entered without + singletons and the ``size`` specified so those values can be filled + in, otherwise the array form will only extend to the maximum value + in the cycles: + + >>> Permutation([[1, 4], [3, 5, 2]], size=10) + Permutation([0, 4, 3, 5, 1, 2], size=10) + >>> _.array_form + [0, 4, 3, 5, 1, 2, 6, 7, 8, 9] + """ + if size is not None: + size = int(size) + + #a) () + #b) (1) = identity + #c) (1, 2) = cycle + #d) ([1, 2, 3]) = array form + #e) ([[1, 2]]) = cyclic form + #f) (Cycle) = conversion to permutation + #g) (Permutation) = adjust size or return copy + ok = True + if not args: # a + return cls._af_new(list(range(size or 0))) + elif len(args) > 1: # c + return cls._af_new(Cycle(*args).list(size)) + if len(args) == 1: + a = args[0] + if isinstance(a, cls): # g + if size is None or size == a.size: + return a + return cls(a.array_form, size=size) + if isinstance(a, Cycle): # f + return cls._af_new(a.list(size)) + if not is_sequence(a): # b + if size is not None and a + 1 > size: + raise ValueError('size is too small when max is %s' % a) + return cls._af_new(list(range(a + 1))) + if has_variety(is_sequence(ai) for ai in a): + ok = False + else: + ok = False + if not ok: + raise ValueError("Permutation argument must be a list of ints, " + "a list of lists, Permutation or Cycle.") + + # safe to assume args are valid; this also makes a copy + # of the args + args = list(args[0]) + + is_cycle = args and is_sequence(args[0]) + if is_cycle: # e + args = [[int(i) for i in c] for c in args] + else: # d + args = [int(i) for i in args] + + # if there are n elements present, 0, 1, ..., n-1 should be present + # unless a cycle notation has been provided. A 0 will be added + # for convenience in case one wants to enter permutations where + # counting starts from 1. + + temp = flatten(args) + if has_dups(temp) and not is_cycle: + raise ValueError('there were repeated elements.') + temp = set(temp) + + if not is_cycle: + if temp != set(range(len(temp))): + raise ValueError('Integers 0 through %s must be present.' % + max(temp)) + if size is not None and temp and max(temp) + 1 > size: + raise ValueError('max element should not exceed %s' % (size - 1)) + + if is_cycle: + # it's not necessarily canonical so we won't store + # it -- use the array form instead + c = Cycle() + for ci in args: + c = c(*ci) + aform = c.list() + else: + aform = list(args) + if size and size > len(aform): + # don't allow for truncation of permutation which + # might split a cycle and lead to an invalid aform + # but do allow the permutation size to be increased + aform.extend(list(range(len(aform), size))) + + return cls._af_new(aform) + + @classmethod + def _af_new(cls, perm): + """A method to produce a Permutation object from a list; + the list is bound to the _array_form attribute, so it must + not be modified; this method is meant for internal use only; + the list ``a`` is supposed to be generated as a temporary value + in a method, so p = Perm._af_new(a) is the only object + to hold a reference to ``a``:: + + Examples + ======== + + >>> from sympy.combinatorics.permutations import Perm + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> a = [2, 1, 3, 0] + >>> p = Perm._af_new(a) + >>> p + Permutation([2, 1, 3, 0]) + + """ + p = super().__new__(cls) + p._array_form = perm + p._size = len(perm) + return p + + def copy(self): + return self.__class__(self.array_form) + + def __getnewargs__(self): + return (self.array_form,) + + def _hashable_content(self): + # the array_form (a list) is the Permutation arg, so we need to + # return a tuple, instead + return tuple(self.array_form) + + @property + def array_form(self): + """ + Return a copy of the attribute _array_form + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([[2, 0], [3, 1]]) + >>> p.array_form + [2, 3, 0, 1] + >>> Permutation([[2, 0, 3, 1]]).array_form + [3, 2, 0, 1] + >>> Permutation([2, 0, 3, 1]).array_form + [2, 0, 3, 1] + >>> Permutation([[1, 2], [4, 5]]).array_form + [0, 2, 1, 3, 5, 4] + """ + return self._array_form[:] + + def list(self, size=None): + """Return the permutation as an explicit list, possibly + trimming unmoved elements if size is less than the maximum + element in the permutation; if this is desired, setting + ``size=-1`` will guarantee such trimming. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation(2, 3)(4, 5) + >>> p.list() + [0, 1, 3, 2, 5, 4] + >>> p.list(10) + [0, 1, 3, 2, 5, 4, 6, 7, 8, 9] + + Passing a length too small will trim trailing, unchanged elements + in the permutation: + + >>> Permutation(2, 4)(1, 2, 4).list(-1) + [0, 2, 1] + >>> Permutation(3).list(-1) + [] + """ + if not self and size is None: + raise ValueError('must give size for empty Cycle') + rv = self.array_form + if size is not None: + if size > self.size: + rv.extend(list(range(self.size, size))) + else: + # find first value from rhs where rv[i] != i + i = self.size - 1 + while rv: + if rv[-1] != i: + break + rv.pop() + i -= 1 + return rv + + @property + def cyclic_form(self): + """ + This is used to convert to the cyclic notation + from the canonical notation. Singletons are omitted. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 3, 1, 2]) + >>> p.cyclic_form + [[1, 3, 2]] + >>> Permutation([1, 0, 2, 4, 3, 5]).cyclic_form + [[0, 1], [3, 4]] + + See Also + ======== + + array_form, full_cyclic_form + """ + if self._cyclic_form is not None: + return list(self._cyclic_form) + array_form = self.array_form + unchecked = [True] * len(array_form) + cyclic_form = [] + for i in range(len(array_form)): + if unchecked[i]: + cycle = [] + cycle.append(i) + unchecked[i] = False + j = i + while unchecked[array_form[j]]: + j = array_form[j] + cycle.append(j) + unchecked[j] = False + if len(cycle) > 1: + cyclic_form.append(cycle) + assert cycle == list(minlex(cycle)) + cyclic_form.sort() + self._cyclic_form = cyclic_form[:] + return cyclic_form + + @property + def full_cyclic_form(self): + """Return permutation in cyclic form including singletons. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation([0, 2, 1]).full_cyclic_form + [[0], [1, 2]] + """ + need = set(range(self.size)) - set(flatten(self.cyclic_form)) + rv = self.cyclic_form + [[i] for i in need] + rv.sort() + return rv + + @property + def size(self): + """ + Returns the number of elements in the permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation([[3, 2], [0, 1]]).size + 4 + + See Also + ======== + + cardinality, length, order, rank + """ + return self._size + + def support(self): + """Return the elements in permutation, P, for which P[i] != i. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([[3, 2], [0, 1], [4]]) + >>> p.array_form + [1, 0, 3, 2, 4] + >>> p.support() + [0, 1, 2, 3] + """ + a = self.array_form + return [i for i, e in enumerate(a) if a[i] != i] + + def __add__(self, other): + """Return permutation that is other higher in rank than self. + + The rank is the lexicographical rank, with the identity permutation + having rank of 0. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> I = Permutation([0, 1, 2, 3]) + >>> a = Permutation([2, 1, 3, 0]) + >>> I + a.rank() == a + True + + See Also + ======== + + __sub__, inversion_vector + + """ + rank = (self.rank() + other) % self.cardinality + rv = self.unrank_lex(self.size, rank) + rv._rank = rank + return rv + + def __sub__(self, other): + """Return the permutation that is other lower in rank than self. + + See Also + ======== + + __add__ + """ + return self.__add__(-other) + + @staticmethod + def rmul(*args): + """ + Return product of Permutations [a, b, c, ...] as the Permutation whose + ith value is a(b(c(i))). + + a, b, c, ... can be Permutation objects or tuples. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + + >>> a, b = [1, 0, 2], [0, 2, 1] + >>> a = Permutation(a); b = Permutation(b) + >>> list(Permutation.rmul(a, b)) + [1, 2, 0] + >>> [a(b(i)) for i in range(3)] + [1, 2, 0] + + This handles the operands in reverse order compared to the ``*`` operator: + + >>> a = Permutation(a); b = Permutation(b) + >>> list(a*b) + [2, 0, 1] + >>> [b(a(i)) for i in range(3)] + [2, 0, 1] + + Notes + ===== + + All items in the sequence will be parsed by Permutation as + necessary as long as the first item is a Permutation: + + >>> Permutation.rmul(a, [0, 2, 1]) == Permutation.rmul(a, b) + True + + The reverse order of arguments will raise a TypeError. + + """ + rv = args[0] + for i in range(1, len(args)): + rv = args[i]*rv + return rv + + @classmethod + def rmul_with_af(cls, *args): + """ + same as rmul, but the elements of args are Permutation objects + which have _array_form + """ + a = [x._array_form for x in args] + rv = cls._af_new(_af_rmuln(*a)) + return rv + + def mul_inv(self, other): + """ + other*~self, self and other have _array_form + """ + a = _af_invert(self._array_form) + b = other._array_form + return self._af_new(_af_rmul(a, b)) + + def __rmul__(self, other): + """This is needed to coerce other to Permutation in rmul.""" + cls = type(self) + return cls(other)*self + + def __mul__(self, other): + """ + Return the product a*b as a Permutation; the ith value is b(a(i)). + + Examples + ======== + + >>> from sympy.combinatorics.permutations import _af_rmul, Permutation + + >>> a, b = [1, 0, 2], [0, 2, 1] + >>> a = Permutation(a); b = Permutation(b) + >>> list(a*b) + [2, 0, 1] + >>> [b(a(i)) for i in range(3)] + [2, 0, 1] + + This handles operands in reverse order compared to _af_rmul and rmul: + + >>> al = list(a); bl = list(b) + >>> _af_rmul(al, bl) + [1, 2, 0] + >>> [al[bl[i]] for i in range(3)] + [1, 2, 0] + + It is acceptable for the arrays to have different lengths; the shorter + one will be padded to match the longer one: + + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> b*Permutation([1, 0]) + Permutation([1, 2, 0]) + >>> Permutation([1, 0])*b + Permutation([2, 0, 1]) + + It is also acceptable to allow coercion to handle conversion of a + single list to the left of a Permutation: + + >>> [0, 1]*a # no change: 2-element identity + Permutation([1, 0, 2]) + >>> [[0, 1]]*a # exchange first two elements + Permutation([0, 1, 2]) + + You cannot use more than 1 cycle notation in a product of cycles + since coercion can only handle one argument to the left. To handle + multiple cycles it is convenient to use Cycle instead of Permutation: + + >>> [[1, 2]]*[[2, 3]]*Permutation([]) # doctest: +SKIP + >>> from sympy.combinatorics.permutations import Cycle + >>> Cycle(1, 2)(2, 3) + (1 3 2) + + """ + from sympy.combinatorics.perm_groups import PermutationGroup, Coset + if isinstance(other, PermutationGroup): + return Coset(self, other, dir='-') + a = self.array_form + # __rmul__ makes sure the other is a Permutation + b = other.array_form + if not b: + perm = a + else: + b.extend(list(range(len(b), len(a)))) + perm = [b[i] for i in a] + b[len(a):] + return self._af_new(perm) + + def commutes_with(self, other): + """ + Checks if the elements are commuting. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> a = Permutation([1, 4, 3, 0, 2, 5]) + >>> b = Permutation([0, 1, 2, 3, 4, 5]) + >>> a.commutes_with(b) + True + >>> b = Permutation([2, 3, 5, 4, 1, 0]) + >>> a.commutes_with(b) + False + """ + a = self.array_form + b = other.array_form + return _af_commutes_with(a, b) + + def __pow__(self, n): + """ + Routine for finding powers of a permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> p = Permutation([2, 0, 3, 1]) + >>> p.order() + 4 + >>> p**4 + Permutation([0, 1, 2, 3]) + """ + if isinstance(n, Permutation): + raise NotImplementedError( + 'p**p is not defined; do you mean p^p (conjugate)?') + n = int(n) + return self._af_new(_af_pow(self.array_form, n)) + + def __rxor__(self, i): + """Return self(i) when ``i`` is an int. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation(1, 2, 9) + >>> 2^p == p(2) == 9 + True + """ + if int_valued(i): + return self(i) + else: + raise NotImplementedError( + "i^p = p(i) when i is an integer, not %s." % i) + + def __xor__(self, h): + """Return the conjugate permutation ``~h*self*h` `. + + Explanation + =========== + + If ``a`` and ``b`` are conjugates, ``a = h*b*~h`` and + ``b = ~h*a*h`` and both have the same cycle structure. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation(1, 2, 9) + >>> q = Permutation(6, 9, 8) + >>> p*q != q*p + True + + Calculate and check properties of the conjugate: + + >>> c = p^q + >>> c == ~q*p*q and p == q*c*~q + True + + The expression q^p^r is equivalent to q^(p*r): + + >>> r = Permutation(9)(4, 6, 8) + >>> q^p^r == q^(p*r) + True + + If the term to the left of the conjugate operator, i, is an integer + then this is interpreted as selecting the ith element from the + permutation to the right: + + >>> all(i^p == p(i) for i in range(p.size)) + True + + Note that the * operator as higher precedence than the ^ operator: + + >>> q^r*p^r == q^(r*p)^r == Permutation(9)(1, 6, 4) + True + + Notes + ===== + + In Python the precedence rule is p^q^r = (p^q)^r which differs + in general from p^(q^r) + + >>> q^p^r + (9)(1 4 8) + >>> q^(p^r) + (9)(1 8 6) + + For a given r and p, both of the following are conjugates of p: + ~r*p*r and r*p*~r. But these are not necessarily the same: + + >>> ~r*p*r == r*p*~r + True + + >>> p = Permutation(1, 2, 9)(5, 6) + >>> ~r*p*r == r*p*~r + False + + The conjugate ~r*p*r was chosen so that ``p^q^r`` would be equivalent + to ``p^(q*r)`` rather than ``p^(r*q)``. To obtain r*p*~r, pass ~r to + this method: + + >>> p^~r == r*p*~r + True + """ + + if self.size != h.size: + raise ValueError("The permutations must be of equal size.") + a = [None]*self.size + h = h._array_form + p = self._array_form + for i in range(self.size): + a[h[i]] = h[p[i]] + return self._af_new(a) + + def transpositions(self): + """ + Return the permutation decomposed into a list of transpositions. + + Explanation + =========== + + It is always possible to express a permutation as the product of + transpositions, see [1] + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([[1, 2, 3], [0, 4, 5, 6, 7]]) + >>> t = p.transpositions() + >>> t + [(0, 7), (0, 6), (0, 5), (0, 4), (1, 3), (1, 2)] + >>> print(''.join(str(c) for c in t)) + (0, 7)(0, 6)(0, 5)(0, 4)(1, 3)(1, 2) + >>> Permutation.rmul(*[Permutation([ti], size=p.size) for ti in t]) == p + True + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Transposition_%28mathematics%29#Properties + + """ + a = self.cyclic_form + res = [] + for x in a: + nx = len(x) + if nx == 2: + res.append(tuple(x)) + elif nx > 2: + first = x[0] + for y in x[nx - 1:0:-1]: + res.append((first, y)) + return res + + @classmethod + def from_sequence(self, i, key=None): + """Return the permutation needed to obtain ``i`` from the sorted + elements of ``i``. If custom sorting is desired, a key can be given. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + + >>> Permutation.from_sequence('SymPy') + (4)(0 1 3) + >>> _(sorted("SymPy")) + ['S', 'y', 'm', 'P', 'y'] + >>> Permutation.from_sequence('SymPy', key=lambda x: x.lower()) + (4)(0 2)(1 3) + """ + ic = list(zip(i, list(range(len(i))))) + if key: + ic.sort(key=lambda x: key(x[0])) + else: + ic.sort() + return ~Permutation([i[1] for i in ic]) + + def __invert__(self): + """ + Return the inverse of the permutation. + + A permutation multiplied by its inverse is the identity permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> p = Permutation([[2, 0], [3, 1]]) + >>> ~p + Permutation([2, 3, 0, 1]) + >>> _ == p**-1 + True + >>> p*~p == ~p*p == Permutation([0, 1, 2, 3]) + True + """ + return self._af_new(_af_invert(self._array_form)) + + def __iter__(self): + """Yield elements from array form. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> list(Permutation(range(3))) + [0, 1, 2] + """ + yield from self.array_form + + def __repr__(self): + return srepr(self) + + def __call__(self, *i): + """ + Allows applying a permutation instance as a bijective function. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([[2, 0], [3, 1]]) + >>> p.array_form + [2, 3, 0, 1] + >>> [p(i) for i in range(4)] + [2, 3, 0, 1] + + If an array is given then the permutation selects the items + from the array (i.e. the permutation is applied to the array): + + >>> from sympy.abc import x + >>> p([x, 1, 0, x**2]) + [0, x**2, x, 1] + """ + # list indices can be Integer or int; leave this + # as it is (don't test or convert it) because this + # gets called a lot and should be fast + if len(i) == 1: + i = i[0] + if not isinstance(i, Iterable): + i = as_int(i) + if i < 0 or i > self.size: + raise TypeError( + "{} should be an integer between 0 and {}" + .format(i, self.size-1)) + return self._array_form[i] + # P([a, b, c]) + if len(i) != self.size: + raise TypeError( + "{} should have the length {}.".format(i, self.size)) + return [i[j] for j in self._array_form] + # P(1, 2, 3) + return self*Permutation(Cycle(*i), size=self.size) + + def atoms(self): + """ + Returns all the elements of a permutation + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation([0, 1, 2, 3, 4, 5]).atoms() + {0, 1, 2, 3, 4, 5} + >>> Permutation([[0, 1], [2, 3], [4, 5]]).atoms() + {0, 1, 2, 3, 4, 5} + """ + return set(self.array_form) + + def apply(self, i): + r"""Apply the permutation to an expression. + + Parameters + ========== + + i : Expr + It should be an integer between $0$ and $n-1$ where $n$ + is the size of the permutation. + + If it is a symbol or a symbolic expression that can + have integer values, an ``AppliedPermutation`` object + will be returned which can represent an unevaluated + function. + + Notes + ===== + + Any permutation can be defined as a bijective function + $\sigma : \{ 0, 1, \dots, n-1 \} \rightarrow \{ 0, 1, \dots, n-1 \}$ + where $n$ denotes the size of the permutation. + + The definition may even be extended for any set with distinctive + elements, such that the permutation can even be applied for + real numbers or such, however, it is not implemented for now for + computational reasons and the integrity with the group theory + module. + + This function is similar to the ``__call__`` magic, however, + ``__call__`` magic already has some other applications like + permuting an array or attaching new cycles, which would + not always be mathematically consistent. + + This also guarantees that the return type is a SymPy integer, + which guarantees the safety to use assumptions. + """ + i = _sympify(i) + if i.is_integer is False: + raise NotImplementedError("{} should be an integer.".format(i)) + + n = self.size + if (i < 0) == True or (i >= n) == True: + raise NotImplementedError( + "{} should be an integer between 0 and {}".format(i, n-1)) + + if i.is_Integer: + return Integer(self._array_form[i]) + return AppliedPermutation(self, i) + + def next_lex(self): + """ + Returns the next permutation in lexicographical order. + If self is the last permutation in lexicographical order + it returns None. + See [4] section 2.4. + + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([2, 3, 1, 0]) + >>> p = Permutation([2, 3, 1, 0]); p.rank() + 17 + >>> p = p.next_lex(); p.rank() + 18 + + See Also + ======== + + rank, unrank_lex + """ + perm = self.array_form[:] + n = len(perm) + i = n - 2 + while perm[i + 1] < perm[i]: + i -= 1 + if i == -1: + return None + else: + j = n - 1 + while perm[j] < perm[i]: + j -= 1 + perm[j], perm[i] = perm[i], perm[j] + i += 1 + j = n - 1 + while i < j: + perm[j], perm[i] = perm[i], perm[j] + i += 1 + j -= 1 + return self._af_new(perm) + + @classmethod + def unrank_nonlex(self, n, r): + """ + This is a linear time unranking algorithm that does not + respect lexicographic order [3]. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> Permutation.unrank_nonlex(4, 5) + Permutation([2, 0, 3, 1]) + >>> Permutation.unrank_nonlex(4, -1) + Permutation([0, 1, 2, 3]) + + See Also + ======== + + next_nonlex, rank_nonlex + """ + def _unrank1(n, r, a): + if n > 0: + a[n - 1], a[r % n] = a[r % n], a[n - 1] + _unrank1(n - 1, r//n, a) + + id_perm = list(range(n)) + n = int(n) + r = r % ifac(n) + _unrank1(n, r, id_perm) + return self._af_new(id_perm) + + def rank_nonlex(self, inv_perm=None): + """ + This is a linear time ranking algorithm that does not + enforce lexicographic order [3]. + + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3]) + >>> p.rank_nonlex() + 23 + + See Also + ======== + + next_nonlex, unrank_nonlex + """ + def _rank1(n, perm, inv_perm): + if n == 1: + return 0 + s = perm[n - 1] + t = inv_perm[n - 1] + perm[n - 1], perm[t] = perm[t], s + inv_perm[n - 1], inv_perm[s] = inv_perm[s], t + return s + n*_rank1(n - 1, perm, inv_perm) + + if inv_perm is None: + inv_perm = (~self).array_form + if not inv_perm: + return 0 + perm = self.array_form[:] + r = _rank1(len(perm), perm, inv_perm) + return r + + def next_nonlex(self): + """ + Returns the next permutation in nonlex order [3]. + If self is the last permutation in this order it returns None. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> p = Permutation([2, 0, 3, 1]); p.rank_nonlex() + 5 + >>> p = p.next_nonlex(); p + Permutation([3, 0, 1, 2]) + >>> p.rank_nonlex() + 6 + + See Also + ======== + + rank_nonlex, unrank_nonlex + """ + r = self.rank_nonlex() + if r == ifac(self.size) - 1: + return None + return self.unrank_nonlex(self.size, r + 1) + + def rank(self): + """ + Returns the lexicographic rank of the permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3]) + >>> p.rank() + 0 + >>> p = Permutation([3, 2, 1, 0]) + >>> p.rank() + 23 + + See Also + ======== + + next_lex, unrank_lex, cardinality, length, order, size + """ + if self._rank is not None: + return self._rank + rank = 0 + rho = self.array_form[:] + n = self.size - 1 + size = n + 1 + psize = int(ifac(n)) + for j in range(size - 1): + rank += rho[j]*psize + for i in range(j + 1, size): + if rho[i] > rho[j]: + rho[i] -= 1 + psize //= n + n -= 1 + self._rank = rank + return rank + + @property + def cardinality(self): + """ + Returns the number of all possible permutations. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3]) + >>> p.cardinality + 24 + + See Also + ======== + + length, order, rank, size + """ + return int(ifac(self.size)) + + def parity(self): + """ + Computes the parity of a permutation. + + Explanation + =========== + + The parity of a permutation reflects the parity of the + number of inversions in the permutation, i.e., the + number of pairs of x and y such that ``x > y`` but ``p[x] < p[y]``. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3]) + >>> p.parity() + 0 + >>> p = Permutation([3, 2, 0, 1]) + >>> p.parity() + 1 + + See Also + ======== + + _af_parity + """ + if self._cyclic_form is not None: + return (self.size - self.cycles) % 2 + + return _af_parity(self.array_form) + + @property + def is_even(self): + """ + Checks if a permutation is even. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3]) + >>> p.is_even + True + >>> p = Permutation([3, 2, 1, 0]) + >>> p.is_even + True + + See Also + ======== + + is_odd + """ + return not self.is_odd + + @property + def is_odd(self): + """ + Checks if a permutation is odd. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3]) + >>> p.is_odd + False + >>> p = Permutation([3, 2, 0, 1]) + >>> p.is_odd + True + + See Also + ======== + + is_even + """ + return bool(self.parity() % 2) + + @property + def is_Singleton(self): + """ + Checks to see if the permutation contains only one number and is + thus the only possible permutation of this set of numbers + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation([0]).is_Singleton + True + >>> Permutation([0, 1]).is_Singleton + False + + See Also + ======== + + is_Empty + """ + return self.size == 1 + + @property + def is_Empty(self): + """ + Checks to see if the permutation is a set with zero elements + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation([]).is_Empty + True + >>> Permutation([0]).is_Empty + False + + See Also + ======== + + is_Singleton + """ + return self.size == 0 + + @property + def is_identity(self): + return self.is_Identity + + @property + def is_Identity(self): + """ + Returns True if the Permutation is an identity permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([]) + >>> p.is_Identity + True + >>> p = Permutation([[0], [1], [2]]) + >>> p.is_Identity + True + >>> p = Permutation([0, 1, 2]) + >>> p.is_Identity + True + >>> p = Permutation([0, 2, 1]) + >>> p.is_Identity + False + + See Also + ======== + + order + """ + af = self.array_form + return not af or all(i == af[i] for i in range(self.size)) + + def ascents(self): + """ + Returns the positions of ascents in a permutation, ie, the location + where p[i] < p[i+1] + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([4, 0, 1, 3, 2]) + >>> p.ascents() + [1, 2] + + See Also + ======== + + descents, inversions, min, max + """ + a = self.array_form + pos = [i for i in range(len(a) - 1) if a[i] < a[i + 1]] + return pos + + def descents(self): + """ + Returns the positions of descents in a permutation, ie, the location + where p[i] > p[i+1] + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([4, 0, 1, 3, 2]) + >>> p.descents() + [0, 3] + + See Also + ======== + + ascents, inversions, min, max + """ + a = self.array_form + pos = [i for i in range(len(a) - 1) if a[i] > a[i + 1]] + return pos + + def max(self) -> int: + """ + The maximum element moved by the permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([1, 0, 2, 3, 4]) + >>> p.max() + 1 + + See Also + ======== + + min, descents, ascents, inversions + """ + a = self.array_form + if not a: + return 0 + return max(_a for i, _a in enumerate(a) if _a != i) + + def min(self) -> int: + """ + The minimum element moved by the permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 4, 3, 2]) + >>> p.min() + 2 + + See Also + ======== + + max, descents, ascents, inversions + """ + a = self.array_form + if not a: + return 0 + return min(_a for i, _a in enumerate(a) if _a != i) + + def inversions(self): + """ + Computes the number of inversions of a permutation. + + Explanation + =========== + + An inversion is where i > j but p[i] < p[j]. + + For small length of p, it iterates over all i and j + values and calculates the number of inversions. + For large length of p, it uses a variation of merge + sort to calculate the number of inversions. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3, 4, 5]) + >>> p.inversions() + 0 + >>> Permutation([3, 2, 1, 0]).inversions() + 6 + + See Also + ======== + + descents, ascents, min, max + + References + ========== + + .. [1] https://www.cp.eng.chula.ac.th/~prabhas//teaching/algo/algo2008/count-inv.htm + + """ + inversions = 0 + a = self.array_form + n = len(a) + if n < 130: + for i in range(n - 1): + b = a[i] + for c in a[i + 1:]: + if b > c: + inversions += 1 + else: + k = 1 + right = 0 + arr = a[:] + temp = a[:] + while k < n: + i = 0 + while i + k < n: + right = i + k * 2 - 1 + if right >= n: + right = n - 1 + inversions += _merge(arr, temp, i, i + k, right) + i = i + k * 2 + k = k * 2 + return inversions + + def commutator(self, x): + """Return the commutator of ``self`` and ``x``: ``~x*~self*x*self`` + + If f and g are part of a group, G, then the commutator of f and g + is the group identity iff f and g commute, i.e. fg == gf. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> p = Permutation([0, 2, 3, 1]) + >>> x = Permutation([2, 0, 3, 1]) + >>> c = p.commutator(x); c + Permutation([2, 1, 3, 0]) + >>> c == ~x*~p*x*p + True + + >>> I = Permutation(3) + >>> p = [I + i for i in range(6)] + >>> for i in range(len(p)): + ... for j in range(len(p)): + ... c = p[i].commutator(p[j]) + ... if p[i]*p[j] == p[j]*p[i]: + ... assert c == I + ... else: + ... assert c != I + ... + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Commutator + """ + + a = self.array_form + b = x.array_form + n = len(a) + if len(b) != n: + raise ValueError("The permutations must be of equal size.") + inva = [None]*n + for i in range(n): + inva[a[i]] = i + invb = [None]*n + for i in range(n): + invb[b[i]] = i + return self._af_new([a[b[inva[i]]] for i in invb]) + + def signature(self): + """ + Gives the signature of the permutation needed to place the + elements of the permutation in canonical order. + + The signature is calculated as (-1)^ + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2]) + >>> p.inversions() + 0 + >>> p.signature() + 1 + >>> q = Permutation([0,2,1]) + >>> q.inversions() + 1 + >>> q.signature() + -1 + + See Also + ======== + + inversions + """ + if self.is_even: + return 1 + return -1 + + def order(self): + """ + Computes the order of a permutation. + + When the permutation is raised to the power of its + order it equals the identity permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> p = Permutation([3, 1, 5, 2, 4, 0]) + >>> p.order() + 4 + >>> (p**(p.order())) + Permutation([], size=6) + + See Also + ======== + + identity, cardinality, length, rank, size + """ + + return reduce(lcm, [len(cycle) for cycle in self.cyclic_form], 1) + + def length(self): + """ + Returns the number of integers moved by a permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation([0, 3, 2, 1]).length() + 2 + >>> Permutation([[0, 1], [2, 3]]).length() + 4 + + See Also + ======== + + min, max, support, cardinality, order, rank, size + """ + + return len(self.support()) + + @property + def cycle_structure(self): + """Return the cycle structure of the permutation as a dictionary + indicating the multiplicity of each cycle length. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation(3).cycle_structure + {1: 4} + >>> Permutation(0, 4, 3)(1, 2)(5, 6).cycle_structure + {2: 2, 3: 1} + """ + if self._cycle_structure: + rv = self._cycle_structure + else: + rv = defaultdict(int) + singletons = self.size + for c in self.cyclic_form: + rv[len(c)] += 1 + singletons -= len(c) + if singletons: + rv[1] = singletons + self._cycle_structure = rv + return dict(rv) # make a copy + + @property + def cycles(self): + """ + Returns the number of cycles contained in the permutation + (including singletons). + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation([0, 1, 2]).cycles + 3 + >>> Permutation([0, 1, 2]).full_cyclic_form + [[0], [1], [2]] + >>> Permutation(0, 1)(2, 3).cycles + 2 + + See Also + ======== + sympy.functions.combinatorial.numbers.stirling + """ + return len(self.full_cyclic_form) + + def index(self): + """ + Returns the index of a permutation. + + The index of a permutation is the sum of all subscripts j such + that p[j] is greater than p[j+1]. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([3, 0, 2, 1, 4]) + >>> p.index() + 2 + """ + a = self.array_form + + return sum(j for j in range(len(a) - 1) if a[j] > a[j + 1]) + + def runs(self): + """ + Returns the runs of a permutation. + + An ascending sequence in a permutation is called a run [5]. + + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([2, 5, 7, 3, 6, 0, 1, 4, 8]) + >>> p.runs() + [[2, 5, 7], [3, 6], [0, 1, 4, 8]] + >>> q = Permutation([1,3,2,0]) + >>> q.runs() + [[1, 3], [2], [0]] + """ + return runs(self.array_form) + + def inversion_vector(self): + """Return the inversion vector of the permutation. + + The inversion vector consists of elements whose value + indicates the number of elements in the permutation + that are lesser than it and lie on its right hand side. + + The inversion vector is the same as the Lehmer encoding of a + permutation. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([4, 8, 0, 7, 1, 5, 3, 6, 2]) + >>> p.inversion_vector() + [4, 7, 0, 5, 0, 2, 1, 1] + >>> p = Permutation([3, 2, 1, 0]) + >>> p.inversion_vector() + [3, 2, 1] + + The inversion vector increases lexicographically with the rank + of the permutation, the -ith element cycling through 0..i. + + >>> p = Permutation(2) + >>> while p: + ... print('%s %s %s' % (p, p.inversion_vector(), p.rank())) + ... p = p.next_lex() + (2) [0, 0] 0 + (1 2) [0, 1] 1 + (2)(0 1) [1, 0] 2 + (0 1 2) [1, 1] 3 + (0 2 1) [2, 0] 4 + (0 2) [2, 1] 5 + + See Also + ======== + + from_inversion_vector + """ + self_array_form = self.array_form + n = len(self_array_form) + inversion_vector = [0] * (n - 1) + + for i in range(n - 1): + val = 0 + for j in range(i + 1, n): + if self_array_form[j] < self_array_form[i]: + val += 1 + inversion_vector[i] = val + return inversion_vector + + def rank_trotterjohnson(self): + """ + Returns the Trotter Johnson rank, which we get from the minimal + change algorithm. See [4] section 2.4. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 1, 2, 3]) + >>> p.rank_trotterjohnson() + 0 + >>> p = Permutation([0, 2, 1, 3]) + >>> p.rank_trotterjohnson() + 7 + + See Also + ======== + + unrank_trotterjohnson, next_trotterjohnson + """ + if self.array_form == [] or self.is_Identity: + return 0 + if self.array_form == [1, 0]: + return 1 + perm = self.array_form + n = self.size + rank = 0 + for j in range(1, n): + k = 1 + i = 0 + while perm[i] != j: + if perm[i] < j: + k += 1 + i += 1 + j1 = j + 1 + if rank % 2 == 0: + rank = j1*rank + j1 - k + else: + rank = j1*rank + k - 1 + return rank + + @classmethod + def unrank_trotterjohnson(cls, size, rank): + """ + Trotter Johnson permutation unranking. See [4] section 2.4. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> Permutation.unrank_trotterjohnson(5, 10) + Permutation([0, 3, 1, 2, 4]) + + See Also + ======== + + rank_trotterjohnson, next_trotterjohnson + """ + perm = [0]*size + r2 = 0 + n = ifac(size) + pj = 1 + for j in range(2, size + 1): + pj *= j + r1 = (rank * pj) // n + k = r1 - j*r2 + if r2 % 2 == 0: + for i in range(j - 1, j - k - 1, -1): + perm[i] = perm[i - 1] + perm[j - k - 1] = j - 1 + else: + for i in range(j - 1, k, -1): + perm[i] = perm[i - 1] + perm[k] = j - 1 + r2 = r1 + return cls._af_new(perm) + + def next_trotterjohnson(self): + """ + Returns the next permutation in Trotter-Johnson order. + If self is the last permutation it returns None. + See [4] section 2.4. If it is desired to generate all such + permutations, they can be generated in order more quickly + with the ``generate_bell`` function. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> p = Permutation([3, 0, 2, 1]) + >>> p.rank_trotterjohnson() + 4 + >>> p = p.next_trotterjohnson(); p + Permutation([0, 3, 2, 1]) + >>> p.rank_trotterjohnson() + 5 + + See Also + ======== + + rank_trotterjohnson, unrank_trotterjohnson, sympy.utilities.iterables.generate_bell + """ + pi = self.array_form[:] + n = len(pi) + st = 0 + rho = pi[:] + done = False + m = n-1 + while m > 0 and not done: + d = rho.index(m) + for i in range(d, m): + rho[i] = rho[i + 1] + par = _af_parity(rho[:m]) + if par == 1: + if d == m: + m -= 1 + else: + pi[st + d], pi[st + d + 1] = pi[st + d + 1], pi[st + d] + done = True + else: + if d == 0: + m -= 1 + st += 1 + else: + pi[st + d], pi[st + d - 1] = pi[st + d - 1], pi[st + d] + done = True + if m == 0: + return None + return self._af_new(pi) + + def get_precedence_matrix(self): + """ + Gets the precedence matrix. This is used for computing the + distance between two permutations. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> p = Permutation.josephus(3, 6, 1) + >>> p + Permutation([2, 5, 3, 1, 4, 0]) + >>> p.get_precedence_matrix() + Matrix([ + [0, 0, 0, 0, 0, 0], + [1, 0, 0, 0, 1, 0], + [1, 1, 0, 1, 1, 1], + [1, 1, 0, 0, 1, 0], + [1, 0, 0, 0, 0, 0], + [1, 1, 0, 1, 1, 0]]) + + See Also + ======== + + get_precedence_distance, get_adjacency_matrix, get_adjacency_distance + """ + m = zeros(self.size) + perm = self.array_form + for i in range(m.rows): + for j in range(i + 1, m.cols): + m[perm[i], perm[j]] = 1 + return m + + def get_precedence_distance(self, other): + """ + Computes the precedence distance between two permutations. + + Explanation + =========== + + Suppose p and p' represent n jobs. The precedence metric + counts the number of times a job j is preceded by job i + in both p and p'. This metric is commutative. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([2, 0, 4, 3, 1]) + >>> q = Permutation([3, 1, 2, 4, 0]) + >>> p.get_precedence_distance(q) + 7 + >>> q.get_precedence_distance(p) + 7 + + See Also + ======== + + get_precedence_matrix, get_adjacency_matrix, get_adjacency_distance + """ + if self.size != other.size: + raise ValueError("The permutations must be of equal size.") + self_prec_mat = self.get_precedence_matrix() + other_prec_mat = other.get_precedence_matrix() + n_prec = 0 + for i in range(self.size): + for j in range(self.size): + if i == j: + continue + if self_prec_mat[i, j] * other_prec_mat[i, j] == 1: + n_prec += 1 + d = self.size * (self.size - 1)//2 - n_prec + return d + + def get_adjacency_matrix(self): + """ + Computes the adjacency matrix of a permutation. + + Explanation + =========== + + If job i is adjacent to job j in a permutation p + then we set m[i, j] = 1 where m is the adjacency + matrix of p. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation.josephus(3, 6, 1) + >>> p.get_adjacency_matrix() + Matrix([ + [0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 1, 0], + [0, 0, 0, 0, 0, 1], + [0, 1, 0, 0, 0, 0], + [1, 0, 0, 0, 0, 0], + [0, 0, 0, 1, 0, 0]]) + >>> q = Permutation([0, 1, 2, 3]) + >>> q.get_adjacency_matrix() + Matrix([ + [0, 1, 0, 0], + [0, 0, 1, 0], + [0, 0, 0, 1], + [0, 0, 0, 0]]) + + See Also + ======== + + get_precedence_matrix, get_precedence_distance, get_adjacency_distance + """ + m = zeros(self.size) + perm = self.array_form + for i in range(self.size - 1): + m[perm[i], perm[i + 1]] = 1 + return m + + def get_adjacency_distance(self, other): + """ + Computes the adjacency distance between two permutations. + + Explanation + =========== + + This metric counts the number of times a pair i,j of jobs is + adjacent in both p and p'. If n_adj is this quantity then + the adjacency distance is n - n_adj - 1 [1] + + [1] Reeves, Colin R. Landscapes, Operators and Heuristic search, Annals + of Operational Research, 86, pp 473-490. (1999) + + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 3, 1, 2, 4]) + >>> q = Permutation.josephus(4, 5, 2) + >>> p.get_adjacency_distance(q) + 3 + >>> r = Permutation([0, 2, 1, 4, 3]) + >>> p.get_adjacency_distance(r) + 4 + + See Also + ======== + + get_precedence_matrix, get_precedence_distance, get_adjacency_matrix + """ + if self.size != other.size: + raise ValueError("The permutations must be of the same size.") + self_adj_mat = self.get_adjacency_matrix() + other_adj_mat = other.get_adjacency_matrix() + n_adj = 0 + for i in range(self.size): + for j in range(self.size): + if i == j: + continue + if self_adj_mat[i, j] * other_adj_mat[i, j] == 1: + n_adj += 1 + d = self.size - n_adj - 1 + return d + + def get_positional_distance(self, other): + """ + Computes the positional distance between two permutations. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> p = Permutation([0, 3, 1, 2, 4]) + >>> q = Permutation.josephus(4, 5, 2) + >>> r = Permutation([3, 1, 4, 0, 2]) + >>> p.get_positional_distance(q) + 12 + >>> p.get_positional_distance(r) + 12 + + See Also + ======== + + get_precedence_distance, get_adjacency_distance + """ + a = self.array_form + b = other.array_form + if len(a) != len(b): + raise ValueError("The permutations must be of the same size.") + return sum(abs(a[i] - b[i]) for i in range(len(a))) + + @classmethod + def josephus(cls, m, n, s=1): + """Return as a permutation the shuffling of range(n) using the Josephus + scheme in which every m-th item is selected until all have been chosen. + The returned permutation has elements listed by the order in which they + were selected. + + The parameter ``s`` stops the selection process when there are ``s`` + items remaining and these are selected by continuing the selection, + counting by 1 rather than by ``m``. + + Consider selecting every 3rd item from 6 until only 2 remain:: + + choices chosen + ======== ====== + 012345 + 01 345 2 + 01 34 25 + 01 4 253 + 0 4 2531 + 0 25314 + 253140 + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation.josephus(3, 6, 2).array_form + [2, 5, 3, 1, 4, 0] + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Flavius_Josephus + .. [2] https://en.wikipedia.org/wiki/Josephus_problem + .. [3] https://web.archive.org/web/20171008094331/http://www.wou.edu/~burtonl/josephus.html + + """ + from collections import deque + m -= 1 + Q = deque(list(range(n))) + perm = [] + while len(Q) > max(s, 1): + for dp in range(m): + Q.append(Q.popleft()) + perm.append(Q.popleft()) + perm.extend(list(Q)) + return cls(perm) + + @classmethod + def from_inversion_vector(cls, inversion): + """ + Calculates the permutation from the inversion vector. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> Permutation.from_inversion_vector([3, 2, 1, 0, 0]) + Permutation([3, 2, 1, 0, 4, 5]) + + """ + size = len(inversion) + N = list(range(size + 1)) + perm = [] + try: + for k in range(size): + val = N[inversion[k]] + perm.append(val) + N.remove(val) + except IndexError: + raise ValueError("The inversion vector is not valid.") + perm.extend(N) + return cls._af_new(perm) + + @classmethod + def random(cls, n): + """ + Generates a random permutation of length ``n``. + + Uses the underlying Python pseudo-random number generator. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> Permutation.random(2) in (Permutation([1, 0]), Permutation([0, 1])) + True + + """ + perm_array = list(range(n)) + random.shuffle(perm_array) + return cls._af_new(perm_array) + + @classmethod + def unrank_lex(cls, size, rank): + """ + Lexicographic permutation unranking. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy import init_printing + >>> init_printing(perm_cyclic=False, pretty_print=False) + >>> a = Permutation.unrank_lex(5, 10) + >>> a.rank() + 10 + >>> a + Permutation([0, 2, 4, 1, 3]) + + See Also + ======== + + rank, next_lex + """ + perm_array = [0] * size + psize = 1 + for i in range(size): + new_psize = psize*(i + 1) + d = (rank % new_psize) // psize + rank -= d*psize + perm_array[size - i - 1] = d + for j in range(size - i, size): + if perm_array[j] > d - 1: + perm_array[j] += 1 + psize = new_psize + return cls._af_new(perm_array) + + def resize(self, n): + """Resize the permutation to the new size ``n``. + + Parameters + ========== + + n : int + The new size of the permutation. + + Raises + ====== + + ValueError + If the permutation cannot be resized to the given size. + This may only happen when resized to a smaller size than + the original. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + + Increasing the size of a permutation: + + >>> p = Permutation(0, 1, 2) + >>> p = p.resize(5) + >>> p + (4)(0 1 2) + + Decreasing the size of the permutation: + + >>> p = p.resize(4) + >>> p + (3)(0 1 2) + + If resizing to the specific size breaks the cycles: + + >>> p.resize(2) + Traceback (most recent call last): + ... + ValueError: The permutation cannot be resized to 2 because the + cycle (0, 1, 2) may break. + """ + aform = self.array_form + l = len(aform) + if n > l: + aform += list(range(l, n)) + return Permutation._af_new(aform) + + elif n < l: + cyclic_form = self.full_cyclic_form + new_cyclic_form = [] + for cycle in cyclic_form: + cycle_min = min(cycle) + cycle_max = max(cycle) + if cycle_min <= n-1: + if cycle_max > n-1: + raise ValueError( + "The permutation cannot be resized to {} " + "because the cycle {} may break." + .format(n, tuple(cycle))) + + new_cyclic_form.append(cycle) + return Permutation(new_cyclic_form) + + return self + + # XXX Deprecated flag + print_cyclic = None + + +def _merge(arr, temp, left, mid, right): + """ + Merges two sorted arrays and calculates the inversion count. + + Helper function for calculating inversions. This method is + for internal use only. + """ + i = k = left + j = mid + inv_count = 0 + while i < mid and j <= right: + if arr[i] < arr[j]: + temp[k] = arr[i] + k += 1 + i += 1 + else: + temp[k] = arr[j] + k += 1 + j += 1 + inv_count += (mid -i) + while i < mid: + temp[k] = arr[i] + k += 1 + i += 1 + if j <= right: + k += right - j + 1 + j += right - j + 1 + arr[left:k + 1] = temp[left:k + 1] + else: + arr[left:right + 1] = temp[left:right + 1] + return inv_count + +Perm = Permutation +_af_new = Perm._af_new + + +class AppliedPermutation(Expr): + """A permutation applied to a symbolic variable. + + Parameters + ========== + + perm : Permutation + x : Expr + + Examples + ======== + + >>> from sympy import Symbol + >>> from sympy.combinatorics import Permutation + + Creating a symbolic permutation function application: + + >>> x = Symbol('x') + >>> p = Permutation(0, 1, 2) + >>> p.apply(x) + AppliedPermutation((0 1 2), x) + >>> _.subs(x, 1) + 2 + """ + def __new__(cls, perm, x, evaluate=None): + if evaluate is None: + evaluate = global_parameters.evaluate + + perm = _sympify(perm) + x = _sympify(x) + + if not isinstance(perm, Permutation): + raise ValueError("{} must be a Permutation instance." + .format(perm)) + + if evaluate: + if x.is_Integer: + return perm.apply(x) + + obj = super().__new__(cls, perm, x) + return obj + + +@dispatch(Permutation, Permutation) +def _eval_is_eq(lhs, rhs): + if lhs._size != rhs._size: + return None + return lhs._array_form == rhs._array_form diff --git a/lib/python3.12/site-packages/sympy/combinatorics/polyhedron.py b/lib/python3.12/site-packages/sympy/combinatorics/polyhedron.py new file mode 100644 index 0000000000000000000000000000000000000000..2bc05d7d97c840649661f3290442499c841ca7c1 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/polyhedron.py @@ -0,0 +1,1019 @@ +from sympy.combinatorics import Permutation as Perm +from sympy.combinatorics.perm_groups import PermutationGroup +from sympy.core import Basic, Tuple, default_sort_key +from sympy.sets import FiniteSet +from sympy.utilities.iterables import (minlex, unflatten, flatten) +from sympy.utilities.misc import as_int + +rmul = Perm.rmul + + +class Polyhedron(Basic): + """ + Represents the polyhedral symmetry group (PSG). + + Explanation + =========== + + The PSG is one of the symmetry groups of the Platonic solids. + There are three polyhedral groups: the tetrahedral group + of order 12, the octahedral group of order 24, and the + icosahedral group of order 60. + + All doctests have been given in the docstring of the + constructor of the object. + + References + ========== + + .. [1] https://mathworld.wolfram.com/PolyhedralGroup.html + + """ + _edges = None + + def __new__(cls, corners, faces=(), pgroup=()): + """ + The constructor of the Polyhedron group object. + + Explanation + =========== + + It takes up to three parameters: the corners, faces, and + allowed transformations. + + The corners/vertices are entered as a list of arbitrary + expressions that are used to identify each vertex. + + The faces are entered as a list of tuples of indices; a tuple + of indices identifies the vertices which define the face. They + should be entered in a cw or ccw order; they will be standardized + by reversal and rotation to be give the lowest lexical ordering. + If no faces are given then no edges will be computed. + + >>> from sympy.combinatorics.polyhedron import Polyhedron + >>> Polyhedron(list('abc'), [(1, 2, 0)]).faces + {(0, 1, 2)} + >>> Polyhedron(list('abc'), [(1, 0, 2)]).faces + {(0, 1, 2)} + + The allowed transformations are entered as allowable permutations + of the vertices for the polyhedron. Instance of Permutations + (as with faces) should refer to the supplied vertices by index. + These permutation are stored as a PermutationGroup. + + Examples + ======== + + >>> from sympy.combinatorics.permutations import Permutation + >>> from sympy import init_printing + >>> from sympy.abc import w, x, y, z + >>> init_printing(pretty_print=False, perm_cyclic=False) + + Here we construct the Polyhedron object for a tetrahedron. + + >>> corners = [w, x, y, z] + >>> faces = [(0, 1, 2), (0, 2, 3), (0, 3, 1), (1, 2, 3)] + + Next, allowed transformations of the polyhedron must be given. This + is given as permutations of vertices. + + Although the vertices of a tetrahedron can be numbered in 24 (4!) + different ways, there are only 12 different orientations for a + physical tetrahedron. The following permutations, applied once or + twice, will generate all 12 of the orientations. (The identity + permutation, Permutation(range(4)), is not included since it does + not change the orientation of the vertices.) + + >>> pgroup = [Permutation([[0, 1, 2], [3]]), \ + Permutation([[0, 1, 3], [2]]), \ + Permutation([[0, 2, 3], [1]]), \ + Permutation([[1, 2, 3], [0]]), \ + Permutation([[0, 1], [2, 3]]), \ + Permutation([[0, 2], [1, 3]]), \ + Permutation([[0, 3], [1, 2]])] + + The Polyhedron is now constructed and demonstrated: + + >>> tetra = Polyhedron(corners, faces, pgroup) + >>> tetra.size + 4 + >>> tetra.edges + {(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)} + >>> tetra.corners + (w, x, y, z) + + It can be rotated with an arbitrary permutation of vertices, e.g. + the following permutation is not in the pgroup: + + >>> tetra.rotate(Permutation([0, 1, 3, 2])) + >>> tetra.corners + (w, x, z, y) + + An allowed permutation of the vertices can be constructed by + repeatedly applying permutations from the pgroup to the vertices. + Here is a demonstration that applying p and p**2 for every p in + pgroup generates all the orientations of a tetrahedron and no others: + + >>> all = ( (w, x, y, z), \ + (x, y, w, z), \ + (y, w, x, z), \ + (w, z, x, y), \ + (z, w, y, x), \ + (w, y, z, x), \ + (y, z, w, x), \ + (x, z, y, w), \ + (z, y, x, w), \ + (y, x, z, w), \ + (x, w, z, y), \ + (z, x, w, y) ) + + >>> got = [] + >>> for p in (pgroup + [p**2 for p in pgroup]): + ... h = Polyhedron(corners) + ... h.rotate(p) + ... got.append(h.corners) + ... + >>> set(got) == set(all) + True + + The make_perm method of a PermutationGroup will randomly pick + permutations, multiply them together, and return the permutation that + can be applied to the polyhedron to give the orientation produced + by those individual permutations. + + Here, 3 permutations are used: + + >>> tetra.pgroup.make_perm(3) # doctest: +SKIP + Permutation([0, 3, 1, 2]) + + To select the permutations that should be used, supply a list + of indices to the permutations in pgroup in the order they should + be applied: + + >>> use = [0, 0, 2] + >>> p002 = tetra.pgroup.make_perm(3, use) + >>> p002 + Permutation([1, 0, 3, 2]) + + + Apply them one at a time: + + >>> tetra.reset() + >>> for i in use: + ... tetra.rotate(pgroup[i]) + ... + >>> tetra.vertices + (x, w, z, y) + >>> sequentially = tetra.vertices + + Apply the composite permutation: + + >>> tetra.reset() + >>> tetra.rotate(p002) + >>> tetra.corners + (x, w, z, y) + >>> tetra.corners in all and tetra.corners == sequentially + True + + Notes + ===== + + Defining permutation groups + --------------------------- + + It is not necessary to enter any permutations, nor is necessary to + enter a complete set of transformations. In fact, for a polyhedron, + all configurations can be constructed from just two permutations. + For example, the orientations of a tetrahedron can be generated from + an axis passing through a vertex and face and another axis passing + through a different vertex or from an axis passing through the + midpoints of two edges opposite of each other. + + For simplicity of presentation, consider a square -- + not a cube -- with vertices 1, 2, 3, and 4: + + 1-----2 We could think of axes of rotation being: + | | 1) through the face + | | 2) from midpoint 1-2 to 3-4 or 1-3 to 2-4 + 3-----4 3) lines 1-4 or 2-3 + + + To determine how to write the permutations, imagine 4 cameras, + one at each corner, labeled A-D: + + A B A B + 1-----2 1-----3 vertex index: + | | | | 1 0 + | | | | 2 1 + 3-----4 2-----4 3 2 + C D C D 4 3 + + original after rotation + along 1-4 + + A diagonal and a face axis will be chosen for the "permutation group" + from which any orientation can be constructed. + + >>> pgroup = [] + + Imagine a clockwise rotation when viewing 1-4 from camera A. The new + orientation is (in camera-order): 1, 3, 2, 4 so the permutation is + given using the *indices* of the vertices as: + + >>> pgroup.append(Permutation((0, 2, 1, 3))) + + Now imagine rotating clockwise when looking down an axis entering the + center of the square as viewed. The new camera-order would be + 3, 1, 4, 2 so the permutation is (using indices): + + >>> pgroup.append(Permutation((2, 0, 3, 1))) + + The square can now be constructed: + ** use real-world labels for the vertices, entering them in + camera order + ** for the faces we use zero-based indices of the vertices + in *edge-order* as the face is traversed; neither the + direction nor the starting point matter -- the faces are + only used to define edges (if so desired). + + >>> square = Polyhedron((1, 2, 3, 4), [(0, 1, 3, 2)], pgroup) + + To rotate the square with a single permutation we can do: + + >>> square.rotate(square.pgroup[0]) + >>> square.corners + (1, 3, 2, 4) + + To use more than one permutation (or to use one permutation more + than once) it is more convenient to use the make_perm method: + + >>> p011 = square.pgroup.make_perm([0, 1, 1]) # diag flip + 2 rotations + >>> square.reset() # return to initial orientation + >>> square.rotate(p011) + >>> square.corners + (4, 2, 3, 1) + + Thinking outside the box + ------------------------ + + Although the Polyhedron object has a direct physical meaning, it + actually has broader application. In the most general sense it is + just a decorated PermutationGroup, allowing one to connect the + permutations to something physical. For example, a Rubik's cube is + not a proper polyhedron, but the Polyhedron class can be used to + represent it in a way that helps to visualize the Rubik's cube. + + >>> from sympy import flatten, unflatten, symbols + >>> from sympy.combinatorics import RubikGroup + >>> facelets = flatten([symbols(s+'1:5') for s in 'UFRBLD']) + >>> def show(): + ... pairs = unflatten(r2.corners, 2) + ... print(pairs[::2]) + ... print(pairs[1::2]) + ... + >>> r2 = Polyhedron(facelets, pgroup=RubikGroup(2)) + >>> show() + [(U1, U2), (F1, F2), (R1, R2), (B1, B2), (L1, L2), (D1, D2)] + [(U3, U4), (F3, F4), (R3, R4), (B3, B4), (L3, L4), (D3, D4)] + >>> r2.rotate(0) # cw rotation of F + >>> show() + [(U1, U2), (F3, F1), (U3, R2), (B1, B2), (L1, D1), (R3, R1)] + [(L4, L2), (F4, F2), (U4, R4), (B3, B4), (L3, D2), (D3, D4)] + + Predefined Polyhedra + ==================== + + For convenience, the vertices and faces are defined for the following + standard solids along with a permutation group for transformations. + When the polyhedron is oriented as indicated below, the vertices in + a given horizontal plane are numbered in ccw direction, starting from + the vertex that will give the lowest indices in a given face. (In the + net of the vertices, indices preceded by "-" indicate replication of + the lhs index in the net.) + + tetrahedron, tetrahedron_faces + ------------------------------ + + 4 vertices (vertex up) net: + + 0 0-0 + 1 2 3-1 + + 4 faces: + + (0, 1, 2) (0, 2, 3) (0, 3, 1) (1, 2, 3) + + cube, cube_faces + ---------------- + + 8 vertices (face up) net: + + 0 1 2 3-0 + 4 5 6 7-4 + + 6 faces: + + (0, 1, 2, 3) + (0, 1, 5, 4) (1, 2, 6, 5) (2, 3, 7, 6) (0, 3, 7, 4) + (4, 5, 6, 7) + + octahedron, octahedron_faces + ---------------------------- + + 6 vertices (vertex up) net: + + 0 0 0-0 + 1 2 3 4-1 + 5 5 5-5 + + 8 faces: + + (0, 1, 2) (0, 2, 3) (0, 3, 4) (0, 1, 4) + (1, 2, 5) (2, 3, 5) (3, 4, 5) (1, 4, 5) + + dodecahedron, dodecahedron_faces + -------------------------------- + + 20 vertices (vertex up) net: + + 0 1 2 3 4 -0 + 5 6 7 8 9 -5 + 14 10 11 12 13-14 + 15 16 17 18 19-15 + + 12 faces: + + (0, 1, 2, 3, 4) (0, 1, 6, 10, 5) (1, 2, 7, 11, 6) + (2, 3, 8, 12, 7) (3, 4, 9, 13, 8) (0, 4, 9, 14, 5) + (5, 10, 16, 15, 14) (6, 10, 16, 17, 11) (7, 11, 17, 18, 12) + (8, 12, 18, 19, 13) (9, 13, 19, 15, 14)(15, 16, 17, 18, 19) + + icosahedron, icosahedron_faces + ------------------------------ + + 12 vertices (face up) net: + + 0 0 0 0 -0 + 1 2 3 4 5 -1 + 6 7 8 9 10 -6 + 11 11 11 11 -11 + + 20 faces: + + (0, 1, 2) (0, 2, 3) (0, 3, 4) + (0, 4, 5) (0, 1, 5) (1, 2, 6) + (2, 3, 7) (3, 4, 8) (4, 5, 9) + (1, 5, 10) (2, 6, 7) (3, 7, 8) + (4, 8, 9) (5, 9, 10) (1, 6, 10) + (6, 7, 11) (7, 8, 11) (8, 9, 11) + (9, 10, 11) (6, 10, 11) + + >>> from sympy.combinatorics.polyhedron import cube + >>> cube.edges + {(0, 1), (0, 3), (0, 4), (1, 2), (1, 5), (2, 3), (2, 6), (3, 7), (4, 5), (4, 7), (5, 6), (6, 7)} + + If you want to use letters or other names for the corners you + can still use the pre-calculated faces: + + >>> corners = list('abcdefgh') + >>> Polyhedron(corners, cube.faces).corners + (a, b, c, d, e, f, g, h) + + References + ========== + + .. [1] www.ocf.berkeley.edu/~wwu/articles/platonicsolids.pdf + + """ + faces = [minlex(f, directed=False, key=default_sort_key) for f in faces] + corners, faces, pgroup = args = \ + [Tuple(*a) for a in (corners, faces, pgroup)] + obj = Basic.__new__(cls, *args) + obj._corners = tuple(corners) # in order given + obj._faces = FiniteSet(*faces) + if pgroup and pgroup[0].size != len(corners): + raise ValueError("Permutation size unequal to number of corners.") + # use the identity permutation if none are given + obj._pgroup = PermutationGroup( + pgroup or [Perm(range(len(corners)))] ) + return obj + + @property + def corners(self): + """ + Get the corners of the Polyhedron. + + The method ``vertices`` is an alias for ``corners``. + + Examples + ======== + + >>> from sympy.combinatorics import Polyhedron + >>> from sympy.abc import a, b, c, d + >>> p = Polyhedron(list('abcd')) + >>> p.corners == p.vertices == (a, b, c, d) + True + + See Also + ======== + + array_form, cyclic_form + """ + return self._corners + vertices = corners + + @property + def array_form(self): + """Return the indices of the corners. + + The indices are given relative to the original position of corners. + + Examples + ======== + + >>> from sympy.combinatorics.polyhedron import tetrahedron + >>> tetrahedron = tetrahedron.copy() + >>> tetrahedron.array_form + [0, 1, 2, 3] + + >>> tetrahedron.rotate(0) + >>> tetrahedron.array_form + [0, 2, 3, 1] + >>> tetrahedron.pgroup[0].array_form + [0, 2, 3, 1] + + See Also + ======== + + corners, cyclic_form + """ + corners = list(self.args[0]) + return [corners.index(c) for c in self.corners] + + @property + def cyclic_form(self): + """Return the indices of the corners in cyclic notation. + + The indices are given relative to the original position of corners. + + See Also + ======== + + corners, array_form + """ + return Perm._af_new(self.array_form).cyclic_form + + @property + def size(self): + """ + Get the number of corners of the Polyhedron. + """ + return len(self._corners) + + @property + def faces(self): + """ + Get the faces of the Polyhedron. + """ + return self._faces + + @property + def pgroup(self): + """ + Get the permutations of the Polyhedron. + """ + return self._pgroup + + @property + def edges(self): + """ + Given the faces of the polyhedra we can get the edges. + + Examples + ======== + + >>> from sympy.combinatorics import Polyhedron + >>> from sympy.abc import a, b, c + >>> corners = (a, b, c) + >>> faces = [(0, 1, 2)] + >>> Polyhedron(corners, faces).edges + {(0, 1), (0, 2), (1, 2)} + + """ + if self._edges is None: + output = set() + for face in self.faces: + for i in range(len(face)): + edge = tuple(sorted([face[i], face[i - 1]])) + output.add(edge) + self._edges = FiniteSet(*output) + return self._edges + + def rotate(self, perm): + """ + Apply a permutation to the polyhedron *in place*. The permutation + may be given as a Permutation instance or an integer indicating + which permutation from pgroup of the Polyhedron should be + applied. + + This is an operation that is analogous to rotation about + an axis by a fixed increment. + + Notes + ===== + + When a Permutation is applied, no check is done to see if that + is a valid permutation for the Polyhedron. For example, a cube + could be given a permutation which effectively swaps only 2 + vertices. A valid permutation (that rotates the object in a + physical way) will be obtained if one only uses + permutations from the ``pgroup`` of the Polyhedron. On the other + hand, allowing arbitrary rotations (applications of permutations) + gives a way to follow named elements rather than indices since + Polyhedron allows vertices to be named while Permutation works + only with indices. + + Examples + ======== + + >>> from sympy.combinatorics import Polyhedron, Permutation + >>> from sympy.combinatorics.polyhedron import cube + >>> cube = cube.copy() + >>> cube.corners + (0, 1, 2, 3, 4, 5, 6, 7) + >>> cube.rotate(0) + >>> cube.corners + (1, 2, 3, 0, 5, 6, 7, 4) + + A non-physical "rotation" that is not prohibited by this method: + + >>> cube.reset() + >>> cube.rotate(Permutation([[1, 2]], size=8)) + >>> cube.corners + (0, 2, 1, 3, 4, 5, 6, 7) + + Polyhedron can be used to follow elements of set that are + identified by letters instead of integers: + + >>> shadow = h5 = Polyhedron(list('abcde')) + >>> p = Permutation([3, 0, 1, 2, 4]) + >>> h5.rotate(p) + >>> h5.corners + (d, a, b, c, e) + >>> _ == shadow.corners + True + >>> copy = h5.copy() + >>> h5.rotate(p) + >>> h5.corners == copy.corners + False + """ + if not isinstance(perm, Perm): + perm = self.pgroup[perm] + # and we know it's valid + else: + if perm.size != self.size: + raise ValueError('Polyhedron and Permutation sizes differ.') + a = perm.array_form + corners = [self.corners[a[i]] for i in range(len(self.corners))] + self._corners = tuple(corners) + + def reset(self): + """Return corners to their original positions. + + Examples + ======== + + >>> from sympy.combinatorics.polyhedron import tetrahedron as T + >>> T = T.copy() + >>> T.corners + (0, 1, 2, 3) + >>> T.rotate(0) + >>> T.corners + (0, 2, 3, 1) + >>> T.reset() + >>> T.corners + (0, 1, 2, 3) + """ + self._corners = self.args[0] + + +def _pgroup_calcs(): + """Return the permutation groups for each of the polyhedra and the face + definitions: tetrahedron, cube, octahedron, dodecahedron, icosahedron, + tetrahedron_faces, cube_faces, octahedron_faces, dodecahedron_faces, + icosahedron_faces + + Explanation + =========== + + (This author did not find and did not know of a better way to do it though + there likely is such a way.) + + Although only 2 permutations are needed for a polyhedron in order to + generate all the possible orientations, a group of permutations is + provided instead. A set of permutations is called a "group" if:: + + a*b = c (for any pair of permutations in the group, a and b, their + product, c, is in the group) + + a*(b*c) = (a*b)*c (for any 3 permutations in the group associativity holds) + + there is an identity permutation, I, such that I*a = a*I for all elements + in the group + + a*b = I (the inverse of each permutation is also in the group) + + None of the polyhedron groups defined follow these definitions of a group. + Instead, they are selected to contain those permutations whose powers + alone will construct all orientations of the polyhedron, i.e. for + permutations ``a``, ``b``, etc... in the group, ``a, a**2, ..., a**o_a``, + ``b, b**2, ..., b**o_b``, etc... (where ``o_i`` is the order of + permutation ``i``) generate all permutations of the polyhedron instead of + mixed products like ``a*b``, ``a*b**2``, etc.... + + Note that for a polyhedron with n vertices, the valid permutations of the + vertices exclude those that do not maintain its faces. e.g. the + permutation BCDE of a square's four corners, ABCD, is a valid + permutation while CBDE is not (because this would twist the square). + + Examples + ======== + + The is_group checks for: closure, the presence of the Identity permutation, + and the presence of the inverse for each of the elements in the group. This + confirms that none of the polyhedra are true groups: + + >>> from sympy.combinatorics.polyhedron import ( + ... tetrahedron, cube, octahedron, dodecahedron, icosahedron) + ... + >>> polyhedra = (tetrahedron, cube, octahedron, dodecahedron, icosahedron) + >>> [h.pgroup.is_group for h in polyhedra] + ... + [True, True, True, True, True] + + Although tests in polyhedron's test suite check that powers of the + permutations in the groups generate all permutations of the vertices + of the polyhedron, here we also demonstrate the powers of the given + permutations create a complete group for the tetrahedron: + + >>> from sympy.combinatorics import Permutation, PermutationGroup + >>> for h in polyhedra[:1]: + ... G = h.pgroup + ... perms = set() + ... for g in G: + ... for e in range(g.order()): + ... p = tuple((g**e).array_form) + ... perms.add(p) + ... + ... perms = [Permutation(p) for p in perms] + ... assert PermutationGroup(perms).is_group + + In addition to doing the above, the tests in the suite confirm that the + faces are all present after the application of each permutation. + + References + ========== + + .. [1] https://dogschool.tripod.com/trianglegroup.html + + """ + def _pgroup_of_double(polyh, ordered_faces, pgroup): + n = len(ordered_faces[0]) + # the vertices of the double which sits inside a give polyhedron + # can be found by tracking the faces of the outer polyhedron. + # A map between face and the vertex of the double is made so that + # after rotation the position of the vertices can be located + fmap = dict(zip(ordered_faces, + range(len(ordered_faces)))) + flat_faces = flatten(ordered_faces) + new_pgroup = [] + for p in pgroup: + h = polyh.copy() + h.rotate(p) + c = h.corners + # reorder corners in the order they should appear when + # enumerating the faces + reorder = unflatten([c[j] for j in flat_faces], n) + # make them canonical + reorder = [tuple(map(as_int, + minlex(f, directed=False))) + for f in reorder] + # map face to vertex: the resulting list of vertices are the + # permutation that we seek for the double + new_pgroup.append(Perm([fmap[f] for f in reorder])) + return new_pgroup + + tetrahedron_faces = [ + (0, 1, 2), (0, 2, 3), (0, 3, 1), # upper 3 + (1, 2, 3), # bottom + ] + + # cw from top + # + _t_pgroup = [ + Perm([[1, 2, 3], [0]]), # cw from top + Perm([[0, 1, 2], [3]]), # cw from front face + Perm([[0, 3, 2], [1]]), # cw from back right face + Perm([[0, 3, 1], [2]]), # cw from back left face + Perm([[0, 1], [2, 3]]), # through front left edge + Perm([[0, 2], [1, 3]]), # through front right edge + Perm([[0, 3], [1, 2]]), # through back edge + ] + + tetrahedron = Polyhedron( + range(4), + tetrahedron_faces, + _t_pgroup) + + cube_faces = [ + (0, 1, 2, 3), # upper + (0, 1, 5, 4), (1, 2, 6, 5), (2, 3, 7, 6), (0, 3, 7, 4), # middle 4 + (4, 5, 6, 7), # lower + ] + + # U, D, F, B, L, R = up, down, front, back, left, right + _c_pgroup = [Perm(p) for p in + [ + [1, 2, 3, 0, 5, 6, 7, 4], # cw from top, U + [4, 0, 3, 7, 5, 1, 2, 6], # cw from F face + [4, 5, 1, 0, 7, 6, 2, 3], # cw from R face + + [1, 0, 4, 5, 2, 3, 7, 6], # cw through UF edge + [6, 2, 1, 5, 7, 3, 0, 4], # cw through UR edge + [6, 7, 3, 2, 5, 4, 0, 1], # cw through UB edge + [3, 7, 4, 0, 2, 6, 5, 1], # cw through UL edge + [4, 7, 6, 5, 0, 3, 2, 1], # cw through FL edge + [6, 5, 4, 7, 2, 1, 0, 3], # cw through FR edge + + [0, 3, 7, 4, 1, 2, 6, 5], # cw through UFL vertex + [5, 1, 0, 4, 6, 2, 3, 7], # cw through UFR vertex + [5, 6, 2, 1, 4, 7, 3, 0], # cw through UBR vertex + [7, 4, 0, 3, 6, 5, 1, 2], # cw through UBL + ]] + + cube = Polyhedron( + range(8), + cube_faces, + _c_pgroup) + + octahedron_faces = [ + (0, 1, 2), (0, 2, 3), (0, 3, 4), (0, 1, 4), # top 4 + (1, 2, 5), (2, 3, 5), (3, 4, 5), (1, 4, 5), # bottom 4 + ] + + octahedron = Polyhedron( + range(6), + octahedron_faces, + _pgroup_of_double(cube, cube_faces, _c_pgroup)) + + dodecahedron_faces = [ + (0, 1, 2, 3, 4), # top + (0, 1, 6, 10, 5), (1, 2, 7, 11, 6), (2, 3, 8, 12, 7), # upper 5 + (3, 4, 9, 13, 8), (0, 4, 9, 14, 5), + (5, 10, 16, 15, 14), (6, 10, 16, 17, 11), (7, 11, 17, 18, + 12), # lower 5 + (8, 12, 18, 19, 13), (9, 13, 19, 15, 14), + (15, 16, 17, 18, 19) # bottom + ] + + def _string_to_perm(s): + rv = [Perm(range(20))] + p = None + for si in s: + if si not in '01': + count = int(si) - 1 + else: + count = 1 + if si == '0': + p = _f0 + elif si == '1': + p = _f1 + rv.extend([p]*count) + return Perm.rmul(*rv) + + # top face cw + _f0 = Perm([ + 1, 2, 3, 4, 0, 6, 7, 8, 9, 5, 11, + 12, 13, 14, 10, 16, 17, 18, 19, 15]) + # front face cw + _f1 = Perm([ + 5, 0, 4, 9, 14, 10, 1, 3, 13, 15, + 6, 2, 8, 19, 16, 17, 11, 7, 12, 18]) + # the strings below, like 0104 are shorthand for F0*F1*F0**4 and are + # the remaining 4 face rotations, 15 edge permutations, and the + # 10 vertex rotations. + _dodeca_pgroup = [_f0, _f1] + [_string_to_perm(s) for s in ''' + 0104 140 014 0410 + 010 1403 03104 04103 102 + 120 1304 01303 021302 03130 + 0412041 041204103 04120410 041204104 041204102 + 10 01 1402 0140 04102 0412 1204 1302 0130 03120'''.strip().split()] + + dodecahedron = Polyhedron( + range(20), + dodecahedron_faces, + _dodeca_pgroup) + + icosahedron_faces = [ + (0, 1, 2), (0, 2, 3), (0, 3, 4), (0, 4, 5), (0, 1, 5), + (1, 6, 7), (1, 2, 7), (2, 7, 8), (2, 3, 8), (3, 8, 9), + (3, 4, 9), (4, 9, 10), (4, 5, 10), (5, 6, 10), (1, 5, 6), + (6, 7, 11), (7, 8, 11), (8, 9, 11), (9, 10, 11), (6, 10, 11)] + + icosahedron = Polyhedron( + range(12), + icosahedron_faces, + _pgroup_of_double( + dodecahedron, dodecahedron_faces, _dodeca_pgroup)) + + return (tetrahedron, cube, octahedron, dodecahedron, icosahedron, + tetrahedron_faces, cube_faces, octahedron_faces, + dodecahedron_faces, icosahedron_faces) + +# ----------------------------------------------------------------------- +# Standard Polyhedron groups +# +# These are generated using _pgroup_calcs() above. However to save +# import time we encode them explicitly here. +# ----------------------------------------------------------------------- + +tetrahedron = Polyhedron( + Tuple(0, 1, 2, 3), + Tuple( + Tuple(0, 1, 2), + Tuple(0, 2, 3), + Tuple(0, 1, 3), + Tuple(1, 2, 3)), + Tuple( + Perm(1, 2, 3), + Perm(3)(0, 1, 2), + Perm(0, 3, 2), + Perm(0, 3, 1), + Perm(0, 1)(2, 3), + Perm(0, 2)(1, 3), + Perm(0, 3)(1, 2) + )) + +cube = Polyhedron( + Tuple(0, 1, 2, 3, 4, 5, 6, 7), + Tuple( + Tuple(0, 1, 2, 3), + Tuple(0, 1, 5, 4), + Tuple(1, 2, 6, 5), + Tuple(2, 3, 7, 6), + Tuple(0, 3, 7, 4), + Tuple(4, 5, 6, 7)), + Tuple( + Perm(0, 1, 2, 3)(4, 5, 6, 7), + Perm(0, 4, 5, 1)(2, 3, 7, 6), + Perm(0, 4, 7, 3)(1, 5, 6, 2), + Perm(0, 1)(2, 4)(3, 5)(6, 7), + Perm(0, 6)(1, 2)(3, 5)(4, 7), + Perm(0, 6)(1, 7)(2, 3)(4, 5), + Perm(0, 3)(1, 7)(2, 4)(5, 6), + Perm(0, 4)(1, 7)(2, 6)(3, 5), + Perm(0, 6)(1, 5)(2, 4)(3, 7), + Perm(1, 3, 4)(2, 7, 5), + Perm(7)(0, 5, 2)(3, 4, 6), + Perm(0, 5, 7)(1, 6, 3), + Perm(0, 7, 2)(1, 4, 6))) + +octahedron = Polyhedron( + Tuple(0, 1, 2, 3, 4, 5), + Tuple( + Tuple(0, 1, 2), + Tuple(0, 2, 3), + Tuple(0, 3, 4), + Tuple(0, 1, 4), + Tuple(1, 2, 5), + Tuple(2, 3, 5), + Tuple(3, 4, 5), + Tuple(1, 4, 5)), + Tuple( + Perm(5)(1, 2, 3, 4), + Perm(0, 4, 5, 2), + Perm(0, 1, 5, 3), + Perm(0, 1)(2, 4)(3, 5), + Perm(0, 2)(1, 3)(4, 5), + Perm(0, 3)(1, 5)(2, 4), + Perm(0, 4)(1, 3)(2, 5), + Perm(0, 5)(1, 4)(2, 3), + Perm(0, 5)(1, 2)(3, 4), + Perm(0, 4, 1)(2, 3, 5), + Perm(0, 1, 2)(3, 4, 5), + Perm(0, 2, 3)(1, 5, 4), + Perm(0, 4, 3)(1, 5, 2))) + +dodecahedron = Polyhedron( + Tuple(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19), + Tuple( + Tuple(0, 1, 2, 3, 4), + Tuple(0, 1, 6, 10, 5), + Tuple(1, 2, 7, 11, 6), + Tuple(2, 3, 8, 12, 7), + Tuple(3, 4, 9, 13, 8), + Tuple(0, 4, 9, 14, 5), + Tuple(5, 10, 16, 15, 14), + Tuple(6, 10, 16, 17, 11), + Tuple(7, 11, 17, 18, 12), + Tuple(8, 12, 18, 19, 13), + Tuple(9, 13, 19, 15, 14), + Tuple(15, 16, 17, 18, 19)), + Tuple( + Perm(0, 1, 2, 3, 4)(5, 6, 7, 8, 9)(10, 11, 12, 13, 14)(15, 16, 17, 18, 19), + Perm(0, 5, 10, 6, 1)(2, 4, 14, 16, 11)(3, 9, 15, 17, 7)(8, 13, 19, 18, 12), + Perm(0, 10, 17, 12, 3)(1, 6, 11, 7, 2)(4, 5, 16, 18, 8)(9, 14, 15, 19, 13), + Perm(0, 6, 17, 19, 9)(1, 11, 18, 13, 4)(2, 7, 12, 8, 3)(5, 10, 16, 15, 14), + Perm(0, 2, 12, 19, 14)(1, 7, 18, 15, 5)(3, 8, 13, 9, 4)(6, 11, 17, 16, 10), + Perm(0, 4, 9, 14, 5)(1, 3, 13, 15, 10)(2, 8, 19, 16, 6)(7, 12, 18, 17, 11), + Perm(0, 1)(2, 5)(3, 10)(4, 6)(7, 14)(8, 16)(9, 11)(12, 15)(13, 17)(18, 19), + Perm(0, 7)(1, 2)(3, 6)(4, 11)(5, 12)(8, 10)(9, 17)(13, 16)(14, 18)(15, 19), + Perm(0, 12)(1, 8)(2, 3)(4, 7)(5, 18)(6, 13)(9, 11)(10, 19)(14, 17)(15, 16), + Perm(0, 8)(1, 13)(2, 9)(3, 4)(5, 12)(6, 19)(7, 14)(10, 18)(11, 15)(16, 17), + Perm(0, 4)(1, 9)(2, 14)(3, 5)(6, 13)(7, 15)(8, 10)(11, 19)(12, 16)(17, 18), + Perm(0, 5)(1, 14)(2, 15)(3, 16)(4, 10)(6, 9)(7, 19)(8, 17)(11, 13)(12, 18), + Perm(0, 11)(1, 6)(2, 10)(3, 16)(4, 17)(5, 7)(8, 15)(9, 18)(12, 14)(13, 19), + Perm(0, 18)(1, 12)(2, 7)(3, 11)(4, 17)(5, 19)(6, 8)(9, 16)(10, 13)(14, 15), + Perm(0, 18)(1, 19)(2, 13)(3, 8)(4, 12)(5, 17)(6, 15)(7, 9)(10, 16)(11, 14), + Perm(0, 13)(1, 19)(2, 15)(3, 14)(4, 9)(5, 8)(6, 18)(7, 16)(10, 12)(11, 17), + Perm(0, 16)(1, 15)(2, 19)(3, 18)(4, 17)(5, 10)(6, 14)(7, 13)(8, 12)(9, 11), + Perm(0, 18)(1, 17)(2, 16)(3, 15)(4, 19)(5, 12)(6, 11)(7, 10)(8, 14)(9, 13), + Perm(0, 15)(1, 19)(2, 18)(3, 17)(4, 16)(5, 14)(6, 13)(7, 12)(8, 11)(9, 10), + Perm(0, 17)(1, 16)(2, 15)(3, 19)(4, 18)(5, 11)(6, 10)(7, 14)(8, 13)(9, 12), + Perm(0, 19)(1, 18)(2, 17)(3, 16)(4, 15)(5, 13)(6, 12)(7, 11)(8, 10)(9, 14), + Perm(1, 4, 5)(2, 9, 10)(3, 14, 6)(7, 13, 16)(8, 15, 11)(12, 19, 17), + Perm(19)(0, 6, 2)(3, 5, 11)(4, 10, 7)(8, 14, 17)(9, 16, 12)(13, 15, 18), + Perm(0, 11, 8)(1, 7, 3)(4, 6, 12)(5, 17, 13)(9, 10, 18)(14, 16, 19), + Perm(0, 7, 13)(1, 12, 9)(2, 8, 4)(5, 11, 19)(6, 18, 14)(10, 17, 15), + Perm(0, 3, 9)(1, 8, 14)(2, 13, 5)(6, 12, 15)(7, 19, 10)(11, 18, 16), + Perm(0, 14, 10)(1, 9, 16)(2, 13, 17)(3, 19, 11)(4, 15, 6)(7, 8, 18), + Perm(0, 16, 7)(1, 10, 11)(2, 5, 17)(3, 14, 18)(4, 15, 12)(8, 9, 19), + Perm(0, 16, 13)(1, 17, 8)(2, 11, 12)(3, 6, 18)(4, 10, 19)(5, 15, 9), + Perm(0, 11, 15)(1, 17, 14)(2, 18, 9)(3, 12, 13)(4, 7, 19)(5, 6, 16), + Perm(0, 8, 15)(1, 12, 16)(2, 18, 10)(3, 19, 5)(4, 13, 14)(6, 7, 17))) + +icosahedron = Polyhedron( + Tuple(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11), + Tuple( + Tuple(0, 1, 2), + Tuple(0, 2, 3), + Tuple(0, 3, 4), + Tuple(0, 4, 5), + Tuple(0, 1, 5), + Tuple(1, 6, 7), + Tuple(1, 2, 7), + Tuple(2, 7, 8), + Tuple(2, 3, 8), + Tuple(3, 8, 9), + Tuple(3, 4, 9), + Tuple(4, 9, 10), + Tuple(4, 5, 10), + Tuple(5, 6, 10), + Tuple(1, 5, 6), + Tuple(6, 7, 11), + Tuple(7, 8, 11), + Tuple(8, 9, 11), + Tuple(9, 10, 11), + Tuple(6, 10, 11)), + Tuple( + Perm(11)(1, 2, 3, 4, 5)(6, 7, 8, 9, 10), + Perm(0, 5, 6, 7, 2)(3, 4, 10, 11, 8), + Perm(0, 1, 7, 8, 3)(4, 5, 6, 11, 9), + Perm(0, 2, 8, 9, 4)(1, 7, 11, 10, 5), + Perm(0, 3, 9, 10, 5)(1, 2, 8, 11, 6), + Perm(0, 4, 10, 6, 1)(2, 3, 9, 11, 7), + Perm(0, 1)(2, 5)(3, 6)(4, 7)(8, 10)(9, 11), + Perm(0, 2)(1, 3)(4, 7)(5, 8)(6, 9)(10, 11), + Perm(0, 3)(1, 9)(2, 4)(5, 8)(6, 11)(7, 10), + Perm(0, 4)(1, 9)(2, 10)(3, 5)(6, 8)(7, 11), + Perm(0, 5)(1, 4)(2, 10)(3, 6)(7, 9)(8, 11), + Perm(0, 6)(1, 5)(2, 10)(3, 11)(4, 7)(8, 9), + Perm(0, 7)(1, 2)(3, 6)(4, 11)(5, 8)(9, 10), + Perm(0, 8)(1, 9)(2, 3)(4, 7)(5, 11)(6, 10), + Perm(0, 9)(1, 11)(2, 10)(3, 4)(5, 8)(6, 7), + Perm(0, 10)(1, 9)(2, 11)(3, 6)(4, 5)(7, 8), + Perm(0, 11)(1, 6)(2, 10)(3, 9)(4, 8)(5, 7), + Perm(0, 11)(1, 8)(2, 7)(3, 6)(4, 10)(5, 9), + Perm(0, 11)(1, 10)(2, 9)(3, 8)(4, 7)(5, 6), + Perm(0, 11)(1, 7)(2, 6)(3, 10)(4, 9)(5, 8), + Perm(0, 11)(1, 9)(2, 8)(3, 7)(4, 6)(5, 10), + Perm(0, 5, 1)(2, 4, 6)(3, 10, 7)(8, 9, 11), + Perm(0, 1, 2)(3, 5, 7)(4, 6, 8)(9, 10, 11), + Perm(0, 2, 3)(1, 8, 4)(5, 7, 9)(6, 11, 10), + Perm(0, 3, 4)(1, 8, 10)(2, 9, 5)(6, 7, 11), + Perm(0, 4, 5)(1, 3, 10)(2, 9, 6)(7, 8, 11), + Perm(0, 10, 7)(1, 5, 6)(2, 4, 11)(3, 9, 8), + Perm(0, 6, 8)(1, 7, 2)(3, 5, 11)(4, 10, 9), + Perm(0, 7, 9)(1, 11, 4)(2, 8, 3)(5, 6, 10), + Perm(0, 8, 10)(1, 7, 6)(2, 11, 5)(3, 9, 4), + Perm(0, 9, 6)(1, 3, 11)(2, 8, 7)(4, 10, 5))) + +tetrahedron_faces = [tuple(arg) for arg in tetrahedron.faces] + +cube_faces = [tuple(arg) for arg in cube.faces] + +octahedron_faces = [tuple(arg) for arg in octahedron.faces] + +dodecahedron_faces = [tuple(arg) for arg in dodecahedron.faces] + +icosahedron_faces = [tuple(arg) for arg in icosahedron.faces] diff --git a/lib/python3.12/site-packages/sympy/combinatorics/prufer.py b/lib/python3.12/site-packages/sympy/combinatorics/prufer.py new file mode 100644 index 0000000000000000000000000000000000000000..e389df87cddc0152b2376e18b9f3df2e94d3d2fb --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/prufer.py @@ -0,0 +1,435 @@ +from sympy.core import Basic +from sympy.core.containers import Tuple +from sympy.tensor.array import Array +from sympy.core.sympify import _sympify +from sympy.utilities.iterables import flatten, iterable +from sympy.utilities.misc import as_int + +from collections import defaultdict + + +class Prufer(Basic): + """ + The Prufer correspondence is an algorithm that describes the + bijection between labeled trees and the Prufer code. A Prufer + code of a labeled tree is unique up to isomorphism and has + a length of n - 2. + + Prufer sequences were first used by Heinz Prufer to give a + proof of Cayley's formula. + + References + ========== + + .. [1] https://mathworld.wolfram.com/LabeledTree.html + + """ + _prufer_repr = None + _tree_repr = None + _nodes = None + _rank = None + + @property + def prufer_repr(self): + """Returns Prufer sequence for the Prufer object. + + This sequence is found by removing the highest numbered vertex, + recording the node it was attached to, and continuing until only + two vertices remain. The Prufer sequence is the list of recorded nodes. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]).prufer_repr + [3, 3, 3, 4] + >>> Prufer([1, 0, 0]).prufer_repr + [1, 0, 0] + + See Also + ======== + + to_prufer + + """ + if self._prufer_repr is None: + self._prufer_repr = self.to_prufer(self._tree_repr[:], self.nodes) + return self._prufer_repr + + @property + def tree_repr(self): + """Returns the tree representation of the Prufer object. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]).tree_repr + [[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]] + >>> Prufer([1, 0, 0]).tree_repr + [[1, 2], [0, 1], [0, 3], [0, 4]] + + See Also + ======== + + to_tree + + """ + if self._tree_repr is None: + self._tree_repr = self.to_tree(self._prufer_repr[:]) + return self._tree_repr + + @property + def nodes(self): + """Returns the number of nodes in the tree. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]).nodes + 6 + >>> Prufer([1, 0, 0]).nodes + 5 + + """ + return self._nodes + + @property + def rank(self): + """Returns the rank of the Prufer sequence. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> p = Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]) + >>> p.rank + 778 + >>> p.next(1).rank + 779 + >>> p.prev().rank + 777 + + See Also + ======== + + prufer_rank, next, prev, size + + """ + if self._rank is None: + self._rank = self.prufer_rank() + return self._rank + + @property + def size(self): + """Return the number of possible trees of this Prufer object. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> Prufer([0]*4).size == Prufer([6]*4).size == 1296 + True + + See Also + ======== + + prufer_rank, rank, next, prev + + """ + return self.prev(self.rank).prev().rank + 1 + + @staticmethod + def to_prufer(tree, n): + """Return the Prufer sequence for a tree given as a list of edges where + ``n`` is the number of nodes in the tree. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> a = Prufer([[0, 1], [0, 2], [0, 3]]) + >>> a.prufer_repr + [0, 0] + >>> Prufer.to_prufer([[0, 1], [0, 2], [0, 3]], 4) + [0, 0] + + See Also + ======== + prufer_repr: returns Prufer sequence of a Prufer object. + + """ + d = defaultdict(int) + L = [] + for edge in tree: + # Increment the value of the corresponding + # node in the degree list as we encounter an + # edge involving it. + d[edge[0]] += 1 + d[edge[1]] += 1 + for i in range(n - 2): + # find the smallest leaf + for x in range(n): + if d[x] == 1: + break + # find the node it was connected to + y = None + for edge in tree: + if x == edge[0]: + y = edge[1] + elif x == edge[1]: + y = edge[0] + if y is not None: + break + # record and update + L.append(y) + for j in (x, y): + d[j] -= 1 + if not d[j]: + d.pop(j) + tree.remove(edge) + return L + + @staticmethod + def to_tree(prufer): + """Return the tree (as a list of edges) of the given Prufer sequence. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> a = Prufer([0, 2], 4) + >>> a.tree_repr + [[0, 1], [0, 2], [2, 3]] + >>> Prufer.to_tree([0, 2]) + [[0, 1], [0, 2], [2, 3]] + + References + ========== + + .. [1] https://hamberg.no/erlend/posts/2010-11-06-prufer-sequence-compact-tree-representation.html + + See Also + ======== + tree_repr: returns tree representation of a Prufer object. + + """ + tree = [] + last = [] + n = len(prufer) + 2 + d = defaultdict(lambda: 1) + for p in prufer: + d[p] += 1 + for i in prufer: + for j in range(n): + # find the smallest leaf (degree = 1) + if d[j] == 1: + break + # (i, j) is the new edge that we append to the tree + # and remove from the degree dictionary + d[i] -= 1 + d[j] -= 1 + tree.append(sorted([i, j])) + last = [i for i in range(n) if d[i] == 1] or [0, 1] + tree.append(last) + + return tree + + @staticmethod + def edges(*runs): + """Return a list of edges and the number of nodes from the given runs + that connect nodes in an integer-labelled tree. + + All node numbers will be shifted so that the minimum node is 0. It is + not a problem if edges are repeated in the runs; only unique edges are + returned. There is no assumption made about what the range of the node + labels should be, but all nodes from the smallest through the largest + must be present. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> Prufer.edges([1, 2, 3], [2, 4, 5]) # a T + ([[0, 1], [1, 2], [1, 3], [3, 4]], 5) + + Duplicate edges are removed: + + >>> Prufer.edges([0, 1, 2, 3], [1, 4, 5], [1, 4, 6]) # a K + ([[0, 1], [1, 2], [1, 4], [2, 3], [4, 5], [4, 6]], 7) + + """ + e = set() + nmin = runs[0][0] + for r in runs: + for i in range(len(r) - 1): + a, b = r[i: i + 2] + if b < a: + a, b = b, a + e.add((a, b)) + rv = [] + got = set() + nmin = nmax = None + for ei in e: + got.update(ei) + nmin = min(ei[0], nmin) if nmin is not None else ei[0] + nmax = max(ei[1], nmax) if nmax is not None else ei[1] + rv.append(list(ei)) + missing = set(range(nmin, nmax + 1)) - got + if missing: + missing = [i + nmin for i in missing] + if len(missing) == 1: + msg = 'Node %s is missing.' % missing.pop() + else: + msg = 'Nodes %s are missing.' % sorted(missing) + raise ValueError(msg) + if nmin != 0: + for i, ei in enumerate(rv): + rv[i] = [n - nmin for n in ei] + nmax -= nmin + return sorted(rv), nmax + 1 + + def prufer_rank(self): + """Computes the rank of a Prufer sequence. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> a = Prufer([[0, 1], [0, 2], [0, 3]]) + >>> a.prufer_rank() + 0 + + See Also + ======== + + rank, next, prev, size + + """ + r = 0 + p = 1 + for i in range(self.nodes - 3, -1, -1): + r += p*self.prufer_repr[i] + p *= self.nodes + return r + + @classmethod + def unrank(self, rank, n): + """Finds the unranked Prufer sequence. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> Prufer.unrank(0, 4) + Prufer([0, 0]) + + """ + n, rank = as_int(n), as_int(rank) + L = defaultdict(int) + for i in range(n - 3, -1, -1): + L[i] = rank % n + rank = (rank - L[i])//n + return Prufer([L[i] for i in range(len(L))]) + + def __new__(cls, *args, **kw_args): + """The constructor for the Prufer object. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + + A Prufer object can be constructed from a list of edges: + + >>> a = Prufer([[0, 1], [0, 2], [0, 3]]) + >>> a.prufer_repr + [0, 0] + + If the number of nodes is given, no checking of the nodes will + be performed; it will be assumed that nodes 0 through n - 1 are + present: + + >>> Prufer([[0, 1], [0, 2], [0, 3]], 4) + Prufer([[0, 1], [0, 2], [0, 3]], 4) + + A Prufer object can be constructed from a Prufer sequence: + + >>> b = Prufer([1, 3]) + >>> b.tree_repr + [[0, 1], [1, 3], [2, 3]] + + """ + arg0 = Array(args[0]) if args[0] else Tuple() + args = (arg0,) + tuple(_sympify(arg) for arg in args[1:]) + ret_obj = Basic.__new__(cls, *args, **kw_args) + args = [list(args[0])] + if args[0] and iterable(args[0][0]): + if not args[0][0]: + raise ValueError( + 'Prufer expects at least one edge in the tree.') + if len(args) > 1: + nnodes = args[1] + else: + nodes = set(flatten(args[0])) + nnodes = max(nodes) + 1 + if nnodes != len(nodes): + missing = set(range(nnodes)) - nodes + if len(missing) == 1: + msg = 'Node %s is missing.' % missing.pop() + else: + msg = 'Nodes %s are missing.' % sorted(missing) + raise ValueError(msg) + ret_obj._tree_repr = [list(i) for i in args[0]] + ret_obj._nodes = nnodes + else: + ret_obj._prufer_repr = args[0] + ret_obj._nodes = len(ret_obj._prufer_repr) + 2 + return ret_obj + + def next(self, delta=1): + """Generates the Prufer sequence that is delta beyond the current one. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> a = Prufer([[0, 1], [0, 2], [0, 3]]) + >>> b = a.next(1) # == a.next() + >>> b.tree_repr + [[0, 2], [0, 1], [1, 3]] + >>> b.rank + 1 + + See Also + ======== + + prufer_rank, rank, prev, size + + """ + return Prufer.unrank(self.rank + delta, self.nodes) + + def prev(self, delta=1): + """Generates the Prufer sequence that is -delta before the current one. + + Examples + ======== + + >>> from sympy.combinatorics.prufer import Prufer + >>> a = Prufer([[0, 1], [1, 2], [2, 3], [1, 4]]) + >>> a.rank + 36 + >>> b = a.prev() + >>> b + Prufer([1, 2, 0]) + >>> b.rank + 35 + + See Also + ======== + + prufer_rank, rank, next, size + + """ + return Prufer.unrank(self.rank -delta, self.nodes) diff --git a/lib/python3.12/site-packages/sympy/combinatorics/rewritingsystem_fsm.py b/lib/python3.12/site-packages/sympy/combinatorics/rewritingsystem_fsm.py new file mode 100644 index 0000000000000000000000000000000000000000..21916530040ac321180692d1a0811da4ae36a056 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/rewritingsystem_fsm.py @@ -0,0 +1,60 @@ +class State: + ''' + A representation of a state managed by a ``StateMachine``. + + Attributes: + name (instance of FreeGroupElement or string) -- State name which is also assigned to the Machine. + transisitons (OrderedDict) -- Represents all the transitions of the state object. + state_type (string) -- Denotes the type (accept/start/dead) of the state. + rh_rule (instance of FreeGroupElement) -- right hand rule for dead state. + state_machine (instance of StateMachine object) -- The finite state machine that the state belongs to. + ''' + + def __init__(self, name, state_machine, state_type=None, rh_rule=None): + self.name = name + self.transitions = {} + self.state_machine = state_machine + self.state_type = state_type[0] + self.rh_rule = rh_rule + + def add_transition(self, letter, state): + ''' + Add a transition from the current state to a new state. + + Keyword Arguments: + letter -- The alphabet element the current state reads to make the state transition. + state -- This will be an instance of the State object which represents a new state after in the transition after the alphabet is read. + + ''' + self.transitions[letter] = state + +class StateMachine: + ''' + Representation of a finite state machine the manages the states and the transitions of the automaton. + + Attributes: + states (dictionary) -- Collection of all registered `State` objects. + name (str) -- Name of the state machine. + ''' + + def __init__(self, name, automaton_alphabet): + self.name = name + self.automaton_alphabet = automaton_alphabet + self.states = {} # Contains all the states in the machine. + self.add_state('start', state_type='s') + + def add_state(self, state_name, state_type=None, rh_rule=None): + ''' + Instantiate a state object and stores it in the 'states' dictionary. + + Arguments: + state_name (instance of FreeGroupElement or string) -- name of the new states. + state_type (string) -- Denotes the type (accept/start/dead) of the state added. + rh_rule (instance of FreeGroupElement) -- right hand rule for dead state. + + ''' + new_state = State(state_name, self, state_type, rh_rule) + self.states[state_name] = new_state + + def __repr__(self): + return "%s" % (self.name) diff --git a/lib/python3.12/site-packages/sympy/combinatorics/schur_number.py b/lib/python3.12/site-packages/sympy/combinatorics/schur_number.py new file mode 100644 index 0000000000000000000000000000000000000000..83aac98e543d4b54d4e6af17adca6e4f4de1b9ac --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/schur_number.py @@ -0,0 +1,160 @@ +""" +The Schur number S(k) is the largest integer n for which the interval [1,n] +can be partitioned into k sum-free sets.(https://mathworld.wolfram.com/SchurNumber.html) +""" +import math +from sympy.core import S +from sympy.core.basic import Basic +from sympy.core.function import Function +from sympy.core.numbers import Integer + + +class SchurNumber(Function): + r""" + This function creates a SchurNumber object + which is evaluated for `k \le 5` otherwise only + the lower bound information can be retrieved. + + Examples + ======== + + >>> from sympy.combinatorics.schur_number import SchurNumber + + Since S(3) = 13, hence the output is a number + >>> SchurNumber(3) + 13 + + We do not know the Schur number for values greater than 5, hence + only the object is returned + >>> SchurNumber(6) + SchurNumber(6) + + Now, the lower bound information can be retrieved using lower_bound() + method + >>> SchurNumber(6).lower_bound() + 536 + + """ + + @classmethod + def eval(cls, k): + if k.is_Number: + if k is S.Infinity: + return S.Infinity + if k.is_zero: + return S.Zero + if not k.is_integer or k.is_negative: + raise ValueError("k should be a positive integer") + first_known_schur_numbers = {1: 1, 2: 4, 3: 13, 4: 44, 5: 160} + if k <= 5: + return Integer(first_known_schur_numbers[k]) + + def lower_bound(self): + f_ = self.args[0] + # Improved lower bounds known for S(6) and S(7) + if f_ == 6: + return Integer(536) + if f_ == 7: + return Integer(1680) + # For other cases, use general expression + if f_.is_Integer: + return 3*self.func(f_ - 1).lower_bound() - 1 + return (3**f_ - 1)/2 + + +def _schur_subsets_number(n): + + if n is S.Infinity: + raise ValueError("Input must be finite") + if n <= 0: + raise ValueError("n must be a non-zero positive integer.") + elif n <= 3: + min_k = 1 + else: + min_k = math.ceil(math.log(2*n + 1, 3)) + + return Integer(min_k) + + +def schur_partition(n): + """ + + This function returns the partition in the minimum number of sum-free subsets + according to the lower bound given by the Schur Number. + + Parameters + ========== + + n: a number + n is the upper limit of the range [1, n] for which we need to find and + return the minimum number of free subsets according to the lower bound + of schur number + + Returns + ======= + + List of lists + List of the minimum number of sum-free subsets + + Notes + ===== + + It is possible for some n to make the partition into less + subsets since the only known Schur numbers are: + S(1) = 1, S(2) = 4, S(3) = 13, S(4) = 44. + e.g for n = 44 the lower bound from the function above is 5 subsets but it has been proven + that can be done with 4 subsets. + + Examples + ======== + + For n = 1, 2, 3 the answer is the set itself + + >>> from sympy.combinatorics.schur_number import schur_partition + >>> schur_partition(2) + [[1, 2]] + + For n > 3, the answer is the minimum number of sum-free subsets: + + >>> schur_partition(5) + [[3, 2], [5], [1, 4]] + + >>> schur_partition(8) + [[3, 2], [6, 5, 8], [1, 4, 7]] + """ + + if isinstance(n, Basic) and not n.is_Number: + raise ValueError("Input value must be a number") + + number_of_subsets = _schur_subsets_number(n) + if n == 1: + sum_free_subsets = [[1]] + elif n == 2: + sum_free_subsets = [[1, 2]] + elif n == 3: + sum_free_subsets = [[1, 2, 3]] + else: + sum_free_subsets = [[1, 4], [2, 3]] + + while len(sum_free_subsets) < number_of_subsets: + sum_free_subsets = _generate_next_list(sum_free_subsets, n) + missed_elements = [3*k + 1 for k in range(len(sum_free_subsets), (n-1)//3 + 1)] + sum_free_subsets[-1] += missed_elements + + return sum_free_subsets + + +def _generate_next_list(current_list, n): + new_list = [] + + for item in current_list: + temp_1 = [number*3 for number in item if number*3 <= n] + temp_2 = [number*3 - 1 for number in item if number*3 - 1 <= n] + new_item = temp_1 + temp_2 + new_list.append(new_item) + + last_list = [3*k + 1 for k in range(len(current_list)+1) if 3*k + 1 <= n] + new_list.append(last_list) + current_list = new_list + + return current_list diff --git a/lib/python3.12/site-packages/sympy/combinatorics/subsets.py b/lib/python3.12/site-packages/sympy/combinatorics/subsets.py new file mode 100644 index 0000000000000000000000000000000000000000..e540cb2395cb27e04c9d513831cb834a05ec2abd --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/subsets.py @@ -0,0 +1,619 @@ +from itertools import combinations + +from sympy.combinatorics.graycode import GrayCode + + +class Subset(): + """ + Represents a basic subset object. + + Explanation + =========== + + We generate subsets using essentially two techniques, + binary enumeration and lexicographic enumeration. + The Subset class takes two arguments, the first one + describes the initial subset to consider and the second + describes the superset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.next_binary().subset + ['b'] + >>> a.prev_binary().subset + ['c'] + """ + + _rank_binary = None + _rank_lex = None + _rank_graycode = None + _subset = None + _superset = None + + def __new__(cls, subset, superset): + """ + Default constructor. + + It takes the ``subset`` and its ``superset`` as its parameters. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.subset + ['c', 'd'] + >>> a.superset + ['a', 'b', 'c', 'd'] + >>> a.size + 2 + """ + if len(subset) > len(superset): + raise ValueError('Invalid arguments have been provided. The ' + 'superset must be larger than the subset.') + for elem in subset: + if elem not in superset: + raise ValueError('The superset provided is invalid as it does ' + 'not contain the element {}'.format(elem)) + obj = object.__new__(cls) + obj._subset = subset + obj._superset = superset + return obj + + def __eq__(self, other): + """Return a boolean indicating whether a == b on the basis of + whether both objects are of the class Subset and if the values + of the subset and superset attributes are the same. + """ + if not isinstance(other, Subset): + return NotImplemented + return self.subset == other.subset and self.superset == other.superset + + def iterate_binary(self, k): + """ + This is a helper function. It iterates over the + binary subsets by ``k`` steps. This variable can be + both positive or negative. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.iterate_binary(-2).subset + ['d'] + >>> a = Subset(['a', 'b', 'c'], ['a', 'b', 'c', 'd']) + >>> a.iterate_binary(2).subset + [] + + See Also + ======== + + next_binary, prev_binary + """ + bin_list = Subset.bitlist_from_subset(self.subset, self.superset) + n = (int(''.join(bin_list), 2) + k) % 2**self.superset_size + bits = bin(n)[2:].rjust(self.superset_size, '0') + return Subset.subset_from_bitlist(self.superset, bits) + + def next_binary(self): + """ + Generates the next binary ordered subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.next_binary().subset + ['b'] + >>> a = Subset(['a', 'b', 'c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.next_binary().subset + [] + + See Also + ======== + + prev_binary, iterate_binary + """ + return self.iterate_binary(1) + + def prev_binary(self): + """ + Generates the previous binary ordered subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset([], ['a', 'b', 'c', 'd']) + >>> a.prev_binary().subset + ['a', 'b', 'c', 'd'] + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.prev_binary().subset + ['c'] + + See Also + ======== + + next_binary, iterate_binary + """ + return self.iterate_binary(-1) + + def next_lexicographic(self): + """ + Generates the next lexicographically ordered subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.next_lexicographic().subset + ['d'] + >>> a = Subset(['d'], ['a', 'b', 'c', 'd']) + >>> a.next_lexicographic().subset + [] + + See Also + ======== + + prev_lexicographic + """ + i = self.superset_size - 1 + indices = Subset.subset_indices(self.subset, self.superset) + + if i in indices: + if i - 1 in indices: + indices.remove(i - 1) + else: + indices.remove(i) + i = i - 1 + while i >= 0 and i not in indices: + i = i - 1 + if i >= 0: + indices.remove(i) + indices.append(i+1) + else: + while i not in indices and i >= 0: + i = i - 1 + indices.append(i + 1) + + ret_set = [] + super_set = self.superset + for i in indices: + ret_set.append(super_set[i]) + return Subset(ret_set, super_set) + + def prev_lexicographic(self): + """ + Generates the previous lexicographically ordered subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset([], ['a', 'b', 'c', 'd']) + >>> a.prev_lexicographic().subset + ['d'] + >>> a = Subset(['c','d'], ['a', 'b', 'c', 'd']) + >>> a.prev_lexicographic().subset + ['c'] + + See Also + ======== + + next_lexicographic + """ + i = self.superset_size - 1 + indices = Subset.subset_indices(self.subset, self.superset) + + while i >= 0 and i not in indices: + i = i - 1 + + if i == 0 or i - 1 in indices: + indices.remove(i) + else: + if i >= 0: + indices.remove(i) + indices.append(i - 1) + indices.append(self.superset_size - 1) + + ret_set = [] + super_set = self.superset + for i in indices: + ret_set.append(super_set[i]) + return Subset(ret_set, super_set) + + def iterate_graycode(self, k): + """ + Helper function used for prev_gray and next_gray. + It performs ``k`` step overs to get the respective Gray codes. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset([1, 2, 3], [1, 2, 3, 4]) + >>> a.iterate_graycode(3).subset + [1, 4] + >>> a.iterate_graycode(-2).subset + [1, 2, 4] + + See Also + ======== + + next_gray, prev_gray + """ + unranked_code = GrayCode.unrank(self.superset_size, + (self.rank_gray + k) % self.cardinality) + return Subset.subset_from_bitlist(self.superset, + unranked_code) + + def next_gray(self): + """ + Generates the next Gray code ordered subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset([1, 2, 3], [1, 2, 3, 4]) + >>> a.next_gray().subset + [1, 3] + + See Also + ======== + + iterate_graycode, prev_gray + """ + return self.iterate_graycode(1) + + def prev_gray(self): + """ + Generates the previous Gray code ordered subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset([2, 3, 4], [1, 2, 3, 4, 5]) + >>> a.prev_gray().subset + [2, 3, 4, 5] + + See Also + ======== + + iterate_graycode, next_gray + """ + return self.iterate_graycode(-1) + + @property + def rank_binary(self): + """ + Computes the binary ordered rank. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset([], ['a','b','c','d']) + >>> a.rank_binary + 0 + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.rank_binary + 3 + + See Also + ======== + + iterate_binary, unrank_binary + """ + if self._rank_binary is None: + self._rank_binary = int("".join( + Subset.bitlist_from_subset(self.subset, + self.superset)), 2) + return self._rank_binary + + @property + def rank_lexicographic(self): + """ + Computes the lexicographic ranking of the subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.rank_lexicographic + 14 + >>> a = Subset([2, 4, 5], [1, 2, 3, 4, 5, 6]) + >>> a.rank_lexicographic + 43 + """ + if self._rank_lex is None: + def _ranklex(self, subset_index, i, n): + if subset_index == [] or i > n: + return 0 + if i in subset_index: + subset_index.remove(i) + return 1 + _ranklex(self, subset_index, i + 1, n) + return 2**(n - i - 1) + _ranklex(self, subset_index, i + 1, n) + indices = Subset.subset_indices(self.subset, self.superset) + self._rank_lex = _ranklex(self, indices, 0, self.superset_size) + return self._rank_lex + + @property + def rank_gray(self): + """ + Computes the Gray code ranking of the subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c','d'], ['a','b','c','d']) + >>> a.rank_gray + 2 + >>> a = Subset([2, 4, 5], [1, 2, 3, 4, 5, 6]) + >>> a.rank_gray + 27 + + See Also + ======== + + iterate_graycode, unrank_gray + """ + if self._rank_graycode is None: + bits = Subset.bitlist_from_subset(self.subset, self.superset) + self._rank_graycode = GrayCode(len(bits), start=bits).rank + return self._rank_graycode + + @property + def subset(self): + """ + Gets the subset represented by the current instance. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.subset + ['c', 'd'] + + See Also + ======== + + superset, size, superset_size, cardinality + """ + return self._subset + + @property + def size(self): + """ + Gets the size of the subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.size + 2 + + See Also + ======== + + subset, superset, superset_size, cardinality + """ + return len(self.subset) + + @property + def superset(self): + """ + Gets the superset of the subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.superset + ['a', 'b', 'c', 'd'] + + See Also + ======== + + subset, size, superset_size, cardinality + """ + return self._superset + + @property + def superset_size(self): + """ + Returns the size of the superset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.superset_size + 4 + + See Also + ======== + + subset, superset, size, cardinality + """ + return len(self.superset) + + @property + def cardinality(self): + """ + Returns the number of all possible subsets. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> a = Subset(['c', 'd'], ['a', 'b', 'c', 'd']) + >>> a.cardinality + 16 + + See Also + ======== + + subset, superset, size, superset_size + """ + return 2**(self.superset_size) + + @classmethod + def subset_from_bitlist(self, super_set, bitlist): + """ + Gets the subset defined by the bitlist. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> Subset.subset_from_bitlist(['a', 'b', 'c', 'd'], '0011').subset + ['c', 'd'] + + See Also + ======== + + bitlist_from_subset + """ + if len(super_set) != len(bitlist): + raise ValueError("The sizes of the lists are not equal") + ret_set = [] + for i in range(len(bitlist)): + if bitlist[i] == '1': + ret_set.append(super_set[i]) + return Subset(ret_set, super_set) + + @classmethod + def bitlist_from_subset(self, subset, superset): + """ + Gets the bitlist corresponding to a subset. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> Subset.bitlist_from_subset(['c', 'd'], ['a', 'b', 'c', 'd']) + '0011' + + See Also + ======== + + subset_from_bitlist + """ + bitlist = ['0'] * len(superset) + if isinstance(subset, Subset): + subset = subset.subset + for i in Subset.subset_indices(subset, superset): + bitlist[i] = '1' + return ''.join(bitlist) + + @classmethod + def unrank_binary(self, rank, superset): + """ + Gets the binary ordered subset of the specified rank. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> Subset.unrank_binary(4, ['a', 'b', 'c', 'd']).subset + ['b'] + + See Also + ======== + + iterate_binary, rank_binary + """ + bits = bin(rank)[2:].rjust(len(superset), '0') + return Subset.subset_from_bitlist(superset, bits) + + @classmethod + def unrank_gray(self, rank, superset): + """ + Gets the Gray code ordered subset of the specified rank. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> Subset.unrank_gray(4, ['a', 'b', 'c']).subset + ['a', 'b'] + >>> Subset.unrank_gray(0, ['a', 'b', 'c']).subset + [] + + See Also + ======== + + iterate_graycode, rank_gray + """ + graycode_bitlist = GrayCode.unrank(len(superset), rank) + return Subset.subset_from_bitlist(superset, graycode_bitlist) + + @classmethod + def subset_indices(self, subset, superset): + """Return indices of subset in superset in a list; the list is empty + if all elements of ``subset`` are not in ``superset``. + + Examples + ======== + + >>> from sympy.combinatorics import Subset + >>> superset = [1, 3, 2, 5, 4] + >>> Subset.subset_indices([3, 2, 1], superset) + [1, 2, 0] + >>> Subset.subset_indices([1, 6], superset) + [] + >>> Subset.subset_indices([], superset) + [] + + """ + a, b = superset, subset + sb = set(b) + d = {} + for i, ai in enumerate(a): + if ai in sb: + d[ai] = i + sb.remove(ai) + if not sb: + break + else: + return [] + return [d[bi] for bi in b] + + +def ksubsets(superset, k): + """ + Finds the subsets of size ``k`` in lexicographic order. + + This uses the itertools generator. + + Examples + ======== + + >>> from sympy.combinatorics.subsets import ksubsets + >>> list(ksubsets([1, 2, 3], 2)) + [(1, 2), (1, 3), (2, 3)] + >>> list(ksubsets([1, 2, 3, 4, 5], 2)) + [(1, 2), (1, 3), (1, 4), (1, 5), (2, 3), (2, 4), \ + (2, 5), (3, 4), (3, 5), (4, 5)] + + See Also + ======== + + Subset + """ + return combinations(superset, k) diff --git a/lib/python3.12/site-packages/sympy/combinatorics/tensor_can.py b/lib/python3.12/site-packages/sympy/combinatorics/tensor_can.py new file mode 100644 index 0000000000000000000000000000000000000000..984d69d9ecd2bb7b222e275da14b16dfcc58c3ae --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/tensor_can.py @@ -0,0 +1,1190 @@ +from sympy.combinatorics.permutations import Permutation, _af_rmul, \ + _af_invert, _af_new +from sympy.combinatorics.perm_groups import PermutationGroup, _orbit, \ + _orbit_transversal +from sympy.combinatorics.util import _distribute_gens_by_base, \ + _orbits_transversals_from_bsgs + +""" + References for tensor canonicalization: + + [1] R. Portugal "Algorithmic simplification of tensor expressions", + J. Phys. A 32 (1999) 7779-7789 + + [2] R. Portugal, B.F. Svaiter "Group-theoretic Approach for Symbolic + Tensor Manipulation: I. Free Indices" + arXiv:math-ph/0107031v1 + + [3] L.R.U. Manssur, R. Portugal "Group-theoretic Approach for Symbolic + Tensor Manipulation: II. Dummy Indices" + arXiv:math-ph/0107032v1 + + [4] xperm.c part of XPerm written by J. M. Martin-Garcia + http://www.xact.es/index.html +""" + + +def dummy_sgs(dummies, sym, n): + """ + Return the strong generators for dummy indices. + + Parameters + ========== + + dummies : List of dummy indices. + `dummies[2k], dummies[2k+1]` are paired indices. + In base form, the dummy indices are always in + consecutive positions. + sym : symmetry under interchange of contracted dummies:: + * None no symmetry + * 0 commuting + * 1 anticommuting + + n : number of indices + + Examples + ======== + + >>> from sympy.combinatorics.tensor_can import dummy_sgs + >>> dummy_sgs(list(range(2, 8)), 0, 8) + [[0, 1, 3, 2, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 5, 4, 6, 7, 8, 9], + [0, 1, 2, 3, 4, 5, 7, 6, 8, 9], [0, 1, 4, 5, 2, 3, 6, 7, 8, 9], + [0, 1, 2, 3, 6, 7, 4, 5, 8, 9]] + """ + if len(dummies) > n: + raise ValueError("List too large") + res = [] + # exchange of contravariant and covariant indices + if sym is not None: + for j in dummies[::2]: + a = list(range(n + 2)) + if sym == 1: + a[n] = n + 1 + a[n + 1] = n + a[j], a[j + 1] = a[j + 1], a[j] + res.append(a) + # rename dummy indices + for j in dummies[:-3:2]: + a = list(range(n + 2)) + a[j:j + 4] = a[j + 2], a[j + 3], a[j], a[j + 1] + res.append(a) + return res + + +def _min_dummies(dummies, sym, indices): + """ + Return list of minima of the orbits of indices in group of dummies. + See ``double_coset_can_rep`` for the description of ``dummies`` and ``sym``. + ``indices`` is the initial list of dummy indices. + + Examples + ======== + + >>> from sympy.combinatorics.tensor_can import _min_dummies + >>> _min_dummies([list(range(2, 8))], [0], list(range(10))) + [0, 1, 2, 2, 2, 2, 2, 2, 8, 9] + """ + num_types = len(sym) + m = [min(dx) if dx else None for dx in dummies] + res = indices[:] + for i in range(num_types): + for c, i in enumerate(indices): + for j in range(num_types): + if i in dummies[j]: + res[c] = m[j] + break + return res + + +def _trace_S(s, j, b, S_cosets): + """ + Return the representative h satisfying s[h[b]] == j + + If there is not such a representative return None + """ + for h in S_cosets[b]: + if s[h[b]] == j: + return h + return None + + +def _trace_D(gj, p_i, Dxtrav): + """ + Return the representative h satisfying h[gj] == p_i + + If there is not such a representative return None + """ + for h in Dxtrav: + if h[gj] == p_i: + return h + return None + + +def _dumx_remove(dumx, dumx_flat, p0): + """ + remove p0 from dumx + """ + res = [] + for dx in dumx: + if p0 not in dx: + res.append(dx) + continue + k = dx.index(p0) + if k % 2 == 0: + p0_paired = dx[k + 1] + else: + p0_paired = dx[k - 1] + dx.remove(p0) + dx.remove(p0_paired) + dumx_flat.remove(p0) + dumx_flat.remove(p0_paired) + res.append(dx) + + +def transversal2coset(size, base, transversal): + a = [] + j = 0 + for i in range(size): + if i in base: + a.append(sorted(transversal[j].values())) + j += 1 + else: + a.append([list(range(size))]) + j = len(a) - 1 + while a[j] == [list(range(size))]: + j -= 1 + return a[:j + 1] + + +def double_coset_can_rep(dummies, sym, b_S, sgens, S_transversals, g): + r""" + Butler-Portugal algorithm for tensor canonicalization with dummy indices. + + Parameters + ========== + + dummies + list of lists of dummy indices, + one list for each type of index; + the dummy indices are put in order contravariant, covariant + [d0, -d0, d1, -d1, ...]. + + sym + list of the symmetries of the index metric for each type. + + possible symmetries of the metrics + * 0 symmetric + * 1 antisymmetric + * None no symmetry + + b_S + base of a minimal slot symmetry BSGS. + + sgens + generators of the slot symmetry BSGS. + + S_transversals + transversals for the slot BSGS. + + g + permutation representing the tensor. + + Returns + ======= + + Return 0 if the tensor is zero, else return the array form of + the permutation representing the canonical form of the tensor. + + Notes + ===== + + A tensor with dummy indices can be represented in a number + of equivalent ways which typically grows exponentially with + the number of indices. To be able to establish if two tensors + with many indices are equal becomes computationally very slow + in absence of an efficient algorithm. + + The Butler-Portugal algorithm [3] is an efficient algorithm to + put tensors in canonical form, solving the above problem. + + Portugal observed that a tensor can be represented by a permutation, + and that the class of tensors equivalent to it under slot and dummy + symmetries is equivalent to the double coset `D*g*S` + (Note: in this documentation we use the conventions for multiplication + of permutations p, q with (p*q)(i) = p[q[i]] which is opposite + to the one used in the Permutation class) + + Using the algorithm by Butler to find a representative of the + double coset one can find a canonical form for the tensor. + + To see this correspondence, + let `g` be a permutation in array form; a tensor with indices `ind` + (the indices including both the contravariant and the covariant ones) + can be written as + + `t = T(ind[g[0]], \dots, ind[g[n-1]])`, + + where `n = len(ind)`; + `g` has size `n + 2`, the last two indices for the sign of the tensor + (trick introduced in [4]). + + A slot symmetry transformation `s` is a permutation acting on the slots + `t \rightarrow T(ind[(g*s)[0]], \dots, ind[(g*s)[n-1]])` + + A dummy symmetry transformation acts on `ind` + `t \rightarrow T(ind[(d*g)[0]], \dots, ind[(d*g)[n-1]])` + + Being interested only in the transformations of the tensor under + these symmetries, one can represent the tensor by `g`, which transforms + as + + `g -> d*g*s`, so it belongs to the coset `D*g*S`, or in other words + to the set of all permutations allowed by the slot and dummy symmetries. + + Let us explain the conventions by an example. + + Given a tensor `T^{d3 d2 d1}{}_{d1 d2 d3}` with the slot symmetries + `T^{a0 a1 a2 a3 a4 a5} = -T^{a2 a1 a0 a3 a4 a5}` + + `T^{a0 a1 a2 a3 a4 a5} = -T^{a4 a1 a2 a3 a0 a5}` + + and symmetric metric, find the tensor equivalent to it which + is the lowest under the ordering of indices: + lexicographic ordering `d1, d2, d3` and then contravariant + before covariant index; that is the canonical form of the tensor. + + The canonical form is `-T^{d1 d2 d3}{}_{d1 d2 d3}` + obtained using `T^{a0 a1 a2 a3 a4 a5} = -T^{a2 a1 a0 a3 a4 a5}`. + + To convert this problem in the input for this function, + use the following ordering of the index names + (- for covariant for short) `d1, -d1, d2, -d2, d3, -d3` + + `T^{d3 d2 d1}{}_{d1 d2 d3}` corresponds to `g = [4, 2, 0, 1, 3, 5, 6, 7]` + where the last two indices are for the sign + + `sgens = [Permutation(0, 2)(6, 7), Permutation(0, 4)(6, 7)]` + + sgens[0] is the slot symmetry `-(0, 2)` + `T^{a0 a1 a2 a3 a4 a5} = -T^{a2 a1 a0 a3 a4 a5}` + + sgens[1] is the slot symmetry `-(0, 4)` + `T^{a0 a1 a2 a3 a4 a5} = -T^{a4 a1 a2 a3 a0 a5}` + + The dummy symmetry group D is generated by the strong base generators + `[(0, 1), (2, 3), (4, 5), (0, 2)(1, 3), (0, 4)(1, 5)]` + where the first three interchange covariant and contravariant + positions of the same index (d1 <-> -d1) and the last two interchange + the dummy indices themselves (d1 <-> d2). + + The dummy symmetry acts from the left + `d = [1, 0, 2, 3, 4, 5, 6, 7]` exchange `d1 \leftrightarrow -d1` + `T^{d3 d2 d1}{}_{d1 d2 d3} == T^{d3 d2}{}_{d1}{}^{d1}{}_{d2 d3}` + + `g=[4, 2, 0, 1, 3, 5, 6, 7] -> [4, 2, 1, 0, 3, 5, 6, 7] = _af_rmul(d, g)` + which differs from `_af_rmul(g, d)`. + + The slot symmetry acts from the right + `s = [2, 1, 0, 3, 4, 5, 7, 6]` exchanges slots 0 and 2 and changes sign + `T^{d3 d2 d1}{}_{d1 d2 d3} == -T^{d1 d2 d3}{}_{d1 d2 d3}` + + `g=[4,2,0,1,3,5,6,7] -> [0, 2, 4, 1, 3, 5, 7, 6] = _af_rmul(g, s)` + + Example in which the tensor is zero, same slot symmetries as above: + `T^{d2}{}_{d1 d3}{}^{d1 d3}{}_{d2}` + + `= -T^{d3}{}_{d1 d3}{}^{d1 d2}{}_{d2}` under slot symmetry `-(0,4)`; + + `= T_{d3 d1}{}^{d3}{}^{d1 d2}{}_{d2}` under slot symmetry `-(0,2)`; + + `= T^{d3}{}_{d1 d3}{}^{d1 d2}{}_{d2}` symmetric metric; + + `= 0` since two of these lines have tensors differ only for the sign. + + The double coset D*g*S consists of permutations `h = d*g*s` corresponding + to equivalent tensors; if there are two `h` which are the same apart + from the sign, return zero; otherwise + choose as representative the tensor with indices + ordered lexicographically according to `[d1, -d1, d2, -d2, d3, -d3]` + that is ``rep = min(D*g*S) = min([d*g*s for d in D for s in S])`` + + The indices are fixed one by one; first choose the lowest index + for slot 0, then the lowest remaining index for slot 1, etc. + Doing this one obtains a chain of stabilizers + + `S \rightarrow S_{b0} \rightarrow S_{b0,b1} \rightarrow \dots` and + `D \rightarrow D_{p0} \rightarrow D_{p0,p1} \rightarrow \dots` + + where ``[b0, b1, ...] = range(b)`` is a base of the symmetric group; + the strong base `b_S` of S is an ordered sublist of it; + therefore it is sufficient to compute once the + strong base generators of S using the Schreier-Sims algorithm; + the stabilizers of the strong base generators are the + strong base generators of the stabilizer subgroup. + + ``dbase = [p0, p1, ...]`` is not in general in lexicographic order, + so that one must recompute the strong base generators each time; + however this is trivial, there is no need to use the Schreier-Sims + algorithm for D. + + The algorithm keeps a TAB of elements `(s_i, d_i, h_i)` + where `h_i = d_i \times g \times s_i` satisfying `h_i[j] = p_j` for `0 \le j < i` + starting from `s_0 = id, d_0 = id, h_0 = g`. + + The equations `h_0[0] = p_0, h_1[1] = p_1, \dots` are solved in this order, + choosing each time the lowest possible value of p_i + + For `j < i` + `d_i*g*s_i*S_{b_0, \dots, b_{i-1}}*b_j = D_{p_0, \dots, p_{i-1}}*p_j` + so that for dx in `D_{p_0,\dots,p_{i-1}}` and sx in + `S_{base[0], \dots, base[i-1]}` one has `dx*d_i*g*s_i*sx*b_j = p_j` + + Search for dx, sx such that this equation holds for `j = i`; + it can be written as `s_i*sx*b_j = J, dx*d_i*g*J = p_j` + `sx*b_j = s_i**-1*J; sx = trace(s_i**-1, S_{b_0,...,b_{i-1}})` + `dx**-1*p_j = d_i*g*J; dx = trace(d_i*g*J, D_{p_0,...,p_{i-1}})` + + `s_{i+1} = s_i*trace(s_i**-1*J, S_{b_0,...,b_{i-1}})` + `d_{i+1} = trace(d_i*g*J, D_{p_0,...,p_{i-1}})**-1*d_i` + `h_{i+1}*b_i = d_{i+1}*g*s_{i+1}*b_i = p_i` + + `h_n*b_j = p_j` for all j, so that `h_n` is the solution. + + Add the found `(s, d, h)` to TAB1. + + At the end of the iteration sort TAB1 with respect to the `h`; + if there are two consecutive `h` in TAB1 which differ only for the + sign, the tensor is zero, so return 0; + if there are two consecutive `h` which are equal, keep only one. + + Then stabilize the slot generators under `i` and the dummy generators + under `p_i`. + + Assign `TAB = TAB1` at the end of the iteration step. + + At the end `TAB` contains a unique `(s, d, h)`, since all the slots + of the tensor `h` have been fixed to have the minimum value according + to the symmetries. The algorithm returns `h`. + + It is important that the slot BSGS has lexicographic minimal base, + otherwise there is an `i` which does not belong to the slot base + for which `p_i` is fixed by the dummy symmetry only, while `i` + is not invariant from the slot stabilizer, so `p_i` is not in + general the minimal value. + + This algorithm differs slightly from the original algorithm [3]: + the canonical form is minimal lexicographically, and + the BSGS has minimal base under lexicographic order. + Equal tensors `h` are eliminated from TAB. + + + Examples + ======== + + >>> from sympy.combinatorics.permutations import Permutation + >>> from sympy.combinatorics.tensor_can import double_coset_can_rep, get_transversals + >>> gens = [Permutation(x) for x in [[2, 1, 0, 3, 4, 5, 7, 6], [4, 1, 2, 3, 0, 5, 7, 6]]] + >>> base = [0, 2] + >>> g = Permutation([4, 2, 0, 1, 3, 5, 6, 7]) + >>> transversals = get_transversals(base, gens) + >>> double_coset_can_rep([list(range(6))], [0], base, gens, transversals, g) + [0, 1, 2, 3, 4, 5, 7, 6] + + >>> g = Permutation([4, 1, 3, 0, 5, 2, 6, 7]) + >>> double_coset_can_rep([list(range(6))], [0], base, gens, transversals, g) + 0 + """ + size = g.size + g = g.array_form + num_dummies = size - 2 + indices = list(range(num_dummies)) + all_metrics_with_sym = not any(_ is None for _ in sym) + num_types = len(sym) + dumx = dummies[:] + dumx_flat = [] + for dx in dumx: + dumx_flat.extend(dx) + b_S = b_S[:] + sgensx = [h._array_form for h in sgens] + if b_S: + S_transversals = transversal2coset(size, b_S, S_transversals) + # strong generating set for D + dsgsx = [] + for i in range(num_types): + dsgsx.extend(dummy_sgs(dumx[i], sym[i], num_dummies)) + idn = list(range(size)) + # TAB = list of entries (s, d, h) where h = _af_rmuln(d,g,s) + # for short, in the following d*g*s means _af_rmuln(d,g,s) + TAB = [(idn, idn, g)] + for i in range(size - 2): + b = i + testb = b in b_S and sgensx + if testb: + sgensx1 = [_af_new(_) for _ in sgensx] + deltab = _orbit(size, sgensx1, b) + else: + deltab = {b} + # p1 = min(IMAGES) = min(Union D_p*h*deltab for h in TAB) + if all_metrics_with_sym: + md = _min_dummies(dumx, sym, indices) + else: + md = [min(_orbit(size, [_af_new( + ddx) for ddx in dsgsx], ii)) for ii in range(size - 2)] + + p_i = min(min(md[h[x]] for x in deltab) for s, d, h in TAB) + dsgsx1 = [_af_new(_) for _ in dsgsx] + Dxtrav = _orbit_transversal(size, dsgsx1, p_i, False, af=True) \ + if dsgsx else None + if Dxtrav: + Dxtrav = [_af_invert(x) for x in Dxtrav] + # compute the orbit of p_i + for ii in range(num_types): + if p_i in dumx[ii]: + # the orbit is made by all the indices in dum[ii] + if sym[ii] is not None: + deltap = dumx[ii] + else: + # the orbit is made by all the even indices if p_i + # is even, by all the odd indices if p_i is odd + p_i_index = dumx[ii].index(p_i) % 2 + deltap = dumx[ii][p_i_index::2] + break + else: + deltap = [p_i] + TAB1 = [] + while TAB: + s, d, h = TAB.pop() + if min(md[h[x]] for x in deltab) != p_i: + continue + deltab1 = [x for x in deltab if md[h[x]] == p_i] + # NEXT = s*deltab1 intersection (d*g)**-1*deltap + dg = _af_rmul(d, g) + dginv = _af_invert(dg) + sdeltab = [s[x] for x in deltab1] + gdeltap = [dginv[x] for x in deltap] + NEXT = [x for x in sdeltab if x in gdeltap] + # d, s satisfy + # d*g*s*base[i-1] = p_{i-1}; using the stabilizers + # d*g*s*S_{base[0],...,base[i-1]}*base[i-1] = + # D_{p_0,...,p_{i-1}}*p_{i-1} + # so that to find d1, s1 satisfying d1*g*s1*b = p_i + # one can look for dx in D_{p_0,...,p_{i-1}} and + # sx in S_{base[0],...,base[i-1]} + # d1 = dx*d; s1 = s*sx + # d1*g*s1*b = dx*d*g*s*sx*b = p_i + for j in NEXT: + if testb: + # solve s1*b = j with s1 = s*sx for some element sx + # of the stabilizer of ..., base[i-1] + # sx*b = s**-1*j; sx = _trace_S(s, j,...) + # s1 = s*trace_S(s**-1*j,...) + s1 = _trace_S(s, j, b, S_transversals) + if not s1: + continue + else: + s1 = [s[ix] for ix in s1] + else: + s1 = s + # assert s1[b] == j # invariant + # solve d1*g*j = p_i with d1 = dx*d for some element dg + # of the stabilizer of ..., p_{i-1} + # dx**-1*p_i = d*g*j; dx**-1 = trace_D(d*g*j,...) + # d1 = trace_D(d*g*j,...)**-1*d + # to save an inversion in the inner loop; notice we did + # Dxtrav = [perm_af_invert(x) for x in Dxtrav] out of the loop + if Dxtrav: + d1 = _trace_D(dg[j], p_i, Dxtrav) + if not d1: + continue + else: + if p_i != dg[j]: + continue + d1 = idn + assert d1[dg[j]] == p_i # invariant + d1 = [d1[ix] for ix in d] + h1 = [d1[g[ix]] for ix in s1] + # assert h1[b] == p_i # invariant + TAB1.append((s1, d1, h1)) + + # if TAB contains equal permutations, keep only one of them; + # if TAB contains equal permutations up to the sign, return 0 + TAB1.sort(key=lambda x: x[-1]) + prev = [0] * size + while TAB1: + s, d, h = TAB1.pop() + if h[:-2] == prev[:-2]: + if h[-1] != prev[-1]: + return 0 + else: + TAB.append((s, d, h)) + prev = h + + # stabilize the SGS + sgensx = [h for h in sgensx if h[b] == b] + if b in b_S: + b_S.remove(b) + _dumx_remove(dumx, dumx_flat, p_i) + dsgsx = [] + for i in range(num_types): + dsgsx.extend(dummy_sgs(dumx[i], sym[i], num_dummies)) + return TAB[0][-1] + + +def canonical_free(base, gens, g, num_free): + """ + Canonicalization of a tensor with respect to free indices + choosing the minimum with respect to lexicographical ordering + in the free indices. + + Explanation + =========== + + ``base``, ``gens`` BSGS for slot permutation group + ``g`` permutation representing the tensor + ``num_free`` number of free indices + The indices must be ordered with first the free indices + + See explanation in double_coset_can_rep + The algorithm is a variation of the one given in [2]. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy.combinatorics.tensor_can import canonical_free + >>> gens = [[1, 0, 2, 3, 5, 4], [2, 3, 0, 1, 4, 5],[0, 1, 3, 2, 5, 4]] + >>> gens = [Permutation(h) for h in gens] + >>> base = [0, 2] + >>> g = Permutation([2, 1, 0, 3, 4, 5]) + >>> canonical_free(base, gens, g, 4) + [0, 3, 1, 2, 5, 4] + + Consider the product of Riemann tensors + ``T = R^{a}_{d0}^{d1,d2}*R_{d2,d1}^{d0,b}`` + The order of the indices is ``[a, b, d0, -d0, d1, -d1, d2, -d2]`` + The permutation corresponding to the tensor is + ``g = [0, 3, 4, 6, 7, 5, 2, 1, 8, 9]`` + + In particular ``a`` is position ``0``, ``b`` is in position ``9``. + Use the slot symmetries to get `T` is a form which is the minimal + in lexicographic order in the free indices ``a`` and ``b``, e.g. + ``-R^{a}_{d0}^{d1,d2}*R^{b,d0}_{d2,d1}`` corresponding to + ``[0, 3, 4, 6, 1, 2, 7, 5, 9, 8]`` + + >>> from sympy.combinatorics.tensor_can import riemann_bsgs, tensor_gens + >>> base, gens = riemann_bsgs + >>> size, sbase, sgens = tensor_gens(base, gens, [[], []], 0) + >>> g = Permutation([0, 3, 4, 6, 7, 5, 2, 1, 8, 9]) + >>> canonical_free(sbase, [Permutation(h) for h in sgens], g, 2) + [0, 3, 4, 6, 1, 2, 7, 5, 9, 8] + """ + g = g.array_form + size = len(g) + if not base: + return g[:] + + transversals = get_transversals(base, gens) + for x in sorted(g[:-2]): + if x not in base: + base.append(x) + h = g + for transv in transversals: + h_i = [size]*num_free + # find the element s in transversals[i] such that + # _af_rmul(h, s) has its free elements with the lowest position in h + s = None + for sk in transv.values(): + h1 = _af_rmul(h, sk) + hi = [h1.index(ix) for ix in range(num_free)] + if hi < h_i: + h_i = hi + s = sk + if s: + h = _af_rmul(h, s) + return h + + +def _get_map_slots(size, fixed_slots): + res = list(range(size)) + pos = 0 + for i in range(size): + if i in fixed_slots: + continue + res[i] = pos + pos += 1 + return res + + +def _lift_sgens(size, fixed_slots, free, s): + a = [] + j = k = 0 + fd = list(zip(fixed_slots, free)) + fd = [y for x, y in sorted(fd)] + num_free = len(free) + for i in range(size): + if i in fixed_slots: + a.append(fd[k]) + k += 1 + else: + a.append(s[j] + num_free) + j += 1 + return a + + +def canonicalize(g, dummies, msym, *v): + """ + canonicalize tensor formed by tensors + + Parameters + ========== + + g : permutation representing the tensor + + dummies : list representing the dummy indices + it can be a list of dummy indices of the same type + or a list of lists of dummy indices, one list for each + type of index; + the dummy indices must come after the free indices, + and put in order contravariant, covariant + [d0, -d0, d1,-d1,...] + + msym : symmetry of the metric(s) + it can be an integer or a list; + in the first case it is the symmetry of the dummy index metric; + in the second case it is the list of the symmetries of the + index metric for each type + + v : list, (base_i, gens_i, n_i, sym_i) for tensors of type `i` + + base_i, gens_i : BSGS for tensors of this type. + The BSGS should have minimal base under lexicographic ordering; + if not, an attempt is made do get the minimal BSGS; + in case of failure, + canonicalize_naive is used, which is much slower. + + n_i : number of tensors of type `i`. + + sym_i : symmetry under exchange of component tensors of type `i`. + + Both for msym and sym_i the cases are + * None no symmetry + * 0 commuting + * 1 anticommuting + + Returns + ======= + + 0 if the tensor is zero, else return the array form of + the permutation representing the canonical form of the tensor. + + Algorithm + ========= + + First one uses canonical_free to get the minimum tensor under + lexicographic order, using only the slot symmetries. + If the component tensors have not minimal BSGS, it is attempted + to find it; if the attempt fails canonicalize_naive + is used instead. + + Compute the residual slot symmetry keeping fixed the free indices + using tensor_gens(base, gens, list_free_indices, sym). + + Reduce the problem eliminating the free indices. + + Then use double_coset_can_rep and lift back the result reintroducing + the free indices. + + Examples + ======== + + one type of index with commuting metric; + + `A_{a b}` and `B_{a b}` antisymmetric and commuting + + `T = A_{d0 d1} * B^{d0}{}_{d2} * B^{d2 d1}` + + `ord = [d0,-d0,d1,-d1,d2,-d2]` order of the indices + + g = [1, 3, 0, 5, 4, 2, 6, 7] + + `T_c = 0` + + >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize, bsgs_direct_product + >>> from sympy.combinatorics import Permutation + >>> base2a, gens2a = get_symmetric_group_sgs(2, 1) + >>> t0 = (base2a, gens2a, 1, 0) + >>> t1 = (base2a, gens2a, 2, 0) + >>> g = Permutation([1, 3, 0, 5, 4, 2, 6, 7]) + >>> canonicalize(g, range(6), 0, t0, t1) + 0 + + same as above, but with `B_{a b}` anticommuting + + `T_c = -A^{d0 d1} * B_{d0}{}^{d2} * B_{d1 d2}` + + can = [0,2,1,4,3,5,7,6] + + >>> t1 = (base2a, gens2a, 2, 1) + >>> canonicalize(g, range(6), 0, t0, t1) + [0, 2, 1, 4, 3, 5, 7, 6] + + two types of indices `[a,b,c,d,e,f]` and `[m,n]`, in this order, + both with commuting metric + + `f^{a b c}` antisymmetric, commuting + + `A_{m a}` no symmetry, commuting + + `T = f^c{}_{d a} * f^f{}_{e b} * A_m{}^d * A^{m b} * A_n{}^a * A^{n e}` + + ord = [c,f,a,-a,b,-b,d,-d,e,-e,m,-m,n,-n] + + g = [0,7,3, 1,9,5, 11,6, 10,4, 13,2, 12,8, 14,15] + + The canonical tensor is + `T_c = -f^{c a b} * f^{f d e} * A^m{}_a * A_{m d} * A^n{}_b * A_{n e}` + + can = [0,2,4, 1,6,8, 10,3, 11,7, 12,5, 13,9, 15,14] + + >>> base_f, gens_f = get_symmetric_group_sgs(3, 1) + >>> base1, gens1 = get_symmetric_group_sgs(1) + >>> base_A, gens_A = bsgs_direct_product(base1, gens1, base1, gens1) + >>> t0 = (base_f, gens_f, 2, 0) + >>> t1 = (base_A, gens_A, 4, 0) + >>> dummies = [range(2, 10), range(10, 14)] + >>> g = Permutation([0, 7, 3, 1, 9, 5, 11, 6, 10, 4, 13, 2, 12, 8, 14, 15]) + >>> canonicalize(g, dummies, [0, 0], t0, t1) + [0, 2, 4, 1, 6, 8, 10, 3, 11, 7, 12, 5, 13, 9, 15, 14] + """ + from sympy.combinatorics.testutil import canonicalize_naive + if not isinstance(msym, list): + if msym not in (0, 1, None): + raise ValueError('msym must be 0, 1 or None') + num_types = 1 + else: + num_types = len(msym) + if not all(msymx in (0, 1, None) for msymx in msym): + raise ValueError('msym entries must be 0, 1 or None') + if len(dummies) != num_types: + raise ValueError( + 'dummies and msym must have the same number of elements') + size = g.size + num_tensors = 0 + v1 = [] + for base_i, gens_i, n_i, sym_i in v: + # check that the BSGS is minimal; + # this property is used in double_coset_can_rep; + # if it is not minimal use canonicalize_naive + if not _is_minimal_bsgs(base_i, gens_i): + mbsgs = get_minimal_bsgs(base_i, gens_i) + if not mbsgs: + can = canonicalize_naive(g, dummies, msym, *v) + return can + base_i, gens_i = mbsgs + v1.append((base_i, gens_i, [[]] * n_i, sym_i)) + num_tensors += n_i + + if num_types == 1 and not isinstance(msym, list): + dummies = [dummies] + msym = [msym] + flat_dummies = [] + for dumx in dummies: + flat_dummies.extend(dumx) + + if flat_dummies and flat_dummies != list(range(flat_dummies[0], flat_dummies[-1] + 1)): + raise ValueError('dummies is not valid') + + # slot symmetry of the tensor + size1, sbase, sgens = gens_products(*v1) + if size != size1: + raise ValueError( + 'g has size %d, generators have size %d' % (size, size1)) + free = [i for i in range(size - 2) if i not in flat_dummies] + num_free = len(free) + + # g1 minimal tensor under slot symmetry + g1 = canonical_free(sbase, sgens, g, num_free) + if not flat_dummies: + return g1 + # save the sign of g1 + sign = 0 if g1[-1] == size - 1 else 1 + + # the free indices are kept fixed. + # Determine free_i, the list of slots of tensors which are fixed + # since they are occupied by free indices, which are fixed. + start = 0 + for i, (base_i, gens_i, n_i, sym_i) in enumerate(v): + free_i = [] + len_tens = gens_i[0].size - 2 + # for each component tensor get a list od fixed islots + for j in range(n_i): + # get the elements corresponding to the component tensor + h = g1[start:(start + len_tens)] + fr = [] + # get the positions of the fixed elements in h + for k in free: + if k in h: + fr.append(h.index(k)) + free_i.append(fr) + start += len_tens + v1[i] = (base_i, gens_i, free_i, sym_i) + # BSGS of the tensor with fixed free indices + # if tensor_gens fails in gens_product, use canonicalize_naive + size, sbase, sgens = gens_products(*v1) + + # reduce the permutations getting rid of the free indices + pos_free = [g1.index(x) for x in range(num_free)] + size_red = size - num_free + g1_red = [x - num_free for x in g1 if x in flat_dummies] + if sign: + g1_red.extend([size_red - 1, size_red - 2]) + else: + g1_red.extend([size_red - 2, size_red - 1]) + map_slots = _get_map_slots(size, pos_free) + sbase_red = [map_slots[i] for i in sbase if i not in pos_free] + sgens_red = [_af_new([map_slots[i] for i in y._array_form if i not in pos_free]) for y in sgens] + dummies_red = [[x - num_free for x in y] for y in dummies] + transv_red = get_transversals(sbase_red, sgens_red) + g1_red = _af_new(g1_red) + g2 = double_coset_can_rep( + dummies_red, msym, sbase_red, sgens_red, transv_red, g1_red) + if g2 == 0: + return 0 + # lift to the case with the free indices + g3 = _lift_sgens(size, pos_free, free, g2) + return g3 + + +def perm_af_direct_product(gens1, gens2, signed=True): + """ + Direct products of the generators gens1 and gens2. + + Examples + ======== + + >>> from sympy.combinatorics.tensor_can import perm_af_direct_product + >>> gens1 = [[1, 0, 2, 3], [0, 1, 3, 2]] + >>> gens2 = [[1, 0]] + >>> perm_af_direct_product(gens1, gens2, False) + [[1, 0, 2, 3, 4, 5], [0, 1, 3, 2, 4, 5], [0, 1, 2, 3, 5, 4]] + >>> gens1 = [[1, 0, 2, 3, 5, 4], [0, 1, 3, 2, 4, 5]] + >>> gens2 = [[1, 0, 2, 3]] + >>> perm_af_direct_product(gens1, gens2, True) + [[1, 0, 2, 3, 4, 5, 7, 6], [0, 1, 3, 2, 4, 5, 6, 7], [0, 1, 2, 3, 5, 4, 6, 7]] + """ + gens1 = [list(x) for x in gens1] + gens2 = [list(x) for x in gens2] + s = 2 if signed else 0 + n1 = len(gens1[0]) - s + n2 = len(gens2[0]) - s + start = list(range(n1)) + end = list(range(n1, n1 + n2)) + if signed: + gens1 = [gen[:-2] + end + [gen[-2] + n2, gen[-1] + n2] + for gen in gens1] + gens2 = [start + [x + n1 for x in gen] for gen in gens2] + else: + gens1 = [gen + end for gen in gens1] + gens2 = [start + [x + n1 for x in gen] for gen in gens2] + + res = gens1 + gens2 + + return res + + +def bsgs_direct_product(base1, gens1, base2, gens2, signed=True): + """ + Direct product of two BSGS. + + Parameters + ========== + + base1 : base of the first BSGS. + + gens1 : strong generating sequence of the first BSGS. + + base2, gens2 : similarly for the second BSGS. + + signed : flag for signed permutations. + + Examples + ======== + + >>> from sympy.combinatorics.tensor_can import (get_symmetric_group_sgs, bsgs_direct_product) + >>> base1, gens1 = get_symmetric_group_sgs(1) + >>> base2, gens2 = get_symmetric_group_sgs(2) + >>> bsgs_direct_product(base1, gens1, base2, gens2) + ([1], [(4)(1 2)]) + """ + s = 2 if signed else 0 + n1 = gens1[0].size - s + base = list(base1) + base += [x + n1 for x in base2] + gens1 = [h._array_form for h in gens1] + gens2 = [h._array_form for h in gens2] + gens = perm_af_direct_product(gens1, gens2, signed) + size = len(gens[0]) + id_af = list(range(size)) + gens = [h for h in gens if h != id_af] + if not gens: + gens = [id_af] + return base, [_af_new(h) for h in gens] + + +def get_symmetric_group_sgs(n, antisym=False): + """ + Return base, gens of the minimal BSGS for (anti)symmetric tensor + + Parameters + ========== + + n : rank of the tensor + antisym : bool + ``antisym = False`` symmetric tensor + ``antisym = True`` antisymmetric tensor + + Examples + ======== + + >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs + >>> get_symmetric_group_sgs(3) + ([0, 1], [(4)(0 1), (4)(1 2)]) + """ + if n == 1: + return [], [_af_new(list(range(3)))] + gens = [Permutation(n - 1)(i, i + 1)._array_form for i in range(n - 1)] + if antisym == 0: + gens = [x + [n, n + 1] for x in gens] + else: + gens = [x + [n + 1, n] for x in gens] + base = list(range(n - 1)) + return base, [_af_new(h) for h in gens] + +riemann_bsgs = [0, 2], [Permutation(0, 1)(4, 5), Permutation(2, 3)(4, 5), + Permutation(5)(0, 2)(1, 3)] + + +def get_transversals(base, gens): + """ + Return transversals for the group with BSGS base, gens + """ + if not base: + return [] + stabs = _distribute_gens_by_base(base, gens) + orbits, transversals = _orbits_transversals_from_bsgs(base, stabs) + transversals = [{x: h._array_form for x, h in y.items()} for y in + transversals] + return transversals + + +def _is_minimal_bsgs(base, gens): + """ + Check if the BSGS has minimal base under lexigographic order. + + base, gens BSGS + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy.combinatorics.tensor_can import riemann_bsgs, _is_minimal_bsgs + >>> _is_minimal_bsgs(*riemann_bsgs) + True + >>> riemann_bsgs1 = ([2, 0], ([Permutation(5)(0, 1)(4, 5), Permutation(5)(0, 2)(1, 3)])) + >>> _is_minimal_bsgs(*riemann_bsgs1) + False + """ + base1 = [] + sgs1 = gens[:] + size = gens[0].size + for i in range(size): + if not all(h._array_form[i] == i for h in sgs1): + base1.append(i) + sgs1 = [h for h in sgs1 if h._array_form[i] == i] + return base1 == base + + +def get_minimal_bsgs(base, gens): + """ + Compute a minimal GSGS + + base, gens BSGS + + If base, gens is a minimal BSGS return it; else return a minimal BSGS + if it fails in finding one, it returns None + + TODO: use baseswap in the case in which if it fails in finding a + minimal BSGS + + Examples + ======== + + >>> from sympy.combinatorics import Permutation + >>> from sympy.combinatorics.tensor_can import get_minimal_bsgs + >>> riemann_bsgs1 = ([2, 0], ([Permutation(5)(0, 1)(4, 5), Permutation(5)(0, 2)(1, 3)])) + >>> get_minimal_bsgs(*riemann_bsgs1) + ([0, 2], [(0 1)(4 5), (5)(0 2)(1 3), (2 3)(4 5)]) + """ + G = PermutationGroup(gens) + base, gens = G.schreier_sims_incremental() + if not _is_minimal_bsgs(base, gens): + return None + return base, gens + + +def tensor_gens(base, gens, list_free_indices, sym=0): + """ + Returns size, res_base, res_gens BSGS for n tensors of the + same type. + + Explanation + =========== + + base, gens BSGS for tensors of this type + list_free_indices list of the slots occupied by fixed indices + for each of the tensors + + sym symmetry under commutation of two tensors + sym None no symmetry + sym 0 commuting + sym 1 anticommuting + + Examples + ======== + + >>> from sympy.combinatorics.tensor_can import tensor_gens, get_symmetric_group_sgs + + two symmetric tensors with 3 indices without free indices + + >>> base, gens = get_symmetric_group_sgs(3) + >>> tensor_gens(base, gens, [[], []]) + (8, [0, 1, 3, 4], [(7)(0 1), (7)(1 2), (7)(3 4), (7)(4 5), (7)(0 3)(1 4)(2 5)]) + + two symmetric tensors with 3 indices with free indices in slot 1 and 0 + + >>> tensor_gens(base, gens, [[1], [0]]) + (8, [0, 4], [(7)(0 2), (7)(4 5)]) + + four symmetric tensors with 3 indices, two of which with free indices + + """ + def _get_bsgs(G, base, gens, free_indices): + """ + return the BSGS for G.pointwise_stabilizer(free_indices) + """ + if not free_indices: + return base[:], gens[:] + else: + H = G.pointwise_stabilizer(free_indices) + base, sgs = H.schreier_sims_incremental() + return base, sgs + + # if not base there is no slot symmetry for the component tensors + # if list_free_indices.count([]) < 2 there is no commutation symmetry + # so there is no resulting slot symmetry + if not base and list_free_indices.count([]) < 2: + n = len(list_free_indices) + size = gens[0].size + size = n * (size - 2) + 2 + return size, [], [_af_new(list(range(size)))] + + # if any(list_free_indices) one needs to compute the pointwise + # stabilizer, so G is needed + if any(list_free_indices): + G = PermutationGroup(gens) + else: + G = None + + # no_free list of lists of indices for component tensors without fixed + # indices + no_free = [] + size = gens[0].size + id_af = list(range(size)) + num_indices = size - 2 + if not list_free_indices[0]: + no_free.append(list(range(num_indices))) + res_base, res_gens = _get_bsgs(G, base, gens, list_free_indices[0]) + for i in range(1, len(list_free_indices)): + base1, gens1 = _get_bsgs(G, base, gens, list_free_indices[i]) + res_base, res_gens = bsgs_direct_product(res_base, res_gens, + base1, gens1, 1) + if not list_free_indices[i]: + no_free.append(list(range(size - 2, size - 2 + num_indices))) + size += num_indices + nr = size - 2 + res_gens = [h for h in res_gens if h._array_form != id_af] + # if sym there are no commuting tensors stop here + if sym is None or not no_free: + if not res_gens: + res_gens = [_af_new(id_af)] + return size, res_base, res_gens + + # if the component tensors have moinimal BSGS, so is their direct + # product P; the slot symmetry group is S = P*C, where C is the group + # to (anti)commute the component tensors with no free indices + # a stabilizer has the property S_i = P_i*C_i; + # the BSGS of P*C has SGS_P + SGS_C and the base is + # the ordered union of the bases of P and C. + # If P has minimal BSGS, so has S with this base. + base_comm = [] + for i in range(len(no_free) - 1): + ind1 = no_free[i] + ind2 = no_free[i + 1] + a = list(range(ind1[0])) + a.extend(ind2) + a.extend(ind1) + base_comm.append(ind1[0]) + a.extend(list(range(ind2[-1] + 1, nr))) + if sym == 0: + a.extend([nr, nr + 1]) + else: + a.extend([nr + 1, nr]) + res_gens.append(_af_new(a)) + res_base = list(res_base) + # each base is ordered; order the union of the two bases + for i in base_comm: + if i not in res_base: + res_base.append(i) + res_base.sort() + if not res_gens: + res_gens = [_af_new(id_af)] + + return size, res_base, res_gens + + +def gens_products(*v): + """ + Returns size, res_base, res_gens BSGS for n tensors of different types. + + Explanation + =========== + + v is a sequence of (base_i, gens_i, free_i, sym_i) + where + base_i, gens_i BSGS of tensor of type `i` + free_i list of the fixed slots for each of the tensors + of type `i`; if there are `n_i` tensors of type `i` + and none of them have fixed slots, `free = [[]]*n_i` + sym 0 (1) if the tensors of type `i` (anti)commute among themselves + + Examples + ======== + + >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, gens_products + >>> base, gens = get_symmetric_group_sgs(2) + >>> gens_products((base, gens, [[], []], 0)) + (6, [0, 2], [(5)(0 1), (5)(2 3), (5)(0 2)(1 3)]) + >>> gens_products((base, gens, [[1], []], 0)) + (6, [2], [(5)(2 3)]) + """ + res_size, res_base, res_gens = tensor_gens(*v[0]) + for i in range(1, len(v)): + size, base, gens = tensor_gens(*v[i]) + res_base, res_gens = bsgs_direct_product(res_base, res_gens, base, + gens, 1) + res_size = res_gens[0].size + id_af = list(range(res_size)) + res_gens = [h for h in res_gens if h != id_af] + if not res_gens: + res_gens = [id_af] + return res_size, res_base, res_gens diff --git a/lib/python3.12/site-packages/sympy/combinatorics/testutil.py b/lib/python3.12/site-packages/sympy/combinatorics/testutil.py new file mode 100644 index 0000000000000000000000000000000000000000..9fe664ce9e7437b97feec90f2052eb2987c57a4e --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/testutil.py @@ -0,0 +1,357 @@ +from sympy.combinatorics import Permutation +from sympy.combinatorics.util import _distribute_gens_by_base + +rmul = Permutation.rmul + + +def _cmp_perm_lists(first, second): + """ + Compare two lists of permutations as sets. + + Explanation + =========== + + This is used for testing purposes. Since the array form of a + permutation is currently a list, Permutation is not hashable + and cannot be put into a set. + + Examples + ======== + + >>> from sympy.combinatorics.permutations import Permutation + >>> from sympy.combinatorics.testutil import _cmp_perm_lists + >>> a = Permutation([0, 2, 3, 4, 1]) + >>> b = Permutation([1, 2, 0, 4, 3]) + >>> c = Permutation([3, 4, 0, 1, 2]) + >>> ls1 = [a, b, c] + >>> ls2 = [b, c, a] + >>> _cmp_perm_lists(ls1, ls2) + True + + """ + return {tuple(a) for a in first} == \ + {tuple(a) for a in second} + + +def _naive_list_centralizer(self, other, af=False): + from sympy.combinatorics.perm_groups import PermutationGroup + """ + Return a list of elements for the centralizer of a subgroup/set/element. + + Explanation + =========== + + This is a brute force implementation that goes over all elements of the + group and checks for membership in the centralizer. It is used to + test ``.centralizer()`` from ``sympy.combinatorics.perm_groups``. + + Examples + ======== + + >>> from sympy.combinatorics.testutil import _naive_list_centralizer + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> D = DihedralGroup(4) + >>> _naive_list_centralizer(D, D) + [Permutation([0, 1, 2, 3]), Permutation([2, 3, 0, 1])] + + See Also + ======== + + sympy.combinatorics.perm_groups.centralizer + + """ + from sympy.combinatorics.permutations import _af_commutes_with + if hasattr(other, 'generators'): + elements = list(self.generate_dimino(af=True)) + gens = [x._array_form for x in other.generators] + commutes_with_gens = lambda x: all(_af_commutes_with(x, gen) for gen in gens) + centralizer_list = [] + if not af: + for element in elements: + if commutes_with_gens(element): + centralizer_list.append(Permutation._af_new(element)) + else: + for element in elements: + if commutes_with_gens(element): + centralizer_list.append(element) + return centralizer_list + elif hasattr(other, 'getitem'): + return _naive_list_centralizer(self, PermutationGroup(other), af) + elif hasattr(other, 'array_form'): + return _naive_list_centralizer(self, PermutationGroup([other]), af) + + +def _verify_bsgs(group, base, gens): + """ + Verify the correctness of a base and strong generating set. + + Explanation + =========== + + This is a naive implementation using the definition of a base and a strong + generating set relative to it. There are other procedures for + verifying a base and strong generating set, but this one will + serve for more robust testing. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import AlternatingGroup + >>> from sympy.combinatorics.testutil import _verify_bsgs + >>> A = AlternatingGroup(4) + >>> A.schreier_sims() + >>> _verify_bsgs(A, A.base, A.strong_gens) + True + + See Also + ======== + + sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims + + """ + from sympy.combinatorics.perm_groups import PermutationGroup + strong_gens_distr = _distribute_gens_by_base(base, gens) + current_stabilizer = group + for i in range(len(base)): + candidate = PermutationGroup(strong_gens_distr[i]) + if current_stabilizer.order() != candidate.order(): + return False + current_stabilizer = current_stabilizer.stabilizer(base[i]) + if current_stabilizer.order() != 1: + return False + return True + + +def _verify_centralizer(group, arg, centr=None): + """ + Verify the centralizer of a group/set/element inside another group. + + This is used for testing ``.centralizer()`` from + ``sympy.combinatorics.perm_groups`` + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... AlternatingGroup) + >>> from sympy.combinatorics.perm_groups import PermutationGroup + >>> from sympy.combinatorics.permutations import Permutation + >>> from sympy.combinatorics.testutil import _verify_centralizer + >>> S = SymmetricGroup(5) + >>> A = AlternatingGroup(5) + >>> centr = PermutationGroup([Permutation([0, 1, 2, 3, 4])]) + >>> _verify_centralizer(S, A, centr) + True + + See Also + ======== + + _naive_list_centralizer, + sympy.combinatorics.perm_groups.PermutationGroup.centralizer, + _cmp_perm_lists + + """ + if centr is None: + centr = group.centralizer(arg) + centr_list = list(centr.generate_dimino(af=True)) + centr_list_naive = _naive_list_centralizer(group, arg, af=True) + return _cmp_perm_lists(centr_list, centr_list_naive) + + +def _verify_normal_closure(group, arg, closure=None): + from sympy.combinatorics.perm_groups import PermutationGroup + """ + Verify the normal closure of a subgroup/subset/element in a group. + + This is used to test + sympy.combinatorics.perm_groups.PermutationGroup.normal_closure + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import (SymmetricGroup, + ... AlternatingGroup) + >>> from sympy.combinatorics.testutil import _verify_normal_closure + >>> S = SymmetricGroup(3) + >>> A = AlternatingGroup(3) + >>> _verify_normal_closure(S, A, closure=A) + True + + See Also + ======== + + sympy.combinatorics.perm_groups.PermutationGroup.normal_closure + + """ + if closure is None: + closure = group.normal_closure(arg) + conjugates = set() + if hasattr(arg, 'generators'): + subgr_gens = arg.generators + elif hasattr(arg, '__getitem__'): + subgr_gens = arg + elif hasattr(arg, 'array_form'): + subgr_gens = [arg] + for el in group.generate_dimino(): + conjugates.update(gen ^ el for gen in subgr_gens) + naive_closure = PermutationGroup(list(conjugates)) + return closure.is_subgroup(naive_closure) + + +def canonicalize_naive(g, dummies, sym, *v): + """ + Canonicalize tensor formed by tensors of the different types. + + Explanation + =========== + + sym_i symmetry under exchange of two component tensors of type `i` + None no symmetry + 0 commuting + 1 anticommuting + + Parameters + ========== + + g : Permutation representing the tensor. + dummies : List of dummy indices. + msym : Symmetry of the metric. + v : A list of (base_i, gens_i, n_i, sym_i) for tensors of type `i`. + base_i, gens_i BSGS for tensors of this type + n_i number of tensors of type `i` + + Returns + ======= + + Returns 0 if the tensor is zero, else returns the array form of + the permutation representing the canonical form of the tensor. + + Examples + ======== + + >>> from sympy.combinatorics.testutil import canonicalize_naive + >>> from sympy.combinatorics.tensor_can import get_symmetric_group_sgs + >>> from sympy.combinatorics import Permutation + >>> g = Permutation([1, 3, 2, 0, 4, 5]) + >>> base2, gens2 = get_symmetric_group_sgs(2) + >>> canonicalize_naive(g, [2, 3], 0, (base2, gens2, 2, 0)) + [0, 2, 1, 3, 4, 5] + """ + from sympy.combinatorics.perm_groups import PermutationGroup + from sympy.combinatorics.tensor_can import gens_products, dummy_sgs + from sympy.combinatorics.permutations import _af_rmul + v1 = [] + for i in range(len(v)): + base_i, gens_i, n_i, sym_i = v[i] + v1.append((base_i, gens_i, [[]]*n_i, sym_i)) + size, sbase, sgens = gens_products(*v1) + dgens = dummy_sgs(dummies, sym, size-2) + if isinstance(sym, int): + num_types = 1 + dummies = [dummies] + sym = [sym] + else: + num_types = len(sym) + dgens = [] + for i in range(num_types): + dgens.extend(dummy_sgs(dummies[i], sym[i], size - 2)) + S = PermutationGroup(sgens) + D = PermutationGroup([Permutation(x) for x in dgens]) + dlist = list(D.generate(af=True)) + g = g.array_form + st = set() + for s in S.generate(af=True): + h = _af_rmul(g, s) + for d in dlist: + q = tuple(_af_rmul(d, h)) + st.add(q) + a = list(st) + a.sort() + prev = (0,)*size + for h in a: + if h[:-2] == prev[:-2]: + if h[-1] != prev[-1]: + return 0 + prev = h + return list(a[0]) + + +def graph_certificate(gr): + """ + Return a certificate for the graph + + Parameters + ========== + + gr : adjacency list + + Explanation + =========== + + The graph is assumed to be unoriented and without + external lines. + + Associate to each vertex of the graph a symmetric tensor with + number of indices equal to the degree of the vertex; indices + are contracted when they correspond to the same line of the graph. + The canonical form of the tensor gives a certificate for the graph. + + This is not an efficient algorithm to get the certificate of a graph. + + Examples + ======== + + >>> from sympy.combinatorics.testutil import graph_certificate + >>> gr1 = {0:[1, 2, 3, 5], 1:[0, 2, 4], 2:[0, 1, 3, 4], 3:[0, 2, 4], 4:[1, 2, 3, 5], 5:[0, 4]} + >>> gr2 = {0:[1, 5], 1:[0, 2, 3, 4], 2:[1, 3, 5], 3:[1, 2, 4, 5], 4:[1, 3, 5], 5:[0, 2, 3, 4]} + >>> c1 = graph_certificate(gr1) + >>> c2 = graph_certificate(gr2) + >>> c1 + [0, 2, 4, 6, 1, 8, 10, 12, 3, 14, 16, 18, 5, 9, 15, 7, 11, 17, 13, 19, 20, 21] + >>> c1 == c2 + True + """ + from sympy.combinatorics.permutations import _af_invert + from sympy.combinatorics.tensor_can import get_symmetric_group_sgs, canonicalize + items = list(gr.items()) + items.sort(key=lambda x: len(x[1]), reverse=True) + pvert = [x[0] for x in items] + pvert = _af_invert(pvert) + + # the indices of the tensor are twice the number of lines of the graph + num_indices = 0 + for v, neigh in items: + num_indices += len(neigh) + # associate to each vertex its indices; for each line + # between two vertices assign the + # even index to the vertex which comes first in items, + # the odd index to the other vertex + vertices = [[] for i in items] + i = 0 + for v, neigh in items: + for v2 in neigh: + if pvert[v] < pvert[v2]: + vertices[pvert[v]].append(i) + vertices[pvert[v2]].append(i+1) + i += 2 + g = [] + for v in vertices: + g.extend(v) + assert len(g) == num_indices + g += [num_indices, num_indices + 1] + size = num_indices + 2 + assert sorted(g) == list(range(size)) + g = Permutation(g) + vlen = [0]*(len(vertices[0])+1) + for neigh in vertices: + vlen[len(neigh)] += 1 + v = [] + for i in range(len(vlen)): + n = vlen[i] + if n: + base, gens = get_symmetric_group_sgs(i) + v.append((base, gens, n, 0)) + v.reverse() + dummies = list(range(num_indices)) + can = canonicalize(g, dummies, 0, *v) + return can diff --git a/lib/python3.12/site-packages/sympy/combinatorics/util.py b/lib/python3.12/site-packages/sympy/combinatorics/util.py new file mode 100644 index 0000000000000000000000000000000000000000..fc73b02f94f4aae6f1b98bb3f0c837fd5a1d1e6d --- /dev/null +++ b/lib/python3.12/site-packages/sympy/combinatorics/util.py @@ -0,0 +1,532 @@ +from sympy.combinatorics.permutations import Permutation, _af_invert, _af_rmul +from sympy.ntheory import isprime + +rmul = Permutation.rmul +_af_new = Permutation._af_new + +############################################ +# +# Utilities for computational group theory +# +############################################ + + +def _base_ordering(base, degree): + r""" + Order `\{0, 1, \dots, n-1\}` so that base points come first and in order. + + Parameters + ========== + + base : the base + degree : the degree of the associated permutation group + + Returns + ======= + + A list ``base_ordering`` such that ``base_ordering[point]`` is the + number of ``point`` in the ordering. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricGroup + >>> from sympy.combinatorics.util import _base_ordering + >>> S = SymmetricGroup(4) + >>> S.schreier_sims() + >>> _base_ordering(S.base, S.degree) + [0, 1, 2, 3] + + Notes + ===== + + This is used in backtrack searches, when we define a relation `\ll` on + the underlying set for a permutation group of degree `n`, + `\{0, 1, \dots, n-1\}`, so that if `(b_1, b_2, \dots, b_k)` is a base we + have `b_i \ll b_j` whenever `i>> from sympy.combinatorics.util import _check_cycles_alt_sym + >>> from sympy.combinatorics import Permutation + >>> a = Permutation([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 12]]) + >>> _check_cycles_alt_sym(a) + False + >>> b = Permutation([[0, 1, 2, 3, 4, 5, 6], [7, 8, 9, 10]]) + >>> _check_cycles_alt_sym(b) + True + + See Also + ======== + + sympy.combinatorics.perm_groups.PermutationGroup.is_alt_sym + + """ + n = perm.size + af = perm.array_form + current_len = 0 + total_len = 0 + used = set() + for i in range(n//2): + if i not in used and i < n//2 - total_len: + current_len = 1 + used.add(i) + j = i + while af[j] != i: + current_len += 1 + j = af[j] + used.add(j) + total_len += current_len + if current_len > n//2 and current_len < n - 2 and isprime(current_len): + return True + return False + + +def _distribute_gens_by_base(base, gens): + r""" + Distribute the group elements ``gens`` by membership in basic stabilizers. + + Explanation + =========== + + Notice that for a base `(b_1, b_2, \dots, b_k)`, the basic stabilizers + are defined as `G^{(i)} = G_{b_1, \dots, b_{i-1}}` for + `i \in\{1, 2, \dots, k\}`. + + Parameters + ========== + + base : a sequence of points in `\{0, 1, \dots, n-1\}` + gens : a list of elements of a permutation group of degree `n`. + + Returns + ======= + list + List of length `k`, where `k` is the length of *base*. The `i`-th entry + contains those elements in *gens* which fix the first `i` elements of + *base* (so that the `0`-th entry is equal to *gens* itself). If no + element fixes the first `i` elements of *base*, the `i`-th element is + set to a list containing the identity element. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> from sympy.combinatorics.util import _distribute_gens_by_base + >>> D = DihedralGroup(3) + >>> D.schreier_sims() + >>> D.strong_gens + [(0 1 2), (0 2), (1 2)] + >>> D.base + [0, 1] + >>> _distribute_gens_by_base(D.base, D.strong_gens) + [[(0 1 2), (0 2), (1 2)], + [(1 2)]] + + See Also + ======== + + _strong_gens_from_distr, _orbits_transversals_from_bsgs, + _handle_precomputed_bsgs + + """ + base_len = len(base) + degree = gens[0].size + stabs = [[] for _ in range(base_len)] + max_stab_index = 0 + for gen in gens: + j = 0 + while j < base_len - 1 and gen._array_form[base[j]] == base[j]: + j += 1 + if j > max_stab_index: + max_stab_index = j + for k in range(j + 1): + stabs[k].append(gen) + for i in range(max_stab_index + 1, base_len): + stabs[i].append(_af_new(list(range(degree)))) + return stabs + + +def _handle_precomputed_bsgs(base, strong_gens, transversals=None, + basic_orbits=None, strong_gens_distr=None): + """ + Calculate BSGS-related structures from those present. + + Explanation + =========== + + The base and strong generating set must be provided; if any of the + transversals, basic orbits or distributed strong generators are not + provided, they will be calculated from the base and strong generating set. + + Parameters + ========== + + base : the base + strong_gens : the strong generators + transversals : basic transversals + basic_orbits : basic orbits + strong_gens_distr : strong generators distributed by membership in basic stabilizers + + Returns + ======= + + (transversals, basic_orbits, strong_gens_distr) + where *transversals* are the basic transversals, *basic_orbits* are the + basic orbits, and *strong_gens_distr* are the strong generators distributed + by membership in basic stabilizers. + + Examples + ======== + + >>> from sympy.combinatorics.named_groups import DihedralGroup + >>> from sympy.combinatorics.util import _handle_precomputed_bsgs + >>> D = DihedralGroup(3) + >>> D.schreier_sims() + >>> _handle_precomputed_bsgs(D.base, D.strong_gens, + ... basic_orbits=D.basic_orbits) + ([{0: (2), 1: (0 1 2), 2: (0 2)}, {1: (2), 2: (1 2)}], [[0, 1, 2], [1, 2]], [[(0 1 2), (0 2), (1 2)], [(1 2)]]) + + See Also + ======== + + _orbits_transversals_from_bsgs, _distribute_gens_by_base + + """ + if strong_gens_distr is None: + strong_gens_distr = _distribute_gens_by_base(base, strong_gens) + if transversals is None: + if basic_orbits is None: + basic_orbits, transversals = \ + _orbits_transversals_from_bsgs(base, strong_gens_distr) + else: + transversals = \ + _orbits_transversals_from_bsgs(base, strong_gens_distr, + transversals_only=True) + else: + if basic_orbits is None: + base_len = len(base) + basic_orbits = [None]*base_len + for i in range(base_len): + basic_orbits[i] = list(transversals[i].keys()) + return transversals, basic_orbits, strong_gens_distr + + +def _orbits_transversals_from_bsgs(base, strong_gens_distr, + transversals_only=False, slp=False): + """ + Compute basic orbits and transversals from a base and strong generating set. + + Explanation + =========== + + The generators are provided as distributed across the basic stabilizers. + If the optional argument ``transversals_only`` is set to True, only the + transversals are returned. + + Parameters + ========== + + base : The base. + strong_gens_distr : Strong generators distributed by membership in basic stabilizers. + transversals_only : bool, default: False + A flag switching between returning only the + transversals and both orbits and transversals. + slp : bool, default: False + If ``True``, return a list of dictionaries containing the + generator presentations of the elements of the transversals, + i.e. the list of indices of generators from ``strong_gens_distr[i]`` + such that their product is the relevant transversal element. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricGroup + >>> from sympy.combinatorics.util import _distribute_gens_by_base + >>> S = SymmetricGroup(3) + >>> S.schreier_sims() + >>> strong_gens_distr = _distribute_gens_by_base(S.base, S.strong_gens) + >>> (S.base, strong_gens_distr) + ([0, 1], [[(0 1 2), (2)(0 1), (1 2)], [(1 2)]]) + + See Also + ======== + + _distribute_gens_by_base, _handle_precomputed_bsgs + + """ + from sympy.combinatorics.perm_groups import _orbit_transversal + base_len = len(base) + degree = strong_gens_distr[0][0].size + transversals = [None]*base_len + slps = [None]*base_len + if transversals_only is False: + basic_orbits = [None]*base_len + for i in range(base_len): + transversals[i], slps[i] = _orbit_transversal(degree, strong_gens_distr[i], + base[i], pairs=True, slp=True) + transversals[i] = dict(transversals[i]) + if transversals_only is False: + basic_orbits[i] = list(transversals[i].keys()) + if transversals_only: + return transversals + else: + if not slp: + return basic_orbits, transversals + return basic_orbits, transversals, slps + + +def _remove_gens(base, strong_gens, basic_orbits=None, strong_gens_distr=None): + """ + Remove redundant generators from a strong generating set. + + Parameters + ========== + + base : a base + strong_gens : a strong generating set relative to *base* + basic_orbits : basic orbits + strong_gens_distr : strong generators distributed by membership in basic stabilizers + + Returns + ======= + + A strong generating set with respect to ``base`` which is a subset of + ``strong_gens``. + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricGroup + >>> from sympy.combinatorics.util import _remove_gens + >>> from sympy.combinatorics.testutil import _verify_bsgs + >>> S = SymmetricGroup(15) + >>> base, strong_gens = S.schreier_sims_incremental() + >>> new_gens = _remove_gens(base, strong_gens) + >>> len(new_gens) + 14 + >>> _verify_bsgs(S, base, new_gens) + True + + Notes + ===== + + This procedure is outlined in [1],p.95. + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E. + "Handbook of computational group theory" + + """ + from sympy.combinatorics.perm_groups import _orbit + base_len = len(base) + degree = strong_gens[0].size + if strong_gens_distr is None: + strong_gens_distr = _distribute_gens_by_base(base, strong_gens) + if basic_orbits is None: + basic_orbits = [] + for i in range(base_len): + basic_orbit = _orbit(degree, strong_gens_distr[i], base[i]) + basic_orbits.append(basic_orbit) + strong_gens_distr.append([]) + res = strong_gens[:] + for i in range(base_len - 1, -1, -1): + gens_copy = strong_gens_distr[i][:] + for gen in strong_gens_distr[i]: + if gen not in strong_gens_distr[i + 1]: + temp_gens = gens_copy[:] + temp_gens.remove(gen) + if temp_gens == []: + continue + temp_orbit = _orbit(degree, temp_gens, base[i]) + if temp_orbit == basic_orbits[i]: + gens_copy.remove(gen) + res.remove(gen) + return res + + +def _strip(g, base, orbits, transversals): + """ + Attempt to decompose a permutation using a (possibly partial) BSGS + structure. + + Explanation + =========== + + This is done by treating the sequence ``base`` as an actual base, and + the orbits ``orbits`` and transversals ``transversals`` as basic orbits and + transversals relative to it. + + This process is called "sifting". A sift is unsuccessful when a certain + orbit element is not found or when after the sift the decomposition + does not end with the identity element. + + The argument ``transversals`` is a list of dictionaries that provides + transversal elements for the orbits ``orbits``. + + Parameters + ========== + + g : permutation to be decomposed + base : sequence of points + orbits : list + A list in which the ``i``-th entry is an orbit of ``base[i]`` + under some subgroup of the pointwise stabilizer of ` + `base[0], base[1], ..., base[i - 1]``. The groups themselves are implicit + in this function since the only information we need is encoded in the orbits + and transversals + transversals : list + A list of orbit transversals associated with the orbits *orbits*. + + Examples + ======== + + >>> from sympy.combinatorics import Permutation, SymmetricGroup + >>> from sympy.combinatorics.util import _strip + >>> S = SymmetricGroup(5) + >>> S.schreier_sims() + >>> g = Permutation([0, 2, 3, 1, 4]) + >>> _strip(g, S.base, S.basic_orbits, S.basic_transversals) + ((4), 5) + + Notes + ===== + + The algorithm is described in [1],pp.89-90. The reason for returning + both the current state of the element being decomposed and the level + at which the sifting ends is that they provide important information for + the randomized version of the Schreier-Sims algorithm. + + References + ========== + + .. [1] Holt, D., Eick, B., O'Brien, E."Handbook of computational group theory" + + See Also + ======== + + sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims + sympy.combinatorics.perm_groups.PermutationGroup.schreier_sims_random + + """ + h = g._array_form + base_len = len(base) + for i in range(base_len): + beta = h[base[i]] + if beta == base[i]: + continue + if beta not in orbits[i]: + return _af_new(h), i + 1 + u = transversals[i][beta]._array_form + h = _af_rmul(_af_invert(u), h) + return _af_new(h), base_len + 1 + + +def _strip_af(h, base, orbits, transversals, j, slp=[], slps={}): + """ + optimized _strip, with h, transversals and result in array form + if the stripped elements is the identity, it returns False, base_len + 1 + + j h[base[i]] == base[i] for i <= j + + """ + base_len = len(base) + for i in range(j+1, base_len): + beta = h[base[i]] + if beta == base[i]: + continue + if beta not in orbits[i]: + if not slp: + return h, i + 1 + return h, i + 1, slp + u = transversals[i][beta] + if h == u: + if not slp: + return False, base_len + 1 + return False, base_len + 1, slp + h = _af_rmul(_af_invert(u), h) + if slp: + u_slp = slps[i][beta][:] + u_slp.reverse() + u_slp = [(i, (g,)) for g in u_slp] + slp = u_slp + slp + if not slp: + return h, base_len + 1 + return h, base_len + 1, slp + + +def _strong_gens_from_distr(strong_gens_distr): + """ + Retrieve strong generating set from generators of basic stabilizers. + + This is just the union of the generators of the first and second basic + stabilizers. + + Parameters + ========== + + strong_gens_distr : strong generators distributed by membership in basic stabilizers + + Examples + ======== + + >>> from sympy.combinatorics import SymmetricGroup + >>> from sympy.combinatorics.util import (_strong_gens_from_distr, + ... _distribute_gens_by_base) + >>> S = SymmetricGroup(3) + >>> S.schreier_sims() + >>> S.strong_gens + [(0 1 2), (2)(0 1), (1 2)] + >>> strong_gens_distr = _distribute_gens_by_base(S.base, S.strong_gens) + >>> _strong_gens_from_distr(strong_gens_distr) + [(0 1 2), (2)(0 1), (1 2)] + + See Also + ======== + + _distribute_gens_by_base + + """ + if len(strong_gens_distr) == 1: + return strong_gens_distr[0][:] + else: + result = strong_gens_distr[0] + for gen in strong_gens_distr[1]: + if gen not in result: + result.append(gen) + return result diff --git a/lib/python3.12/site-packages/sympy/functions/__pycache__/__init__.cpython-312.pyc b/lib/python3.12/site-packages/sympy/functions/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..840191bbe69e6a489c5f11ca60672cfdb45d4655 Binary files /dev/null and b/lib/python3.12/site-packages/sympy/functions/__pycache__/__init__.cpython-312.pyc differ diff --git a/lib/python3.12/site-packages/sympy/functions/combinatorial/__init__.py b/lib/python3.12/site-packages/sympy/functions/combinatorial/__init__.py new file mode 100644 index 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0000000000000000000000000000000000000000..1b805d4fd7f1835c1f21b9c4d035442080a469e5 Binary files /dev/null and b/lib/python3.12/site-packages/sympy/functions/combinatorial/__pycache__/factorials.cpython-312.pyc differ diff --git a/lib/python3.12/site-packages/sympy/functions/combinatorial/factorials.py b/lib/python3.12/site-packages/sympy/functions/combinatorial/factorials.py new file mode 100644 index 0000000000000000000000000000000000000000..97e5052408bc9d0cc68749f85bc2901ace05f803 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/functions/combinatorial/factorials.py @@ -0,0 +1,1133 @@ +from __future__ import annotations +from functools import reduce + +from sympy.core import S, sympify, Dummy, Mod +from sympy.core.cache import cacheit +from sympy.core.function import Function, ArgumentIndexError, PoleError +from sympy.core.logic import fuzzy_and +from sympy.core.numbers import Integer, pi, I +from sympy.core.relational import Eq +from sympy.external.gmpy import gmpy as _gmpy +from sympy.ntheory import sieve +from sympy.ntheory.residue_ntheory import binomial_mod +from sympy.polys.polytools import Poly + +from math import factorial as _factorial, prod, sqrt as _sqrt + +class CombinatorialFunction(Function): + """Base class for combinatorial functions. """ + + def _eval_simplify(self, **kwargs): + from sympy.simplify.combsimp import combsimp + # combinatorial function with non-integer arguments is + # automatically passed to gammasimp + expr = combsimp(self) + measure = kwargs['measure'] + if measure(expr) <= kwargs['ratio']*measure(self): + return expr + return self + + +############################################################################### +######################## FACTORIAL and MULTI-FACTORIAL ######################## +############################################################################### + + +class factorial(CombinatorialFunction): + r"""Implementation of factorial function over nonnegative integers. + By convention (consistent with the gamma function and the binomial + coefficients), factorial of a negative integer is complex infinity. + + The factorial is very important in combinatorics where it gives + the number of ways in which `n` objects can be permuted. It also + arises in calculus, probability, number theory, etc. + + There is strict relation of factorial with gamma function. In + fact `n! = gamma(n+1)` for nonnegative integers. Rewrite of this + kind is very useful in case of combinatorial simplification. + + Computation of the factorial is done using two algorithms. For + small arguments a precomputed look up table is used. However for bigger + input algorithm Prime-Swing is used. It is the fastest algorithm + known and computes `n!` via prime factorization of special class + of numbers, called here the 'Swing Numbers'. + + Examples + ======== + + >>> from sympy import Symbol, factorial, S + >>> n = Symbol('n', integer=True) + + >>> factorial(0) + 1 + + >>> factorial(7) + 5040 + + >>> factorial(-2) + zoo + + >>> factorial(n) + factorial(n) + + >>> factorial(2*n) + factorial(2*n) + + >>> factorial(S(1)/2) + factorial(1/2) + + See Also + ======== + + factorial2, RisingFactorial, FallingFactorial + """ + + def fdiff(self, argindex=1): + from sympy.functions.special.gamma_functions import (gamma, polygamma) + if argindex == 1: + return gamma(self.args[0] + 1)*polygamma(0, self.args[0] + 1) + else: + raise ArgumentIndexError(self, argindex) + + _small_swing = [ + 1, 1, 1, 3, 3, 15, 5, 35, 35, 315, 63, 693, 231, 3003, 429, 6435, 6435, 109395, + 12155, 230945, 46189, 969969, 88179, 2028117, 676039, 16900975, 1300075, + 35102025, 5014575, 145422675, 9694845, 300540195, 300540195 + ] + + _small_factorials: list[int] = [] + + @classmethod + def _swing(cls, n): + if n < 33: + return cls._small_swing[n] + else: + N, primes = int(_sqrt(n)), [] + + for prime in sieve.primerange(3, N + 1): + p, q = 1, n + + while True: + q //= prime + + if q > 0: + if q & 1 == 1: + p *= prime + else: + break + + if p > 1: + primes.append(p) + + for prime in sieve.primerange(N + 1, n//3 + 1): + if (n // prime) & 1 == 1: + primes.append(prime) + + L_product = prod(sieve.primerange(n//2 + 1, n + 1)) + R_product = prod(primes) + + return L_product*R_product + + @classmethod + def _recursive(cls, n): + if n < 2: + return 1 + else: + return (cls._recursive(n//2)**2)*cls._swing(n) + + @classmethod + def eval(cls, n): + n = sympify(n) + + if n.is_Number: + if n.is_zero: + return S.One + elif n is S.Infinity: + return S.Infinity + elif n.is_Integer: + if n.is_negative: + return S.ComplexInfinity + else: + n = n.p + + if n < 20: + if not cls._small_factorials: + result = 1 + for i in range(1, 20): + result *= i + cls._small_factorials.append(result) + result = cls._small_factorials[n-1] + + # GMPY factorial is faster, use it when available + # + # XXX: There is a sympy.external.gmpy.factorial function + # which provides gmpy.fac if available or the flint version + # if flint is used. It could be used here to avoid the + # conditional logic but it needs to be checked whether the + # pure Python fallback used there is as fast as the + # fallback used here (perhaps the fallback here should be + # moved to sympy.external.ntheory). + elif _gmpy is not None: + result = _gmpy.fac(n) + + else: + bits = bin(n).count('1') + result = cls._recursive(n)*2**(n - bits) + + return Integer(result) + + def _facmod(self, n, q): + res, N = 1, int(_sqrt(n)) + + # Exponent of prime p in n! is e_p(n) = [n/p] + [n/p**2] + ... + # for p > sqrt(n), e_p(n) < sqrt(n), the primes with [n/p] = m, + # occur consecutively and are grouped together in pw[m] for + # simultaneous exponentiation at a later stage + pw = [1]*N + + m = 2 # to initialize the if condition below + for prime in sieve.primerange(2, n + 1): + if m > 1: + m, y = 0, n // prime + while y: + m += y + y //= prime + if m < N: + pw[m] = pw[m]*prime % q + else: + res = res*pow(prime, m, q) % q + + for ex, bs in enumerate(pw): + if ex == 0 or bs == 1: + continue + if bs == 0: + return 0 + res = res*pow(bs, ex, q) % q + + return res + + def _eval_Mod(self, q): + n = self.args[0] + if n.is_integer and n.is_nonnegative and q.is_integer: + aq = abs(q) + d = aq - n + if d.is_nonpositive: + return S.Zero + else: + isprime = aq.is_prime + if d == 1: + # Apply Wilson's theorem (if a natural number n > 1 + # is a prime number, then (n-1)! = -1 mod n) and + # its inverse (if n > 4 is a composite number, then + # (n-1)! = 0 mod n) + if isprime: + return -1 % q + elif isprime is False and (aq - 6).is_nonnegative: + return S.Zero + elif n.is_Integer and q.is_Integer: + n, d, aq = map(int, (n, d, aq)) + if isprime and (d - 1 < n): + fc = self._facmod(d - 1, aq) + fc = pow(fc, aq - 2, aq) + if d%2: + fc = -fc + else: + fc = self._facmod(n, aq) + + return fc % q + + def _eval_rewrite_as_gamma(self, n, piecewise=True, **kwargs): + from sympy.functions.special.gamma_functions import gamma + return gamma(n + 1) + + def _eval_rewrite_as_Product(self, n, **kwargs): + from sympy.concrete.products import Product + if n.is_nonnegative and n.is_integer: + i = Dummy('i', integer=True) + return Product(i, (i, 1, n)) + + def _eval_is_integer(self): + if self.args[0].is_integer and self.args[0].is_nonnegative: + return True + + def _eval_is_positive(self): + if self.args[0].is_integer and self.args[0].is_nonnegative: + return True + + def _eval_is_even(self): + x = self.args[0] + if x.is_integer and x.is_nonnegative: + return (x - 2).is_nonnegative + + def _eval_is_composite(self): + x = self.args[0] + if x.is_integer and x.is_nonnegative: + return (x - 3).is_nonnegative + + def _eval_is_real(self): + x = self.args[0] + if x.is_nonnegative or x.is_noninteger: + return True + + def _eval_as_leading_term(self, x, logx=None, cdir=0): + arg = self.args[0].as_leading_term(x) + arg0 = arg.subs(x, 0) + if arg0.is_zero: + return S.One + elif not arg0.is_infinite: + return self.func(arg) + raise PoleError("Cannot expand %s around 0" % (self)) + +class MultiFactorial(CombinatorialFunction): + pass + + +class subfactorial(CombinatorialFunction): + r"""The subfactorial counts the derangements of $n$ items and is + defined for non-negative integers as: + + .. math:: !n = \begin{cases} 1 & n = 0 \\ 0 & n = 1 \\ + (n-1)(!(n-1) + !(n-2)) & n > 1 \end{cases} + + It can also be written as ``int(round(n!/exp(1)))`` but the + recursive definition with caching is implemented for this function. + + An interesting analytic expression is the following [2]_ + + .. math:: !x = \Gamma(x + 1, -1)/e + + which is valid for non-negative integers `x`. The above formula + is not very useful in case of non-integers. `\Gamma(x + 1, -1)` is + single-valued only for integral arguments `x`, elsewhere on the positive + real axis it has an infinite number of branches none of which are real. + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Subfactorial + .. [2] https://mathworld.wolfram.com/Subfactorial.html + + Examples + ======== + + >>> from sympy import subfactorial + >>> from sympy.abc import n + >>> subfactorial(n + 1) + subfactorial(n + 1) + >>> subfactorial(5) + 44 + + See Also + ======== + + factorial, uppergamma, + sympy.utilities.iterables.generate_derangements + """ + + @classmethod + @cacheit + def _eval(self, n): + if not n: + return S.One + elif n == 1: + return S.Zero + else: + z1, z2 = 1, 0 + for i in range(2, n + 1): + z1, z2 = z2, (i - 1)*(z2 + z1) + return z2 + + @classmethod + def eval(cls, arg): + if arg.is_Number: + if arg.is_Integer and arg.is_nonnegative: + return cls._eval(arg) + elif arg is S.NaN: + return S.NaN + elif arg is S.Infinity: + return S.Infinity + + def _eval_is_even(self): + if self.args[0].is_odd and self.args[0].is_nonnegative: + return True + + def _eval_is_integer(self): + if self.args[0].is_integer and self.args[0].is_nonnegative: + return True + + def _eval_rewrite_as_factorial(self, arg, **kwargs): + from sympy.concrete.summations import summation + i = Dummy('i') + f = S.NegativeOne**i / factorial(i) + return factorial(arg) * summation(f, (i, 0, arg)) + + def _eval_rewrite_as_gamma(self, arg, piecewise=True, **kwargs): + from sympy.functions.elementary.exponential import exp + from sympy.functions.special.gamma_functions import (gamma, lowergamma) + return (S.NegativeOne**(arg + 1)*exp(-I*pi*arg)*lowergamma(arg + 1, -1) + + gamma(arg + 1))*exp(-1) + + def _eval_rewrite_as_uppergamma(self, arg, **kwargs): + from sympy.functions.special.gamma_functions import uppergamma + return uppergamma(arg + 1, -1)/S.Exp1 + + def _eval_is_nonnegative(self): + if self.args[0].is_integer and self.args[0].is_nonnegative: + return True + + def _eval_is_odd(self): + if self.args[0].is_even and self.args[0].is_nonnegative: + return True + + +class factorial2(CombinatorialFunction): + r"""The double factorial `n!!`, not to be confused with `(n!)!` + + The double factorial is defined for nonnegative integers and for odd + negative integers as: + + .. math:: n!! = \begin{cases} 1 & n = 0 \\ + n(n-2)(n-4) \cdots 1 & n\ \text{positive odd} \\ + n(n-2)(n-4) \cdots 2 & n\ \text{positive even} \\ + (n+2)!!/(n+2) & n\ \text{negative odd} \end{cases} + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Double_factorial + + Examples + ======== + + >>> from sympy import factorial2, var + >>> n = var('n') + >>> n + n + >>> factorial2(n + 1) + factorial2(n + 1) + >>> factorial2(5) + 15 + >>> factorial2(-1) + 1 + >>> factorial2(-5) + 1/3 + + See Also + ======== + + factorial, RisingFactorial, FallingFactorial + """ + + @classmethod + def eval(cls, arg): + # TODO: extend this to complex numbers? + + if arg.is_Number: + if not arg.is_Integer: + raise ValueError("argument must be nonnegative integer " + "or negative odd integer") + + # This implementation is faster than the recursive one + # It also avoids "maximum recursion depth exceeded" runtime error + if arg.is_nonnegative: + if arg.is_even: + k = arg / 2 + return 2**k * factorial(k) + return factorial(arg) / factorial2(arg - 1) + + + if arg.is_odd: + return arg*(S.NegativeOne)**((1 - arg)/2) / factorial2(-arg) + raise ValueError("argument must be nonnegative integer " + "or negative odd integer") + + + def _eval_is_even(self): + # Double factorial is even for every positive even input + n = self.args[0] + if n.is_integer: + if n.is_odd: + return False + if n.is_even: + if n.is_positive: + return True + if n.is_zero: + return False + + def _eval_is_integer(self): + # Double factorial is an integer for every nonnegative input, and for + # -1 and -3 + n = self.args[0] + if n.is_integer: + if (n + 1).is_nonnegative: + return True + if n.is_odd: + return (n + 3).is_nonnegative + + def _eval_is_odd(self): + # Double factorial is odd for every odd input not smaller than -3, and + # for 0 + n = self.args[0] + if n.is_odd: + return (n + 3).is_nonnegative + if n.is_even: + if n.is_positive: + return False + if n.is_zero: + return True + + def _eval_is_positive(self): + # Double factorial is positive for every nonnegative input, and for + # every odd negative input which is of the form -1-4k for an + # nonnegative integer k + n = self.args[0] + if n.is_integer: + if (n + 1).is_nonnegative: + return True + if n.is_odd: + return ((n + 1) / 2).is_even + + def _eval_rewrite_as_gamma(self, n, piecewise=True, **kwargs): + from sympy.functions.elementary.miscellaneous import sqrt + from sympy.functions.elementary.piecewise import Piecewise + from sympy.functions.special.gamma_functions import gamma + return 2**(n/2)*gamma(n/2 + 1) * Piecewise((1, Eq(Mod(n, 2), 0)), + (sqrt(2/pi), Eq(Mod(n, 2), 1))) + + +############################################################################### +######################## RISING and FALLING FACTORIALS ######################## +############################################################################### + + +class RisingFactorial(CombinatorialFunction): + r""" + Rising factorial (also called Pochhammer symbol [1]_) is a double valued + function arising in concrete mathematics, hypergeometric functions + and series expansions. It is defined by: + + .. math:: \texttt{rf(y, k)} = (x)^k = x \cdot (x+1) \cdots (x+k-1) + + where `x` can be arbitrary expression and `k` is an integer. For + more information check "Concrete mathematics" by Graham, pp. 66 + or visit https://mathworld.wolfram.com/RisingFactorial.html page. + + When `x` is a `~.Poly` instance of degree $\ge 1$ with a single variable, + `(x)^k = x(y) \cdot x(y+1) \cdots x(y+k-1)`, where `y` is the + variable of `x`. This is as described in [2]_. + + Examples + ======== + + >>> from sympy import rf, Poly + >>> from sympy.abc import x + >>> rf(x, 0) + 1 + >>> rf(1, 5) + 120 + >>> rf(x, 5) == x*(1 + x)*(2 + x)*(3 + x)*(4 + x) + True + >>> rf(Poly(x**3, x), 2) + Poly(x**6 + 3*x**5 + 3*x**4 + x**3, x, domain='ZZ') + + Rewriting is complicated unless the relationship between + the arguments is known, but rising factorial can + be rewritten in terms of gamma, factorial, binomial, + and falling factorial. + + >>> from sympy import Symbol, factorial, ff, binomial, gamma + >>> n = Symbol('n', integer=True, positive=True) + >>> R = rf(n, n + 2) + >>> for i in (rf, ff, factorial, binomial, gamma): + ... R.rewrite(i) + ... + RisingFactorial(n, n + 2) + FallingFactorial(2*n + 1, n + 2) + factorial(2*n + 1)/factorial(n - 1) + binomial(2*n + 1, n + 2)*factorial(n + 2) + gamma(2*n + 2)/gamma(n) + + See Also + ======== + + factorial, factorial2, FallingFactorial + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Pochhammer_symbol + .. [2] Peter Paule, "Greatest Factorial Factorization and Symbolic + Summation", Journal of Symbolic Computation, vol. 20, pp. 235-268, + 1995. + + """ + + @classmethod + def eval(cls, x, k): + x = sympify(x) + k = sympify(k) + + if x is S.NaN or k is S.NaN: + return S.NaN + elif x is S.One: + return factorial(k) + elif k.is_Integer: + if k.is_zero: + return S.One + else: + if k.is_positive: + if x is S.Infinity: + return S.Infinity + elif x is S.NegativeInfinity: + if k.is_odd: + return S.NegativeInfinity + else: + return S.Infinity + else: + if isinstance(x, Poly): + gens = x.gens + if len(gens)!= 1: + raise ValueError("rf only defined for " + "polynomials on one generator") + else: + return reduce(lambda r, i: + r*(x.shift(i)), + range(int(k)), 1) + else: + return reduce(lambda r, i: r*(x + i), + range(int(k)), 1) + + else: + if x is S.Infinity: + return S.Infinity + elif x is S.NegativeInfinity: + return S.Infinity + else: + if isinstance(x, Poly): + gens = x.gens + if len(gens)!= 1: + raise ValueError("rf only defined for " + "polynomials on one generator") + else: + return 1/reduce(lambda r, i: + r*(x.shift(-i)), + range(1, abs(int(k)) + 1), 1) + else: + return 1/reduce(lambda r, i: + r*(x - i), + range(1, abs(int(k)) + 1), 1) + + if k.is_integer == False: + if x.is_integer and x.is_negative: + return S.Zero + + def _eval_rewrite_as_gamma(self, x, k, piecewise=True, **kwargs): + from sympy.functions.elementary.piecewise import Piecewise + from sympy.functions.special.gamma_functions import gamma + if not piecewise: + if (x <= 0) == True: + return S.NegativeOne**k*gamma(1 - x) / gamma(-k - x + 1) + return gamma(x + k) / gamma(x) + return Piecewise( + (gamma(x + k) / gamma(x), x > 0), + (S.NegativeOne**k*gamma(1 - x) / gamma(-k - x + 1), True)) + + def _eval_rewrite_as_FallingFactorial(self, x, k, **kwargs): + return FallingFactorial(x + k - 1, k) + + def _eval_rewrite_as_factorial(self, x, k, **kwargs): + from sympy.functions.elementary.piecewise import Piecewise + if x.is_integer and k.is_integer: + return Piecewise( + (factorial(k + x - 1)/factorial(x - 1), x > 0), + (S.NegativeOne**k*factorial(-x)/factorial(-k - x), True)) + + def _eval_rewrite_as_binomial(self, x, k, **kwargs): + if k.is_integer: + return factorial(k) * binomial(x + k - 1, k) + + def _eval_rewrite_as_tractable(self, x, k, limitvar=None, **kwargs): + from sympy.functions.special.gamma_functions import gamma + if limitvar: + k_lim = k.subs(limitvar, S.Infinity) + if k_lim is S.Infinity: + return (gamma(x + k).rewrite('tractable', deep=True) / gamma(x)) + elif k_lim is S.NegativeInfinity: + return (S.NegativeOne**k*gamma(1 - x) / gamma(-k - x + 1).rewrite('tractable', deep=True)) + return self.rewrite(gamma).rewrite('tractable', deep=True) + + def _eval_is_integer(self): + return fuzzy_and((self.args[0].is_integer, self.args[1].is_integer, + self.args[1].is_nonnegative)) + + +class FallingFactorial(CombinatorialFunction): + r""" + Falling factorial (related to rising factorial) is a double valued + function arising in concrete mathematics, hypergeometric functions + and series expansions. It is defined by + + .. math:: \texttt{ff(x, k)} = (x)_k = x \cdot (x-1) \cdots (x-k+1) + + where `x` can be arbitrary expression and `k` is an integer. For + more information check "Concrete mathematics" by Graham, pp. 66 + or [1]_. + + When `x` is a `~.Poly` instance of degree $\ge 1$ with single variable, + `(x)_k = x(y) \cdot x(y-1) \cdots x(y-k+1)`, where `y` is the + variable of `x`. This is as described in + + >>> from sympy import ff, Poly, Symbol + >>> from sympy.abc import x + >>> n = Symbol('n', integer=True) + + >>> ff(x, 0) + 1 + >>> ff(5, 5) + 120 + >>> ff(x, 5) == x*(x - 1)*(x - 2)*(x - 3)*(x - 4) + True + >>> ff(Poly(x**2, x), 2) + Poly(x**4 - 2*x**3 + x**2, x, domain='ZZ') + >>> ff(n, n) + factorial(n) + + Rewriting is complicated unless the relationship between + the arguments is known, but falling factorial can + be rewritten in terms of gamma, factorial and binomial + and rising factorial. + + >>> from sympy import factorial, rf, gamma, binomial, Symbol + >>> n = Symbol('n', integer=True, positive=True) + >>> F = ff(n, n - 2) + >>> for i in (rf, ff, factorial, binomial, gamma): + ... F.rewrite(i) + ... + RisingFactorial(3, n - 2) + FallingFactorial(n, n - 2) + factorial(n)/2 + binomial(n, n - 2)*factorial(n - 2) + gamma(n + 1)/2 + + See Also + ======== + + factorial, factorial2, RisingFactorial + + References + ========== + + .. [1] https://mathworld.wolfram.com/FallingFactorial.html + .. [2] Peter Paule, "Greatest Factorial Factorization and Symbolic + Summation", Journal of Symbolic Computation, vol. 20, pp. 235-268, + 1995. + + """ + + @classmethod + def eval(cls, x, k): + x = sympify(x) + k = sympify(k) + + if x is S.NaN or k is S.NaN: + return S.NaN + elif k.is_integer and x == k: + return factorial(x) + elif k.is_Integer: + if k.is_zero: + return S.One + else: + if k.is_positive: + if x is S.Infinity: + return S.Infinity + elif x is S.NegativeInfinity: + if k.is_odd: + return S.NegativeInfinity + else: + return S.Infinity + else: + if isinstance(x, Poly): + gens = x.gens + if len(gens)!= 1: + raise ValueError("ff only defined for " + "polynomials on one generator") + else: + return reduce(lambda r, i: + r*(x.shift(-i)), + range(int(k)), 1) + else: + return reduce(lambda r, i: r*(x - i), + range(int(k)), 1) + else: + if x is S.Infinity: + return S.Infinity + elif x is S.NegativeInfinity: + return S.Infinity + else: + if isinstance(x, Poly): + gens = x.gens + if len(gens)!= 1: + raise ValueError("rf only defined for " + "polynomials on one generator") + else: + return 1/reduce(lambda r, i: + r*(x.shift(i)), + range(1, abs(int(k)) + 1), 1) + else: + return 1/reduce(lambda r, i: r*(x + i), + range(1, abs(int(k)) + 1), 1) + + def _eval_rewrite_as_gamma(self, x, k, piecewise=True, **kwargs): + from sympy.functions.elementary.piecewise import Piecewise + from sympy.functions.special.gamma_functions import gamma + if not piecewise: + if (x < 0) == True: + return S.NegativeOne**k*gamma(k - x) / gamma(-x) + return gamma(x + 1) / gamma(x - k + 1) + return Piecewise( + (gamma(x + 1) / gamma(x - k + 1), x >= 0), + (S.NegativeOne**k*gamma(k - x) / gamma(-x), True)) + + def _eval_rewrite_as_RisingFactorial(self, x, k, **kwargs): + return rf(x - k + 1, k) + + def _eval_rewrite_as_binomial(self, x, k, **kwargs): + if k.is_integer: + return factorial(k) * binomial(x, k) + + def _eval_rewrite_as_factorial(self, x, k, **kwargs): + from sympy.functions.elementary.piecewise import Piecewise + if x.is_integer and k.is_integer: + return Piecewise( + (factorial(x)/factorial(-k + x), x >= 0), + (S.NegativeOne**k*factorial(k - x - 1)/factorial(-x - 1), True)) + + def _eval_rewrite_as_tractable(self, x, k, limitvar=None, **kwargs): + from sympy.functions.special.gamma_functions import gamma + if limitvar: + k_lim = k.subs(limitvar, S.Infinity) + if k_lim is S.Infinity: + return (S.NegativeOne**k*gamma(k - x).rewrite('tractable', deep=True) / gamma(-x)) + elif k_lim is S.NegativeInfinity: + return (gamma(x + 1) / gamma(x - k + 1).rewrite('tractable', deep=True)) + return self.rewrite(gamma).rewrite('tractable', deep=True) + + def _eval_is_integer(self): + return fuzzy_and((self.args[0].is_integer, self.args[1].is_integer, + self.args[1].is_nonnegative)) + + +rf = RisingFactorial +ff = FallingFactorial + +############################################################################### +########################### BINOMIAL COEFFICIENTS ############################# +############################################################################### + + +class binomial(CombinatorialFunction): + r"""Implementation of the binomial coefficient. It can be defined + in two ways depending on its desired interpretation: + + .. math:: \binom{n}{k} = \frac{n!}{k!(n-k)!}\ \text{or}\ + \binom{n}{k} = \frac{(n)_k}{k!} + + First, in a strict combinatorial sense it defines the + number of ways we can choose `k` elements from a set of + `n` elements. In this case both arguments are nonnegative + integers and binomial is computed using an efficient + algorithm based on prime factorization. + + The other definition is generalization for arbitrary `n`, + however `k` must also be nonnegative. This case is very + useful when evaluating summations. + + For the sake of convenience, for negative integer `k` this function + will return zero no matter the other argument. + + To expand the binomial when `n` is a symbol, use either + ``expand_func()`` or ``expand(func=True)``. The former will keep + the polynomial in factored form while the latter will expand the + polynomial itself. See examples for details. + + Examples + ======== + + >>> from sympy import Symbol, Rational, binomial, expand_func + >>> n = Symbol('n', integer=True, positive=True) + + >>> binomial(15, 8) + 6435 + + >>> binomial(n, -1) + 0 + + Rows of Pascal's triangle can be generated with the binomial function: + + >>> for N in range(8): + ... print([binomial(N, i) for i in range(N + 1)]) + ... + [1] + [1, 1] + [1, 2, 1] + [1, 3, 3, 1] + [1, 4, 6, 4, 1] + [1, 5, 10, 10, 5, 1] + [1, 6, 15, 20, 15, 6, 1] + [1, 7, 21, 35, 35, 21, 7, 1] + + As can a given diagonal, e.g. the 4th diagonal: + + >>> N = -4 + >>> [binomial(N, i) for i in range(1 - N)] + [1, -4, 10, -20, 35] + + >>> binomial(Rational(5, 4), 3) + -5/128 + >>> binomial(Rational(-5, 4), 3) + -195/128 + + >>> binomial(n, 3) + binomial(n, 3) + + >>> binomial(n, 3).expand(func=True) + n**3/6 - n**2/2 + n/3 + + >>> expand_func(binomial(n, 3)) + n*(n - 2)*(n - 1)/6 + + In many cases, we can also compute binomial coefficients modulo a + prime p quickly using Lucas' Theorem [2]_, though we need to include + `evaluate=False` to postpone evaluation: + + >>> from sympy import Mod + >>> Mod(binomial(156675, 4433, evaluate=False), 10**5 + 3) + 28625 + + Using a generalisation of Lucas's Theorem given by Granville [3]_, + we can extend this to arbitrary n: + + >>> Mod(binomial(10**18, 10**12, evaluate=False), (10**5 + 3)**2) + 3744312326 + + References + ========== + + .. [1] https://www.johndcook.com/blog/binomial_coefficients/ + .. [2] https://en.wikipedia.org/wiki/Lucas%27s_theorem + .. [3] Binomial coefficients modulo prime powers, Andrew Granville, + Available: https://web.archive.org/web/20170202003812/http://www.dms.umontreal.ca/~andrew/PDF/BinCoeff.pdf + """ + + def fdiff(self, argindex=1): + from sympy.functions.special.gamma_functions import polygamma + if argindex == 1: + # https://functions.wolfram.com/GammaBetaErf/Binomial/20/01/01/ + n, k = self.args + return binomial(n, k)*(polygamma(0, n + 1) - \ + polygamma(0, n - k + 1)) + elif argindex == 2: + # https://functions.wolfram.com/GammaBetaErf/Binomial/20/01/02/ + n, k = self.args + return binomial(n, k)*(polygamma(0, n - k + 1) - \ + polygamma(0, k + 1)) + else: + raise ArgumentIndexError(self, argindex) + + @classmethod + def _eval(self, n, k): + # n.is_Number and k.is_Integer and k != 1 and n != k + + if k.is_Integer: + if n.is_Integer and n >= 0: + n, k = int(n), int(k) + + if k > n: + return S.Zero + elif k > n // 2: + k = n - k + + # XXX: This conditional logic should be moved to + # sympy.external.gmpy and the pure Python version of bincoef + # should be moved to sympy.external.ntheory. + if _gmpy is not None: + return Integer(_gmpy.bincoef(n, k)) + + d, result = n - k, 1 + for i in range(1, k + 1): + d += 1 + result = result * d // i + return Integer(result) + else: + d, result = n - k, 1 + for i in range(1, k + 1): + d += 1 + result *= d + return result / _factorial(k) + + @classmethod + def eval(cls, n, k): + n, k = map(sympify, (n, k)) + d = n - k + n_nonneg, n_isint = n.is_nonnegative, n.is_integer + if k.is_zero or ((n_nonneg or n_isint is False) + and d.is_zero): + return S.One + if (k - 1).is_zero or ((n_nonneg or n_isint is False) + and (d - 1).is_zero): + return n + if k.is_integer: + if k.is_negative or (n_nonneg and n_isint and d.is_negative): + return S.Zero + elif n.is_number: + res = cls._eval(n, k) + return res.expand(basic=True) if res else res + elif n_nonneg is False and n_isint: + # a special case when binomial evaluates to complex infinity + return S.ComplexInfinity + elif k.is_number: + from sympy.functions.special.gamma_functions import gamma + return gamma(n + 1)/(gamma(k + 1)*gamma(n - k + 1)) + + def _eval_Mod(self, q): + n, k = self.args + + if any(x.is_integer is False for x in (n, k, q)): + raise ValueError("Integers expected for binomial Mod") + + if all(x.is_Integer for x in (n, k, q)): + n, k = map(int, (n, k)) + aq, res = abs(q), 1 + + # handle negative integers k or n + if k < 0: + return S.Zero + if n < 0: + n = -n + k - 1 + res = -1 if k%2 else 1 + + # non negative integers k and n + if k > n: + return S.Zero + + isprime = aq.is_prime + aq = int(aq) + if isprime: + if aq < n: + # use Lucas Theorem + N, K = n, k + while N or K: + res = res*binomial(N % aq, K % aq) % aq + N, K = N // aq, K // aq + + else: + # use Factorial Modulo + d = n - k + if k > d: + k, d = d, k + kf = 1 + for i in range(2, k + 1): + kf = kf*i % aq + df = kf + for i in range(k + 1, d + 1): + df = df*i % aq + res *= df + for i in range(d + 1, n + 1): + res = res*i % aq + + res *= pow(kf*df % aq, aq - 2, aq) + res %= aq + + elif _sqrt(q) < k and q != 1: + res = binomial_mod(n, k, q) + + else: + # Binomial Factorization is performed by calculating the + # exponents of primes <= n in `n! /(k! (n - k)!)`, + # for non-negative integers n and k. As the exponent of + # prime in n! is e_p(n) = [n/p] + [n/p**2] + ... + # the exponent of prime in binomial(n, k) would be + # e_p(n) - e_p(k) - e_p(n - k) + M = int(_sqrt(n)) + for prime in sieve.primerange(2, n + 1): + if prime > n - k: + res = res*prime % aq + elif prime > n // 2: + continue + elif prime > M: + if n % prime < k % prime: + res = res*prime % aq + else: + N, K = n, k + exp = a = 0 + + while N > 0: + a = int((N % prime) < (K % prime + a)) + N, K = N // prime, K // prime + exp += a + + if exp > 0: + res *= pow(prime, exp, aq) + res %= aq + + return S(res % q) + + def _eval_expand_func(self, **hints): + """ + Function to expand binomial(n, k) when m is positive integer + Also, + n is self.args[0] and k is self.args[1] while using binomial(n, k) + """ + n = self.args[0] + if n.is_Number: + return binomial(*self.args) + + k = self.args[1] + if (n-k).is_Integer: + k = n - k + + if k.is_Integer: + if k.is_zero: + return S.One + elif k.is_negative: + return S.Zero + else: + n, result = self.args[0], 1 + for i in range(1, k + 1): + result *= n - k + i + return result / _factorial(k) + else: + return binomial(*self.args) + + def _eval_rewrite_as_factorial(self, n, k, **kwargs): + return factorial(n)/(factorial(k)*factorial(n - k)) + + def _eval_rewrite_as_gamma(self, n, k, piecewise=True, **kwargs): + from sympy.functions.special.gamma_functions import gamma + return gamma(n + 1)/(gamma(k + 1)*gamma(n - k + 1)) + + def _eval_rewrite_as_tractable(self, n, k, limitvar=None, **kwargs): + return self._eval_rewrite_as_gamma(n, k).rewrite('tractable') + + def _eval_rewrite_as_FallingFactorial(self, n, k, **kwargs): + if k.is_integer: + return ff(n, k) / factorial(k) + + def _eval_is_integer(self): + n, k = self.args + if n.is_integer and k.is_integer: + return True + elif k.is_integer is False: + return False + + def _eval_is_nonnegative(self): + n, k = self.args + if n.is_integer and k.is_integer: + if n.is_nonnegative or k.is_negative or k.is_even: + return True + elif k.is_even is False: + return False + + def _eval_as_leading_term(self, x, logx=None, cdir=0): + from sympy.functions.special.gamma_functions import gamma + return self.rewrite(gamma)._eval_as_leading_term(x, logx=logx, cdir=cdir) diff --git a/lib/python3.12/site-packages/sympy/functions/combinatorial/numbers.py b/lib/python3.12/site-packages/sympy/functions/combinatorial/numbers.py new file mode 100644 index 0000000000000000000000000000000000000000..a70d7ac7394c7dd6eb03c48b4936ef67aabebf8e --- /dev/null +++ b/lib/python3.12/site-packages/sympy/functions/combinatorial/numbers.py @@ -0,0 +1,3169 @@ +""" +This module implements some special functions that commonly appear in +combinatorial contexts (e.g. in power series); in particular, +sequences of rational numbers such as Bernoulli and Fibonacci numbers. + +Factorials, binomial coefficients and related functions are located in +the separate 'factorials' module. +""" +from math import prod +from collections import defaultdict +from typing import Tuple as tTuple + +from sympy.core import S, Symbol, Add, Dummy +from sympy.core.cache import cacheit +from sympy.core.containers import Dict +from sympy.core.expr import Expr +from sympy.core.function import ArgumentIndexError, Function, expand_mul +from sympy.core.logic import fuzzy_not +from sympy.core.mul import Mul +from sympy.core.numbers import E, I, pi, oo, Rational, Integer +from sympy.core.relational import Eq, is_le, is_gt, is_lt +from sympy.external.gmpy import SYMPY_INTS, remove, lcm, legendre, jacobi, kronecker +from sympy.functions.combinatorial.factorials import (binomial, + factorial, subfactorial) +from sympy.functions.elementary.exponential import log +from sympy.functions.elementary.piecewise import Piecewise +from sympy.ntheory.factor_ import (factorint, _divisor_sigma, is_carmichael, + find_carmichael_numbers_in_range, find_first_n_carmichaels) +from sympy.ntheory.generate import _primepi +from sympy.ntheory.partitions_ import _partition, _partition_rec +from sympy.ntheory.primetest import isprime, is_square +from sympy.polys.appellseqs import bernoulli_poly, euler_poly, genocchi_poly +from sympy.polys.polytools import cancel +from sympy.utilities.enumerative import MultisetPartitionTraverser +from sympy.utilities.exceptions import sympy_deprecation_warning +from sympy.utilities.iterables import multiset, multiset_derangements, iterable +from sympy.utilities.memoization import recurrence_memo +from sympy.utilities.misc import as_int + +from mpmath import mp, workprec +from mpmath.libmp import ifib as _ifib + + +def _product(a, b): + return prod(range(a, b + 1)) + + +# Dummy symbol used for computing polynomial sequences +_sym = Symbol('x') + + +#----------------------------------------------------------------------------# +# # +# Carmichael numbers # +# # +#----------------------------------------------------------------------------# + +class carmichael(Function): + r""" + Carmichael Numbers: + + Certain cryptographic algorithms make use of big prime numbers. + However, checking whether a big number is prime is not so easy. + Randomized prime number checking tests exist that offer a high degree of + confidence of accurate determination at low cost, such as the Fermat test. + + Let 'a' be a random number between $2$ and $n - 1$, where $n$ is the + number whose primality we are testing. Then, $n$ is probably prime if it + satisfies the modular arithmetic congruence relation: + + .. math :: a^{n-1} = 1 \pmod{n} + + (where mod refers to the modulo operation) + + If a number passes the Fermat test several times, then it is prime with a + high probability. + + Unfortunately, certain composite numbers (non-primes) still pass the Fermat + test with every number smaller than themselves. + These numbers are called Carmichael numbers. + + A Carmichael number will pass a Fermat primality test to every base $b$ + relatively prime to the number, even though it is not actually prime. + This makes tests based on Fermat's Little Theorem less effective than + strong probable prime tests such as the Baillie-PSW primality test and + the Miller-Rabin primality test. + + Examples + ======== + + >>> from sympy.ntheory.factor_ import find_first_n_carmichaels, find_carmichael_numbers_in_range + >>> find_first_n_carmichaels(5) + [561, 1105, 1729, 2465, 2821] + >>> find_carmichael_numbers_in_range(0, 562) + [561] + >>> find_carmichael_numbers_in_range(0,1000) + [561] + >>> find_carmichael_numbers_in_range(0,2000) + [561, 1105, 1729] + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Carmichael_number + .. [2] https://en.wikipedia.org/wiki/Fermat_primality_test + .. [3] https://www.jstor.org/stable/23248683?seq=1#metadata_info_tab_contents + """ + + @staticmethod + def is_perfect_square(n): + sympy_deprecation_warning( + """ +is_perfect_square is just a wrapper around sympy.ntheory.primetest.is_square +so use that directly instead. + """, + deprecated_since_version="1.11", + active_deprecations_target='deprecated-carmichael-static-methods', + ) + return is_square(n) + + @staticmethod + def divides(p, n): + sympy_deprecation_warning( + """ + divides can be replaced by directly testing n % p == 0. + """, + deprecated_since_version="1.11", + active_deprecations_target='deprecated-carmichael-static-methods', + ) + return n % p == 0 + + @staticmethod + def is_prime(n): + sympy_deprecation_warning( + """ +is_prime is just a wrapper around sympy.ntheory.primetest.isprime so use that +directly instead. + """, + deprecated_since_version="1.11", + active_deprecations_target='deprecated-carmichael-static-methods', + ) + return isprime(n) + + @staticmethod + def is_carmichael(n): + sympy_deprecation_warning( + """ +is_carmichael is just a wrapper around sympy.ntheory.factor_.is_carmichael so use that +directly instead. + """, + deprecated_since_version="1.13", + active_deprecations_target='deprecated-ntheory-symbolic-functions', + ) + return is_carmichael(n) + + @staticmethod + def find_carmichael_numbers_in_range(x, y): + sympy_deprecation_warning( + """ +find_carmichael_numbers_in_range is just a wrapper around sympy.ntheory.factor_.find_carmichael_numbers_in_range so use that +directly instead. + """, + deprecated_since_version="1.13", + active_deprecations_target='deprecated-ntheory-symbolic-functions', + ) + return find_carmichael_numbers_in_range(x, y) + + @staticmethod + def find_first_n_carmichaels(n): + sympy_deprecation_warning( + """ +find_first_n_carmichaels is just a wrapper around sympy.ntheory.factor_.find_first_n_carmichaels so use that +directly instead. + """, + deprecated_since_version="1.13", + active_deprecations_target='deprecated-ntheory-symbolic-functions', + ) + return find_first_n_carmichaels(n) + + +#----------------------------------------------------------------------------# +# # +# Fibonacci numbers # +# # +#----------------------------------------------------------------------------# + + +class fibonacci(Function): + r""" + Fibonacci numbers / Fibonacci polynomials + + The Fibonacci numbers are the integer sequence defined by the + initial terms `F_0 = 0`, `F_1 = 1` and the two-term recurrence + relation `F_n = F_{n-1} + F_{n-2}`. This definition + extended to arbitrary real and complex arguments using + the formula + + .. math :: F_z = \frac{\phi^z - \cos(\pi z) \phi^{-z}}{\sqrt 5} + + The Fibonacci polynomials are defined by `F_1(x) = 1`, + `F_2(x) = x`, and `F_n(x) = x*F_{n-1}(x) + F_{n-2}(x)` for `n > 2`. + For all positive integers `n`, `F_n(1) = F_n`. + + * ``fibonacci(n)`` gives the `n^{th}` Fibonacci number, `F_n` + * ``fibonacci(n, x)`` gives the `n^{th}` Fibonacci polynomial in `x`, `F_n(x)` + + Examples + ======== + + >>> from sympy import fibonacci, Symbol + + >>> [fibonacci(x) for x in range(11)] + [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55] + >>> fibonacci(5, Symbol('t')) + t**4 + 3*t**2 + 1 + + See Also + ======== + + bell, bernoulli, catalan, euler, harmonic, lucas, genocchi, partition, tribonacci + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Fibonacci_number + .. [2] https://mathworld.wolfram.com/FibonacciNumber.html + + """ + + @staticmethod + def _fib(n): + return _ifib(n) + + @staticmethod + @recurrence_memo([None, S.One, _sym]) + def _fibpoly(n, prev): + return (prev[-2] + _sym*prev[-1]).expand() + + @classmethod + def eval(cls, n, sym=None): + if n is S.Infinity: + return S.Infinity + + if n.is_Integer: + if sym is None: + n = int(n) + if n < 0: + return S.NegativeOne**(n + 1) * fibonacci(-n) + else: + return Integer(cls._fib(n)) + else: + if n < 1: + raise ValueError("Fibonacci polynomials are defined " + "only for positive integer indices.") + return cls._fibpoly(n).subs(_sym, sym) + + def _eval_rewrite_as_tractable(self, n, **kwargs): + from sympy.functions import sqrt, cos + return (S.GoldenRatio**n - cos(S.Pi*n)/S.GoldenRatio**n)/sqrt(5) + + def _eval_rewrite_as_sqrt(self, n, **kwargs): + from sympy.functions.elementary.miscellaneous import sqrt + return 2**(-n)*sqrt(5)*((1 + sqrt(5))**n - (-sqrt(5) + 1)**n) / 5 + + def _eval_rewrite_as_GoldenRatio(self,n, **kwargs): + return (S.GoldenRatio**n - 1/(-S.GoldenRatio)**n)/(2*S.GoldenRatio-1) + + +#----------------------------------------------------------------------------# +# # +# Lucas numbers # +# # +#----------------------------------------------------------------------------# + + +class lucas(Function): + """ + Lucas numbers + + Lucas numbers satisfy a recurrence relation similar to that of + the Fibonacci sequence, in which each term is the sum of the + preceding two. They are generated by choosing the initial + values `L_0 = 2` and `L_1 = 1`. + + * ``lucas(n)`` gives the `n^{th}` Lucas number + + Examples + ======== + + >>> from sympy import lucas + + >>> [lucas(x) for x in range(11)] + [2, 1, 3, 4, 7, 11, 18, 29, 47, 76, 123] + + See Also + ======== + + bell, bernoulli, catalan, euler, fibonacci, harmonic, genocchi, partition, tribonacci + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Lucas_number + .. [2] https://mathworld.wolfram.com/LucasNumber.html + + """ + + @classmethod + def eval(cls, n): + if n is S.Infinity: + return S.Infinity + + if n.is_Integer: + return fibonacci(n + 1) + fibonacci(n - 1) + + def _eval_rewrite_as_sqrt(self, n, **kwargs): + from sympy.functions.elementary.miscellaneous import sqrt + return 2**(-n)*((1 + sqrt(5))**n + (-sqrt(5) + 1)**n) + + +#----------------------------------------------------------------------------# +# # +# Tribonacci numbers # +# # +#----------------------------------------------------------------------------# + + +class tribonacci(Function): + r""" + Tribonacci numbers / Tribonacci polynomials + + The Tribonacci numbers are the integer sequence defined by the + initial terms `T_0 = 0`, `T_1 = 1`, `T_2 = 1` and the three-term + recurrence relation `T_n = T_{n-1} + T_{n-2} + T_{n-3}`. + + The Tribonacci polynomials are defined by `T_0(x) = 0`, `T_1(x) = 1`, + `T_2(x) = x^2`, and `T_n(x) = x^2 T_{n-1}(x) + x T_{n-2}(x) + T_{n-3}(x)` + for `n > 2`. For all positive integers `n`, `T_n(1) = T_n`. + + * ``tribonacci(n)`` gives the `n^{th}` Tribonacci number, `T_n` + * ``tribonacci(n, x)`` gives the `n^{th}` Tribonacci polynomial in `x`, `T_n(x)` + + Examples + ======== + + >>> from sympy import tribonacci, Symbol + + >>> [tribonacci(x) for x in range(11)] + [0, 1, 1, 2, 4, 7, 13, 24, 44, 81, 149] + >>> tribonacci(5, Symbol('t')) + t**8 + 3*t**5 + 3*t**2 + + See Also + ======== + + bell, bernoulli, catalan, euler, fibonacci, harmonic, lucas, genocchi, partition + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Generalizations_of_Fibonacci_numbers#Tribonacci_numbers + .. [2] https://mathworld.wolfram.com/TribonacciNumber.html + .. [3] https://oeis.org/A000073 + + """ + + @staticmethod + @recurrence_memo([S.Zero, S.One, S.One]) + def _trib(n, prev): + return (prev[-3] + prev[-2] + prev[-1]) + + @staticmethod + @recurrence_memo([S.Zero, S.One, _sym**2]) + def _tribpoly(n, prev): + return (prev[-3] + _sym*prev[-2] + _sym**2*prev[-1]).expand() + + @classmethod + def eval(cls, n, sym=None): + if n is S.Infinity: + return S.Infinity + + if n.is_Integer: + n = int(n) + if n < 0: + raise ValueError("Tribonacci polynomials are defined " + "only for non-negative integer indices.") + if sym is None: + return Integer(cls._trib(n)) + else: + return cls._tribpoly(n).subs(_sym, sym) + + def _eval_rewrite_as_sqrt(self, n, **kwargs): + from sympy.functions.elementary.miscellaneous import cbrt, sqrt + w = (-1 + S.ImaginaryUnit * sqrt(3)) / 2 + a = (1 + cbrt(19 + 3*sqrt(33)) + cbrt(19 - 3*sqrt(33))) / 3 + b = (1 + w*cbrt(19 + 3*sqrt(33)) + w**2*cbrt(19 - 3*sqrt(33))) / 3 + c = (1 + w**2*cbrt(19 + 3*sqrt(33)) + w*cbrt(19 - 3*sqrt(33))) / 3 + Tn = (a**(n + 1)/((a - b)*(a - c)) + + b**(n + 1)/((b - a)*(b - c)) + + c**(n + 1)/((c - a)*(c - b))) + return Tn + + def _eval_rewrite_as_TribonacciConstant(self, n, **kwargs): + from sympy.functions.elementary.integers import floor + from sympy.functions.elementary.miscellaneous import cbrt, sqrt + b = cbrt(586 + 102*sqrt(33)) + Tn = 3 * b * S.TribonacciConstant**n / (b**2 - 2*b + 4) + return floor(Tn + S.Half) + + +#----------------------------------------------------------------------------# +# # +# Bernoulli numbers # +# # +#----------------------------------------------------------------------------# + + +class bernoulli(Function): + r""" + Bernoulli numbers / Bernoulli polynomials / Bernoulli function + + The Bernoulli numbers are a sequence of rational numbers + defined by `B_0 = 1` and the recursive relation (`n > 0`): + + .. math :: n+1 = \sum_{k=0}^n \binom{n+1}{k} B_k + + They are also commonly defined by their exponential generating + function, which is `\frac{x}{1 - e^{-x}}`. For odd indices > 1, + the Bernoulli numbers are zero. + + The Bernoulli polynomials satisfy the analogous formula: + + .. math :: B_n(x) = \sum_{k=0}^n (-1)^k \binom{n}{k} B_k x^{n-k} + + Bernoulli numbers and Bernoulli polynomials are related as + `B_n(1) = B_n`. + + The generalized Bernoulli function `\operatorname{B}(s, a)` + is defined for any complex `s` and `a`, except where `a` is a + nonpositive integer and `s` is not a nonnegative integer. It is + an entire function of `s` for fixed `a`, related to the Hurwitz + zeta function by + + .. math:: \operatorname{B}(s, a) = \begin{cases} + -s \zeta(1-s, a) & s \ne 0 \\ 1 & s = 0 \end{cases} + + When `s` is a nonnegative integer this function reduces to the + Bernoulli polynomials: `\operatorname{B}(n, x) = B_n(x)`. When + `a` is omitted it is assumed to be 1, yielding the (ordinary) + Bernoulli function which interpolates the Bernoulli numbers and is + related to the Riemann zeta function. + + We compute Bernoulli numbers using Ramanujan's formula: + + .. math :: B_n = \frac{A(n) - S(n)}{\binom{n+3}{n}} + + where: + + .. math :: A(n) = \begin{cases} \frac{n+3}{3} & + n \equiv 0\ \text{or}\ 2 \pmod{6} \\ + -\frac{n+3}{6} & n \equiv 4 \pmod{6} \end{cases} + + and: + + .. math :: S(n) = \sum_{k=1}^{[n/6]} \binom{n+3}{n-6k} B_{n-6k} + + This formula is similar to the sum given in the definition, but + cuts `\frac{2}{3}` of the terms. For Bernoulli polynomials, we use + Appell sequences. + + For `n` a nonnegative integer and `s`, `a`, `x` arbitrary complex numbers, + + * ``bernoulli(n)`` gives the nth Bernoulli number, `B_n` + * ``bernoulli(s)`` gives the Bernoulli function `\operatorname{B}(s)` + * ``bernoulli(n, x)`` gives the nth Bernoulli polynomial in `x`, `B_n(x)` + * ``bernoulli(s, a)`` gives the generalized Bernoulli function + `\operatorname{B}(s, a)` + + .. versionchanged:: 1.12 + ``bernoulli(1)`` gives `+\frac{1}{2}` instead of `-\frac{1}{2}`. + This choice of value confers several theoretical advantages [5]_, + including the extension to complex parameters described above + which this function now implements. The previous behavior, defined + only for nonnegative integers `n`, can be obtained with + ``(-1)**n*bernoulli(n)``. + + Examples + ======== + + >>> from sympy import bernoulli + >>> from sympy.abc import x + >>> [bernoulli(n) for n in range(11)] + [1, 1/2, 1/6, 0, -1/30, 0, 1/42, 0, -1/30, 0, 5/66] + >>> bernoulli(1000001) + 0 + >>> bernoulli(3, x) + x**3 - 3*x**2/2 + x/2 + + See Also + ======== + + andre, bell, catalan, euler, fibonacci, harmonic, lucas, genocchi, + partition, tribonacci, sympy.polys.appellseqs.bernoulli_poly + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Bernoulli_number + .. [2] https://en.wikipedia.org/wiki/Bernoulli_polynomial + .. [3] https://mathworld.wolfram.com/BernoulliNumber.html + .. [4] https://mathworld.wolfram.com/BernoulliPolynomial.html + .. [5] Peter Luschny, "The Bernoulli Manifesto", + https://luschny.de/math/zeta/The-Bernoulli-Manifesto.html + .. [6] Peter Luschny, "An introduction to the Bernoulli function", + https://arxiv.org/abs/2009.06743 + + """ + + args: tTuple[Integer] + + # Calculates B_n for positive even n + @staticmethod + def _calc_bernoulli(n): + s = 0 + a = int(binomial(n + 3, n - 6)) + for j in range(1, n//6 + 1): + s += a * bernoulli(n - 6*j) + # Avoid computing each binomial coefficient from scratch + a *= _product(n - 6 - 6*j + 1, n - 6*j) + a //= _product(6*j + 4, 6*j + 9) + if n % 6 == 4: + s = -Rational(n + 3, 6) - s + else: + s = Rational(n + 3, 3) - s + return s / binomial(n + 3, n) + + # We implement a specialized memoization scheme to handle each + # case modulo 6 separately + _cache = {0: S.One, 1: Rational(1, 2), 2: Rational(1, 6), 4: Rational(-1, 30)} + _highest = {0: 0, 1: 1, 2: 2, 4: 4} + + @classmethod + def eval(cls, n, x=None): + if x is S.One: + return cls(n) + elif n.is_zero: + return S.One + elif n.is_integer is False or n.is_nonnegative is False: + if x is not None and x.is_Integer and x.is_nonpositive: + return S.NaN + return + # Bernoulli numbers + elif x is None: + if n is S.One: + return S.Half + elif n.is_odd and (n-1).is_positive: + return S.Zero + elif n.is_Number: + n = int(n) + # Use mpmath for enormous Bernoulli numbers + if n > 500: + p, q = mp.bernfrac(n) + return Rational(int(p), int(q)) + case = n % 6 + highest_cached = cls._highest[case] + if n <= highest_cached: + return cls._cache[n] + # To avoid excessive recursion when, say, bernoulli(1000) is + # requested, calculate and cache the entire sequence ... B_988, + # B_994, B_1000 in increasing order + for i in range(highest_cached + 6, n + 6, 6): + b = cls._calc_bernoulli(i) + cls._cache[i] = b + cls._highest[case] = i + return b + # Bernoulli polynomials + elif n.is_Number: + return bernoulli_poly(n, x) + + def _eval_rewrite_as_zeta(self, n, x=1, **kwargs): + from sympy.functions.special.zeta_functions import zeta + return Piecewise((1, Eq(n, 0)), (-n * zeta(1-n, x), True)) + + def _eval_evalf(self, prec): + if not all(x.is_number for x in self.args): + return + n = self.args[0]._to_mpmath(prec) + x = (self.args[1] if len(self.args) > 1 else S.One)._to_mpmath(prec) + with workprec(prec): + if n == 0: + res = mp.mpf(1) + elif n == 1: + res = x - mp.mpf(0.5) + elif mp.isint(n) and n >= 0: + res = mp.bernoulli(n) if x == 1 else mp.bernpoly(n, x) + else: + res = -n * mp.zeta(1-n, x) + return Expr._from_mpmath(res, prec) + + +#----------------------------------------------------------------------------# +# # +# Bell numbers # +# # +#----------------------------------------------------------------------------# + + +class bell(Function): + r""" + Bell numbers / Bell polynomials + + The Bell numbers satisfy `B_0 = 1` and + + .. math:: B_n = \sum_{k=0}^{n-1} \binom{n-1}{k} B_k. + + They are also given by: + + .. math:: B_n = \frac{1}{e} \sum_{k=0}^{\infty} \frac{k^n}{k!}. + + The Bell polynomials are given by `B_0(x) = 1` and + + .. math:: B_n(x) = x \sum_{k=1}^{n-1} \binom{n-1}{k-1} B_{k-1}(x). + + The second kind of Bell polynomials (are sometimes called "partial" Bell + polynomials or incomplete Bell polynomials) are defined as + + .. math:: B_{n,k}(x_1, x_2,\dotsc x_{n-k+1}) = + \sum_{j_1+j_2+j_2+\dotsb=k \atop j_1+2j_2+3j_2+\dotsb=n} + \frac{n!}{j_1!j_2!\dotsb j_{n-k+1}!} + \left(\frac{x_1}{1!} \right)^{j_1} + \left(\frac{x_2}{2!} \right)^{j_2} \dotsb + \left(\frac{x_{n-k+1}}{(n-k+1)!} \right) ^{j_{n-k+1}}. + + * ``bell(n)`` gives the `n^{th}` Bell number, `B_n`. + * ``bell(n, x)`` gives the `n^{th}` Bell polynomial, `B_n(x)`. + * ``bell(n, k, (x1, x2, ...))`` gives Bell polynomials of the second kind, + `B_{n,k}(x_1, x_2, \dotsc, x_{n-k+1})`. + + Notes + ===== + + Not to be confused with Bernoulli numbers and Bernoulli polynomials, + which use the same notation. + + Examples + ======== + + >>> from sympy import bell, Symbol, symbols + + >>> [bell(n) for n in range(11)] + [1, 1, 2, 5, 15, 52, 203, 877, 4140, 21147, 115975] + >>> bell(30) + 846749014511809332450147 + >>> bell(4, Symbol('t')) + t**4 + 6*t**3 + 7*t**2 + t + >>> bell(6, 2, symbols('x:6')[1:]) + 6*x1*x5 + 15*x2*x4 + 10*x3**2 + + See Also + ======== + + bernoulli, catalan, euler, fibonacci, harmonic, lucas, genocchi, partition, tribonacci + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Bell_number + .. [2] https://mathworld.wolfram.com/BellNumber.html + .. [3] https://mathworld.wolfram.com/BellPolynomial.html + + """ + + @staticmethod + @recurrence_memo([1, 1]) + def _bell(n, prev): + s = 1 + a = 1 + for k in range(1, n): + a = a * (n - k) // k + s += a * prev[k] + return s + + @staticmethod + @recurrence_memo([S.One, _sym]) + def _bell_poly(n, prev): + s = 1 + a = 1 + for k in range(2, n + 1): + a = a * (n - k + 1) // (k - 1) + s += a * prev[k - 1] + return expand_mul(_sym * s) + + @staticmethod + def _bell_incomplete_poly(n, k, symbols): + r""" + The second kind of Bell polynomials (incomplete Bell polynomials). + + Calculated by recurrence formula: + + .. math:: B_{n,k}(x_1, x_2, \dotsc, x_{n-k+1}) = + \sum_{m=1}^{n-k+1} + \x_m \binom{n-1}{m-1} B_{n-m,k-1}(x_1, x_2, \dotsc, x_{n-m-k}) + + where + `B_{0,0} = 1;` + `B_{n,0} = 0; for n \ge 1` + `B_{0,k} = 0; for k \ge 1` + + """ + if (n == 0) and (k == 0): + return S.One + elif (n == 0) or (k == 0): + return S.Zero + s = S.Zero + a = S.One + for m in range(1, n - k + 2): + s += a * bell._bell_incomplete_poly( + n - m, k - 1, symbols) * symbols[m - 1] + a = a * (n - m) / m + return expand_mul(s) + + @classmethod + def eval(cls, n, k_sym=None, symbols=None): + if n is S.Infinity: + if k_sym is None: + return S.Infinity + else: + raise ValueError("Bell polynomial is not defined") + + if n.is_negative or n.is_integer is False: + raise ValueError("a non-negative integer expected") + + if n.is_Integer and n.is_nonnegative: + if k_sym is None: + return Integer(cls._bell(int(n))) + elif symbols is None: + return cls._bell_poly(int(n)).subs(_sym, k_sym) + else: + r = cls._bell_incomplete_poly(int(n), int(k_sym), symbols) + return r + + def _eval_rewrite_as_Sum(self, n, k_sym=None, symbols=None, **kwargs): + from sympy.concrete.summations import Sum + if (k_sym is not None) or (symbols is not None): + return self + + # Dobinski's formula + if not n.is_nonnegative: + return self + k = Dummy('k', integer=True, nonnegative=True) + return 1 / E * Sum(k**n / factorial(k), (k, 0, S.Infinity)) + + +#----------------------------------------------------------------------------# +# # +# Harmonic numbers # +# # +#----------------------------------------------------------------------------# + + +class harmonic(Function): + r""" + Harmonic numbers + + The nth harmonic number is given by `\operatorname{H}_{n} = + 1 + \frac{1}{2} + \frac{1}{3} + \ldots + \frac{1}{n}`. + + More generally: + + .. math:: \operatorname{H}_{n,m} = \sum_{k=1}^{n} \frac{1}{k^m} + + As `n \rightarrow \infty`, `\operatorname{H}_{n,m} \rightarrow \zeta(m)`, + the Riemann zeta function. + + * ``harmonic(n)`` gives the nth harmonic number, `\operatorname{H}_n` + + * ``harmonic(n, m)`` gives the nth generalized harmonic number + of order `m`, `\operatorname{H}_{n,m}`, where + ``harmonic(n) == harmonic(n, 1)`` + + This function can be extended to complex `n` and `m` where `n` is not a + negative integer or `m` is a nonpositive integer as + + .. math:: \operatorname{H}_{n,m} = \begin{cases} \zeta(m) - \zeta(m, n+1) + & m \ne 1 \\ \psi(n+1) + \gamma & m = 1 \end{cases} + + Examples + ======== + + >>> from sympy import harmonic, oo + + >>> [harmonic(n) for n in range(6)] + [0, 1, 3/2, 11/6, 25/12, 137/60] + >>> [harmonic(n, 2) for n in range(6)] + [0, 1, 5/4, 49/36, 205/144, 5269/3600] + >>> harmonic(oo, 2) + pi**2/6 + + >>> from sympy import Symbol, Sum + >>> n = Symbol("n") + + >>> harmonic(n).rewrite(Sum) + Sum(1/_k, (_k, 1, n)) + + We can evaluate harmonic numbers for all integral and positive + rational arguments: + + >>> from sympy import S, expand_func, simplify + >>> harmonic(8) + 761/280 + >>> harmonic(11) + 83711/27720 + + >>> H = harmonic(1/S(3)) + >>> H + harmonic(1/3) + >>> He = expand_func(H) + >>> He + -log(6) - sqrt(3)*pi/6 + 2*Sum(log(sin(_k*pi/3))*cos(2*_k*pi/3), (_k, 1, 1)) + + 3*Sum(1/(3*_k + 1), (_k, 0, 0)) + >>> He.doit() + -log(6) - sqrt(3)*pi/6 - log(sqrt(3)/2) + 3 + >>> H = harmonic(25/S(7)) + >>> He = simplify(expand_func(H).doit()) + >>> He + log(sin(2*pi/7)**(2*cos(16*pi/7))/(14*sin(pi/7)**(2*cos(pi/7))*cos(pi/14)**(2*sin(pi/14)))) + pi*tan(pi/14)/2 + 30247/9900 + >>> He.n(40) + 1.983697455232980674869851942390639915940 + >>> harmonic(25/S(7)).n(40) + 1.983697455232980674869851942390639915940 + + We can rewrite harmonic numbers in terms of polygamma functions: + + >>> from sympy import digamma, polygamma + >>> m = Symbol("m", integer=True, positive=True) + + >>> harmonic(n).rewrite(digamma) + polygamma(0, n + 1) + EulerGamma + + >>> harmonic(n).rewrite(polygamma) + polygamma(0, n + 1) + EulerGamma + + >>> harmonic(n,3).rewrite(polygamma) + polygamma(2, n + 1)/2 + zeta(3) + + >>> simplify(harmonic(n,m).rewrite(polygamma)) + Piecewise((polygamma(0, n + 1) + EulerGamma, Eq(m, 1)), + (-(-1)**m*polygamma(m - 1, n + 1)/factorial(m - 1) + zeta(m), True)) + + Integer offsets in the argument can be pulled out: + + >>> from sympy import expand_func + + >>> expand_func(harmonic(n+4)) + harmonic(n) + 1/(n + 4) + 1/(n + 3) + 1/(n + 2) + 1/(n + 1) + + >>> expand_func(harmonic(n-4)) + harmonic(n) - 1/(n - 1) - 1/(n - 2) - 1/(n - 3) - 1/n + + Some limits can be computed as well: + + >>> from sympy import limit, oo + + >>> limit(harmonic(n), n, oo) + oo + + >>> limit(harmonic(n, 2), n, oo) + pi**2/6 + + >>> limit(harmonic(n, 3), n, oo) + zeta(3) + + For `m > 1`, `H_{n,m}` tends to `\zeta(m)` in the limit of infinite `n`: + + >>> m = Symbol("m", positive=True) + >>> limit(harmonic(n, m+1), n, oo) + zeta(m + 1) + + See Also + ======== + + bell, bernoulli, catalan, euler, fibonacci, lucas, genocchi, partition, tribonacci + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Harmonic_number + .. [2] https://functions.wolfram.com/GammaBetaErf/HarmonicNumber/ + .. [3] https://functions.wolfram.com/GammaBetaErf/HarmonicNumber2/ + + """ + + @classmethod + def eval(cls, n, m=None): + from sympy.functions.special.zeta_functions import zeta + if m is S.One: + return cls(n) + if m is None: + m = S.One + if n.is_zero: + return S.Zero + elif m.is_zero: + return n + elif n is S.Infinity: + if m.is_negative: + return S.NaN + elif is_le(m, S.One): + return S.Infinity + elif is_gt(m, S.One): + return zeta(m) + elif m.is_Integer and m.is_nonpositive: + return (bernoulli(1-m, n+1) - bernoulli(1-m)) / (1-m) + elif n.is_Integer: + if n.is_negative and (m.is_integer is False or m.is_nonpositive is False): + return S.ComplexInfinity if m is S.One else S.NaN + if n.is_nonnegative: + return Add(*(k**(-m) for k in range(1, int(n)+1))) + + def _eval_rewrite_as_polygamma(self, n, m=S.One, **kwargs): + from sympy.functions.special.gamma_functions import gamma, polygamma + if m.is_integer and m.is_positive: + return Piecewise((polygamma(0, n+1) + S.EulerGamma, Eq(m, 1)), + (S.NegativeOne**m * (polygamma(m-1, 1) - polygamma(m-1, n+1)) / + gamma(m), True)) + + def _eval_rewrite_as_digamma(self, n, m=1, **kwargs): + from sympy.functions.special.gamma_functions import polygamma + return self.rewrite(polygamma) + + def _eval_rewrite_as_trigamma(self, n, m=1, **kwargs): + from sympy.functions.special.gamma_functions import polygamma + return self.rewrite(polygamma) + + def _eval_rewrite_as_Sum(self, n, m=None, **kwargs): + from sympy.concrete.summations import Sum + k = Dummy("k", integer=True) + if m is None: + m = S.One + return Sum(k**(-m), (k, 1, n)) + + def _eval_rewrite_as_zeta(self, n, m=S.One, **kwargs): + from sympy.functions.special.zeta_functions import zeta + from sympy.functions.special.gamma_functions import digamma + return Piecewise((digamma(n + 1) + S.EulerGamma, Eq(m, 1)), + (zeta(m) - zeta(m, n+1), True)) + + def _eval_expand_func(self, **hints): + from sympy.concrete.summations import Sum + n = self.args[0] + m = self.args[1] if len(self.args) == 2 else 1 + + if m == S.One: + if n.is_Add: + off = n.args[0] + nnew = n - off + if off.is_Integer and off.is_positive: + result = [S.One/(nnew + i) for i in range(off, 0, -1)] + [harmonic(nnew)] + return Add(*result) + elif off.is_Integer and off.is_negative: + result = [-S.One/(nnew + i) for i in range(0, off, -1)] + [harmonic(nnew)] + return Add(*result) + + if n.is_Rational: + # Expansions for harmonic numbers at general rational arguments (u + p/q) + # Split n as u + p/q with p < q + p, q = n.as_numer_denom() + u = p // q + p = p - u * q + if u.is_nonnegative and p.is_positive and q.is_positive and p < q: + from sympy.functions.elementary.exponential import log + from sympy.functions.elementary.integers import floor + from sympy.functions.elementary.trigonometric import sin, cos, cot + k = Dummy("k") + t1 = q * Sum(1 / (q * k + p), (k, 0, u)) + t2 = 2 * Sum(cos((2 * pi * p * k) / S(q)) * + log(sin((pi * k) / S(q))), + (k, 1, floor((q - 1) / S(2)))) + t3 = (pi / 2) * cot((pi * p) / q) + log(2 * q) + return t1 + t2 - t3 + + return self + + def _eval_rewrite_as_tractable(self, n, m=1, limitvar=None, **kwargs): + from sympy.functions.special.zeta_functions import zeta + from sympy.functions.special.gamma_functions import polygamma + pg = self.rewrite(polygamma) + if not isinstance(pg, harmonic): + return pg.rewrite("tractable", deep=True) + arg = m - S.One + if arg.is_nonzero: + return (zeta(m) - zeta(m, n+1)).rewrite("tractable", deep=True) + + def _eval_evalf(self, prec): + if not all(x.is_number for x in self.args): + return + n = self.args[0]._to_mpmath(prec) + m = (self.args[1] if len(self.args) > 1 else S.One)._to_mpmath(prec) + if mp.isint(n) and n < 0: + return S.NaN + with workprec(prec): + if m == 1: + res = mp.harmonic(n) + else: + res = mp.zeta(m) - mp.zeta(m, n+1) + return Expr._from_mpmath(res, prec) + + def fdiff(self, argindex=1): + from sympy.functions.special.zeta_functions import zeta + if len(self.args) == 2: + n, m = self.args + else: + n, m = self.args + (1,) + if argindex == 1: + return m * zeta(m+1, n+1) + else: + raise ArgumentIndexError + + +#----------------------------------------------------------------------------# +# # +# Euler numbers # +# # +#----------------------------------------------------------------------------# + + +class euler(Function): + r""" + Euler numbers / Euler polynomials / Euler function + + The Euler numbers are given by: + + .. math:: E_{2n} = I \sum_{k=1}^{2n+1} \sum_{j=0}^k \binom{k}{j} + \frac{(-1)^j (k-2j)^{2n+1}}{2^k I^k k} + + .. math:: E_{2n+1} = 0 + + Euler numbers and Euler polynomials are related by + + .. math:: E_n = 2^n E_n\left(\frac{1}{2}\right). + + We compute symbolic Euler polynomials using Appell sequences, + but numerical evaluation of the Euler polynomial is computed + more efficiently (and more accurately) using the mpmath library. + + The Euler polynomials are special cases of the generalized Euler function, + related to the Genocchi function as + + .. math:: \operatorname{E}(s, a) = -\frac{\operatorname{G}(s+1, a)}{s+1} + + with the limit of `\psi\left(\frac{a+1}{2}\right) - \psi\left(\frac{a}{2}\right)` + being taken when `s = -1`. The (ordinary) Euler function interpolating + the Euler numbers is then obtained as + `\operatorname{E}(s) = 2^s \operatorname{E}\left(s, \frac{1}{2}\right)`. + + * ``euler(n)`` gives the nth Euler number `E_n`. + * ``euler(s)`` gives the Euler function `\operatorname{E}(s)`. + * ``euler(n, x)`` gives the nth Euler polynomial `E_n(x)`. + * ``euler(s, a)`` gives the generalized Euler function `\operatorname{E}(s, a)`. + + Examples + ======== + + >>> from sympy import euler, Symbol, S + >>> [euler(n) for n in range(10)] + [1, 0, -1, 0, 5, 0, -61, 0, 1385, 0] + >>> [2**n*euler(n,1) for n in range(10)] + [1, 1, 0, -2, 0, 16, 0, -272, 0, 7936] + >>> n = Symbol("n") + >>> euler(n + 2*n) + euler(3*n) + + >>> x = Symbol("x") + >>> euler(n, x) + euler(n, x) + + >>> euler(0, x) + 1 + >>> euler(1, x) + x - 1/2 + >>> euler(2, x) + x**2 - x + >>> euler(3, x) + x**3 - 3*x**2/2 + 1/4 + >>> euler(4, x) + x**4 - 2*x**3 + x + + >>> euler(12, S.Half) + 2702765/4096 + >>> euler(12) + 2702765 + + See Also + ======== + + andre, bell, bernoulli, catalan, fibonacci, harmonic, lucas, genocchi, + partition, tribonacci, sympy.polys.appellseqs.euler_poly + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Euler_numbers + .. [2] https://mathworld.wolfram.com/EulerNumber.html + .. [3] https://en.wikipedia.org/wiki/Alternating_permutation + .. [4] https://mathworld.wolfram.com/AlternatingPermutation.html + + """ + + @classmethod + def eval(cls, n, x=None): + if n.is_zero: + return S.One + elif n is S.NegativeOne: + if x is None: + return S.Pi/2 + from sympy.functions.special.gamma_functions import digamma + return digamma((x+1)/2) - digamma(x/2) + elif n.is_integer is False or n.is_nonnegative is False: + return + # Euler numbers + elif x is None: + if n.is_odd and n.is_positive: + return S.Zero + elif n.is_Number: + from mpmath import mp + n = n._to_mpmath(mp.prec) + res = mp.eulernum(n, exact=True) + return Integer(res) + # Euler polynomials + elif n.is_Number: + return euler_poly(n, x) + + def _eval_rewrite_as_Sum(self, n, x=None, **kwargs): + from sympy.concrete.summations import Sum + if x is None and n.is_even: + k = Dummy("k", integer=True) + j = Dummy("j", integer=True) + n = n / 2 + Em = (S.ImaginaryUnit * Sum(Sum(binomial(k, j) * (S.NegativeOne**j * + (k - 2*j)**(2*n + 1)) / + (2**k*S.ImaginaryUnit**k * k), (j, 0, k)), (k, 1, 2*n + 1))) + return Em + if x: + k = Dummy("k", integer=True) + return Sum(binomial(n, k)*euler(k)/2**k*(x - S.Half)**(n - k), (k, 0, n)) + + def _eval_rewrite_as_genocchi(self, n, x=None, **kwargs): + if x is None: + return Piecewise((S.Pi/2, Eq(n, -1)), + (-2**n * genocchi(n+1, S.Half) / (n+1), True)) + from sympy.functions.special.gamma_functions import digamma + return Piecewise((digamma((x+1)/2) - digamma(x/2), Eq(n, -1)), + (-genocchi(n+1, x) / (n+1), True)) + + def _eval_evalf(self, prec): + if not all(i.is_number for i in self.args): + return + from mpmath import mp + m, x = (self.args[0], None) if len(self.args) == 1 else self.args + m = m._to_mpmath(prec) + if x is not None: + x = x._to_mpmath(prec) + with workprec(prec): + if mp.isint(m) and m >= 0: + res = mp.eulernum(m) if x is None else mp.eulerpoly(m, x) + else: + if m == -1: + res = mp.pi if x is None else mp.digamma((x+1)/2) - mp.digamma(x/2) + else: + y = 0.5 if x is None else x + res = 2 * (mp.zeta(-m, y) - 2**(m+1) * mp.zeta(-m, (y+1)/2)) + if x is None: + res *= 2**m + return Expr._from_mpmath(res, prec) + + +#----------------------------------------------------------------------------# +# # +# Catalan numbers # +# # +#----------------------------------------------------------------------------# + + +class catalan(Function): + r""" + Catalan numbers + + The `n^{th}` catalan number is given by: + + .. math :: C_n = \frac{1}{n+1} \binom{2n}{n} + + * ``catalan(n)`` gives the `n^{th}` Catalan number, `C_n` + + Examples + ======== + + >>> from sympy import (Symbol, binomial, gamma, hyper, + ... catalan, diff, combsimp, Rational, I) + + >>> [catalan(i) for i in range(1,10)] + [1, 2, 5, 14, 42, 132, 429, 1430, 4862] + + >>> n = Symbol("n", integer=True) + + >>> catalan(n) + catalan(n) + + Catalan numbers can be transformed into several other, identical + expressions involving other mathematical functions + + >>> catalan(n).rewrite(binomial) + binomial(2*n, n)/(n + 1) + + >>> catalan(n).rewrite(gamma) + 4**n*gamma(n + 1/2)/(sqrt(pi)*gamma(n + 2)) + + >>> catalan(n).rewrite(hyper) + hyper((-n, 1 - n), (2,), 1) + + For some non-integer values of n we can get closed form + expressions by rewriting in terms of gamma functions: + + >>> catalan(Rational(1, 2)).rewrite(gamma) + 8/(3*pi) + + We can differentiate the Catalan numbers C(n) interpreted as a + continuous real function in n: + + >>> diff(catalan(n), n) + (polygamma(0, n + 1/2) - polygamma(0, n + 2) + log(4))*catalan(n) + + As a more advanced example consider the following ratio + between consecutive numbers: + + >>> combsimp((catalan(n + 1)/catalan(n)).rewrite(binomial)) + 2*(2*n + 1)/(n + 2) + + The Catalan numbers can be generalized to complex numbers: + + >>> catalan(I).rewrite(gamma) + 4**I*gamma(1/2 + I)/(sqrt(pi)*gamma(2 + I)) + + and evaluated with arbitrary precision: + + >>> catalan(I).evalf(20) + 0.39764993382373624267 - 0.020884341620842555705*I + + See Also + ======== + + andre, bell, bernoulli, euler, fibonacci, harmonic, lucas, genocchi, + partition, tribonacci, sympy.functions.combinatorial.factorials.binomial + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Catalan_number + .. [2] https://mathworld.wolfram.com/CatalanNumber.html + .. [3] https://functions.wolfram.com/GammaBetaErf/CatalanNumber/ + .. [4] http://geometer.org/mathcircles/catalan.pdf + + """ + + @classmethod + def eval(cls, n): + from sympy.functions.special.gamma_functions import gamma + if (n.is_Integer and n.is_nonnegative) or \ + (n.is_noninteger and n.is_negative): + return 4**n*gamma(n + S.Half)/(gamma(S.Half)*gamma(n + 2)) + + if (n.is_integer and n.is_negative): + if (n + 1).is_negative: + return S.Zero + if (n + 1).is_zero: + return Rational(-1, 2) + + def fdiff(self, argindex=1): + from sympy.functions.elementary.exponential import log + from sympy.functions.special.gamma_functions import polygamma + n = self.args[0] + return catalan(n)*(polygamma(0, n + S.Half) - polygamma(0, n + 2) + log(4)) + + def _eval_rewrite_as_binomial(self, n, **kwargs): + return binomial(2*n, n)/(n + 1) + + def _eval_rewrite_as_factorial(self, n, **kwargs): + return factorial(2*n) / (factorial(n+1) * factorial(n)) + + def _eval_rewrite_as_gamma(self, n, piecewise=True, **kwargs): + from sympy.functions.special.gamma_functions import gamma + # The gamma function allows to generalize Catalan numbers to complex n + return 4**n*gamma(n + S.Half)/(gamma(S.Half)*gamma(n + 2)) + + def _eval_rewrite_as_hyper(self, n, **kwargs): + from sympy.functions.special.hyper import hyper + return hyper([1 - n, -n], [2], 1) + + def _eval_rewrite_as_Product(self, n, **kwargs): + from sympy.concrete.products import Product + if not (n.is_integer and n.is_nonnegative): + return self + k = Dummy('k', integer=True, positive=True) + return Product((n + k) / k, (k, 2, n)) + + def _eval_is_integer(self): + if self.args[0].is_integer and self.args[0].is_nonnegative: + return True + + def _eval_is_positive(self): + if self.args[0].is_nonnegative: + return True + + def _eval_is_composite(self): + if self.args[0].is_integer and (self.args[0] - 3).is_positive: + return True + + def _eval_evalf(self, prec): + from sympy.functions.special.gamma_functions import gamma + if self.args[0].is_number: + return self.rewrite(gamma)._eval_evalf(prec) + + +#----------------------------------------------------------------------------# +# # +# Genocchi numbers # +# # +#----------------------------------------------------------------------------# + + +class genocchi(Function): + r""" + Genocchi numbers / Genocchi polynomials / Genocchi function + + The Genocchi numbers are a sequence of integers `G_n` that satisfy the + relation: + + .. math:: \frac{-2t}{1 + e^{-t}} = \sum_{n=0}^\infty \frac{G_n t^n}{n!} + + They are related to the Bernoulli numbers by + + .. math:: G_n = 2 (1 - 2^n) B_n + + and generalize like the Bernoulli numbers to the Genocchi polynomials and + function as + + .. math:: \operatorname{G}(s, a) = 2 \left(\operatorname{B}(s, a) - + 2^s \operatorname{B}\left(s, \frac{a+1}{2}\right)\right) + + .. versionchanged:: 1.12 + ``genocchi(1)`` gives `-1` instead of `1`. + + Examples + ======== + + >>> from sympy import genocchi, Symbol + >>> [genocchi(n) for n in range(9)] + [0, -1, -1, 0, 1, 0, -3, 0, 17] + >>> n = Symbol('n', integer=True, positive=True) + >>> genocchi(2*n + 1) + 0 + >>> x = Symbol('x') + >>> genocchi(4, x) + -4*x**3 + 6*x**2 - 1 + + See Also + ======== + + bell, bernoulli, catalan, euler, fibonacci, harmonic, lucas, partition, tribonacci + sympy.polys.appellseqs.genocchi_poly + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Genocchi_number + .. [2] https://mathworld.wolfram.com/GenocchiNumber.html + .. [3] Peter Luschny, "An introduction to the Bernoulli function", + https://arxiv.org/abs/2009.06743 + + """ + + @classmethod + def eval(cls, n, x=None): + if x is S.One: + return cls(n) + elif n.is_integer is False or n.is_nonnegative is False: + return + # Genocchi numbers + elif x is None: + if n.is_odd and (n-1).is_positive: + return S.Zero + elif n.is_Number: + return 2 * (1-S(2)**n) * bernoulli(n) + # Genocchi polynomials + elif n.is_Number: + return genocchi_poly(n, x) + + def _eval_rewrite_as_bernoulli(self, n, x=1, **kwargs): + if x == 1 and n.is_integer and n.is_nonnegative: + return 2 * (1-S(2)**n) * bernoulli(n) + return 2 * (bernoulli(n, x) - 2**n * bernoulli(n, (x+1) / 2)) + + def _eval_rewrite_as_dirichlet_eta(self, n, x=1, **kwargs): + from sympy.functions.special.zeta_functions import dirichlet_eta + return -2*n * dirichlet_eta(1-n, x) + + def _eval_is_integer(self): + if len(self.args) > 1 and self.args[1] != 1: + return + n = self.args[0] + if n.is_integer and n.is_nonnegative: + return True + + def _eval_is_negative(self): + if len(self.args) > 1 and self.args[1] != 1: + return + n = self.args[0] + if n.is_integer and n.is_nonnegative: + if n.is_odd: + return fuzzy_not((n-1).is_positive) + return (n/2).is_odd + + def _eval_is_positive(self): + if len(self.args) > 1 and self.args[1] != 1: + return + n = self.args[0] + if n.is_integer and n.is_nonnegative: + if n.is_zero or n.is_odd: + return False + return (n/2).is_even + + def _eval_is_even(self): + if len(self.args) > 1 and self.args[1] != 1: + return + n = self.args[0] + if n.is_integer and n.is_nonnegative: + if n.is_even: + return n.is_zero + return (n-1).is_positive + + def _eval_is_odd(self): + if len(self.args) > 1 and self.args[1] != 1: + return + n = self.args[0] + if n.is_integer and n.is_nonnegative: + if n.is_even: + return fuzzy_not(n.is_zero) + return fuzzy_not((n-1).is_positive) + + def _eval_is_prime(self): + if len(self.args) > 1 and self.args[1] != 1: + return + n = self.args[0] + # only G_6 = -3 and G_8 = 17 are prime, + # but SymPy does not consider negatives as prime + # so only n=8 is tested + return (n-8).is_zero + + def _eval_evalf(self, prec): + if all(i.is_number for i in self.args): + return self.rewrite(bernoulli)._eval_evalf(prec) + + +#----------------------------------------------------------------------------# +# # +# Andre numbers # +# # +#----------------------------------------------------------------------------# + + +class andre(Function): + r""" + Andre numbers / Andre function + + The Andre number `\mathcal{A}_n` is Luschny's name for half the number of + *alternating permutations* on `n` elements, where a permutation is alternating + if adjacent elements alternately compare "greater" and "smaller" going from + left to right. For example, `2 < 3 > 1 < 4` is an alternating permutation. + + This sequence is A000111 in the OEIS, which assigns the names *up/down numbers* + and *Euler zigzag numbers*. It satisfies a recurrence relation similar to that + for the Catalan numbers, with `\mathcal{A}_0 = 1` and + + .. math:: 2 \mathcal{A}_{n+1} = \sum_{k=0}^n \binom{n}{k} \mathcal{A}_k \mathcal{A}_{n-k} + + The Bernoulli and Euler numbers are signed transformations of the odd- and + even-indexed elements of this sequence respectively: + + .. math :: \operatorname{B}_{2k} = \frac{2k \mathcal{A}_{2k-1}}{(-4)^k - (-16)^k} + + .. math :: \operatorname{E}_{2k} = (-1)^k \mathcal{A}_{2k} + + Like the Bernoulli and Euler numbers, the Andre numbers are interpolated by the + entire Andre function: + + .. math :: \mathcal{A}(s) = (-i)^{s+1} \operatorname{Li}_{-s}(i) + + i^{s+1} \operatorname{Li}_{-s}(-i) = \\ \frac{2 \Gamma(s+1)}{(2\pi)^{s+1}} + (\zeta(s+1, 1/4) - \zeta(s+1, 3/4) \cos{\pi s}) + + Examples + ======== + + >>> from sympy import andre, euler, bernoulli + >>> [andre(n) for n in range(11)] + [1, 1, 1, 2, 5, 16, 61, 272, 1385, 7936, 50521] + >>> [(-1)**k * andre(2*k) for k in range(7)] + [1, -1, 5, -61, 1385, -50521, 2702765] + >>> [euler(2*k) for k in range(7)] + [1, -1, 5, -61, 1385, -50521, 2702765] + >>> [andre(2*k-1) * (2*k) / ((-4)**k - (-16)**k) for k in range(1, 8)] + [1/6, -1/30, 1/42, -1/30, 5/66, -691/2730, 7/6] + >>> [bernoulli(2*k) for k in range(1, 8)] + [1/6, -1/30, 1/42, -1/30, 5/66, -691/2730, 7/6] + + See Also + ======== + + bernoulli, catalan, euler, sympy.polys.appellseqs.andre_poly + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Alternating_permutation + .. [2] https://mathworld.wolfram.com/EulerZigzagNumber.html + .. [3] Peter Luschny, "An introduction to the Bernoulli function", + https://arxiv.org/abs/2009.06743 + """ + + @classmethod + def eval(cls, n): + if n is S.NaN: + return S.NaN + elif n is S.Infinity: + return S.Infinity + if n.is_zero: + return S.One + elif n == -1: + return -log(2) + elif n == -2: + return -2*S.Catalan + elif n.is_Integer: + if n.is_nonnegative and n.is_even: + return abs(euler(n)) + elif n.is_odd: + from sympy.functions.special.zeta_functions import zeta + m = -n-1 + return I**m * Rational(1-2**m, 4**m) * zeta(-n) + + def _eval_rewrite_as_zeta(self, s, **kwargs): + from sympy.functions.elementary.trigonometric import cos + from sympy.functions.special.gamma_functions import gamma + from sympy.functions.special.zeta_functions import zeta + return 2 * gamma(s+1) / (2*pi)**(s+1) * \ + (zeta(s+1, S.One/4) - cos(pi*s) * zeta(s+1, S(3)/4)) + + def _eval_rewrite_as_polylog(self, s, **kwargs): + from sympy.functions.special.zeta_functions import polylog + return (-I)**(s+1) * polylog(-s, I) + I**(s+1) * polylog(-s, -I) + + def _eval_is_integer(self): + n = self.args[0] + if n.is_integer and n.is_nonnegative: + return True + + def _eval_is_positive(self): + if self.args[0].is_nonnegative: + return True + + def _eval_evalf(self, prec): + if not self.args[0].is_number: + return + s = self.args[0]._to_mpmath(prec+12) + with workprec(prec+12): + sp, cp = mp.sinpi(s/2), mp.cospi(s/2) + res = 2*mp.dirichlet(-s, (-sp, cp, sp, -cp)) + return Expr._from_mpmath(res, prec) + + +#----------------------------------------------------------------------------# +# # +# Partition numbers # +# # +#----------------------------------------------------------------------------# + + +class partition(Function): + r""" + Partition numbers + + The Partition numbers are a sequence of integers `p_n` that represent the + number of distinct ways of representing `n` as a sum of natural numbers + (with order irrelevant). The generating function for `p_n` is given by: + + .. math:: \sum_{n=0}^\infty p_n x^n = \prod_{k=1}^\infty (1 - x^k)^{-1} + + Examples + ======== + + >>> from sympy import partition, Symbol + >>> [partition(n) for n in range(9)] + [1, 1, 2, 3, 5, 7, 11, 15, 22] + >>> n = Symbol('n', integer=True, negative=True) + >>> partition(n) + 0 + + See Also + ======== + + bell, bernoulli, catalan, euler, fibonacci, harmonic, lucas, genocchi, tribonacci + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Partition_(number_theory%29 + .. [2] https://en.wikipedia.org/wiki/Pentagonal_number_theorem + + """ + is_integer = True + is_nonnegative = True + + @classmethod + def eval(cls, n): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_negative is True: + return S.Zero + if n.is_zero is True or n is S.One: + return S.One + if n.is_Integer is True: + return S(_partition(as_int(n))) + + def _eval_is_positive(self): + if self.args[0].is_nonnegative is True: + return True + + +class divisor_sigma(Function): + r""" + Calculate the divisor function `\sigma_k(n)` for positive integer n + + ``divisor_sigma(n, k)`` is equal to ``sum([x**k for x in divisors(n)])`` + + If n's prime factorization is: + + .. math :: + n = \prod_{i=1}^\omega p_i^{m_i}, + + then + + .. math :: + \sigma_k(n) = \prod_{i=1}^\omega (1+p_i^k+p_i^{2k}+\cdots + + p_i^{m_ik}). + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import divisor_sigma + >>> divisor_sigma(18, 0) + 6 + >>> divisor_sigma(39, 1) + 56 + >>> divisor_sigma(12, 2) + 210 + >>> divisor_sigma(37) + 38 + + See Also + ======== + + sympy.ntheory.factor_.divisor_count, totient, sympy.ntheory.factor_.divisors, sympy.ntheory.factor_.factorint + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Divisor_function + + """ + is_integer = True + is_positive = True + + @classmethod + def eval(cls, n, k=S.One): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False: + raise ValueError("n should be a positive integer") + if k.is_integer is False: + raise TypeError("k should be an integer") + if k.is_nonnegative is False: + raise ValueError("k should be a nonnegative integer") + if n.is_prime is True: + return 1 + n**k + if n is S.One: + return S.One + if n.is_Integer is True: + if k.is_zero is True: + return Mul(*[e + 1 for e in factorint(n).values()]) + if k.is_Integer is True: + return S(_divisor_sigma(as_int(n), as_int(k))) + if k.is_zero is False: + return Mul(*[cancel((p**(k*(e + 1)) - 1) / (p**k - 1)) for p, e in factorint(n).items()]) + + +class udivisor_sigma(Function): + r""" + Calculate the unitary divisor function `\sigma_k^*(n)` for positive integer n + + ``udivisor_sigma(n, k)`` is equal to ``sum([x**k for x in udivisors(n)])`` + + If n's prime factorization is: + + .. math :: + n = \prod_{i=1}^\omega p_i^{m_i}, + + then + + .. math :: + \sigma_k^*(n) = \prod_{i=1}^\omega (1+ p_i^{m_ik}). + + Parameters + ========== + + k : power of divisors in the sum + + for k = 0, 1: + ``udivisor_sigma(n, 0)`` is equal to ``udivisor_count(n)`` + ``udivisor_sigma(n, 1)`` is equal to ``sum(udivisors(n))`` + + Default for k is 1. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import udivisor_sigma + >>> udivisor_sigma(18, 0) + 4 + >>> udivisor_sigma(74, 1) + 114 + >>> udivisor_sigma(36, 3) + 47450 + >>> udivisor_sigma(111) + 152 + + See Also + ======== + + sympy.ntheory.factor_.divisor_count, totient, sympy.ntheory.factor_.divisors, + sympy.ntheory.factor_.udivisors, sympy.ntheory.factor_.udivisor_count, divisor_sigma, + sympy.ntheory.factor_.factorint + + References + ========== + + .. [1] https://mathworld.wolfram.com/UnitaryDivisorFunction.html + + """ + is_integer = True + is_positive = True + + @classmethod + def eval(cls, n, k=S.One): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False: + raise ValueError("n should be a positive integer") + if k.is_integer is False: + raise TypeError("k should be an integer") + if k.is_nonnegative is False: + raise ValueError("k should be a nonnegative integer") + if n.is_prime is True: + return 1 + n**k + if n.is_Integer: + return Mul(*[1+p**(k*e) for p, e in factorint(n).items()]) + + +class legendre_symbol(Function): + r""" + Returns the Legendre symbol `(a / p)`. + + For an integer ``a`` and an odd prime ``p``, the Legendre symbol is + defined as + + .. math :: + \genfrac(){}{}{a}{p} = \begin{cases} + 0 & \text{if } p \text{ divides } a\\ + 1 & \text{if } a \text{ is a quadratic residue modulo } p\\ + -1 & \text{if } a \text{ is a quadratic nonresidue modulo } p + \end{cases} + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import legendre_symbol + >>> [legendre_symbol(i, 7) for i in range(7)] + [0, 1, 1, -1, 1, -1, -1] + >>> sorted(set([i**2 % 7 for i in range(7)])) + [0, 1, 2, 4] + + See Also + ======== + + sympy.ntheory.residue_ntheory.is_quad_residue, jacobi_symbol + + """ + is_integer = True + is_prime = False + + @classmethod + def eval(cls, a, p): + if a.is_integer is False: + raise TypeError("a should be an integer") + if p.is_integer is False: + raise TypeError("p should be an integer") + if p.is_prime is False or p.is_odd is False: + raise ValueError("p should be an odd prime integer") + if (a % p).is_zero is True: + return S.Zero + if a is S.One: + return S.One + if a.is_Integer is True and p.is_Integer is True: + return S(legendre(as_int(a), as_int(p))) + + +class jacobi_symbol(Function): + r""" + Returns the Jacobi symbol `(m / n)`. + + For any integer ``m`` and any positive odd integer ``n`` the Jacobi symbol + is defined as the product of the Legendre symbols corresponding to the + prime factors of ``n``: + + .. math :: + \genfrac(){}{}{m}{n} = + \genfrac(){}{}{m}{p^{1}}^{\alpha_1} + \genfrac(){}{}{m}{p^{2}}^{\alpha_2} + ... + \genfrac(){}{}{m}{p^{k}}^{\alpha_k} + \text{ where } n = + p_1^{\alpha_1} + p_2^{\alpha_2} + ... + p_k^{\alpha_k} + + Like the Legendre symbol, if the Jacobi symbol `\genfrac(){}{}{m}{n} = -1` + then ``m`` is a quadratic nonresidue modulo ``n``. + + But, unlike the Legendre symbol, if the Jacobi symbol + `\genfrac(){}{}{m}{n} = 1` then ``m`` may or may not be a quadratic residue + modulo ``n``. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import jacobi_symbol, legendre_symbol + >>> from sympy import S + >>> jacobi_symbol(45, 77) + -1 + >>> jacobi_symbol(60, 121) + 1 + + The relationship between the ``jacobi_symbol`` and ``legendre_symbol`` can + be demonstrated as follows: + + >>> L = legendre_symbol + >>> S(45).factors() + {3: 2, 5: 1} + >>> jacobi_symbol(7, 45) == L(7, 3)**2 * L(7, 5)**1 + True + + See Also + ======== + + sympy.ntheory.residue_ntheory.is_quad_residue, legendre_symbol + + """ + is_integer = True + is_prime = False + + @classmethod + def eval(cls, m, n): + if m.is_integer is False: + raise TypeError("m should be an integer") + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False or n.is_odd is False: + raise ValueError("n should be an odd positive integer") + if m is S.One or n is S.One: + return S.One + if (m % n).is_zero is True: + return S.Zero + if m.is_Integer is True and n.is_Integer is True: + return S(jacobi(as_int(m), as_int(n))) + + +class kronecker_symbol(Function): + r""" + Returns the Kronecker symbol `(a / n)`. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import kronecker_symbol + >>> kronecker_symbol(45, 77) + -1 + >>> kronecker_symbol(13, -120) + 1 + + See Also + ======== + + jacobi_symbol, legendre_symbol + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Kronecker_symbol + + """ + is_integer = True + is_prime = False + + @classmethod + def eval(cls, a, n): + if a.is_integer is False: + raise TypeError("a should be an integer") + if n.is_integer is False: + raise TypeError("n should be an integer") + if a is S.One or n is S.One: + return S.One + if a.is_Integer is True and n.is_Integer is True: + return S(kronecker(as_int(a), as_int(n))) + + +class mobius(Function): + """ + Mobius function maps natural number to {-1, 0, 1} + + It is defined as follows: + 1) `1` if `n = 1`. + 2) `0` if `n` has a squared prime factor. + 3) `(-1)^k` if `n` is a square-free positive integer with `k` + number of prime factors. + + It is an important multiplicative function in number theory + and combinatorics. It has applications in mathematical series, + algebraic number theory and also physics (Fermion operator has very + concrete realization with Mobius Function model). + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import mobius + >>> mobius(13*7) + 1 + >>> mobius(1) + 1 + >>> mobius(13*7*5) + -1 + >>> mobius(13**2) + 0 + + Even in the case of a symbol, if it clearly contains a squared prime factor, it will be zero. + + >>> from sympy import Symbol + >>> n = Symbol("n", integer=True, positive=True) + >>> mobius(4*n) + 0 + >>> mobius(n**2) + 0 + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/M%C3%B6bius_function + .. [2] Thomas Koshy "Elementary Number Theory with Applications" + .. [3] https://oeis.org/A008683 + + """ + is_integer = True + is_prime = False + + @classmethod + def eval(cls, n): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False: + raise ValueError("n should be a positive integer") + if n.is_prime is True: + return S.NegativeOne + if n is S.One: + return S.One + result = None + for m, e in (_.as_base_exp() for _ in Mul.make_args(n)): + if m.is_integer is True and m.is_positive is True and \ + e.is_integer is True and e.is_positive is True: + lt = is_lt(S.One, e) # 1 < e + if lt is True: + result = S.Zero + elif m.is_Integer is True: + factors = factorint(m) + if any(v > 1 for v in factors.values()): + result = S.Zero + elif lt is False: + s = S.NegativeOne if len(factors) % 2 else S.One + if result is None: + result = s + else: + result *= s + else: + return + return result + + +class primenu(Function): + r""" + Calculate the number of distinct prime factors for a positive integer n. + + If n's prime factorization is: + + .. math :: + n = \prod_{i=1}^k p_i^{m_i}, + + then ``primenu(n)`` or `\nu(n)` is: + + .. math :: + \nu(n) = k. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import primenu + >>> primenu(1) + 0 + >>> primenu(30) + 3 + + See Also + ======== + + sympy.ntheory.factor_.factorint + + References + ========== + + .. [1] https://mathworld.wolfram.com/PrimeFactor.html + .. [2] https://oeis.org/A001221 + + """ + is_integer = True + is_nonnegative = True + + @classmethod + def eval(cls, n): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False: + raise ValueError("n should be a positive integer") + if n.is_prime is True: + return S.One + if n is S.One: + return S.Zero + if n.is_Integer is True: + return S(len(factorint(n))) + + +class primeomega(Function): + r""" + Calculate the number of prime factors counting multiplicities for a + positive integer n. + + If n's prime factorization is: + + .. math :: + n = \prod_{i=1}^k p_i^{m_i}, + + then ``primeomega(n)`` or `\Omega(n)` is: + + .. math :: + \Omega(n) = \sum_{i=1}^k m_i. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import primeomega + >>> primeomega(1) + 0 + >>> primeomega(20) + 3 + + See Also + ======== + + sympy.ntheory.factor_.factorint + + References + ========== + + .. [1] https://mathworld.wolfram.com/PrimeFactor.html + .. [2] https://oeis.org/A001222 + + """ + is_integer = True + is_nonnegative = True + + @classmethod + def eval(cls, n): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False: + raise ValueError("n should be a positive integer") + if n.is_prime is True: + return S.One + if n is S.One: + return S.Zero + if n.is_Integer is True: + return S(sum(factorint(n).values())) + + +class totient(Function): + r""" + Calculate the Euler totient function phi(n) + + ``totient(n)`` or `\phi(n)` is the number of positive integers `\leq` n + that are relatively prime to n. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import totient + >>> totient(1) + 1 + >>> totient(25) + 20 + >>> totient(45) == totient(5)*totient(9) + True + + See Also + ======== + + sympy.ntheory.factor_.divisor_count + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Euler%27s_totient_function + .. [2] https://mathworld.wolfram.com/TotientFunction.html + .. [3] https://oeis.org/A000010 + + """ + is_integer = True + is_positive = True + + @classmethod + def eval(cls, n): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False: + raise ValueError("n should be a positive integer") + if n is S.One: + return S.One + if n.is_prime is True: + return n - 1 + if isinstance(n, Dict): + return S(prod(p**(k-1)*(p-1) for p, k in n.items())) + if n.is_Integer is True: + return S(prod(p**(k-1)*(p-1) for p, k in factorint(n).items())) + + +class reduced_totient(Function): + r""" + Calculate the Carmichael reduced totient function lambda(n) + + ``reduced_totient(n)`` or `\lambda(n)` is the smallest m > 0 such that + `k^m \equiv 1 \mod n` for all k relatively prime to n. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import reduced_totient + >>> reduced_totient(1) + 1 + >>> reduced_totient(8) + 2 + >>> reduced_totient(30) + 4 + + See Also + ======== + + totient + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Carmichael_function + .. [2] https://mathworld.wolfram.com/CarmichaelFunction.html + .. [3] https://oeis.org/A002322 + + """ + is_integer = True + is_positive = True + + @classmethod + def eval(cls, n): + if n.is_integer is False: + raise TypeError("n should be an integer") + if n.is_positive is False: + raise ValueError("n should be a positive integer") + if n is S.One: + return S.One + if n.is_prime is True: + return n - 1 + if isinstance(n, Dict): + t = 1 + if 2 in n: + t = (1 << (n[2] - 2)) if 2 < n[2] else n[2] + return S(lcm(int(t), *(int(p-1)*int(p)**int(k-1) for p, k in n.items() if p != 2))) + if n.is_Integer is True: + n, t = remove(int(n), 2) + if not t: + t = 1 + elif 2 < t: + t = 1 << (t - 2) + return S(lcm(t, *((p-1)*p**(k-1) for p, k in factorint(n).items()))) + + +class primepi(Function): + r""" Represents the prime counting function pi(n) = the number + of prime numbers less than or equal to n. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import primepi + >>> from sympy import prime, prevprime, isprime + >>> primepi(25) + 9 + + So there are 9 primes less than or equal to 25. Is 25 prime? + + >>> isprime(25) + False + + It is not. So the first prime less than 25 must be the + 9th prime: + + >>> prevprime(25) == prime(9) + True + + See Also + ======== + + sympy.ntheory.primetest.isprime : Test if n is prime + sympy.ntheory.generate.primerange : Generate all primes in a given range + sympy.ntheory.generate.prime : Return the nth prime + + References + ========== + + .. [1] https://oeis.org/A000720 + + """ + is_integer = True + is_nonnegative = True + + @classmethod + def eval(cls, n): + if n is S.Infinity: + return S.Infinity + if n is S.NegativeInfinity: + return S.Zero + if n.is_real is False: + raise TypeError("n should be a real") + if is_lt(n, S(2)) is True: + return S.Zero + try: + n = int(n) + except TypeError: + return + return S(_primepi(n)) + + +####################################################################### +### +### Functions for enumerating partitions, permutations and combinations +### +####################################################################### + + +class _MultisetHistogram(tuple): + pass + + +_N = -1 +_ITEMS = -2 +_M = slice(None, _ITEMS) + + +def _multiset_histogram(n): + """Return tuple used in permutation and combination counting. Input + is a dictionary giving items with counts as values or a sequence of + items (which need not be sorted). + + The data is stored in a class deriving from tuple so it is easily + recognized and so it can be converted easily to a list. + """ + if isinstance(n, dict): # item: count + if not all(isinstance(v, int) and v >= 0 for v in n.values()): + raise ValueError + tot = sum(n.values()) + items = sum(1 for k in n if n[k] > 0) + return _MultisetHistogram([n[k] for k in n if n[k] > 0] + [items, tot]) + else: + n = list(n) + s = set(n) + lens = len(s) + lenn = len(n) + if lens == lenn: + n = [1]*lenn + [lenn, lenn] + return _MultisetHistogram(n) + m = dict(zip(s, range(lens))) + d = dict(zip(range(lens), (0,)*lens)) + for i in n: + d[m[i]] += 1 + return _multiset_histogram(d) + + +def nP(n, k=None, replacement=False): + """Return the number of permutations of ``n`` items taken ``k`` at a time. + + Possible values for ``n``: + + integer - set of length ``n`` + + sequence - converted to a multiset internally + + multiset - {element: multiplicity} + + If ``k`` is None then the total of all permutations of length 0 + through the number of items represented by ``n`` will be returned. + + If ``replacement`` is True then a given item can appear more than once + in the ``k`` items. (For example, for 'ab' permutations of 2 would + include 'aa', 'ab', 'ba' and 'bb'.) The multiplicity of elements in + ``n`` is ignored when ``replacement`` is True but the total number + of elements is considered since no element can appear more times than + the number of elements in ``n``. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import nP + >>> from sympy.utilities.iterables import multiset_permutations, multiset + >>> nP(3, 2) + 6 + >>> nP('abc', 2) == nP(multiset('abc'), 2) == 6 + True + >>> nP('aab', 2) + 3 + >>> nP([1, 2, 2], 2) + 3 + >>> [nP(3, i) for i in range(4)] + [1, 3, 6, 6] + >>> nP(3) == sum(_) + True + + When ``replacement`` is True, each item can have multiplicity + equal to the length represented by ``n``: + + >>> nP('aabc', replacement=True) + 121 + >>> [len(list(multiset_permutations('aaaabbbbcccc', i))) for i in range(5)] + [1, 3, 9, 27, 81] + >>> sum(_) + 121 + + See Also + ======== + sympy.utilities.iterables.multiset_permutations + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Permutation + + """ + try: + n = as_int(n) + except ValueError: + return Integer(_nP(_multiset_histogram(n), k, replacement)) + return Integer(_nP(n, k, replacement)) + + +@cacheit +def _nP(n, k=None, replacement=False): + + if k == 0: + return 1 + if isinstance(n, SYMPY_INTS): # n different items + # assert n >= 0 + if k is None: + return sum(_nP(n, i, replacement) for i in range(n + 1)) + elif replacement: + return n**k + elif k > n: + return 0 + elif k == n: + return factorial(k) + elif k == 1: + return n + else: + # assert k >= 0 + return _product(n - k + 1, n) + elif isinstance(n, _MultisetHistogram): + if k is None: + return sum(_nP(n, i, replacement) for i in range(n[_N] + 1)) + elif replacement: + return n[_ITEMS]**k + elif k == n[_N]: + return factorial(k)/prod([factorial(i) for i in n[_M] if i > 1]) + elif k > n[_N]: + return 0 + elif k == 1: + return n[_ITEMS] + else: + # assert k >= 0 + tot = 0 + n = list(n) + for i in range(len(n[_M])): + if not n[i]: + continue + n[_N] -= 1 + if n[i] == 1: + n[i] = 0 + n[_ITEMS] -= 1 + tot += _nP(_MultisetHistogram(n), k - 1) + n[_ITEMS] += 1 + n[i] = 1 + else: + n[i] -= 1 + tot += _nP(_MultisetHistogram(n), k - 1) + n[i] += 1 + n[_N] += 1 + return tot + + +@cacheit +def _AOP_product(n): + """for n = (m1, m2, .., mk) return the coefficients of the polynomial, + prod(sum(x**i for i in range(nj + 1)) for nj in n); i.e. the coefficients + of the product of AOPs (all-one polynomials) or order given in n. The + resulting coefficient corresponding to x**r is the number of r-length + combinations of sum(n) elements with multiplicities given in n. + The coefficients are given as a default dictionary (so if a query is made + for a key that is not present, 0 will be returned). + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import _AOP_product + >>> from sympy.abc import x + >>> n = (2, 2, 3) # e.g. aabbccc + >>> prod = ((x**2 + x + 1)*(x**2 + x + 1)*(x**3 + x**2 + x + 1)).expand() + >>> c = _AOP_product(n); dict(c) + {0: 1, 1: 3, 2: 6, 3: 8, 4: 8, 5: 6, 6: 3, 7: 1} + >>> [c[i] for i in range(8)] == [prod.coeff(x, i) for i in range(8)] + True + + The generating poly used here is the same as that listed in + https://tinyurl.com/cep849r, but in a refactored form. + + """ + + n = list(n) + ord = sum(n) + need = (ord + 2)//2 + rv = [1]*(n.pop() + 1) + rv.extend((0,) * (need - len(rv))) + rv = rv[:need] + while n: + ni = n.pop() + N = ni + 1 + was = rv[:] + for i in range(1, min(N, len(rv))): + rv[i] += rv[i - 1] + for i in range(N, need): + rv[i] += rv[i - 1] - was[i - N] + rev = list(reversed(rv)) + if ord % 2: + rv = rv + rev + else: + rv[-1:] = rev + d = defaultdict(int) + for i, r in enumerate(rv): + d[i] = r + return d + + +def nC(n, k=None, replacement=False): + """Return the number of combinations of ``n`` items taken ``k`` at a time. + + Possible values for ``n``: + + integer - set of length ``n`` + + sequence - converted to a multiset internally + + multiset - {element: multiplicity} + + If ``k`` is None then the total of all combinations of length 0 + through the number of items represented in ``n`` will be returned. + + If ``replacement`` is True then a given item can appear more than once + in the ``k`` items. (For example, for 'ab' sets of 2 would include 'aa', + 'ab', and 'bb'.) The multiplicity of elements in ``n`` is ignored when + ``replacement`` is True but the total number of elements is considered + since no element can appear more times than the number of elements in + ``n``. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import nC + >>> from sympy.utilities.iterables import multiset_combinations + >>> nC(3, 2) + 3 + >>> nC('abc', 2) + 3 + >>> nC('aab', 2) + 2 + + When ``replacement`` is True, each item can have multiplicity + equal to the length represented by ``n``: + + >>> nC('aabc', replacement=True) + 35 + >>> [len(list(multiset_combinations('aaaabbbbcccc', i))) for i in range(5)] + [1, 3, 6, 10, 15] + >>> sum(_) + 35 + + If there are ``k`` items with multiplicities ``m_1, m_2, ..., m_k`` + then the total of all combinations of length 0 through ``k`` is the + product, ``(m_1 + 1)*(m_2 + 1)*...*(m_k + 1)``. When the multiplicity + of each item is 1 (i.e., k unique items) then there are 2**k + combinations. For example, if there are 4 unique items, the total number + of combinations is 16: + + >>> sum(nC(4, i) for i in range(5)) + 16 + + See Also + ======== + + sympy.utilities.iterables.multiset_combinations + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Combination + .. [2] https://tinyurl.com/cep849r + + """ + + if isinstance(n, SYMPY_INTS): + if k is None: + if not replacement: + return 2**n + return sum(nC(n, i, replacement) for i in range(n + 1)) + if k < 0: + raise ValueError("k cannot be negative") + if replacement: + return binomial(n + k - 1, k) + return binomial(n, k) + if isinstance(n, _MultisetHistogram): + N = n[_N] + if k is None: + if not replacement: + return prod(m + 1 for m in n[_M]) + return sum(nC(n, i, replacement) for i in range(N + 1)) + elif replacement: + return nC(n[_ITEMS], k, replacement) + # assert k >= 0 + elif k in (1, N - 1): + return n[_ITEMS] + elif k in (0, N): + return 1 + return _AOP_product(tuple(n[_M]))[k] + else: + return nC(_multiset_histogram(n), k, replacement) + + +def _eval_stirling1(n, k): + if n == k == 0: + return S.One + if 0 in (n, k): + return S.Zero + + # some special values + if n == k: + return S.One + elif k == n - 1: + return binomial(n, 2) + elif k == n - 2: + return (3*n - 1)*binomial(n, 3)/4 + elif k == n - 3: + return binomial(n, 2)*binomial(n, 4) + + return _stirling1(n, k) + + +@cacheit +def _stirling1(n, k): + row = [0, 1]+[0]*(k-1) # for n = 1 + for i in range(2, n+1): + for j in range(min(k,i), 0, -1): + row[j] = (i-1) * row[j] + row[j-1] + return Integer(row[k]) + + +def _eval_stirling2(n, k): + if n == k == 0: + return S.One + if 0 in (n, k): + return S.Zero + + # some special values + if n == k: + return S.One + elif k == n - 1: + return binomial(n, 2) + elif k == 1: + return S.One + elif k == 2: + return Integer(2**(n - 1) - 1) + + return _stirling2(n, k) + + +@cacheit +def _stirling2(n, k): + row = [0, 1]+[0]*(k-1) # for n = 1 + for i in range(2, n+1): + for j in range(min(k,i), 0, -1): + row[j] = j * row[j] + row[j-1] + return Integer(row[k]) + + +def stirling(n, k, d=None, kind=2, signed=False): + r"""Return Stirling number $S(n, k)$ of the first or second (default) kind. + + The sum of all Stirling numbers of the second kind for $k = 1$ + through $n$ is ``bell(n)``. The recurrence relationship for these numbers + is: + + .. math :: {0 \brace 0} = 1; {n \brace 0} = {0 \brace k} = 0; + + .. math :: {{n+1} \brace k} = j {n \brace k} + {n \brace {k-1}} + + where $j$ is: + $n$ for Stirling numbers of the first kind, + $-n$ for signed Stirling numbers of the first kind, + $k$ for Stirling numbers of the second kind. + + The first kind of Stirling number counts the number of permutations of + ``n`` distinct items that have ``k`` cycles; the second kind counts the + ways in which ``n`` distinct items can be partitioned into ``k`` parts. + If ``d`` is given, the "reduced Stirling number of the second kind" is + returned: $S^{d}(n, k) = S(n - d + 1, k - d + 1)$ with $n \ge k \ge d$. + (This counts the ways to partition $n$ consecutive integers into $k$ + groups with no pairwise difference less than $d$. See example below.) + + To obtain the signed Stirling numbers of the first kind, use keyword + ``signed=True``. Using this keyword automatically sets ``kind`` to 1. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import stirling, bell + >>> from sympy.combinatorics import Permutation + >>> from sympy.utilities.iterables import multiset_partitions, permutations + + First kind (unsigned by default): + + >>> [stirling(6, i, kind=1) for i in range(7)] + [0, 120, 274, 225, 85, 15, 1] + >>> perms = list(permutations(range(4))) + >>> [sum(Permutation(p).cycles == i for p in perms) for i in range(5)] + [0, 6, 11, 6, 1] + >>> [stirling(4, i, kind=1) for i in range(5)] + [0, 6, 11, 6, 1] + + First kind (signed): + + >>> [stirling(4, i, signed=True) for i in range(5)] + [0, -6, 11, -6, 1] + + Second kind: + + >>> [stirling(10, i) for i in range(12)] + [0, 1, 511, 9330, 34105, 42525, 22827, 5880, 750, 45, 1, 0] + >>> sum(_) == bell(10) + True + >>> len(list(multiset_partitions(range(4), 2))) == stirling(4, 2) + True + + Reduced second kind: + + >>> from sympy import subsets, oo + >>> def delta(p): + ... if len(p) == 1: + ... return oo + ... return min(abs(i[0] - i[1]) for i in subsets(p, 2)) + >>> parts = multiset_partitions(range(5), 3) + >>> d = 2 + >>> sum(1 for p in parts if all(delta(i) >= d for i in p)) + 7 + >>> stirling(5, 3, 2) + 7 + + See Also + ======== + sympy.utilities.iterables.multiset_partitions + + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Stirling_numbers_of_the_first_kind + .. [2] https://en.wikipedia.org/wiki/Stirling_numbers_of_the_second_kind + + """ + # TODO: make this a class like bell() + + n = as_int(n) + k = as_int(k) + if n < 0: + raise ValueError('n must be nonnegative') + if k > n: + return S.Zero + if d: + # assert k >= d + # kind is ignored -- only kind=2 is supported + return _eval_stirling2(n - d + 1, k - d + 1) + elif signed: + # kind is ignored -- only kind=1 is supported + return S.NegativeOne**(n - k)*_eval_stirling1(n, k) + + if kind == 1: + return _eval_stirling1(n, k) + elif kind == 2: + return _eval_stirling2(n, k) + else: + raise ValueError('kind must be 1 or 2, not %s' % k) + + +@cacheit +def _nT(n, k): + """Return the partitions of ``n`` items into ``k`` parts. This + is used by ``nT`` for the case when ``n`` is an integer.""" + # really quick exits + if k > n or k < 0: + return 0 + if k in (1, n): + return 1 + if k == 0: + return 0 + # exits that could be done below but this is quicker + if k == 2: + return n//2 + d = n - k + if d <= 3: + return d + # quick exit + if 3*k >= n: # or, equivalently, 2*k >= d + # all the information needed in this case + # will be in the cache needed to calculate + # partition(d), so... + # update cache + tot = _partition_rec(d) + # and correct for values not needed + if d - k > 0: + tot -= sum(_partition_rec.fetch_item(slice(d - k))) + return tot + # regular exit + # nT(n, k) = Sum(nT(n - k, m), (m, 1, k)); + # calculate needed nT(i, j) values + p = [1]*d + for i in range(2, k + 1): + for m in range(i + 1, d): + p[m] += p[m - i] + d -= 1 + # if p[0] were appended to the end of p then the last + # k values of p are the nT(n, j) values for 0 < j < k in reverse + # order p[-1] = nT(n, 1), p[-2] = nT(n, 2), etc.... Instead of + # putting the 1 from p[0] there, however, it is simply added to + # the sum below which is valid for 1 < k <= n//2 + return (1 + sum(p[1 - k:])) + + +def nT(n, k=None): + """Return the number of ``k``-sized partitions of ``n`` items. + + Possible values for ``n``: + + integer - ``n`` identical items + + sequence - converted to a multiset internally + + multiset - {element: multiplicity} + + Note: the convention for ``nT`` is different than that of ``nC`` and + ``nP`` in that + here an integer indicates ``n`` *identical* items instead of a set of + length ``n``; this is in keeping with the ``partitions`` function which + treats its integer-``n`` input like a list of ``n`` 1s. One can use + ``range(n)`` for ``n`` to indicate ``n`` distinct items. + + If ``k`` is None then the total number of ways to partition the elements + represented in ``n`` will be returned. + + Examples + ======== + + >>> from sympy.functions.combinatorial.numbers import nT + + Partitions of the given multiset: + + >>> [nT('aabbc', i) for i in range(1, 7)] + [1, 8, 11, 5, 1, 0] + >>> nT('aabbc') == sum(_) + True + + >>> [nT("mississippi", i) for i in range(1, 12)] + [1, 74, 609, 1521, 1768, 1224, 579, 197, 50, 9, 1] + + Partitions when all items are identical: + + >>> [nT(5, i) for i in range(1, 6)] + [1, 2, 2, 1, 1] + >>> nT('1'*5) == sum(_) + True + + When all items are different: + + >>> [nT(range(5), i) for i in range(1, 6)] + [1, 15, 25, 10, 1] + >>> nT(range(5)) == sum(_) + True + + Partitions of an integer expressed as a sum of positive integers: + + >>> from sympy import partition + >>> partition(4) + 5 + >>> nT(4, 1) + nT(4, 2) + nT(4, 3) + nT(4, 4) + 5 + >>> nT('1'*4) + 5 + + See Also + ======== + sympy.utilities.iterables.partitions + sympy.utilities.iterables.multiset_partitions + sympy.functions.combinatorial.numbers.partition + + References + ========== + + .. [1] https://web.archive.org/web/20210507012732/https://teaching.csse.uwa.edu.au/units/CITS7209/partition.pdf + + """ + + if isinstance(n, SYMPY_INTS): + # n identical items + if k is None: + return partition(n) + if isinstance(k, SYMPY_INTS): + n = as_int(n) + k = as_int(k) + return Integer(_nT(n, k)) + if not isinstance(n, _MultisetHistogram): + try: + # if n contains hashable items there is some + # quick handling that can be done + u = len(set(n)) + if u <= 1: + return nT(len(n), k) + elif u == len(n): + n = range(u) + raise TypeError + except TypeError: + n = _multiset_histogram(n) + N = n[_N] + if k is None and N == 1: + return 1 + if k in (1, N): + return 1 + if k == 2 or N == 2 and k is None: + m, r = divmod(N, 2) + rv = sum(nC(n, i) for i in range(1, m + 1)) + if not r: + rv -= nC(n, m)//2 + if k is None: + rv += 1 # for k == 1 + return rv + if N == n[_ITEMS]: + # all distinct + if k is None: + return bell(N) + return stirling(N, k) + m = MultisetPartitionTraverser() + if k is None: + return m.count_partitions(n[_M]) + # MultisetPartitionTraverser does not have a range-limited count + # method, so need to enumerate and count + tot = 0 + for discard in m.enum_range(n[_M], k-1, k): + tot += 1 + return tot + + +#-----------------------------------------------------------------------------# +# # +# Motzkin numbers # +# # +#-----------------------------------------------------------------------------# + + +class motzkin(Function): + """ + The nth Motzkin number is the number + of ways of drawing non-intersecting chords + between n points on a circle (not necessarily touching + every point by a chord). The Motzkin numbers are named + after Theodore Motzkin and have diverse applications + in geometry, combinatorics and number theory. + + Motzkin numbers are the integer sequence defined by the + initial terms `M_0 = 1`, `M_1 = 1` and the two-term recurrence relation + `M_n = \frac{2*n + 1}{n + 2} * M_{n-1} + \frac{3n - 3}{n + 2} * M_{n-2}`. + + + Examples + ======== + + >>> from sympy import motzkin + + >>> motzkin.is_motzkin(5) + False + >>> motzkin.find_motzkin_numbers_in_range(2,300) + [2, 4, 9, 21, 51, 127] + >>> motzkin.find_motzkin_numbers_in_range(2,900) + [2, 4, 9, 21, 51, 127, 323, 835] + >>> motzkin.find_first_n_motzkins(10) + [1, 1, 2, 4, 9, 21, 51, 127, 323, 835] + + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Motzkin_number + .. [2] https://mathworld.wolfram.com/MotzkinNumber.html + + """ + + @staticmethod + def is_motzkin(n): + try: + n = as_int(n) + except ValueError: + return False + if n > 0: + if n in (1, 2): + return True + + tn1 = 1 + tn = 2 + i = 3 + while tn < n: + a = ((2*i + 1)*tn + (3*i - 3)*tn1)/(i + 2) + i += 1 + tn1 = tn + tn = a + + if tn == n: + return True + else: + return False + + else: + return False + + @staticmethod + def find_motzkin_numbers_in_range(x, y): + if 0 <= x <= y: + motzkins = [] + if x <= 1 <= y: + motzkins.append(1) + tn1 = 1 + tn = 2 + i = 3 + while tn <= y: + if tn >= x: + motzkins.append(tn) + a = ((2*i + 1)*tn + (3*i - 3)*tn1)/(i + 2) + i += 1 + tn1 = tn + tn = int(a) + + return motzkins + + else: + raise ValueError('The provided range is not valid. This condition should satisfy x <= y') + + @staticmethod + def find_first_n_motzkins(n): + try: + n = as_int(n) + except ValueError: + raise ValueError('The provided number must be a positive integer') + if n < 0: + raise ValueError('The provided number must be a positive integer') + motzkins = [1] + if n >= 1: + motzkins.append(1) + tn1 = 1 + tn = 2 + i = 3 + while i <= n: + motzkins.append(tn) + a = ((2*i + 1)*tn + (3*i - 3)*tn1)/(i + 2) + i += 1 + tn1 = tn + tn = int(a) + + return motzkins + + @staticmethod + @recurrence_memo([S.One, S.One]) + def _motzkin(n, prev): + return ((2*n + 1)*prev[-1] + (3*n - 3)*prev[-2]) // (n + 2) + + @classmethod + def eval(cls, n): + try: + n = as_int(n) + except ValueError: + raise ValueError('The provided number must be a positive integer') + if n < 0: + raise ValueError('The provided number must be a positive integer') + return Integer(cls._motzkin(n - 1)) + + +def nD(i=None, brute=None, *, n=None, m=None): + """return the number of derangements for: ``n`` unique items, ``i`` + items (as a sequence or multiset), or multiplicities, ``m`` given + as a sequence or multiset. + + Examples + ======== + + >>> from sympy.utilities.iterables import generate_derangements as enum + >>> from sympy.functions.combinatorial.numbers import nD + + A derangement ``d`` of sequence ``s`` has all ``d[i] != s[i]``: + + >>> set([''.join(i) for i in enum('abc')]) + {'bca', 'cab'} + >>> nD('abc') + 2 + + Input as iterable or dictionary (multiset form) is accepted: + + >>> assert nD([1, 2, 2, 3, 3, 3]) == nD({1: 1, 2: 2, 3: 3}) + + By default, a brute-force enumeration and count of multiset permutations + is only done if there are fewer than 9 elements. There may be cases when + there is high multiplicity with few unique elements that will benefit + from a brute-force enumeration, too. For this reason, the `brute` + keyword (default None) is provided. When False, the brute-force + enumeration will never be used. When True, it will always be used. + + >>> nD('1111222233', brute=True) + 44 + + For convenience, one may specify ``n`` distinct items using the + ``n`` keyword: + + >>> assert nD(n=3) == nD('abc') == 2 + + Since the number of derangments depends on the multiplicity of the + elements and not the elements themselves, it may be more convenient + to give a list or multiset of multiplicities using keyword ``m``: + + >>> assert nD('abc') == nD(m=(1,1,1)) == nD(m={1:3}) == 2 + + """ + from sympy.integrals.integrals import integrate + from sympy.functions.special.polynomials import laguerre + from sympy.abc import x + def ok(x): + if not isinstance(x, SYMPY_INTS): + raise TypeError('expecting integer values') + if x < 0: + raise ValueError('value must not be negative') + return True + + if (i, n, m).count(None) != 2: + raise ValueError('enter only 1 of i, n, or m') + if i is not None: + if isinstance(i, SYMPY_INTS): + raise TypeError('items must be a list or dictionary') + if not i: + return S.Zero + if type(i) is not dict: + s = list(i) + ms = multiset(s) + elif type(i) is dict: + all(ok(_) for _ in i.values()) + ms = {k: v for k, v in i.items() if v} + s = None + if not ms: + return S.Zero + N = sum(ms.values()) + counts = multiset(ms.values()) + nkey = len(ms) + elif n is not None: + ok(n) + if not n: + return S.Zero + return subfactorial(n) + elif m is not None: + if isinstance(m, dict): + all(ok(i) and ok(j) for i, j in m.items()) + counts = {k: v for k, v in m.items() if k*v} + elif iterable(m) or isinstance(m, str): + m = list(m) + all(ok(i) for i in m) + counts = multiset([i for i in m if i]) + else: + raise TypeError('expecting iterable') + if not counts: + return S.Zero + N = sum(k*v for k, v in counts.items()) + nkey = sum(counts.values()) + s = None + big = int(max(counts)) + if big == 1: # no repetition + return subfactorial(nkey) + nval = len(counts) + if big*2 > N: + return S.Zero + if big*2 == N: + if nkey == 2 and nval == 1: + return S.One # aaabbb + if nkey - 1 == big: # one element repeated + return factorial(big) # e.g. abc part of abcddd + if N < 9 and brute is None or brute: + # for all possibilities, this was found to be faster + if s is None: + s = [] + i = 0 + for m, v in counts.items(): + for j in range(v): + s.extend([i]*m) + i += 1 + return Integer(sum(1 for i in multiset_derangements(s))) + from sympy.functions.elementary.exponential import exp + return Integer(abs(integrate(exp(-x)*Mul(*[ + laguerre(i, x)**m for i, m in counts.items()]), (x, 0, oo)))) diff --git a/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/__init__.py b/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/__pycache__/__init__.cpython-312.pyc 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b/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/test_comb_factorials.py new file mode 100644 index 0000000000000000000000000000000000000000..bf56945e760886bd86b0e5c637d720a3a85513bb --- /dev/null +++ b/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/test_comb_factorials.py @@ -0,0 +1,653 @@ +from sympy.concrete.products import Product +from sympy.core.function import expand_func +from sympy.core.mod import Mod +from sympy.core.mul import Mul +from sympy.core import EulerGamma +from sympy.core.numbers import (Float, I, Rational, nan, oo, pi, zoo) +from sympy.core.relational import Eq +from sympy.core.singleton import S +from sympy.core.symbol import (Dummy, Symbol, symbols) +from sympy.functions.combinatorial.factorials import (ff, rf, binomial, factorial, factorial2) +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.piecewise import Piecewise +from sympy.functions.special.gamma_functions import (gamma, polygamma) +from sympy.polys.polytools import Poly +from sympy.series.order import O +from sympy.simplify.simplify import simplify +from sympy.core.expr import unchanged +from sympy.core.function import ArgumentIndexError +from sympy.functions.combinatorial.factorials import subfactorial +from sympy.functions.special.gamma_functions import uppergamma +from sympy.testing.pytest import XFAIL, raises, slow + +#Solves and Fixes Issue #10388 - This is the updated test for the same solved issue + +def test_rf_eval_apply(): + x, y = symbols('x,y') + n, k = symbols('n k', integer=True) + m = Symbol('m', integer=True, nonnegative=True) + + assert rf(nan, y) is nan + assert rf(x, nan) is nan + + assert unchanged(rf, x, y) + + assert rf(oo, 0) == 1 + assert rf(-oo, 0) == 1 + + assert rf(oo, 6) is oo + assert rf(-oo, 7) is -oo + assert rf(-oo, 6) is oo + + assert rf(oo, -6) is oo + assert rf(-oo, -7) is oo + + assert rf(-1, pi) == 0 + assert rf(-5, 1 + I) == 0 + + assert unchanged(rf, -3, k) + assert unchanged(rf, x, Symbol('k', integer=False)) + assert rf(-3, Symbol('k', integer=False)) == 0 + assert rf(Symbol('x', negative=True, integer=True), Symbol('k', integer=False)) == 0 + + assert rf(x, 0) == 1 + assert rf(x, 1) == x + assert rf(x, 2) == x*(x + 1) + assert rf(x, 3) == x*(x + 1)*(x + 2) + assert rf(x, 5) == x*(x + 1)*(x + 2)*(x + 3)*(x + 4) + + assert rf(x, -1) == 1/(x - 1) + assert rf(x, -2) == 1/((x - 1)*(x - 2)) + assert rf(x, -3) == 1/((x - 1)*(x - 2)*(x - 3)) + + assert rf(1, 100) == factorial(100) + + assert rf(x**2 + 3*x, 2) == (x**2 + 3*x)*(x**2 + 3*x + 1) + assert isinstance(rf(x**2 + 3*x, 2), Mul) + assert rf(x**3 + x, -2) == 1/((x**3 + x - 1)*(x**3 + x - 2)) + + assert rf(Poly(x**2 + 3*x, x), 2) == Poly(x**4 + 8*x**3 + 19*x**2 + 12*x, x) + assert isinstance(rf(Poly(x**2 + 3*x, x), 2), Poly) + raises(ValueError, lambda: rf(Poly(x**2 + 3*x, x, y), 2)) + assert rf(Poly(x**3 + x, x), -2) == 1/(x**6 - 9*x**5 + 35*x**4 - 75*x**3 + 94*x**2 - 66*x + 20) + raises(ValueError, lambda: rf(Poly(x**3 + x, x, y), -2)) + + assert rf(x, m).is_integer is None + assert rf(n, k).is_integer is None + assert rf(n, m).is_integer is True + assert rf(n, k + pi).is_integer is False + assert rf(n, m + pi).is_integer is False + assert rf(pi, m).is_integer is False + + def check(x, k, o, n): + a, b = Dummy(), Dummy() + r = lambda x, k: o(a, b).rewrite(n).subs({a:x,b:k}) + for i in range(-5,5): + for j in range(-5,5): + assert o(i, j) == r(i, j), (o, n, i, j) + check(x, k, rf, ff) + check(x, k, rf, binomial) + check(n, k, rf, factorial) + check(x, y, rf, factorial) + check(x, y, rf, binomial) + + assert rf(x, k).rewrite(ff) == ff(x + k - 1, k) + assert rf(x, k).rewrite(gamma) == Piecewise( + (gamma(k + x)/gamma(x), x > 0), + ((-1)**k*gamma(1 - x)/gamma(-k - x + 1), True)) + assert rf(5, k).rewrite(gamma) == gamma(k + 5)/24 + assert rf(x, k).rewrite(binomial) == factorial(k)*binomial(x + k - 1, k) + assert rf(n, k).rewrite(factorial) == Piecewise( + (factorial(k + n - 1)/factorial(n - 1), n > 0), + ((-1)**k*factorial(-n)/factorial(-k - n), True)) + assert rf(5, k).rewrite(factorial) == factorial(k + 4)/24 + assert rf(x, y).rewrite(factorial) == rf(x, y) + assert rf(x, y).rewrite(binomial) == rf(x, y) + + import random + from mpmath import rf as mpmath_rf + for i in range(100): + x = -500 + 500 * random.random() + k = -500 + 500 * random.random() + assert (abs(mpmath_rf(x, k) - rf(x, k)) < 10**(-15)) + + +def test_ff_eval_apply(): + x, y = symbols('x,y') + n, k = symbols('n k', integer=True) + m = Symbol('m', integer=True, nonnegative=True) + + assert ff(nan, y) is nan + assert ff(x, nan) is nan + + assert unchanged(ff, x, y) + + assert ff(oo, 0) == 1 + assert ff(-oo, 0) == 1 + + assert ff(oo, 6) is oo + assert ff(-oo, 7) is -oo + assert ff(-oo, 6) is oo + + assert ff(oo, -6) is oo + assert ff(-oo, -7) is oo + + assert ff(x, 0) == 1 + assert ff(x, 1) == x + assert ff(x, 2) == x*(x - 1) + assert ff(x, 3) == x*(x - 1)*(x - 2) + assert ff(x, 5) == x*(x - 1)*(x - 2)*(x - 3)*(x - 4) + + assert ff(x, -1) == 1/(x + 1) + assert ff(x, -2) == 1/((x + 1)*(x + 2)) + assert ff(x, -3) == 1/((x + 1)*(x + 2)*(x + 3)) + + assert ff(100, 100) == factorial(100) + + assert ff(2*x**2 - 5*x, 2) == (2*x**2 - 5*x)*(2*x**2 - 5*x - 1) + assert isinstance(ff(2*x**2 - 5*x, 2), Mul) + assert ff(x**2 + 3*x, -2) == 1/((x**2 + 3*x + 1)*(x**2 + 3*x + 2)) + + assert ff(Poly(2*x**2 - 5*x, x), 2) == Poly(4*x**4 - 28*x**3 + 59*x**2 - 35*x, x) + assert isinstance(ff(Poly(2*x**2 - 5*x, x), 2), Poly) + raises(ValueError, lambda: ff(Poly(2*x**2 - 5*x, x, y), 2)) + assert ff(Poly(x**2 + 3*x, x), -2) == 1/(x**4 + 12*x**3 + 49*x**2 + 78*x + 40) + raises(ValueError, lambda: ff(Poly(x**2 + 3*x, x, y), -2)) + + + assert ff(x, m).is_integer is None + assert ff(n, k).is_integer is None + assert ff(n, m).is_integer is True + assert ff(n, k + pi).is_integer is False + assert ff(n, m + pi).is_integer is False + assert ff(pi, m).is_integer is False + + assert isinstance(ff(x, x), ff) + assert ff(n, n) == factorial(n) + + def check(x, k, o, n): + a, b = Dummy(), Dummy() + r = lambda x, k: o(a, b).rewrite(n).subs({a:x,b:k}) + for i in range(-5,5): + for j in range(-5,5): + assert o(i, j) == r(i, j), (o, n) + check(x, k, ff, rf) + check(x, k, ff, gamma) + check(n, k, ff, factorial) + check(x, k, ff, binomial) + check(x, y, ff, factorial) + check(x, y, ff, binomial) + + assert ff(x, k).rewrite(rf) == rf(x - k + 1, k) + assert ff(x, k).rewrite(gamma) == Piecewise( + (gamma(x + 1)/gamma(-k + x + 1), x >= 0), + ((-1)**k*gamma(k - x)/gamma(-x), True)) + assert ff(5, k).rewrite(gamma) == 120/gamma(6 - k) + assert ff(n, k).rewrite(factorial) == Piecewise( + (factorial(n)/factorial(-k + n), n >= 0), + ((-1)**k*factorial(k - n - 1)/factorial(-n - 1), True)) + assert ff(5, k).rewrite(factorial) == 120/factorial(5 - k) + assert ff(x, k).rewrite(binomial) == factorial(k) * binomial(x, k) + assert ff(x, y).rewrite(factorial) == ff(x, y) + assert ff(x, y).rewrite(binomial) == ff(x, y) + + import random + from mpmath import ff as mpmath_ff + for i in range(100): + x = -500 + 500 * random.random() + k = -500 + 500 * random.random() + a = mpmath_ff(x, k) + b = ff(x, k) + assert (abs(a - b) < abs(a) * 10**(-15)) + + +def test_rf_ff_eval_hiprec(): + maple = Float('6.9109401292234329956525265438452') + us = ff(18, Rational(2, 3)).evalf(32) + assert abs(us - maple)/us < 1e-31 + + maple = Float('6.8261540131125511557924466355367') + us = rf(18, Rational(2, 3)).evalf(32) + assert abs(us - maple)/us < 1e-31 + + maple = Float('34.007346127440197150854651814225') + us = rf(Float('4.4', 32), Float('2.2', 32)); + assert abs(us - maple)/us < 1e-31 + + +def test_rf_lambdify_mpmath(): + from sympy.utilities.lambdify import lambdify + x, y = symbols('x,y') + f = lambdify((x,y), rf(x, y), 'mpmath') + maple = Float('34.007346127440197') + us = f(4.4, 2.2) + assert abs(us - maple)/us < 1e-15 + + +def test_factorial(): + x = Symbol('x') + n = Symbol('n', integer=True) + k = Symbol('k', integer=True, nonnegative=True) + r = Symbol('r', integer=False) + s = Symbol('s', integer=False, negative=True) + t = Symbol('t', nonnegative=True) + u = Symbol('u', noninteger=True) + + assert factorial(-2) is zoo + assert factorial(0) == 1 + assert factorial(7) == 5040 + assert factorial(19) == 121645100408832000 + assert factorial(31) == 8222838654177922817725562880000000 + assert factorial(n).func == factorial + assert factorial(2*n).func == factorial + + assert factorial(x).is_integer is None + assert factorial(n).is_integer is None + assert factorial(k).is_integer + assert factorial(r).is_integer is None + + assert factorial(n).is_positive is None + assert factorial(k).is_positive + + assert factorial(x).is_real is None + assert factorial(n).is_real is None + assert factorial(k).is_real is True + assert factorial(r).is_real is None + assert factorial(s).is_real is True + assert factorial(t).is_real is True + assert factorial(u).is_real is True + + assert factorial(x).is_composite is None + assert factorial(n).is_composite is None + assert factorial(k).is_composite is None + assert factorial(k + 3).is_composite is True + assert factorial(r).is_composite is None + assert factorial(s).is_composite is None + assert factorial(t).is_composite is None + assert factorial(u).is_composite is None + + assert factorial(oo) is oo + + +def test_factorial_Mod(): + pr = Symbol('pr', prime=True) + p, q = 10**9 + 9, 10**9 + 33 # prime modulo + r, s = 10**7 + 5, 33333333 # composite modulo + assert Mod(factorial(pr - 1), pr) == pr - 1 + assert Mod(factorial(pr - 1), -pr) == -1 + assert Mod(factorial(r - 1, evaluate=False), r) == 0 + assert Mod(factorial(s - 1, evaluate=False), s) == 0 + assert Mod(factorial(p - 1, evaluate=False), p) == p - 1 + assert Mod(factorial(q - 1, evaluate=False), q) == q - 1 + assert Mod(factorial(p - 50, evaluate=False), p) == 854928834 + assert Mod(factorial(q - 1800, evaluate=False), q) == 905504050 + assert Mod(factorial(153, evaluate=False), r) == Mod(factorial(153), r) + assert Mod(factorial(255, evaluate=False), s) == Mod(factorial(255), s) + assert Mod(factorial(4, evaluate=False), 3) == S.Zero + assert Mod(factorial(5, evaluate=False), 6) == S.Zero + + +def test_factorial_diff(): + n = Symbol('n', integer=True) + + assert factorial(n).diff(n) == \ + gamma(1 + n)*polygamma(0, 1 + n) + assert factorial(n**2).diff(n) == \ + 2*n*gamma(1 + n**2)*polygamma(0, 1 + n**2) + raises(ArgumentIndexError, lambda: factorial(n**2).fdiff(2)) + + +def test_factorial_series(): + n = Symbol('n', integer=True) + + assert factorial(n).series(n, 0, 3) == \ + 1 - n*EulerGamma + n**2*(EulerGamma**2/2 + pi**2/12) + O(n**3) + + +def test_factorial_rewrite(): + n = Symbol('n', integer=True) + k = Symbol('k', integer=True, nonnegative=True) + + assert factorial(n).rewrite(gamma) == gamma(n + 1) + _i = Dummy('i') + assert factorial(k).rewrite(Product).dummy_eq(Product(_i, (_i, 1, k))) + assert factorial(n).rewrite(Product) == factorial(n) + + +def test_factorial2(): + n = Symbol('n', integer=True) + + assert factorial2(-1) == 1 + assert factorial2(0) == 1 + assert factorial2(7) == 105 + assert factorial2(8) == 384 + + # The following is exhaustive + tt = Symbol('tt', integer=True, nonnegative=True) + tte = Symbol('tte', even=True, nonnegative=True) + tpe = Symbol('tpe', even=True, positive=True) + tto = Symbol('tto', odd=True, nonnegative=True) + tf = Symbol('tf', integer=True, nonnegative=False) + tfe = Symbol('tfe', even=True, nonnegative=False) + tfo = Symbol('tfo', odd=True, nonnegative=False) + ft = Symbol('ft', integer=False, nonnegative=True) + ff = Symbol('ff', integer=False, nonnegative=False) + fn = Symbol('fn', integer=False) + nt = Symbol('nt', nonnegative=True) + nf = Symbol('nf', nonnegative=False) + nn = Symbol('nn') + z = Symbol('z', zero=True) + #Solves and Fixes Issue #10388 - This is the updated test for the same solved issue + raises(ValueError, lambda: factorial2(oo)) + raises(ValueError, lambda: factorial2(Rational(5, 2))) + raises(ValueError, lambda: factorial2(-4)) + assert factorial2(n).is_integer is None + assert factorial2(tt - 1).is_integer + assert factorial2(tte - 1).is_integer + assert factorial2(tpe - 3).is_integer + assert factorial2(tto - 4).is_integer + assert factorial2(tto - 2).is_integer + assert factorial2(tf).is_integer is None + assert factorial2(tfe).is_integer is None + assert factorial2(tfo).is_integer is None + assert factorial2(ft).is_integer is None + assert factorial2(ff).is_integer is None + assert factorial2(fn).is_integer is None + assert factorial2(nt).is_integer is None + assert factorial2(nf).is_integer is None + assert factorial2(nn).is_integer is None + + assert factorial2(n).is_positive is None + assert factorial2(tt - 1).is_positive is True + assert factorial2(tte - 1).is_positive is True + assert factorial2(tpe - 3).is_positive is True + assert factorial2(tpe - 1).is_positive is True + assert factorial2(tto - 2).is_positive is True + assert factorial2(tto - 1).is_positive is True + assert factorial2(tf).is_positive is None + assert factorial2(tfe).is_positive is None + assert factorial2(tfo).is_positive is None + assert factorial2(ft).is_positive is None + assert factorial2(ff).is_positive is None + assert factorial2(fn).is_positive is None + assert factorial2(nt).is_positive is None + assert factorial2(nf).is_positive is None + assert factorial2(nn).is_positive is None + + assert factorial2(tt).is_even is None + assert factorial2(tt).is_odd is None + assert factorial2(tte).is_even is None + assert factorial2(tte).is_odd is None + assert factorial2(tte + 2).is_even is True + assert factorial2(tpe).is_even is True + assert factorial2(tpe).is_odd is False + assert factorial2(tto).is_odd is True + assert factorial2(tf).is_even is None + assert factorial2(tf).is_odd is None + assert factorial2(tfe).is_even is None + assert factorial2(tfe).is_odd is None + assert factorial2(tfo).is_even is False + assert factorial2(tfo).is_odd is None + assert factorial2(z).is_even is False + assert factorial2(z).is_odd is True + + +def test_factorial2_rewrite(): + n = Symbol('n', integer=True) + assert factorial2(n).rewrite(gamma) == \ + 2**(n/2)*Piecewise((1, Eq(Mod(n, 2), 0)), (sqrt(2)/sqrt(pi), Eq(Mod(n, 2), 1)))*gamma(n/2 + 1) + assert factorial2(2*n).rewrite(gamma) == 2**n*gamma(n + 1) + assert factorial2(2*n + 1).rewrite(gamma) == \ + sqrt(2)*2**(n + S.Half)*gamma(n + Rational(3, 2))/sqrt(pi) + + +def test_binomial(): + x = Symbol('x') + n = Symbol('n', integer=True) + nz = Symbol('nz', integer=True, nonzero=True) + k = Symbol('k', integer=True) + kp = Symbol('kp', integer=True, positive=True) + kn = Symbol('kn', integer=True, negative=True) + u = Symbol('u', negative=True) + v = Symbol('v', nonnegative=True) + p = Symbol('p', positive=True) + z = Symbol('z', zero=True) + nt = Symbol('nt', integer=False) + kt = Symbol('kt', integer=False) + a = Symbol('a', integer=True, nonnegative=True) + b = Symbol('b', integer=True, nonnegative=True) + + assert binomial(0, 0) == 1 + assert binomial(1, 1) == 1 + assert binomial(10, 10) == 1 + assert binomial(n, z) == 1 + assert binomial(1, 2) == 0 + assert binomial(-1, 2) == 1 + assert binomial(1, -1) == 0 + assert binomial(-1, 1) == -1 + assert binomial(-1, -1) == 0 + assert binomial(S.Half, S.Half) == 1 + assert binomial(-10, 1) == -10 + assert binomial(-10, 7) == -11440 + assert binomial(n, -1) == 0 # holds for all integers (negative, zero, positive) + assert binomial(kp, -1) == 0 + assert binomial(nz, 0) == 1 + assert expand_func(binomial(n, 1)) == n + assert expand_func(binomial(n, 2)) == n*(n - 1)/2 + assert expand_func(binomial(n, n - 2)) == n*(n - 1)/2 + assert expand_func(binomial(n, n - 1)) == n + assert binomial(n, 3).func == binomial + assert binomial(n, 3).expand(func=True) == n**3/6 - n**2/2 + n/3 + assert expand_func(binomial(n, 3)) == n*(n - 2)*(n - 1)/6 + assert binomial(n, n).func == binomial # e.g. (-1, -1) == 0, (2, 2) == 1 + assert binomial(n, n + 1).func == binomial # e.g. (-1, 0) == 1 + assert binomial(kp, kp + 1) == 0 + assert binomial(kn, kn) == 0 # issue #14529 + assert binomial(n, u).func == binomial + assert binomial(kp, u).func == binomial + assert binomial(n, p).func == binomial + assert binomial(n, k).func == binomial + assert binomial(n, n + p).func == binomial + assert binomial(kp, kp + p).func == binomial + + assert expand_func(binomial(n, n - 3)) == n*(n - 2)*(n - 1)/6 + + assert binomial(n, k).is_integer + assert binomial(nt, k).is_integer is None + assert binomial(x, nt).is_integer is False + + assert binomial(gamma(25), 6) == 79232165267303928292058750056084441948572511312165380965440075720159859792344339983120618959044048198214221915637090855535036339620413440000 + assert binomial(1324, 47) == 906266255662694632984994480774946083064699457235920708992926525848438478406790323869952 + assert binomial(1735, 43) == 190910140420204130794758005450919715396159959034348676124678207874195064798202216379800 + assert binomial(2512, 53) == 213894469313832631145798303740098720367984955243020898718979538096223399813295457822575338958939834177325304000 + assert binomial(3383, 52) == 27922807788818096863529701501764372757272890613101645521813434902890007725667814813832027795881839396839287659777235 + assert binomial(4321, 51) == 124595639629264868916081001263541480185227731958274383287107643816863897851139048158022599533438936036467601690983780576 + + assert binomial(a, b).is_nonnegative is True + assert binomial(-1, 2, evaluate=False).is_nonnegative is True + assert binomial(10, 5, evaluate=False).is_nonnegative is True + assert binomial(10, -3, evaluate=False).is_nonnegative is True + assert binomial(-10, -3, evaluate=False).is_nonnegative is True + assert binomial(-10, 2, evaluate=False).is_nonnegative is True + assert binomial(-10, 1, evaluate=False).is_nonnegative is False + assert binomial(-10, 7, evaluate=False).is_nonnegative is False + + # issue #14625 + for _ in (pi, -pi, nt, v, a): + assert binomial(_, _) == 1 + assert binomial(_, _ - 1) == _ + assert isinstance(binomial(u, u), binomial) + assert isinstance(binomial(u, u - 1), binomial) + assert isinstance(binomial(x, x), binomial) + assert isinstance(binomial(x, x - 1), binomial) + + #issue #18802 + assert expand_func(binomial(x + 1, x)) == x + 1 + assert expand_func(binomial(x, x - 1)) == x + assert expand_func(binomial(x + 1, x - 1)) == x*(x + 1)/2 + assert expand_func(binomial(x**2 + 1, x**2)) == x**2 + 1 + + # issue #13980 and #13981 + assert binomial(-7, -5) == 0 + assert binomial(-23, -12) == 0 + assert binomial(Rational(13, 2), -10) == 0 + assert binomial(-49, -51) == 0 + + assert binomial(19, Rational(-7, 2)) == S(-68719476736)/(911337863661225*pi) + assert binomial(0, Rational(3, 2)) == S(-2)/(3*pi) + assert binomial(-3, Rational(-7, 2)) is zoo + assert binomial(kn, kt) is zoo + + assert binomial(nt, kt).func == binomial + assert binomial(nt, Rational(15, 6)) == 8*gamma(nt + 1)/(15*sqrt(pi)*gamma(nt - Rational(3, 2))) + assert binomial(Rational(20, 3), Rational(-10, 8)) == gamma(Rational(23, 3))/(gamma(Rational(-1, 4))*gamma(Rational(107, 12))) + assert binomial(Rational(19, 2), Rational(-7, 2)) == Rational(-1615, 8388608) + assert binomial(Rational(-13, 5), Rational(-7, 8)) == gamma(Rational(-8, 5))/(gamma(Rational(-29, 40))*gamma(Rational(1, 8))) + assert binomial(Rational(-19, 8), Rational(-13, 5)) == gamma(Rational(-11, 8))/(gamma(Rational(-8, 5))*gamma(Rational(49, 40))) + + # binomial for complexes + assert binomial(I, Rational(-89, 8)) == gamma(1 + I)/(gamma(Rational(-81, 8))*gamma(Rational(97, 8) + I)) + assert binomial(I, 2*I) == gamma(1 + I)/(gamma(1 - I)*gamma(1 + 2*I)) + assert binomial(-7, I) is zoo + assert binomial(Rational(-7, 6), I) == gamma(Rational(-1, 6))/(gamma(Rational(-1, 6) - I)*gamma(1 + I)) + assert binomial((1+2*I), (1+3*I)) == gamma(2 + 2*I)/(gamma(1 - I)*gamma(2 + 3*I)) + assert binomial(I, 5) == Rational(1, 3) - I/S(12) + assert binomial((2*I + 3), 7) == -13*I/S(63) + assert isinstance(binomial(I, n), binomial) + assert expand_func(binomial(3, 2, evaluate=False)) == 3 + assert expand_func(binomial(n, 0, evaluate=False)) == 1 + assert expand_func(binomial(n, -2, evaluate=False)) == 0 + assert expand_func(binomial(n, k)) == binomial(n, k) + + +def test_binomial_Mod(): + p, q = 10**5 + 3, 10**9 + 33 # prime modulo + r = 10**7 + 5 # composite modulo + + # A few tests to get coverage + # Lucas Theorem + assert Mod(binomial(156675, 4433, evaluate=False), p) == Mod(binomial(156675, 4433), p) + + # factorial Mod + assert Mod(binomial(1234, 432, evaluate=False), q) == Mod(binomial(1234, 432), q) + + # binomial factorize + assert Mod(binomial(253, 113, evaluate=False), r) == Mod(binomial(253, 113), r) + + # using Granville's generalisation of Lucas' Theorem + assert Mod(binomial(10**18, 10**12, evaluate=False), p*p) == 3744312326 + + +@slow +def test_binomial_Mod_slow(): + p, q = 10**5 + 3, 10**9 + 33 # prime modulo + r, s = 10**7 + 5, 33333333 # composite modulo + + n, k, m = symbols('n k m') + assert (binomial(n, k) % q).subs({n: s, k: p}) == Mod(binomial(s, p), q) + assert (binomial(n, k) % m).subs({n: 8, k: 5, m: 13}) == 4 + assert (binomial(9, k) % 7).subs(k, 2) == 1 + + # Lucas Theorem + assert Mod(binomial(123456, 43253, evaluate=False), p) == Mod(binomial(123456, 43253), p) + assert Mod(binomial(-178911, 237, evaluate=False), p) == Mod(-binomial(178911 + 237 - 1, 237), p) + assert Mod(binomial(-178911, 238, evaluate=False), p) == Mod(binomial(178911 + 238 - 1, 238), p) + + # factorial Mod + assert Mod(binomial(9734, 451, evaluate=False), q) == Mod(binomial(9734, 451), q) + assert Mod(binomial(-10733, 4459, evaluate=False), q) == Mod(binomial(-10733, 4459), q) + assert Mod(binomial(-15733, 4458, evaluate=False), q) == Mod(binomial(-15733, 4458), q) + assert Mod(binomial(23, -38, evaluate=False), q) is S.Zero + assert Mod(binomial(23, 38, evaluate=False), q) is S.Zero + + # binomial factorize + assert Mod(binomial(753, 119, evaluate=False), r) == Mod(binomial(753, 119), r) + assert Mod(binomial(3781, 948, evaluate=False), s) == Mod(binomial(3781, 948), s) + assert Mod(binomial(25773, 1793, evaluate=False), s) == Mod(binomial(25773, 1793), s) + assert Mod(binomial(-753, 118, evaluate=False), r) == Mod(binomial(-753, 118), r) + assert Mod(binomial(-25773, 1793, evaluate=False), s) == Mod(binomial(-25773, 1793), s) + + +def test_binomial_diff(): + n = Symbol('n', integer=True) + k = Symbol('k', integer=True) + + assert binomial(n, k).diff(n) == \ + (-polygamma(0, 1 + n - k) + polygamma(0, 1 + n))*binomial(n, k) + assert binomial(n**2, k**3).diff(n) == \ + 2*n*(-polygamma( + 0, 1 + n**2 - k**3) + polygamma(0, 1 + n**2))*binomial(n**2, k**3) + + assert binomial(n, k).diff(k) == \ + (-polygamma(0, 1 + k) + polygamma(0, 1 + n - k))*binomial(n, k) + assert binomial(n**2, k**3).diff(k) == \ + 3*k**2*(-polygamma( + 0, 1 + k**3) + polygamma(0, 1 + n**2 - k**3))*binomial(n**2, k**3) + raises(ArgumentIndexError, lambda: binomial(n, k).fdiff(3)) + + +def test_binomial_rewrite(): + n = Symbol('n', integer=True) + k = Symbol('k', integer=True) + x = Symbol('x') + + assert binomial(n, k).rewrite( + factorial) == factorial(n)/(factorial(k)*factorial(n - k)) + assert binomial( + n, k).rewrite(gamma) == gamma(n + 1)/(gamma(k + 1)*gamma(n - k + 1)) + assert binomial(n, k).rewrite(ff) == ff(n, k) / factorial(k) + assert binomial(n, x).rewrite(ff) == binomial(n, x) + + +@XFAIL +def test_factorial_simplify_fail(): + # simplify(factorial(x + 1).diff(x) - ((x + 1)*factorial(x)).diff(x))) == 0 + from sympy.abc import x + assert simplify(x*polygamma(0, x + 1) - x*polygamma(0, x + 2) + + polygamma(0, x + 1) - polygamma(0, x + 2) + 1) == 0 + + +def test_subfactorial(): + assert all(subfactorial(i) == ans for i, ans in enumerate( + [1, 0, 1, 2, 9, 44, 265, 1854, 14833, 133496])) + assert subfactorial(oo) is oo + assert subfactorial(nan) is nan + assert subfactorial(23) == 9510425471055777937262 + assert unchanged(subfactorial, 2.2) + + x = Symbol('x') + assert subfactorial(x).rewrite(uppergamma) == uppergamma(x + 1, -1)/S.Exp1 + + tt = Symbol('tt', integer=True, nonnegative=True) + tf = Symbol('tf', integer=True, nonnegative=False) + tn = Symbol('tf', integer=True) + ft = Symbol('ft', integer=False, nonnegative=True) + ff = Symbol('ff', integer=False, nonnegative=False) + fn = Symbol('ff', integer=False) + nt = Symbol('nt', nonnegative=True) + nf = Symbol('nf', nonnegative=False) + nn = Symbol('nf') + te = Symbol('te', even=True, nonnegative=True) + to = Symbol('to', odd=True, nonnegative=True) + assert subfactorial(tt).is_integer + assert subfactorial(tf).is_integer is None + assert subfactorial(tn).is_integer is None + assert subfactorial(ft).is_integer is None + assert subfactorial(ff).is_integer is None + assert subfactorial(fn).is_integer is None + assert subfactorial(nt).is_integer is None + assert subfactorial(nf).is_integer is None + assert subfactorial(nn).is_integer is None + assert subfactorial(tt).is_nonnegative + assert subfactorial(tf).is_nonnegative is None + assert subfactorial(tn).is_nonnegative is None + assert subfactorial(ft).is_nonnegative is None + assert subfactorial(ff).is_nonnegative is None + assert subfactorial(fn).is_nonnegative is None + assert subfactorial(nt).is_nonnegative is None + assert subfactorial(nf).is_nonnegative is None + assert subfactorial(nn).is_nonnegative is None + assert subfactorial(tt).is_even is None + assert subfactorial(tt).is_odd is None + assert subfactorial(te).is_odd is True + assert subfactorial(to).is_even is True diff --git a/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/test_comb_numbers.py b/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/test_comb_numbers.py new file mode 100644 index 0000000000000000000000000000000000000000..e521c2f63bb7ea0864155707e34f2d105bd35806 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/functions/combinatorial/tests/test_comb_numbers.py @@ -0,0 +1,1241 @@ +import string + +from sympy.concrete.products import Product +from sympy.concrete.summations import Sum +from sympy.core.function import (diff, expand_func) +from sympy.core import (EulerGamma, TribonacciConstant) +from sympy.core.numbers import (Float, I, Rational, oo, pi) +from sympy.core.singleton import S +from sympy.core.symbol import (Dummy, Symbol, symbols) +from sympy.functions.combinatorial.numbers import carmichael +from sympy.functions.elementary.complexes import (im, re) +from sympy.functions.elementary.integers import floor +from sympy.polys.polytools import cancel +from sympy.series.limits import limit, Limit +from sympy.series.order import O +from sympy.functions import ( + bernoulli, harmonic, bell, fibonacci, tribonacci, lucas, euler, catalan, + genocchi, andre, partition, divisor_sigma, udivisor_sigma, legendre_symbol, + jacobi_symbol, kronecker_symbol, mobius, + primenu, primeomega, totient, reduced_totient, primepi, + motzkin, binomial, gamma, sqrt, cbrt, hyper, log, digamma, + trigamma, polygamma, factorial, sin, cos, cot, polylog, zeta, dirichlet_eta) +from sympy.functions.combinatorial.numbers import _nT +from sympy.ntheory.factor_ import factorint + +from sympy.core.expr import unchanged +from sympy.core.numbers import GoldenRatio, Integer + +from sympy.testing.pytest import raises, nocache_fail, warns_deprecated_sympy +from sympy.abc import x + + +def test_carmichael(): + with warns_deprecated_sympy(): + assert carmichael.is_prime(2821) == False + + +def test_bernoulli(): + assert bernoulli(0) == 1 + assert bernoulli(1) == Rational(1, 2) + assert bernoulli(2) == Rational(1, 6) + assert bernoulli(3) == 0 + assert bernoulli(4) == Rational(-1, 30) + assert bernoulli(5) == 0 + assert bernoulli(6) == Rational(1, 42) + assert bernoulli(7) == 0 + assert bernoulli(8) == Rational(-1, 30) + assert bernoulli(10) == Rational(5, 66) + assert bernoulli(1000001) == 0 + + assert bernoulli(0, x) == 1 + assert bernoulli(1, x) == x - S.Half + assert bernoulli(2, x) == x**2 - x + Rational(1, 6) + assert bernoulli(3, x) == x**3 - (3*x**2)/2 + x/2 + + # Should be fast; computed with mpmath + b = bernoulli(1000) + assert b.p % 10**10 == 7950421099 + assert b.q == 342999030 + + b = bernoulli(10**6, evaluate=False).evalf() + assert str(b) == '-2.23799235765713e+4767529' + + # Issue #8527 + l = Symbol('l', integer=True) + m = Symbol('m', integer=True, nonnegative=True) + n = Symbol('n', integer=True, positive=True) + assert isinstance(bernoulli(2 * l + 1), bernoulli) + assert isinstance(bernoulli(2 * m + 1), bernoulli) + assert bernoulli(2 * n + 1) == 0 + + assert bernoulli(x, 1) == bernoulli(x) + + assert str(bernoulli(0.0, 2.3).evalf(n=10)) == '1.000000000' + assert str(bernoulli(1.0).evalf(n=10)) == '0.5000000000' + assert str(bernoulli(1.2).evalf(n=10)) == '0.4195995367' + assert str(bernoulli(1.2, 0.8).evalf(n=10)) == '0.2144830348' + assert str(bernoulli(1.2, -0.8).evalf(n=10)) == '-1.158865646 - 0.6745558744*I' + assert str(bernoulli(3.0, 1j).evalf(n=10)) == '1.5 - 0.5*I' + assert str(bernoulli(I).evalf(n=10)) == '0.9268485643 - 0.5821580598*I' + assert str(bernoulli(I, I).evalf(n=10)) == '0.1267792071 + 0.01947413152*I' + assert bernoulli(x).evalf() == bernoulli(x) + + +def test_bernoulli_rewrite(): + from sympy.functions.elementary.piecewise import Piecewise + n = Symbol('n', integer=True, nonnegative=True) + + assert bernoulli(-1).rewrite(zeta) == pi**2/6 + assert bernoulli(-2).rewrite(zeta) == 2*zeta(3) + assert not bernoulli(n, -3).rewrite(zeta).has(harmonic) + assert bernoulli(-4, x).rewrite(zeta) == 4*zeta(5, x) + assert isinstance(bernoulli(n, x).rewrite(zeta), Piecewise) + assert bernoulli(n+1, x).rewrite(zeta) == -(n+1) * zeta(-n, x) + + +def test_fibonacci(): + assert [fibonacci(n) for n in range(-3, 5)] == [2, -1, 1, 0, 1, 1, 2, 3] + assert fibonacci(100) == 354224848179261915075 + assert [lucas(n) for n in range(-3, 5)] == [-4, 3, -1, 2, 1, 3, 4, 7] + assert lucas(100) == 792070839848372253127 + + assert fibonacci(1, x) == 1 + assert fibonacci(2, x) == x + assert fibonacci(3, x) == x**2 + 1 + assert fibonacci(4, x) == x**3 + 2*x + + # issue #8800 + n = Dummy('n') + assert fibonacci(n).limit(n, S.Infinity) is S.Infinity + assert lucas(n).limit(n, S.Infinity) is S.Infinity + + assert fibonacci(n).rewrite(sqrt) == \ + 2**(-n)*sqrt(5)*((1 + sqrt(5))**n - (-sqrt(5) + 1)**n) / 5 + assert fibonacci(n).rewrite(sqrt).subs(n, 10).expand() == fibonacci(10) + assert fibonacci(n).rewrite(GoldenRatio).subs(n,10).evalf() == \ + Float(fibonacci(10)) + assert lucas(n).rewrite(sqrt) == \ + (fibonacci(n-1).rewrite(sqrt) + fibonacci(n+1).rewrite(sqrt)).simplify() + assert lucas(n).rewrite(sqrt).subs(n, 10).expand() == lucas(10) + raises(ValueError, lambda: fibonacci(-3, x)) + + +def test_tribonacci(): + assert [tribonacci(n) for n in range(8)] == [0, 1, 1, 2, 4, 7, 13, 24] + assert tribonacci(100) == 98079530178586034536500564 + + assert tribonacci(0, x) == 0 + assert tribonacci(1, x) == 1 + assert tribonacci(2, x) == x**2 + assert tribonacci(3, x) == x**4 + x + assert tribonacci(4, x) == x**6 + 2*x**3 + 1 + assert tribonacci(5, x) == x**8 + 3*x**5 + 3*x**2 + + n = Dummy('n') + assert tribonacci(n).limit(n, S.Infinity) is S.Infinity + + w = (-1 + S.ImaginaryUnit * sqrt(3)) / 2 + a = (1 + cbrt(19 + 3*sqrt(33)) + cbrt(19 - 3*sqrt(33))) / 3 + b = (1 + w*cbrt(19 + 3*sqrt(33)) + w**2*cbrt(19 - 3*sqrt(33))) / 3 + c = (1 + w**2*cbrt(19 + 3*sqrt(33)) + w*cbrt(19 - 3*sqrt(33))) / 3 + assert tribonacci(n).rewrite(sqrt) == \ + (a**(n + 1)/((a - b)*(a - c)) + + b**(n + 1)/((b - a)*(b - c)) + + c**(n + 1)/((c - a)*(c - b))) + assert tribonacci(n).rewrite(sqrt).subs(n, 4).simplify() == tribonacci(4) + assert tribonacci(n).rewrite(GoldenRatio).subs(n,10).evalf() == \ + Float(tribonacci(10)) + assert tribonacci(n).rewrite(TribonacciConstant) == floor( + 3*TribonacciConstant**n*(102*sqrt(33) + 586)**Rational(1, 3)/ + (-2*(102*sqrt(33) + 586)**Rational(1, 3) + 4 + (102*sqrt(33) + + 586)**Rational(2, 3)) + S.Half) + raises(ValueError, lambda: tribonacci(-1, x)) + + +@nocache_fail +def test_bell(): + assert [bell(n) for n in range(8)] == [1, 1, 2, 5, 15, 52, 203, 877] + + assert bell(0, x) == 1 + assert bell(1, x) == x + assert bell(2, x) == x**2 + x + assert bell(5, x) == x**5 + 10*x**4 + 25*x**3 + 15*x**2 + x + assert bell(oo) is S.Infinity + raises(ValueError, lambda: bell(oo, x)) + + raises(ValueError, lambda: bell(-1)) + raises(ValueError, lambda: bell(S.Half)) + + X = symbols('x:6') + # X = (x0, x1, .. x5) + # at the same time: X[1] = x1, X[2] = x2 for standard readablity. + # but we must supply zero-based indexed object X[1:] = (x1, .. x5) + + assert bell(6, 2, X[1:]) == 6*X[5]*X[1] + 15*X[4]*X[2] + 10*X[3]**2 + assert bell( + 6, 3, X[1:]) == 15*X[4]*X[1]**2 + 60*X[3]*X[2]*X[1] + 15*X[2]**3 + + X = (1, 10, 100, 1000, 10000) + assert bell(6, 2, X) == (6 + 15 + 10)*10000 + + X = (1, 2, 3, 3, 5) + assert bell(6, 2, X) == 6*5 + 15*3*2 + 10*3**2 + + X = (1, 2, 3, 5) + assert bell(6, 3, X) == 15*5 + 60*3*2 + 15*2**3 + + # Dobinski's formula + n = Symbol('n', integer=True, nonnegative=True) + # For large numbers, this is too slow + # For nonintegers, there are significant precision errors + for i in [0, 2, 3, 7, 13, 42, 55]: + # Running without the cache this is either very slow or goes into an + # infinite loop. + assert bell(i).evalf() == bell(n).rewrite(Sum).evalf(subs={n: i}) + + m = Symbol("m") + assert bell(m).rewrite(Sum) == bell(m) + assert bell(n, m).rewrite(Sum) == bell(n, m) + # issue 9184 + n = Dummy('n') + assert bell(n).limit(n, S.Infinity) is S.Infinity + + +def test_harmonic(): + n = Symbol("n") + m = Symbol("m") + + assert harmonic(n, 0) == n + assert harmonic(n).evalf() == harmonic(n) + assert harmonic(n, 1) == harmonic(n) + assert harmonic(1, n) == 1 + + assert harmonic(0, 1) == 0 + assert harmonic(1, 1) == 1 + assert harmonic(2, 1) == Rational(3, 2) + assert harmonic(3, 1) == Rational(11, 6) + assert harmonic(4, 1) == Rational(25, 12) + assert harmonic(0, 2) == 0 + assert harmonic(1, 2) == 1 + assert harmonic(2, 2) == Rational(5, 4) + assert harmonic(3, 2) == Rational(49, 36) + assert harmonic(4, 2) == Rational(205, 144) + assert harmonic(0, 3) == 0 + assert harmonic(1, 3) == 1 + assert harmonic(2, 3) == Rational(9, 8) + assert harmonic(3, 3) == Rational(251, 216) + assert harmonic(4, 3) == Rational(2035, 1728) + + assert harmonic(oo, -1) is S.NaN + assert harmonic(oo, 0) is oo + assert harmonic(oo, S.Half) is oo + assert harmonic(oo, 1) is oo + assert harmonic(oo, 2) == (pi**2)/6 + assert harmonic(oo, 3) == zeta(3) + assert harmonic(oo, Dummy(negative=True)) is S.NaN + ip = Dummy(integer=True, positive=True) + if (1/ip <= 1) is True: #---------------------------------+ + assert None, 'delete this if-block and the next line' #| + ip = Dummy(even=True, positive=True) #--------------------+ + assert harmonic(oo, 1/ip) is oo + assert harmonic(oo, 1 + ip) is zeta(1 + ip) + + assert harmonic(0, m) == 0 + assert harmonic(-1, -1) == 0 + assert harmonic(-1, 0) == -1 + assert harmonic(-1, 1) is S.ComplexInfinity + assert harmonic(-1, 2) is S.NaN + assert harmonic(-3, -2) == -5 + assert harmonic(-3, -3) == 9 + + +def test_harmonic_rational(): + ne = S(6) + no = S(5) + pe = S(8) + po = S(9) + qe = S(10) + qo = S(13) + + Heee = harmonic(ne + pe/qe) + Aeee = (-log(10) + 2*(Rational(-1, 4) + sqrt(5)/4)*log(sqrt(-sqrt(5)/8 + Rational(5, 8))) + + 2*(-sqrt(5)/4 - Rational(1, 4))*log(sqrt(sqrt(5)/8 + Rational(5, 8))) + + pi*sqrt(2*sqrt(5)/5 + 1)/2 + Rational(13944145, 4720968)) + + Heeo = harmonic(ne + pe/qo) + Aeeo = (-log(26) + 2*log(sin(pi*Rational(3, 13)))*cos(pi*Rational(4, 13)) + 2*log(sin(pi*Rational(2, 13)))*cos(pi*Rational(32, 13)) + + 2*log(sin(pi*Rational(5, 13)))*cos(pi*Rational(80, 13)) - 2*log(sin(pi*Rational(6, 13)))*cos(pi*Rational(5, 13)) + - 2*log(sin(pi*Rational(4, 13)))*cos(pi/13) + pi*cot(pi*Rational(5, 13))/2 - 2*log(sin(pi/13))*cos(pi*Rational(3, 13)) + + Rational(2422020029, 702257080)) + + Heoe = harmonic(ne + po/qe) + Aeoe = (-log(20) + 2*(Rational(1, 4) + sqrt(5)/4)*log(Rational(-1, 4) + sqrt(5)/4) + + 2*(Rational(-1, 4) + sqrt(5)/4)*log(sqrt(-sqrt(5)/8 + Rational(5, 8))) + + 2*(-sqrt(5)/4 - Rational(1, 4))*log(sqrt(sqrt(5)/8 + Rational(5, 8))) + + 2*(-sqrt(5)/4 + Rational(1, 4))*log(Rational(1, 4) + sqrt(5)/4) + + Rational(11818877030, 4286604231) + pi*sqrt(2*sqrt(5) + 5)/2) + + Heoo = harmonic(ne + po/qo) + Aeoo = (-log(26) + 2*log(sin(pi*Rational(3, 13)))*cos(pi*Rational(54, 13)) + 2*log(sin(pi*Rational(4, 13)))*cos(pi*Rational(6, 13)) + + 2*log(sin(pi*Rational(6, 13)))*cos(pi*Rational(108, 13)) - 2*log(sin(pi*Rational(5, 13)))*cos(pi/13) + - 2*log(sin(pi/13))*cos(pi*Rational(5, 13)) + pi*cot(pi*Rational(4, 13))/2 + - 2*log(sin(pi*Rational(2, 13)))*cos(pi*Rational(3, 13)) + Rational(11669332571, 3628714320)) + + Hoee = harmonic(no + pe/qe) + Aoee = (-log(10) + 2*(Rational(-1, 4) + sqrt(5)/4)*log(sqrt(-sqrt(5)/8 + Rational(5, 8))) + + 2*(-sqrt(5)/4 - Rational(1, 4))*log(sqrt(sqrt(5)/8 + Rational(5, 8))) + + pi*sqrt(2*sqrt(5)/5 + 1)/2 + Rational(779405, 277704)) + + Hoeo = harmonic(no + pe/qo) + Aoeo = (-log(26) + 2*log(sin(pi*Rational(3, 13)))*cos(pi*Rational(4, 13)) + 2*log(sin(pi*Rational(2, 13)))*cos(pi*Rational(32, 13)) + + 2*log(sin(pi*Rational(5, 13)))*cos(pi*Rational(80, 13)) - 2*log(sin(pi*Rational(6, 13)))*cos(pi*Rational(5, 13)) + - 2*log(sin(pi*Rational(4, 13)))*cos(pi/13) + pi*cot(pi*Rational(5, 13))/2 + - 2*log(sin(pi/13))*cos(pi*Rational(3, 13)) + Rational(53857323, 16331560)) + + Hooe = harmonic(no + po/qe) + Aooe = (-log(20) + 2*(Rational(1, 4) + sqrt(5)/4)*log(Rational(-1, 4) + sqrt(5)/4) + + 2*(Rational(-1, 4) + sqrt(5)/4)*log(sqrt(-sqrt(5)/8 + Rational(5, 8))) + + 2*(-sqrt(5)/4 - Rational(1, 4))*log(sqrt(sqrt(5)/8 + Rational(5, 8))) + + 2*(-sqrt(5)/4 + Rational(1, 4))*log(Rational(1, 4) + sqrt(5)/4) + + Rational(486853480, 186374097) + pi*sqrt(2*sqrt(5) + 5)/2) + + Hooo = harmonic(no + po/qo) + Aooo = (-log(26) + 2*log(sin(pi*Rational(3, 13)))*cos(pi*Rational(54, 13)) + 2*log(sin(pi*Rational(4, 13)))*cos(pi*Rational(6, 13)) + + 2*log(sin(pi*Rational(6, 13)))*cos(pi*Rational(108, 13)) - 2*log(sin(pi*Rational(5, 13)))*cos(pi/13) + - 2*log(sin(pi/13))*cos(pi*Rational(5, 13)) + pi*cot(pi*Rational(4, 13))/2 + - 2*log(sin(pi*Rational(2, 13)))*cos(3*pi/13) + Rational(383693479, 125128080)) + + H = [Heee, Heeo, Heoe, Heoo, Hoee, Hoeo, Hooe, Hooo] + A = [Aeee, Aeeo, Aeoe, Aeoo, Aoee, Aoeo, Aooe, Aooo] + for h, a in zip(H, A): + e = expand_func(h).doit() + assert cancel(e/a) == 1 + assert abs(h.n() - a.n()) < 1e-12 + + +def test_harmonic_evalf(): + assert str(harmonic(1.5).evalf(n=10)) == '1.280372306' + assert str(harmonic(1.5, 2).evalf(n=10)) == '1.154576311' # issue 7443 + assert str(harmonic(4.0, -3).evalf(n=10)) == '100.0000000' + assert str(harmonic(7.0, 1.0).evalf(n=10)) == '2.592857143' + assert str(harmonic(1, pi).evalf(n=10)) == '1.000000000' + assert str(harmonic(2, pi).evalf(n=10)) == '1.113314732' + assert str(harmonic(1000.0, pi).evalf(n=10)) == '1.176241563' + assert str(harmonic(I).evalf(n=10)) == '0.6718659855 + 1.076674047*I' + assert str(harmonic(I, I).evalf(n=10)) == '-0.3970915266 + 1.9629689*I' + + assert harmonic(-1.0, 1).evalf() is S.NaN + assert harmonic(-2.0, 2.0).evalf() is S.NaN + +def test_harmonic_rewrite(): + from sympy.functions.elementary.piecewise import Piecewise + n = Symbol("n") + m = Symbol("m", integer=True, positive=True) + x1 = Symbol("x1", positive=True) + x2 = Symbol("x2", negative=True) + + assert harmonic(n).rewrite(digamma) == polygamma(0, n + 1) + EulerGamma + assert harmonic(n).rewrite(trigamma) == polygamma(0, n + 1) + EulerGamma + assert harmonic(n).rewrite(polygamma) == polygamma(0, n + 1) + EulerGamma + + assert harmonic(n,3).rewrite(polygamma) == polygamma(2, n + 1)/2 - polygamma(2, 1)/2 + assert isinstance(harmonic(n,m).rewrite(polygamma), Piecewise) + + assert expand_func(harmonic(n+4)) == harmonic(n) + 1/(n + 4) + 1/(n + 3) + 1/(n + 2) + 1/(n + 1) + assert expand_func(harmonic(n-4)) == harmonic(n) - 1/(n - 1) - 1/(n - 2) - 1/(n - 3) - 1/n + + assert harmonic(n, m).rewrite("tractable") == harmonic(n, m).rewrite(polygamma) + assert harmonic(n, x1).rewrite("tractable") == harmonic(n, x1) + assert harmonic(n, x1 + 1).rewrite("tractable") == zeta(x1 + 1) - zeta(x1 + 1, n + 1) + assert harmonic(n, x2).rewrite("tractable") == zeta(x2) - zeta(x2, n + 1) + + _k = Dummy("k") + assert harmonic(n).rewrite(Sum).dummy_eq(Sum(1/_k, (_k, 1, n))) + assert harmonic(n, m).rewrite(Sum).dummy_eq(Sum(_k**(-m), (_k, 1, n))) + + +def test_harmonic_calculus(): + y = Symbol("y", positive=True) + z = Symbol("z", negative=True) + assert harmonic(x, 1).limit(x, 0) == 0 + assert harmonic(x, y).limit(x, 0) == 0 + assert harmonic(x, 1).series(x, y, 2) == \ + harmonic(y) + (x - y)*zeta(2, y + 1) + O((x - y)**2, (x, y)) + assert limit(harmonic(x, y), x, oo) == harmonic(oo, y) + assert limit(harmonic(x, y + 1), x, oo) == zeta(y + 1) + assert limit(harmonic(x, y - 1), x, oo) == harmonic(oo, y - 1) + assert limit(harmonic(x, z), x, oo) == Limit(harmonic(x, z), x, oo, dir='-') + assert limit(harmonic(x, z + 1), x, oo) == oo + assert limit(harmonic(x, z + 2), x, oo) == harmonic(oo, z + 2) + assert limit(harmonic(x, z - 1), x, oo) == Limit(harmonic(x, z - 1), x, oo, dir='-') + + +def test_euler(): + assert euler(0) == 1 + assert euler(1) == 0 + assert euler(2) == -1 + assert euler(3) == 0 + assert euler(4) == 5 + assert euler(6) == -61 + assert euler(8) == 1385 + + assert euler(20, evaluate=False) != 370371188237525 + + n = Symbol('n', integer=True) + assert euler(n) != -1 + assert euler(n).subs(n, 2) == -1 + + assert euler(-1) == S.Pi / 2 + assert euler(-1, 1) == 2*log(2) + assert euler(-2).evalf() == (2*S.Catalan).evalf() + assert euler(-3).evalf() == (S.Pi**3 / 16).evalf() + assert str(euler(2.3).evalf(n=10)) == '-1.052850274' + assert str(euler(1.2, 3.4).evalf(n=10)) == '3.575613489' + assert str(euler(I).evalf(n=10)) == '1.248446443 - 0.7675445124*I' + assert str(euler(I, I).evalf(n=10)) == '0.04812930469 + 0.01052411008*I' + + assert euler(20).evalf() == 370371188237525.0 + assert euler(20, evaluate=False).evalf() == 370371188237525.0 + + assert euler(n).rewrite(Sum) == euler(n) + n = Symbol('n', integer=True, nonnegative=True) + assert euler(2*n + 1).rewrite(Sum) == 0 + _j = Dummy('j') + _k = Dummy('k') + assert euler(2*n).rewrite(Sum).dummy_eq( + I*Sum((-1)**_j*2**(-_k)*I**(-_k)*(-2*_j + _k)**(2*n + 1)* + binomial(_k, _j)/_k, (_j, 0, _k), (_k, 1, 2*n + 1))) + + +def test_euler_odd(): + n = Symbol('n', odd=True, positive=True) + assert euler(n) == 0 + n = Symbol('n', odd=True) + assert euler(n) != 0 + + +def test_euler_polynomials(): + assert euler(0, x) == 1 + assert euler(1, x) == x - S.Half + assert euler(2, x) == x**2 - x + assert euler(3, x) == x**3 - (3*x**2)/2 + Rational(1, 4) + m = Symbol('m') + assert isinstance(euler(m, x), euler) + from sympy.core.numbers import Float + A = Float('-0.46237208575048694923364757452876131e8') # from Maple + B = euler(19, S.Pi).evalf(32) + assert abs((A - B)/A) < 1e-31 + + +def test_euler_polynomial_rewrite(): + m = Symbol('m') + A = euler(m, x).rewrite('Sum'); + assert A.subs({m:3, x:5}).doit() == euler(3, 5) + + +def test_catalan(): + n = Symbol('n', integer=True) + m = Symbol('m', integer=True, positive=True) + k = Symbol('k', integer=True, nonnegative=True) + p = Symbol('p', nonnegative=True) + + catalans = [1, 1, 2, 5, 14, 42, 132, 429, 1430, 4862, 16796, 58786] + for i, c in enumerate(catalans): + assert catalan(i) == c + assert catalan(n).rewrite(factorial).subs(n, i) == c + assert catalan(n).rewrite(Product).subs(n, i).doit() == c + + assert unchanged(catalan, x) + assert catalan(2*x).rewrite(binomial) == binomial(4*x, 2*x)/(2*x + 1) + assert catalan(S.Half).rewrite(gamma) == 8/(3*pi) + assert catalan(S.Half).rewrite(factorial).rewrite(gamma) ==\ + 8 / (3 * pi) + assert catalan(3*x).rewrite(gamma) == 4**( + 3*x)*gamma(3*x + S.Half)/(sqrt(pi)*gamma(3*x + 2)) + assert catalan(x).rewrite(hyper) == hyper((-x + 1, -x), (2,), 1) + + assert catalan(n).rewrite(factorial) == factorial(2*n) / (factorial(n + 1) + * factorial(n)) + assert isinstance(catalan(n).rewrite(Product), catalan) + assert isinstance(catalan(m).rewrite(Product), Product) + + assert diff(catalan(x), x) == (polygamma( + 0, x + S.Half) - polygamma(0, x + 2) + log(4))*catalan(x) + + assert catalan(x).evalf() == catalan(x) + c = catalan(S.Half).evalf() + assert str(c) == '0.848826363156775' + c = catalan(I).evalf(3) + assert str((re(c), im(c))) == '(0.398, -0.0209)' + + # Assumptions + assert catalan(p).is_positive is True + assert catalan(k).is_integer is True + assert catalan(m+3).is_composite is True + + +def test_genocchi(): + genocchis = [0, -1, -1, 0, 1, 0, -3, 0, 17] + for n, g in enumerate(genocchis): + assert genocchi(n) == g + + m = Symbol('m', integer=True) + n = Symbol('n', integer=True, positive=True) + assert unchanged(genocchi, m) + assert genocchi(2*n + 1) == 0 + gn = 2 * (1 - 2**n) * bernoulli(n) + assert genocchi(n).rewrite(bernoulli).factor() == gn.factor() + gnx = 2 * (bernoulli(n, x) - 2**n * bernoulli(n, (x+1) / 2)) + assert genocchi(n, x).rewrite(bernoulli).factor() == gnx.factor() + assert genocchi(2 * n).is_odd + assert genocchi(2 * n).is_even is False + assert genocchi(2 * n + 1).is_even + assert genocchi(n).is_integer + assert genocchi(4 * n).is_positive + # these are the only 2 prime Genocchi numbers + assert genocchi(6, evaluate=False).is_prime == S(-3).is_prime + assert genocchi(8, evaluate=False).is_prime + assert genocchi(4 * n + 2).is_negative + assert genocchi(4 * n + 1).is_negative is False + assert genocchi(4 * n - 2).is_negative + + g0 = genocchi(0, evaluate=False) + assert g0.is_positive is False + assert g0.is_negative is False + assert g0.is_even is True + assert g0.is_odd is False + + assert genocchi(0, x) == 0 + assert genocchi(1, x) == -1 + assert genocchi(2, x) == 1 - 2*x + assert genocchi(3, x) == 3*x - 3*x**2 + assert genocchi(4, x) == -1 + 6*x**2 - 4*x**3 + y = Symbol("y") + assert genocchi(5, (x+y)**100) == -5*(x+y)**400 + 10*(x+y)**300 - 5*(x+y)**100 + + assert str(genocchi(5.0, 4.0).evalf(n=10)) == '-660.0000000' + assert str(genocchi(Rational(5, 4)).evalf(n=10)) == '-1.104286457' + assert str(genocchi(-2).evalf(n=10)) == '3.606170709' + assert str(genocchi(1.3, 3.7).evalf(n=10)) == '-1.847375373' + assert str(genocchi(I, 1.0).evalf(n=10)) == '-0.3161917278 - 1.45311955*I' + + n = Symbol('n') + assert genocchi(n, x).rewrite(dirichlet_eta) == -2*n * dirichlet_eta(1-n, x) + + +def test_andre(): + nums = [1, 1, 1, 2, 5, 16, 61, 272, 1385, 7936, 50521] + for n, a in enumerate(nums): + assert andre(n) == a + assert andre(S.Infinity) == S.Infinity + assert andre(-1) == -log(2) + assert andre(-2) == -2*S.Catalan + assert andre(-3) == 3*zeta(3)/16 + assert andre(-5) == -15*zeta(5)/256 + # In fact andre(-2*n) is related to the Dirichlet *beta* function + # at 2*n, but SymPy doesn't implement that (or general L-functions) + assert unchanged(andre, -4) + + n = Symbol('n', integer=True, nonnegative=True) + assert unchanged(andre, n) + assert andre(n).is_integer is True + assert andre(n).is_positive is True + + assert str(andre(10, evaluate=False).evalf(n=10)) == '50521.00000' + assert str(andre(-1, evaluate=False).evalf(n=10)) == '-0.6931471806' + assert str(andre(-2, evaluate=False).evalf(n=10)) == '-1.831931188' + assert str(andre(-4, evaluate=False).evalf(n=10)) == '1.977889103' + assert str(andre(I, evaluate=False).evalf(n=10)) == '2.378417833 + 0.6343322845*I' + + assert andre(x).rewrite(polylog) == \ + (-I)**(x+1) * polylog(-x, I) + I**(x+1) * polylog(-x, -I) + assert andre(x).rewrite(zeta) == \ + 2 * gamma(x+1) / (2*pi)**(x+1) * \ + (zeta(x+1, Rational(1,4)) - cos(pi*x) * zeta(x+1, Rational(3,4))) + + +@nocache_fail +def test_partition(): + partition_nums = [1, 1, 2, 3, 5, 7, 11, 15, 22] + for n, p in enumerate(partition_nums): + assert partition(n) == p + + x = Symbol('x') + y = Symbol('y', real=True) + m = Symbol('m', integer=True) + n = Symbol('n', integer=True, negative=True) + p = Symbol('p', integer=True, nonnegative=True) + assert partition(m).is_integer + assert not partition(m).is_negative + assert partition(m).is_nonnegative + assert partition(n).is_zero + assert partition(p).is_positive + assert partition(x).subs(x, 7) == 15 + assert partition(y).subs(y, 8) == 22 + raises(TypeError, lambda: partition(Rational(5, 4))) + + +def test_divisor_sigma(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: divisor_sigma(m)) + raises(TypeError, lambda: divisor_sigma(4.5)) + raises(TypeError, lambda: divisor_sigma(1, m)) + raises(TypeError, lambda: divisor_sigma(1, 4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: divisor_sigma(m)) + raises(ValueError, lambda: divisor_sigma(0)) + m = Symbol('m', negative=True) + raises(ValueError, lambda: divisor_sigma(1, m)) + raises(ValueError, lambda: divisor_sigma(1, -1)) + + # special case + p = Symbol('p', prime=True) + k = Symbol('k', integer=True) + assert divisor_sigma(p, 1) == p + 1 + assert divisor_sigma(p, k) == p**k + 1 + + # property + n = Symbol('n', integer=True, positive=True) + assert divisor_sigma(n).is_integer is True + assert divisor_sigma(n).is_positive is True + + # symbolic + k = Symbol('k', integer=True, zero=False) + assert divisor_sigma(4, k) == 2**(2*k) + 2**k + 1 + assert divisor_sigma(6, k) == (2**k + 1) * (3**k + 1) + + # Integer + assert divisor_sigma(23450) == 50592 + assert divisor_sigma(23450, 0) == 24 + assert divisor_sigma(23450, 1) == 50592 + assert divisor_sigma(23450, 2) == 730747500 + assert divisor_sigma(23450, 3) == 14666785333344 + + +def test_udivisor_sigma(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: udivisor_sigma(m)) + raises(TypeError, lambda: udivisor_sigma(4.5)) + raises(TypeError, lambda: udivisor_sigma(1, m)) + raises(TypeError, lambda: udivisor_sigma(1, 4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: udivisor_sigma(m)) + raises(ValueError, lambda: udivisor_sigma(0)) + m = Symbol('m', negative=True) + raises(ValueError, lambda: udivisor_sigma(1, m)) + raises(ValueError, lambda: udivisor_sigma(1, -1)) + + # special case + p = Symbol('p', prime=True) + k = Symbol('k', integer=True) + assert udivisor_sigma(p, 1) == p + 1 + assert udivisor_sigma(p, k) == p**k + 1 + + # property + n = Symbol('n', integer=True, positive=True) + assert udivisor_sigma(n).is_integer is True + assert udivisor_sigma(n).is_positive is True + + # Integer + A034444 = [1, 2, 2, 2, 2, 4, 2, 2, 2, 4, 2, 4, 2, 4, 4, 2, 2, 4, 2, 4, + 4, 4, 2, 4, 2, 4, 2, 4, 2, 8, 2, 2, 4, 4, 4, 4, 2, 4, 4, 4, + 2, 8, 2, 4, 4, 4, 2, 4, 2, 4, 4, 4, 2, 4, 4, 4, 4, 4, 2, 8] + for n, val in enumerate(A034444, 1): + assert udivisor_sigma(n, 0) == val + A034448 = [1, 3, 4, 5, 6, 12, 8, 9, 10, 18, 12, 20, 14, 24, 24, 17, 18, + 30, 20, 30, 32, 36, 24, 36, 26, 42, 28, 40, 30, 72, 32, 33, + 48, 54, 48, 50, 38, 60, 56, 54, 42, 96, 44, 60, 60, 72, 48] + for n, val in enumerate(A034448, 1): + assert udivisor_sigma(n, 1) == val + A034676 = [1, 5, 10, 17, 26, 50, 50, 65, 82, 130, 122, 170, 170, 250, + 260, 257, 290, 410, 362, 442, 500, 610, 530, 650, 626, 850, + 730, 850, 842, 1300, 962, 1025, 1220, 1450, 1300, 1394, 1370] + for n, val in enumerate(A034676, 1): + assert udivisor_sigma(n, 2) == val + + +def test_legendre_symbol(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: legendre_symbol(m, 3)) + raises(TypeError, lambda: legendre_symbol(4.5, 3)) + raises(TypeError, lambda: legendre_symbol(1, m)) + raises(TypeError, lambda: legendre_symbol(1, 4.5)) + m = Symbol('m', prime=False) + raises(ValueError, lambda: legendre_symbol(1, m)) + raises(ValueError, lambda: legendre_symbol(1, 6)) + m = Symbol('m', odd=False) + raises(ValueError, lambda: legendre_symbol(1, m)) + raises(ValueError, lambda: legendre_symbol(1, 2)) + + # special case + p = Symbol('p', prime=True) + k = Symbol('k', integer=True) + assert legendre_symbol(p*k, p) == 0 + assert legendre_symbol(1, p) == 1 + + # property + n = Symbol('n') + m = Symbol('m') + assert legendre_symbol(m, n).is_integer is True + assert legendre_symbol(m, n).is_prime is False + + # Integer + assert legendre_symbol(5, 11) == 1 + assert legendre_symbol(25, 41) == 1 + assert legendre_symbol(67, 101) == -1 + assert legendre_symbol(0, 13) == 0 + assert legendre_symbol(9, 3) == 0 + + +def test_jacobi_symbol(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: jacobi_symbol(m, 3)) + raises(TypeError, lambda: jacobi_symbol(4.5, 3)) + raises(TypeError, lambda: jacobi_symbol(1, m)) + raises(TypeError, lambda: jacobi_symbol(1, 4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: jacobi_symbol(1, m)) + raises(ValueError, lambda: jacobi_symbol(1, -6)) + m = Symbol('m', odd=False) + raises(ValueError, lambda: jacobi_symbol(1, m)) + raises(ValueError, lambda: jacobi_symbol(1, 2)) + + # special case + p = Symbol('p', integer=True) + k = Symbol('k', integer=True) + assert jacobi_symbol(p*k, p) == 0 + assert jacobi_symbol(1, p) == 1 + assert jacobi_symbol(1, 1) == 1 + assert jacobi_symbol(0, 1) == 1 + + # property + n = Symbol('n') + m = Symbol('m') + assert jacobi_symbol(m, n).is_integer is True + assert jacobi_symbol(m, n).is_prime is False + + # Integer + assert jacobi_symbol(25, 41) == 1 + assert jacobi_symbol(-23, 83) == -1 + assert jacobi_symbol(3, 9) == 0 + assert jacobi_symbol(42, 97) == -1 + assert jacobi_symbol(3, 5) == -1 + assert jacobi_symbol(7, 9) == 1 + assert jacobi_symbol(0, 3) == 0 + assert jacobi_symbol(0, 1) == 1 + assert jacobi_symbol(2, 1) == 1 + assert jacobi_symbol(1, 3) == 1 + + +def test_kronecker_symbol(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: kronecker_symbol(m, 3)) + raises(TypeError, lambda: kronecker_symbol(4.5, 3)) + raises(TypeError, lambda: kronecker_symbol(1, m)) + raises(TypeError, lambda: kronecker_symbol(1, 4.5)) + + # special case + p = Symbol('p', integer=True) + assert kronecker_symbol(1, p) == 1 + assert kronecker_symbol(1, 1) == 1 + assert kronecker_symbol(0, 1) == 1 + + # property + n = Symbol('n') + m = Symbol('m') + assert kronecker_symbol(m, n).is_integer is True + assert kronecker_symbol(m, n).is_prime is False + + # Integer + for n in range(3, 10, 2): + for a in range(-n, n): + val = kronecker_symbol(a, n) + assert val == jacobi_symbol(a, n) + minus = kronecker_symbol(a, -n) + if a < 0: + assert -minus == val + else: + assert minus == val + even = kronecker_symbol(a, 2 * n) + if a % 2 == 0: + assert even == 0 + elif a % 8 in [1, 7]: + assert even == val + else: + assert -even == val + assert kronecker_symbol(1, 0) == kronecker_symbol(-1, 0) == 1 + assert kronecker_symbol(0, 0) == 0 + + +def test_mobius(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: mobius(m)) + raises(TypeError, lambda: mobius(4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: mobius(m)) + raises(ValueError, lambda: mobius(-3)) + + # special case + p = Symbol('p', prime=True) + assert mobius(p) == -1 + + # property + n = Symbol('n', integer=True, positive=True) + assert mobius(n).is_integer is True + assert mobius(n).is_prime is False + + # symbolic + n = Symbol('n', integer=True, positive=True) + k = Symbol('k', integer=True, positive=True) + assert mobius(n**2) == 0 + assert mobius(4*n) == 0 + assert isinstance(mobius(n**k), mobius) + assert mobius(n**(k+1)) == 0 + assert isinstance(mobius(3**k), mobius) + assert mobius(3**(k+1)) == 0 + m = Symbol('m') + assert isinstance(mobius(4*m), mobius) + + # Integer + assert mobius(13*7) == 1 + assert mobius(1) == 1 + assert mobius(13*7*5) == -1 + assert mobius(13**2) == 0 + A008683 = [1, -1, -1, 0, -1, 1, -1, 0, 0, 1, -1, 0, -1, 1, 1, 0, -1, 0, + -1, 0, 1, 1, -1, 0, 0, 1, 0, 0, -1, -1, -1, 0, 1, 1, 1, 0, -1, + 1, 1, 0, -1, -1, -1, 0, 0, 1, -1, 0, 0, 0, 1, 0, -1, 0, 1, 0] + for n, val in enumerate(A008683, 1): + assert mobius(n) == val + + +def test_primenu(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: primenu(m)) + raises(TypeError, lambda: primenu(4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: primenu(m)) + raises(ValueError, lambda: primenu(0)) + + # special case + p = Symbol('p', prime=True) + assert primenu(p) == 1 + + # property + n = Symbol('n', integer=True, positive=True) + assert primenu(n).is_integer is True + assert primenu(n).is_nonnegative is True + + # Integer + assert primenu(7*13) == 2 + assert primenu(2*17*19) == 3 + assert primenu(2**3 * 17 * 19**2) == 3 + A001221 = [0, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, + 1, 2, 2, 2, 1, 2, 1, 2, 1, 2, 1, 3, 1, 1, 2, 2, 2, 2] + for n, val in enumerate(A001221, 1): + assert primenu(n) == val + + +def test_primeomega(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: primeomega(m)) + raises(TypeError, lambda: primeomega(4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: primeomega(m)) + raises(ValueError, lambda: primeomega(0)) + + # special case + p = Symbol('p', prime=True) + assert primeomega(p) == 1 + + # property + n = Symbol('n', integer=True, positive=True) + assert primeomega(n).is_integer is True + assert primeomega(n).is_nonnegative is True + + # Integer + assert primeomega(7*13) == 2 + assert primeomega(2*17*19) == 3 + assert primeomega(2**3 * 17 * 19**2) == 6 + A001222 = [0, 1, 1, 2, 1, 2, 1, 3, 2, 2, 1, 3, 1, 2, 2, 4, 1, 3, + 1, 3, 2, 2, 1, 4, 2, 2, 3, 3, 1, 3, 1, 5, 2, 2, 2, 4] + for n, val in enumerate(A001222, 1): + assert primeomega(n) == val + + +def test_totient(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: totient(m)) + raises(TypeError, lambda: totient(4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: totient(m)) + raises(ValueError, lambda: totient(0)) + + # special case + p = Symbol('p', prime=True) + assert totient(p) == p - 1 + + # property + n = Symbol('n', integer=True, positive=True) + assert totient(n).is_integer is True + assert totient(n).is_positive is True + + # Integer + assert totient(7*13) == totient(factorint(7*13)) == (7-1)*(13-1) + assert totient(2*17*19) == totient(factorint(2*17*19)) == (17-1)*(19-1) + assert totient(2**3 * 17 * 19**2) == totient({2: 3, 17: 1, 19: 2}) == 2**2 * (17-1) * 19*(19-1) + A000010 = [1, 1, 2, 2, 4, 2, 6, 4, 6, 4, 10, 4, 12, 6, 8, 8, 16, + 6, 18, 8, 12, 10, 22, 8, 20, 12, 18, 12, 28, 8, 30, 16, + 20, 16, 24, 12, 36, 18, 24, 16, 40, 12, 42, 20, 24, 22] + for n, val in enumerate(A000010, 1): + assert totient(n) == val + + +def test_reduced_totient(): + # error + m = Symbol('m', integer=False) + raises(TypeError, lambda: reduced_totient(m)) + raises(TypeError, lambda: reduced_totient(4.5)) + m = Symbol('m', positive=False) + raises(ValueError, lambda: reduced_totient(m)) + raises(ValueError, lambda: reduced_totient(0)) + + # special case + p = Symbol('p', prime=True) + assert reduced_totient(p) == p - 1 + + # property + n = Symbol('n', integer=True, positive=True) + assert reduced_totient(n).is_integer is True + assert reduced_totient(n).is_positive is True + + # Integer + assert reduced_totient(7*13) == reduced_totient(factorint(7*13)) == 12 + assert reduced_totient(2*17*19) == reduced_totient(factorint(2*17*19)) == 144 + assert reduced_totient(2**2 * 11) == reduced_totient({2: 2, 11: 1}) == 10 + assert reduced_totient(2**3 * 17 * 19**2) == reduced_totient({2: 3, 17: 1, 19: 2}) == 2736 + A002322 = [1, 1, 2, 2, 4, 2, 6, 2, 6, 4, 10, 2, 12, 6, 4, 4, 16, 6, + 18, 4, 6, 10, 22, 2, 20, 12, 18, 6, 28, 4, 30, 8, 10, 16, + 12, 6, 36, 18, 12, 4, 40, 6, 42, 10, 12, 22, 46, 4, 42] + for n, val in enumerate(A002322, 1): + assert reduced_totient(n) == val + + +def test_primepi(): + # error + z = Symbol('z', real=False) + raises(TypeError, lambda: primepi(z)) + raises(TypeError, lambda: primepi(I)) + + # property + n = Symbol('n', integer=True, positive=True) + assert primepi(n).is_integer is True + assert primepi(n).is_nonnegative is True + + # infinity + assert primepi(oo) == oo + assert primepi(-oo) == 0 + + # symbol + x = Symbol('x') + assert isinstance(primepi(x), primepi) + + # Integer + assert primepi(0) == 0 + A000720 = [0, 1, 2, 2, 3, 3, 4, 4, 4, 4, 5, 5, 6, 6, 6, 6, 7, 7, 8, + 8, 8, 8, 9, 9, 9, 9, 9, 9, 10, 10, 11, 11, 11, 11, 11, 11, + 12, 12, 12, 12, 13, 13, 14, 14, 14, 14, 15, 15, 15, 15] + for n, val in enumerate(A000720, 1): + assert primepi(n) == primepi(n + 0.5) == val + + +def test__nT(): + assert [_nT(i, j) for i in range(5) for j in range(i + 2)] == [ + 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 2, 1, 1, 0] + check = [_nT(10, i) for i in range(11)] + assert check == [0, 1, 5, 8, 9, 7, 5, 3, 2, 1, 1] + assert all(type(i) is int for i in check) + assert _nT(10, 5) == 7 + assert _nT(100, 98) == 2 + assert _nT(100, 100) == 1 + assert _nT(10, 3) == 8 + + +def test_nC_nP_nT(): + from sympy.utilities.iterables import ( + multiset_permutations, multiset_combinations, multiset_partitions, + partitions, subsets, permutations) + from sympy.functions.combinatorial.numbers import ( + nP, nC, nT, stirling, _stirling1, _stirling2, _multiset_histogram, _AOP_product) + + from sympy.combinatorics.permutations import Permutation + from sympy.core.random import choice + + c = string.ascii_lowercase + for i in range(100): + s = ''.join(choice(c) for i in range(7)) + u = len(s) == len(set(s)) + try: + tot = 0 + for i in range(8): + check = nP(s, i) + tot += check + assert len(list(multiset_permutations(s, i))) == check + if u: + assert nP(len(s), i) == check + assert nP(s) == tot + except AssertionError: + print(s, i, 'failed perm test') + raise ValueError() + + for i in range(100): + s = ''.join(choice(c) for i in range(7)) + u = len(s) == len(set(s)) + try: + tot = 0 + for i in range(8): + check = nC(s, i) + tot += check + assert len(list(multiset_combinations(s, i))) == check + if u: + assert nC(len(s), i) == check + assert nC(s) == tot + if u: + assert nC(len(s)) == tot + except AssertionError: + print(s, i, 'failed combo test') + raise ValueError() + + for i in range(1, 10): + tot = 0 + for j in range(1, i + 2): + check = nT(i, j) + assert check.is_Integer + tot += check + assert sum(1 for p in partitions(i, j, size=True) if p[0] == j) == check + assert nT(i) == tot + + for i in range(1, 10): + tot = 0 + for j in range(1, i + 2): + check = nT(range(i), j) + tot += check + assert len(list(multiset_partitions(list(range(i)), j))) == check + assert nT(range(i)) == tot + + for i in range(100): + s = ''.join(choice(c) for i in range(7)) + u = len(s) == len(set(s)) + try: + tot = 0 + for i in range(1, 8): + check = nT(s, i) + tot += check + assert len(list(multiset_partitions(s, i))) == check + if u: + assert nT(range(len(s)), i) == check + if u: + assert nT(range(len(s))) == tot + assert nT(s) == tot + except AssertionError: + print(s, i, 'failed partition test') + raise ValueError() + + # tests for Stirling numbers of the first kind that are not tested in the + # above + assert [stirling(9, i, kind=1) for i in range(11)] == [ + 0, 40320, 109584, 118124, 67284, 22449, 4536, 546, 36, 1, 0] + perms = list(permutations(range(4))) + assert [sum(1 for p in perms if Permutation(p).cycles == i) + for i in range(5)] == [0, 6, 11, 6, 1] == [ + stirling(4, i, kind=1) for i in range(5)] + # http://oeis.org/A008275 + assert [stirling(n, k, signed=1) + for n in range(10) for k in range(1, n + 1)] == [ + 1, -1, + 1, 2, -3, + 1, -6, 11, -6, + 1, 24, -50, 35, -10, + 1, -120, 274, -225, 85, -15, + 1, 720, -1764, 1624, -735, 175, -21, + 1, -5040, 13068, -13132, 6769, -1960, 322, -28, + 1, 40320, -109584, 118124, -67284, 22449, -4536, 546, -36, 1] + # https://en.wikipedia.org/wiki/Stirling_numbers_of_the_first_kind + assert [stirling(n, k, kind=1) + for n in range(10) for k in range(n+1)] == [ + 1, + 0, 1, + 0, 1, 1, + 0, 2, 3, 1, + 0, 6, 11, 6, 1, + 0, 24, 50, 35, 10, 1, + 0, 120, 274, 225, 85, 15, 1, + 0, 720, 1764, 1624, 735, 175, 21, 1, + 0, 5040, 13068, 13132, 6769, 1960, 322, 28, 1, + 0, 40320, 109584, 118124, 67284, 22449, 4536, 546, 36, 1] + # https://en.wikipedia.org/wiki/Stirling_numbers_of_the_second_kind + assert [stirling(n, k, kind=2) + for n in range(10) for k in range(n+1)] == [ + 1, + 0, 1, + 0, 1, 1, + 0, 1, 3, 1, + 0, 1, 7, 6, 1, + 0, 1, 15, 25, 10, 1, + 0, 1, 31, 90, 65, 15, 1, + 0, 1, 63, 301, 350, 140, 21, 1, + 0, 1, 127, 966, 1701, 1050, 266, 28, 1, + 0, 1, 255, 3025, 7770, 6951, 2646, 462, 36, 1] + assert stirling(3, 4, kind=1) == stirling(3, 4, kind=1) == 0 + raises(ValueError, lambda: stirling(-2, 2)) + + # Assertion that the return type is SymPy Integer. + assert isinstance(_stirling1(6, 3), Integer) + assert isinstance(_stirling2(6, 3), Integer) + + def delta(p): + if len(p) == 1: + return oo + return min(abs(i[0] - i[1]) for i in subsets(p, 2)) + parts = multiset_partitions(range(5), 3) + d = 2 + assert (sum(1 for p in parts if all(delta(i) >= d for i in p)) == + stirling(5, 3, d=d) == 7) + + # other coverage tests + assert nC('abb', 2) == nC('aab', 2) == 2 + assert nP(3, 3, replacement=True) == nP('aabc', 3, replacement=True) == 27 + assert nP(3, 4) == 0 + assert nP('aabc', 5) == 0 + assert nC(4, 2, replacement=True) == nC('abcdd', 2, replacement=True) == \ + len(list(multiset_combinations('aabbccdd', 2))) == 10 + assert nC('abcdd') == sum(nC('abcdd', i) for i in range(6)) == 24 + assert nC(list('abcdd'), 4) == 4 + assert nT('aaaa') == nT(4) == len(list(partitions(4))) == 5 + assert nT('aaab') == len(list(multiset_partitions('aaab'))) == 7 + assert nC('aabb'*3, 3) == 4 # aaa, bbb, abb, baa + assert dict(_AOP_product((4,1,1,1))) == { + 0: 1, 1: 4, 2: 7, 3: 8, 4: 8, 5: 7, 6: 4, 7: 1} + # the following was the first t that showed a problem in a previous form of + # the function, so it's not as random as it may appear + t = (3, 9, 4, 6, 6, 5, 5, 2, 10, 4) + assert sum(_AOP_product(t)[i] for i in range(55)) == 58212000 + raises(ValueError, lambda: _multiset_histogram({1:'a'})) + + +def test_PR_14617(): + from sympy.functions.combinatorial.numbers import nT + for n in (0, []): + for k in (-1, 0, 1): + if k == 0: + assert nT(n, k) == 1 + else: + assert nT(n, k) == 0 + + +def test_issue_8496(): + n = Symbol("n") + k = Symbol("k") + + raises(TypeError, lambda: catalan(n, k)) + + +def test_issue_8601(): + n = Symbol('n', integer=True, negative=True) + + assert catalan(n - 1) is S.Zero + assert catalan(Rational(-1, 2)) is S.ComplexInfinity + assert catalan(-S.One) == Rational(-1, 2) + c1 = catalan(-5.6).evalf() + assert str(c1) == '6.93334070531408e-5' + c2 = catalan(-35.4).evalf() + assert str(c2) == '-4.14189164517449e-24' + + +def test_motzkin(): + assert motzkin.is_motzkin(4) == True + assert motzkin.is_motzkin(9) == True + assert motzkin.is_motzkin(10) == False + assert motzkin.find_motzkin_numbers_in_range(10,200) == [21, 51, 127] + assert motzkin.find_motzkin_numbers_in_range(10,400) == [21, 51, 127, 323] + assert motzkin.find_motzkin_numbers_in_range(10,1600) == [21, 51, 127, 323, 835] + assert motzkin.find_first_n_motzkins(5) == [1, 1, 2, 4, 9] + assert motzkin.find_first_n_motzkins(7) == [1, 1, 2, 4, 9, 21, 51] + assert motzkin.find_first_n_motzkins(10) == [1, 1, 2, 4, 9, 21, 51, 127, 323, 835] + raises(ValueError, lambda: motzkin.eval(77.58)) + raises(ValueError, lambda: motzkin.eval(-8)) + raises(ValueError, lambda: motzkin.find_motzkin_numbers_in_range(-2,7)) + raises(ValueError, lambda: motzkin.find_motzkin_numbers_in_range(13,7)) + raises(ValueError, lambda: motzkin.find_first_n_motzkins(112.8)) + + +def test_nD_derangements(): + from sympy.utilities.iterables import (partitions, multiset, + multiset_derangements, multiset_permutations) + from sympy.functions.combinatorial.numbers import nD + + got = [] + for i in partitions(8, k=4): + s = [] + it = 0 + for k, v in i.items(): + for i in range(v): + s.extend([it]*k) + it += 1 + ms = multiset(s) + c1 = sum(1 for i in multiset_permutations(s) if + all(i != j for i, j in zip(i, s))) + assert c1 == nD(ms) == nD(ms, 0) == nD(ms, 1) + v = [tuple(i) for i in multiset_derangements(s)] + c2 = len(v) + assert c2 == len(set(v)) + assert c1 == c2 + got.append(c1) + assert got == [1, 4, 6, 12, 24, 24, 61, 126, 315, 780, 297, 772, + 2033, 5430, 14833] + + assert nD('1112233456', brute=True) == nD('1112233456') == 16356 + assert nD('') == nD([]) == nD({}) == 0 + assert nD({1: 0}) == 0 + raises(ValueError, lambda: nD({1: -1})) + assert nD('112') == 0 + assert nD(i='112') == 0 + assert [nD(n=i) for i in range(6)] == [0, 0, 1, 2, 9, 44] + assert nD((i for i in range(4))) == nD('0123') == 9 + assert nD(m=(i for i in range(4))) == 3 + assert nD(m={0: 1, 1: 1, 2: 1, 3: 1}) == 3 + assert nD(m=[0, 1, 2, 3]) == 3 + raises(TypeError, lambda: nD(m=0)) + raises(TypeError, lambda: nD(-1)) + assert nD({-1: 1, -2: 1}) == 1 + assert nD(m={0: 3}) == 0 + raises(ValueError, lambda: nD(i='123', n=3)) + raises(ValueError, lambda: nD(i='123', m=(1,2))) + raises(ValueError, lambda: nD(n=0, m=(1,2))) + raises(ValueError, lambda: nD({1: -1})) + raises(ValueError, lambda: nD(m={-1: 1, 2: 1})) + raises(ValueError, lambda: nD(m={1: -1, 2: 1})) + raises(ValueError, lambda: nD(m=[-1, 2])) + raises(TypeError, lambda: nD({1: x})) + raises(TypeError, lambda: nD(m={1: x})) + raises(TypeError, lambda: nD(m={x: 1})) + + +def test_deprecated_ntheory_symbolic_functions(): + from sympy.testing.pytest import warns_deprecated_sympy + + with warns_deprecated_sympy(): + assert not carmichael.is_carmichael(3) + with warns_deprecated_sympy(): + assert carmichael.find_carmichael_numbers_in_range(10, 20) == [] + with warns_deprecated_sympy(): + assert carmichael.find_first_n_carmichaels(1) diff --git a/lib/python3.12/site-packages/sympy/functions/special/__pycache__/elliptic_integrals.cpython-312.pyc b/lib/python3.12/site-packages/sympy/functions/special/__pycache__/elliptic_integrals.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..4e37dce9f8fb141330696428a5a9c566b0acd0bd Binary files /dev/null and b/lib/python3.12/site-packages/sympy/functions/special/__pycache__/elliptic_integrals.cpython-312.pyc differ diff --git a/lib/python3.12/site-packages/sympy/series/__init__.py b/lib/python3.12/site-packages/sympy/series/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..953653e21856b82bc0b708ccd922efb728a084ed --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/__init__.py @@ -0,0 +1,23 @@ +"""A module that handles series: find a limit, order the series etc. +""" +from .order import Order +from .limits import limit, Limit +from .gruntz import gruntz +from .series import series +from .approximants import approximants +from .residues import residue +from .sequences import SeqPer, SeqFormula, sequence, SeqAdd, SeqMul +from .fourier import fourier_series +from .formal import fps +from .limitseq import difference_delta, limit_seq + +from sympy.core.singleton import S +EmptySequence = S.EmptySequence + +O = Order + +__all__ = ['Order', 'O', 'limit', 'Limit', 'gruntz', 'series', 'approximants', + 'residue', 'EmptySequence', 'SeqPer', 'SeqFormula', 'sequence', + 'SeqAdd', 'SeqMul', 'fourier_series', 'fps', 'difference_delta', + 'limit_seq' + ] diff --git a/lib/python3.12/site-packages/sympy/series/__pycache__/__init__.cpython-312.pyc b/lib/python3.12/site-packages/sympy/series/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..f644d19db549604a21487320f139b309443736e4 Binary files /dev/null and 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b/lib/python3.12/site-packages/sympy/series/acceleration.py @@ -0,0 +1,101 @@ +""" +Convergence acceleration / extrapolation methods for series and +sequences. + +References: +Carl M. Bender & Steven A. Orszag, "Advanced Mathematical Methods for +Scientists and Engineers: Asymptotic Methods and Perturbation Theory", +Springer 1999. (Shanks transformation: pp. 368-375, Richardson +extrapolation: pp. 375-377.) +""" + +from sympy.core.numbers import Integer +from sympy.core.singleton import S +from sympy.functions.combinatorial.factorials import factorial + + +def richardson(A, k, n, N): + """ + Calculate an approximation for lim k->oo A(k) using Richardson + extrapolation with the terms A(n), A(n+1), ..., A(n+N+1). + Choosing N ~= 2*n often gives good results. + + Examples + ======== + + A simple example is to calculate exp(1) using the limit definition. + This limit converges slowly; n = 100 only produces two accurate + digits: + + >>> from sympy.abc import n + >>> e = (1 + 1/n)**n + >>> print(round(e.subs(n, 100).evalf(), 10)) + 2.7048138294 + + Richardson extrapolation with 11 appropriately chosen terms gives + a value that is accurate to the indicated precision: + + >>> from sympy import E + >>> from sympy.series.acceleration import richardson + >>> print(round(richardson(e, n, 10, 20).evalf(), 10)) + 2.7182818285 + >>> print(round(E.evalf(), 10)) + 2.7182818285 + + Another useful application is to speed up convergence of series. + Computing 100 terms of the zeta(2) series 1/k**2 yields only + two accurate digits: + + >>> from sympy.abc import k, n + >>> from sympy import Sum + >>> A = Sum(k**-2, (k, 1, n)) + >>> print(round(A.subs(n, 100).evalf(), 10)) + 1.6349839002 + + Richardson extrapolation performs much better: + + >>> from sympy import pi + >>> print(round(richardson(A, n, 10, 20).evalf(), 10)) + 1.6449340668 + >>> print(round(((pi**2)/6).evalf(), 10)) # Exact value + 1.6449340668 + + """ + s = S.Zero + for j in range(0, N + 1): + s += (A.subs(k, Integer(n + j)).doit() * (n + j)**N * + S.NegativeOne**(j + N) / (factorial(j) * factorial(N - j))) + return s + + +def shanks(A, k, n, m=1): + """ + Calculate an approximation for lim k->oo A(k) using the n-term Shanks + transformation S(A)(n). With m > 1, calculate the m-fold recursive + Shanks transformation S(S(...S(A)...))(n). + + The Shanks transformation is useful for summing Taylor series that + converge slowly near a pole or singularity, e.g. for log(2): + + >>> from sympy.abc import k, n + >>> from sympy import Sum, Integer + >>> from sympy.series.acceleration import shanks + >>> A = Sum(Integer(-1)**(k+1) / k, (k, 1, n)) + >>> print(round(A.subs(n, 100).doit().evalf(), 10)) + 0.6881721793 + >>> print(round(shanks(A, n, 25).evalf(), 10)) + 0.6931396564 + >>> print(round(shanks(A, n, 25, 5).evalf(), 10)) + 0.6931471806 + + The correct value is 0.6931471805599453094172321215. + """ + table = [A.subs(k, Integer(j)).doit() for j in range(n + m + 2)] + table2 = table[:] + + for i in range(1, m + 1): + for j in range(i, n + m + 1): + x, y, z = table[j - 1], table[j], table[j + 1] + table2[j] = (z*x - y**2) / (z + x - 2*y) + table = table2[:] + return table[n] diff --git a/lib/python3.12/site-packages/sympy/series/approximants.py b/lib/python3.12/site-packages/sympy/series/approximants.py new file mode 100644 index 0000000000000000000000000000000000000000..3d54ce41bc7367606ae6260f8e9ac00149cedc0f --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/approximants.py @@ -0,0 +1,103 @@ +from sympy.core.singleton import S +from sympy.core.symbol import Symbol +from sympy.polys.polytools import lcm +from sympy.utilities import public + +@public +def approximants(l, X=Symbol('x'), simplify=False): + """ + Return a generator for consecutive Pade approximants for a series. + It can also be used for computing the rational generating function of a + series when possible, since the last approximant returned by the generator + will be the generating function (if any). + + Explanation + =========== + + The input list can contain more complex expressions than integer or rational + numbers; symbols may also be involved in the computation. An example below + show how to compute the generating function of the whole Pascal triangle. + + The generator can be asked to apply the sympy.simplify function on each + generated term, which will make the computation slower; however it may be + useful when symbols are involved in the expressions. + + Examples + ======== + + >>> from sympy.series import approximants + >>> from sympy import lucas, fibonacci, symbols, binomial + >>> g = [lucas(k) for k in range(16)] + >>> [e for e in approximants(g)] + [2, -4/(x - 2), (5*x - 2)/(3*x - 1), (x - 2)/(x**2 + x - 1)] + + >>> h = [fibonacci(k) for k in range(16)] + >>> [e for e in approximants(h)] + [x, -x/(x - 1), (x**2 - x)/(2*x - 1), -x/(x**2 + x - 1)] + + >>> x, t = symbols("x,t") + >>> p=[sum(binomial(k,i)*x**i for i in range(k+1)) for k in range(16)] + >>> y = approximants(p, t) + >>> for k in range(3): print(next(y)) + 1 + (x + 1)/((-x - 1)*(t*(x + 1) + (x + 1)/(-x - 1))) + nan + + >>> y = approximants(p, t, simplify=True) + >>> for k in range(3): print(next(y)) + 1 + -1/(t*(x + 1) - 1) + nan + + See Also + ======== + + sympy.concrete.guess.guess_generating_function_rational + mpmath.pade + """ + from sympy.simplify import simplify as simp + from sympy.simplify.radsimp import denom + p1, q1 = [S.One], [S.Zero] + p2, q2 = [S.Zero], [S.One] + while len(l): + b = 0 + while l[b]==0: + b += 1 + if b == len(l): + return + m = [S.One/l[b]] + for k in range(b+1, len(l)): + s = 0 + for j in range(b, k): + s -= l[j+1] * m[b-j-1] + m.append(s/l[b]) + l = m + a, l[0] = l[0], 0 + p = [0] * max(len(p2), b+len(p1)) + q = [0] * max(len(q2), b+len(q1)) + for k in range(len(p2)): + p[k] = a*p2[k] + for k in range(b, b+len(p1)): + p[k] += p1[k-b] + for k in range(len(q2)): + q[k] = a*q2[k] + for k in range(b, b+len(q1)): + q[k] += q1[k-b] + while p[-1]==0: p.pop() + while q[-1]==0: q.pop() + p1, p2 = p2, p + q1, q2 = q2, q + + # yield result + c = 1 + for x in p: + c = lcm(c, denom(x)) + for x in q: + c = lcm(c, denom(x)) + out = ( sum(c*e*X**k for k, e in enumerate(p)) + / sum(c*e*X**k for k, e in enumerate(q)) ) + if simplify: + yield(simp(out)) + else: + yield out + return diff --git a/lib/python3.12/site-packages/sympy/series/aseries.py b/lib/python3.12/site-packages/sympy/series/aseries.py new file mode 100644 index 0000000000000000000000000000000000000000..dbbe0664e6d43a9329f37789c16c48143eda5413 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/aseries.py @@ -0,0 +1,10 @@ +from sympy.core.sympify import sympify + + +def aseries(expr, x=None, n=6, bound=0, hir=False): + """ + See the docstring of Expr.aseries() for complete details of this wrapper. + + """ + expr = sympify(expr) + return expr.aseries(x, n, bound, hir) diff --git a/lib/python3.12/site-packages/sympy/series/benchmarks/__init__.py b/lib/python3.12/site-packages/sympy/series/benchmarks/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git 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b/lib/python3.12/site-packages/sympy/series/benchmarks/__pycache__/bench_order.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..eaf299b5b4b84e4fde4b24f9ff3726345e2ab9a1 Binary files /dev/null and b/lib/python3.12/site-packages/sympy/series/benchmarks/__pycache__/bench_order.cpython-312.pyc differ diff --git a/lib/python3.12/site-packages/sympy/series/benchmarks/bench_limit.py b/lib/python3.12/site-packages/sympy/series/benchmarks/bench_limit.py new file mode 100644 index 0000000000000000000000000000000000000000..eafc28328848dad4b3ea433537971f5785253afe --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/benchmarks/bench_limit.py @@ -0,0 +1,9 @@ +from sympy.core.numbers import oo +from sympy.core.symbol import Symbol +from sympy.series.limits import limit + +x = Symbol('x') + + +def timeit_limit_1x(): + limit(1/x, x, oo) diff --git a/lib/python3.12/site-packages/sympy/series/benchmarks/bench_order.py b/lib/python3.12/site-packages/sympy/series/benchmarks/bench_order.py new file mode 100644 index 0000000000000000000000000000000000000000..1c85fa173dfc2a478792de8ab816c23ba9d408ef --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/benchmarks/bench_order.py @@ -0,0 +1,10 @@ +from sympy.core.add import Add +from sympy.core.symbol import Symbol +from sympy.series.order import O + +x = Symbol('x') +l = [x**i for i in range(1000)] +l.append(O(x**1001)) + +def timeit_order_1x(): + Add(*l) diff --git a/lib/python3.12/site-packages/sympy/series/formal.py b/lib/python3.12/site-packages/sympy/series/formal.py new file mode 100644 index 0000000000000000000000000000000000000000..5ad724b21455d3e233c22192e10d7d52d161554c --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/formal.py @@ -0,0 +1,1869 @@ +"""Formal Power Series""" + +from collections import defaultdict + +from sympy.core.numbers import (nan, oo, zoo) +from sympy.core.add import Add +from sympy.core.expr import Expr +from sympy.core.function import Derivative, Function, expand +from sympy.core.mul import Mul +from sympy.core.numbers import Rational +from sympy.core.relational import Eq +from sympy.sets.sets import Interval +from sympy.core.singleton import S +from sympy.core.symbol import Wild, Dummy, symbols, Symbol +from sympy.core.sympify import sympify +from sympy.discrete.convolutions import convolution +from sympy.functions.combinatorial.factorials import binomial, factorial, rf +from sympy.functions.combinatorial.numbers import bell +from sympy.functions.elementary.integers import floor, frac, ceiling +from sympy.functions.elementary.miscellaneous import Min, Max +from sympy.functions.elementary.piecewise import Piecewise +from sympy.series.limits import Limit +from sympy.series.order import Order +from sympy.series.sequences import sequence +from sympy.series.series_class import SeriesBase +from sympy.utilities.iterables import iterable + + + +def rational_algorithm(f, x, k, order=4, full=False): + """ + Rational algorithm for computing + formula of coefficients of Formal Power Series + of a function. + + Explanation + =========== + + Applicable when f(x) or some derivative of f(x) + is a rational function in x. + + :func:`rational_algorithm` uses :func:`~.apart` function for partial fraction + decomposition. :func:`~.apart` by default uses 'undetermined coefficients + method'. By setting ``full=True``, 'Bronstein's algorithm' can be used + instead. + + Looks for derivative of a function up to 4'th order (by default). + This can be overridden using order option. + + Parameters + ========== + + x : Symbol + order : int, optional + Order of the derivative of ``f``, Default is 4. + full : bool + + Returns + ======= + + formula : Expr + ind : Expr + Independent terms. + order : int + full : bool + + Examples + ======== + + >>> from sympy import log, atan + >>> from sympy.series.formal import rational_algorithm as ra + >>> from sympy.abc import x, k + + >>> ra(1 / (1 - x), x, k) + (1, 0, 0) + >>> ra(log(1 + x), x, k) + (-1/((-1)**k*k), 0, 1) + + >>> ra(atan(x), x, k, full=True) + ((-I/(2*(-I)**k) + I/(2*I**k))/k, 0, 1) + + Notes + ===== + + By setting ``full=True``, range of admissible functions to be solved using + ``rational_algorithm`` can be increased. This option should be used + carefully as it can significantly slow down the computation as ``doit`` is + performed on the :class:`~.RootSum` object returned by the :func:`~.apart` + function. Use ``full=False`` whenever possible. + + See Also + ======== + + sympy.polys.partfrac.apart + + References + ========== + + .. [1] Formal Power Series - Dominik Gruntz, Wolfram Koepf + .. [2] Power Series in Computer Algebra - Wolfram Koepf + + """ + from sympy.polys import RootSum, apart + from sympy.integrals import integrate + + diff = f + ds = [] # list of diff + + for i in range(order + 1): + if i: + diff = diff.diff(x) + + if diff.is_rational_function(x): + coeff, sep = S.Zero, S.Zero + + terms = apart(diff, x, full=full) + if terms.has(RootSum): + terms = terms.doit() + + for t in Add.make_args(terms): + num, den = t.as_numer_denom() + if not den.has(x): + sep += t + else: + if isinstance(den, Mul): + # m*(n*x - a)**j -> (n*x - a)**j + ind = den.as_independent(x) + den = ind[1] + num /= ind[0] + + # (n*x - a)**j -> (x - b) + den, j = den.as_base_exp() + a, xterm = den.as_coeff_add(x) + + # term -> m/x**n + if not a: + sep += t + continue + + xc = xterm[0].coeff(x) + a /= -xc + num /= xc**j + + ak = ((-1)**j * num * + binomial(j + k - 1, k).rewrite(factorial) / + a**(j + k)) + coeff += ak + + # Hacky, better way? + if coeff.is_zero: + return None + if (coeff.has(x) or coeff.has(zoo) or coeff.has(oo) or + coeff.has(nan)): + return None + + for j in range(i): + coeff = (coeff / (k + j + 1)) + sep = integrate(sep, x) + sep += (ds.pop() - sep).limit(x, 0) # constant of integration + return (coeff.subs(k, k - i), sep, i) + + else: + ds.append(diff) + + return None + + +def rational_independent(terms, x): + """ + Returns a list of all the rationally independent terms. + + Examples + ======== + + >>> from sympy import sin, cos + >>> from sympy.series.formal import rational_independent + >>> from sympy.abc import x + + >>> rational_independent([cos(x), sin(x)], x) + [cos(x), sin(x)] + >>> rational_independent([x**2, sin(x), x*sin(x), x**3], x) + [x**3 + x**2, x*sin(x) + sin(x)] + """ + if not terms: + return [] + + ind = terms[0:1] + + for t in terms[1:]: + n = t.as_independent(x)[1] + for i, term in enumerate(ind): + d = term.as_independent(x)[1] + q = (n / d).cancel() + if q.is_rational_function(x): + ind[i] += t + break + else: + ind.append(t) + return ind + + +def simpleDE(f, x, g, order=4): + r""" + Generates simple DE. + + Explanation + =========== + + DE is of the form + + .. math:: + f^k(x) + \sum\limits_{j=0}^{k-1} A_j f^j(x) = 0 + + where :math:`A_j` should be rational function in x. + + Generates DE's upto order 4 (default). DE's can also have free parameters. + + By increasing order, higher order DE's can be found. + + Yields a tuple of (DE, order). + """ + from sympy.solvers.solveset import linsolve + + a = symbols('a:%d' % (order)) + + def _makeDE(k): + eq = f.diff(x, k) + Add(*[a[i]*f.diff(x, i) for i in range(0, k)]) + DE = g(x).diff(x, k) + Add(*[a[i]*g(x).diff(x, i) for i in range(0, k)]) + return eq, DE + + found = False + for k in range(1, order + 1): + eq, DE = _makeDE(k) + eq = eq.expand() + terms = eq.as_ordered_terms() + ind = rational_independent(terms, x) + if found or len(ind) == k: + sol = dict(zip(a, (i for s in linsolve(ind, a[:k]) for i in s))) + if sol: + found = True + DE = DE.subs(sol) + DE = DE.as_numer_denom()[0] + DE = DE.factor().as_coeff_mul(Derivative)[1][0] + yield DE.collect(Derivative(g(x))), k + + +def exp_re(DE, r, k): + """Converts a DE with constant coefficients (explike) into a RE. + + Explanation + =========== + + Performs the substitution: + + .. math:: + f^j(x) \\to r(k + j) + + Normalises the terms so that lowest order of a term is always r(k). + + Examples + ======== + + >>> from sympy import Function, Derivative + >>> from sympy.series.formal import exp_re + >>> from sympy.abc import x, k + >>> f, r = Function('f'), Function('r') + + >>> exp_re(-f(x) + Derivative(f(x)), r, k) + -r(k) + r(k + 1) + >>> exp_re(Derivative(f(x), x) + Derivative(f(x), (x, 2)), r, k) + r(k) + r(k + 1) + + See Also + ======== + + sympy.series.formal.hyper_re + """ + RE = S.Zero + + g = DE.atoms(Function).pop() + + mini = None + for t in Add.make_args(DE): + coeff, d = t.as_independent(g) + if isinstance(d, Derivative): + j = d.derivative_count + else: + j = 0 + if mini is None or j < mini: + mini = j + RE += coeff * r(k + j) + if mini: + RE = RE.subs(k, k - mini) + return RE + + +def hyper_re(DE, r, k): + """ + Converts a DE into a RE. + + Explanation + =========== + + Performs the substitution: + + .. math:: + x^l f^j(x) \\to (k + 1 - l)_j . a_{k + j - l} + + Normalises the terms so that lowest order of a term is always r(k). + + Examples + ======== + + >>> from sympy import Function, Derivative + >>> from sympy.series.formal import hyper_re + >>> from sympy.abc import x, k + >>> f, r = Function('f'), Function('r') + + >>> hyper_re(-f(x) + Derivative(f(x)), r, k) + (k + 1)*r(k + 1) - r(k) + >>> hyper_re(-x*f(x) + Derivative(f(x), (x, 2)), r, k) + (k + 2)*(k + 3)*r(k + 3) - r(k) + + See Also + ======== + + sympy.series.formal.exp_re + """ + RE = S.Zero + + g = DE.atoms(Function).pop() + x = g.atoms(Symbol).pop() + + mini = None + for t in Add.make_args(DE.expand()): + coeff, d = t.as_independent(g) + c, v = coeff.as_independent(x) + l = v.as_coeff_exponent(x)[1] + if isinstance(d, Derivative): + j = d.derivative_count + else: + j = 0 + RE += c * rf(k + 1 - l, j) * r(k + j - l) + if mini is None or j - l < mini: + mini = j - l + + RE = RE.subs(k, k - mini) + + m = Wild('m') + return RE.collect(r(k + m)) + + +def _transformation_a(f, x, P, Q, k, m, shift): + f *= x**(-shift) + P = P.subs(k, k + shift) + Q = Q.subs(k, k + shift) + return f, P, Q, m + + +def _transformation_c(f, x, P, Q, k, m, scale): + f = f.subs(x, x**scale) + P = P.subs(k, k / scale) + Q = Q.subs(k, k / scale) + m *= scale + return f, P, Q, m + + +def _transformation_e(f, x, P, Q, k, m): + f = f.diff(x) + P = P.subs(k, k + 1) * (k + m + 1) + Q = Q.subs(k, k + 1) * (k + 1) + return f, P, Q, m + + +def _apply_shift(sol, shift): + return [(res, cond + shift) for res, cond in sol] + + +def _apply_scale(sol, scale): + return [(res, cond / scale) for res, cond in sol] + + +def _apply_integrate(sol, x, k): + return [(res / ((cond + 1)*(cond.as_coeff_Add()[1].coeff(k))), cond + 1) + for res, cond in sol] + + +def _compute_formula(f, x, P, Q, k, m, k_max): + """Computes the formula for f.""" + from sympy.polys import roots + + sol = [] + for i in range(k_max + 1, k_max + m + 1): + if (i < 0) == True: + continue + r = f.diff(x, i).limit(x, 0) / factorial(i) + if r.is_zero: + continue + + kterm = m*k + i + res = r + + p = P.subs(k, kterm) + q = Q.subs(k, kterm) + c1 = p.subs(k, 1/k).leadterm(k)[0] + c2 = q.subs(k, 1/k).leadterm(k)[0] + res *= (-c1 / c2)**k + + res *= Mul(*[rf(-r, k)**mul for r, mul in roots(p, k).items()]) + res /= Mul(*[rf(-r, k)**mul for r, mul in roots(q, k).items()]) + + sol.append((res, kterm)) + + return sol + + +def _rsolve_hypergeometric(f, x, P, Q, k, m): + """ + Recursive wrapper to rsolve_hypergeometric. + + Explanation + =========== + + Returns a Tuple of (formula, series independent terms, + maximum power of x in independent terms) if successful + otherwise ``None``. + + See :func:`rsolve_hypergeometric` for details. + """ + from sympy.polys import lcm, roots + from sympy.integrals import integrate + + # transformation - c + proots, qroots = roots(P, k), roots(Q, k) + all_roots = dict(proots) + all_roots.update(qroots) + scale = lcm([r.as_numer_denom()[1] for r, t in all_roots.items() + if r.is_rational]) + f, P, Q, m = _transformation_c(f, x, P, Q, k, m, scale) + + # transformation - a + qroots = roots(Q, k) + if qroots: + k_min = Min(*qroots.keys()) + else: + k_min = S.Zero + shift = k_min + m + f, P, Q, m = _transformation_a(f, x, P, Q, k, m, shift) + + l = (x*f).limit(x, 0) + if not isinstance(l, Limit) and l != 0: # Ideally should only be l != 0 + return None + + qroots = roots(Q, k) + if qroots: + k_max = Max(*qroots.keys()) + else: + k_max = S.Zero + + ind, mp = S.Zero, -oo + for i in range(k_max + m + 1): + r = f.diff(x, i).limit(x, 0) / factorial(i) + if r.is_finite is False: + old_f = f + f, P, Q, m = _transformation_a(f, x, P, Q, k, m, i) + f, P, Q, m = _transformation_e(f, x, P, Q, k, m) + sol, ind, mp = _rsolve_hypergeometric(f, x, P, Q, k, m) + sol = _apply_integrate(sol, x, k) + sol = _apply_shift(sol, i) + ind = integrate(ind, x) + ind += (old_f - ind).limit(x, 0) # constant of integration + mp += 1 + return sol, ind, mp + elif r: + ind += r*x**(i + shift) + pow_x = Rational((i + shift), scale) + if pow_x > mp: + mp = pow_x # maximum power of x + ind = ind.subs(x, x**(1/scale)) + + sol = _compute_formula(f, x, P, Q, k, m, k_max) + sol = _apply_shift(sol, shift) + sol = _apply_scale(sol, scale) + + return sol, ind, mp + + +def rsolve_hypergeometric(f, x, P, Q, k, m): + """ + Solves RE of hypergeometric type. + + Explanation + =========== + + Attempts to solve RE of the form + + Q(k)*a(k + m) - P(k)*a(k) + + Transformations that preserve Hypergeometric type: + + a. x**n*f(x): b(k + m) = R(k - n)*b(k) + b. f(A*x): b(k + m) = A**m*R(k)*b(k) + c. f(x**n): b(k + n*m) = R(k/n)*b(k) + d. f(x**(1/m)): b(k + 1) = R(k*m)*b(k) + e. f'(x): b(k + m) = ((k + m + 1)/(k + 1))*R(k + 1)*b(k) + + Some of these transformations have been used to solve the RE. + + Returns + ======= + + formula : Expr + ind : Expr + Independent terms. + order : int + + Examples + ======== + + >>> from sympy import exp, ln, S + >>> from sympy.series.formal import rsolve_hypergeometric as rh + >>> from sympy.abc import x, k + + >>> rh(exp(x), x, -S.One, (k + 1), k, 1) + (Piecewise((1/factorial(k), Eq(Mod(k, 1), 0)), (0, True)), 1, 1) + + >>> rh(ln(1 + x), x, k**2, k*(k + 1), k, 1) + (Piecewise(((-1)**(k - 1)*factorial(k - 1)/RisingFactorial(2, k - 1), + Eq(Mod(k, 1), 0)), (0, True)), x, 2) + + References + ========== + + .. [1] Formal Power Series - Dominik Gruntz, Wolfram Koepf + .. [2] Power Series in Computer Algebra - Wolfram Koepf + """ + result = _rsolve_hypergeometric(f, x, P, Q, k, m) + + if result is None: + return None + + sol_list, ind, mp = result + + sol_dict = defaultdict(lambda: S.Zero) + for res, cond in sol_list: + j, mk = cond.as_coeff_Add() + c = mk.coeff(k) + + if j.is_integer is False: + res *= x**frac(j) + j = floor(j) + + res = res.subs(k, (k - j) / c) + cond = Eq(k % c, j % c) + sol_dict[cond] += res # Group together formula for same conditions + + sol = [] + for cond, res in sol_dict.items(): + sol.append((res, cond)) + sol.append((S.Zero, True)) + sol = Piecewise(*sol) + + if mp is -oo: + s = S.Zero + elif mp.is_integer is False: + s = ceiling(mp) + else: + s = mp + 1 + + # save all the terms of + # form 1/x**k in ind + if s < 0: + ind += sum(sequence(sol * x**k, (k, s, -1))) + s = S.Zero + + return (sol, ind, s) + + +def _solve_hyper_RE(f, x, RE, g, k): + """See docstring of :func:`rsolve_hypergeometric` for details.""" + terms = Add.make_args(RE) + + if len(terms) == 2: + gs = list(RE.atoms(Function)) + P, Q = map(RE.coeff, gs) + m = gs[1].args[0] - gs[0].args[0] + if m < 0: + P, Q = Q, P + m = abs(m) + return rsolve_hypergeometric(f, x, P, Q, k, m) + + +def _solve_explike_DE(f, x, DE, g, k): + """Solves DE with constant coefficients.""" + from sympy.solvers import rsolve + + for t in Add.make_args(DE): + coeff, d = t.as_independent(g) + if coeff.free_symbols: + return + + RE = exp_re(DE, g, k) + + init = {} + for i in range(len(Add.make_args(RE))): + if i: + f = f.diff(x) + init[g(k).subs(k, i)] = f.limit(x, 0) + + sol = rsolve(RE, g(k), init) + + if sol: + return (sol / factorial(k), S.Zero, S.Zero) + + +def _solve_simple(f, x, DE, g, k): + """Converts DE into RE and solves using :func:`rsolve`.""" + from sympy.solvers import rsolve + + RE = hyper_re(DE, g, k) + + init = {} + for i in range(len(Add.make_args(RE))): + if i: + f = f.diff(x) + init[g(k).subs(k, i)] = f.limit(x, 0) / factorial(i) + + sol = rsolve(RE, g(k), init) + + if sol: + return (sol, S.Zero, S.Zero) + + +def _transform_explike_DE(DE, g, x, order, syms): + """Converts DE with free parameters into DE with constant coefficients.""" + from sympy.solvers.solveset import linsolve + + eq = [] + highest_coeff = DE.coeff(Derivative(g(x), x, order)) + for i in range(order): + coeff = DE.coeff(Derivative(g(x), x, i)) + coeff = (coeff / highest_coeff).expand().collect(x) + for t in Add.make_args(coeff): + eq.append(t) + temp = [] + for e in eq: + if e.has(x): + break + elif e.has(Symbol): + temp.append(e) + else: + eq = temp + if eq: + sol = dict(zip(syms, (i for s in linsolve(eq, list(syms)) for i in s))) + if sol: + DE = DE.subs(sol) + DE = DE.factor().as_coeff_mul(Derivative)[1][0] + DE = DE.collect(Derivative(g(x))) + return DE + + +def _transform_DE_RE(DE, g, k, order, syms): + """Converts DE with free parameters into RE of hypergeometric type.""" + from sympy.solvers.solveset import linsolve + + RE = hyper_re(DE, g, k) + + eq = [] + for i in range(1, order): + coeff = RE.coeff(g(k + i)) + eq.append(coeff) + sol = dict(zip(syms, (i for s in linsolve(eq, list(syms)) for i in s))) + if sol: + m = Wild('m') + RE = RE.subs(sol) + RE = RE.factor().as_numer_denom()[0].collect(g(k + m)) + RE = RE.as_coeff_mul(g)[1][0] + for i in range(order): # smallest order should be g(k) + if RE.coeff(g(k + i)) and i: + RE = RE.subs(k, k - i) + break + return RE + + +def solve_de(f, x, DE, order, g, k): + """ + Solves the DE. + + Explanation + =========== + + Tries to solve DE by either converting into a RE containing two terms or + converting into a DE having constant coefficients. + + Returns + ======= + + formula : Expr + ind : Expr + Independent terms. + order : int + + Examples + ======== + + >>> from sympy import Derivative as D, Function + >>> from sympy import exp, ln + >>> from sympy.series.formal import solve_de + >>> from sympy.abc import x, k + >>> f = Function('f') + + >>> solve_de(exp(x), x, D(f(x), x) - f(x), 1, f, k) + (Piecewise((1/factorial(k), Eq(Mod(k, 1), 0)), (0, True)), 1, 1) + + >>> solve_de(ln(1 + x), x, (x + 1)*D(f(x), x, 2) + D(f(x)), 2, f, k) + (Piecewise(((-1)**(k - 1)*factorial(k - 1)/RisingFactorial(2, k - 1), + Eq(Mod(k, 1), 0)), (0, True)), x, 2) + """ + sol = None + syms = DE.free_symbols.difference({g, x}) + + if syms: + RE = _transform_DE_RE(DE, g, k, order, syms) + else: + RE = hyper_re(DE, g, k) + if not RE.free_symbols.difference({k}): + sol = _solve_hyper_RE(f, x, RE, g, k) + + if sol: + return sol + + if syms: + DE = _transform_explike_DE(DE, g, x, order, syms) + if not DE.free_symbols.difference({x}): + sol = _solve_explike_DE(f, x, DE, g, k) + + if sol: + return sol + + +def hyper_algorithm(f, x, k, order=4): + """ + Hypergeometric algorithm for computing Formal Power Series. + + Explanation + =========== + + Steps: + * Generates DE + * Convert the DE into RE + * Solves the RE + + Examples + ======== + + >>> from sympy import exp, ln + >>> from sympy.series.formal import hyper_algorithm + + >>> from sympy.abc import x, k + + >>> hyper_algorithm(exp(x), x, k) + (Piecewise((1/factorial(k), Eq(Mod(k, 1), 0)), (0, True)), 1, 1) + + >>> hyper_algorithm(ln(1 + x), x, k) + (Piecewise(((-1)**(k - 1)*factorial(k - 1)/RisingFactorial(2, k - 1), + Eq(Mod(k, 1), 0)), (0, True)), x, 2) + + See Also + ======== + + sympy.series.formal.simpleDE + sympy.series.formal.solve_de + """ + g = Function('g') + + des = [] # list of DE's + sol = None + for DE, i in simpleDE(f, x, g, order): + if DE is not None: + sol = solve_de(f, x, DE, i, g, k) + if sol: + return sol + if not DE.free_symbols.difference({x}): + des.append(DE) + + # If nothing works + # Try plain rsolve + for DE in des: + sol = _solve_simple(f, x, DE, g, k) + if sol: + return sol + + +def _compute_fps(f, x, x0, dir, hyper, order, rational, full): + """Recursive wrapper to compute fps. + + See :func:`compute_fps` for details. + """ + if x0 in [S.Infinity, S.NegativeInfinity]: + dir = S.One if x0 is S.Infinity else -S.One + temp = f.subs(x, 1/x) + result = _compute_fps(temp, x, 0, dir, hyper, order, rational, full) + if result is None: + return None + return (result[0], result[1].subs(x, 1/x), result[2].subs(x, 1/x)) + elif x0 or dir == -S.One: + if dir == -S.One: + rep = -x + x0 + rep2 = -x + rep2b = x0 + else: + rep = x + x0 + rep2 = x + rep2b = -x0 + temp = f.subs(x, rep) + result = _compute_fps(temp, x, 0, S.One, hyper, order, rational, full) + if result is None: + return None + return (result[0], result[1].subs(x, rep2 + rep2b), + result[2].subs(x, rep2 + rep2b)) + + if f.is_polynomial(x): + k = Dummy('k') + ak = sequence(Coeff(f, x, k), (k, 1, oo)) + xk = sequence(x**k, (k, 0, oo)) + ind = f.coeff(x, 0) + return ak, xk, ind + + # Break instances of Add + # this allows application of different + # algorithms on different terms increasing the + # range of admissible functions. + if isinstance(f, Add): + result = False + ak = sequence(S.Zero, (0, oo)) + ind, xk = S.Zero, None + for t in Add.make_args(f): + res = _compute_fps(t, x, 0, S.One, hyper, order, rational, full) + if res: + if not result: + result = True + xk = res[1] + if res[0].start > ak.start: + seq = ak + s, f = ak.start, res[0].start + else: + seq = res[0] + s, f = res[0].start, ak.start + save = Add(*[z[0]*z[1] for z in zip(seq[0:(f - s)], xk[s:f])]) + ak += res[0] + ind += res[2] + save + else: + ind += t + if result: + return ak, xk, ind + return None + + # The symbolic term - symb, if present, is being separated from the function + # Otherwise symb is being set to S.One + syms = f.free_symbols.difference({x}) + (f, symb) = expand(f).as_independent(*syms) + + result = None + + # from here on it's x0=0 and dir=1 handling + k = Dummy('k') + if rational: + result = rational_algorithm(f, x, k, order, full) + + if result is None and hyper: + result = hyper_algorithm(f, x, k, order) + + if result is None: + return None + + from sympy.simplify.powsimp import powsimp + if symb.is_zero: + symb = S.One + else: + symb = powsimp(symb) + ak = sequence(result[0], (k, result[2], oo)) + xk_formula = powsimp(x**k * symb) + xk = sequence(xk_formula, (k, 0, oo)) + ind = powsimp(result[1] * symb) + + return ak, xk, ind + + +def compute_fps(f, x, x0=0, dir=1, hyper=True, order=4, rational=True, + full=False): + """ + Computes the formula for Formal Power Series of a function. + + Explanation + =========== + + Tries to compute the formula by applying the following techniques + (in order): + + * rational_algorithm + * Hypergeometric algorithm + + Parameters + ========== + + x : Symbol + x0 : number, optional + Point to perform series expansion about. Default is 0. + dir : {1, -1, '+', '-'}, optional + If dir is 1 or '+' the series is calculated from the right and + for -1 or '-' the series is calculated from the left. For smooth + functions this flag will not alter the results. Default is 1. + hyper : {True, False}, optional + Set hyper to False to skip the hypergeometric algorithm. + By default it is set to False. + order : int, optional + Order of the derivative of ``f``, Default is 4. + rational : {True, False}, optional + Set rational to False to skip rational algorithm. By default it is set + to True. + full : {True, False}, optional + Set full to True to increase the range of rational algorithm. + See :func:`rational_algorithm` for details. By default it is set to + False. + + Returns + ======= + + ak : sequence + Sequence of coefficients. + xk : sequence + Sequence of powers of x. + ind : Expr + Independent terms. + mul : Pow + Common terms. + + See Also + ======== + + sympy.series.formal.rational_algorithm + sympy.series.formal.hyper_algorithm + """ + f = sympify(f) + x = sympify(x) + + if not f.has(x): + return None + + x0 = sympify(x0) + + if dir == '+': + dir = S.One + elif dir == '-': + dir = -S.One + elif dir not in [S.One, -S.One]: + raise ValueError("Dir must be '+' or '-'") + else: + dir = sympify(dir) + + return _compute_fps(f, x, x0, dir, hyper, order, rational, full) + + +class Coeff(Function): + """ + Coeff(p, x, n) represents the nth coefficient of the polynomial p in x + """ + @classmethod + def eval(cls, p, x, n): + if p.is_polynomial(x) and n.is_integer: + return p.coeff(x, n) + + +class FormalPowerSeries(SeriesBase): + """ + Represents Formal Power Series of a function. + + Explanation + =========== + + No computation is performed. This class should only to be used to represent + a series. No checks are performed. + + For computing a series use :func:`fps`. + + See Also + ======== + + sympy.series.formal.fps + """ + def __new__(cls, *args): + args = map(sympify, args) + return Expr.__new__(cls, *args) + + def __init__(self, *args): + ak = args[4][0] + k = ak.variables[0] + self.ak_seq = sequence(ak.formula, (k, 1, oo)) + self.fact_seq = sequence(factorial(k), (k, 1, oo)) + self.bell_coeff_seq = self.ak_seq * self.fact_seq + self.sign_seq = sequence((-1, 1), (k, 1, oo)) + + @property + def function(self): + return self.args[0] + + @property + def x(self): + return self.args[1] + + @property + def x0(self): + return self.args[2] + + @property + def dir(self): + return self.args[3] + + @property + def ak(self): + return self.args[4][0] + + @property + def xk(self): + return self.args[4][1] + + @property + def ind(self): + return self.args[4][2] + + @property + def interval(self): + return Interval(0, oo) + + @property + def start(self): + return self.interval.inf + + @property + def stop(self): + return self.interval.sup + + @property + def length(self): + return oo + + @property + def infinite(self): + """Returns an infinite representation of the series""" + from sympy.concrete import Sum + ak, xk = self.ak, self.xk + k = ak.variables[0] + inf_sum = Sum(ak.formula * xk.formula, (k, ak.start, ak.stop)) + + return self.ind + inf_sum + + def _get_pow_x(self, term): + """Returns the power of x in a term.""" + xterm, pow_x = term.as_independent(self.x)[1].as_base_exp() + if not xterm.has(self.x): + return S.Zero + return pow_x + + def polynomial(self, n=6): + """ + Truncated series as polynomial. + + Explanation + =========== + + Returns series expansion of ``f`` upto order ``O(x**n)`` + as a polynomial(without ``O`` term). + """ + terms = [] + sym = self.free_symbols + for i, t in enumerate(self): + xp = self._get_pow_x(t) + if xp.has(*sym): + xp = xp.as_coeff_add(*sym)[0] + if xp >= n: + break + elif xp.is_integer is True and i == n + 1: + break + elif t is not S.Zero: + terms.append(t) + + return Add(*terms) + + def truncate(self, n=6): + """ + Truncated series. + + Explanation + =========== + + Returns truncated series expansion of f upto + order ``O(x**n)``. + + If n is ``None``, returns an infinite iterator. + """ + if n is None: + return iter(self) + + x, x0 = self.x, self.x0 + pt_xk = self.xk.coeff(n) + if x0 is S.NegativeInfinity: + x0 = S.Infinity + + return self.polynomial(n) + Order(pt_xk, (x, x0)) + + def zero_coeff(self): + return self._eval_term(0) + + def _eval_term(self, pt): + try: + pt_xk = self.xk.coeff(pt) + pt_ak = self.ak.coeff(pt).simplify() # Simplify the coefficients + except IndexError: + term = S.Zero + else: + term = (pt_ak * pt_xk) + + if self.ind: + ind = S.Zero + sym = self.free_symbols + for t in Add.make_args(self.ind): + pow_x = self._get_pow_x(t) + if pow_x.has(*sym): + pow_x = pow_x.as_coeff_add(*sym)[0] + if pt == 0 and pow_x < 1: + ind += t + elif pow_x >= pt and pow_x < pt + 1: + ind += t + term += ind + + return term.collect(self.x) + + def _eval_subs(self, old, new): + x = self.x + if old.has(x): + return self + + def _eval_as_leading_term(self, x, logx=None, cdir=0): + for t in self: + if t is not S.Zero: + return t + + def _eval_derivative(self, x): + f = self.function.diff(x) + ind = self.ind.diff(x) + + pow_xk = self._get_pow_x(self.xk.formula) + ak = self.ak + k = ak.variables[0] + if ak.formula.has(x): + form = [] + for e, c in ak.formula.args: + temp = S.Zero + for t in Add.make_args(e): + pow_x = self._get_pow_x(t) + temp += t * (pow_xk + pow_x) + form.append((temp, c)) + form = Piecewise(*form) + ak = sequence(form.subs(k, k + 1), (k, ak.start - 1, ak.stop)) + else: + ak = sequence((ak.formula * pow_xk).subs(k, k + 1), + (k, ak.start - 1, ak.stop)) + + return self.func(f, self.x, self.x0, self.dir, (ak, self.xk, ind)) + + def integrate(self, x=None, **kwargs): + """ + Integrate Formal Power Series. + + Examples + ======== + + >>> from sympy import fps, sin, integrate + >>> from sympy.abc import x + >>> f = fps(sin(x)) + >>> f.integrate(x).truncate() + -1 + x**2/2 - x**4/24 + O(x**6) + >>> integrate(f, (x, 0, 1)) + 1 - cos(1) + """ + from sympy.integrals import integrate + + if x is None: + x = self.x + elif iterable(x): + return integrate(self.function, x) + + f = integrate(self.function, x) + ind = integrate(self.ind, x) + ind += (f - ind).limit(x, 0) # constant of integration + + pow_xk = self._get_pow_x(self.xk.formula) + ak = self.ak + k = ak.variables[0] + if ak.formula.has(x): + form = [] + for e, c in ak.formula.args: + temp = S.Zero + for t in Add.make_args(e): + pow_x = self._get_pow_x(t) + temp += t / (pow_xk + pow_x + 1) + form.append((temp, c)) + form = Piecewise(*form) + ak = sequence(form.subs(k, k - 1), (k, ak.start + 1, ak.stop)) + else: + ak = sequence((ak.formula / (pow_xk + 1)).subs(k, k - 1), + (k, ak.start + 1, ak.stop)) + + return self.func(f, self.x, self.x0, self.dir, (ak, self.xk, ind)) + + def product(self, other, x=None, n=6): + """ + Multiplies two Formal Power Series, using discrete convolution and + return the truncated terms upto specified order. + + Parameters + ========== + + n : Number, optional + Specifies the order of the term up to which the polynomial should + be truncated. + + Examples + ======== + + >>> from sympy import fps, sin, exp + >>> from sympy.abc import x + >>> f1 = fps(sin(x)) + >>> f2 = fps(exp(x)) + + >>> f1.product(f2, x).truncate(4) + x + x**2 + x**3/3 + O(x**4) + + See Also + ======== + + sympy.discrete.convolutions + sympy.series.formal.FormalPowerSeriesProduct + + """ + + if n is None: + return iter(self) + + other = sympify(other) + + if not isinstance(other, FormalPowerSeries): + raise ValueError("Both series should be an instance of FormalPowerSeries" + " class.") + + if self.dir != other.dir: + raise ValueError("Both series should be calculated from the" + " same direction.") + elif self.x0 != other.x0: + raise ValueError("Both series should be calculated about the" + " same point.") + + elif self.x != other.x: + raise ValueError("Both series should have the same symbol.") + + return FormalPowerSeriesProduct(self, other) + + def coeff_bell(self, n): + r""" + self.coeff_bell(n) returns a sequence of Bell polynomials of the second kind. + Note that ``n`` should be a integer. + + The second kind of Bell polynomials (are sometimes called "partial" Bell + polynomials or incomplete Bell polynomials) are defined as + + .. math:: + B_{n,k}(x_1, x_2,\dotsc x_{n-k+1}) = + \sum_{j_1+j_2+j_2+\dotsb=k \atop j_1+2j_2+3j_2+\dotsb=n} + \frac{n!}{j_1!j_2!\dotsb j_{n-k+1}!} + \left(\frac{x_1}{1!} \right)^{j_1} + \left(\frac{x_2}{2!} \right)^{j_2} \dotsb + \left(\frac{x_{n-k+1}}{(n-k+1)!} \right) ^{j_{n-k+1}}. + + * ``bell(n, k, (x1, x2, ...))`` gives Bell polynomials of the second kind, + `B_{n,k}(x_1, x_2, \dotsc, x_{n-k+1})`. + + See Also + ======== + + sympy.functions.combinatorial.numbers.bell + + """ + + inner_coeffs = [bell(n, j, tuple(self.bell_coeff_seq[:n-j+1])) for j in range(1, n+1)] + + k = Dummy('k') + return sequence(tuple(inner_coeffs), (k, 1, oo)) + + def compose(self, other, x=None, n=6): + r""" + Returns the truncated terms of the formal power series of the composed function, + up to specified ``n``. + + Explanation + =========== + + If ``f`` and ``g`` are two formal power series of two different functions, + then the coefficient sequence ``ak`` of the composed formal power series `fp` + will be as follows. + + .. math:: + \sum\limits_{k=0}^{n} b_k B_{n,k}(x_1, x_2, \dotsc, x_{n-k+1}) + + Parameters + ========== + + n : Number, optional + Specifies the order of the term up to which the polynomial should + be truncated. + + Examples + ======== + + >>> from sympy import fps, sin, exp + >>> from sympy.abc import x + >>> f1 = fps(exp(x)) + >>> f2 = fps(sin(x)) + + >>> f1.compose(f2, x).truncate() + 1 + x + x**2/2 - x**4/8 - x**5/15 + O(x**6) + + >>> f1.compose(f2, x).truncate(8) + 1 + x + x**2/2 - x**4/8 - x**5/15 - x**6/240 + x**7/90 + O(x**8) + + See Also + ======== + + sympy.functions.combinatorial.numbers.bell + sympy.series.formal.FormalPowerSeriesCompose + + References + ========== + + .. [1] Comtet, Louis: Advanced combinatorics; the art of finite and infinite expansions. Reidel, 1974. + + """ + + if n is None: + return iter(self) + + other = sympify(other) + + if not isinstance(other, FormalPowerSeries): + raise ValueError("Both series should be an instance of FormalPowerSeries" + " class.") + + if self.dir != other.dir: + raise ValueError("Both series should be calculated from the" + " same direction.") + elif self.x0 != other.x0: + raise ValueError("Both series should be calculated about the" + " same point.") + + elif self.x != other.x: + raise ValueError("Both series should have the same symbol.") + + if other._eval_term(0).as_coeff_mul(other.x)[0] is not S.Zero: + raise ValueError("The formal power series of the inner function should not have any " + "constant coefficient term.") + + return FormalPowerSeriesCompose(self, other) + + def inverse(self, x=None, n=6): + r""" + Returns the truncated terms of the inverse of the formal power series, + up to specified ``n``. + + Explanation + =========== + + If ``f`` and ``g`` are two formal power series of two different functions, + then the coefficient sequence ``ak`` of the composed formal power series ``fp`` + will be as follows. + + .. math:: + \sum\limits_{k=0}^{n} (-1)^{k} x_0^{-k-1} B_{n,k}(x_1, x_2, \dotsc, x_{n-k+1}) + + Parameters + ========== + + n : Number, optional + Specifies the order of the term up to which the polynomial should + be truncated. + + Examples + ======== + + >>> from sympy import fps, exp, cos + >>> from sympy.abc import x + >>> f1 = fps(exp(x)) + >>> f2 = fps(cos(x)) + + >>> f1.inverse(x).truncate() + 1 - x + x**2/2 - x**3/6 + x**4/24 - x**5/120 + O(x**6) + + >>> f2.inverse(x).truncate(8) + 1 + x**2/2 + 5*x**4/24 + 61*x**6/720 + O(x**8) + + See Also + ======== + + sympy.functions.combinatorial.numbers.bell + sympy.series.formal.FormalPowerSeriesInverse + + References + ========== + + .. [1] Comtet, Louis: Advanced combinatorics; the art of finite and infinite expansions. Reidel, 1974. + + """ + + if n is None: + return iter(self) + + if self._eval_term(0).is_zero: + raise ValueError("Constant coefficient should exist for an inverse of a formal" + " power series to exist.") + + return FormalPowerSeriesInverse(self) + + def __add__(self, other): + other = sympify(other) + + if isinstance(other, FormalPowerSeries): + if self.dir != other.dir: + raise ValueError("Both series should be calculated from the" + " same direction.") + elif self.x0 != other.x0: + raise ValueError("Both series should be calculated about the" + " same point.") + + x, y = self.x, other.x + f = self.function + other.function.subs(y, x) + + if self.x not in f.free_symbols: + return f + + ak = self.ak + other.ak + if self.ak.start > other.ak.start: + seq = other.ak + s, e = other.ak.start, self.ak.start + else: + seq = self.ak + s, e = self.ak.start, other.ak.start + save = Add(*[z[0]*z[1] for z in zip(seq[0:(e - s)], self.xk[s:e])]) + ind = self.ind + other.ind + save + + return self.func(f, x, self.x0, self.dir, (ak, self.xk, ind)) + + elif not other.has(self.x): + f = self.function + other + ind = self.ind + other + + return self.func(f, self.x, self.x0, self.dir, + (self.ak, self.xk, ind)) + + return Add(self, other) + + def __radd__(self, other): + return self.__add__(other) + + def __neg__(self): + return self.func(-self.function, self.x, self.x0, self.dir, + (-self.ak, self.xk, -self.ind)) + + def __sub__(self, other): + return self.__add__(-other) + + def __rsub__(self, other): + return (-self).__add__(other) + + def __mul__(self, other): + other = sympify(other) + + if other.has(self.x): + return Mul(self, other) + + f = self.function * other + ak = self.ak.coeff_mul(other) + ind = self.ind * other + + return self.func(f, self.x, self.x0, self.dir, (ak, self.xk, ind)) + + def __rmul__(self, other): + return self.__mul__(other) + + +class FiniteFormalPowerSeries(FormalPowerSeries): + """Base Class for Product, Compose and Inverse classes""" + + def __init__(self, *args): + pass + + @property + def ffps(self): + return self.args[0] + + @property + def gfps(self): + return self.args[1] + + @property + def f(self): + return self.ffps.function + + @property + def g(self): + return self.gfps.function + + @property + def infinite(self): + raise NotImplementedError("No infinite version for an object of" + " FiniteFormalPowerSeries class.") + + def _eval_terms(self, n): + raise NotImplementedError("(%s)._eval_terms()" % self) + + def _eval_term(self, pt): + raise NotImplementedError("By the current logic, one can get terms" + "upto a certain order, instead of getting term by term.") + + def polynomial(self, n): + return self._eval_terms(n) + + def truncate(self, n=6): + ffps = self.ffps + pt_xk = ffps.xk.coeff(n) + x, x0 = ffps.x, ffps.x0 + + return self.polynomial(n) + Order(pt_xk, (x, x0)) + + def _eval_derivative(self, x): + raise NotImplementedError + + def integrate(self, x): + raise NotImplementedError + + +class FormalPowerSeriesProduct(FiniteFormalPowerSeries): + """Represents the product of two formal power series of two functions. + + Explanation + =========== + + No computation is performed. Terms are calculated using a term by term logic, + instead of a point by point logic. + + There are two differences between a :obj:`FormalPowerSeries` object and a + :obj:`FormalPowerSeriesProduct` object. The first argument contains the two + functions involved in the product. Also, the coefficient sequence contains + both the coefficient sequence of the formal power series of the involved functions. + + See Also + ======== + + sympy.series.formal.FormalPowerSeries + sympy.series.formal.FiniteFormalPowerSeries + + """ + + def __init__(self, *args): + ffps, gfps = self.ffps, self.gfps + + k = ffps.ak.variables[0] + self.coeff1 = sequence(ffps.ak.formula, (k, 0, oo)) + + k = gfps.ak.variables[0] + self.coeff2 = sequence(gfps.ak.formula, (k, 0, oo)) + + @property + def function(self): + """Function of the product of two formal power series.""" + return self.f * self.g + + def _eval_terms(self, n): + """ + Returns the first ``n`` terms of the product formal power series. + Term by term logic is implemented here. + + Examples + ======== + + >>> from sympy import fps, sin, exp + >>> from sympy.abc import x + >>> f1 = fps(sin(x)) + >>> f2 = fps(exp(x)) + >>> fprod = f1.product(f2, x) + + >>> fprod._eval_terms(4) + x**3/3 + x**2 + x + + See Also + ======== + + sympy.series.formal.FormalPowerSeries.product + + """ + coeff1, coeff2 = self.coeff1, self.coeff2 + + aks = convolution(coeff1[:n], coeff2[:n]) + + terms = [] + for i in range(0, n): + terms.append(aks[i] * self.ffps.xk.coeff(i)) + + return Add(*terms) + + +class FormalPowerSeriesCompose(FiniteFormalPowerSeries): + """ + Represents the composed formal power series of two functions. + + Explanation + =========== + + No computation is performed. Terms are calculated using a term by term logic, + instead of a point by point logic. + + There are two differences between a :obj:`FormalPowerSeries` object and a + :obj:`FormalPowerSeriesCompose` object. The first argument contains the outer + function and the inner function involved in the omposition. Also, the + coefficient sequence contains the generic sequence which is to be multiplied + by a custom ``bell_seq`` finite sequence. The finite terms will then be added up to + get the final terms. + + See Also + ======== + + sympy.series.formal.FormalPowerSeries + sympy.series.formal.FiniteFormalPowerSeries + + """ + + @property + def function(self): + """Function for the composed formal power series.""" + f, g, x = self.f, self.g, self.ffps.x + return f.subs(x, g) + + def _eval_terms(self, n): + """ + Returns the first `n` terms of the composed formal power series. + Term by term logic is implemented here. + + Explanation + =========== + + The coefficient sequence of the :obj:`FormalPowerSeriesCompose` object is the generic sequence. + It is multiplied by ``bell_seq`` to get a sequence, whose terms are added up to get + the final terms for the polynomial. + + Examples + ======== + + >>> from sympy import fps, sin, exp + >>> from sympy.abc import x + >>> f1 = fps(exp(x)) + >>> f2 = fps(sin(x)) + >>> fcomp = f1.compose(f2, x) + + >>> fcomp._eval_terms(6) + -x**5/15 - x**4/8 + x**2/2 + x + 1 + + >>> fcomp._eval_terms(8) + x**7/90 - x**6/240 - x**5/15 - x**4/8 + x**2/2 + x + 1 + + See Also + ======== + + sympy.series.formal.FormalPowerSeries.compose + sympy.series.formal.FormalPowerSeries.coeff_bell + + """ + + ffps, gfps = self.ffps, self.gfps + terms = [ffps.zero_coeff()] + + for i in range(1, n): + bell_seq = gfps.coeff_bell(i) + seq = (ffps.bell_coeff_seq * bell_seq) + terms.append(Add(*(seq[:i])) / ffps.fact_seq[i-1] * ffps.xk.coeff(i)) + + return Add(*terms) + + +class FormalPowerSeriesInverse(FiniteFormalPowerSeries): + """ + Represents the Inverse of a formal power series. + + Explanation + =========== + + No computation is performed. Terms are calculated using a term by term logic, + instead of a point by point logic. + + There is a single difference between a :obj:`FormalPowerSeries` object and a + :obj:`FormalPowerSeriesInverse` object. The coefficient sequence contains the + generic sequence which is to be multiplied by a custom ``bell_seq`` finite sequence. + The finite terms will then be added up to get the final terms. + + See Also + ======== + + sympy.series.formal.FormalPowerSeries + sympy.series.formal.FiniteFormalPowerSeries + + """ + def __init__(self, *args): + ffps = self.ffps + k = ffps.xk.variables[0] + + inv = ffps.zero_coeff() + inv_seq = sequence(inv ** (-(k + 1)), (k, 1, oo)) + self.aux_seq = ffps.sign_seq * ffps.fact_seq * inv_seq + + @property + def function(self): + """Function for the inverse of a formal power series.""" + f = self.f + return 1 / f + + @property + def g(self): + raise ValueError("Only one function is considered while performing" + "inverse of a formal power series.") + + @property + def gfps(self): + raise ValueError("Only one function is considered while performing" + "inverse of a formal power series.") + + def _eval_terms(self, n): + """ + Returns the first ``n`` terms of the composed formal power series. + Term by term logic is implemented here. + + Explanation + =========== + + The coefficient sequence of the `FormalPowerSeriesInverse` object is the generic sequence. + It is multiplied by ``bell_seq`` to get a sequence, whose terms are added up to get + the final terms for the polynomial. + + Examples + ======== + + >>> from sympy import fps, exp, cos + >>> from sympy.abc import x + >>> f1 = fps(exp(x)) + >>> f2 = fps(cos(x)) + >>> finv1, finv2 = f1.inverse(), f2.inverse() + + >>> finv1._eval_terms(6) + -x**5/120 + x**4/24 - x**3/6 + x**2/2 - x + 1 + + >>> finv2._eval_terms(8) + 61*x**6/720 + 5*x**4/24 + x**2/2 + 1 + + See Also + ======== + + sympy.series.formal.FormalPowerSeries.inverse + sympy.series.formal.FormalPowerSeries.coeff_bell + + """ + ffps = self.ffps + terms = [ffps.zero_coeff()] + + for i in range(1, n): + bell_seq = ffps.coeff_bell(i) + seq = (self.aux_seq * bell_seq) + terms.append(Add(*(seq[:i])) / ffps.fact_seq[i-1] * ffps.xk.coeff(i)) + + return Add(*terms) + + +def fps(f, x=None, x0=0, dir=1, hyper=True, order=4, rational=True, full=False): + """ + Generates Formal Power Series of ``f``. + + Explanation + =========== + + Returns the formal series expansion of ``f`` around ``x = x0`` + with respect to ``x`` in the form of a ``FormalPowerSeries`` object. + + Formal Power Series is represented using an explicit formula + computed using different algorithms. + + See :func:`compute_fps` for the more details regarding the computation + of formula. + + Parameters + ========== + + x : Symbol, optional + If x is None and ``f`` is univariate, the univariate symbols will be + supplied, otherwise an error will be raised. + x0 : number, optional + Point to perform series expansion about. Default is 0. + dir : {1, -1, '+', '-'}, optional + If dir is 1 or '+' the series is calculated from the right and + for -1 or '-' the series is calculated from the left. For smooth + functions this flag will not alter the results. Default is 1. + hyper : {True, False}, optional + Set hyper to False to skip the hypergeometric algorithm. + By default it is set to False. + order : int, optional + Order of the derivative of ``f``, Default is 4. + rational : {True, False}, optional + Set rational to False to skip rational algorithm. By default it is set + to True. + full : {True, False}, optional + Set full to True to increase the range of rational algorithm. + See :func:`rational_algorithm` for details. By default it is set to + False. + + Examples + ======== + + >>> from sympy import fps, ln, atan, sin + >>> from sympy.abc import x, n + + Rational Functions + + >>> fps(ln(1 + x)).truncate() + x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6) + + >>> fps(atan(x), full=True).truncate() + x - x**3/3 + x**5/5 + O(x**6) + + Symbolic Functions + + >>> fps(x**n*sin(x**2), x).truncate(8) + -x**(n + 6)/6 + x**(n + 2) + O(x**(n + 8)) + + See Also + ======== + + sympy.series.formal.FormalPowerSeries + sympy.series.formal.compute_fps + """ + f = sympify(f) + + if x is None: + free = f.free_symbols + if len(free) == 1: + x = free.pop() + elif not free: + return f + else: + raise NotImplementedError("multivariate formal power series") + + result = compute_fps(f, x, x0, dir, hyper, order, rational, full) + + if result is None: + return f + + return FormalPowerSeries(f, x, x0, dir, result) diff --git a/lib/python3.12/site-packages/sympy/series/fourier.py b/lib/python3.12/site-packages/sympy/series/fourier.py new file mode 100644 index 0000000000000000000000000000000000000000..3919fba404a40ea9c1ea4eff4409df0f8140661e --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/fourier.py @@ -0,0 +1,811 @@ +"""Fourier Series""" + +from sympy.core.numbers import (oo, pi) +from sympy.core.symbol import Wild +from sympy.core.expr import Expr +from sympy.core.add import Add +from sympy.core.containers import Tuple +from sympy.core.singleton import S +from sympy.core.symbol import Dummy, Symbol +from sympy.core.sympify import sympify +from sympy.functions.elementary.trigonometric import sin, cos, sinc +from sympy.series.series_class import SeriesBase +from sympy.series.sequences import SeqFormula +from sympy.sets.sets import Interval +from sympy.utilities.iterables import is_sequence + + +__doctest_requires__ = {('fourier_series',): ['matplotlib']} + + +def fourier_cos_seq(func, limits, n): + """Returns the cos sequence in a Fourier series""" + from sympy.integrals import integrate + x, L = limits[0], limits[2] - limits[1] + cos_term = cos(2*n*pi*x / L) + formula = 2 * cos_term * integrate(func * cos_term, limits) / L + a0 = formula.subs(n, S.Zero) / 2 + return a0, SeqFormula(2 * cos_term * integrate(func * cos_term, limits) + / L, (n, 1, oo)) + + +def fourier_sin_seq(func, limits, n): + """Returns the sin sequence in a Fourier series""" + from sympy.integrals import integrate + x, L = limits[0], limits[2] - limits[1] + sin_term = sin(2*n*pi*x / L) + return SeqFormula(2 * sin_term * integrate(func * sin_term, limits) + / L, (n, 1, oo)) + + +def _process_limits(func, limits): + """ + Limits should be of the form (x, start, stop). + x should be a symbol. Both start and stop should be bounded. + + Explanation + =========== + + * If x is not given, x is determined from func. + * If limits is None. Limit of the form (x, -pi, pi) is returned. + + Examples + ======== + + >>> from sympy.series.fourier import _process_limits as pari + >>> from sympy.abc import x + >>> pari(x**2, (x, -2, 2)) + (x, -2, 2) + >>> pari(x**2, (-2, 2)) + (x, -2, 2) + >>> pari(x**2, None) + (x, -pi, pi) + """ + def _find_x(func): + free = func.free_symbols + if len(free) == 1: + return free.pop() + elif not free: + return Dummy('k') + else: + raise ValueError( + " specify dummy variables for %s. If the function contains" + " more than one free symbol, a dummy variable should be" + " supplied explicitly e.g. FourierSeries(m*n**2, (n, -pi, pi))" + % func) + + x, start, stop = None, None, None + if limits is None: + x, start, stop = _find_x(func), -pi, pi + if is_sequence(limits, Tuple): + if len(limits) == 3: + x, start, stop = limits + elif len(limits) == 2: + x = _find_x(func) + start, stop = limits + + if not isinstance(x, Symbol) or start is None or stop is None: + raise ValueError('Invalid limits given: %s' % str(limits)) + + unbounded = [S.NegativeInfinity, S.Infinity] + if start in unbounded or stop in unbounded: + raise ValueError("Both the start and end value should be bounded") + + return sympify((x, start, stop)) + + +def finite_check(f, x, L): + + def check_fx(exprs, x): + return x not in exprs.free_symbols + + def check_sincos(_expr, x, L): + if isinstance(_expr, (sin, cos)): + sincos_args = _expr.args[0] + + if sincos_args.match(a*(pi/L)*x + b) is not None: + return True + else: + return False + + from sympy.simplify.fu import TR2, TR1, sincos_to_sum + _expr = sincos_to_sum(TR2(TR1(f))) + add_coeff = _expr.as_coeff_add() + + a = Wild('a', properties=[lambda k: k.is_Integer, lambda k: k != S.Zero, ]) + b = Wild('b', properties=[lambda k: x not in k.free_symbols, ]) + + for s in add_coeff[1]: + mul_coeffs = s.as_coeff_mul()[1] + for t in mul_coeffs: + if not (check_fx(t, x) or check_sincos(t, x, L)): + return False, f + + return True, _expr + + +class FourierSeries(SeriesBase): + r"""Represents Fourier sine/cosine series. + + Explanation + =========== + + This class only represents a fourier series. + No computation is performed. + + For how to compute Fourier series, see the :func:`fourier_series` + docstring. + + See Also + ======== + + sympy.series.fourier.fourier_series + """ + def __new__(cls, *args): + args = map(sympify, args) + return Expr.__new__(cls, *args) + + @property + def function(self): + return self.args[0] + + @property + def x(self): + return self.args[1][0] + + @property + def period(self): + return (self.args[1][1], self.args[1][2]) + + @property + def a0(self): + return self.args[2][0] + + @property + def an(self): + return self.args[2][1] + + @property + def bn(self): + return self.args[2][2] + + @property + def interval(self): + return Interval(0, oo) + + @property + def start(self): + return self.interval.inf + + @property + def stop(self): + return self.interval.sup + + @property + def length(self): + return oo + + @property + def L(self): + return abs(self.period[1] - self.period[0]) / 2 + + def _eval_subs(self, old, new): + x = self.x + if old.has(x): + return self + + def truncate(self, n=3): + """ + Return the first n nonzero terms of the series. + + If ``n`` is None return an iterator. + + Parameters + ========== + + n : int or None + Amount of non-zero terms in approximation or None. + + Returns + ======= + + Expr or iterator : + Approximation of function expanded into Fourier series. + + Examples + ======== + + >>> from sympy import fourier_series, pi + >>> from sympy.abc import x + >>> s = fourier_series(x, (x, -pi, pi)) + >>> s.truncate(4) + 2*sin(x) - sin(2*x) + 2*sin(3*x)/3 - sin(4*x)/2 + + See Also + ======== + + sympy.series.fourier.FourierSeries.sigma_approximation + """ + if n is None: + return iter(self) + + terms = [] + for t in self: + if len(terms) == n: + break + if t is not S.Zero: + terms.append(t) + + return Add(*terms) + + def sigma_approximation(self, n=3): + r""" + Return :math:`\sigma`-approximation of Fourier series with respect + to order n. + + Explanation + =========== + + Sigma approximation adjusts a Fourier summation to eliminate the Gibbs + phenomenon which would otherwise occur at discontinuities. + A sigma-approximated summation for a Fourier series of a T-periodical + function can be written as + + .. math:: + s(\theta) = \frac{1}{2} a_0 + \sum _{k=1}^{m-1} + \operatorname{sinc} \Bigl( \frac{k}{m} \Bigr) \cdot + \left[ a_k \cos \Bigl( \frac{2\pi k}{T} \theta \Bigr) + + b_k \sin \Bigl( \frac{2\pi k}{T} \theta \Bigr) \right], + + where :math:`a_0, a_k, b_k, k=1,\ldots,{m-1}` are standard Fourier + series coefficients and + :math:`\operatorname{sinc} \Bigl( \frac{k}{m} \Bigr)` is a Lanczos + :math:`\sigma` factor (expressed in terms of normalized + :math:`\operatorname{sinc}` function). + + Parameters + ========== + + n : int + Highest order of the terms taken into account in approximation. + + Returns + ======= + + Expr : + Sigma approximation of function expanded into Fourier series. + + Examples + ======== + + >>> from sympy import fourier_series, pi + >>> from sympy.abc import x + >>> s = fourier_series(x, (x, -pi, pi)) + >>> s.sigma_approximation(4) + 2*sin(x)*sinc(pi/4) - 2*sin(2*x)/pi + 2*sin(3*x)*sinc(3*pi/4)/3 + + See Also + ======== + + sympy.series.fourier.FourierSeries.truncate + + Notes + ===== + + The behaviour of + :meth:`~sympy.series.fourier.FourierSeries.sigma_approximation` + is different from :meth:`~sympy.series.fourier.FourierSeries.truncate` + - it takes all nonzero terms of degree smaller than n, rather than + first n nonzero ones. + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Gibbs_phenomenon + .. [2] https://en.wikipedia.org/wiki/Sigma_approximation + """ + terms = [sinc(pi * i / n) * t for i, t in enumerate(self[:n]) + if t is not S.Zero] + return Add(*terms) + + def shift(self, s): + """ + Shift the function by a term independent of x. + + Explanation + =========== + + f(x) -> f(x) + s + + This is fast, if Fourier series of f(x) is already + computed. + + Examples + ======== + + >>> from sympy import fourier_series, pi + >>> from sympy.abc import x + >>> s = fourier_series(x**2, (x, -pi, pi)) + >>> s.shift(1).truncate() + -4*cos(x) + cos(2*x) + 1 + pi**2/3 + """ + s, x = sympify(s), self.x + + if x in s.free_symbols: + raise ValueError("'%s' should be independent of %s" % (s, x)) + + a0 = self.a0 + s + sfunc = self.function + s + + return self.func(sfunc, self.args[1], (a0, self.an, self.bn)) + + def shiftx(self, s): + """ + Shift x by a term independent of x. + + Explanation + =========== + + f(x) -> f(x + s) + + This is fast, if Fourier series of f(x) is already + computed. + + Examples + ======== + + >>> from sympy import fourier_series, pi + >>> from sympy.abc import x + >>> s = fourier_series(x**2, (x, -pi, pi)) + >>> s.shiftx(1).truncate() + -4*cos(x + 1) + cos(2*x + 2) + pi**2/3 + """ + s, x = sympify(s), self.x + + if x in s.free_symbols: + raise ValueError("'%s' should be independent of %s" % (s, x)) + + an = self.an.subs(x, x + s) + bn = self.bn.subs(x, x + s) + sfunc = self.function.subs(x, x + s) + + return self.func(sfunc, self.args[1], (self.a0, an, bn)) + + def scale(self, s): + """ + Scale the function by a term independent of x. + + Explanation + =========== + + f(x) -> s * f(x) + + This is fast, if Fourier series of f(x) is already + computed. + + Examples + ======== + + >>> from sympy import fourier_series, pi + >>> from sympy.abc import x + >>> s = fourier_series(x**2, (x, -pi, pi)) + >>> s.scale(2).truncate() + -8*cos(x) + 2*cos(2*x) + 2*pi**2/3 + """ + s, x = sympify(s), self.x + + if x in s.free_symbols: + raise ValueError("'%s' should be independent of %s" % (s, x)) + + an = self.an.coeff_mul(s) + bn = self.bn.coeff_mul(s) + a0 = self.a0 * s + sfunc = self.args[0] * s + + return self.func(sfunc, self.args[1], (a0, an, bn)) + + def scalex(self, s): + """ + Scale x by a term independent of x. + + Explanation + =========== + + f(x) -> f(s*x) + + This is fast, if Fourier series of f(x) is already + computed. + + Examples + ======== + + >>> from sympy import fourier_series, pi + >>> from sympy.abc import x + >>> s = fourier_series(x**2, (x, -pi, pi)) + >>> s.scalex(2).truncate() + -4*cos(2*x) + cos(4*x) + pi**2/3 + """ + s, x = sympify(s), self.x + + if x in s.free_symbols: + raise ValueError("'%s' should be independent of %s" % (s, x)) + + an = self.an.subs(x, x * s) + bn = self.bn.subs(x, x * s) + sfunc = self.function.subs(x, x * s) + + return self.func(sfunc, self.args[1], (self.a0, an, bn)) + + def _eval_as_leading_term(self, x, logx=None, cdir=0): + for t in self: + if t is not S.Zero: + return t + + def _eval_term(self, pt): + if pt == 0: + return self.a0 + return self.an.coeff(pt) + self.bn.coeff(pt) + + def __neg__(self): + return self.scale(-1) + + def __add__(self, other): + if isinstance(other, FourierSeries): + if self.period != other.period: + raise ValueError("Both the series should have same periods") + + x, y = self.x, other.x + function = self.function + other.function.subs(y, x) + + if self.x not in function.free_symbols: + return function + + an = self.an + other.an + bn = self.bn + other.bn + a0 = self.a0 + other.a0 + + return self.func(function, self.args[1], (a0, an, bn)) + + return Add(self, other) + + def __sub__(self, other): + return self.__add__(-other) + + +class FiniteFourierSeries(FourierSeries): + r"""Represents Finite Fourier sine/cosine series. + + For how to compute Fourier series, see the :func:`fourier_series` + docstring. + + Parameters + ========== + + f : Expr + Expression for finding fourier_series + + limits : ( x, start, stop) + x is the independent variable for the expression f + (start, stop) is the period of the fourier series + + exprs: (a0, an, bn) or Expr + a0 is the constant term a0 of the fourier series + an is a dictionary of coefficients of cos terms + an[k] = coefficient of cos(pi*(k/L)*x) + bn is a dictionary of coefficients of sin terms + bn[k] = coefficient of sin(pi*(k/L)*x) + + or exprs can be an expression to be converted to fourier form + + Methods + ======= + + This class is an extension of FourierSeries class. + Please refer to sympy.series.fourier.FourierSeries for + further information. + + See Also + ======== + + sympy.series.fourier.FourierSeries + sympy.series.fourier.fourier_series + """ + + def __new__(cls, f, limits, exprs): + f = sympify(f) + limits = sympify(limits) + exprs = sympify(exprs) + + if not (isinstance(exprs, Tuple) and len(exprs) == 3): # exprs is not of form (a0, an, bn) + # Converts the expression to fourier form + c, e = exprs.as_coeff_add() + from sympy.simplify.fu import TR10 + rexpr = c + Add(*[TR10(i) for i in e]) + a0, exp_ls = rexpr.expand(trig=False, power_base=False, power_exp=False, log=False).as_coeff_add() + + x = limits[0] + L = abs(limits[2] - limits[1]) / 2 + + a = Wild('a', properties=[lambda k: k.is_Integer, lambda k: k is not S.Zero, ]) + b = Wild('b', properties=[lambda k: x not in k.free_symbols, ]) + + an = {} + bn = {} + + # separates the coefficients of sin and cos terms in dictionaries an, and bn + for p in exp_ls: + t = p.match(b * cos(a * (pi / L) * x)) + q = p.match(b * sin(a * (pi / L) * x)) + if t: + an[t[a]] = t[b] + an.get(t[a], S.Zero) + elif q: + bn[q[a]] = q[b] + bn.get(q[a], S.Zero) + else: + a0 += p + + exprs = Tuple(a0, an, bn) + + return Expr.__new__(cls, f, limits, exprs) + + @property + def interval(self): + _length = 1 if self.a0 else 0 + _length += max(set(self.an.keys()).union(set(self.bn.keys()))) + 1 + return Interval(0, _length) + + @property + def length(self): + return self.stop - self.start + + def shiftx(self, s): + s, x = sympify(s), self.x + + if x in s.free_symbols: + raise ValueError("'%s' should be independent of %s" % (s, x)) + + _expr = self.truncate().subs(x, x + s) + sfunc = self.function.subs(x, x + s) + + return self.func(sfunc, self.args[1], _expr) + + def scale(self, s): + s, x = sympify(s), self.x + + if x in s.free_symbols: + raise ValueError("'%s' should be independent of %s" % (s, x)) + + _expr = self.truncate() * s + sfunc = self.function * s + + return self.func(sfunc, self.args[1], _expr) + + def scalex(self, s): + s, x = sympify(s), self.x + + if x in s.free_symbols: + raise ValueError("'%s' should be independent of %s" % (s, x)) + + _expr = self.truncate().subs(x, x * s) + sfunc = self.function.subs(x, x * s) + + return self.func(sfunc, self.args[1], _expr) + + def _eval_term(self, pt): + if pt == 0: + return self.a0 + + _term = self.an.get(pt, S.Zero) * cos(pt * (pi / self.L) * self.x) \ + + self.bn.get(pt, S.Zero) * sin(pt * (pi / self.L) * self.x) + return _term + + def __add__(self, other): + if isinstance(other, FourierSeries): + return other.__add__(fourier_series(self.function, self.args[1],\ + finite=False)) + elif isinstance(other, FiniteFourierSeries): + if self.period != other.period: + raise ValueError("Both the series should have same periods") + + x, y = self.x, other.x + function = self.function + other.function.subs(y, x) + + if self.x not in function.free_symbols: + return function + + return fourier_series(function, limits=self.args[1]) + + +def fourier_series(f, limits=None, finite=True): + r"""Computes the Fourier trigonometric series expansion. + + Explanation + =========== + + Fourier trigonometric series of $f(x)$ over the interval $(a, b)$ + is defined as: + + .. math:: + \frac{a_0}{2} + \sum_{n=1}^{\infty} + (a_n \cos(\frac{2n \pi x}{L}) + b_n \sin(\frac{2n \pi x}{L})) + + where the coefficients are: + + .. math:: + L = b - a + + .. math:: + a_0 = \frac{2}{L} \int_{a}^{b}{f(x) dx} + + .. math:: + a_n = \frac{2}{L} \int_{a}^{b}{f(x) \cos(\frac{2n \pi x}{L}) dx} + + .. math:: + b_n = \frac{2}{L} \int_{a}^{b}{f(x) \sin(\frac{2n \pi x}{L}) dx} + + The condition whether the function $f(x)$ given should be periodic + or not is more than necessary, because it is sufficient to consider + the series to be converging to $f(x)$ only in the given interval, + not throughout the whole real line. + + This also brings a lot of ease for the computation because + you do not have to make $f(x)$ artificially periodic by + wrapping it with piecewise, modulo operations, + but you can shape the function to look like the desired periodic + function only in the interval $(a, b)$, and the computed series will + automatically become the series of the periodic version of $f(x)$. + + This property is illustrated in the examples section below. + + Parameters + ========== + + limits : (sym, start, end), optional + *sym* denotes the symbol the series is computed with respect to. + + *start* and *end* denotes the start and the end of the interval + where the fourier series converges to the given function. + + Default range is specified as $-\pi$ and $\pi$. + + Returns + ======= + + FourierSeries + A symbolic object representing the Fourier trigonometric series. + + Examples + ======== + + Computing the Fourier series of $f(x) = x^2$: + + >>> from sympy import fourier_series, pi + >>> from sympy.abc import x + >>> f = x**2 + >>> s = fourier_series(f, (x, -pi, pi)) + >>> s1 = s.truncate(n=3) + >>> s1 + -4*cos(x) + cos(2*x) + pi**2/3 + + Shifting of the Fourier series: + + >>> s.shift(1).truncate() + -4*cos(x) + cos(2*x) + 1 + pi**2/3 + >>> s.shiftx(1).truncate() + -4*cos(x + 1) + cos(2*x + 2) + pi**2/3 + + Scaling of the Fourier series: + + >>> s.scale(2).truncate() + -8*cos(x) + 2*cos(2*x) + 2*pi**2/3 + >>> s.scalex(2).truncate() + -4*cos(2*x) + cos(4*x) + pi**2/3 + + Computing the Fourier series of $f(x) = x$: + + This illustrates how truncating to the higher order gives better + convergence. + + .. plot:: + :context: reset + :format: doctest + :include-source: True + + >>> from sympy import fourier_series, pi, plot + >>> from sympy.abc import x + >>> f = x + >>> s = fourier_series(f, (x, -pi, pi)) + >>> s1 = s.truncate(n = 3) + >>> s2 = s.truncate(n = 5) + >>> s3 = s.truncate(n = 7) + >>> p = plot(f, s1, s2, s3, (x, -pi, pi), show=False, legend=True) + + >>> p[0].line_color = (0, 0, 0) + >>> p[0].label = 'x' + >>> p[1].line_color = (0.7, 0.7, 0.7) + >>> p[1].label = 'n=3' + >>> p[2].line_color = (0.5, 0.5, 0.5) + >>> p[2].label = 'n=5' + >>> p[3].line_color = (0.3, 0.3, 0.3) + >>> p[3].label = 'n=7' + + >>> p.show() + + This illustrates how the series converges to different sawtooth + waves if the different ranges are specified. + + .. plot:: + :context: close-figs + :format: doctest + :include-source: True + + >>> s1 = fourier_series(x, (x, -1, 1)).truncate(10) + >>> s2 = fourier_series(x, (x, -pi, pi)).truncate(10) + >>> s3 = fourier_series(x, (x, 0, 1)).truncate(10) + >>> p = plot(x, s1, s2, s3, (x, -5, 5), show=False, legend=True) + + >>> p[0].line_color = (0, 0, 0) + >>> p[0].label = 'x' + >>> p[1].line_color = (0.7, 0.7, 0.7) + >>> p[1].label = '[-1, 1]' + >>> p[2].line_color = (0.5, 0.5, 0.5) + >>> p[2].label = '[-pi, pi]' + >>> p[3].line_color = (0.3, 0.3, 0.3) + >>> p[3].label = '[0, 1]' + + >>> p.show() + + Notes + ===== + + Computing Fourier series can be slow + due to the integration required in computing + an, bn. + + It is faster to compute Fourier series of a function + by using shifting and scaling on an already + computed Fourier series rather than computing + again. + + e.g. If the Fourier series of ``x**2`` is known + the Fourier series of ``x**2 - 1`` can be found by shifting by ``-1``. + + See Also + ======== + + sympy.series.fourier.FourierSeries + + References + ========== + + .. [1] https://mathworld.wolfram.com/FourierSeries.html + """ + f = sympify(f) + + limits = _process_limits(f, limits) + x = limits[0] + + if x not in f.free_symbols: + return f + + if finite: + L = abs(limits[2] - limits[1]) / 2 + is_finite, res_f = finite_check(f, x, L) + if is_finite: + return FiniteFourierSeries(f, limits, res_f) + + n = Dummy('n') + center = (limits[1] + limits[2]) / 2 + if center.is_zero: + neg_f = f.subs(x, -x) + if f == neg_f: + a0, an = fourier_cos_seq(f, limits, n) + bn = SeqFormula(0, (1, oo)) + return FourierSeries(f, limits, (a0, an, bn)) + elif f == -neg_f: + a0 = S.Zero + an = SeqFormula(0, (1, oo)) + bn = fourier_sin_seq(f, limits, n) + return FourierSeries(f, limits, (a0, an, bn)) + a0, an = fourier_cos_seq(f, limits, n) + bn = fourier_sin_seq(f, limits, n) + return FourierSeries(f, limits, (a0, an, bn)) diff --git a/lib/python3.12/site-packages/sympy/series/gruntz.py b/lib/python3.12/site-packages/sympy/series/gruntz.py new file mode 100644 index 0000000000000000000000000000000000000000..8711074f3fdf593090ca2f782a8177e3517b0c38 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/gruntz.py @@ -0,0 +1,739 @@ +""" +Limits +====== + +Implemented according to the PhD thesis +https://www.cybertester.com/data/gruntz.pdf, which contains very thorough +descriptions of the algorithm including many examples. We summarize here +the gist of it. + +All functions are sorted according to how rapidly varying they are at +infinity using the following rules. Any two functions f and g can be +compared using the properties of L: + +L=lim log|f(x)| / log|g(x)| (for x -> oo) + +We define >, < ~ according to:: + + 1. f > g .... L=+-oo + + we say that: + - f is greater than any power of g + - f is more rapidly varying than g + - f goes to infinity/zero faster than g + + 2. f < g .... L=0 + + we say that: + - f is lower than any power of g + + 3. f ~ g .... L!=0, +-oo + + we say that: + - both f and g are bounded from above and below by suitable integral + powers of the other + +Examples +======== +:: + 2 < x < exp(x) < exp(x**2) < exp(exp(x)) + 2 ~ 3 ~ -5 + x ~ x**2 ~ x**3 ~ 1/x ~ x**m ~ -x + exp(x) ~ exp(-x) ~ exp(2x) ~ exp(x)**2 ~ exp(x+exp(-x)) + f ~ 1/f + +So we can divide all the functions into comparability classes (x and x^2 +belong to one class, exp(x) and exp(-x) belong to some other class). In +principle, we could compare any two functions, but in our algorithm, we +do not compare anything below the class 2~3~-5 (for example log(x) is +below this), so we set 2~3~-5 as the lowest comparability class. + +Given the function f, we find the list of most rapidly varying (mrv set) +subexpressions of it. This list belongs to the same comparability class. +Let's say it is {exp(x), exp(2x)}. Using the rule f ~ 1/f we find an +element "w" (either from the list or a new one) from the same +comparability class which goes to zero at infinity. In our example we +set w=exp(-x) (but we could also set w=exp(-2x) or w=exp(-3x) ...). We +rewrite the mrv set using w, in our case {1/w, 1/w^2}, and substitute it +into f. Then we expand f into a series in w:: + + f = c0*w^e0 + c1*w^e1 + ... + O(w^en), where e0oo, lim f = lim c0*w^e0, because all the other terms go to zero, +because w goes to zero faster than the ci and ei. So:: + + for e0>0, lim f = 0 + for e0<0, lim f = +-oo (the sign depends on the sign of c0) + for e0=0, lim f = lim c0 + +We need to recursively compute limits at several places of the algorithm, but +as is shown in the PhD thesis, it always finishes. + +Important functions from the implementation: + +compare(a, b, x) compares "a" and "b" by computing the limit L. +mrv(e, x) returns list of most rapidly varying (mrv) subexpressions of "e" +rewrite(e, Omega, x, wsym) rewrites "e" in terms of w +leadterm(f, x) returns the lowest power term in the series of f +mrv_leadterm(e, x) returns the lead term (c0, e0) for e +limitinf(e, x) computes lim e (for x->oo) +limit(e, z, z0) computes any limit by converting it to the case x->oo + +All the functions are really simple and straightforward except +rewrite(), which is the most difficult/complex part of the algorithm. +When the algorithm fails, the bugs are usually in the series expansion +(i.e. in SymPy) or in rewrite. + +This code is almost exact rewrite of the Maple code inside the Gruntz +thesis. + +Debugging +--------- + +Because the gruntz algorithm is highly recursive, it's difficult to +figure out what went wrong inside a debugger. Instead, turn on nice +debug prints by defining the environment variable SYMPY_DEBUG. For +example: + +[user@localhost]: SYMPY_DEBUG=True ./bin/isympy + +In [1]: limit(sin(x)/x, x, 0) +limitinf(_x*sin(1/_x), _x) = 1 ++-mrv_leadterm(_x*sin(1/_x), _x) = (1, 0) +| +-mrv(_x*sin(1/_x), _x) = set([_x]) +| | +-mrv(_x, _x) = set([_x]) +| | +-mrv(sin(1/_x), _x) = set([_x]) +| | +-mrv(1/_x, _x) = set([_x]) +| | +-mrv(_x, _x) = set([_x]) +| +-mrv_leadterm(exp(_x)*sin(exp(-_x)), _x, set([exp(_x)])) = (1, 0) +| +-rewrite(exp(_x)*sin(exp(-_x)), set([exp(_x)]), _x, _w) = (1/_w*sin(_w), -_x) +| +-sign(_x, _x) = 1 +| +-mrv_leadterm(1, _x) = (1, 0) ++-sign(0, _x) = 0 ++-limitinf(1, _x) = 1 + +And check manually which line is wrong. Then go to the source code and +debug this function to figure out the exact problem. + +""" +from functools import reduce + +from sympy.core import Basic, S, Mul, PoleError, expand_mul +from sympy.core.cache import cacheit +from sympy.core.intfunc import ilcm +from sympy.core.numbers import I, oo +from sympy.core.symbol import Dummy, Wild +from sympy.core.traversal import bottom_up + +from sympy.functions import log, exp, sign as _sign +from sympy.series.order import Order +from sympy.utilities.exceptions import SymPyDeprecationWarning +from sympy.utilities.misc import debug_decorator as debug +from sympy.utilities.timeutils import timethis + +timeit = timethis('gruntz') + + +def compare(a, b, x): + """Returns "<" if a" for a>b""" + # log(exp(...)) must always be simplified here for termination + la, lb = log(a), log(b) + if isinstance(a, Basic) and (isinstance(a, exp) or (a.is_Pow and a.base == S.Exp1)): + la = a.exp + if isinstance(b, Basic) and (isinstance(b, exp) or (b.is_Pow and b.base == S.Exp1)): + lb = b.exp + + c = limitinf(la/lb, x) + if c == 0: + return "<" + elif c.is_infinite: + return ">" + else: + return "=" + + +class SubsSet(dict): + """ + Stores (expr, dummy) pairs, and how to rewrite expr-s. + + Explanation + =========== + + The gruntz algorithm needs to rewrite certain expressions in term of a new + variable w. We cannot use subs, because it is just too smart for us. For + example:: + + > Omega=[exp(exp(_p - exp(-_p))/(1 - 1/_p)), exp(exp(_p))] + > O2=[exp(-exp(_p) + exp(-exp(-_p))*exp(_p)/(1 - 1/_p))/_w, 1/_w] + > e = exp(exp(_p - exp(-_p))/(1 - 1/_p)) - exp(exp(_p)) + > e.subs(Omega[0],O2[0]).subs(Omega[1],O2[1]) + -1/w + exp(exp(p)*exp(-exp(-p))/(1 - 1/p)) + + is really not what we want! + + So we do it the hard way and keep track of all the things we potentially + want to substitute by dummy variables. Consider the expression:: + + exp(x - exp(-x)) + exp(x) + x. + + The mrv set is {exp(x), exp(-x), exp(x - exp(-x))}. + We introduce corresponding dummy variables d1, d2, d3 and rewrite:: + + d3 + d1 + x. + + This class first of all keeps track of the mapping expr->variable, i.e. + will at this stage be a dictionary:: + + {exp(x): d1, exp(-x): d2, exp(x - exp(-x)): d3}. + + [It turns out to be more convenient this way round.] + But sometimes expressions in the mrv set have other expressions from the + mrv set as subexpressions, and we need to keep track of that as well. In + this case, d3 is really exp(x - d2), so rewrites at this stage is:: + + {d3: exp(x-d2)}. + + The function rewrite uses all this information to correctly rewrite our + expression in terms of w. In this case w can be chosen to be exp(-x), + i.e. d2. The correct rewriting then is:: + + exp(-w)/w + 1/w + x. + """ + def __init__(self): + self.rewrites = {} + + def __repr__(self): + return super().__repr__() + ', ' + self.rewrites.__repr__() + + def __getitem__(self, key): + if key not in self: + self[key] = Dummy() + return dict.__getitem__(self, key) + + def do_subs(self, e): + """Substitute the variables with expressions""" + for expr, var in self.items(): + e = e.xreplace({var: expr}) + return e + + def meets(self, s2): + """Tell whether or not self and s2 have non-empty intersection""" + return set(self.keys()).intersection(list(s2.keys())) != set() + + def union(self, s2, exps=None): + """Compute the union of self and s2, adjusting exps""" + res = self.copy() + tr = {} + for expr, var in s2.items(): + if expr in self: + if exps: + exps = exps.xreplace({var: res[expr]}) + tr[var] = res[expr] + else: + res[expr] = var + for var, rewr in s2.rewrites.items(): + res.rewrites[var] = rewr.xreplace(tr) + return res, exps + + def copy(self): + """Create a shallow copy of SubsSet""" + r = SubsSet() + r.rewrites = self.rewrites.copy() + for expr, var in self.items(): + r[expr] = var + return r + + +@debug +def mrv(e, x): + """Returns a SubsSet of most rapidly varying (mrv) subexpressions of 'e', + and e rewritten in terms of these""" + from sympy.simplify.powsimp import powsimp + e = powsimp(e, deep=True, combine='exp') + if not isinstance(e, Basic): + raise TypeError("e should be an instance of Basic") + if not e.has(x): + return SubsSet(), e + elif e == x: + s = SubsSet() + return s, s[x] + elif e.is_Mul or e.is_Add: + i, d = e.as_independent(x) # throw away x-independent terms + if d.func != e.func: + s, expr = mrv(d, x) + return s, e.func(i, expr) + a, b = d.as_two_terms() + s1, e1 = mrv(a, x) + s2, e2 = mrv(b, x) + return mrv_max1(s1, s2, e.func(i, e1, e2), x) + elif e.is_Pow and e.base != S.Exp1: + e1 = S.One + while e.is_Pow: + b1 = e.base + e1 *= e.exp + e = b1 + if b1 == 1: + return SubsSet(), b1 + if e1.has(x): + if limitinf(b1, x) is S.One: + if limitinf(e1, x).is_infinite is False: + return mrv(exp(e1*(b1 - 1)), x) + return mrv(exp(e1*log(b1)), x) + else: + s, expr = mrv(b1, x) + return s, expr**e1 + elif isinstance(e, log): + s, expr = mrv(e.args[0], x) + return s, log(expr) + elif isinstance(e, exp) or (e.is_Pow and e.base == S.Exp1): + # We know from the theory of this algorithm that exp(log(...)) may always + # be simplified here, and doing so is vital for termination. + if isinstance(e.exp, log): + return mrv(e.exp.args[0], x) + # if a product has an infinite factor the result will be + # infinite if there is no zero, otherwise NaN; here, we + # consider the result infinite if any factor is infinite + li = limitinf(e.exp, x) + if any(_.is_infinite for _ in Mul.make_args(li)): + s1 = SubsSet() + e1 = s1[e] + s2, e2 = mrv(e.exp, x) + su = s1.union(s2)[0] + su.rewrites[e1] = exp(e2) + return mrv_max3(s1, e1, s2, exp(e2), su, e1, x) + else: + s, expr = mrv(e.exp, x) + return s, exp(expr) + elif e.is_Function: + l = [mrv(a, x) for a in e.args] + l2 = [s for (s, _) in l if s != SubsSet()] + if len(l2) != 1: + # e.g. something like BesselJ(x, x) + raise NotImplementedError("MRV set computation for functions in" + " several variables not implemented.") + s, ss = l2[0], SubsSet() + args = [ss.do_subs(x[1]) for x in l] + return s, e.func(*args) + elif e.is_Derivative: + raise NotImplementedError("MRV set computation for derivatives" + " not implemented yet.") + raise NotImplementedError( + "Don't know how to calculate the mrv of '%s'" % e) + + +def mrv_max3(f, expsf, g, expsg, union, expsboth, x): + """ + Computes the maximum of two sets of expressions f and g, which + are in the same comparability class, i.e. max() compares (two elements of) + f and g and returns either (f, expsf) [if f is larger], (g, expsg) + [if g is larger] or (union, expsboth) [if f, g are of the same class]. + """ + if not isinstance(f, SubsSet): + raise TypeError("f should be an instance of SubsSet") + if not isinstance(g, SubsSet): + raise TypeError("g should be an instance of SubsSet") + if f == SubsSet(): + return g, expsg + elif g == SubsSet(): + return f, expsf + elif f.meets(g): + return union, expsboth + + c = compare(list(f.keys())[0], list(g.keys())[0], x) + if c == ">": + return f, expsf + elif c == "<": + return g, expsg + else: + if c != "=": + raise ValueError("c should be =") + return union, expsboth + + +def mrv_max1(f, g, exps, x): + """Computes the maximum of two sets of expressions f and g, which + are in the same comparability class, i.e. mrv_max1() compares (two elements of) + f and g and returns the set, which is in the higher comparability class + of the union of both, if they have the same order of variation. + Also returns exps, with the appropriate substitutions made. + """ + u, b = f.union(g, exps) + return mrv_max3(f, g.do_subs(exps), g, f.do_subs(exps), + u, b, x) + + +@debug +@cacheit +@timeit +def sign(e, x): + """ + Returns a sign of an expression e(x) for x->oo. + + :: + + e > 0 for x sufficiently large ... 1 + e == 0 for x sufficiently large ... 0 + e < 0 for x sufficiently large ... -1 + + The result of this function is currently undefined if e changes sign + arbitrarily often for arbitrarily large x (e.g. sin(x)). + + Note that this returns zero only if e is *constantly* zero + for x sufficiently large. [If e is constant, of course, this is just + the same thing as the sign of e.] + """ + if not isinstance(e, Basic): + raise TypeError("e should be an instance of Basic") + + if e.is_positive: + return 1 + elif e.is_negative: + return -1 + elif e.is_zero: + return 0 + + elif not e.has(x): + from sympy.simplify import logcombine + e = logcombine(e) + return _sign(e) + elif e == x: + return 1 + elif e.is_Mul: + a, b = e.as_two_terms() + sa = sign(a, x) + if not sa: + return 0 + return sa * sign(b, x) + elif isinstance(e, exp): + return 1 + elif e.is_Pow: + if e.base == S.Exp1: + return 1 + s = sign(e.base, x) + if s == 1: + return 1 + if e.exp.is_Integer: + return s**e.exp + elif isinstance(e, log): + return sign(e.args[0] - 1, x) + + # if all else fails, do it the hard way + c0, e0 = mrv_leadterm(e, x) + return sign(c0, x) + + +@debug +@timeit +@cacheit +def limitinf(e, x): + """Limit e(x) for x-> oo.""" + # rewrite e in terms of tractable functions only + + old = e + if not e.has(x): + return e # e is a constant + from sympy.simplify.powsimp import powdenest + from sympy.calculus.util import AccumBounds + if e.has(Order): + e = e.expand().removeO() + if not x.is_positive or x.is_integer: + # We make sure that x.is_positive is True and x.is_integer is None + # so we get all the correct mathematical behavior from the expression. + # We need a fresh variable. + p = Dummy('p', positive=True) + e = e.subs(x, p) + x = p + e = e.rewrite('tractable', deep=True, limitvar=x) + e = powdenest(e) + if isinstance(e, AccumBounds): + if mrv_leadterm(e.min, x) != mrv_leadterm(e.max, x): + raise NotImplementedError + c0, e0 = mrv_leadterm(e.min, x) + else: + c0, e0 = mrv_leadterm(e, x) + sig = sign(e0, x) + if sig == 1: + return S.Zero # e0>0: lim f = 0 + elif sig == -1: # e0<0: lim f = +-oo (the sign depends on the sign of c0) + if c0.match(I*Wild("a", exclude=[I])): + return c0*oo + s = sign(c0, x) + # the leading term shouldn't be 0: + if s == 0: + raise ValueError("Leading term should not be 0") + return s*oo + elif sig == 0: + if c0 == old: + c0 = c0.cancel() + return limitinf(c0, x) # e0=0: lim f = lim c0 + else: + raise ValueError("{} could not be evaluated".format(sig)) + + +def moveup2(s, x): + r = SubsSet() + for expr, var in s.items(): + r[expr.xreplace({x: exp(x)})] = var + for var, expr in s.rewrites.items(): + r.rewrites[var] = s.rewrites[var].xreplace({x: exp(x)}) + return r + + +def moveup(l, x): + return [e.xreplace({x: exp(x)}) for e in l] + + +@debug +@timeit +def calculate_series(e, x, logx=None): + """ Calculates at least one term of the series of ``e`` in ``x``. + + This is a place that fails most often, so it is in its own function. + """ + + SymPyDeprecationWarning( + feature="calculate_series", + useinstead="series() with suitable n, or as_leading_term", + issue=21838, + deprecated_since_version="1.12" + ).warn() + + from sympy.simplify.powsimp import powdenest + + for t in e.lseries(x, logx=logx): + # bottom_up function is required for a specific case - when e is + # -exp(p/(p + 1)) + exp(-p**2/(p + 1) + p) + t = bottom_up(t, lambda w: + getattr(w, 'normal', lambda: w)()) + # And the expression + # `(-sin(1/x) + sin((x + exp(x))*exp(-x)/x))*exp(x)` + # from the first test of test_gruntz_eval_special needs to + # be expanded. But other forms need to be have at least + # factor_terms applied. `factor` accomplishes both and is + # faster than using `factor_terms` for the gruntz suite. It + # does not appear that use of `cancel` is necessary. + # t = cancel(t, expand=False) + t = t.factor() + + if t.has(exp) and t.has(log): + t = powdenest(t) + + if not t.is_zero: + break + + return t + + +@debug +@timeit +@cacheit +def mrv_leadterm(e, x): + """Returns (c0, e0) for e.""" + Omega = SubsSet() + if not e.has(x): + return (e, S.Zero) + if Omega == SubsSet(): + Omega, exps = mrv(e, x) + if not Omega: + # e really does not depend on x after simplification + return exps, S.Zero + if x in Omega: + # move the whole omega up (exponentiate each term): + Omega_up = moveup2(Omega, x) + exps_up = moveup([exps], x)[0] + # NOTE: there is no need to move this down! + Omega = Omega_up + exps = exps_up + # + # The positive dummy, w, is used here so log(w*2) etc. will expand; + # a unique dummy is needed in this algorithm + # + # For limits of complex functions, the algorithm would have to be + # improved, or just find limits of Re and Im components separately. + # + w = Dummy("w", positive=True) + f, logw = rewrite(exps, Omega, x, w) + try: + lt = f.leadterm(w, logx=logw) + except (NotImplementedError, PoleError, ValueError): + n0 = 1 + _series = Order(1) + incr = S.One + while _series.is_Order: + _series = f._eval_nseries(w, n=n0+incr, logx=logw) + incr *= 2 + series = _series.expand().removeO() + try: + lt = series.leadterm(w, logx=logw) + except (NotImplementedError, PoleError, ValueError): + lt = f.as_coeff_exponent(w) + if lt[0].has(w): + base = f.as_base_exp()[0].as_coeff_exponent(w) + ex = f.as_base_exp()[1] + lt = (base[0]**ex, base[1]*ex) + return (lt[0].subs(log(w), logw), lt[1]) + + +def build_expression_tree(Omega, rewrites): + r""" Helper function for rewrite. + + We need to sort Omega (mrv set) so that we replace an expression before + we replace any expression in terms of which it has to be rewritten:: + + e1 ---> e2 ---> e3 + \ + -> e4 + + Here we can do e1, e2, e3, e4 or e1, e2, e4, e3. + To do this we assemble the nodes into a tree, and sort them by height. + + This function builds the tree, rewrites then sorts the nodes. + """ + class Node: + def __init__(self): + self.before = [] + self.expr = None + self.var = None + def ht(self): + return reduce(lambda x, y: x + y, + [x.ht() for x in self.before], 1) + nodes = {} + for expr, v in Omega: + n = Node() + n.var = v + n.expr = expr + nodes[v] = n + for _, v in Omega: + if v in rewrites: + n = nodes[v] + r = rewrites[v] + for _, v2 in Omega: + if r.has(v2): + n.before.append(nodes[v2]) + + return nodes + + +@debug +@timeit +def rewrite(e, Omega, x, wsym): + """e(x) ... the function + Omega ... the mrv set + wsym ... the symbol which is going to be used for w + + Returns the rewritten e in terms of w and log(w). See test_rewrite1() + for examples and correct results. + """ + + from sympy import AccumBounds + if not isinstance(Omega, SubsSet): + raise TypeError("Omega should be an instance of SubsSet") + if len(Omega) == 0: + raise ValueError("Length cannot be 0") + # all items in Omega must be exponentials + for t in Omega.keys(): + if not isinstance(t, exp): + raise ValueError("Value should be exp") + rewrites = Omega.rewrites + Omega = list(Omega.items()) + + nodes = build_expression_tree(Omega, rewrites) + Omega.sort(key=lambda x: nodes[x[1]].ht(), reverse=True) + + # make sure we know the sign of each exp() term; after the loop, + # g is going to be the "w" - the simplest one in the mrv set + for g, _ in Omega: + sig = sign(g.exp, x) + if sig != 1 and sig != -1 and not sig.has(AccumBounds): + raise NotImplementedError('Result depends on the sign of %s' % sig) + if sig == 1: + wsym = 1/wsym # if g goes to oo, substitute 1/w + # O2 is a list, which results by rewriting each item in Omega using "w" + O2 = [] + denominators = [] + for f, var in Omega: + c = limitinf(f.exp/g.exp, x) + if c.is_Rational: + denominators.append(c.q) + arg = f.exp + if var in rewrites: + if not isinstance(rewrites[var], exp): + raise ValueError("Value should be exp") + arg = rewrites[var].args[0] + O2.append((var, exp((arg - c*g.exp).expand())*wsym**c)) + + # Remember that Omega contains subexpressions of "e". So now we find + # them in "e" and substitute them for our rewriting, stored in O2 + + # the following powsimp is necessary to automatically combine exponentials, + # so that the .xreplace() below succeeds: + # TODO this should not be necessary + from sympy.simplify.powsimp import powsimp + f = powsimp(e, deep=True, combine='exp') + for a, b in O2: + f = f.xreplace({a: b}) + + for _, var in Omega: + assert not f.has(var) + + # finally compute the logarithm of w (logw). + logw = g.exp + if sig == 1: + logw = -logw # log(w)->log(1/w)=-log(w) + + # Some parts of SymPy have difficulty computing series expansions with + # non-integral exponents. The following heuristic improves the situation: + exponent = reduce(ilcm, denominators, 1) + f = f.subs({wsym: wsym**exponent}) + logw /= exponent + + # bottom_up function is required for a specific case - when f is + # -exp(p/(p + 1)) + exp(-p**2/(p + 1) + p). No current simplification + # methods reduce this to 0 while not expanding polynomials. + f = bottom_up(f, lambda w: getattr(w, 'normal', lambda: w)()) + f = expand_mul(f) + + return f, logw + + +def gruntz(e, z, z0, dir="+"): + """ + Compute the limit of e(z) at the point z0 using the Gruntz algorithm. + + Explanation + =========== + + ``z0`` can be any expression, including oo and -oo. + + For ``dir="+"`` (default) it calculates the limit from the right + (z->z0+) and for ``dir="-"`` the limit from the left (z->z0-). For infinite z0 + (oo or -oo), the dir argument does not matter. + + This algorithm is fully described in the module docstring in the gruntz.py + file. It relies heavily on the series expansion. Most frequently, gruntz() + is only used if the faster limit() function (which uses heuristics) fails. + """ + if not z.is_symbol: + raise NotImplementedError("Second argument must be a Symbol") + + # convert all limits to the limit z->oo; sign of z is handled in limitinf + r = None + if z0 in (oo, I*oo): + e0 = e + elif z0 in (-oo, -I*oo): + e0 = e.subs(z, -z) + else: + if str(dir) == "-": + e0 = e.subs(z, z0 - 1/z) + elif str(dir) == "+": + e0 = e.subs(z, z0 + 1/z) + else: + raise NotImplementedError("dir must be '+' or '-'") + + r = limitinf(e0, z) + + # This is a bit of a heuristic for nice results... we always rewrite + # tractable functions in terms of familiar intractable ones. + # It might be nicer to rewrite the exactly to what they were initially, + # but that would take some work to implement. + return r.rewrite('intractable', deep=True) diff --git a/lib/python3.12/site-packages/sympy/series/kauers.py b/lib/python3.12/site-packages/sympy/series/kauers.py new file mode 100644 index 0000000000000000000000000000000000000000..9e9645ff15ee5ae3c1d1c8709f76aed1b366f50a --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/kauers.py @@ -0,0 +1,51 @@ +def finite_diff(expression, variable, increment=1): + """ + Takes as input a polynomial expression and the variable used to construct + it and returns the difference between function's value when the input is + incremented to 1 and the original function value. If you want an increment + other than one supply it as a third argument. + + Examples + ======== + + >>> from sympy.abc import x, y, z + >>> from sympy.series.kauers import finite_diff + >>> finite_diff(x**2, x) + 2*x + 1 + >>> finite_diff(y**3 + 2*y**2 + 3*y + 4, y) + 3*y**2 + 7*y + 6 + >>> finite_diff(x**2 + 3*x + 8, x, 2) + 4*x + 10 + >>> finite_diff(z**3 + 8*z, z, 3) + 9*z**2 + 27*z + 51 + """ + expression = expression.expand() + expression2 = expression.subs(variable, variable + increment) + expression2 = expression2.expand() + return expression2 - expression + +def finite_diff_kauers(sum): + """ + Takes as input a Sum instance and returns the difference between the sum + with the upper index incremented by 1 and the original sum. For example, + if S(n) is a sum, then finite_diff_kauers will return S(n + 1) - S(n). + + Examples + ======== + + >>> from sympy.series.kauers import finite_diff_kauers + >>> from sympy import Sum + >>> from sympy.abc import x, y, m, n, k + >>> finite_diff_kauers(Sum(k, (k, 1, n))) + n + 1 + >>> finite_diff_kauers(Sum(1/k, (k, 1, n))) + 1/(n + 1) + >>> finite_diff_kauers(Sum((x*y**2), (x, 1, n), (y, 1, m))) + (m + 1)**2*(n + 1) + >>> finite_diff_kauers(Sum((x*y), (x, 1, m), (y, 1, n))) + (m + 1)*(n + 1) + """ + function = sum.function + for l in sum.limits: + function = function.subs(l[0], l[- 1] + 1) + return function diff --git a/lib/python3.12/site-packages/sympy/series/limits.py b/lib/python3.12/site-packages/sympy/series/limits.py new file mode 100644 index 0000000000000000000000000000000000000000..b3976e5512274968eafdf098b4c2d7285a05959e --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/limits.py @@ -0,0 +1,385 @@ +from sympy.calculus.accumulationbounds import AccumBounds +from sympy.core import S, Symbol, Add, sympify, Expr, PoleError, Mul +from sympy.core.exprtools import factor_terms +from sympy.core.numbers import Float, _illegal +from sympy.functions.combinatorial.factorials import factorial +from sympy.functions.elementary.complexes import (Abs, sign, arg, re) +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.special.gamma_functions import gamma +from sympy.polys import PolynomialError, factor +from sympy.series.order import Order +from .gruntz import gruntz + +def limit(e, z, z0, dir="+"): + """Computes the limit of ``e(z)`` at the point ``z0``. + + Parameters + ========== + + e : expression, the limit of which is to be taken + + z : symbol representing the variable in the limit. + Other symbols are treated as constants. Multivariate limits + are not supported. + + z0 : the value toward which ``z`` tends. Can be any expression, + including ``oo`` and ``-oo``. + + dir : string, optional (default: "+") + The limit is bi-directional if ``dir="+-"``, from the right + (z->z0+) if ``dir="+"``, and from the left (z->z0-) if + ``dir="-"``. For infinite ``z0`` (``oo`` or ``-oo``), the ``dir`` + argument is determined from the direction of the infinity + (i.e., ``dir="-"`` for ``oo``). + + Examples + ======== + + >>> from sympy import limit, sin, oo + >>> from sympy.abc import x + >>> limit(sin(x)/x, x, 0) + 1 + >>> limit(1/x, x, 0) # default dir='+' + oo + >>> limit(1/x, x, 0, dir="-") + -oo + >>> limit(1/x, x, 0, dir='+-') + zoo + >>> limit(1/x, x, oo) + 0 + + Notes + ===== + + First we try some heuristics for easy and frequent cases like "x", "1/x", + "x**2" and similar, so that it's fast. For all other cases, we use the + Gruntz algorithm (see the gruntz() function). + + See Also + ======== + + limit_seq : returns the limit of a sequence. + """ + + return Limit(e, z, z0, dir).doit(deep=False) + + +def heuristics(e, z, z0, dir): + """Computes the limit of an expression term-wise. + Parameters are the same as for the ``limit`` function. + Works with the arguments of expression ``e`` one by one, computing + the limit of each and then combining the results. This approach + works only for simple limits, but it is fast. + """ + + rv = None + if z0 is S.Infinity: + rv = limit(e.subs(z, 1/z), z, S.Zero, "+") + if isinstance(rv, Limit): + return + elif e.is_Mul or e.is_Add or e.is_Pow or e.is_Function: + r = [] + from sympy.simplify.simplify import together + for a in e.args: + l = limit(a, z, z0, dir) + if l.has(S.Infinity) and l.is_finite is None: + if isinstance(e, Add): + m = factor_terms(e) + if not isinstance(m, Mul): # try together + m = together(m) + if not isinstance(m, Mul): # try factor if the previous methods failed + m = factor(e) + if isinstance(m, Mul): + return heuristics(m, z, z0, dir) + return + return + elif isinstance(l, Limit): + return + elif l is S.NaN: + return + else: + r.append(l) + if r: + rv = e.func(*r) + if rv is S.NaN and e.is_Mul and any(isinstance(rr, AccumBounds) for rr in r): + r2 = [] + e2 = [] + for ii, rval in enumerate(r): + if isinstance(rval, AccumBounds): + r2.append(rval) + else: + e2.append(e.args[ii]) + + if len(e2) > 0: + e3 = Mul(*e2).simplify() + l = limit(e3, z, z0, dir) + rv = l * Mul(*r2) + + if rv is S.NaN: + try: + from sympy.simplify.ratsimp import ratsimp + rat_e = ratsimp(e) + except PolynomialError: + return + if rat_e is S.NaN or rat_e == e: + return + return limit(rat_e, z, z0, dir) + return rv + + +class Limit(Expr): + """Represents an unevaluated limit. + + Examples + ======== + + >>> from sympy import Limit, sin + >>> from sympy.abc import x + >>> Limit(sin(x)/x, x, 0) + Limit(sin(x)/x, x, 0, dir='+') + >>> Limit(1/x, x, 0, dir="-") + Limit(1/x, x, 0, dir='-') + + """ + + def __new__(cls, e, z, z0, dir="+"): + e = sympify(e) + z = sympify(z) + z0 = sympify(z0) + + if z0 in (S.Infinity, S.ImaginaryUnit*S.Infinity): + dir = "-" + elif z0 in (S.NegativeInfinity, S.ImaginaryUnit*S.NegativeInfinity): + dir = "+" + + if(z0.has(z)): + raise NotImplementedError("Limits approaching a variable point are" + " not supported (%s -> %s)" % (z, z0)) + if isinstance(dir, str): + dir = Symbol(dir) + elif not isinstance(dir, Symbol): + raise TypeError("direction must be of type basestring or " + "Symbol, not %s" % type(dir)) + if str(dir) not in ('+', '-', '+-'): + raise ValueError("direction must be one of '+', '-' " + "or '+-', not %s" % dir) + + obj = Expr.__new__(cls) + obj._args = (e, z, z0, dir) + return obj + + + @property + def free_symbols(self): + e = self.args[0] + isyms = e.free_symbols + isyms.difference_update(self.args[1].free_symbols) + isyms.update(self.args[2].free_symbols) + return isyms + + + def pow_heuristics(self, e): + _, z, z0, _ = self.args + b1, e1 = e.base, e.exp + if not b1.has(z): + res = limit(e1*log(b1), z, z0) + return exp(res) + + ex_lim = limit(e1, z, z0) + base_lim = limit(b1, z, z0) + + if base_lim is S.One: + if ex_lim in (S.Infinity, S.NegativeInfinity): + res = limit(e1*(b1 - 1), z, z0) + return exp(res) + if base_lim is S.NegativeInfinity and ex_lim is S.Infinity: + return S.ComplexInfinity + + + def doit(self, **hints): + """Evaluates the limit. + + Parameters + ========== + + deep : bool, optional (default: True) + Invoke the ``doit`` method of the expressions involved before + taking the limit. + + hints : optional keyword arguments + To be passed to ``doit`` methods; only used if deep is True. + """ + + e, z, z0, dir = self.args + + if str(dir) == '+-': + r = limit(e, z, z0, dir='+') + l = limit(e, z, z0, dir='-') + if isinstance(r, Limit) and isinstance(l, Limit): + if r.args[0] == l.args[0]: + return self + if r == l: + return l + if r.is_infinite and l.is_infinite: + return S.ComplexInfinity + raise ValueError("The limit does not exist since " + "left hand limit = %s and right hand limit = %s" + % (l, r)) + + if z0 is S.ComplexInfinity: + raise NotImplementedError("Limits at complex " + "infinity are not implemented") + + if z0.is_infinite: + cdir = sign(z0) + cdir = cdir/abs(cdir) + e = e.subs(z, cdir*z) + dir = "-" + z0 = S.Infinity + + if hints.get('deep', True): + e = e.doit(**hints) + z = z.doit(**hints) + z0 = z0.doit(**hints) + + if e == z: + return z0 + + if not e.has(z): + return e + + if z0 is S.NaN: + return S.NaN + + if e.has(*_illegal): + return self + + if e.is_Order: + return Order(limit(e.expr, z, z0), *e.args[1:]) + + cdir = 0 + if str(dir) == "+": + cdir = 1 + elif str(dir) == "-": + cdir = -1 + + def set_signs(expr): + if not expr.args: + return expr + newargs = tuple(set_signs(arg) for arg in expr.args) + if newargs != expr.args: + expr = expr.func(*newargs) + abs_flag = isinstance(expr, Abs) + arg_flag = isinstance(expr, arg) + sign_flag = isinstance(expr, sign) + if abs_flag or sign_flag or arg_flag: + sig = limit(expr.args[0], z, z0, dir) + if sig.is_zero: + sig = limit(1/expr.args[0], z, z0, dir) + if sig.is_extended_real: + if (sig < 0) == True: + return (-expr.args[0] if abs_flag else + S.NegativeOne if sign_flag else S.Pi) + elif (sig > 0) == True: + return (expr.args[0] if abs_flag else + S.One if sign_flag else S.Zero) + return expr + + if e.has(Float): + # Convert floats like 0.5 to exact SymPy numbers like S.Half, to + # prevent rounding errors which can lead to unexpected execution + # of conditional blocks that work on comparisons + # Also see comments in https://github.com/sympy/sympy/issues/19453 + from sympy.simplify.simplify import nsimplify + e = nsimplify(e) + e = set_signs(e) + + + if e.is_meromorphic(z, z0): + if z0 is S.Infinity: + newe = e.subs(z, 1/z) + # cdir changes sign as oo- should become 0+ + cdir = -cdir + else: + newe = e.subs(z, z + z0) + try: + coeff, ex = newe.leadterm(z, cdir=cdir) + except ValueError: + pass + else: + if ex > 0: + return S.Zero + elif ex == 0: + return coeff + if cdir == 1 or not(int(ex) & 1): + return S.Infinity*sign(coeff) + elif cdir == -1: + return S.NegativeInfinity*sign(coeff) + else: + return S.ComplexInfinity + + if z0 is S.Infinity: + if e.is_Mul: + e = factor_terms(e) + newe = e.subs(z, 1/z) + # cdir changes sign as oo- should become 0+ + cdir = -cdir + else: + newe = e.subs(z, z + z0) + try: + coeff, ex = newe.leadterm(z, cdir=cdir) + except (ValueError, NotImplementedError, PoleError): + # The NotImplementedError catching is for custom functions + from sympy.simplify.powsimp import powsimp + e = powsimp(e) + if e.is_Pow: + r = self.pow_heuristics(e) + if r is not None: + return r + try: + coeff = newe.as_leading_term(z, cdir=cdir) + if coeff != newe and (coeff.has(exp) or coeff.has(S.Exp1)): + return gruntz(coeff, z, 0, "-" if re(cdir).is_negative else "+") + except (ValueError, NotImplementedError, PoleError): + pass + else: + if isinstance(coeff, AccumBounds) and ex == S.Zero: + return coeff + if coeff.has(S.Infinity, S.NegativeInfinity, S.ComplexInfinity, S.NaN): + return self + if not coeff.has(z): + if ex.is_positive: + return S.Zero + elif ex == 0: + return coeff + elif ex.is_negative: + if cdir == 1: + return S.Infinity*sign(coeff) + elif cdir == -1: + return S.NegativeInfinity*sign(coeff)*S.NegativeOne**(S.One + ex) + else: + return S.ComplexInfinity + else: + raise NotImplementedError("Not sure of sign of %s" % ex) + + # gruntz fails on factorials but works with the gamma function + # If no factorial term is present, e should remain unchanged. + # factorial is defined to be zero for negative inputs (which + # differs from gamma) so only rewrite for positive z0. + if z0.is_extended_positive: + e = e.rewrite(factorial, gamma) + + l = None + + try: + r = gruntz(e, z, z0, dir) + if r is S.NaN or l is S.NaN: + raise PoleError() + except (PoleError, ValueError): + if l is not None: + raise + r = heuristics(e, z, z0, dir) + if r is None: + return self + + return r diff --git a/lib/python3.12/site-packages/sympy/series/limitseq.py b/lib/python3.12/site-packages/sympy/series/limitseq.py new file mode 100644 index 0000000000000000000000000000000000000000..ceac4e7b63bfc09d9dfc26c12c7d2acc8b8d44da --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/limitseq.py @@ -0,0 +1,257 @@ +"""Limits of sequences""" + +from sympy.calculus.accumulationbounds import AccumulationBounds +from sympy.core.add import Add +from sympy.core.function import PoleError +from sympy.core.power import Pow +from sympy.core.singleton import S +from sympy.core.symbol import Dummy +from sympy.core.sympify import sympify +from sympy.functions.combinatorial.numbers import fibonacci +from sympy.functions.combinatorial.factorials import factorial, subfactorial +from sympy.functions.special.gamma_functions import gamma +from sympy.functions.elementary.complexes import Abs +from sympy.functions.elementary.miscellaneous import Max, Min +from sympy.functions.elementary.trigonometric import cos, sin +from sympy.series.limits import Limit + + +def difference_delta(expr, n=None, step=1): + """Difference Operator. + + Explanation + =========== + + Discrete analog of differential operator. Given a sequence x[n], + returns the sequence x[n + step] - x[n]. + + Examples + ======== + + >>> from sympy import difference_delta as dd + >>> from sympy.abc import n + >>> dd(n*(n + 1), n) + 2*n + 2 + >>> dd(n*(n + 1), n, 2) + 4*n + 6 + + References + ========== + + .. [1] https://reference.wolfram.com/language/ref/DifferenceDelta.html + """ + expr = sympify(expr) + + if n is None: + f = expr.free_symbols + if len(f) == 1: + n = f.pop() + elif len(f) == 0: + return S.Zero + else: + raise ValueError("Since there is more than one variable in the" + " expression, a variable must be supplied to" + " take the difference of %s" % expr) + step = sympify(step) + if step.is_number is False or step.is_finite is False: + raise ValueError("Step should be a finite number.") + + if hasattr(expr, '_eval_difference_delta'): + result = expr._eval_difference_delta(n, step) + if result: + return result + + return expr.subs(n, n + step) - expr + + +def dominant(expr, n): + """Finds the dominant term in a sum, that is a term that dominates + every other term. + + Explanation + =========== + + If limit(a/b, n, oo) is oo then a dominates b. + If limit(a/b, n, oo) is 0 then b dominates a. + Otherwise, a and b are comparable. + + If there is no unique dominant term, then returns ``None``. + + Examples + ======== + + >>> from sympy import Sum + >>> from sympy.series.limitseq import dominant + >>> from sympy.abc import n, k + >>> dominant(5*n**3 + 4*n**2 + n + 1, n) + 5*n**3 + >>> dominant(2**n + Sum(k, (k, 0, n)), n) + 2**n + + See Also + ======== + + sympy.series.limitseq.dominant + """ + terms = Add.make_args(expr.expand(func=True)) + term0 = terms[-1] + comp = [term0] # comparable terms + for t in terms[:-1]: + r = term0/t + e = r.gammasimp() + if e == r: + e = r.factor() + l = limit_seq(e, n) + if l is None: + return None + elif l.is_zero: + term0 = t + comp = [term0] + elif l not in [S.Infinity, S.NegativeInfinity]: + comp.append(t) + if len(comp) > 1: + return None + return term0 + + +def _limit_inf(expr, n): + try: + return Limit(expr, n, S.Infinity).doit(deep=False) + except (NotImplementedError, PoleError): + return None + + +def _limit_seq(expr, n, trials): + from sympy.concrete.summations import Sum + + for i in range(trials): + if not expr.has(Sum): + result = _limit_inf(expr, n) + if result is not None: + return result + + num, den = expr.as_numer_denom() + if not den.has(n) or not num.has(n): + result = _limit_inf(expr.doit(), n) + if result is not None: + return result + return None + + num, den = (difference_delta(t.expand(), n) for t in [num, den]) + expr = (num / den).gammasimp() + + if not expr.has(Sum): + result = _limit_inf(expr, n) + if result is not None: + return result + + num, den = expr.as_numer_denom() + + num = dominant(num, n) + if num is None: + return None + + den = dominant(den, n) + if den is None: + return None + + expr = (num / den).gammasimp() + + +def limit_seq(expr, n=None, trials=5): + """Finds the limit of a sequence as index ``n`` tends to infinity. + + Parameters + ========== + + expr : Expr + SymPy expression for the ``n-th`` term of the sequence + n : Symbol, optional + The index of the sequence, an integer that tends to positive + infinity. If None, inferred from the expression unless it has + multiple symbols. + trials: int, optional + The algorithm is highly recursive. ``trials`` is a safeguard from + infinite recursion in case the limit is not easily computed by the + algorithm. Try increasing ``trials`` if the algorithm returns ``None``. + + Admissible Terms + ================ + + The algorithm is designed for sequences built from rational functions, + indefinite sums, and indefinite products over an indeterminate n. Terms of + alternating sign are also allowed, but more complex oscillatory behavior is + not supported. + + Examples + ======== + + >>> from sympy import limit_seq, Sum, binomial + >>> from sympy.abc import n, k, m + >>> limit_seq((5*n**3 + 3*n**2 + 4) / (3*n**3 + 4*n - 5), n) + 5/3 + >>> limit_seq(binomial(2*n, n) / Sum(binomial(2*k, k), (k, 1, n)), n) + 3/4 + >>> limit_seq(Sum(k**2 * Sum(2**m/m, (m, 1, k)), (k, 1, n)) / (2**n*n), n) + 4 + + See Also + ======== + + sympy.series.limitseq.dominant + + References + ========== + + .. [1] Computing Limits of Sequences - Manuel Kauers + """ + + from sympy.concrete.summations import Sum + if n is None: + free = expr.free_symbols + if len(free) == 1: + n = free.pop() + elif not free: + return expr + else: + raise ValueError("Expression has more than one variable. " + "Please specify a variable.") + elif n not in expr.free_symbols: + return expr + + expr = expr.rewrite(fibonacci, S.GoldenRatio) + expr = expr.rewrite(factorial, subfactorial, gamma) + n_ = Dummy("n", integer=True, positive=True) + n1 = Dummy("n", odd=True, positive=True) + n2 = Dummy("n", even=True, positive=True) + + # If there is a negative term raised to a power involving n, or a + # trigonometric function, then consider even and odd n separately. + powers = (p.as_base_exp() for p in expr.atoms(Pow)) + if (any(b.is_negative and e.has(n) for b, e in powers) or + expr.has(cos, sin)): + L1 = _limit_seq(expr.xreplace({n: n1}), n1, trials) + if L1 is not None: + L2 = _limit_seq(expr.xreplace({n: n2}), n2, trials) + if L1 != L2: + if L1.is_comparable and L2.is_comparable: + return AccumulationBounds(Min(L1, L2), Max(L1, L2)) + else: + return None + else: + L1 = _limit_seq(expr.xreplace({n: n_}), n_, trials) + if L1 is not None: + return L1 + else: + if expr.is_Add: + limits = [limit_seq(term, n, trials) for term in expr.args] + if any(result is None for result in limits): + return None + else: + return Add(*limits) + # Maybe the absolute value is easier to deal with (though not if + # it has a Sum). If it tends to 0, the limit is 0. + elif not expr.has(Sum): + lim = _limit_seq(Abs(expr.xreplace({n: n_})), n_, trials) + if lim is not None and lim.is_zero: + return S.Zero diff --git a/lib/python3.12/site-packages/sympy/series/order.py b/lib/python3.12/site-packages/sympy/series/order.py new file mode 100644 index 0000000000000000000000000000000000000000..9bf6c83a1119648c93cffa76cf62b33b6f3176bf --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/order.py @@ -0,0 +1,517 @@ +from sympy.core import S, sympify, Expr, Dummy, Add, Mul +from sympy.core.cache import cacheit +from sympy.core.containers import Tuple +from sympy.core.function import Function, PoleError, expand_power_base, expand_log +from sympy.core.sorting import default_sort_key +from sympy.functions.elementary.exponential import exp, log +from sympy.sets.sets import Complement +from sympy.utilities.iterables import uniq, is_sequence + + +class Order(Expr): + r""" Represents the limiting behavior of some function. + + Explanation + =========== + + The order of a function characterizes the function based on the limiting + behavior of the function as it goes to some limit. Only taking the limit + point to be a number is currently supported. This is expressed in + big O notation [1]_. + + The formal definition for the order of a function `g(x)` about a point `a` + is such that `g(x) = O(f(x))` as `x \rightarrow a` if and only if there + exists a `\delta > 0` and an `M > 0` such that `|g(x)| \leq M|f(x)|` for + `|x-a| < \delta`. This is equivalent to `\limsup_{x \rightarrow a} + |g(x)/f(x)| < \infty`. + + Let's illustrate it on the following example by taking the expansion of + `\sin(x)` about 0: + + .. math :: + \sin(x) = x - x^3/3! + O(x^5) + + where in this case `O(x^5) = x^5/5! - x^7/7! + \cdots`. By the definition + of `O`, there is a `\delta > 0` and an `M` such that: + + .. math :: + |x^5/5! - x^7/7! + ....| <= M|x^5| \text{ for } |x| < \delta + + or by the alternate definition: + + .. math :: + \lim_{x \rightarrow 0} | (x^5/5! - x^7/7! + ....) / x^5| < \infty + + which surely is true, because + + .. math :: + \lim_{x \rightarrow 0} | (x^5/5! - x^7/7! + ....) / x^5| = 1/5! + + + As it is usually used, the order of a function can be intuitively thought + of representing all terms of powers greater than the one specified. For + example, `O(x^3)` corresponds to any terms proportional to `x^3, + x^4,\ldots` and any higher power. For a polynomial, this leaves terms + proportional to `x^2`, `x` and constants. + + Examples + ======== + + >>> from sympy import O, oo, cos, pi + >>> from sympy.abc import x, y + + >>> O(x + x**2) + O(x) + >>> O(x + x**2, (x, 0)) + O(x) + >>> O(x + x**2, (x, oo)) + O(x**2, (x, oo)) + + >>> O(1 + x*y) + O(1, x, y) + >>> O(1 + x*y, (x, 0), (y, 0)) + O(1, x, y) + >>> O(1 + x*y, (x, oo), (y, oo)) + O(x*y, (x, oo), (y, oo)) + + >>> O(1) in O(1, x) + True + >>> O(1, x) in O(1) + False + >>> O(x) in O(1, x) + True + >>> O(x**2) in O(x) + True + + >>> O(x)*x + O(x**2) + >>> O(x) - O(x) + O(x) + >>> O(cos(x)) + O(1) + >>> O(cos(x), (x, pi/2)) + O(x - pi/2, (x, pi/2)) + + References + ========== + + .. [1] `Big O notation `_ + + Notes + ===== + + In ``O(f(x), x)`` the expression ``f(x)`` is assumed to have a leading + term. ``O(f(x), x)`` is automatically transformed to + ``O(f(x).as_leading_term(x),x)``. + + ``O(expr*f(x), x)`` is ``O(f(x), x)`` + + ``O(expr, x)`` is ``O(1)`` + + ``O(0, x)`` is 0. + + Multivariate O is also supported: + + ``O(f(x, y), x, y)`` is transformed to + ``O(f(x, y).as_leading_term(x,y).as_leading_term(y), x, y)`` + + In the multivariate case, it is assumed the limits w.r.t. the various + symbols commute. + + If no symbols are passed then all symbols in the expression are used + and the limit point is assumed to be zero. + + """ + + is_Order = True + + __slots__ = () + + @cacheit + def __new__(cls, expr, *args, **kwargs): + expr = sympify(expr) + + if not args: + if expr.is_Order: + variables = expr.variables + point = expr.point + else: + variables = list(expr.free_symbols) + point = [S.Zero]*len(variables) + else: + args = list(args if is_sequence(args) else [args]) + variables, point = [], [] + if is_sequence(args[0]): + for a in args: + v, p = list(map(sympify, a)) + variables.append(v) + point.append(p) + else: + variables = list(map(sympify, args)) + point = [S.Zero]*len(variables) + + if not all(v.is_symbol for v in variables): + raise TypeError('Variables are not symbols, got %s' % variables) + + if len(list(uniq(variables))) != len(variables): + raise ValueError('Variables are supposed to be unique symbols, got %s' % variables) + + if expr.is_Order: + expr_vp = dict(expr.args[1:]) + new_vp = dict(expr_vp) + vp = dict(zip(variables, point)) + for v, p in vp.items(): + if v in new_vp.keys(): + if p != new_vp[v]: + raise NotImplementedError( + "Mixing Order at different points is not supported.") + else: + new_vp[v] = p + if set(expr_vp.keys()) == set(new_vp.keys()): + return expr + else: + variables = list(new_vp.keys()) + point = [new_vp[v] for v in variables] + + if expr is S.NaN: + return S.NaN + + if any(x in p.free_symbols for x in variables for p in point): + raise ValueError('Got %s as a point.' % point) + + if variables: + if any(p != point[0] for p in point): + raise NotImplementedError( + "Multivariable orders at different points are not supported.") + if point[0] in (S.Infinity, S.Infinity*S.ImaginaryUnit): + s = {k: 1/Dummy() for k in variables} + rs = {1/v: 1/k for k, v in s.items()} + ps = [S.Zero for p in point] + elif point[0] in (S.NegativeInfinity, S.NegativeInfinity*S.ImaginaryUnit): + s = {k: -1/Dummy() for k in variables} + rs = {-1/v: -1/k for k, v in s.items()} + ps = [S.Zero for p in point] + elif point[0] is not S.Zero: + s = {k: Dummy() + point[0] for k in variables} + rs = {(v - point[0]).together(): k - point[0] for k, v in s.items()} + ps = [S.Zero for p in point] + else: + s = () + rs = () + ps = list(point) + + expr = expr.subs(s) + + if expr.is_Add: + expr = expr.factor() + + if s: + args = tuple([r[0] for r in rs.items()]) + else: + args = tuple(variables) + + if len(variables) > 1: + # XXX: better way? We need this expand() to + # workaround e.g: expr = x*(x + y). + # (x*(x + y)).as_leading_term(x, y) currently returns + # x*y (wrong order term!). That's why we want to deal with + # expand()'ed expr (handled in "if expr.is_Add" branch below). + expr = expr.expand() + + old_expr = None + while old_expr != expr: + old_expr = expr + if expr.is_Add: + lst = expr.extract_leading_order(args) + expr = Add(*[f.expr for (e, f) in lst]) + + elif expr: + try: + expr = expr.as_leading_term(*args) + except PoleError: + if isinstance(expr, Function) or\ + all(isinstance(arg, Function) for arg in expr.args): + # It is not possible to simplify an expression + # containing only functions (which raise error on + # call to leading term) further + pass + else: + orders = [] + pts = tuple(zip(args, ps)) + for arg in expr.args: + try: + lt = arg.as_leading_term(*args) + except PoleError: + lt = arg + if lt not in args: + order = Order(lt) + else: + order = Order(lt, *pts) + orders.append(order) + if expr.is_Add: + new_expr = Order(Add(*orders), *pts) + if new_expr.is_Add: + new_expr = Order(Add(*[a.expr for a in new_expr.args]), *pts) + expr = new_expr.expr + elif expr.is_Mul: + expr = Mul(*[a.expr for a in orders]) + elif expr.is_Pow: + e = expr.exp + b = expr.base + expr = exp(e * log(b)) + + # It would probably be better to handle this somewhere + # else. This is needed for a testcase in which there is a + # symbol with the assumptions zero=True. + if expr.is_zero: + expr = S.Zero + else: + expr = expr.as_independent(*args, as_Add=False)[1] + + expr = expand_power_base(expr) + expr = expand_log(expr) + + if len(args) == 1: + # The definition of O(f(x)) symbol explicitly stated that + # the argument of f(x) is irrelevant. That's why we can + # combine some power exponents (only "on top" of the + # expression tree for f(x)), e.g.: + # x**p * (-x)**q -> x**(p+q) for real p, q. + x = args[0] + margs = list(Mul.make_args( + expr.as_independent(x, as_Add=False)[1])) + + for i, t in enumerate(margs): + if t.is_Pow: + b, q = t.args + if b in (x, -x) and q.is_real and not q.has(x): + margs[i] = x**q + elif b.is_Pow and not b.exp.has(x): + b, r = b.args + if b in (x, -x) and r.is_real: + margs[i] = x**(r*q) + elif b.is_Mul and b.args[0] is S.NegativeOne: + b = -b + if b.is_Pow and not b.exp.has(x): + b, r = b.args + if b in (x, -x) and r.is_real: + margs[i] = x**(r*q) + + expr = Mul(*margs) + + expr = expr.subs(rs) + + if expr.is_Order: + expr = expr.expr + + if not expr.has(*variables) and not expr.is_zero: + expr = S.One + + # create Order instance: + vp = dict(zip(variables, point)) + variables.sort(key=default_sort_key) + point = [vp[v] for v in variables] + args = (expr,) + Tuple(*zip(variables, point)) + obj = Expr.__new__(cls, *args) + return obj + + def _eval_nseries(self, x, n, logx, cdir=0): + return self + + @property + def expr(self): + return self.args[0] + + @property + def variables(self): + if self.args[1:]: + return tuple(x[0] for x in self.args[1:]) + else: + return () + + @property + def point(self): + if self.args[1:]: + return tuple(x[1] for x in self.args[1:]) + else: + return () + + @property + def free_symbols(self): + return self.expr.free_symbols | set(self.variables) + + def _eval_power(b, e): + if e.is_Number and e.is_nonnegative: + return b.func(b.expr ** e, *b.args[1:]) + if e == O(1): + return b + return + + def as_expr_variables(self, order_symbols): + if order_symbols is None: + order_symbols = self.args[1:] + else: + if (not all(o[1] == order_symbols[0][1] for o in order_symbols) and + not all(p == self.point[0] for p in self.point)): # pragma: no cover + raise NotImplementedError('Order at points other than 0 ' + 'or oo not supported, got %s as a point.' % self.point) + if order_symbols and order_symbols[0][1] != self.point[0]: + raise NotImplementedError( + "Multiplying Order at different points is not supported.") + order_symbols = dict(order_symbols) + for s, p in dict(self.args[1:]).items(): + if s not in order_symbols.keys(): + order_symbols[s] = p + order_symbols = sorted(order_symbols.items(), key=lambda x: default_sort_key(x[0])) + return self.expr, tuple(order_symbols) + + def removeO(self): + return S.Zero + + def getO(self): + return self + + @cacheit + def contains(self, expr): + r""" + Return True if expr belongs to Order(self.expr, \*self.variables). + Return False if self belongs to expr. + Return None if the inclusion relation cannot be determined + (e.g. when self and expr have different symbols). + """ + expr = sympify(expr) + if expr.is_zero: + return True + if expr is S.NaN: + return False + point = self.point[0] if self.point else S.Zero + if expr.is_Order: + if (any(p != point for p in expr.point) or + any(p != point for p in self.point)): + return None + if expr.expr == self.expr: + # O(1) + O(1), O(1) + O(1, x), etc. + return all(x in self.args[1:] for x in expr.args[1:]) + if expr.expr.is_Add: + return all(self.contains(x) for x in expr.expr.args) + if self.expr.is_Add and point.is_zero: + return any(self.func(x, *self.args[1:]).contains(expr) + for x in self.expr.args) + if self.variables and expr.variables: + common_symbols = tuple( + [s for s in self.variables if s in expr.variables]) + elif self.variables: + common_symbols = self.variables + else: + common_symbols = expr.variables + if not common_symbols: + return None + if (self.expr.is_Pow and len(self.variables) == 1 + and self.variables == expr.variables): + symbol = self.variables[0] + other = expr.expr.as_independent(symbol, as_Add=False)[1] + if (other.is_Pow and other.base == symbol and + self.expr.base == symbol): + if point.is_zero: + rv = (self.expr.exp - other.exp).is_nonpositive + if point.is_infinite: + rv = (self.expr.exp - other.exp).is_nonnegative + if rv is not None: + return rv + + from sympy.simplify.powsimp import powsimp + r = None + ratio = self.expr/expr.expr + ratio = powsimp(ratio, deep=True, combine='exp') + for s in common_symbols: + from sympy.series.limits import Limit + l = Limit(ratio, s, point).doit(heuristics=False) + if not isinstance(l, Limit): + l = l != 0 + else: + l = None + if r is None: + r = l + else: + if r != l: + return + return r + + if self.expr.is_Pow and len(self.variables) == 1: + symbol = self.variables[0] + other = expr.as_independent(symbol, as_Add=False)[1] + if (other.is_Pow and other.base == symbol and + self.expr.base == symbol): + if point.is_zero: + rv = (self.expr.exp - other.exp).is_nonpositive + if point.is_infinite: + rv = (self.expr.exp - other.exp).is_nonnegative + if rv is not None: + return rv + + obj = self.func(expr, *self.args[1:]) + return self.contains(obj) + + def __contains__(self, other): + result = self.contains(other) + if result is None: + raise TypeError('contains did not evaluate to a bool') + return result + + def _eval_subs(self, old, new): + if old in self.variables: + newexpr = self.expr.subs(old, new) + i = self.variables.index(old) + newvars = list(self.variables) + newpt = list(self.point) + if new.is_symbol: + newvars[i] = new + else: + syms = new.free_symbols + if len(syms) == 1 or old in syms: + if old in syms: + var = self.variables[i] + else: + var = syms.pop() + # First, try to substitute self.point in the "new" + # expr to see if this is a fixed point. + # E.g. O(y).subs(y, sin(x)) + point = new.subs(var, self.point[i]) + if point != self.point[i]: + from sympy.solvers.solveset import solveset + d = Dummy() + sol = solveset(old - new.subs(var, d), d) + if isinstance(sol, Complement): + e1 = sol.args[0] + e2 = sol.args[1] + sol = set(e1) - set(e2) + res = [dict(zip((d, ), sol))] + point = d.subs(res[0]).limit(old, self.point[i]) + newvars[i] = var + newpt[i] = point + elif old not in syms: + del newvars[i], newpt[i] + if not syms and new == self.point[i]: + newvars.extend(syms) + newpt.extend([S.Zero]*len(syms)) + else: + return + return Order(newexpr, *zip(newvars, newpt)) + + def _eval_conjugate(self): + expr = self.expr._eval_conjugate() + if expr is not None: + return self.func(expr, *self.args[1:]) + + def _eval_derivative(self, x): + return self.func(self.expr.diff(x), *self.args[1:]) or self + + def _eval_transpose(self): + expr = self.expr._eval_transpose() + if expr is not None: + return self.func(expr, *self.args[1:]) + + def __neg__(self): + return self + +O = Order diff --git a/lib/python3.12/site-packages/sympy/series/residues.py b/lib/python3.12/site-packages/sympy/series/residues.py new file mode 100644 index 0000000000000000000000000000000000000000..a426f9e799bd040eea5124f718c2fa43e5de026b --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/residues.py @@ -0,0 +1,73 @@ +""" +This module implements the Residue function and related tools for working +with residues. +""" + +from sympy.core.mul import Mul +from sympy.core.singleton import S +from sympy.core.sympify import sympify +from sympy.utilities.timeutils import timethis + + +@timethis('residue') +def residue(expr, x, x0): + """ + Finds the residue of ``expr`` at the point x=x0. + + The residue is defined as the coefficient of ``1/(x-x0)`` in the power series + expansion about ``x=x0``. + + Examples + ======== + + >>> from sympy import Symbol, residue, sin + >>> x = Symbol("x") + >>> residue(1/x, x, 0) + 1 + >>> residue(1/x**2, x, 0) + 0 + >>> residue(2/sin(x), x, 0) + 2 + + This function is essential for the Residue Theorem [1]. + + References + ========== + + .. [1] https://en.wikipedia.org/wiki/Residue_theorem + """ + # The current implementation uses series expansion to + # calculate it. A more general implementation is explained in + # the section 5.6 of the Bronstein's book {M. Bronstein: + # Symbolic Integration I, Springer Verlag (2005)}. For purely + # rational functions, the algorithm is much easier. See + # sections 2.4, 2.5, and 2.7 (this section actually gives an + # algorithm for computing any Laurent series coefficient for + # a rational function). The theory in section 2.4 will help to + # understand why the resultant works in the general algorithm. + # For the definition of a resultant, see section 1.4 (and any + # previous sections for more review). + + from sympy.series.order import Order + from sympy.simplify.radsimp import collect + expr = sympify(expr) + if x0 != 0: + expr = expr.subs(x, x + x0) + for n in (0, 1, 2, 4, 8, 16, 32): + s = expr.nseries(x, n=n) + if not s.has(Order) or s.getn() >= 0: + break + s = collect(s.removeO(), x) + if s.is_Add: + args = s.args + else: + args = [s] + res = S.Zero + for arg in args: + c, m = arg.as_coeff_mul(x) + m = Mul(*m) + if not (m in (S.One, x) or (m.is_Pow and m.exp.is_Integer)): + raise NotImplementedError('term of unexpected form: %s' % m) + if m == 1/x: + res += c + return res diff --git a/lib/python3.12/site-packages/sympy/series/sequences.py b/lib/python3.12/site-packages/sympy/series/sequences.py new file mode 100644 index 0000000000000000000000000000000000000000..7787515ddb05afaf34751bf451544935723d0921 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/sequences.py @@ -0,0 +1,1239 @@ +from sympy.core.basic import Basic +from sympy.core.cache import cacheit +from sympy.core.containers import Tuple +from sympy.core.decorators import call_highest_priority +from sympy.core.parameters import global_parameters +from sympy.core.function import AppliedUndef, expand +from sympy.core.mul import Mul +from sympy.core.numbers import Integer +from sympy.core.relational import Eq +from sympy.core.singleton import S, Singleton +from sympy.core.sorting import ordered +from sympy.core.symbol import Dummy, Symbol, Wild +from sympy.core.sympify import sympify +from sympy.matrices import Matrix +from sympy.polys import lcm, factor +from sympy.sets.sets import Interval, Intersection +from sympy.tensor.indexed import Idx +from sympy.utilities.iterables import flatten, is_sequence, iterable + + +############################################################################### +# SEQUENCES # +############################################################################### + + +class SeqBase(Basic): + """Base class for sequences""" + + is_commutative = True + _op_priority = 15 + + @staticmethod + def _start_key(expr): + """Return start (if possible) else S.Infinity. + + adapted from Set._infimum_key + """ + try: + start = expr.start + except NotImplementedError: + start = S.Infinity + return start + + def _intersect_interval(self, other): + """Returns start and stop. + + Takes intersection over the two intervals. + """ + interval = Intersection(self.interval, other.interval) + return interval.inf, interval.sup + + @property + def gen(self): + """Returns the generator for the sequence""" + raise NotImplementedError("(%s).gen" % self) + + @property + def interval(self): + """The interval on which the sequence is defined""" + raise NotImplementedError("(%s).interval" % self) + + @property + def start(self): + """The starting point of the sequence. This point is included""" + raise NotImplementedError("(%s).start" % self) + + @property + def stop(self): + """The ending point of the sequence. This point is included""" + raise NotImplementedError("(%s).stop" % self) + + @property + def length(self): + """Length of the sequence""" + raise NotImplementedError("(%s).length" % self) + + @property + def variables(self): + """Returns a tuple of variables that are bounded""" + return () + + @property + def free_symbols(self): + """ + This method returns the symbols in the object, excluding those + that take on a specific value (i.e. the dummy symbols). + + Examples + ======== + + >>> from sympy import SeqFormula + >>> from sympy.abc import n, m + >>> SeqFormula(m*n**2, (n, 0, 5)).free_symbols + {m} + """ + return ({j for i in self.args for j in i.free_symbols + .difference(self.variables)}) + + @cacheit + def coeff(self, pt): + """Returns the coefficient at point pt""" + if pt < self.start or pt > self.stop: + raise IndexError("Index %s out of bounds %s" % (pt, self.interval)) + return self._eval_coeff(pt) + + def _eval_coeff(self, pt): + raise NotImplementedError("The _eval_coeff method should be added to" + "%s to return coefficient so it is available" + "when coeff calls it." + % self.func) + + def _ith_point(self, i): + """Returns the i'th point of a sequence. + + Explanation + =========== + + If start point is negative infinity, point is returned from the end. + Assumes the first point to be indexed zero. + + Examples + ========= + + >>> from sympy import oo + >>> from sympy.series.sequences import SeqPer + + bounded + + >>> SeqPer((1, 2, 3), (-10, 10))._ith_point(0) + -10 + >>> SeqPer((1, 2, 3), (-10, 10))._ith_point(5) + -5 + + End is at infinity + + >>> SeqPer((1, 2, 3), (0, oo))._ith_point(5) + 5 + + Starts at negative infinity + + >>> SeqPer((1, 2, 3), (-oo, 0))._ith_point(5) + -5 + """ + if self.start is S.NegativeInfinity: + initial = self.stop + else: + initial = self.start + + if self.start is S.NegativeInfinity: + step = -1 + else: + step = 1 + + return initial + i*step + + def _add(self, other): + """ + Should only be used internally. + + Explanation + =========== + + self._add(other) returns a new, term-wise added sequence if self + knows how to add with other, otherwise it returns ``None``. + + ``other`` should only be a sequence object. + + Used within :class:`SeqAdd` class. + """ + return None + + def _mul(self, other): + """ + Should only be used internally. + + Explanation + =========== + + self._mul(other) returns a new, term-wise multiplied sequence if self + knows how to multiply with other, otherwise it returns ``None``. + + ``other`` should only be a sequence object. + + Used within :class:`SeqMul` class. + """ + return None + + def coeff_mul(self, other): + """ + Should be used when ``other`` is not a sequence. Should be + defined to define custom behaviour. + + Examples + ======== + + >>> from sympy import SeqFormula + >>> from sympy.abc import n + >>> SeqFormula(n**2).coeff_mul(2) + SeqFormula(2*n**2, (n, 0, oo)) + + Notes + ===== + + '*' defines multiplication of sequences with sequences only. + """ + return Mul(self, other) + + def __add__(self, other): + """Returns the term-wise addition of 'self' and 'other'. + + ``other`` should be a sequence. + + Examples + ======== + + >>> from sympy import SeqFormula + >>> from sympy.abc import n + >>> SeqFormula(n**2) + SeqFormula(n**3) + SeqFormula(n**3 + n**2, (n, 0, oo)) + """ + if not isinstance(other, SeqBase): + raise TypeError('cannot add sequence and %s' % type(other)) + return SeqAdd(self, other) + + @call_highest_priority('__add__') + def __radd__(self, other): + return self + other + + def __sub__(self, other): + """Returns the term-wise subtraction of ``self`` and ``other``. + + ``other`` should be a sequence. + + Examples + ======== + + >>> from sympy import SeqFormula + >>> from sympy.abc import n + >>> SeqFormula(n**2) - (SeqFormula(n)) + SeqFormula(n**2 - n, (n, 0, oo)) + """ + if not isinstance(other, SeqBase): + raise TypeError('cannot subtract sequence and %s' % type(other)) + return SeqAdd(self, -other) + + @call_highest_priority('__sub__') + def __rsub__(self, other): + return (-self) + other + + def __neg__(self): + """Negates the sequence. + + Examples + ======== + + >>> from sympy import SeqFormula + >>> from sympy.abc import n + >>> -SeqFormula(n**2) + SeqFormula(-n**2, (n, 0, oo)) + """ + return self.coeff_mul(-1) + + def __mul__(self, other): + """Returns the term-wise multiplication of 'self' and 'other'. + + ``other`` should be a sequence. For ``other`` not being a + sequence see :func:`coeff_mul` method. + + Examples + ======== + + >>> from sympy import SeqFormula + >>> from sympy.abc import n + >>> SeqFormula(n**2) * (SeqFormula(n)) + SeqFormula(n**3, (n, 0, oo)) + """ + if not isinstance(other, SeqBase): + raise TypeError('cannot multiply sequence and %s' % type(other)) + return SeqMul(self, other) + + @call_highest_priority('__mul__') + def __rmul__(self, other): + return self * other + + def __iter__(self): + for i in range(self.length): + pt = self._ith_point(i) + yield self.coeff(pt) + + def __getitem__(self, index): + if isinstance(index, int): + index = self._ith_point(index) + return self.coeff(index) + elif isinstance(index, slice): + start, stop = index.start, index.stop + if start is None: + start = 0 + if stop is None: + stop = self.length + return [self.coeff(self._ith_point(i)) for i in + range(start, stop, index.step or 1)] + + def find_linear_recurrence(self,n,d=None,gfvar=None): + r""" + Finds the shortest linear recurrence that satisfies the first n + terms of sequence of order `\leq` ``n/2`` if possible. + If ``d`` is specified, find shortest linear recurrence of order + `\leq` min(d, n/2) if possible. + Returns list of coefficients ``[b(1), b(2), ...]`` corresponding to the + recurrence relation ``x(n) = b(1)*x(n-1) + b(2)*x(n-2) + ...`` + Returns ``[]`` if no recurrence is found. + If gfvar is specified, also returns ordinary generating function as a + function of gfvar. + + Examples + ======== + + >>> from sympy import sequence, sqrt, oo, lucas + >>> from sympy.abc import n, x, y + >>> sequence(n**2).find_linear_recurrence(10, 2) + [] + >>> sequence(n**2).find_linear_recurrence(10) + [3, -3, 1] + >>> sequence(2**n).find_linear_recurrence(10) + [2] + >>> sequence(23*n**4+91*n**2).find_linear_recurrence(10) + [5, -10, 10, -5, 1] + >>> sequence(sqrt(5)*(((1 + sqrt(5))/2)**n - (-(1 + sqrt(5))/2)**(-n))/5).find_linear_recurrence(10) + [1, 1] + >>> sequence(x+y*(-2)**(-n), (n, 0, oo)).find_linear_recurrence(30) + [1/2, 1/2] + >>> sequence(3*5**n + 12).find_linear_recurrence(20,gfvar=x) + ([6, -5], 3*(5 - 21*x)/((x - 1)*(5*x - 1))) + >>> sequence(lucas(n)).find_linear_recurrence(15,gfvar=x) + ([1, 1], (x - 2)/(x**2 + x - 1)) + """ + from sympy.simplify import simplify + x = [simplify(expand(t)) for t in self[:n]] + lx = len(x) + if d is None: + r = lx//2 + else: + r = min(d,lx//2) + coeffs = [] + for l in range(1, r+1): + l2 = 2*l + mlist = [] + for k in range(l): + mlist.append(x[k:k+l]) + m = Matrix(mlist) + if m.det() != 0: + y = simplify(m.LUsolve(Matrix(x[l:l2]))) + if lx == l2: + coeffs = flatten(y[::-1]) + break + mlist = [] + for k in range(l,lx-l): + mlist.append(x[k:k+l]) + m = Matrix(mlist) + if m*y == Matrix(x[l2:]): + coeffs = flatten(y[::-1]) + break + if gfvar is None: + return coeffs + else: + l = len(coeffs) + if l == 0: + return [], None + else: + n, d = x[l-1]*gfvar**(l-1), 1 - coeffs[l-1]*gfvar**l + for i in range(l-1): + n += x[i]*gfvar**i + for j in range(l-i-1): + n -= coeffs[i]*x[j]*gfvar**(i+j+1) + d -= coeffs[i]*gfvar**(i+1) + return coeffs, simplify(factor(n)/factor(d)) + +class EmptySequence(SeqBase, metaclass=Singleton): + """Represents an empty sequence. + + The empty sequence is also available as a singleton as + ``S.EmptySequence``. + + Examples + ======== + + >>> from sympy import EmptySequence, SeqPer + >>> from sympy.abc import x + >>> EmptySequence + EmptySequence + >>> SeqPer((1, 2), (x, 0, 10)) + EmptySequence + SeqPer((1, 2), (x, 0, 10)) + >>> SeqPer((1, 2)) * EmptySequence + EmptySequence + >>> EmptySequence.coeff_mul(-1) + EmptySequence + """ + + @property + def interval(self): + return S.EmptySet + + @property + def length(self): + return S.Zero + + def coeff_mul(self, coeff): + """See docstring of SeqBase.coeff_mul""" + return self + + def __iter__(self): + return iter([]) + + +class SeqExpr(SeqBase): + """Sequence expression class. + + Various sequences should inherit from this class. + + Examples + ======== + + >>> from sympy.series.sequences import SeqExpr + >>> from sympy.abc import x + >>> from sympy import Tuple + >>> s = SeqExpr(Tuple(1, 2, 3), Tuple(x, 0, 10)) + >>> s.gen + (1, 2, 3) + >>> s.interval + Interval(0, 10) + >>> s.length + 11 + + See Also + ======== + + sympy.series.sequences.SeqPer + sympy.series.sequences.SeqFormula + """ + + @property + def gen(self): + return self.args[0] + + @property + def interval(self): + return Interval(self.args[1][1], self.args[1][2]) + + @property + def start(self): + return self.interval.inf + + @property + def stop(self): + return self.interval.sup + + @property + def length(self): + return self.stop - self.start + 1 + + @property + def variables(self): + return (self.args[1][0],) + + +class SeqPer(SeqExpr): + """ + Represents a periodic sequence. + + The elements are repeated after a given period. + + Examples + ======== + + >>> from sympy import SeqPer, oo + >>> from sympy.abc import k + + >>> s = SeqPer((1, 2, 3), (0, 5)) + >>> s.periodical + (1, 2, 3) + >>> s.period + 3 + + For value at a particular point + + >>> s.coeff(3) + 1 + + supports slicing + + >>> s[:] + [1, 2, 3, 1, 2, 3] + + iterable + + >>> list(s) + [1, 2, 3, 1, 2, 3] + + sequence starts from negative infinity + + >>> SeqPer((1, 2, 3), (-oo, 0))[0:6] + [1, 2, 3, 1, 2, 3] + + Periodic formulas + + >>> SeqPer((k, k**2, k**3), (k, 0, oo))[0:6] + [0, 1, 8, 3, 16, 125] + + See Also + ======== + + sympy.series.sequences.SeqFormula + """ + + def __new__(cls, periodical, limits=None): + periodical = sympify(periodical) + + def _find_x(periodical): + free = periodical.free_symbols + if len(periodical.free_symbols) == 1: + return free.pop() + else: + return Dummy('k') + + x, start, stop = None, None, None + if limits is None: + x, start, stop = _find_x(periodical), 0, S.Infinity + if is_sequence(limits, Tuple): + if len(limits) == 3: + x, start, stop = limits + elif len(limits) == 2: + x = _find_x(periodical) + start, stop = limits + + if not isinstance(x, (Symbol, Idx)) or start is None or stop is None: + raise ValueError('Invalid limits given: %s' % str(limits)) + + if start is S.NegativeInfinity and stop is S.Infinity: + raise ValueError("Both the start and end value" + "cannot be unbounded") + + limits = sympify((x, start, stop)) + + if is_sequence(periodical, Tuple): + periodical = sympify(tuple(flatten(periodical))) + else: + raise ValueError("invalid period %s should be something " + "like e.g (1, 2) " % periodical) + + if Interval(limits[1], limits[2]) is S.EmptySet: + return S.EmptySequence + + return Basic.__new__(cls, periodical, limits) + + @property + def period(self): + return len(self.gen) + + @property + def periodical(self): + return self.gen + + def _eval_coeff(self, pt): + if self.start is S.NegativeInfinity: + idx = (self.stop - pt) % self.period + else: + idx = (pt - self.start) % self.period + return self.periodical[idx].subs(self.variables[0], pt) + + def _add(self, other): + """See docstring of SeqBase._add""" + if isinstance(other, SeqPer): + per1, lper1 = self.periodical, self.period + per2, lper2 = other.periodical, other.period + + per_length = lcm(lper1, lper2) + + new_per = [] + for x in range(per_length): + ele1 = per1[x % lper1] + ele2 = per2[x % lper2] + new_per.append(ele1 + ele2) + + start, stop = self._intersect_interval(other) + return SeqPer(new_per, (self.variables[0], start, stop)) + + def _mul(self, other): + """See docstring of SeqBase._mul""" + if isinstance(other, SeqPer): + per1, lper1 = self.periodical, self.period + per2, lper2 = other.periodical, other.period + + per_length = lcm(lper1, lper2) + + new_per = [] + for x in range(per_length): + ele1 = per1[x % lper1] + ele2 = per2[x % lper2] + new_per.append(ele1 * ele2) + + start, stop = self._intersect_interval(other) + return SeqPer(new_per, (self.variables[0], start, stop)) + + def coeff_mul(self, coeff): + """See docstring of SeqBase.coeff_mul""" + coeff = sympify(coeff) + per = [x * coeff for x in self.periodical] + return SeqPer(per, self.args[1]) + + +class SeqFormula(SeqExpr): + """ + Represents sequence based on a formula. + + Elements are generated using a formula. + + Examples + ======== + + >>> from sympy import SeqFormula, oo, Symbol + >>> n = Symbol('n') + >>> s = SeqFormula(n**2, (n, 0, 5)) + >>> s.formula + n**2 + + For value at a particular point + + >>> s.coeff(3) + 9 + + supports slicing + + >>> s[:] + [0, 1, 4, 9, 16, 25] + + iterable + + >>> list(s) + [0, 1, 4, 9, 16, 25] + + sequence starts from negative infinity + + >>> SeqFormula(n**2, (-oo, 0))[0:6] + [0, 1, 4, 9, 16, 25] + + See Also + ======== + + sympy.series.sequences.SeqPer + """ + + def __new__(cls, formula, limits=None): + formula = sympify(formula) + + def _find_x(formula): + free = formula.free_symbols + if len(free) == 1: + return free.pop() + elif not free: + return Dummy('k') + else: + raise ValueError( + " specify dummy variables for %s. If the formula contains" + " more than one free symbol, a dummy variable should be" + " supplied explicitly e.g., SeqFormula(m*n**2, (n, 0, 5))" + % formula) + + x, start, stop = None, None, None + if limits is None: + x, start, stop = _find_x(formula), 0, S.Infinity + if is_sequence(limits, Tuple): + if len(limits) == 3: + x, start, stop = limits + elif len(limits) == 2: + x = _find_x(formula) + start, stop = limits + + if not isinstance(x, (Symbol, Idx)) or start is None or stop is None: + raise ValueError('Invalid limits given: %s' % str(limits)) + + if start is S.NegativeInfinity and stop is S.Infinity: + raise ValueError("Both the start and end value " + "cannot be unbounded") + limits = sympify((x, start, stop)) + + if Interval(limits[1], limits[2]) is S.EmptySet: + return S.EmptySequence + + return Basic.__new__(cls, formula, limits) + + @property + def formula(self): + return self.gen + + def _eval_coeff(self, pt): + d = self.variables[0] + return self.formula.subs(d, pt) + + def _add(self, other): + """See docstring of SeqBase._add""" + if isinstance(other, SeqFormula): + form1, v1 = self.formula, self.variables[0] + form2, v2 = other.formula, other.variables[0] + formula = form1 + form2.subs(v2, v1) + start, stop = self._intersect_interval(other) + return SeqFormula(formula, (v1, start, stop)) + + def _mul(self, other): + """See docstring of SeqBase._mul""" + if isinstance(other, SeqFormula): + form1, v1 = self.formula, self.variables[0] + form2, v2 = other.formula, other.variables[0] + formula = form1 * form2.subs(v2, v1) + start, stop = self._intersect_interval(other) + return SeqFormula(formula, (v1, start, stop)) + + def coeff_mul(self, coeff): + """See docstring of SeqBase.coeff_mul""" + coeff = sympify(coeff) + formula = self.formula * coeff + return SeqFormula(formula, self.args[1]) + + def expand(self, *args, **kwargs): + return SeqFormula(expand(self.formula, *args, **kwargs), self.args[1]) + +class RecursiveSeq(SeqBase): + """ + A finite degree recursive sequence. + + Explanation + =========== + + That is, a sequence a(n) that depends on a fixed, finite number of its + previous values. The general form is + + a(n) = f(a(n - 1), a(n - 2), ..., a(n - d)) + + for some fixed, positive integer d, where f is some function defined by a + SymPy expression. + + Parameters + ========== + + recurrence : SymPy expression defining recurrence + This is *not* an equality, only the expression that the nth term is + equal to. For example, if :code:`a(n) = f(a(n - 1), ..., a(n - d))`, + then the expression should be :code:`f(a(n - 1), ..., a(n - d))`. + + yn : applied undefined function + Represents the nth term of the sequence as e.g. :code:`y(n)` where + :code:`y` is an undefined function and `n` is the sequence index. + + n : symbolic argument + The name of the variable that the recurrence is in, e.g., :code:`n` if + the recurrence function is :code:`y(n)`. + + initial : iterable with length equal to the degree of the recurrence + The initial values of the recurrence. + + start : start value of sequence (inclusive) + + Examples + ======== + + >>> from sympy import Function, symbols + >>> from sympy.series.sequences import RecursiveSeq + >>> y = Function("y") + >>> n = symbols("n") + >>> fib = RecursiveSeq(y(n - 1) + y(n - 2), y(n), n, [0, 1]) + + >>> fib.coeff(3) # Value at a particular point + 2 + + >>> fib[:6] # supports slicing + [0, 1, 1, 2, 3, 5] + + >>> fib.recurrence # inspect recurrence + Eq(y(n), y(n - 2) + y(n - 1)) + + >>> fib.degree # automatically determine degree + 2 + + >>> for x in zip(range(10), fib): # supports iteration + ... print(x) + (0, 0) + (1, 1) + (2, 1) + (3, 2) + (4, 3) + (5, 5) + (6, 8) + (7, 13) + (8, 21) + (9, 34) + + See Also + ======== + + sympy.series.sequences.SeqFormula + + """ + + def __new__(cls, recurrence, yn, n, initial=None, start=0): + if not isinstance(yn, AppliedUndef): + raise TypeError("recurrence sequence must be an applied undefined function" + ", found `{}`".format(yn)) + + if not isinstance(n, Basic) or not n.is_symbol: + raise TypeError("recurrence variable must be a symbol" + ", found `{}`".format(n)) + + if yn.args != (n,): + raise TypeError("recurrence sequence does not match symbol") + + y = yn.func + + k = Wild("k", exclude=(n,)) + degree = 0 + + # Find all applications of y in the recurrence and check that: + # 1. The function y is only being used with a single argument; and + # 2. All arguments are n + k for constant negative integers k. + + prev_ys = recurrence.find(y) + for prev_y in prev_ys: + if len(prev_y.args) != 1: + raise TypeError("Recurrence should be in a single variable") + + shift = prev_y.args[0].match(n + k)[k] + if not (shift.is_constant() and shift.is_integer and shift < 0): + raise TypeError("Recurrence should have constant," + " negative, integer shifts" + " (found {})".format(prev_y)) + + if -shift > degree: + degree = -shift + + if not initial: + initial = [Dummy("c_{}".format(k)) for k in range(degree)] + + if len(initial) != degree: + raise ValueError("Number of initial terms must equal degree") + + degree = Integer(degree) + start = sympify(start) + + initial = Tuple(*(sympify(x) for x in initial)) + + seq = Basic.__new__(cls, recurrence, yn, n, initial, start) + + seq.cache = {y(start + k): init for k, init in enumerate(initial)} + seq.degree = degree + + return seq + + @property + def _recurrence(self): + """Equation defining recurrence.""" + return self.args[0] + + @property + def recurrence(self): + """Equation defining recurrence.""" + return Eq(self.yn, self.args[0]) + + @property + def yn(self): + """Applied function representing the nth term""" + return self.args[1] + + @property + def y(self): + """Undefined function for the nth term of the sequence""" + return self.yn.func + + @property + def n(self): + """Sequence index symbol""" + return self.args[2] + + @property + def initial(self): + """The initial values of the sequence""" + return self.args[3] + + @property + def start(self): + """The starting point of the sequence. This point is included""" + return self.args[4] + + @property + def stop(self): + """The ending point of the sequence. (oo)""" + return S.Infinity + + @property + def interval(self): + """Interval on which sequence is defined.""" + return (self.start, S.Infinity) + + def _eval_coeff(self, index): + if index - self.start < len(self.cache): + return self.cache[self.y(index)] + + for current in range(len(self.cache), index + 1): + # Use xreplace over subs for performance. + # See issue #10697. + seq_index = self.start + current + current_recurrence = self._recurrence.xreplace({self.n: seq_index}) + new_term = current_recurrence.xreplace(self.cache) + + self.cache[self.y(seq_index)] = new_term + + return self.cache[self.y(self.start + current)] + + def __iter__(self): + index = self.start + while True: + yield self._eval_coeff(index) + index += 1 + + +def sequence(seq, limits=None): + """ + Returns appropriate sequence object. + + Explanation + =========== + + If ``seq`` is a SymPy sequence, returns :class:`SeqPer` object + otherwise returns :class:`SeqFormula` object. + + Examples + ======== + + >>> from sympy import sequence + >>> from sympy.abc import n + >>> sequence(n**2, (n, 0, 5)) + SeqFormula(n**2, (n, 0, 5)) + >>> sequence((1, 2, 3), (n, 0, 5)) + SeqPer((1, 2, 3), (n, 0, 5)) + + See Also + ======== + + sympy.series.sequences.SeqPer + sympy.series.sequences.SeqFormula + """ + seq = sympify(seq) + + if is_sequence(seq, Tuple): + return SeqPer(seq, limits) + else: + return SeqFormula(seq, limits) + + +############################################################################### +# OPERATIONS # +############################################################################### + + +class SeqExprOp(SeqBase): + """ + Base class for operations on sequences. + + Examples + ======== + + >>> from sympy.series.sequences import SeqExprOp, sequence + >>> from sympy.abc import n + >>> s1 = sequence(n**2, (n, 0, 10)) + >>> s2 = sequence((1, 2, 3), (n, 5, 10)) + >>> s = SeqExprOp(s1, s2) + >>> s.gen + (n**2, (1, 2, 3)) + >>> s.interval + Interval(5, 10) + >>> s.length + 6 + + See Also + ======== + + sympy.series.sequences.SeqAdd + sympy.series.sequences.SeqMul + """ + @property + def gen(self): + """Generator for the sequence. + + returns a tuple of generators of all the argument sequences. + """ + return tuple(a.gen for a in self.args) + + @property + def interval(self): + """Sequence is defined on the intersection + of all the intervals of respective sequences + """ + return Intersection(*(a.interval for a in self.args)) + + @property + def start(self): + return self.interval.inf + + @property + def stop(self): + return self.interval.sup + + @property + def variables(self): + """Cumulative of all the bound variables""" + return tuple(flatten([a.variables for a in self.args])) + + @property + def length(self): + return self.stop - self.start + 1 + + +class SeqAdd(SeqExprOp): + """Represents term-wise addition of sequences. + + Rules: + * The interval on which sequence is defined is the intersection + of respective intervals of sequences. + * Anything + :class:`EmptySequence` remains unchanged. + * Other rules are defined in ``_add`` methods of sequence classes. + + Examples + ======== + + >>> from sympy import EmptySequence, oo, SeqAdd, SeqPer, SeqFormula + >>> from sympy.abc import n + >>> SeqAdd(SeqPer((1, 2), (n, 0, oo)), EmptySequence) + SeqPer((1, 2), (n, 0, oo)) + >>> SeqAdd(SeqPer((1, 2), (n, 0, 5)), SeqPer((1, 2), (n, 6, 10))) + EmptySequence + >>> SeqAdd(SeqPer((1, 2), (n, 0, oo)), SeqFormula(n**2, (n, 0, oo))) + SeqAdd(SeqFormula(n**2, (n, 0, oo)), SeqPer((1, 2), (n, 0, oo))) + >>> SeqAdd(SeqFormula(n**3), SeqFormula(n**2)) + SeqFormula(n**3 + n**2, (n, 0, oo)) + + See Also + ======== + + sympy.series.sequences.SeqMul + """ + + def __new__(cls, *args, **kwargs): + evaluate = kwargs.get('evaluate', global_parameters.evaluate) + + # flatten inputs + args = list(args) + + # adapted from sympy.sets.sets.Union + def _flatten(arg): + if isinstance(arg, SeqBase): + if isinstance(arg, SeqAdd): + return sum(map(_flatten, arg.args), []) + else: + return [arg] + if iterable(arg): + return sum(map(_flatten, arg), []) + raise TypeError("Input must be Sequences or " + " iterables of Sequences") + args = _flatten(args) + + args = [a for a in args if a is not S.EmptySequence] + + # Addition of no sequences is EmptySequence + if not args: + return S.EmptySequence + + if Intersection(*(a.interval for a in args)) is S.EmptySet: + return S.EmptySequence + + # reduce using known rules + if evaluate: + return SeqAdd.reduce(args) + + args = list(ordered(args, SeqBase._start_key)) + + return Basic.__new__(cls, *args) + + @staticmethod + def reduce(args): + """Simplify :class:`SeqAdd` using known rules. + + Iterates through all pairs and ask the constituent + sequences if they can simplify themselves with any other constituent. + + Notes + ===== + + adapted from ``Union.reduce`` + + """ + new_args = True + while new_args: + for id1, s in enumerate(args): + new_args = False + for id2, t in enumerate(args): + if id1 == id2: + continue + new_seq = s._add(t) + # This returns None if s does not know how to add + # with t. Returns the newly added sequence otherwise + if new_seq is not None: + new_args = [a for a in args if a not in (s, t)] + new_args.append(new_seq) + break + if new_args: + args = new_args + break + + if len(args) == 1: + return args.pop() + else: + return SeqAdd(args, evaluate=False) + + def _eval_coeff(self, pt): + """adds up the coefficients of all the sequences at point pt""" + return sum(a.coeff(pt) for a in self.args) + + +class SeqMul(SeqExprOp): + r"""Represents term-wise multiplication of sequences. + + Explanation + =========== + + Handles multiplication of sequences only. For multiplication + with other objects see :func:`SeqBase.coeff_mul`. + + Rules: + * The interval on which sequence is defined is the intersection + of respective intervals of sequences. + * Anything \* :class:`EmptySequence` returns :class:`EmptySequence`. + * Other rules are defined in ``_mul`` methods of sequence classes. + + Examples + ======== + + >>> from sympy import EmptySequence, oo, SeqMul, SeqPer, SeqFormula + >>> from sympy.abc import n + >>> SeqMul(SeqPer((1, 2), (n, 0, oo)), EmptySequence) + EmptySequence + >>> SeqMul(SeqPer((1, 2), (n, 0, 5)), SeqPer((1, 2), (n, 6, 10))) + EmptySequence + >>> SeqMul(SeqPer((1, 2), (n, 0, oo)), SeqFormula(n**2)) + SeqMul(SeqFormula(n**2, (n, 0, oo)), SeqPer((1, 2), (n, 0, oo))) + >>> SeqMul(SeqFormula(n**3), SeqFormula(n**2)) + SeqFormula(n**5, (n, 0, oo)) + + See Also + ======== + + sympy.series.sequences.SeqAdd + """ + + def __new__(cls, *args, **kwargs): + evaluate = kwargs.get('evaluate', global_parameters.evaluate) + + # flatten inputs + args = list(args) + + # adapted from sympy.sets.sets.Union + def _flatten(arg): + if isinstance(arg, SeqBase): + if isinstance(arg, SeqMul): + return sum(map(_flatten, arg.args), []) + else: + return [arg] + elif iterable(arg): + return sum(map(_flatten, arg), []) + raise TypeError("Input must be Sequences or " + " iterables of Sequences") + args = _flatten(args) + + # Multiplication of no sequences is EmptySequence + if not args: + return S.EmptySequence + + if Intersection(*(a.interval for a in args)) is S.EmptySet: + return S.EmptySequence + + # reduce using known rules + if evaluate: + return SeqMul.reduce(args) + + args = list(ordered(args, SeqBase._start_key)) + + return Basic.__new__(cls, *args) + + @staticmethod + def reduce(args): + """Simplify a :class:`SeqMul` using known rules. + + Explanation + =========== + + Iterates through all pairs and ask the constituent + sequences if they can simplify themselves with any other constituent. + + Notes + ===== + + adapted from ``Union.reduce`` + + """ + new_args = True + while new_args: + for id1, s in enumerate(args): + new_args = False + for id2, t in enumerate(args): + if id1 == id2: + continue + new_seq = s._mul(t) + # This returns None if s does not know how to multiply + # with t. Returns the newly multiplied sequence otherwise + if new_seq is not None: + new_args = [a for a in args if a not in (s, t)] + new_args.append(new_seq) + break + if new_args: + args = new_args + break + + if len(args) == 1: + return args.pop() + else: + return SeqMul(args, evaluate=False) + + def _eval_coeff(self, pt): + """multiplies the coefficients of all the sequences at point pt""" + val = 1 + for a in self.args: + val *= a.coeff(pt) + return val diff --git a/lib/python3.12/site-packages/sympy/series/series.py b/lib/python3.12/site-packages/sympy/series/series.py new file mode 100644 index 0000000000000000000000000000000000000000..e9feec7d3b1987bfaa5238969f531e9f98b88b25 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/series.py @@ -0,0 +1,63 @@ +from sympy.core.sympify import sympify + + +def series(expr, x=None, x0=0, n=6, dir="+"): + """Series expansion of expr around point `x = x0`. + + Parameters + ========== + + expr : Expression + The expression whose series is to be expanded. + + x : Symbol + It is the variable of the expression to be calculated. + + x0 : Value + The value around which ``x`` is calculated. Can be any value + from ``-oo`` to ``oo``. + + n : Value + The number of terms upto which the series is to be expanded. + + dir : String, optional + The series-expansion can be bi-directional. If ``dir="+"``, + then (x->x0+). If ``dir="-"``, then (x->x0-). For infinite + ``x0`` (``oo`` or ``-oo``), the ``dir`` argument is determined + from the direction of the infinity (i.e., ``dir="-"`` for + ``oo``). + + Examples + ======== + + >>> from sympy import series, tan, oo + >>> from sympy.abc import x + >>> f = tan(x) + >>> series(f, x, 2, 6, "+") + tan(2) + (1 + tan(2)**2)*(x - 2) + (x - 2)**2*(tan(2)**3 + tan(2)) + + (x - 2)**3*(1/3 + 4*tan(2)**2/3 + tan(2)**4) + (x - 2)**4*(tan(2)**5 + + 5*tan(2)**3/3 + 2*tan(2)/3) + (x - 2)**5*(2/15 + 17*tan(2)**2/15 + + 2*tan(2)**4 + tan(2)**6) + O((x - 2)**6, (x, 2)) + + >>> series(f, x, 2, 3, "-") + tan(2) + (2 - x)*(-tan(2)**2 - 1) + (2 - x)**2*(tan(2)**3 + tan(2)) + + O((x - 2)**3, (x, 2)) + + >>> series(f, x, 2, oo, "+") + Traceback (most recent call last): + ... + TypeError: 'Infinity' object cannot be interpreted as an integer + + Returns + ======= + + Expr + Series expansion of the expression about x0 + + See Also + ======== + + sympy.core.expr.Expr.series: See the docstring of Expr.series() for complete details of this wrapper. + """ + expr = sympify(expr) + return expr.series(x, x0, n, dir) diff --git a/lib/python3.12/site-packages/sympy/series/series_class.py b/lib/python3.12/site-packages/sympy/series/series_class.py new file mode 100644 index 0000000000000000000000000000000000000000..ff04993b266a3cbd3f767042d4325fb11edb2168 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/series_class.py @@ -0,0 +1,99 @@ +""" +Contains the base class for series +Made using sequences in mind +""" + +from sympy.core.expr import Expr +from sympy.core.singleton import S +from sympy.core.cache import cacheit + + +class SeriesBase(Expr): + """Base Class for series""" + + @property + def interval(self): + """The interval on which the series is defined""" + raise NotImplementedError("(%s).interval" % self) + + @property + def start(self): + """The starting point of the series. This point is included""" + raise NotImplementedError("(%s).start" % self) + + @property + def stop(self): + """The ending point of the series. This point is included""" + raise NotImplementedError("(%s).stop" % self) + + @property + def length(self): + """Length of the series expansion""" + raise NotImplementedError("(%s).length" % self) + + @property + def variables(self): + """Returns a tuple of variables that are bounded""" + return () + + @property + def free_symbols(self): + """ + This method returns the symbols in the object, excluding those + that take on a specific value (i.e. the dummy symbols). + """ + return ({j for i in self.args for j in i.free_symbols} + .difference(self.variables)) + + @cacheit + def term(self, pt): + """Term at point pt of a series""" + if pt < self.start or pt > self.stop: + raise IndexError("Index %s out of bounds %s" % (pt, self.interval)) + return self._eval_term(pt) + + def _eval_term(self, pt): + raise NotImplementedError("The _eval_term method should be added to" + "%s to return series term so it is available" + "when 'term' calls it." + % self.func) + + def _ith_point(self, i): + """ + Returns the i'th point of a series + If start point is negative infinity, point is returned from the end. + Assumes the first point to be indexed zero. + + Examples + ======== + + TODO + """ + if self.start is S.NegativeInfinity: + initial = self.stop + step = -1 + else: + initial = self.start + step = 1 + + return initial + i*step + + def __iter__(self): + i = 0 + while i < self.length: + pt = self._ith_point(i) + yield self.term(pt) + i += 1 + + def __getitem__(self, index): + if isinstance(index, int): + index = self._ith_point(index) + return self.term(index) + elif isinstance(index, slice): + start, stop = index.start, index.stop + if start is None: + start = 0 + if stop is None: + stop = self.length + return [self.term(self._ith_point(i)) for i in + range(start, stop, index.step or 1)] diff --git a/lib/python3.12/site-packages/sympy/series/tests/__init__.py b/lib/python3.12/site-packages/sympy/series/tests/__init__.py new file mode 100644 index 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0000000000000000000000000000000000000000..9c03d2ce38add99b0dce8725b6c8d8844b31f76b --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_approximants.py @@ -0,0 +1,23 @@ +from sympy.series import approximants +from sympy.core.symbol import symbols +from sympy.functions.combinatorial.factorials import binomial +from sympy.functions.combinatorial.numbers import (fibonacci, lucas) + + +def test_approximants(): + x, t = symbols("x,t") + g = [lucas(k) for k in range(16)] + assert list(approximants(g)) == ( + [2, -4/(x - 2), (5*x - 2)/(3*x - 1), (x - 2)/(x**2 + x - 1)] ) + g = [lucas(k)+fibonacci(k+2) for k in range(16)] + assert list(approximants(g)) == ( + [3, -3/(x - 1), (3*x - 3)/(2*x - 1), -3/(x**2 + x - 1)] ) + g = [lucas(k)**2 for k in range(16)] + assert list(approximants(g)) == ( + [4, -16/(x - 4), (35*x - 4)/(9*x - 1), (37*x - 28)/(13*x**2 + 11*x - 7), + (50*x**2 + 63*x - 52)/(37*x**2 + 19*x - 13), + (-x**2 - 7*x + 4)/(x**3 - 2*x**2 - 2*x + 1)] ) + p = [sum(binomial(k,i)*x**i for i in range(k+1)) for k in range(16)] + y = approximants(p, t, simplify=True) + assert next(y) == 1 + assert next(y) == -1/(t*(x + 1) - 1) diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_aseries.py b/lib/python3.12/site-packages/sympy/series/tests/test_aseries.py new file mode 100644 index 0000000000000000000000000000000000000000..055d6b8aef23212a8c8f19475f537a5a2b9e2b1b --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_aseries.py @@ -0,0 +1,56 @@ +from sympy.core.function import PoleError +from sympy.core.numbers import oo +from sympy.core.singleton import S +from sympy.core.symbol import Symbol +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import (cos, sin) +from sympy.series.order import O +from sympy.abc import x + +from sympy.testing.pytest import raises + +def test_simple(): + # Gruntz' theses pp. 91 to 96 + # 6.6 + e = sin(1/x + exp(-x)) - sin(1/x) + assert e.aseries(x) == (1/(24*x**4) - 1/(2*x**2) + 1 + O(x**(-6), (x, oo)))*exp(-x) + + e = exp(x) * (exp(1/x + exp(-x)) - exp(1/x)) + assert e.aseries(x, n=4) == 1/(6*x**3) + 1/(2*x**2) + 1/x + 1 + O(x**(-4), (x, oo)) + + e = exp(exp(x) / (1 - 1/x)) + assert e.aseries(x) == exp(exp(x) / (1 - 1/x)) + + # The implementation of bound in aseries is incorrect currently. This test + # should be commented out when that is fixed. + # assert e.aseries(x, bound=3) == exp(exp(x) / x**2)*exp(exp(x) / x)*exp(-exp(x) + exp(x)/(1 - 1/x) - \ + # exp(x) / x - exp(x) / x**2) * exp(exp(x)) + + e = exp(sin(1/x + exp(-exp(x)))) - exp(sin(1/x)) + assert e.aseries(x, n=4) == (-1/(2*x**3) + 1/x + 1 + O(x**(-4), (x, oo)))*exp(-exp(x)) + + e3 = lambda x:exp(exp(exp(x))) + e = e3(x)/e3(x - 1/e3(x)) + assert e.aseries(x, n=3) == 1 + exp(x + exp(x))*exp(-exp(exp(x)))\ + + ((-exp(x)/2 - S.Half)*exp(x + exp(x))\ + + exp(2*x + 2*exp(x))/2)*exp(-2*exp(exp(x))) + O(exp(-3*exp(exp(x))), (x, oo)) + + e = exp(exp(x)) * (exp(sin(1/x + 1/exp(exp(x)))) - exp(sin(1/x))) + assert e.aseries(x, n=4) == -1/(2*x**3) + 1/x + 1 + O(x**(-4), (x, oo)) + + n = Symbol('n', integer=True) + e = (sqrt(n)*log(n)**2*exp(sqrt(log(n))*log(log(n))**2*exp(sqrt(log(log(n)))*log(log(log(n)))**3)))/n + assert e.aseries(n) == \ + exp(exp(sqrt(log(log(n)))*log(log(log(n)))**3)*sqrt(log(n))*log(log(n))**2)*log(n)**2/sqrt(n) + + +def test_hierarchical(): + e = sin(1/x + exp(-x)) + assert e.aseries(x, n=3, hir=True) == -exp(-2*x)*sin(1/x)/2 + \ + exp(-x)*cos(1/x) + sin(1/x) + O(exp(-3*x), (x, oo)) + + e = sin(x) * cos(exp(-x)) + assert e.aseries(x, hir=True) == exp(-4*x)*sin(x)/24 - \ + exp(-2*x)*sin(x)/2 + sin(x) + O(exp(-6*x), (x, oo)) + raises(PoleError, lambda: e.aseries(x)) diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_demidovich.py b/lib/python3.12/site-packages/sympy/series/tests/test_demidovich.py new file mode 100644 index 0000000000000000000000000000000000000000..98cafbae6f019dd3d97d306099d5780ed2f37f04 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_demidovich.py @@ -0,0 +1,143 @@ +from sympy.core.numbers import (Rational, oo, pi) +from sympy.core.singleton import S +from sympy.core.symbol import Symbol +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.miscellaneous import (root, sqrt) +from sympy.functions.elementary.trigonometric import (asin, cos, sin, tan) +from sympy.polys.rationaltools import together +from sympy.series.limits import limit + +# Numbers listed with the tests refer to problem numbers in the book +# "Anti-demidovich, problemas resueltos, Ed. URSS" + +x = Symbol("x") + + +def test_leadterm(): + assert (3 + 2*x**(log(3)/log(2) - 1)).leadterm(x) == (3, 0) + + +def root3(x): + return root(x, 3) + + +def root4(x): + return root(x, 4) + + +def test_Limits_simple_0(): + assert limit((2**(x + 1) + 3**(x + 1))/(2**x + 3**x), x, oo) == 3 # 175 + + +def test_Limits_simple_1(): + assert limit((x + 1)*(x + 2)*(x + 3)/x**3, x, oo) == 1 # 172 + assert limit(sqrt(x + 1) - sqrt(x), x, oo) == 0 # 179 + assert limit((2*x - 3)*(3*x + 5)*(4*x - 6)/(3*x**3 + x - 1), x, oo) == 8 # Primjer 1 + assert limit(x/root3(x**3 + 10), x, oo) == 1 # Primjer 2 + assert limit((x + 1)**2/(x**2 + 1), x, oo) == 1 # 181 + + +def test_Limits_simple_2(): + assert limit(1000*x/(x**2 - 1), x, oo) == 0 # 182 + assert limit((x**2 - 5*x + 1)/(3*x + 7), x, oo) is oo # 183 + assert limit((2*x**2 - x + 3)/(x**3 - 8*x + 5), x, oo) == 0 # 184 + assert limit((2*x**2 - 3*x - 4)/sqrt(x**4 + 1), x, oo) == 2 # 186 + assert limit((2*x + 3)/(x + root3(x)), x, oo) == 2 # 187 + assert limit(x**2/(10 + x*sqrt(x)), x, oo) is oo # 188 + assert limit(root3(x**2 + 1)/(x + 1), x, oo) == 0 # 189 + assert limit(sqrt(x)/sqrt(x + sqrt(x + sqrt(x))), x, oo) == 1 # 190 + + +def test_Limits_simple_3a(): + a = Symbol('a') + #issue 3513 + assert together(limit((x**2 - (a + 1)*x + a)/(x**3 - a**3), x, a)) == \ + (a - 1)/(3*a**2) # 196 + + +def test_Limits_simple_3b(): + h = Symbol("h") + assert limit(((x + h)**3 - x**3)/h, h, 0) == 3*x**2 # 197 + assert limit((1/(1 - x) - 3/(1 - x**3)), x, 1) == -1 # 198 + assert limit((sqrt(1 + x) - 1)/(root3(1 + x) - 1), x, 0) == Rational(3)/2 # Primer 4 + assert limit((sqrt(x) - 1)/(x - 1), x, 1) == Rational(1)/2 # 199 + assert limit((sqrt(x) - 8)/(root3(x) - 4), x, 64) == 3 # 200 + assert limit((root3(x) - 1)/(root4(x) - 1), x, 1) == Rational(4)/3 # 201 + assert limit( + (root3(x**2) - 2*root3(x) + 1)/(x - 1)**2, x, 1) == Rational(1)/9 # 202 + + +def test_Limits_simple_4a(): + a = Symbol('a') + assert limit((sqrt(x) - sqrt(a))/(x - a), x, a) == 1/(2*sqrt(a)) # Primer 5 + assert limit((sqrt(x) - 1)/(root3(x) - 1), x, 1) == Rational(3, 2) # 205 + assert limit((sqrt(1 + x) - sqrt(1 - x))/x, x, 0) == 1 # 207 + assert limit(sqrt(x**2 - 5*x + 6) - x, x, oo) == Rational(-5, 2) # 213 + + +def test_limits_simple_4aa(): + assert limit(x*(sqrt(x**2 + 1) - x), x, oo) == Rational(1)/2 # 214 + + +def test_Limits_simple_4b(): + #issue 3511 + assert limit(x - root3(x**3 - 1), x, oo) == 0 # 215 + + +def test_Limits_simple_4c(): + assert limit(log(1 + exp(x))/x, x, -oo) == 0 # 267a + assert limit(log(1 + exp(x))/x, x, oo) == 1 # 267b + + +def test_bounded(): + assert limit(sin(x)/x, x, oo) == 0 # 216b + assert limit(x*sin(1/x), x, 0) == 0 # 227a + + +def test_f1a(): + #issue 3508: + assert limit((sin(2*x)/x)**(1 + x), x, 0) == 2 # Primer 7 + + +def test_f1a2(): + #issue 3509: + assert limit(((x - 1)/(x + 1))**x, x, oo) == exp(-2) # Primer 9 + + +def test_f1b(): + m = Symbol("m") + n = Symbol("n") + h = Symbol("h") + a = Symbol("a") + assert limit(sin(x)/x, x, 2) == sin(2)/2 # 216a + assert limit(sin(3*x)/x, x, 0) == 3 # 217 + assert limit(sin(5*x)/sin(2*x), x, 0) == Rational(5, 2) # 218 + assert limit(sin(pi*x)/sin(3*pi*x), x, 0) == Rational(1, 3) # 219 + assert limit(x*sin(pi/x), x, oo) == pi # 220 + assert limit((1 - cos(x))/x**2, x, 0) == S.Half # 221 + assert limit(x*sin(1/x), x, oo) == 1 # 227b + assert limit((cos(m*x) - cos(n*x))/x**2, x, 0) == -m**2/2 + n**2/2 # 232 + assert limit((tan(x) - sin(x))/x**3, x, 0) == S.Half # 233 + assert limit((x - sin(2*x))/(x + sin(3*x)), x, 0) == -Rational(1, 4) # 237 + assert limit((1 - sqrt(cos(x)))/x**2, x, 0) == Rational(1, 4) # 239 + assert limit((sqrt(1 + sin(x)) - sqrt(1 - sin(x)))/x, x, 0) == 1 # 240 + + assert limit((1 + h/x)**x, x, oo) == exp(h) # Primer 9 + assert limit((sin(x) - sin(a))/(x - a), x, a) == cos(a) # 222, *176 + assert limit((cos(x) - cos(a))/(x - a), x, a) == -sin(a) # 223 + assert limit((sin(x + h) - sin(x))/h, h, 0) == cos(x) # 225 + + +def test_f2a(): + assert limit(((x + 1)/(2*x + 1))**(x**2), x, oo) == 0 # Primer 8 + + +def test_f2(): + assert limit((sqrt( + cos(x)) - root3(cos(x)))/(sin(x)**2), x, 0) == -Rational(1, 12) # *184 + + +def test_f3(): + a = Symbol('a') + #issue 3504 + assert limit(asin(a*x)/x, x, 0) == a diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_formal.py b/lib/python3.12/site-packages/sympy/series/tests/test_formal.py new file mode 100644 index 0000000000000000000000000000000000000000..0a28418fbb326ce3aa973eecaf8c3b1231f6c767 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_formal.py @@ -0,0 +1,618 @@ +from sympy.concrete.summations import Sum +from sympy.core.add import Add +from sympy.core.function import (Derivative, Function) +from sympy.core.mul import Mul +from sympy.core.numbers import (I, Rational, oo, pi) +from sympy.core.singleton import S +from sympy.core.symbol import symbols +from sympy.functions.combinatorial.factorials import factorial +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.hyperbolic import (acosh, asech) +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import (acos, asin, atan, cos, sin) +from sympy.functions.special.bessel import airyai +from sympy.functions.special.error_functions import erf +from sympy.functions.special.gamma_functions import gamma +from sympy.integrals.integrals import integrate +from sympy.series.formal import fps +from sympy.series.order import O +from sympy.series.formal import (rational_algorithm, FormalPowerSeries, + FormalPowerSeriesProduct, FormalPowerSeriesCompose, + FormalPowerSeriesInverse, simpleDE, + rational_independent, exp_re, hyper_re) +from sympy.testing.pytest import raises, XFAIL, slow + +x, y, z = symbols('x y z') +n, m, k = symbols('n m k', integer=True) +f, r = Function('f'), Function('r') + + +def test_rational_algorithm(): + f = 1 / ((x - 1)**2 * (x - 2)) + assert rational_algorithm(f, x, k) == \ + (-2**(-k - 1) + 1 - (factorial(k + 1) / factorial(k)), 0, 0) + + f = (1 + x + x**2 + x**3) / ((x - 1) * (x - 2)) + assert rational_algorithm(f, x, k) == \ + (-15*2**(-k - 1) + 4, x + 4, 0) + + f = z / (y*m - m*x - y*x + x**2) + assert rational_algorithm(f, x, k) == \ + (((-y**(-k - 1)*z) / (y - m)) + ((m**(-k - 1)*z) / (y - m)), 0, 0) + + f = x / (1 - x - x**2) + assert rational_algorithm(f, x, k) is None + assert rational_algorithm(f, x, k, full=True) == \ + (((Rational(-1, 2) + sqrt(5)/2)**(-k - 1) * + (-sqrt(5)/10 + S.Half)) + + ((-sqrt(5)/2 - S.Half)**(-k - 1) * + (sqrt(5)/10 + S.Half)), 0, 0) + + f = 1 / (x**2 + 2*x + 2) + assert rational_algorithm(f, x, k) is None + assert rational_algorithm(f, x, k, full=True) == \ + ((I*(-1 + I)**(-k - 1)) / 2 - (I*(-1 - I)**(-k - 1)) / 2, 0, 0) + + f = log(1 + x) + assert rational_algorithm(f, x, k) == \ + (-(-1)**(-k) / k, 0, 1) + + f = atan(x) + assert rational_algorithm(f, x, k) is None + assert rational_algorithm(f, x, k, full=True) == \ + (((I*I**(-k)) / 2 - (I*(-I)**(-k)) / 2) / k, 0, 1) + + f = x*atan(x) - log(1 + x**2) / 2 + assert rational_algorithm(f, x, k) is None + assert rational_algorithm(f, x, k, full=True) == \ + (((I*I**(-k + 1)) / 2 - (I*(-I)**(-k + 1)) / 2) / + (k*(k - 1)), 0, 2) + + f = log((1 + x) / (1 - x)) / 2 - atan(x) + assert rational_algorithm(f, x, k) is None + assert rational_algorithm(f, x, k, full=True) == \ + ((-(-1)**(-k) / 2 - (I*I**(-k)) / 2 + (I*(-I)**(-k)) / 2 + + S.Half) / k, 0, 1) + + assert rational_algorithm(cos(x), x, k) is None + + +def test_rational_independent(): + ri = rational_independent + assert ri([], x) == [] + assert ri([cos(x), sin(x)], x) == [cos(x), sin(x)] + assert ri([x**2, sin(x), x*sin(x), x**3], x) == \ + [x**3 + x**2, x*sin(x) + sin(x)] + assert ri([S.One, x*log(x), log(x), sin(x)/x, cos(x), sin(x), x], x) == \ + [x + 1, x*log(x) + log(x), sin(x)/x + sin(x), cos(x)] + + +def test_simpleDE(): + # Tests just the first valid DE + for DE in simpleDE(exp(x), x, f): + assert DE == (-f(x) + Derivative(f(x), x), 1) + break + for DE in simpleDE(sin(x), x, f): + assert DE == (f(x) + Derivative(f(x), x, x), 2) + break + for DE in simpleDE(log(1 + x), x, f): + assert DE == ((x + 1)*Derivative(f(x), x, 2) + Derivative(f(x), x), 2) + break + for DE in simpleDE(asin(x), x, f): + assert DE == (x*Derivative(f(x), x) + (x**2 - 1)*Derivative(f(x), x, x), + 2) + break + for DE in simpleDE(exp(x)*sin(x), x, f): + assert DE == (2*f(x) - 2*Derivative(f(x)) + Derivative(f(x), x, x), 2) + break + for DE in simpleDE(((1 + x)/(1 - x))**n, x, f): + assert DE == (2*n*f(x) + (x**2 - 1)*Derivative(f(x), x), 1) + break + for DE in simpleDE(airyai(x), x, f): + assert DE == (-x*f(x) + Derivative(f(x), x, x), 2) + break + + +def test_exp_re(): + d = -f(x) + Derivative(f(x), x) + assert exp_re(d, r, k) == -r(k) + r(k + 1) + + d = f(x) + Derivative(f(x), x, x) + assert exp_re(d, r, k) == r(k) + r(k + 2) + + d = f(x) + Derivative(f(x), x) + Derivative(f(x), x, x) + assert exp_re(d, r, k) == r(k) + r(k + 1) + r(k + 2) + + d = Derivative(f(x), x) + Derivative(f(x), x, x) + assert exp_re(d, r, k) == r(k) + r(k + 1) + + d = Derivative(f(x), x, 3) + Derivative(f(x), x, 4) + Derivative(f(x)) + assert exp_re(d, r, k) == r(k) + r(k + 2) + r(k + 3) + + +def test_hyper_re(): + d = f(x) + Derivative(f(x), x, x) + assert hyper_re(d, r, k) == r(k) + (k+1)*(k+2)*r(k + 2) + + d = -x*f(x) + Derivative(f(x), x, x) + assert hyper_re(d, r, k) == (k + 2)*(k + 3)*r(k + 3) - r(k) + + d = 2*f(x) - 2*Derivative(f(x), x) + Derivative(f(x), x, x) + assert hyper_re(d, r, k) == \ + (-2*k - 2)*r(k + 1) + (k + 1)*(k + 2)*r(k + 2) + 2*r(k) + + d = 2*n*f(x) + (x**2 - 1)*Derivative(f(x), x) + assert hyper_re(d, r, k) == \ + k*r(k) + 2*n*r(k + 1) + (-k - 2)*r(k + 2) + + d = (x**10 + 4)*Derivative(f(x), x) + x*(x**10 - 1)*Derivative(f(x), x, x) + assert hyper_re(d, r, k) == \ + (k*(k - 1) + k)*r(k) + (4*k - (k + 9)*(k + 10) + 40)*r(k + 10) + + d = ((x**2 - 1)*Derivative(f(x), x, 3) + 3*x*Derivative(f(x), x, x) + + Derivative(f(x), x)) + assert hyper_re(d, r, k) == \ + ((k*(k - 2)*(k - 1) + 3*k*(k - 1) + k)*r(k) + + (-k*(k + 1)*(k + 2))*r(k + 2)) + + +def test_fps(): + assert fps(1) == 1 + assert fps(2, x) == 2 + assert fps(2, x, dir='+') == 2 + assert fps(2, x, dir='-') == 2 + assert fps(1/x + 1/x**2) == 1/x + 1/x**2 + assert fps(log(1 + x), hyper=False, rational=False) == log(1 + x) + + f = fps(x**2 + x + 1) + assert isinstance(f, FormalPowerSeries) + assert f.function == x**2 + x + 1 + assert f[0] == 1 + assert f[2] == x**2 + assert f.truncate(4) == x**2 + x + 1 + O(x**4) + assert f.polynomial() == x**2 + x + 1 + + f = fps(log(1 + x)) + assert isinstance(f, FormalPowerSeries) + assert f.function == log(1 + x) + assert f.subs(x, y) == f + assert f[:5] == [0, x, -x**2/2, x**3/3, -x**4/4] + assert f.as_leading_term(x) == x + assert f.polynomial(6) == x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + + k = f.ak.variables[0] + assert f.infinite == Sum((-(-1)**(-k)*x**k)/k, (k, 1, oo)) + + ft, s = f.truncate(n=None), f[:5] + for i, t in enumerate(ft): + if i == 5: + break + assert s[i] == t + + f = sin(x).fps(x) + assert isinstance(f, FormalPowerSeries) + assert f.truncate() == x - x**3/6 + x**5/120 + O(x**6) + + raises(NotImplementedError, lambda: fps(y*x)) + raises(ValueError, lambda: fps(x, dir=0)) + + +@slow +def test_fps__rational(): + assert fps(1/x) == (1/x) + assert fps((x**2 + x + 1) / x**3, dir=-1) == (x**2 + x + 1) / x**3 + + f = 1 / ((x - 1)**2 * (x - 2)) + assert fps(f, x).truncate() == \ + (Rational(-1, 2) - x*Rational(5, 4) - 17*x**2/8 - 49*x**3/16 - 129*x**4/32 - + 321*x**5/64 + O(x**6)) + + f = (1 + x + x**2 + x**3) / ((x - 1) * (x - 2)) + assert fps(f, x).truncate() == \ + (S.Half + x*Rational(5, 4) + 17*x**2/8 + 49*x**3/16 + 113*x**4/32 + + 241*x**5/64 + O(x**6)) + + f = x / (1 - x - x**2) + assert fps(f, x, full=True).truncate() == \ + x + x**2 + 2*x**3 + 3*x**4 + 5*x**5 + O(x**6) + + f = 1 / (x**2 + 2*x + 2) + assert fps(f, x, full=True).truncate() == \ + S.Half - x/2 + x**2/4 - x**4/8 + x**5/8 + O(x**6) + + f = log(1 + x) + assert fps(f, x).truncate() == \ + x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6) + assert fps(f, x, dir=1).truncate() == fps(f, x, dir=-1).truncate() + assert fps(f, x, 2).truncate() == \ + (log(3) - Rational(2, 3) - (x - 2)**2/18 + (x - 2)**3/81 - + (x - 2)**4/324 + (x - 2)**5/1215 + x/3 + O((x - 2)**6, (x, 2))) + assert fps(f, x, 2, dir=-1).truncate() == \ + (log(3) - Rational(2, 3) - (-x + 2)**2/18 - (-x + 2)**3/81 - + (-x + 2)**4/324 - (-x + 2)**5/1215 + x/3 + O((x - 2)**6, (x, 2))) + + f = atan(x) + assert fps(f, x, full=True).truncate() == x - x**3/3 + x**5/5 + O(x**6) + assert fps(f, x, full=True, dir=1).truncate() == \ + fps(f, x, full=True, dir=-1).truncate() + assert fps(f, x, 2, full=True).truncate() == \ + (atan(2) - Rational(2, 5) - 2*(x - 2)**2/25 + 11*(x - 2)**3/375 - + 6*(x - 2)**4/625 + 41*(x - 2)**5/15625 + x/5 + O((x - 2)**6, (x, 2))) + assert fps(f, x, 2, full=True, dir=-1).truncate() == \ + (atan(2) - Rational(2, 5) - 2*(-x + 2)**2/25 - 11*(-x + 2)**3/375 - + 6*(-x + 2)**4/625 - 41*(-x + 2)**5/15625 + x/5 + O((x - 2)**6, (x, 2))) + + f = x*atan(x) - log(1 + x**2) / 2 + assert fps(f, x, full=True).truncate() == x**2/2 - x**4/12 + O(x**6) + + f = log((1 + x) / (1 - x)) / 2 - atan(x) + assert fps(f, x, full=True).truncate(n=10) == 2*x**3/3 + 2*x**7/7 + O(x**10) + + +@slow +def test_fps__hyper(): + f = sin(x) + assert fps(f, x).truncate() == x - x**3/6 + x**5/120 + O(x**6) + + f = cos(x) + assert fps(f, x).truncate() == 1 - x**2/2 + x**4/24 + O(x**6) + + f = exp(x) + assert fps(f, x).truncate() == \ + 1 + x + x**2/2 + x**3/6 + x**4/24 + x**5/120 + O(x**6) + + f = atan(x) + assert fps(f, x).truncate() == x - x**3/3 + x**5/5 + O(x**6) + + f = exp(acos(x)) + assert fps(f, x).truncate() == \ + (exp(pi/2) - x*exp(pi/2) + x**2*exp(pi/2)/2 - x**3*exp(pi/2)/3 + + 5*x**4*exp(pi/2)/24 - x**5*exp(pi/2)/6 + O(x**6)) + + f = exp(acosh(x)) + assert fps(f, x).truncate() == I + x - I*x**2/2 - I*x**4/8 + O(x**6) + + f = atan(1/x) + assert fps(f, x).truncate() == pi/2 - x + x**3/3 - x**5/5 + O(x**6) + + f = x*atan(x) - log(1 + x**2) / 2 + assert fps(f, x, rational=False).truncate() == x**2/2 - x**4/12 + O(x**6) + + f = log(1 + x) + assert fps(f, x, rational=False).truncate() == \ + x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6) + + f = airyai(x**2) + assert fps(f, x).truncate() == \ + (3**Rational(5, 6)*gamma(Rational(1, 3))/(6*pi) - + 3**Rational(2, 3)*x**2/(3*gamma(Rational(1, 3))) + O(x**6)) + + f = exp(x)*sin(x) + assert fps(f, x).truncate() == x + x**2 + x**3/3 - x**5/30 + O(x**6) + + f = exp(x)*sin(x)/x + assert fps(f, x).truncate() == 1 + x + x**2/3 - x**4/30 - x**5/90 + O(x**6) + + f = sin(x) * cos(x) + assert fps(f, x).truncate() == x - 2*x**3/3 + 2*x**5/15 + O(x**6) + + +def test_fps_shift(): + f = x**-5*sin(x) + assert fps(f, x).truncate() == \ + 1/x**4 - 1/(6*x**2) + Rational(1, 120) - x**2/5040 + x**4/362880 + O(x**6) + + f = x**2*atan(x) + assert fps(f, x, rational=False).truncate() == \ + x**3 - x**5/3 + O(x**6) + + f = cos(sqrt(x))*x + assert fps(f, x).truncate() == \ + x - x**2/2 + x**3/24 - x**4/720 + x**5/40320 + O(x**6) + + f = x**2*cos(sqrt(x)) + assert fps(f, x).truncate() == \ + x**2 - x**3/2 + x**4/24 - x**5/720 + O(x**6) + + +def test_fps__Add_expr(): + f = x*atan(x) - log(1 + x**2) / 2 + assert fps(f, x).truncate() == x**2/2 - x**4/12 + O(x**6) + + f = sin(x) + cos(x) - exp(x) + log(1 + x) + assert fps(f, x).truncate() == x - 3*x**2/2 - x**4/4 + x**5/5 + O(x**6) + + f = 1/x + sin(x) + assert fps(f, x).truncate() == 1/x + x - x**3/6 + x**5/120 + O(x**6) + + f = sin(x) - cos(x) + 1/(x - 1) + assert fps(f, x).truncate() == \ + -2 - x**2/2 - 7*x**3/6 - 25*x**4/24 - 119*x**5/120 + O(x**6) + + +def test_fps__asymptotic(): + f = exp(x) + assert fps(f, x, oo) == f + assert fps(f, x, -oo).truncate() == O(1/x**6, (x, oo)) + + f = erf(x) + assert fps(f, x, oo).truncate() == 1 + O(1/x**6, (x, oo)) + assert fps(f, x, -oo).truncate() == -1 + O(1/x**6, (x, oo)) + + f = atan(x) + assert fps(f, x, oo, full=True).truncate() == \ + -1/(5*x**5) + 1/(3*x**3) - 1/x + pi/2 + O(1/x**6, (x, oo)) + assert fps(f, x, -oo, full=True).truncate() == \ + -1/(5*x**5) + 1/(3*x**3) - 1/x - pi/2 + O(1/x**6, (x, oo)) + + f = log(1 + x) + assert fps(f, x, oo) != \ + (-1/(5*x**5) - 1/(4*x**4) + 1/(3*x**3) - 1/(2*x**2) + 1/x - log(1/x) + + O(1/x**6, (x, oo))) + assert fps(f, x, -oo) != \ + (-1/(5*x**5) - 1/(4*x**4) + 1/(3*x**3) - 1/(2*x**2) + 1/x + I*pi - + log(-1/x) + O(1/x**6, (x, oo))) + + +def test_fps__fractional(): + f = sin(sqrt(x)) / x + assert fps(f, x).truncate() == \ + (1/sqrt(x) - sqrt(x)/6 + x**Rational(3, 2)/120 - + x**Rational(5, 2)/5040 + x**Rational(7, 2)/362880 - + x**Rational(9, 2)/39916800 + x**Rational(11, 2)/6227020800 + O(x**6)) + + f = sin(sqrt(x)) * x + assert fps(f, x).truncate() == \ + (x**Rational(3, 2) - x**Rational(5, 2)/6 + x**Rational(7, 2)/120 - + x**Rational(9, 2)/5040 + x**Rational(11, 2)/362880 + O(x**6)) + + f = atan(sqrt(x)) / x**2 + assert fps(f, x).truncate() == \ + (x**Rational(-3, 2) - x**Rational(-1, 2)/3 + x**S.Half/5 - + x**Rational(3, 2)/7 + x**Rational(5, 2)/9 - x**Rational(7, 2)/11 + + x**Rational(9, 2)/13 - x**Rational(11, 2)/15 + O(x**6)) + + f = exp(sqrt(x)) + assert fps(f, x).truncate().expand() == \ + (1 + x/2 + x**2/24 + x**3/720 + x**4/40320 + x**5/3628800 + sqrt(x) + + x**Rational(3, 2)/6 + x**Rational(5, 2)/120 + x**Rational(7, 2)/5040 + + x**Rational(9, 2)/362880 + x**Rational(11, 2)/39916800 + O(x**6)) + + f = exp(sqrt(x))*x + assert fps(f, x).truncate().expand() == \ + (x + x**2/2 + x**3/24 + x**4/720 + x**5/40320 + x**Rational(3, 2) + + x**Rational(5, 2)/6 + x**Rational(7, 2)/120 + x**Rational(9, 2)/5040 + + x**Rational(11, 2)/362880 + O(x**6)) + + +def test_fps__logarithmic_singularity(): + f = log(1 + 1/x) + assert fps(f, x) != \ + -log(x) + x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6) + assert fps(f, x, rational=False) != \ + -log(x) + x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6) + + +@XFAIL +def test_fps__logarithmic_singularity_fail(): + f = asech(x) # Algorithms for computing limits probably needs improvemnts + assert fps(f, x) == log(2) - log(x) - x**2/4 - 3*x**4/64 + O(x**6) + + +def test_fps_symbolic(): + f = x**n*sin(x**2) + assert fps(f, x).truncate(8) == x**(n + 2) - x**(n + 6)/6 + O(x**(n + 8), x) + + f = x**n*log(1 + x) + fp = fps(f, x) + k = fp.ak.variables[0] + assert fp.infinite == \ + Sum((-(-1)**(-k)*x**(k + n))/k, (k, 1, oo)) + + f = (x - 2)**n*log(1 + x) + assert fps(f, x, 2).truncate() == \ + ((x - 2)**n*log(3) + (x - 2)**(n + 1)/3 - (x - 2)**(n + 2)/18 + (x - 2)**(n + 3)/81 - + (x - 2)**(n + 4)/324 + (x - 2)**(n + 5)/1215 + O((x - 2)**(n + 6), (x, 2))) + + f = x**(n - 2)*cos(x) + assert fps(f, x).truncate() == \ + (x**(n - 2) - x**n/2 + x**(n + 2)/24 + O(x**(n + 4), x)) + + f = x**(n - 2)*sin(x) + x**n*exp(x) + assert fps(f, x).truncate() == \ + (x**(n - 1) + x**(n + 1) + x**(n + 2)/2 + x**n + + x**(n + 4)/24 + x**(n + 5)/60 + O(x**(n + 6), x)) + + f = x**n*atan(x) + assert fps(f, x, oo).truncate() == \ + (-x**(n - 5)/5 + x**(n - 3)/3 + x**n*(pi/2 - 1/x) + + O((1/x)**(-n)/x**6, (x, oo))) + + f = x**(n/2)*cos(x) + assert fps(f, x).truncate() == \ + x**(n/2) - x**(n/2 + 2)/2 + x**(n/2 + 4)/24 + O(x**(n/2 + 6), x) + + f = x**(n + m)*sin(x) + assert fps(f, x).truncate() == \ + x**(m + n + 1) - x**(m + n + 3)/6 + x**(m + n + 5)/120 + O(x**(m + n + 6), x) + + +def test_fps__slow(): + f = x*exp(x)*sin(2*x) # TODO: rsolve needs improvement + assert fps(f, x).truncate() == 2*x**2 + 2*x**3 - x**4/3 - x**5 + O(x**6) + + +def test_fps__operations(): + f1, f2 = fps(sin(x)), fps(cos(x)) + + fsum = f1 + f2 + assert fsum.function == sin(x) + cos(x) + assert fsum.truncate() == \ + 1 + x - x**2/2 - x**3/6 + x**4/24 + x**5/120 + O(x**6) + + fsum = f1 + 1 + assert fsum.function == sin(x) + 1 + assert fsum.truncate() == 1 + x - x**3/6 + x**5/120 + O(x**6) + + fsum = 1 + f2 + assert fsum.function == cos(x) + 1 + assert fsum.truncate() == 2 - x**2/2 + x**4/24 + O(x**6) + + assert (f1 + x) == Add(f1, x) + + assert -f2.truncate() == -1 + x**2/2 - x**4/24 + O(x**6) + assert (f1 - f1) is S.Zero + + fsub = f1 - f2 + assert fsub.function == sin(x) - cos(x) + assert fsub.truncate() == \ + -1 + x + x**2/2 - x**3/6 - x**4/24 + x**5/120 + O(x**6) + + fsub = f1 - 1 + assert fsub.function == sin(x) - 1 + assert fsub.truncate() == -1 + x - x**3/6 + x**5/120 + O(x**6) + + fsub = 1 - f2 + assert fsub.function == -cos(x) + 1 + assert fsub.truncate() == x**2/2 - x**4/24 + O(x**6) + + raises(ValueError, lambda: f1 + fps(exp(x), dir=-1)) + raises(ValueError, lambda: f1 + fps(exp(x), x0=1)) + + fm = f1 * 3 + + assert fm.function == 3*sin(x) + assert fm.truncate() == 3*x - x**3/2 + x**5/40 + O(x**6) + + fm = 3 * f2 + + assert fm.function == 3*cos(x) + assert fm.truncate() == 3 - 3*x**2/2 + x**4/8 + O(x**6) + + assert (f1 * f2) == Mul(f1, f2) + assert (f1 * x) == Mul(f1, x) + + fd = f1.diff() + assert fd.function == cos(x) + assert fd.truncate() == 1 - x**2/2 + x**4/24 + O(x**6) + + fd = f2.diff() + assert fd.function == -sin(x) + assert fd.truncate() == -x + x**3/6 - x**5/120 + O(x**6) + + fd = f2.diff().diff() + assert fd.function == -cos(x) + assert fd.truncate() == -1 + x**2/2 - x**4/24 + O(x**6) + + f3 = fps(exp(sqrt(x))) + fd = f3.diff() + assert fd.truncate().expand() == \ + (1/(2*sqrt(x)) + S.Half + x/12 + x**2/240 + x**3/10080 + x**4/725760 + + x**5/79833600 + sqrt(x)/4 + x**Rational(3, 2)/48 + x**Rational(5, 2)/1440 + + x**Rational(7, 2)/80640 + x**Rational(9, 2)/7257600 + x**Rational(11, 2)/958003200 + + O(x**6)) + + assert f1.integrate((x, 0, 1)) == -cos(1) + 1 + assert integrate(f1, (x, 0, 1)) == -cos(1) + 1 + + fi = integrate(f1, x) + assert fi.function == -cos(x) + assert fi.truncate() == -1 + x**2/2 - x**4/24 + O(x**6) + + fi = f2.integrate(x) + assert fi.function == sin(x) + assert fi.truncate() == x - x**3/6 + x**5/120 + O(x**6) + +def test_fps__product(): + f1, f2, f3 = fps(sin(x)), fps(exp(x)), fps(cos(x)) + + raises(ValueError, lambda: f1.product(exp(x), x)) + raises(ValueError, lambda: f1.product(fps(exp(x), dir=-1), x, 4)) + raises(ValueError, lambda: f1.product(fps(exp(x), x0=1), x, 4)) + raises(ValueError, lambda: f1.product(fps(exp(y)), x, 4)) + + fprod = f1.product(f2, x) + assert isinstance(fprod, FormalPowerSeriesProduct) + assert isinstance(fprod.ffps, FormalPowerSeries) + assert isinstance(fprod.gfps, FormalPowerSeries) + assert fprod.f == sin(x) + assert fprod.g == exp(x) + assert fprod.function == sin(x) * exp(x) + assert fprod._eval_terms(4) == x + x**2 + x**3/3 + assert fprod.truncate(4) == x + x**2 + x**3/3 + O(x**4) + assert fprod.polynomial(4) == x + x**2 + x**3/3 + + raises(NotImplementedError, lambda: fprod._eval_term(5)) + raises(NotImplementedError, lambda: fprod.infinite) + raises(NotImplementedError, lambda: fprod._eval_derivative(x)) + raises(NotImplementedError, lambda: fprod.integrate(x)) + + assert f1.product(f3, x)._eval_terms(4) == x - 2*x**3/3 + assert f1.product(f3, x).truncate(4) == x - 2*x**3/3 + O(x**4) + + +def test_fps__compose(): + f1, f2, f3 = fps(exp(x)), fps(sin(x)), fps(cos(x)) + + raises(ValueError, lambda: f1.compose(sin(x), x)) + raises(ValueError, lambda: f1.compose(fps(sin(x), dir=-1), x, 4)) + raises(ValueError, lambda: f1.compose(fps(sin(x), x0=1), x, 4)) + raises(ValueError, lambda: f1.compose(fps(sin(y)), x, 4)) + + raises(ValueError, lambda: f1.compose(f3, x)) + raises(ValueError, lambda: f2.compose(f3, x)) + + fcomp = f1.compose(f2, x) + assert isinstance(fcomp, FormalPowerSeriesCompose) + assert isinstance(fcomp.ffps, FormalPowerSeries) + assert isinstance(fcomp.gfps, FormalPowerSeries) + assert fcomp.f == exp(x) + assert fcomp.g == sin(x) + assert fcomp.function == exp(sin(x)) + assert fcomp._eval_terms(6) == 1 + x + x**2/2 - x**4/8 - x**5/15 + assert fcomp.truncate() == 1 + x + x**2/2 - x**4/8 - x**5/15 + O(x**6) + assert fcomp.truncate(5) == 1 + x + x**2/2 - x**4/8 + O(x**5) + + raises(NotImplementedError, lambda: fcomp._eval_term(5)) + raises(NotImplementedError, lambda: fcomp.infinite) + raises(NotImplementedError, lambda: fcomp._eval_derivative(x)) + raises(NotImplementedError, lambda: fcomp.integrate(x)) + + assert f1.compose(f2, x).truncate(4) == 1 + x + x**2/2 + O(x**4) + assert f1.compose(f2, x).truncate(8) == \ + 1 + x + x**2/2 - x**4/8 - x**5/15 - x**6/240 + x**7/90 + O(x**8) + assert f1.compose(f2, x).truncate(6) == \ + 1 + x + x**2/2 - x**4/8 - x**5/15 + O(x**6) + + assert f2.compose(f2, x).truncate(4) == x - x**3/3 + O(x**4) + assert f2.compose(f2, x).truncate(8) == x - x**3/3 + x**5/10 - 8*x**7/315 + O(x**8) + assert f2.compose(f2, x).truncate(6) == x - x**3/3 + x**5/10 + O(x**6) + + +def test_fps__inverse(): + f1, f2, f3 = fps(sin(x)), fps(exp(x)), fps(cos(x)) + + raises(ValueError, lambda: f1.inverse(x)) + + finv = f2.inverse(x) + assert isinstance(finv, FormalPowerSeriesInverse) + assert isinstance(finv.ffps, FormalPowerSeries) + raises(ValueError, lambda: finv.gfps) + + assert finv.f == exp(x) + assert finv.function == exp(-x) + assert finv._eval_terms(5) == 1 - x + x**2/2 - x**3/6 + x**4/24 + assert finv.truncate() == 1 - x + x**2/2 - x**3/6 + x**4/24 - x**5/120 + O(x**6) + assert finv.truncate(5) == 1 - x + x**2/2 - x**3/6 + x**4/24 + O(x**5) + + raises(NotImplementedError, lambda: finv._eval_term(5)) + raises(ValueError, lambda: finv.g) + raises(NotImplementedError, lambda: finv.infinite) + raises(NotImplementedError, lambda: finv._eval_derivative(x)) + raises(NotImplementedError, lambda: finv.integrate(x)) + + assert f2.inverse(x).truncate(8) == \ + 1 - x + x**2/2 - x**3/6 + x**4/24 - x**5/120 + x**6/720 - x**7/5040 + O(x**8) + + assert f3.inverse(x).truncate() == 1 + x**2/2 + 5*x**4/24 + O(x**6) + assert f3.inverse(x).truncate(8) == 1 + x**2/2 + 5*x**4/24 + 61*x**6/720 + O(x**8) diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_fourier.py b/lib/python3.12/site-packages/sympy/series/tests/test_fourier.py new file mode 100644 index 0000000000000000000000000000000000000000..e3f206af3cc0c43e78065d8a1b788bf5138131bd --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_fourier.py @@ -0,0 +1,165 @@ +from sympy.core.add import Add +from sympy.core.numbers import (Rational, oo, pi) +from sympy.core.singleton import S +from sympy.core.symbol import symbols +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.piecewise import Piecewise +from sympy.functions.elementary.trigonometric import (cos, sin, sinc, tan) +from sympy.series.fourier import fourier_series +from sympy.series.fourier import FourierSeries +from sympy.testing.pytest import raises +from functools import lru_cache + +x, y, z = symbols('x y z') + +# Don't declare these during import because they are slow +@lru_cache() +def _get_examples(): + fo = fourier_series(x, (x, -pi, pi)) + fe = fourier_series(x**2, (-pi, pi)) + fp = fourier_series(Piecewise((0, x < 0), (pi, True)), (x, -pi, pi)) + return fo, fe, fp + + +def test_FourierSeries(): + fo, fe, fp = _get_examples() + + assert fourier_series(1, (-pi, pi)) == 1 + assert (Piecewise((0, x < 0), (pi, True)). + fourier_series((x, -pi, pi)).truncate()) == fp.truncate() + assert isinstance(fo, FourierSeries) + assert fo.function == x + assert fo.x == x + assert fo.period == (-pi, pi) + + assert fo.term(3) == 2*sin(3*x) / 3 + assert fe.term(3) == -4*cos(3*x) / 9 + assert fp.term(3) == 2*sin(3*x) / 3 + + assert fo.as_leading_term(x) == 2*sin(x) + assert fe.as_leading_term(x) == pi**2 / 3 + assert fp.as_leading_term(x) == pi / 2 + + assert fo.truncate() == 2*sin(x) - sin(2*x) + (2*sin(3*x) / 3) + assert fe.truncate() == -4*cos(x) + cos(2*x) + pi**2 / 3 + assert fp.truncate() == 2*sin(x) + (2*sin(3*x) / 3) + pi / 2 + + fot = fo.truncate(n=None) + s = [0, 2*sin(x), -sin(2*x)] + for i, t in enumerate(fot): + if i == 3: + break + assert s[i] == t + + def _check_iter(f, i): + for ind, t in enumerate(f): + assert t == f[ind] + if ind == i: + break + + _check_iter(fo, 3) + _check_iter(fe, 3) + _check_iter(fp, 3) + + assert fo.subs(x, x**2) == fo + + raises(ValueError, lambda: fourier_series(x, (0, 1, 2))) + raises(ValueError, lambda: fourier_series(x, (x, 0, oo))) + raises(ValueError, lambda: fourier_series(x*y, (0, oo))) + + +def test_FourierSeries_2(): + p = Piecewise((0, x < 0), (x, True)) + f = fourier_series(p, (x, -2, 2)) + + assert f.term(3) == (2*sin(3*pi*x / 2) / (3*pi) - + 4*cos(3*pi*x / 2) / (9*pi**2)) + assert f.truncate() == (2*sin(pi*x / 2) / pi - sin(pi*x) / pi - + 4*cos(pi*x / 2) / pi**2 + S.Half) + + +def test_square_wave(): + """Test if fourier_series approximates discontinuous function correctly.""" + square_wave = Piecewise((1, x < pi), (-1, True)) + s = fourier_series(square_wave, (x, 0, 2*pi)) + + assert s.truncate(3) == 4 / pi * sin(x) + 4 / (3 * pi) * sin(3 * x) + \ + 4 / (5 * pi) * sin(5 * x) + assert s.sigma_approximation(4) == 4 / pi * sin(x) * sinc(pi / 4) + \ + 4 / (3 * pi) * sin(3 * x) * sinc(3 * pi / 4) + + +def test_sawtooth_wave(): + s = fourier_series(x, (x, 0, pi)) + assert s.truncate(4) == \ + pi/2 - sin(2*x) - sin(4*x)/2 - sin(6*x)/3 + s = fourier_series(x, (x, 0, 1)) + assert s.truncate(4) == \ + S.Half - sin(2*pi*x)/pi - sin(4*pi*x)/(2*pi) - sin(6*pi*x)/(3*pi) + + +def test_FourierSeries__operations(): + fo, fe, fp = _get_examples() + + fes = fe.scale(-1).shift(pi**2) + assert fes.truncate() == 4*cos(x) - cos(2*x) + 2*pi**2 / 3 + + assert fp.shift(-pi/2).truncate() == (2*sin(x) + (2*sin(3*x) / 3) + + (2*sin(5*x) / 5)) + + fos = fo.scale(3) + assert fos.truncate() == 6*sin(x) - 3*sin(2*x) + 2*sin(3*x) + + fx = fe.scalex(2).shiftx(1) + assert fx.truncate() == -4*cos(2*x + 2) + cos(4*x + 4) + pi**2 / 3 + + fl = fe.scalex(3).shift(-pi).scalex(2).shiftx(1).scale(4) + assert fl.truncate() == (-16*cos(6*x + 6) + 4*cos(12*x + 12) - + 4*pi + 4*pi**2 / 3) + + raises(ValueError, lambda: fo.shift(x)) + raises(ValueError, lambda: fo.shiftx(sin(x))) + raises(ValueError, lambda: fo.scale(x*y)) + raises(ValueError, lambda: fo.scalex(x**2)) + + +def test_FourierSeries__neg(): + fo, fe, fp = _get_examples() + + assert (-fo).truncate() == -2*sin(x) + sin(2*x) - (2*sin(3*x) / 3) + assert (-fe).truncate() == +4*cos(x) - cos(2*x) - pi**2 / 3 + + +def test_FourierSeries__add__sub(): + fo, fe, fp = _get_examples() + + assert fo + fo == fo.scale(2) + assert fo - fo == 0 + assert -fe - fe == fe.scale(-2) + + assert (fo + fe).truncate() == 2*sin(x) - sin(2*x) - 4*cos(x) + cos(2*x) \ + + pi**2 / 3 + assert (fo - fe).truncate() == 2*sin(x) - sin(2*x) + 4*cos(x) - cos(2*x) \ + - pi**2 / 3 + + assert isinstance(fo + 1, Add) + + raises(ValueError, lambda: fo + fourier_series(x, (x, 0, 2))) + + +def test_FourierSeries_finite(): + + assert fourier_series(sin(x)).truncate(1) == sin(x) + # assert type(fourier_series(sin(x)*log(x))).truncate() == FourierSeries + # assert type(fourier_series(sin(x**2+6))).truncate() == FourierSeries + assert fourier_series(sin(x)*log(y)*exp(z),(x,pi,-pi)).truncate() == sin(x)*log(y)*exp(z) + assert fourier_series(sin(x)**6).truncate(oo) == -15*cos(2*x)/32 + 3*cos(4*x)/16 - cos(6*x)/32 \ + + Rational(5, 16) + assert fourier_series(sin(x) ** 6).truncate() == -15 * cos(2 * x) / 32 + 3 * cos(4 * x) / 16 \ + + Rational(5, 16) + assert fourier_series(sin(4*x+3) + cos(3*x+4)).truncate(oo) == -sin(4)*sin(3*x) + sin(4*x)*cos(3) \ + + cos(4)*cos(3*x) + sin(3)*cos(4*x) + assert fourier_series(sin(x)+cos(x)*tan(x)).truncate(oo) == 2*sin(x) + assert fourier_series(cos(pi*x), (x, -1, 1)).truncate(oo) == cos(pi*x) + assert fourier_series(cos(3*pi*x + 4) - sin(4*pi*x)*log(pi*y), (x, -1, 1)).truncate(oo) == -log(pi*y)*sin(4*pi*x)\ + - sin(4)*sin(3*pi*x) + cos(4)*cos(3*pi*x) diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_gruntz.py b/lib/python3.12/site-packages/sympy/series/tests/test_gruntz.py new file mode 100644 index 0000000000000000000000000000000000000000..4565c876085b04e7f521bcf79571daf4a93ad653 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_gruntz.py @@ -0,0 +1,482 @@ +from sympy.core import EulerGamma +from sympy.core.numbers import (E, I, Integer, Rational, oo, pi) +from sympy.core.singleton import S +from sympy.core.symbol import Symbol +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import (acot, atan, cos, sin) +from sympy.functions.elementary.complexes import sign as _sign +from sympy.functions.special.error_functions import (Ei, erf) +from sympy.functions.special.gamma_functions import (digamma, gamma, loggamma) +from sympy.functions.special.zeta_functions import zeta +from sympy.polys.polytools import cancel +from sympy.functions.elementary.hyperbolic import cosh, coth, sinh, tanh +from sympy.series.gruntz import compare, mrv, rewrite, mrv_leadterm, gruntz, \ + sign +from sympy.testing.pytest import XFAIL, skip, slow + +""" +This test suite is testing the limit algorithm using the bottom up approach. +See the documentation in limits2.py. The algorithm itself is highly recursive +by nature, so "compare" is logically the lowest part of the algorithm, yet in +some sense it's the most complex part, because it needs to calculate a limit +to return the result. + +Nevertheless, the rest of the algorithm depends on compare working correctly. +""" + +x = Symbol('x', real=True) +m = Symbol('m', real=True) + + +runslow = False + + +def _sskip(): + if not runslow: + skip("slow") + + +@slow +def test_gruntz_evaluation(): + # Gruntz' thesis pp. 122 to 123 + # 8.1 + assert gruntz(exp(x)*(exp(1/x - exp(-x)) - exp(1/x)), x, oo) == -1 + # 8.2 + assert gruntz(exp(x)*(exp(1/x + exp(-x) + exp(-x**2)) + - exp(1/x - exp(-exp(x)))), x, oo) == 1 + # 8.3 + assert gruntz(exp(exp(x - exp(-x))/(1 - 1/x)) - exp(exp(x)), x, oo) is oo + # 8.5 + assert gruntz(exp(exp(exp(x + exp(-x)))) / exp(exp(exp(x))), x, oo) is oo + # 8.6 + assert gruntz(exp(exp(exp(x))) / exp(exp(exp(x - exp(-exp(x))))), + x, oo) is oo + # 8.7 + assert gruntz(exp(exp(exp(x))) / exp(exp(exp(x - exp(-exp(exp(x)))))), + x, oo) == 1 + # 8.8 + assert gruntz(exp(exp(x)) / exp(exp(x - exp(-exp(exp(x))))), x, oo) == 1 + # 8.9 + assert gruntz(log(x)**2 * exp(sqrt(log(x))*(log(log(x)))**2 + * exp(sqrt(log(log(x))) * (log(log(log(x))))**3)) / sqrt(x), + x, oo) == 0 + # 8.10 + assert gruntz((x*log(x)*(log(x*exp(x) - x**2))**2) + / (log(log(x**2 + 2*exp(exp(3*x**3*log(x)))))), x, oo) == Rational(1, 3) + # 8.11 + assert gruntz((exp(x*exp(-x)/(exp(-x) + exp(-2*x**2/(x + 1)))) - exp(x))/x, + x, oo) == -exp(2) + # 8.12 + assert gruntz((3**x + 5**x)**(1/x), x, oo) == 5 + # 8.13 + assert gruntz(x/log(x**(log(x**(log(2)/log(x))))), x, oo) is oo + # 8.14 + assert gruntz(exp(exp(2*log(x**5 + x)*log(log(x)))) + / exp(exp(10*log(x)*log(log(x)))), x, oo) is oo + # 8.15 + assert gruntz(exp(exp(Rational(5, 2)*x**Rational(-5, 7) + Rational(21, 8)*x**Rational(6, 11) + + 2*x**(-8) + Rational(54, 17)*x**Rational(49, 45)))**8 + / log(log(-log(Rational(4, 3)*x**Rational(-5, 14))))**Rational(7, 6), x, oo) is oo + # 8.16 + assert gruntz((exp(4*x*exp(-x)/(1/exp(x) + 1/exp(2*x**2/(x + 1)))) - exp(x)) + / exp(x)**4, x, oo) == 1 + # 8.17 + assert gruntz(exp(x*exp(-x)/(exp(-x) + exp(-2*x**2/(x + 1))))/exp(x), x, oo) \ + == 1 + # 8.19 + assert gruntz(log(x)*(log(log(x) + log(log(x))) - log(log(x))) + / (log(log(x) + log(log(log(x))))), x, oo) == 1 + # 8.20 + assert gruntz(exp((log(log(x + exp(log(x)*log(log(x)))))) + / (log(log(log(exp(x) + x + log(x)))))), x, oo) == E + # Another + assert gruntz(exp(exp(exp(x + exp(-x)))) / exp(exp(x)), x, oo) is oo + + +def test_gruntz_evaluation_slow(): + _sskip() + # 8.4 + assert gruntz(exp(exp(exp(x)/(1 - 1/x))) + - exp(exp(exp(x)/(1 - 1/x - log(x)**(-log(x))))), x, oo) is -oo + # 8.18 + assert gruntz((exp(exp(-x/(1 + exp(-x))))*exp(-x/(1 + exp(-x/(1 + exp(-x))))) + *exp(exp(-x + exp(-x/(1 + exp(-x)))))) + / (exp(-x/(1 + exp(-x))))**2 - exp(x) + x, x, oo) == 2 + + +@slow +def test_gruntz_eval_special(): + # Gruntz, p. 126 + assert gruntz(exp(x)*(sin(1/x + exp(-x)) - sin(1/x + exp(-x**2))), x, oo) == 1 + assert gruntz((erf(x - exp(-exp(x))) - erf(x)) * exp(exp(x)) * exp(x**2), + x, oo) == -2/sqrt(pi) + assert gruntz(exp(exp(x)) * (exp(sin(1/x + exp(-exp(x)))) - exp(sin(1/x))), + x, oo) == 1 + assert gruntz(exp(x)*(gamma(x + exp(-x)) - gamma(x)), x, oo) is oo + assert gruntz(exp(exp(digamma(digamma(x))))/x, x, oo) == exp(Rational(-1, 2)) + assert gruntz(exp(exp(digamma(log(x))))/x, x, oo) == exp(Rational(-1, 2)) + assert gruntz(digamma(digamma(digamma(x))), x, oo) is oo + assert gruntz(loggamma(loggamma(x)), x, oo) is oo + assert gruntz(((gamma(x + 1/gamma(x)) - gamma(x))/log(x) - cos(1/x)) + * x*log(x), x, oo) == Rational(-1, 2) + assert gruntz(x * (gamma(x - 1/gamma(x)) - gamma(x) + log(x)), x, oo) \ + == S.Half + assert gruntz((gamma(x + 1/gamma(x)) - gamma(x)) / log(x), x, oo) == 1 + + +def test_gruntz_eval_special_slow(): + _sskip() + assert gruntz(gamma(x + 1)/sqrt(2*pi) + - exp(-x)*(x**(x + S.Half) + x**(x - S.Half)/12), x, oo) is oo + assert gruntz(exp(exp(exp(digamma(digamma(digamma(x))))))/x, x, oo) == 0 + + +@XFAIL +def test_grunts_eval_special_slow_sometimes_fail(): + _sskip() + # XXX This sometimes fails!!! + assert gruntz(exp(gamma(x - exp(-x))*exp(1/x)) - exp(gamma(x)), x, oo) is oo + + +def test_gruntz_Ei(): + assert gruntz((Ei(x - exp(-exp(x))) - Ei(x)) *exp(-x)*exp(exp(x))*x, x, oo) == -1 + + +@XFAIL +def test_gruntz_eval_special_fail(): + # TODO zeta function series + assert gruntz( + exp((log(2) + 1)*x) * (zeta(x + exp(-x)) - zeta(x)), x, oo) == -log(2) + + # TODO 8.35 - 8.37 (bessel, max-min) + + +def test_gruntz_hyperbolic(): + assert gruntz(cosh(x), x, oo) is oo + assert gruntz(cosh(x), x, -oo) is oo + assert gruntz(sinh(x), x, oo) is oo + assert gruntz(sinh(x), x, -oo) is -oo + assert gruntz(2*cosh(x)*exp(x), x, oo) is oo + assert gruntz(2*cosh(x)*exp(x), x, -oo) == 1 + assert gruntz(2*sinh(x)*exp(x), x, oo) is oo + assert gruntz(2*sinh(x)*exp(x), x, -oo) == -1 + assert gruntz(tanh(x), x, oo) == 1 + assert gruntz(tanh(x), x, -oo) == -1 + assert gruntz(coth(x), x, oo) == 1 + assert gruntz(coth(x), x, -oo) == -1 + + +def test_compare1(): + assert compare(2, x, x) == "<" + assert compare(x, exp(x), x) == "<" + assert compare(exp(x), exp(x**2), x) == "<" + assert compare(exp(x**2), exp(exp(x)), x) == "<" + assert compare(1, exp(exp(x)), x) == "<" + + assert compare(x, 2, x) == ">" + assert compare(exp(x), x, x) == ">" + assert compare(exp(x**2), exp(x), x) == ">" + assert compare(exp(exp(x)), exp(x**2), x) == ">" + assert compare(exp(exp(x)), 1, x) == ">" + + assert compare(2, 3, x) == "=" + assert compare(3, -5, x) == "=" + assert compare(2, -5, x) == "=" + + assert compare(x, x**2, x) == "=" + assert compare(x**2, x**3, x) == "=" + assert compare(x**3, 1/x, x) == "=" + assert compare(1/x, x**m, x) == "=" + assert compare(x**m, -x, x) == "=" + + assert compare(exp(x), exp(-x), x) == "=" + assert compare(exp(-x), exp(2*x), x) == "=" + assert compare(exp(2*x), exp(x)**2, x) == "=" + assert compare(exp(x)**2, exp(x + exp(-x)), x) == "=" + assert compare(exp(x), exp(x + exp(-x)), x) == "=" + + assert compare(exp(x**2), 1/exp(x**2), x) == "=" + + +def test_compare2(): + assert compare(exp(x), x**5, x) == ">" + assert compare(exp(x**2), exp(x)**2, x) == ">" + assert compare(exp(x), exp(x + exp(-x)), x) == "=" + assert compare(exp(x + exp(-x)), exp(x), x) == "=" + assert compare(exp(x + exp(-x)), exp(-x), x) == "=" + assert compare(exp(-x), x, x) == ">" + assert compare(x, exp(-x), x) == "<" + assert compare(exp(x + 1/x), x, x) == ">" + assert compare(exp(-exp(x)), exp(x), x) == ">" + assert compare(exp(exp(-exp(x)) + x), exp(-exp(x)), x) == "<" + + +def test_compare3(): + assert compare(exp(exp(x)), exp(x + exp(-exp(x))), x) == ">" + + +def test_sign1(): + assert sign(Rational(0), x) == 0 + assert sign(Rational(3), x) == 1 + assert sign(Rational(-5), x) == -1 + assert sign(log(x), x) == 1 + assert sign(exp(-x), x) == 1 + assert sign(exp(x), x) == 1 + assert sign(-exp(x), x) == -1 + assert sign(3 - 1/x, x) == 1 + assert sign(-3 - 1/x, x) == -1 + assert sign(sin(1/x), x) == 1 + assert sign((x**Integer(2)), x) == 1 + assert sign(x**2, x) == 1 + assert sign(x**5, x) == 1 + + +def test_sign2(): + assert sign(x, x) == 1 + assert sign(-x, x) == -1 + y = Symbol("y", positive=True) + assert sign(y, x) == 1 + assert sign(-y, x) == -1 + assert sign(y*x, x) == 1 + assert sign(-y*x, x) == -1 + + +def mmrv(a, b): + return set(mrv(a, b)[0].keys()) + + +def test_mrv1(): + assert mmrv(x, x) == {x} + assert mmrv(x + 1/x, x) == {x} + assert mmrv(x**2, x) == {x} + assert mmrv(log(x), x) == {x} + assert mmrv(exp(x), x) == {exp(x)} + assert mmrv(exp(-x), x) == {exp(-x)} + assert mmrv(exp(x**2), x) == {exp(x**2)} + assert mmrv(-exp(1/x), x) == {x} + assert mmrv(exp(x + 1/x), x) == {exp(x + 1/x)} + + +def test_mrv2a(): + assert mmrv(exp(x + exp(-exp(x))), x) == {exp(-exp(x))} + assert mmrv(exp(x + exp(-x)), x) == {exp(x + exp(-x)), exp(-x)} + assert mmrv(exp(1/x + exp(-x)), x) == {exp(-x)} + +#sometimes infinite recursion due to log(exp(x**2)) not simplifying + + +def test_mrv2b(): + assert mmrv(exp(x + exp(-x**2)), x) == {exp(-x**2)} + +#sometimes infinite recursion due to log(exp(x**2)) not simplifying + + +def test_mrv2c(): + assert mmrv( + exp(-x + 1/x**2) - exp(x + 1/x), x) == {exp(x + 1/x), exp(1/x**2 - x)} + +#sometimes infinite recursion due to log(exp(x**2)) not simplifying + + +def test_mrv3(): + assert mmrv(exp(x**2) + x*exp(x) + log(x)**x/x, x) == {exp(x**2)} + assert mmrv( + exp(x)*(exp(1/x + exp(-x)) - exp(1/x)), x) == {exp(x), exp(-x)} + assert mmrv(log( + x**2 + 2*exp(exp(3*x**3*log(x)))), x) == {exp(exp(3*x**3*log(x)))} + assert mmrv(log(x - log(x))/log(x), x) == {x} + assert mmrv( + (exp(1/x - exp(-x)) - exp(1/x))*exp(x), x) == {exp(x), exp(-x)} + assert mmrv( + 1/exp(-x + exp(-x)) - exp(x), x) == {exp(x), exp(-x), exp(x - exp(-x))} + assert mmrv(log(log(x*exp(x*exp(x)) + 1)), x) == {exp(x*exp(x))} + assert mmrv(exp(exp(log(log(x) + 1/x))), x) == {x} + + +def test_mrv4(): + ln = log + assert mmrv((ln(ln(x) + ln(ln(x))) - ln(ln(x)))/ln(ln(x) + ln(ln(ln(x))))*ln(x), + x) == {x} + assert mmrv(log(log(x*exp(x*exp(x)) + 1)) - exp(exp(log(log(x) + 1/x))), x) == \ + {exp(x*exp(x))} + + +def mrewrite(a, b, c): + return rewrite(a[1], a[0], b, c) + + +def test_rewrite1(): + e = exp(x) + assert mrewrite(mrv(e, x), x, m) == (1/m, -x) + e = exp(x**2) + assert mrewrite(mrv(e, x), x, m) == (1/m, -x**2) + e = exp(x + 1/x) + assert mrewrite(mrv(e, x), x, m) == (1/m, -x - 1/x) + e = 1/exp(-x + exp(-x)) - exp(x) + assert mrewrite(mrv(e, x), x, m) == (1/(m*exp(m)) - 1/m, -x) + + +def test_rewrite2(): + e = exp(x)*log(log(exp(x))) + assert mmrv(e, x) == {exp(x)} + assert mrewrite(mrv(e, x), x, m) == (1/m*log(x), -x) + +#sometimes infinite recursion due to log(exp(x**2)) not simplifying + + +def test_rewrite3(): + e = exp(-x + 1/x**2) - exp(x + 1/x) + #both of these are correct and should be equivalent: + assert mrewrite(mrv(e, x), x, m) in [(-1/m + m*exp( + 1/x + 1/x**2), -x - 1/x), (m - 1/m*exp(1/x + x**(-2)), x**(-2) - x)] + + +def test_mrv_leadterm1(): + assert mrv_leadterm(-exp(1/x), x) == (-1, 0) + assert mrv_leadterm(1/exp(-x + exp(-x)) - exp(x), x) == (-1, 0) + assert mrv_leadterm( + (exp(1/x - exp(-x)) - exp(1/x))*exp(x), x) == (-exp(1/x), 0) + + +def test_mrv_leadterm2(): + #Gruntz: p51, 3.25 + assert mrv_leadterm((log(exp(x) + x) - x)/log(exp(x) + log(x))*exp(x), x) == \ + (1, 0) + + +def test_mrv_leadterm3(): + #Gruntz: p56, 3.27 + assert mmrv(exp(-x + exp(-x)*exp(-x*log(x))), x) == {exp(-x - x*log(x))} + assert mrv_leadterm(exp(-x + exp(-x)*exp(-x*log(x))), x) == (exp(-x), 0) + + +def test_limit1(): + assert gruntz(x, x, oo) is oo + assert gruntz(x, x, -oo) is -oo + assert gruntz(-x, x, oo) is -oo + assert gruntz(x**2, x, -oo) is oo + assert gruntz(-x**2, x, oo) is -oo + assert gruntz(x*log(x), x, 0, dir="+") == 0 + assert gruntz(1/x, x, oo) == 0 + assert gruntz(exp(x), x, oo) is oo + assert gruntz(-exp(x), x, oo) is -oo + assert gruntz(exp(x)/x, x, oo) is oo + assert gruntz(1/x - exp(-x), x, oo) == 0 + assert gruntz(x + 1/x, x, oo) is oo + + +def test_limit2(): + assert gruntz(x**x, x, 0, dir="+") == 1 + assert gruntz((exp(x) - 1)/x, x, 0) == 1 + assert gruntz(1 + 1/x, x, oo) == 1 + assert gruntz(-exp(1/x), x, oo) == -1 + assert gruntz(x + exp(-x), x, oo) is oo + assert gruntz(x + exp(-x**2), x, oo) is oo + assert gruntz(x + exp(-exp(x)), x, oo) is oo + assert gruntz(13 + 1/x - exp(-x), x, oo) == 13 + + +def test_limit3(): + a = Symbol('a') + assert gruntz(x - log(1 + exp(x)), x, oo) == 0 + assert gruntz(x - log(a + exp(x)), x, oo) == 0 + assert gruntz(exp(x)/(1 + exp(x)), x, oo) == 1 + assert gruntz(exp(x)/(a + exp(x)), x, oo) == 1 + + +def test_limit4(): + #issue 3463 + assert gruntz((3**x + 5**x)**(1/x), x, oo) == 5 + #issue 3463 + assert gruntz((3**(1/x) + 5**(1/x))**x, x, 0) == 5 + + +@XFAIL +def test_MrvTestCase_page47_ex3_21(): + h = exp(-x/(1 + exp(-x))) + expr = exp(h)*exp(-x/(1 + h))*exp(exp(-x + h))/h**2 - exp(x) + x + assert mmrv(expr, x) == {1/h, exp(-x), exp(x), exp(x - h), exp(x/(1 + h))} + + +def test_gruntz_I(): + y = Symbol("y") + assert gruntz(I*x, x, oo) == I*oo + assert gruntz(y*I*x, x, oo) == y*I*oo + assert gruntz(y*3*I*x, x, oo) == y*I*oo + assert gruntz(y*3*sin(I)*x, x, oo).simplify().rewrite(_sign) == _sign(y)*I*oo + + +def test_issue_4814(): + assert gruntz((x + 1)**(1/log(x + 1)), x, oo) == E + + +def test_intractable(): + assert gruntz(1/gamma(x), x, oo) == 0 + assert gruntz(1/loggamma(x), x, oo) == 0 + assert gruntz(gamma(x)/loggamma(x), x, oo) is oo + assert gruntz(exp(gamma(x))/gamma(x), x, oo) is oo + assert gruntz(gamma(x), x, 3) == 2 + assert gruntz(gamma(Rational(1, 7) + 1/x), x, oo) == gamma(Rational(1, 7)) + assert gruntz(log(x**x)/log(gamma(x)), x, oo) == 1 + assert gruntz(log(gamma(gamma(x)))/exp(x), x, oo) is oo + + +def test_aseries_trig(): + assert cancel(gruntz(1/log(atan(x)), x, oo) + - 1/(log(pi) + log(S.Half))) == 0 + assert gruntz(1/acot(x), x, -oo) is -oo + + +def test_exp_log_series(): + assert gruntz(x/log(log(x*exp(x))), x, oo) is oo + + +def test_issue_3644(): + assert gruntz(((x**7 + x + 1)/(2**x + x**2))**(-1/x), x, oo) == 2 + + +def test_issue_6843(): + n = Symbol('n', integer=True, positive=True) + r = (n + 1)*x**(n + 1)/(x**(n + 1) - 1) - x/(x - 1) + assert gruntz(r, x, 1).simplify() == n/2 + + +def test_issue_4190(): + assert gruntz(x - gamma(1/x), x, oo) == S.EulerGamma + + +@XFAIL +def test_issue_5172(): + n = Symbol('n') + r = Symbol('r', positive=True) + c = Symbol('c') + p = Symbol('p', positive=True) + m = Symbol('m', negative=True) + expr = ((2*n*(n - r + 1)/(n + r*(n - r + 1)))**c + \ + (r - 1)*(n*(n - r + 2)/(n + r*(n - r + 1)))**c - n)/(n**c - n) + expr = expr.subs(c, c + 1) + assert gruntz(expr.subs(c, m), n, oo) == 1 + # fail: + assert gruntz(expr.subs(c, p), n, oo).simplify() == \ + (2**(p + 1) + r - 1)/(r + 1)**(p + 1) + + +def test_issue_4109(): + assert gruntz(1/gamma(x), x, 0) == 0 + assert gruntz(x*gamma(x), x, 0) == 1 + + +def test_issue_6682(): + assert gruntz(exp(2*Ei(-x))/x**2, x, 0) == exp(2*EulerGamma) + + +def test_issue_7096(): + from sympy.functions import sign + assert gruntz(x**-pi, x, 0, dir='-') == oo*sign((-1)**(-pi)) + +def test_issue_24210_25885(): + eq = exp(x)/(1+1/x)**x**2 + ans = sqrt(E) + assert gruntz(eq, x, oo) == ans + assert gruntz(1/eq, x, oo) == 1/ans diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_kauers.py b/lib/python3.12/site-packages/sympy/series/tests/test_kauers.py new file mode 100644 index 0000000000000000000000000000000000000000..bfb9044b33416bc38879649b258150ba2906250c --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_kauers.py @@ -0,0 +1,23 @@ +from sympy.series.kauers import finite_diff +from sympy.series.kauers import finite_diff_kauers +from sympy.abc import x, y, z, m, n, w +from sympy.core.numbers import pi +from sympy.functions.elementary.trigonometric import (cos, sin) +from sympy.concrete.summations import Sum + + +def test_finite_diff(): + assert finite_diff(x**2 + 2*x + 1, x) == 2*x + 3 + assert finite_diff(y**3 + 2*y**2 + 3*y + 5, y) == 3*y**2 + 7*y + 6 + assert finite_diff(z**2 - 2*z + 3, z) == 2*z - 1 + assert finite_diff(w**2 + 3*w - 2, w) == 2*w + 4 + assert finite_diff(sin(x), x, pi/6) == -sin(x) + sin(x + pi/6) + assert finite_diff(cos(y), y, pi/3) == -cos(y) + cos(y + pi/3) + assert finite_diff(x**2 - 2*x + 3, x, 2) == 4*x + assert finite_diff(n**2 - 2*n + 3, n, 3) == 6*n + 3 + +def test_finite_diff_kauers(): + assert finite_diff_kauers(Sum(x**2, (x, 1, n))) == (n + 1)**2 + assert finite_diff_kauers(Sum(y, (y, 1, m))) == (m + 1) + assert finite_diff_kauers(Sum((x*y), (x, 1, m), (y, 1, n))) == (m + 1)*(n + 1) + assert finite_diff_kauers(Sum((x*y**2), (x, 1, m), (y, 1, n))) == (n + 1)**2*(m + 1) diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_limits.py b/lib/python3.12/site-packages/sympy/series/tests/test_limits.py new file mode 100644 index 0000000000000000000000000000000000000000..21777c15e65cddf54ab53062cc3d2b58fadef114 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_limits.py @@ -0,0 +1,1414 @@ +from itertools import product + +from sympy.concrete.summations import Sum +from sympy.core.function import (Function, diff) +from sympy.core import EulerGamma, GoldenRatio +from sympy.core.mod import Mod +from sympy.core.numbers import (E, I, Rational, oo, pi, zoo) +from sympy.core.singleton import S +from sympy.core.symbol import (Symbol, symbols) +from sympy.functions.combinatorial.numbers import fibonacci +from sympy.functions.combinatorial.factorials import (binomial, factorial, subfactorial) +from sympy.functions.elementary.complexes import (Abs, re, sign) +from sympy.functions.elementary.exponential import (LambertW, exp, log) +from sympy.functions.elementary.hyperbolic import (atanh, asinh, acosh, acoth, acsch, asech, tanh, sinh) +from sympy.functions.elementary.integers import (ceiling, floor, frac) +from sympy.functions.elementary.miscellaneous import (cbrt, real_root, sqrt) +from sympy.functions.elementary.piecewise import Piecewise +from sympy.functions.elementary.trigonometric import (acos, acot, acsc, asec, asin, + atan, cos, cot, csc, sec, sin, tan) +from sympy.functions.special.bessel import (besseli, bessely, besselj, besselk) +from sympy.functions.special.error_functions import (Ei, erf, erfc, erfi, fresnelc, fresnels) +from sympy.functions.special.gamma_functions import (digamma, gamma, uppergamma) +from sympy.functions.special.hyper import meijerg +from sympy.integrals.integrals import (Integral, integrate) +from sympy.series.limits import (Limit, limit) +from sympy.simplify.simplify import (logcombine, simplify) +from sympy.simplify.hyperexpand import hyperexpand + +from sympy.calculus.accumulationbounds import AccumBounds +from sympy.core.mul import Mul +from sympy.series.limits import heuristics +from sympy.series.order import Order +from sympy.testing.pytest import XFAIL, raises + +from sympy import elliptic_e, elliptic_k + +from sympy.abc import x, y, z, k +n = Symbol('n', integer=True, positive=True) + + +def test_basic1(): + assert limit(x, x, oo) is oo + assert limit(x, x, -oo) is -oo + assert limit(-x, x, oo) is -oo + assert limit(x**2, x, -oo) is oo + assert limit(-x**2, x, oo) is -oo + assert limit(x*log(x), x, 0, dir="+") == 0 + assert limit(1/x, x, oo) == 0 + assert limit(exp(x), x, oo) is oo + assert limit(-exp(x), x, oo) is -oo + assert limit(exp(x)/x, x, oo) is oo + assert limit(1/x - exp(-x), x, oo) == 0 + assert limit(x + 1/x, x, oo) is oo + assert limit(x - x**2, x, oo) is -oo + assert limit((1 + x)**(1 + sqrt(2)), x, 0) == 1 + assert limit((1 + x)**oo, x, 0) == Limit((x + 1)**oo, x, 0) + assert limit((1 + x)**oo, x, 0, dir='-') == Limit((x + 1)**oo, x, 0, dir='-') + assert limit((1 + x + y)**oo, x, 0, dir='-') == Limit((1 + x + y)**oo, x, 0, dir='-') + assert limit(y/x/log(x), x, 0) == -oo*sign(y) + assert limit(cos(x + y)/x, x, 0) == sign(cos(y))*oo + assert limit(gamma(1/x + 3), x, oo) == 2 + assert limit(S.NaN, x, -oo) is S.NaN + assert limit(Order(2)*x, x, S.NaN) is S.NaN + assert limit(1/(x - 1), x, 1, dir="+") is oo + assert limit(1/(x - 1), x, 1, dir="-") is -oo + assert limit(1/(5 - x)**3, x, 5, dir="+") is -oo + assert limit(1/(5 - x)**3, x, 5, dir="-") is oo + assert limit(1/sin(x), x, pi, dir="+") is -oo + assert limit(1/sin(x), x, pi, dir="-") is oo + assert limit(1/cos(x), x, pi/2, dir="+") is -oo + assert limit(1/cos(x), x, pi/2, dir="-") is oo + assert limit(1/tan(x**3), x, (2*pi)**Rational(1, 3), dir="+") is oo + assert limit(1/tan(x**3), x, (2*pi)**Rational(1, 3), dir="-") is -oo + assert limit(1/cot(x)**3, x, (pi*Rational(3, 2)), dir="+") is -oo + assert limit(1/cot(x)**3, x, (pi*Rational(3, 2)), dir="-") is oo + assert limit(tan(x), x, oo) == AccumBounds(S.NegativeInfinity, S.Infinity) + assert limit(cot(x), x, oo) == AccumBounds(S.NegativeInfinity, S.Infinity) + assert limit(sec(x), x, oo) == AccumBounds(S.NegativeInfinity, S.Infinity) + assert limit(csc(x), x, oo) == AccumBounds(S.NegativeInfinity, S.Infinity) + + # test bi-directional limits + assert limit(sin(x)/x, x, 0, dir="+-") == 1 + assert limit(x**2, x, 0, dir="+-") == 0 + assert limit(1/x**2, x, 0, dir="+-") is oo + + # test failing bi-directional limits + assert limit(1/x, x, 0, dir="+-") is zoo + # approaching 0 + # from dir="+" + assert limit(1 + 1/x, x, 0) is oo + # from dir='-' + # Add + assert limit(1 + 1/x, x, 0, dir='-') is -oo + # Pow + assert limit(x**(-2), x, 0, dir='-') is oo + assert limit(x**(-3), x, 0, dir='-') is -oo + assert limit(1/sqrt(x), x, 0, dir='-') == (-oo)*I + assert limit(x**2, x, 0, dir='-') == 0 + assert limit(sqrt(x), x, 0, dir='-') == 0 + assert limit(x**-pi, x, 0, dir='-') == -oo*(-1)**(1 - pi) + assert limit((1 + cos(x))**oo, x, 0) == Limit((cos(x) + 1)**oo, x, 0) + + # test pull request 22491 + assert limit(1/asin(x), x, 0, dir = '+') == oo + assert limit(1/asin(x), x, 0, dir = '-') == -oo + assert limit(1/sinh(x), x, 0, dir = '+') == oo + assert limit(1/sinh(x), x, 0, dir = '-') == -oo + assert limit(log(1/x) + 1/sin(x), x, 0, dir = '+') == oo + assert limit(log(1/x) + 1/x, x, 0, dir = '+') == oo + + +def test_basic2(): + assert limit(x**x, x, 0, dir="+") == 1 + assert limit((exp(x) - 1)/x, x, 0) == 1 + assert limit(1 + 1/x, x, oo) == 1 + assert limit(-exp(1/x), x, oo) == -1 + assert limit(x + exp(-x), x, oo) is oo + assert limit(x + exp(-x**2), x, oo) is oo + assert limit(x + exp(-exp(x)), x, oo) is oo + assert limit(13 + 1/x - exp(-x), x, oo) == 13 + + +def test_basic3(): + assert limit(1/x, x, 0, dir="+") is oo + assert limit(1/x, x, 0, dir="-") is -oo + + +def test_basic4(): + assert limit(2*x + y*x, x, 0) == 0 + assert limit(2*x + y*x, x, 1) == 2 + y + assert limit(2*x**8 + y*x**(-3), x, -2) == 512 - y/8 + assert limit(sqrt(x + 1) - sqrt(x), x, oo) == 0 + assert integrate(1/(x**3 + 1), (x, 0, oo)) == 2*pi*sqrt(3)/9 + + +def test_log(): + # https://github.com/sympy/sympy/issues/21598 + a, b, c = symbols('a b c', positive=True) + A = log(a/b) - (log(a) - log(b)) + assert A.limit(a, oo) == 0 + assert (A * c).limit(a, oo) == 0 + + tau, x = symbols('tau x', positive=True) + # The value of manualintegrate in the issue + expr = tau**2*((tau - 1)*(tau + 1)*log(x + 1)/(tau**2 + 1)**2 + 1/((tau**2\ + + 1)*(x + 1)) - (-2*tau*atan(x/tau) + (tau**2/2 - 1/2)*log(tau**2\ + + x**2))/(tau**2 + 1)**2) + assert limit(expr, x, oo) == pi*tau**3/(tau**2 + 1)**2 + + +def test_piecewise(): + # https://github.com/sympy/sympy/issues/18363 + assert limit((real_root(x - 6, 3) + 2)/(x + 2), x, -2, '+') == Rational(1, 12) + + +def test_piecewise2(): + func1 = 2*sqrt(x)*Piecewise(((4*x - 2)/Abs(sqrt(4 - 4*(2*x - 1)**2)), 4*x - 2\ + >= 0), ((2 - 4*x)/Abs(sqrt(4 - 4*(2*x - 1)**2)), True)) + func2 = Piecewise((x**2/2, x <= 0.5), (x/2 - 0.125, True)) + func3 = Piecewise(((x - 9) / 5, x < -1), ((x - 9) / 5, x > 4), (sqrt(Abs(x - 3)), True)) + assert limit(func1, x, 0) == 1 + assert limit(func2, x, 0) == 0 + assert limit(func3, x, -1) == 2 + + +def test_basic5(): + class my(Function): + @classmethod + def eval(cls, arg): + if arg is S.Infinity: + return S.NaN + assert limit(my(x), x, oo) == Limit(my(x), x, oo) + + +def test_issue_3885(): + assert limit(x*y + x*z, z, 2) == x*y + 2*x + + +def test_Limit(): + assert Limit(sin(x)/x, x, 0) != 1 + assert Limit(sin(x)/x, x, 0).doit() == 1 + assert Limit(x, x, 0, dir='+-').args == (x, x, 0, Symbol('+-')) + + +def test_floor(): + assert limit(floor(x), x, -2, "+") == -2 + assert limit(floor(x), x, -2, "-") == -3 + assert limit(floor(x), x, -1, "+") == -1 + assert limit(floor(x), x, -1, "-") == -2 + assert limit(floor(x), x, 0, "+") == 0 + assert limit(floor(x), x, 0, "-") == -1 + assert limit(floor(x), x, 1, "+") == 1 + assert limit(floor(x), x, 1, "-") == 0 + assert limit(floor(x), x, 2, "+") == 2 + assert limit(floor(x), x, 2, "-") == 1 + assert limit(floor(x), x, 248, "+") == 248 + assert limit(floor(x), x, 248, "-") == 247 + + # https://github.com/sympy/sympy/issues/14478 + assert limit(x*floor(3/x)/2, x, 0, '+') == Rational(3, 2) + assert limit(floor(x + 1/2) - floor(x), x, oo) == AccumBounds(-S.Half, S(3)/2) + + # test issue 9158 + assert limit(floor(atan(x)), x, oo) == 1 + assert limit(floor(atan(x)), x, -oo) == -2 + assert limit(ceiling(atan(x)), x, oo) == 2 + assert limit(ceiling(atan(x)), x, -oo) == -1 + + +def test_floor_requires_robust_assumptions(): + assert limit(floor(sin(x)), x, 0, "+") == 0 + assert limit(floor(sin(x)), x, 0, "-") == -1 + assert limit(floor(cos(x)), x, 0, "+") == 0 + assert limit(floor(cos(x)), x, 0, "-") == 0 + assert limit(floor(5 + sin(x)), x, 0, "+") == 5 + assert limit(floor(5 + sin(x)), x, 0, "-") == 4 + assert limit(floor(5 + cos(x)), x, 0, "+") == 5 + assert limit(floor(5 + cos(x)), x, 0, "-") == 5 + + +def test_ceiling(): + assert limit(ceiling(x), x, -2, "+") == -1 + assert limit(ceiling(x), x, -2, "-") == -2 + assert limit(ceiling(x), x, -1, "+") == 0 + assert limit(ceiling(x), x, -1, "-") == -1 + assert limit(ceiling(x), x, 0, "+") == 1 + assert limit(ceiling(x), x, 0, "-") == 0 + assert limit(ceiling(x), x, 1, "+") == 2 + assert limit(ceiling(x), x, 1, "-") == 1 + assert limit(ceiling(x), x, 2, "+") == 3 + assert limit(ceiling(x), x, 2, "-") == 2 + assert limit(ceiling(x), x, 248, "+") == 249 + assert limit(ceiling(x), x, 248, "-") == 248 + + # https://github.com/sympy/sympy/issues/14478 + assert limit(x*ceiling(3/x)/2, x, 0, '+') == Rational(3, 2) + assert limit(ceiling(x + 1/2) - ceiling(x), x, oo) == AccumBounds(-S.Half, S(3)/2) + + +def test_ceiling_requires_robust_assumptions(): + assert limit(ceiling(sin(x)), x, 0, "+") == 1 + assert limit(ceiling(sin(x)), x, 0, "-") == 0 + assert limit(ceiling(cos(x)), x, 0, "+") == 1 + assert limit(ceiling(cos(x)), x, 0, "-") == 1 + assert limit(ceiling(5 + sin(x)), x, 0, "+") == 6 + assert limit(ceiling(5 + sin(x)), x, 0, "-") == 5 + assert limit(ceiling(5 + cos(x)), x, 0, "+") == 6 + assert limit(ceiling(5 + cos(x)), x, 0, "-") == 6 + + +def test_frac(): + assert limit(frac(x), x, oo) == AccumBounds(0, 1) + assert limit(frac(x)**(1/x), x, oo) == AccumBounds(0, 1) + assert limit(frac(x)**(1/x), x, -oo) == AccumBounds(1, oo) + assert limit(frac(x)**x, x, oo) == AccumBounds(0, oo) # wolfram gives (0, 1) + assert limit(frac(sin(x)), x, 0, "+") == 0 + assert limit(frac(sin(x)), x, 0, "-") == 1 + assert limit(frac(cos(x)), x, 0, "+-") == 1 + assert limit(frac(x**2), x, 0, "+-") == 0 + raises(ValueError, lambda: limit(frac(x), x, 0, '+-')) + assert limit(frac(-2*x + 1), x, 0, "+") == 1 + assert limit(frac(-2*x + 1), x, 0, "-") == 0 + assert limit(frac(x + S.Half), x, 0, "+-") == S(1)/2 + assert limit(frac(1/x), x, 0) == AccumBounds(0, 1) + + +def test_issue_14355(): + assert limit(floor(sin(x)/x), x, 0, '+') == 0 + assert limit(floor(sin(x)/x), x, 0, '-') == 0 + # test comment https://github.com/sympy/sympy/issues/14355#issuecomment-372121314 + assert limit(floor(-tan(x)/x), x, 0, '+') == -2 + assert limit(floor(-tan(x)/x), x, 0, '-') == -2 + + +def test_atan(): + x = Symbol("x", real=True) + assert limit(atan(x)*sin(1/x), x, 0) == 0 + assert limit(atan(x) + sqrt(x + 1) - sqrt(x), x, oo) == pi/2 + + +def test_set_signs(): + assert limit(abs(x), x, 0) == 0 + assert limit(abs(sin(x)), x, 0) == 0 + assert limit(abs(cos(x)), x, 0) == 1 + assert limit(abs(sin(x + 1)), x, 0) == sin(1) + + # https://github.com/sympy/sympy/issues/9449 + assert limit((Abs(x + y) - Abs(x - y))/(2*x), x, 0) == sign(y) + + # https://github.com/sympy/sympy/issues/12398 + assert limit(Abs(log(x)/x**3), x, oo) == 0 + assert limit(x*(Abs(log(x)/x**3)/Abs(log(x + 1)/(x + 1)**3) - 1), x, oo) == 3 + + # https://github.com/sympy/sympy/issues/18501 + assert limit(Abs(log(x - 1)**3 - 1), x, 1, '+') == oo + + # https://github.com/sympy/sympy/issues/18997 + assert limit(Abs(log(x)), x, 0) == oo + assert limit(Abs(log(Abs(x))), x, 0) == oo + + # https://github.com/sympy/sympy/issues/19026 + z = Symbol('z', positive=True) + assert limit(Abs(log(z) + 1)/log(z), z, oo) == 1 + + # https://github.com/sympy/sympy/issues/20704 + assert limit(z*(Abs(1/z + y) - Abs(y - 1/z))/2, z, 0) == 0 + + # https://github.com/sympy/sympy/issues/21606 + assert limit(cos(z)/sign(z), z, pi, '-') == -1 + + +def test_heuristic(): + x = Symbol("x", real=True) + assert heuristics(sin(1/x) + atan(x), x, 0, '+') == AccumBounds(-1, 1) + assert limit(log(2 + sqrt(atan(x))*sqrt(sin(1/x))), x, 0) == log(2) + + +def test_issue_3871(): + z = Symbol("z", positive=True) + f = -1/z*exp(-z*x) + assert limit(f, x, oo) == 0 + assert f.limit(x, oo) == 0 + + +def test_exponential(): + n = Symbol('n') + x = Symbol('x', real=True) + assert limit((1 + x/n)**n, n, oo) == exp(x) + assert limit((1 + x/(2*n))**n, n, oo) == exp(x/2) + assert limit((1 + x/(2*n + 1))**n, n, oo) == exp(x/2) + assert limit(((x - 1)/(x + 1))**x, x, oo) == exp(-2) + assert limit(1 + (1 + 1/x)**x, x, oo) == 1 + S.Exp1 + assert limit((2 + 6*x)**x/(6*x)**x, x, oo) == exp(S('1/3')) + + +def test_exponential2(): + n = Symbol('n') + assert limit((1 + x/(n + sin(n)))**n, n, oo) == exp(x) + + +def test_doit(): + f = Integral(2 * x, x) + l = Limit(f, x, oo) + assert l.doit() is oo + + +def test_series_AccumBounds(): + assert limit(sin(k) - sin(k + 1), k, oo) == AccumBounds(-2, 2) + assert limit(cos(k) - cos(k + 1) + 1, k, oo) == AccumBounds(-1, 3) + + # not the exact bound + assert limit(sin(k) - sin(k)*cos(k), k, oo) == AccumBounds(-2, 2) + + # test for issue #9934 + lo = (-3 + cos(1))/2 + hi = (1 + cos(1))/2 + t1 = Mul(AccumBounds(lo, hi), 1/(-1 + cos(1)), evaluate=False) + assert limit(simplify(Sum(cos(n).rewrite(exp), (n, 0, k)).doit().rewrite(sin)), k, oo) == t1 + + t2 = Mul(AccumBounds(-1 + sin(1)/2, sin(1)/2 + 1), 1/(1 - cos(1))) + assert limit(simplify(Sum(sin(n).rewrite(exp), (n, 0, k)).doit().rewrite(sin)), k, oo) == t2 + + assert limit(((sin(x) + 1)/2)**x, x, oo) == AccumBounds(0, oo) # wolfram says 0 + + # https://github.com/sympy/sympy/issues/12312 + e = 2**(-x)*(sin(x) + 1)**x + assert limit(e, x, oo) == AccumBounds(0, oo) + + +def test_bessel_functions_at_infinity(): + # Pull Request 23844 implements limits for all bessel and modified bessel + # functions approaching infinity along any direction i.e. abs(z0) tends to oo + + assert limit(besselj(1, x), x, oo) == 0 + assert limit(besselj(1, x), x, -oo) == 0 + assert limit(besselj(1, x), x, I*oo) == oo*I + assert limit(besselj(1, x), x, -I*oo) == -oo*I + assert limit(bessely(1, x), x, oo) == 0 + assert limit(bessely(1, x), x, -oo) == 0 + assert limit(bessely(1, x), x, I*oo) == -oo + assert limit(bessely(1, x), x, -I*oo) == -oo + assert limit(besseli(1, x), x, oo) == oo + assert limit(besseli(1, x), x, -oo) == -oo + assert limit(besseli(1, x), x, I*oo) == 0 + assert limit(besseli(1, x), x, -I*oo) == 0 + assert limit(besselk(1, x), x, oo) == 0 + assert limit(besselk(1, x), x, -oo) == -oo*I + assert limit(besselk(1, x), x, I*oo) == 0 + assert limit(besselk(1, x), x, -I*oo) == 0 + + # test issue 14874 + assert limit(besselk(0, x), x, oo) == 0 + + +@XFAIL +def test_doit2(): + f = Integral(2 * x, x) + l = Limit(f, x, oo) + # limit() breaks on the contained Integral. + assert l.doit(deep=False) == l + + +def test_issue_2929(): + assert limit((x * exp(x))/(exp(x) - 1), x, -oo) == 0 + + +def test_issue_3792(): + assert limit((1 - cos(x))/x**2, x, S.Half) == 4 - 4*cos(S.Half) + assert limit(sin(sin(x + 1) + 1), x, 0) == sin(1 + sin(1)) + assert limit(abs(sin(x + 1) + 1), x, 0) == 1 + sin(1) + + +def test_issue_4090(): + assert limit(1/(x + 3), x, 2) == Rational(1, 5) + assert limit(1/(x + pi), x, 2) == S.One/(2 + pi) + assert limit(log(x)/(x**2 + 3), x, 2) == log(2)/7 + assert limit(log(x)/(x**2 + pi), x, 2) == log(2)/(4 + pi) + + +def test_issue_4547(): + assert limit(cot(x), x, 0, dir='+') is oo + assert limit(cot(x), x, pi/2, dir='+') == 0 + + +def test_issue_5164(): + assert limit(x**0.5, x, oo) == oo**0.5 is oo + assert limit(x**0.5, x, 16) == 4 # Should this be a float? + assert limit(x**0.5, x, 0) == 0 + assert limit(x**(-0.5), x, oo) == 0 + assert limit(x**(-0.5), x, 4) == S.Half # Should this be a float? + + +def test_issue_5383(): + func = (1.0 * 1 + 1.0 * x)**(1.0 * 1 / x) + assert limit(func, x, 0) == E + + +def test_issue_14793(): + expr = ((x + S(1)/2) * log(x) - x + log(2*pi)/2 - \ + log(factorial(x)) + S(1)/(12*x))*x**3 + assert limit(expr, x, oo) == S(1)/360 + + +def test_issue_5183(): + # using list(...) so py.test can recalculate values + tests = list(product([x, -x], + [-1, 1], + [2, 3, S.Half, Rational(2, 3)], + ['-', '+'])) + results = (oo, oo, -oo, oo, -oo*I, oo, -oo*(-1)**Rational(1, 3), oo, + 0, 0, 0, 0, 0, 0, 0, 0, + oo, oo, oo, -oo, oo, -oo*I, oo, -oo*(-1)**Rational(1, 3), + 0, 0, 0, 0, 0, 0, 0, 0) + assert len(tests) == len(results) + for i, (args, res) in enumerate(zip(tests, results)): + y, s, e, d = args + eq = y**(s*e) + try: + assert limit(eq, x, 0, dir=d) == res + except AssertionError: + if 0: # change to 1 if you want to see the failing tests + print() + print(i, res, eq, d, limit(eq, x, 0, dir=d)) + else: + assert None + + +def test_issue_5184(): + assert limit(sin(x)/x, x, oo) == 0 + assert limit(atan(x), x, oo) == pi/2 + assert limit(gamma(x), x, oo) is oo + assert limit(cos(x)/x, x, oo) == 0 + assert limit(gamma(x), x, S.Half) == sqrt(pi) + + r = Symbol('r', real=True) + assert limit(r*sin(1/r), r, 0) == 0 + + +def test_issue_5229(): + assert limit((1 + y)**(1/y) - S.Exp1, y, 0) == 0 + + +def test_issue_4546(): + # using list(...) so py.test can recalculate values + tests = list(product([cot, tan], + [-pi/2, 0, pi/2, pi, pi*Rational(3, 2)], + ['-', '+'])) + results = (0, 0, -oo, oo, 0, 0, -oo, oo, 0, 0, + oo, -oo, 0, 0, oo, -oo, 0, 0, oo, -oo) + assert len(tests) == len(results) + for i, (args, res) in enumerate(zip(tests, results)): + f, l, d = args + eq = f(x) + try: + assert limit(eq, x, l, dir=d) == res + except AssertionError: + if 0: # change to 1 if you want to see the failing tests + print() + print(i, res, eq, l, d, limit(eq, x, l, dir=d)) + else: + assert None + + +def test_issue_3934(): + assert limit((1 + x**log(3))**(1/x), x, 0) == 1 + assert limit((5**(1/x) + 3**(1/x))**x, x, 0) == 5 + + +def test_calculate_series(): + # NOTE + # The calculate_series method is being deprecated and is no longer responsible + # for result being returned. The mrv_leadterm function now uses simple leadterm + # calls rather than calculate_series. + + # needs gruntz calculate_series to go to n = 32 + assert limit(x**Rational(77, 3)/(1 + x**Rational(77, 3)), x, oo) == 1 + # needs gruntz calculate_series to go to n = 128 + assert limit(x**101.1/(1 + x**101.1), x, oo) == 1 + + +def test_issue_5955(): + assert limit((x**16)/(1 + x**16), x, oo) == 1 + assert limit((x**100)/(1 + x**100), x, oo) == 1 + assert limit((x**1885)/(1 + x**1885), x, oo) == 1 + assert limit((x**1000/((x + 1)**1000 + exp(-x))), x, oo) == 1 + + +def test_newissue(): + assert limit(exp(1/sin(x))/exp(cot(x)), x, 0) == 1 + + +def test_extended_real_line(): + assert limit(x - oo, x, oo) == Limit(x - oo, x, oo) + assert limit(1/(x + sin(x)) - oo, x, 0) == Limit(1/(x + sin(x)) - oo, x, 0) + assert limit(oo/x, x, oo) == Limit(oo/x, x, oo) + assert limit(x - oo + 1/x, x, oo) == Limit(x - oo + 1/x, x, oo) + + +@XFAIL +def test_order_oo(): + x = Symbol('x', positive=True) + assert Order(x)*oo != Order(1, x) + assert limit(oo/(x**2 - 4), x, oo) is oo + + +def test_issue_5436(): + raises(NotImplementedError, lambda: limit(exp(x*y), x, oo)) + raises(NotImplementedError, lambda: limit(exp(-x*y), x, oo)) + + +def test_Limit_dir(): + raises(TypeError, lambda: Limit(x, x, 0, dir=0)) + raises(ValueError, lambda: Limit(x, x, 0, dir='0')) + + +def test_polynomial(): + assert limit((x + 1)**1000/((x + 1)**1000 + 1), x, oo) == 1 + assert limit((x + 1)**1000/((x + 1)**1000 + 1), x, -oo) == 1 + + +def test_rational(): + assert limit(1/y - (1/(y + x) + x/(y + x)/y)/z, x, oo) == (z - 1)/(y*z) + assert limit(1/y - (1/(y + x) + x/(y + x)/y)/z, x, -oo) == (z - 1)/(y*z) + + +def test_issue_5740(): + assert limit(log(x)*z - log(2*x)*y, x, 0) == oo*sign(y - z) + + +def test_issue_6366(): + n = Symbol('n', integer=True, positive=True) + r = (n + 1)*x**(n + 1)/(x**(n + 1) - 1) - x/(x - 1) + assert limit(r, x, 1).cancel() == n/2 + + +def test_factorial(): + f = factorial(x) + assert limit(f, x, oo) is oo + assert limit(x/f, x, oo) == 0 + # see Stirling's approximation: + # https://en.wikipedia.org/wiki/Stirling's_approximation + assert limit(f/(sqrt(2*pi*x)*(x/E)**x), x, oo) == 1 + assert limit(f, x, -oo) == gamma(-oo) + + +def test_issue_6560(): + e = (5*x**3/4 - x*Rational(3, 4) + (y*(3*x**2/2 - S.Half) + + 35*x**4/8 - 15*x**2/4 + Rational(3, 8))/(2*(y + 1))) + assert limit(e, y, oo) == 5*x**3/4 + 3*x**2/4 - 3*x/4 - Rational(1, 4) + +@XFAIL +def test_issue_5172(): + n = Symbol('n') + r = Symbol('r', positive=True) + c = Symbol('c') + p = Symbol('p', positive=True) + m = Symbol('m', negative=True) + expr = ((2*n*(n - r + 1)/(n + r*(n - r + 1)))**c + + (r - 1)*(n*(n - r + 2)/(n + r*(n - r + 1)))**c - n)/(n**c - n) + expr = expr.subs(c, c + 1) + raises(NotImplementedError, lambda: limit(expr, n, oo)) + assert limit(expr.subs(c, m), n, oo) == 1 + assert limit(expr.subs(c, p), n, oo).simplify() == \ + (2**(p + 1) + r - 1)/(r + 1)**(p + 1) + + +def test_issue_7088(): + a = Symbol('a') + assert limit(sqrt(x/(x + a)), x, oo) == 1 + + +def test_branch_cuts(): + assert limit(asin(I*x + 2), x, 0) == pi - asin(2) + assert limit(asin(I*x + 2), x, 0, '-') == asin(2) + assert limit(asin(I*x - 2), x, 0) == -asin(2) + assert limit(asin(I*x - 2), x, 0, '-') == -pi + asin(2) + assert limit(acos(I*x + 2), x, 0) == -acos(2) + assert limit(acos(I*x + 2), x, 0, '-') == acos(2) + assert limit(acos(I*x - 2), x, 0) == acos(-2) + assert limit(acos(I*x - 2), x, 0, '-') == 2*pi - acos(-2) + assert limit(atan(x + 2*I), x, 0) == I*atanh(2) + assert limit(atan(x + 2*I), x, 0, '-') == -pi + I*atanh(2) + assert limit(atan(x - 2*I), x, 0) == pi - I*atanh(2) + assert limit(atan(x - 2*I), x, 0, '-') == -I*atanh(2) + assert limit(atan(1/x), x, 0) == pi/2 + assert limit(atan(1/x), x, 0, '-') == -pi/2 + assert limit(atan(x), x, oo) == pi/2 + assert limit(atan(x), x, -oo) == -pi/2 + assert limit(acot(x + S(1)/2*I), x, 0) == pi - I*acoth(S(1)/2) + assert limit(acot(x + S(1)/2*I), x, 0, '-') == -I*acoth(S(1)/2) + assert limit(acot(x - S(1)/2*I), x, 0) == I*acoth(S(1)/2) + assert limit(acot(x - S(1)/2*I), x, 0, '-') == -pi + I*acoth(S(1)/2) + assert limit(acot(x), x, 0) == pi/2 + assert limit(acot(x), x, 0, '-') == -pi/2 + assert limit(asec(I*x + S(1)/2), x, 0) == asec(S(1)/2) + assert limit(asec(I*x + S(1)/2), x, 0, '-') == -asec(S(1)/2) + assert limit(asec(I*x - S(1)/2), x, 0) == 2*pi - asec(-S(1)/2) + assert limit(asec(I*x - S(1)/2), x, 0, '-') == asec(-S(1)/2) + assert limit(acsc(I*x + S(1)/2), x, 0) == acsc(S(1)/2) + assert limit(acsc(I*x + S(1)/2), x, 0, '-') == pi - acsc(S(1)/2) + assert limit(acsc(I*x - S(1)/2), x, 0) == -pi + acsc(S(1)/2) + assert limit(acsc(I*x - S(1)/2), x, 0, '-') == -acsc(S(1)/2) + + assert limit(log(I*x - 1), x, 0) == I*pi + assert limit(log(I*x - 1), x, 0, '-') == -I*pi + assert limit(log(-I*x - 1), x, 0) == -I*pi + assert limit(log(-I*x - 1), x, 0, '-') == I*pi + + assert limit(sqrt(I*x - 1), x, 0) == I + assert limit(sqrt(I*x - 1), x, 0, '-') == -I + assert limit(sqrt(-I*x - 1), x, 0) == -I + assert limit(sqrt(-I*x - 1), x, 0, '-') == I + + assert limit(cbrt(I*x - 1), x, 0) == (-1)**(S(1)/3) + assert limit(cbrt(I*x - 1), x, 0, '-') == -(-1)**(S(2)/3) + assert limit(cbrt(-I*x - 1), x, 0) == -(-1)**(S(2)/3) + assert limit(cbrt(-I*x - 1), x, 0, '-') == (-1)**(S(1)/3) + + +def test_issue_6364(): + a = Symbol('a') + e = z/(1 - sqrt(1 + z)*sin(a)**2 - sqrt(1 - z)*cos(a)**2) + assert limit(e, z, 0) == 1/(cos(a)**2 - S.Half) + + +def test_issue_6682(): + assert limit(exp(2*Ei(-x))/x**2, x, 0) == exp(2*EulerGamma) + + +def test_issue_4099(): + a = Symbol('a') + assert limit(a/x, x, 0) == oo*sign(a) + assert limit(-a/x, x, 0) == -oo*sign(a) + assert limit(-a*x, x, oo) == -oo*sign(a) + assert limit(a*x, x, oo) == oo*sign(a) + + +def test_issue_4503(): + dx = Symbol('dx') + assert limit((sqrt(1 + exp(x + dx)) - sqrt(1 + exp(x)))/dx, dx, 0) == \ + exp(x)/(2*sqrt(exp(x) + 1)) + + +def test_issue_6052(): + G = meijerg((), (), (1,), (0,), -x) + g = hyperexpand(G) + assert limit(g, x, 0, '+-') == 0 + assert limit(g, x, oo) == -oo + + +def test_issue_7224(): + expr = sqrt(x)*besseli(1,sqrt(8*x)) + assert limit(x*diff(expr, x, x)/expr, x, 0) == 2 + assert limit(x*diff(expr, x, x)/expr, x, 1).evalf() == 2.0 + + +def test_issue_8208(): + assert limit(n**(Rational(1, 1e9) - 1), n, oo) == 0 + + +def test_issue_8229(): + assert limit((x**Rational(1, 4) - 2)/(sqrt(x) - 4)**Rational(2, 3), x, 16) == 0 + + +def test_issue_8433(): + d, t = symbols('d t', positive=True) + assert limit(erf(1 - t/d), t, oo) == -1 + + +def test_issue_8481(): + k = Symbol('k', integer=True, nonnegative=True) + lamda = Symbol('lamda', positive=True) + assert limit(lamda**k * exp(-lamda) / factorial(k), k, oo) == 0 + + +def test_issue_8462(): + assert limit(binomial(n, n/2), n, oo) == oo + assert limit(binomial(n, n/2) * 3 ** (-n), n, oo) == 0 + + +def test_issue_8634(): + n = Symbol('n', integer=True, positive=True) + x = Symbol('x') + assert limit(x**n, x, -oo) == oo*sign((-1)**n) + + +def test_issue_8635_18176(): + x = Symbol('x', real=True) + k = Symbol('k', positive=True) + assert limit(x**n - x**(n - 0), x, oo) == 0 + assert limit(x**n - x**(n - 5), x, oo) == oo + assert limit(x**n - x**(n - 2.5), x, oo) == oo + assert limit(x**n - x**(n - k - 1), x, oo) == oo + x = Symbol('x', positive=True) + assert limit(x**n - x**(n - 1), x, oo) == oo + assert limit(x**n - x**(n + 2), x, oo) == -oo + + +def test_issue_8730(): + assert limit(subfactorial(x), x, oo) is oo + + +def test_issue_9252(): + n = Symbol('n', integer=True) + c = Symbol('c', positive=True) + assert limit((log(n))**(n/log(n)) / (1 + c)**n, n, oo) == 0 + # limit should depend on the value of c + raises(NotImplementedError, lambda: limit((log(n))**(n/log(n)) / c**n, n, oo)) + + +def test_issue_9558(): + assert limit(sin(x)**15, x, 0, '-') == 0 + + +def test_issue_10801(): + # make sure limits work with binomial + assert limit(16**k / (k * binomial(2*k, k)**2), k, oo) == pi + + +def test_issue_10976(): + s, x = symbols('s x', real=True) + assert limit(erf(s*x)/erf(s), s, 0) == x + + +def test_issue_9041(): + assert limit(factorial(n) / ((n/exp(1))**n * sqrt(2*pi*n)), n, oo) == 1 + + +def test_issue_9205(): + x, y, a = symbols('x, y, a') + assert Limit(x, x, a).free_symbols == {a} + assert Limit(x, x, a, '-').free_symbols == {a} + assert Limit(x + y, x + y, a).free_symbols == {a} + assert Limit(-x**2 + y, x**2, a).free_symbols == {y, a} + + +def test_issue_9471(): + assert limit(((27**(log(n,3)))/n**3),n,oo) == 1 + assert limit(((27**(log(n,3)+1))/n**3),n,oo) == 27 + + +def test_issue_10382(): + assert limit(fibonacci(n + 1)/fibonacci(n), n, oo) == GoldenRatio + + +def test_issue_11496(): + assert limit(erfc(log(1/x)), x, oo) == 2 + + +def test_issue_11879(): + assert simplify(limit(((x+y)**n-x**n)/y, y, 0)) == n*x**(n-1) + + +def test_limit_with_Float(): + k = symbols("k") + assert limit(1.0 ** k, k, oo) == 1 + assert limit(0.3*1.0**k, k, oo) == Rational(3, 10) + + +def test_issue_10610(): + assert limit(3**x*3**(-x - 1)*(x + 1)**2/x**2, x, oo) == Rational(1, 3) + + +def test_issue_10868(): + assert limit(log(x) + asech(x), x, 0, '+') == log(2) + assert limit(log(x) + asech(x), x, 0, '-') == log(2) + 2*I*pi + raises(ValueError, lambda: limit(log(x) + asech(x), x, 0, '+-')) + assert limit(log(x) + asech(x), x, oo) == oo + assert limit(log(x) + acsch(x), x, 0, '+') == log(2) + assert limit(log(x) + acsch(x), x, 0, '-') == -oo + raises(ValueError, lambda: limit(log(x) + acsch(x), x, 0, '+-')) + assert limit(log(x) + acsch(x), x, oo) == oo + + +def test_issue_6599(): + assert limit((n + cos(n))/n, n, oo) == 1 + + +def test_issue_12555(): + assert limit((3**x + 2* x**10) / (x**10 + exp(x)), x, -oo) == 2 + assert limit((3**x + 2* x**10) / (x**10 + exp(x)), x, oo) is oo + + +def test_issue_12769(): + r, z, x = symbols('r z x', real=True) + a, b, s0, K, F0, s, T = symbols('a b s0 K F0 s T', positive=True, real=True) + fx = (F0**b*K**b*r*s0 - sqrt((F0**2*K**(2*b)*a**2*(b - 1) + \ + F0**(2*b)*K**2*a**2*(b - 1) + F0**(2*b)*K**(2*b)*s0**2*(b - 1)*(b**2 - 2*b + 1) - \ + 2*F0**(2*b)*K**(b + 1)*a*r*s0*(b**2 - 2*b + 1) + \ + 2*F0**(b + 1)*K**(2*b)*a*r*s0*(b**2 - 2*b + 1) - \ + 2*F0**(b + 1)*K**(b + 1)*a**2*(b - 1))/((b - 1)*(b**2 - 2*b + 1))))*(b*r - b - r + 1) + + assert fx.subs(K, F0).factor(deep=True) == limit(fx, K, F0).factor(deep=True) + + +def test_issue_13332(): + assert limit(sqrt(30)*5**(-5*x - 1)*(46656*x)**x*(5*x + 2)**(5*x + 5*S.Half) * + (6*x + 2)**(-6*x - 5*S.Half), x, oo) == Rational(25, 36) + + +def test_issue_12564(): + assert limit(x**2 + x*sin(x) + cos(x), x, -oo) is oo + assert limit(x**2 + x*sin(x) + cos(x), x, oo) is oo + assert limit(((x + cos(x))**2).expand(), x, oo) is oo + assert limit(((x + sin(x))**2).expand(), x, oo) is oo + assert limit(((x + cos(x))**2).expand(), x, -oo) is oo + assert limit(((x + sin(x))**2).expand(), x, -oo) is oo + + +def test_issue_14456(): + raises(NotImplementedError, lambda: Limit(exp(x), x, zoo).doit()) + raises(NotImplementedError, lambda: Limit(x**2/(x+1), x, zoo).doit()) + + +def test_issue_14411(): + assert limit(3*sec(4*pi*x - x/3), x, 3*pi/(24*pi - 2)) is -oo + + +def test_issue_13382(): + assert limit(x*(((x + 1)**2 + 1)/(x**2 + 1) - 1), x, oo) == 2 + + +def test_issue_13403(): + assert limit(x*(-1 + (x + log(x + 1) + 1)/(x + log(x))), x, oo) == 1 + + +def test_issue_13416(): + assert limit((-x**3*log(x)**3 + (x - 1)*(x + 1)**2*log(x + 1)**3)/(x**2*log(x)**3), x, oo) == 1 + + +def test_issue_13462(): + assert limit(n**2*(2*n*(-(1 - 1/(2*n))**x + 1) - x - (-x**2/4 + x/4)/n), n, oo) == x**3/24 - x**2/8 + x/12 + + +def test_issue_13750(): + a = Symbol('a') + assert limit(erf(a - x), x, oo) == -1 + assert limit(erf(sqrt(x) - x), x, oo) == -1 + + +def test_issue_14276(): + assert isinstance(limit(sin(x)**log(x), x, oo), Limit) + assert isinstance(limit(sin(x)**cos(x), x, oo), Limit) + assert isinstance(limit(sin(log(cos(x))), x, oo), Limit) + assert limit((1 + 1/(x**2 + cos(x)))**(x**2 + x), x, oo) == E + + +def test_issue_14514(): + assert limit((1/(log(x)**log(x)))**(1/x), x, oo) == 1 + + +def test_issues_14525(): + assert limit(sin(x)**2 - cos(x) + tan(x)*csc(x), x, oo) == AccumBounds(S.NegativeInfinity, S.Infinity) + assert limit(sin(x)**2 - cos(x) + sin(x)*cot(x), x, oo) == AccumBounds(S.NegativeInfinity, S.Infinity) + assert limit(cot(x) - tan(x)**2, x, oo) == AccumBounds(S.NegativeInfinity, S.Infinity) + assert limit(cos(x) - tan(x)**2, x, oo) == AccumBounds(S.NegativeInfinity, S.One) + assert limit(sin(x) - tan(x)**2, x, oo) == AccumBounds(S.NegativeInfinity, S.One) + assert limit(cos(x)**2 - tan(x)**2, x, oo) == AccumBounds(S.NegativeInfinity, S.One) + assert limit(tan(x)**2 + sin(x)**2 - cos(x), x, oo) == AccumBounds(-S.One, S.Infinity) + + +def test_issue_14574(): + assert limit(sqrt(x)*cos(x - x**2) / (x + 1), x, oo) == 0 + + +def test_issue_10102(): + assert limit(fresnels(x), x, oo) == S.Half + assert limit(3 + fresnels(x), x, oo) == 3 + S.Half + assert limit(5*fresnels(x), x, oo) == Rational(5, 2) + assert limit(fresnelc(x), x, oo) == S.Half + assert limit(fresnels(x), x, -oo) == Rational(-1, 2) + assert limit(4*fresnelc(x), x, -oo) == -2 + + +def test_issue_14377(): + raises(NotImplementedError, lambda: limit(exp(I*x)*sin(pi*x), x, oo)) + + +def test_issue_15146(): + e = (x/2) * (-2*x**3 - 2*(x**3 - 1) * x**2 * digamma(x**3 + 1) + \ + 2*(x**3 - 1) * x**2 * digamma(x**3 + x + 1) + x + 3) + assert limit(e, x, oo) == S(1)/3 + + +def test_issue_15202(): + e = (2**x*(2 + 2**(-x)*(-2*2**x + x + 2))/(x + 1))**(x + 1) + assert limit(e, x, oo) == exp(1) + + e = (log(x, 2)**7 + 10*x*factorial(x) + 5**x) / (factorial(x + 1) + 3*factorial(x) + 10**x) + assert limit(e, x, oo) == 10 + + +def test_issue_15282(): + assert limit((x**2000 - (x + 1)**2000) / x**1999, x, oo) == -2000 + + +def test_issue_15984(): + assert limit((-x + log(exp(x) + 1))/x, x, oo, dir='-') == 0 + + +def test_issue_13571(): + assert limit(uppergamma(x, 1) / gamma(x), x, oo) == 1 + + +def test_issue_13575(): + assert limit(acos(erfi(x)), x, 1) == acos(erfi(S.One)) + + +def test_issue_17325(): + assert Limit(sin(x)/x, x, 0, dir="+-").doit() == 1 + assert Limit(x**2, x, 0, dir="+-").doit() == 0 + assert Limit(1/x**2, x, 0, dir="+-").doit() is oo + assert Limit(1/x, x, 0, dir="+-").doit() is zoo + + +def test_issue_10978(): + assert LambertW(x).limit(x, 0) == 0 + + +def test_issue_14313_comment(): + assert limit(floor(n/2), n, oo) is oo + + +@XFAIL +def test_issue_15323(): + d = ((1 - 1/x)**x).diff(x) + assert limit(d, x, 1, dir='+') == 1 + + +def test_issue_12571(): + assert limit(-LambertW(-log(x))/log(x), x, 1) == 1 + + +def test_issue_14590(): + assert limit((x**3*((x + 1)/x)**x)/((x + 1)*(x + 2)*(x + 3)), x, oo) == exp(1) + + +def test_issue_14393(): + a, b = symbols('a b') + assert limit((x**b - y**b)/(x**a - y**a), x, y) == b*y**(-a + b)/a + + +def test_issue_14556(): + assert limit(factorial(n + 1)**(1/(n + 1)) - factorial(n)**(1/n), n, oo) == exp(-1) + + +def test_issue_14811(): + assert limit(((1 + ((S(2)/3)**(x + 1)))**(2**x))/(2**((S(4)/3)**(x - 1))), x, oo) == oo + + +def test_issue_16222(): + assert limit(exp(x), x, 1000000000) == exp(1000000000) + + +def test_issue_16714(): + assert limit(((x**(x + 1) + (x + 1)**x) / x**(x + 1))**x, x, oo) == exp(exp(1)) + + +def test_issue_16722(): + z = symbols('z', positive=True) + assert limit(binomial(n + z, n)*n**-z, n, oo) == 1/gamma(z + 1) + z = symbols('z', positive=True, integer=True) + assert limit(binomial(n + z, n)*n**-z, n, oo) == 1/gamma(z + 1) + + +def test_issue_17431(): + assert limit(((n + 1) + 1) / (((n + 1) + 2) * factorial(n + 1)) * + (n + 2) * factorial(n) / (n + 1), n, oo) == 0 + assert limit((n + 2)**2*factorial(n)/((n + 1)*(n + 3)*factorial(n + 1)) + , n, oo) == 0 + assert limit((n + 1) * factorial(n) / (n * factorial(n + 1)), n, oo) == 0 + + +def test_issue_17671(): + assert limit(Ei(-log(x)) - log(log(x))/x, x, 1) == EulerGamma + + +def test_issue_17751(): + a, b, c, x = symbols('a b c x', positive=True) + assert limit((a + 1)*x - sqrt((a + 1)**2*x**2 + b*x + c), x, oo) == -b/(2*a + 2) + + +def test_issue_17792(): + assert limit(factorial(n)/sqrt(n)*(exp(1)/n)**n, n, oo) == sqrt(2)*sqrt(pi) + + +def test_issue_18118(): + assert limit(sign(sin(x)), x, 0, "-") == -1 + assert limit(sign(sin(x)), x, 0, "+") == 1 + + +def test_issue_18306(): + assert limit(sin(sqrt(x))/sqrt(sin(x)), x, 0, '+') == 1 + + +def test_issue_18378(): + assert limit(log(exp(3*x) + x)/log(exp(x) + x**100), x, oo) == 3 + + +def test_issue_18399(): + assert limit((1 - S(1)/2*x)**(3*x), x, oo) is zoo + assert limit((-x)**x, x, oo) is zoo + + +def test_issue_18442(): + assert limit(tan(x)**(2**(sqrt(pi))), x, oo, dir='-') == Limit(tan(x)**(2**(sqrt(pi))), x, oo, dir='-') + + +def test_issue_18452(): + assert limit(abs(log(x))**x, x, 0) == 1 + assert limit(abs(log(x))**x, x, 0, "-") == 1 + + +def test_issue_18473(): + assert limit(sin(x)**(1/x), x, oo) == Limit(sin(x)**(1/x), x, oo, dir='-') + assert limit(cos(x)**(1/x), x, oo) == Limit(cos(x)**(1/x), x, oo, dir='-') + assert limit(tan(x)**(1/x), x, oo) == Limit(tan(x)**(1/x), x, oo, dir='-') + assert limit((cos(x) + 2)**(1/x), x, oo) == 1 + assert limit((sin(x) + 10)**(1/x), x, oo) == 1 + assert limit((cos(x) - 2)**(1/x), x, oo) == Limit((cos(x) - 2)**(1/x), x, oo, dir='-') + assert limit((cos(x) + 1)**(1/x), x, oo) == AccumBounds(0, 1) + assert limit((tan(x)**2)**(2/x) , x, oo) == AccumBounds(0, oo) + assert limit((sin(x)**2)**(1/x), x, oo) == AccumBounds(0, 1) + # Tests for issue #23751 + assert limit((cos(x) + 1)**(1/x), x, -oo) == AccumBounds(1, oo) + assert limit((sin(x)**2)**(1/x), x, -oo) == AccumBounds(1, oo) + assert limit((tan(x)**2)**(2/x) , x, -oo) == AccumBounds(0, oo) + + +def test_issue_18482(): + assert limit((2*exp(3*x)/(exp(2*x) + 1))**(1/x), x, oo) == exp(1) + + +def test_issue_18508(): + assert limit(sin(x)/sqrt(1-cos(x)), x, 0) == sqrt(2) + assert limit(sin(x)/sqrt(1-cos(x)), x, 0, dir='+') == sqrt(2) + assert limit(sin(x)/sqrt(1-cos(x)), x, 0, dir='-') == -sqrt(2) + + +def test_issue_18521(): + raises(NotImplementedError, lambda: limit(exp((2 - n) * x), x, oo)) + + +def test_issue_18969(): + a, b = symbols('a b', positive=True) + assert limit(LambertW(a), a, b) == LambertW(b) + assert limit(exp(LambertW(a)), a, b) == exp(LambertW(b)) + + +def test_issue_18992(): + assert limit(n/(factorial(n)**(1/n)), n, oo) == exp(1) + + +def test_issue_19067(): + x = Symbol('x') + assert limit(gamma(x)/(gamma(x - 1)*gamma(x + 2)), x, 0) == -1 + + +def test_issue_19586(): + assert limit(x**(2**x*3**(-x)), x, oo) == 1 + + +def test_issue_13715(): + n = Symbol('n') + p = Symbol('p', zero=True) + assert limit(n + p, n, 0) == 0 + + +def test_issue_15055(): + assert limit(n**3*((-n - 1)*sin(1/n) + (n + 2)*sin(1/(n + 1)))/(-n + 1), n, oo) == 1 + + +def test_issue_16708(): + m, vi = symbols('m vi', positive=True) + B, ti, d = symbols('B ti d') + assert limit((B*ti*vi - sqrt(m)*sqrt(-2*B*d*vi + m*(vi)**2) + m*vi)/(B*vi), B, 0) == (d + ti*vi)/vi + + +def test_issue_19154(): + assert limit(besseli(1, 3 *x)/(x *besseli(1, x)**3), x , oo) == 2*sqrt(3)*pi/3 + assert limit(besseli(1, 3 *x)/(x *besseli(1, x)**3), x , -oo) == -2*sqrt(3)*pi/3 + + +def test_issue_19453(): + beta = Symbol("beta", positive=True) + h = Symbol("h", positive=True) + m = Symbol("m", positive=True) + w = Symbol("omega", positive=True) + g = Symbol("g", positive=True) + + e = exp(1) + q = 3*h**2*beta*g*e**(0.5*h*beta*w) + p = m**2*w**2 + s = e**(h*beta*w) - 1 + Z = -q/(4*p*s) - q/(2*p*s**2) - q*(e**(h*beta*w) + 1)/(2*p*s**3)\ + + e**(0.5*h*beta*w)/s + E = -diff(log(Z), beta) + + assert limit(E - 0.5*h*w, beta, oo) == 0 + assert limit(E.simplify() - 0.5*h*w, beta, oo) == 0 + + +def test_issue_19739(): + assert limit((-S(1)/4)**x, x, oo) == 0 + + +def test_issue_19766(): + assert limit(2**(-x)*sqrt(4**(x + 1) + 1), x, oo) == 2 + + +def test_issue_19770(): + m = Symbol('m') + # the result is not 0 for non-real m + assert limit(cos(m*x)/x, x, oo) == Limit(cos(m*x)/x, x, oo, dir='-') + m = Symbol('m', real=True) + # can be improved to give the correct result 0 + assert limit(cos(m*x)/x, x, oo) == Limit(cos(m*x)/x, x, oo, dir='-') + m = Symbol('m', nonzero=True) + assert limit(cos(m*x), x, oo) == AccumBounds(-1, 1) + assert limit(cos(m*x)/x, x, oo) == 0 + + +def test_issue_7535(): + assert limit(tan(x)/sin(tan(x)), x, pi/2) == Limit(tan(x)/sin(tan(x)), x, pi/2, dir='+') + assert limit(tan(x)/sin(tan(x)), x, pi/2, dir='-') == Limit(tan(x)/sin(tan(x)), x, pi/2, dir='-') + assert limit(tan(x)/sin(tan(x)), x, pi/2, dir='+-') == Limit(tan(x)/sin(tan(x)), x, pi/2, dir='+-') + assert limit(sin(tan(x)),x,pi/2) == AccumBounds(-1, 1) + assert -oo*(1/sin(-oo)) == AccumBounds(-oo, oo) + assert oo*(1/sin(oo)) == AccumBounds(-oo, oo) + assert oo*(1/sin(-oo)) == AccumBounds(-oo, oo) + assert -oo*(1/sin(oo)) == AccumBounds(-oo, oo) + + +def test_issue_20365(): + assert limit(((x + 1)**(1/x) - E)/x, x, 0) == -E/2 + + +def test_issue_21031(): + assert limit(((1 + x)**(1/x) - (1 + 2*x)**(1/(2*x)))/asin(x), x, 0) == E/2 + + +def test_issue_21038(): + assert limit(sin(pi*x)/(3*x - 12), x, 4) == pi/3 + + +def test_issue_20578(): + expr = abs(x) * sin(1/x) + assert limit(expr,x,0,'+') == 0 + assert limit(expr,x,0,'-') == 0 + assert limit(expr,x,0,'+-') == 0 + + +def test_issue_21227(): + f = log(x) + + assert f.nseries(x, logx=y) == y + assert f.nseries(x, logx=-x) == -x + + f = log(-log(x)) + + assert f.nseries(x, logx=y) == log(-y) + assert f.nseries(x, logx=-x) == log(x) + + f = log(log(x)) + + assert f.nseries(x, logx=y) == log(y) + assert f.nseries(x, logx=-x) == log(-x) + assert f.nseries(x, logx=x) == log(x) + + f = log(log(log(1/x))) + + assert f.nseries(x, logx=y) == log(log(-y)) + assert f.nseries(x, logx=-y) == log(log(y)) + assert f.nseries(x, logx=x) == log(log(-x)) + assert f.nseries(x, logx=-x) == log(log(x)) + + +def test_issue_21415(): + exp = (x-1)*cos(1/(x-1)) + assert exp.limit(x,1) == 0 + assert exp.expand().limit(x,1) == 0 + + +def test_issue_21530(): + assert limit(sinh(n + 1)/sinh(n), n, oo) == E + + +def test_issue_21550(): + r = (sqrt(5) - 1)/2 + assert limit((x - r)/(x**2 + x - 1), x, r) == sqrt(5)/5 + + +def test_issue_21661(): + out = limit((x**(x + 1) * (log(x) + 1) + 1) / x, x, 11) + assert out == S(3138428376722)/11 + 285311670611*log(11) + + +def test_issue_21701(): + assert limit((besselj(z, x)/x**z).subs(z, 7), x, 0) == S(1)/645120 + + +def test_issue_21721(): + a = Symbol('a', real=True) + I = integrate(1/(pi*(1 + (x - a)**2)), x) + assert I.limit(x, oo) == S.Half + + +def test_issue_21756(): + term = (1 - exp(-2*I*pi*z))/(1 - exp(-2*I*pi*z/5)) + assert term.limit(z, 0) == 5 + assert re(term).limit(z, 0) == 5 + + +def test_issue_21785(): + a = Symbol('a') + assert sqrt((-a**2 + x**2)/(1 - x**2)).limit(a, 1, '-') == I + + +def test_issue_22181(): + assert limit((-1)**x * 2**(-x), x, oo) == 0 + + +def test_issue_22220(): + e1 = sqrt(30)*atan(sqrt(30)*tan(x/2)/6)/30 + e2 = sqrt(30)*I*(-log(sqrt(2)*tan(x/2) - 2*sqrt(15)*I/5) + + +log(sqrt(2)*tan(x/2) + 2*sqrt(15)*I/5))/60 + + assert limit(e1, x, -pi) == -sqrt(30)*pi/60 + assert limit(e2, x, -pi) == -sqrt(30)*pi/30 + + assert limit(e1, x, -pi, '-') == sqrt(30)*pi/60 + assert limit(e2, x, -pi, '-') == 0 + + # test https://github.com/sympy/sympy/issues/22220#issuecomment-972727694 + expr = log(x - I) - log(-x - I) + expr2 = logcombine(expr, force=True) + assert limit(expr, x, oo) == limit(expr2, x, oo) == I*pi + + # test https://github.com/sympy/sympy/issues/22220#issuecomment-1077618340 + expr = expr = (-log(tan(x/2) - I) +log(tan(x/2) + I)) + assert limit(expr, x, pi, '+') == 2*I*pi + assert limit(expr, x, pi, '-') == 0 + + +def test_issue_22334(): + k, n = symbols('k, n', positive=True) + assert limit((n+1)**k/((n+1)**(k+1) - (n)**(k+1)), n, oo) == 1/(k + 1) + assert limit((n+1)**k/((n+1)**(k+1) - (n)**(k+1)).expand(), n, oo) == 1/(k + 1) + assert limit((n+1)**k/(n*(-n**k + (n + 1)**k) + (n + 1)**k), n, oo) == 1/(k + 1) + + +def test_sympyissue_22986(): + assert limit(acosh(1 + 1/x)*sqrt(x), x, oo) == sqrt(2) + + +def test_issue_23231(): + f = (2**x - 2**(-x))/(2**x + 2**(-x)) + assert limit(f, x, -oo) == -1 + + +def test_issue_23596(): + assert integrate(((1 + x)/x**2)*exp(-1/x), (x, 0, oo)) == oo + + +def test_issue_23752(): + expr1 = sqrt(-I*x**2 + x - 3) + expr2 = sqrt(-I*x**2 + I*x - 3) + assert limit(expr1, x, 0, '+') == -sqrt(3)*I + assert limit(expr1, x, 0, '-') == -sqrt(3)*I + assert limit(expr2, x, 0, '+') == sqrt(3)*I + assert limit(expr2, x, 0, '-') == -sqrt(3)*I + + +def test_issue_24276(): + fx = log(tan(pi/2*tanh(x))).diff(x) + assert fx.limit(x, oo) == 2 + assert fx.simplify().limit(x, oo) == 2 + assert fx.rewrite(sin).limit(x, oo) == 2 + assert fx.rewrite(sin).simplify().limit(x, oo) == 2 + +def test_issue_25230(): + a = Symbol('a', real = True) + b = Symbol('b', positive = True) + c = Symbol('c', negative = True) + n = Symbol('n', integer = True) + raises(NotImplementedError, lambda: limit(Mod(x, a), x, a)) + assert limit(Mod(x, b), x, n*b, '+') == 0 + assert limit(Mod(x, b), x, n*b, '-') == b + assert limit(Mod(x, c), x, n*c, '+') == c + assert limit(Mod(x, c), x, n*c, '-') == 0 + + +def test_issue_25582(): + + assert limit(asin(exp(x)), x, oo, '-') == -oo*I + assert limit(acos(exp(x)), x, oo, '-') == oo*I + assert limit(atan(exp(x)), x, oo, '-') == pi/2 + assert limit(acot(exp(x)), x, oo, '-') == 0 + assert limit(asec(exp(x)), x, oo, '-') == pi/2 + assert limit(acsc(exp(x)), x, oo, '-') == 0 + + +def test_issue_25847(): + #atan + assert limit(atan(sin(x)/x), x, 0, '+-') == pi/4 + assert limit(atan(exp(1/x)), x, 0, '+') == pi/2 + assert limit(atan(exp(1/x)), x, 0, '-') == 0 + + #asin + assert limit(asin(sin(x)/x), x, 0, '+-') == pi/2 + assert limit(asin(exp(1/x)), x, 0, '+') == -oo*I + assert limit(asin(exp(1/x)), x, 0, '-') == 0 + + #acos + assert limit(acos(sin(x)/x), x, 0, '+-') == 0 + assert limit(acos(exp(1/x)), x, 0, '+') == oo*I + assert limit(acos(exp(1/x)), x, 0, '-') == pi/2 + + #acot + assert limit(acot(sin(x)/x), x, 0, '+-') == pi/4 + assert limit(acot(exp(1/x)), x, 0, '+') == 0 + assert limit(acot(exp(1/x)), x, 0, '-') == pi/2 + + #asec + assert limit(asec(sin(x)/x), x, 0, '+-') == 0 + assert limit(asec(exp(1/x)), x, 0, '+') == pi/2 + assert limit(asec(exp(1/x)), x, 0, '-') == oo*I + + #acsc + assert limit(acsc(sin(x)/x), x, 0, '+-') == pi/2 + assert limit(acsc(exp(1/x)), x, 0, '+') == 0 + assert limit(acsc(exp(1/x)), x, 0, '-') == -oo*I + + #atanh + assert limit(atanh(sin(x)/x), x, 0, '+-') == oo + assert limit(atanh(exp(1/x)), x, 0, '+') == -I*pi/2 + assert limit(atanh(exp(1/x)), x, 0, '-') == 0 + + #asinh + assert limit(asinh(sin(x)/x), x, 0, '+-') == log(1 + sqrt(2)) + assert limit(asinh(exp(1/x)), x, 0, '+') == oo + assert limit(asinh(exp(1/x)), x, 0, '-') == 0 + + #acosh + assert limit(acosh(sin(x)/x), x, 0, '+-') == 0 + assert limit(acosh(exp(1/x)), x, 0, '+') == oo + assert limit(acosh(exp(1/x)), x, 0, '-') == I*pi/2 + + #acoth + assert limit(acoth(sin(x)/x), x, 0, '+-') == oo + assert limit(acoth(exp(1/x)), x, 0, '+') == 0 + assert limit(acoth(exp(1/x)), x, 0, '-') == -I*pi/2 + + #asech + assert limit(asech(sin(x)/x), x, 0, '+-') == 0 + assert limit(asech(exp(1/x)), x, 0, '+') == I*pi/2 + assert limit(asech(exp(1/x)), x, 0, '-') == oo + + #acsch + assert limit(acsch(sin(x)/x), x, 0, '+-') == log(1 + sqrt(2)) + assert limit(acsch(exp(1/x)), x, 0, '+') == 0 + assert limit(acsch(exp(1/x)), x, 0, '-') == oo + + +def test_issue_26040(): + assert limit(besseli(0, x + 1)/besseli(0, x), x, oo) == S.Exp1 + + +def test_issue_26250(): + e = elliptic_e(4*x/(x**2 + 2*x + 1)) + k = elliptic_k(4*x/(x**2 + 2*x + 1)) + e1 = ((1-3*x**2)*e**2/2 - (x**2-2*x+1)*e*k/2) + e2 = pi**2*(x**8 - 2*x**7 - x**6 + 4*x**5 - x**4 - 2*x**3 + x**2) + assert limit(e1/e2, x, 0) == -S(1)/8 diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_limitseq.py b/lib/python3.12/site-packages/sympy/series/tests/test_limitseq.py new file mode 100644 index 0000000000000000000000000000000000000000..362bb0397feb0ec63929920855c81279eca0bd6a --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_limitseq.py @@ -0,0 +1,177 @@ +from sympy.concrete.summations import Sum +from sympy.core.add import Add +from sympy.core.numbers import (I, Rational, oo, pi) +from sympy.core.singleton import S +from sympy.core.symbol import (Symbol, symbols) +from sympy.functions.combinatorial.factorials import (binomial, factorial, subfactorial) +from sympy.functions.combinatorial.numbers import (fibonacci, harmonic) +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import (cos, sin) +from sympy.functions.special.gamma_functions import gamma +from sympy.series.limitseq import limit_seq +from sympy.series.limitseq import difference_delta as dd +from sympy.testing.pytest import raises, XFAIL +from sympy.calculus.accumulationbounds import AccumulationBounds + +n, m, k = symbols('n m k', integer=True) + + +def test_difference_delta(): + e = n*(n + 1) + e2 = e * k + + assert dd(e) == 2*n + 2 + assert dd(e2, n, 2) == k*(4*n + 6) + + raises(ValueError, lambda: dd(e2)) + raises(ValueError, lambda: dd(e2, n, oo)) + + +def test_difference_delta__Sum(): + e = Sum(1/k, (k, 1, n)) + assert dd(e, n) == 1/(n + 1) + assert dd(e, n, 5) == Add(*[1/(i + n + 1) for i in range(5)]) + + e = Sum(1/k, (k, 1, 3*n)) + assert dd(e, n) == Add(*[1/(i + 3*n + 1) for i in range(3)]) + + e = n * Sum(1/k, (k, 1, n)) + assert dd(e, n) == 1 + Sum(1/k, (k, 1, n)) + + e = Sum(1/k, (k, 1, n), (m, 1, n)) + assert dd(e, n) == harmonic(n) + + +def test_difference_delta__Add(): + e = n + n*(n + 1) + assert dd(e, n) == 2*n + 3 + assert dd(e, n, 2) == 4*n + 8 + + e = n + Sum(1/k, (k, 1, n)) + assert dd(e, n) == 1 + 1/(n + 1) + assert dd(e, n, 5) == 5 + Add(*[1/(i + n + 1) for i in range(5)]) + + +def test_difference_delta__Pow(): + e = 4**n + assert dd(e, n) == 3*4**n + assert dd(e, n, 2) == 15*4**n + + e = 4**(2*n) + assert dd(e, n) == 15*4**(2*n) + assert dd(e, n, 2) == 255*4**(2*n) + + e = n**4 + assert dd(e, n) == (n + 1)**4 - n**4 + + e = n**n + assert dd(e, n) == (n + 1)**(n + 1) - n**n + + +def test_limit_seq(): + e = binomial(2*n, n) / Sum(binomial(2*k, k), (k, 1, n)) + assert limit_seq(e) == S(3) / 4 + assert limit_seq(e, m) == e + + e = (5*n**3 + 3*n**2 + 4) / (3*n**3 + 4*n - 5) + assert limit_seq(e, n) == S(5) / 3 + + e = (harmonic(n) * Sum(harmonic(k), (k, 1, n))) / (n * harmonic(2*n)**2) + assert limit_seq(e, n) == 1 + + e = Sum(k**2 * Sum(2**m/m, (m, 1, k)), (k, 1, n)) / (2**n*n) + assert limit_seq(e, n) == 4 + + e = (Sum(binomial(3*k, k) * binomial(5*k, k), (k, 1, n)) / + (binomial(3*n, n) * binomial(5*n, n))) + assert limit_seq(e, n) == S(84375) / 83351 + + e = Sum(harmonic(k)**2/k, (k, 1, 2*n)) / harmonic(n)**3 + assert limit_seq(e, n) == S.One / 3 + + raises(ValueError, lambda: limit_seq(e * m)) + + +def test_alternating_sign(): + assert limit_seq((-1)**n/n**2, n) == 0 + assert limit_seq((-2)**(n+1)/(n + 3**n), n) == 0 + assert limit_seq((2*n + (-1)**n)/(n + 1), n) == 2 + assert limit_seq(sin(pi*n), n) == 0 + assert limit_seq(cos(2*pi*n), n) == 1 + assert limit_seq((S.NegativeOne/5)**n, n) == 0 + assert limit_seq((Rational(-1, 5))**n, n) == 0 + assert limit_seq((I/3)**n, n) == 0 + assert limit_seq(sqrt(n)*(I/2)**n, n) == 0 + assert limit_seq(n**7*(I/3)**n, n) == 0 + assert limit_seq(n/(n + 1) + (I/2)**n, n) == 1 + + +def test_accum_bounds(): + assert limit_seq((-1)**n, n) == AccumulationBounds(-1, 1) + assert limit_seq(cos(pi*n), n) == AccumulationBounds(-1, 1) + assert limit_seq(sin(pi*n/2)**2, n) == AccumulationBounds(0, 1) + assert limit_seq(2*(-3)**n/(n + 3**n), n) == AccumulationBounds(-2, 2) + assert limit_seq(3*n/(n + 1) + 2*(-1)**n, n) == AccumulationBounds(1, 5) + + +def test_limitseq_sum(): + from sympy.abc import x, y, z + assert limit_seq(Sum(1/x, (x, 1, y)) - log(y), y) == S.EulerGamma + assert limit_seq(Sum(1/x, (x, 1, y)) - 1/y, y) is S.Infinity + assert (limit_seq(binomial(2*x, x) / Sum(binomial(2*y, y), (y, 1, x)), x) == + S(3) / 4) + assert (limit_seq(Sum(y**2 * Sum(2**z/z, (z, 1, y)), (y, 1, x)) / + (2**x*x), x) == 4) + + +def test_issue_9308(): + assert limit_seq(subfactorial(n)/factorial(n), n) == exp(-1) + + +def test_issue_10382(): + n = Symbol('n', integer=True) + assert limit_seq(fibonacci(n+1)/fibonacci(n), n).together() == S.GoldenRatio + + +def test_issue_11672(): + assert limit_seq(Rational(-1, 2)**n, n) == 0 + + +def test_issue_14196(): + k, n = symbols('k, n', positive=True) + m = Symbol('m') + assert limit_seq(Sum(m**k, (m, 1, n)).doit()/(n**(k + 1)), n) == 1/(k + 1) + + +def test_issue_16735(): + assert limit_seq(5**n/factorial(n), n) == 0 + + +def test_issue_19868(): + assert limit_seq(1/gamma(n + S.One/2), n) == 0 + + +@XFAIL +def test_limit_seq_fail(): + # improve Summation algorithm or add ad-hoc criteria + e = (harmonic(n)**3 * Sum(1/harmonic(k), (k, 1, n)) / + (n * Sum(harmonic(k)/k, (k, 1, n)))) + assert limit_seq(e, n) == 2 + + # No unique dominant term + e = (Sum(2**k * binomial(2*k, k) / k**2, (k, 1, n)) / + (Sum(2**k/k*2, (k, 1, n)) * Sum(binomial(2*k, k), (k, 1, n)))) + assert limit_seq(e, n) == S(3) / 7 + + # Simplifications of summations needs to be improved. + e = n**3*Sum(2**k/k**2, (k, 1, n))**2 / (2**n * Sum(2**k/k, (k, 1, n))) + assert limit_seq(e, n) == 2 + + e = (harmonic(n) * Sum(2**k/k, (k, 1, n)) / + (n * Sum(2**k*harmonic(k)/k**2, (k, 1, n)))) + assert limit_seq(e, n) == 1 + + e = (Sum(2**k*factorial(k) / k**2, (k, 1, 2*n)) / + (Sum(4**k/k**2, (k, 1, n)) * Sum(factorial(k), (k, 1, 2*n)))) + assert limit_seq(e, n) == S(3) / 16 diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_lseries.py b/lib/python3.12/site-packages/sympy/series/tests/test_lseries.py new file mode 100644 index 0000000000000000000000000000000000000000..42d327bf60c76eebdc4570d631efef4bc84b58e3 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_lseries.py @@ -0,0 +1,65 @@ +from sympy.core.numbers import E +from sympy.core.singleton import S +from sympy.functions.elementary.exponential import exp +from sympy.functions.elementary.hyperbolic import tanh +from sympy.functions.elementary.trigonometric import (cos, sin) +from sympy.series.order import Order +from sympy.abc import x, y + + +def test_sin(): + e = sin(x).lseries(x) + assert next(e) == x + assert next(e) == -x**3/6 + assert next(e) == x**5/120 + + +def test_cos(): + e = cos(x).lseries(x) + assert next(e) == 1 + assert next(e) == -x**2/2 + assert next(e) == x**4/24 + + +def test_exp(): + e = exp(x).lseries(x) + assert next(e) == 1 + assert next(e) == x + assert next(e) == x**2/2 + assert next(e) == x**3/6 + + +def test_exp2(): + e = exp(cos(x)).lseries(x) + assert next(e) == E + assert next(e) == -E*x**2/2 + assert next(e) == E*x**4/6 + assert next(e) == -31*E*x**6/720 + + +def test_simple(): + assert list(x.lseries()) == [x] + assert list(S.One.lseries(x)) == [1] + assert not next((x/(x + y)).lseries(y)).has(Order) + + +def test_issue_5183(): + s = (x + 1/x).lseries() + assert list(s) == [1/x, x] + assert next((x + x**2).lseries()) == x + assert next(((1 + x)**7).lseries(x)) == 1 + assert next((sin(x + y)).series(x, n=3).lseries(y)) == x + # it would be nice if all terms were grouped, but in the + # following case that would mean that all the terms would have + # to be known since, for example, every term has a constant in it. + s = ((1 + x)**7).series(x, 1, n=None) + assert [next(s) for i in range(2)] == [128, -448 + 448*x] + + +def test_issue_6999(): + s = tanh(x).lseries(x, 1) + assert next(s) == tanh(1) + assert next(s) == x - (x - 1)*tanh(1)**2 - 1 + assert next(s) == -(x - 1)**2*tanh(1) + (x - 1)**2*tanh(1)**3 + assert next(s) == -(x - 1)**3*tanh(1)**4 - (x - 1)**3/3 + \ + 4*(x - 1)**3*tanh(1)**2/3 diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_nseries.py b/lib/python3.12/site-packages/sympy/series/tests/test_nseries.py new file mode 100644 index 0000000000000000000000000000000000000000..a2f20add82d3e858e2ce145fc9fcd4a6548a48cc --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_nseries.py @@ -0,0 +1,557 @@ +from sympy.calculus.util import AccumBounds +from sympy.core.function import (Derivative, PoleError) +from sympy.core.numbers import (E, I, Integer, Rational, pi) +from sympy.core.singleton import S +from sympy.core.symbol import (Symbol, symbols) +from sympy.functions.elementary.complexes import sign +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.hyperbolic import (acosh, acoth, asinh, atanh, cosh, coth, sinh, tanh) +from sympy.functions.elementary.integers import (ceiling, floor, frac) +from sympy.functions.elementary.miscellaneous import (cbrt, sqrt) +from sympy.functions.elementary.trigonometric import (asin, cos, cot, sin, tan) +from sympy.series.limits import limit +from sympy.series.order import O +from sympy.abc import x, y, z + +from sympy.testing.pytest import raises, XFAIL + + +def test_simple_1(): + assert x.nseries(x, n=5) == x + assert y.nseries(x, n=5) == y + assert (1/(x*y)).nseries(y, n=5) == 1/(x*y) + assert Rational(3, 4).nseries(x, n=5) == Rational(3, 4) + assert x.nseries() == x + + +def test_mul_0(): + assert (x*log(x)).nseries(x, n=5) == x*log(x) + + +def test_mul_1(): + assert (x*log(2 + x)).nseries(x, n=5) == x*log(2) + x**2/2 - x**3/8 + \ + x**4/24 + O(x**5) + assert (x*log(1 + x)).nseries( + x, n=5) == x**2 - x**3/2 + x**4/3 + O(x**5) + + +def test_pow_0(): + assert (x**2).nseries(x, n=5) == x**2 + assert (1/x).nseries(x, n=5) == 1/x + assert (1/x**2).nseries(x, n=5) == 1/x**2 + assert (x**Rational(2, 3)).nseries(x, n=5) == (x**Rational(2, 3)) + assert (sqrt(x)**3).nseries(x, n=5) == (sqrt(x)**3) + + +def test_pow_1(): + assert ((1 + x)**2).nseries(x, n=5) == x**2 + 2*x + 1 + + # https://github.com/sympy/sympy/issues/21075 + assert ((sqrt(x) + 1)**2).nseries(x) == 2*sqrt(x) + x + 1 + assert ((sqrt(x) + cbrt(x))**2).nseries(x) == 2*x**Rational(5, 6)\ + + x**Rational(2, 3) + x + + +def test_geometric_1(): + assert (1/(1 - x)).nseries(x, n=5) == 1 + x + x**2 + x**3 + x**4 + O(x**5) + assert (x/(1 - x)).nseries(x, n=6) == x + x**2 + x**3 + x**4 + x**5 + O(x**6) + assert (x**3/(1 - x)).nseries(x, n=8) == x**3 + x**4 + x**5 + x**6 + \ + x**7 + O(x**8) + + +def test_sqrt_1(): + assert sqrt(1 + x).nseries(x, n=5) == 1 + x/2 - x**2/8 + x**3/16 - 5*x**4/128 + O(x**5) + + +def test_exp_1(): + assert exp(x).nseries(x, n=5) == 1 + x + x**2/2 + x**3/6 + x**4/24 + O(x**5) + assert exp(x).nseries(x, n=12) == 1 + x + x**2/2 + x**3/6 + x**4/24 + x**5/120 + \ + x**6/720 + x**7/5040 + x**8/40320 + x**9/362880 + x**10/3628800 + \ + x**11/39916800 + O(x**12) + assert exp(1/x).nseries(x, n=5) == exp(1/x) + assert exp(1/(1 + x)).nseries(x, n=4) == \ + (E*(1 - x - 13*x**3/6 + 3*x**2/2)).expand() + O(x**4) + assert exp(2 + x).nseries(x, n=5) == \ + (exp(2)*(1 + x + x**2/2 + x**3/6 + x**4/24)).expand() + O(x**5) + + +def test_exp_sqrt_1(): + assert exp(1 + sqrt(x)).nseries(x, n=3) == \ + (exp(1)*(1 + sqrt(x) + x/2 + sqrt(x)*x/6)).expand() + O(sqrt(x)**3) + + +def test_power_x_x1(): + assert (exp(x*log(x))).nseries(x, n=4) == \ + 1 + x*log(x) + x**2*log(x)**2/2 + x**3*log(x)**3/6 + O(x**4*log(x)**4) + + +def test_power_x_x2(): + assert (x**x).nseries(x, n=4) == \ + 1 + x*log(x) + x**2*log(x)**2/2 + x**3*log(x)**3/6 + O(x**4*log(x)**4) + + +def test_log_singular1(): + assert log(1 + 1/x).nseries(x, n=5) == x - log(x) - x**2/2 + x**3/3 - \ + x**4/4 + O(x**5) + + +def test_log_power1(): + e = 1 / (1/x + x ** (log(3)/log(2))) + assert e.nseries(x, n=5) == -x**(log(3)/log(2) + 2) + x + O(x**5) + + +def test_log_series(): + l = Symbol('l') + e = 1/(1 - log(x)) + assert e.nseries(x, n=5, logx=l) == 1/(1 - l) + + +def test_log2(): + e = log(-1/x) + assert e.nseries(x, n=5) == -log(x) + log(-1) + + +def test_log3(): + l = Symbol('l') + e = 1/log(-1/x) + assert e.nseries(x, n=4, logx=l) == 1/(-l + log(-1)) + + +def test_series1(): + e = sin(x) + assert e.nseries(x, 0, 0) != 0 + assert e.nseries(x, 0, 0) == O(1, x) + assert e.nseries(x, 0, 1) == O(x, x) + assert e.nseries(x, 0, 2) == x + O(x**2, x) + assert e.nseries(x, 0, 3) == x + O(x**3, x) + assert e.nseries(x, 0, 4) == x - x**3/6 + O(x**4, x) + + e = (exp(x) - 1)/x + assert e.nseries(x, 0, 3) == 1 + x/2 + x**2/6 + O(x**3) + + assert x.nseries(x, 0, 2) == x + + +@XFAIL +def test_series1_failing(): + assert x.nseries(x, 0, 0) == O(1, x) + assert x.nseries(x, 0, 1) == O(x, x) + + +def test_seriesbug1(): + assert (1/x).nseries(x, 0, 3) == 1/x + assert (x + 1/x).nseries(x, 0, 3) == x + 1/x + + +def test_series2x(): + assert ((x + 1)**(-2)).nseries(x, 0, 4) == 1 - 2*x + 3*x**2 - 4*x**3 + O(x**4, x) + assert ((x + 1)**(-1)).nseries(x, 0, 4) == 1 - x + x**2 - x**3 + O(x**4, x) + assert ((x + 1)**0).nseries(x, 0, 3) == 1 + assert ((x + 1)**1).nseries(x, 0, 3) == 1 + x + assert ((x + 1)**2).nseries(x, 0, 3) == x**2 + 2*x + 1 + assert ((x + 1)**3).nseries(x, 0, 3) == 1 + 3*x + 3*x**2 + O(x**3) + + assert (1/(1 + x)).nseries(x, 0, 4) == 1 - x + x**2 - x**3 + O(x**4, x) + assert (x + 3/(1 + 2*x)).nseries(x, 0, 4) == 3 - 5*x + 12*x**2 - 24*x**3 + O(x**4, x) + + assert ((1/x + 1)**3).nseries(x, 0, 3) == 1 + 3/x + 3/x**2 + x**(-3) + assert (1/(1 + 1/x)).nseries(x, 0, 4) == x - x**2 + x**3 - O(x**4, x) + assert (1/(1 + 1/x**2)).nseries(x, 0, 6) == x**2 - x**4 + O(x**6, x) + + +def test_bug2(): # 1/log(0)*log(0) problem + w = Symbol("w") + e = (w**(-1) + w**( + -log(3)*log(2)**(-1)))**(-1)*(3*w**(-log(3)*log(2)**(-1)) + 2*w**(-1)) + e = e.expand() + assert e.nseries(w, 0, 4).subs(w, 0) == 3 + + +def test_exp(): + e = (1 + x)**(1/x) + assert e.nseries(x, n=3) == exp(1) - x*exp(1)/2 + 11*exp(1)*x**2/24 + O(x**3) + + +def test_exp2(): + w = Symbol("w") + e = w**(1 - log(x)/(log(2) + log(x))) + logw = Symbol("logw") + assert e.nseries( + w, 0, 1, logx=logw) == exp(logw*log(2)/(log(x) + log(2))) + + +def test_bug3(): + e = (2/x + 3/x**2)/(1/x + 1/x**2) + assert e.nseries(x, n=3) == 3 - x + x**2 + O(x**3) + + +def test_generalexponent(): + p = 2 + e = (2/x + 3/x**p)/(1/x + 1/x**p) + assert e.nseries(x, 0, 3) == 3 - x + x**2 + O(x**3) + p = S.Half + e = (2/x + 3/x**p)/(1/x + 1/x**p) + assert e.nseries(x, 0, 2) == 2 - x + sqrt(x) + x**(S(3)/2) + O(x**2) + + e = 1 + sqrt(x) + assert e.nseries(x, 0, 4) == 1 + sqrt(x) + +# more complicated example + + +def test_genexp_x(): + e = 1/(1 + sqrt(x)) + assert e.nseries(x, 0, 2) == \ + 1 + x - sqrt(x) - sqrt(x)**3 + O(x**2, x) + +# more complicated example + + +def test_genexp_x2(): + p = Rational(3, 2) + e = (2/x + 3/x**p)/(1/x + 1/x**p) + assert e.nseries(x, 0, 3) == 3 + x + x**2 - sqrt(x) - x**(S(3)/2) - x**(S(5)/2) + O(x**3) + + +def test_seriesbug2(): + w = Symbol("w") + #simple case (1): + e = ((2*w)/w)**(1 + w) + assert e.nseries(w, 0, 1) == 2 + O(w, w) + assert e.nseries(w, 0, 1).subs(w, 0) == 2 + + +def test_seriesbug2b(): + w = Symbol("w") + #test sin + e = sin(2*w)/w + assert e.nseries(w, 0, 3) == 2 - 4*w**2/3 + O(w**3) + + +def test_seriesbug2d(): + w = Symbol("w", real=True) + e = log(sin(2*w)/w) + assert e.series(w, n=5) == log(2) - 2*w**2/3 - 4*w**4/45 + O(w**5) + + +def test_seriesbug2c(): + w = Symbol("w", real=True) + #more complicated case, but sin(x)~x, so the result is the same as in (1) + e = (sin(2*w)/w)**(1 + w) + assert e.series(w, 0, 1) == 2 + O(w) + assert e.series(w, 0, 3) == 2 + 2*w*log(2) + \ + w**2*(Rational(-4, 3) + log(2)**2) + O(w**3) + assert e.series(w, 0, 2).subs(w, 0) == 2 + + +def test_expbug4(): + x = Symbol("x", real=True) + assert (log( + sin(2*x)/x)*(1 + x)).series(x, 0, 2) == log(2) + x*log(2) + O(x**2, x) + assert exp( + log(sin(2*x)/x)*(1 + x)).series(x, 0, 2) == 2 + 2*x*log(2) + O(x**2) + + assert exp(log(2) + O(x)).nseries(x, 0, 2) == 2 + O(x) + assert ((2 + O(x))**(1 + x)).nseries(x, 0, 2) == 2 + O(x) + + +def test_logbug4(): + assert log(2 + O(x)).nseries(x, 0, 2) == log(2) + O(x, x) + + +def test_expbug5(): + assert exp(log(1 + x)/x).nseries(x, n=3) == exp(1) + -exp(1)*x/2 + 11*exp(1)*x**2/24 + O(x**3) + + assert exp(O(x)).nseries(x, 0, 2) == 1 + O(x) + + +def test_sinsinbug(): + assert sin(sin(x)).nseries(x, 0, 8) == x - x**3/3 + x**5/10 - 8*x**7/315 + O(x**8) + + +def test_issue_3258(): + a = x/(exp(x) - 1) + assert a.nseries(x, 0, 5) == 1 - x/2 - x**4/720 + x**2/12 + O(x**5) + + +def test_issue_3204(): + x = Symbol("x", nonnegative=True) + f = sin(x**3)**Rational(1, 3) + assert f.nseries(x, 0, 17) == x - x**7/18 - x**13/3240 + O(x**17) + + +def test_issue_3224(): + f = sqrt(1 - sqrt(y)) + assert f.nseries(y, 0, 2) == 1 - sqrt(y)/2 - y/8 - sqrt(y)**3/16 + O(y**2) + + +def test_issue_3463(): + w, i = symbols('w,i') + r = log(5)/log(3) + p = w**(-1 + r) + e = 1/x*(-log(w**(1 + r)) + log(w + w**r)) + e_ser = -r*log(w)/x + p/x - p**2/(2*x) + O(w) + assert e.nseries(w, n=1) == e_ser + + +def test_sin(): + assert sin(8*x).nseries(x, n=4) == 8*x - 256*x**3/3 + O(x**4) + assert sin(x + y).nseries(x, n=1) == sin(y) + O(x) + assert sin(x + y).nseries(x, n=2) == sin(y) + cos(y)*x + O(x**2) + assert sin(x + y).nseries(x, n=5) == sin(y) + cos(y)*x - sin(y)*x**2/2 - \ + cos(y)*x**3/6 + sin(y)*x**4/24 + O(x**5) + + +def test_issue_3515(): + e = sin(8*x)/x + assert e.nseries(x, n=6) == 8 - 256*x**2/3 + 4096*x**4/15 + O(x**6) + + +def test_issue_3505(): + e = sin(x)**(-4)*(sqrt(cos(x))*sin(x)**2 - + cos(x)**Rational(1, 3)*sin(x)**2) + assert e.nseries(x, n=9) == Rational(-1, 12) - 7*x**2/288 - \ + 43*x**4/10368 - 1123*x**6/2488320 + 377*x**8/29859840 + O(x**9) + + +def test_issue_3501(): + a = Symbol("a") + e = x**(-2)*(x*sin(a + x) - x*sin(a)) + assert e.nseries(x, n=6) == cos(a) - sin(a)*x/2 - cos(a)*x**2/6 + \ + x**3*sin(a)/24 + x**4*cos(a)/120 - x**5*sin(a)/720 + O(x**6) + e = x**(-2)*(x*cos(a + x) - x*cos(a)) + assert e.nseries(x, n=6) == -sin(a) - cos(a)*x/2 + sin(a)*x**2/6 + \ + cos(a)*x**3/24 - x**4*sin(a)/120 - x**5*cos(a)/720 + O(x**6) + + +def test_issue_3502(): + e = sin(5*x)/sin(2*x) + assert e.nseries(x, n=2) == Rational(5, 2) + O(x**2) + assert e.nseries(x, n=6) == \ + Rational(5, 2) - 35*x**2/4 + 329*x**4/48 + O(x**6) + + +def test_issue_3503(): + e = sin(2 + x)/(2 + x) + assert e.nseries(x, n=2) == sin(2)/2 + x*cos(2)/2 - x*sin(2)/4 + O(x**2) + + +def test_issue_3506(): + e = (x + sin(3*x))**(-2)*(x*(x + sin(3*x)) - (x + sin(3*x))*sin(2*x)) + assert e.nseries(x, n=7) == \ + Rational(-1, 4) + 5*x**2/96 + 91*x**4/768 + 11117*x**6/129024 + O(x**7) + + +def test_issue_3508(): + x = Symbol("x", real=True) + assert log(sin(x)).series(x, n=5) == log(x) - x**2/6 - x**4/180 + O(x**5) + e = -log(x) + x*(-log(x) + log(sin(2*x))) + log(sin(2*x)) + assert e.series(x, n=5) == \ + log(2) + log(2)*x - 2*x**2/3 - 2*x**3/3 - 4*x**4/45 + O(x**5) + + +def test_issue_3507(): + e = x**(-4)*(x**2 - x**2*sqrt(cos(x))) + assert e.nseries(x, n=9) == \ + Rational(1, 4) + x**2/96 + 19*x**4/5760 + 559*x**6/645120 + 29161*x**8/116121600 + O(x**9) + + +def test_issue_3639(): + assert sin(cos(x)).nseries(x, n=5) == \ + sin(1) - x**2*cos(1)/2 - x**4*sin(1)/8 + x**4*cos(1)/24 + O(x**5) + + +def test_hyperbolic(): + assert sinh(x).nseries(x, n=6) == x + x**3/6 + x**5/120 + O(x**6) + assert cosh(x).nseries(x, n=5) == 1 + x**2/2 + x**4/24 + O(x**5) + assert tanh(x).nseries(x, n=6) == x - x**3/3 + 2*x**5/15 + O(x**6) + assert coth(x).nseries(x, n=6) == \ + 1/x - x**3/45 + x/3 + 2*x**5/945 + O(x**6) + assert asinh(x).nseries(x, n=6) == x - x**3/6 + 3*x**5/40 + O(x**6) + assert acosh(x).nseries(x, n=6) == \ + pi*I/2 - I*x - 3*I*x**5/40 - I*x**3/6 + O(x**6) + assert atanh(x).nseries(x, n=6) == x + x**3/3 + x**5/5 + O(x**6) + assert acoth(x).nseries(x, n=6) == -I*pi/2 + x + x**3/3 + x**5/5 + O(x**6) + + +def test_series2(): + w = Symbol("w", real=True) + x = Symbol("x", real=True) + e = w**(-2)*(w*exp(1/x - w) - w*exp(1/x)) + assert e.nseries(w, n=4) == -exp(1/x) + w*exp(1/x)/2 - w**2*exp(1/x)/6 + w**3*exp(1/x)/24 + O(w**4) + + +def test_series3(): + w = Symbol("w", real=True) + e = w**(-6)*(w**3*tan(w) - w**3*sin(w)) + assert e.nseries(w, n=8) == Integer(1)/2 + w**2/8 + 13*w**4/240 + 529*w**6/24192 + O(w**8) + + +def test_bug4(): + w = Symbol("w") + e = x/(w**4 + x**2*w**4 + 2*x*w**4)*w**4 + assert e.nseries(w, n=2).removeO().expand() in [x/(1 + 2*x + x**2), + 1/(1 + x/2 + 1/x/2)/2, 1/x/(1 + 2/x + x**(-2))] + + +def test_bug5(): + w = Symbol("w") + l = Symbol('l') + e = (-log(w) + log(1 + w*log(x)))**(-2)*w**(-2)*((-log(w) + + log(1 + x*w))*(-log(w) + log(1 + w*log(x)))*w - x*(-log(w) + + log(1 + w*log(x)))*w) + assert e.nseries(w, n=0, logx=l) == x/w/l + 1/w + O(1, w) + assert e.nseries(w, n=1, logx=l) == x/w/l + 1/w - x/l + 1/l*log(x) \ + + x*log(x)/l**2 + O(w) + + +def test_issue_4115(): + assert (sin(x)/(1 - cos(x))).nseries(x, n=1) == 2/x + O(x) + assert (sin(x)**2/(1 - cos(x))).nseries(x, n=1) == 2 + O(x) + + +def test_pole(): + raises(PoleError, lambda: sin(1/x).series(x, 0, 5)) + raises(PoleError, lambda: sin(1 + 1/x).series(x, 0, 5)) + raises(PoleError, lambda: (x*sin(1/x)).series(x, 0, 5)) + + +def test_expsinbug(): + assert exp(sin(x)).series(x, 0, 0) == O(1, x) + assert exp(sin(x)).series(x, 0, 1) == 1 + O(x) + assert exp(sin(x)).series(x, 0, 2) == 1 + x + O(x**2) + assert exp(sin(x)).series(x, 0, 3) == 1 + x + x**2/2 + O(x**3) + assert exp(sin(x)).series(x, 0, 4) == 1 + x + x**2/2 + O(x**4) + assert exp(sin(x)).series(x, 0, 5) == 1 + x + x**2/2 - x**4/8 + O(x**5) + + +def test_floor(): + x = Symbol('x') + assert floor(x).series(x) == 0 + assert floor(-x).series(x) == -1 + assert floor(sin(x)).series(x) == 0 + assert floor(sin(-x)).series(x) == -1 + assert floor(x**3).series(x) == 0 + assert floor(-x**3).series(x) == -1 + assert floor(cos(x)).series(x) == 0 + assert floor(cos(-x)).series(x) == 0 + assert floor(5 + sin(x)).series(x) == 5 + assert floor(5 + sin(-x)).series(x) == 4 + + assert floor(x).series(x, 2) == 2 + assert floor(-x).series(x, 2) == -3 + + x = Symbol('x', negative=True) + assert floor(x + 1.5).series(x) == 1 + + +def test_frac(): + assert frac(x).series(x, cdir=1) == x + assert frac(x).series(x, cdir=-1) == 1 + x + assert frac(2*x + 1).series(x, cdir=1) == 2*x + assert frac(2*x + 1).series(x, cdir=-1) == 1 + 2*x + assert frac(x**2).series(x, cdir=1) == x**2 + assert frac(x**2).series(x, cdir=-1) == x**2 + assert frac(sin(x) + 5).series(x, cdir=1) == x - x**3/6 + x**5/120 + O(x**6) + assert frac(sin(x) + 5).series(x, cdir=-1) == 1 + x - x**3/6 + x**5/120 + O(x**6) + assert frac(sin(x) + S.Half).series(x) == S.Half + x - x**3/6 + x**5/120 + O(x**6) + assert frac(x**8).series(x, cdir=1) == O(x**6) + assert frac(1/x).series(x) == AccumBounds(0, 1) + O(x**6) + + +def test_ceiling(): + assert ceiling(x).series(x) == 1 + assert ceiling(-x).series(x) == 0 + assert ceiling(sin(x)).series(x) == 1 + assert ceiling(sin(-x)).series(x) == 0 + assert ceiling(1 - cos(x)).series(x) == 1 + assert ceiling(1 - cos(-x)).series(x) == 1 + assert ceiling(x).series(x, 2) == 3 + assert ceiling(-x).series(x, 2) == -2 + + +def test_abs(): + a = Symbol('a') + assert abs(x).nseries(x, n=4) == x + assert abs(-x).nseries(x, n=4) == x + assert abs(x + 1).nseries(x, n=4) == x + 1 + assert abs(sin(x)).nseries(x, n=4) == x - Rational(1, 6)*x**3 + O(x**4) + assert abs(sin(-x)).nseries(x, n=4) == x - Rational(1, 6)*x**3 + O(x**4) + assert abs(x - a).nseries(x, 1) == -a*sign(1 - a) + (x - 1)*sign(1 - a) + sign(1 - a) + + +def test_dir(): + assert abs(x).series(x, 0, dir="+") == x + assert abs(x).series(x, 0, dir="-") == -x + assert floor(x + 2).series(x, 0, dir='+') == 2 + assert floor(x + 2).series(x, 0, dir='-') == 1 + assert floor(x + 2.2).series(x, 0, dir='-') == 2 + assert ceiling(x + 2.2).series(x, 0, dir='-') == 3 + assert sin(x + y).series(x, 0, dir='-') == sin(x + y).series(x, 0, dir='+') + + +def test_cdir(): + assert abs(x).series(x, 0, cdir=1) == x + assert abs(x).series(x, 0, cdir=-1) == -x + assert floor(x + 2).series(x, 0, cdir=1) == 2 + assert floor(x + 2).series(x, 0, cdir=-1) == 1 + assert floor(x + 2.2).series(x, 0, cdir=1) == 2 + assert ceiling(x + 2.2).series(x, 0, cdir=-1) == 3 + assert sin(x + y).series(x, 0, cdir=-1) == sin(x + y).series(x, 0, cdir=1) + + +def test_issue_3504(): + a = Symbol("a") + e = asin(a*x)/x + assert e.series(x, 4, n=2).removeO() == \ + (x - 4)*(a/(4*sqrt(-16*a**2 + 1)) - asin(4*a)/16) + asin(4*a)/4 + + +def test_issue_4441(): + a, b = symbols('a,b') + f = 1/(1 + a*x) + assert f.series(x, 0, 5) == 1 - a*x + a**2*x**2 - a**3*x**3 + \ + a**4*x**4 + O(x**5) + f = 1/(1 + (a + b)*x) + assert f.series(x, 0, 3) == 1 + x*(-a - b)\ + + x**2*(a + b)**2 + O(x**3) + + +def test_issue_4329(): + assert tan(x).series(x, pi/2, n=3).removeO() == \ + -pi/6 + x/3 - 1/(x - pi/2) + assert cot(x).series(x, pi, n=3).removeO() == \ + -x/3 + pi/3 + 1/(x - pi) + assert limit(tan(x)**tan(2*x), x, pi/4) == exp(-1) + + +def test_issue_5183(): + assert abs(x + x**2).series(n=1) == O(x) + assert abs(x + x**2).series(n=2) == x + O(x**2) + assert ((1 + x)**2).series(x, n=6) == x**2 + 2*x + 1 + assert (1 + 1/x).series() == 1 + 1/x + assert Derivative(exp(x).series(), x).doit() == \ + 1 + x + x**2/2 + x**3/6 + x**4/24 + O(x**5) + + +def test_issue_5654(): + a = Symbol('a') + assert (1/(x**2+a**2)**2).nseries(x, x0=I*a, n=0) == \ + -I/(4*a**3*(-I*a + x)) - 1/(4*a**2*(-I*a + x)**2) + O(1, (x, I*a)) + assert (1/(x**2+a**2)**2).nseries(x, x0=I*a, n=1) == 3/(16*a**4) \ + -I/(4*a**3*(-I*a + x)) - 1/(4*a**2*(-I*a + x)**2) + O(-I*a + x, (x, I*a)) + + +def test_issue_5925(): + sx = sqrt(x + z).series(z, 0, 1) + sxy = sqrt(x + y + z).series(z, 0, 1) + s1, s2 = sx.subs(x, x + y), sxy + assert (s1 - s2).expand().removeO().simplify() == 0 + + sx = sqrt(x + z).series(z, 0, 1) + sxy = sqrt(x + y + z).series(z, 0, 1) + assert sxy.subs({x:1, y:2}) == sx.subs(x, 3) + + +def test_exp_2(): + assert exp(x**3).nseries(x, 0, 14) == 1 + x**3 + x**6/2 + x**9/6 + x**12/24 + O(x**14) diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_order.py b/lib/python3.12/site-packages/sympy/series/tests/test_order.py new file mode 100644 index 0000000000000000000000000000000000000000..dd4cd9938d6ebbc4d8d915e09ec6e9c02c6fe599 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_order.py @@ -0,0 +1,477 @@ +from sympy.core.add import Add +from sympy.core.function import (Function, expand) +from sympy.core.numbers import (I, Rational, nan, oo, pi) +from sympy.core.singleton import S +from sympy.core.symbol import (Symbol, symbols) +from sympy.functions.elementary.complexes import (conjugate, transpose) +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import (cos, sin) +from sympy.integrals.integrals import Integral +from sympy.series.order import O, Order +from sympy.core.expr import unchanged +from sympy.testing.pytest import raises +from sympy.abc import w, x, y, z + + +def test_caching_bug(): + #needs to be a first test, so that all caches are clean + #cache it + O(w) + #and test that this won't raise an exception + O(w**(-1/x/log(3)*log(5)), w) + + +def test_free_symbols(): + assert Order(1).free_symbols == set() + assert Order(x).free_symbols == {x} + assert Order(1, x).free_symbols == {x} + assert Order(x*y).free_symbols == {x, y} + assert Order(x, x, y).free_symbols == {x, y} + + +def test_simple_1(): + o = Rational(0) + assert Order(2*x) == Order(x) + assert Order(x)*3 == Order(x) + assert -28*Order(x) == Order(x) + assert Order(Order(x)) == Order(x) + assert Order(Order(x), y) == Order(Order(x), x, y) + assert Order(-23) == Order(1) + assert Order(exp(x)) == Order(1, x) + assert Order(exp(1/x)).expr == exp(1/x) + assert Order(x*exp(1/x)).expr == x*exp(1/x) + assert Order(x**(o/3)).expr == x**(o/3) + assert Order(x**(o*Rational(5, 3))).expr == x**(o*Rational(5, 3)) + assert Order(x**2 + x + y, x) == O(1, x) + assert Order(x**2 + x + y, y) == O(1, y) + raises(ValueError, lambda: Order(exp(x), x, x)) + raises(TypeError, lambda: Order(x, 2 - x)) + + +def test_simple_2(): + assert Order(2*x)*x == Order(x**2) + assert Order(2*x)/x == Order(1, x) + assert Order(2*x)*x*exp(1/x) == Order(x**2*exp(1/x)) + assert (Order(2*x)*x*exp(1/x)/log(x)**3).expr == x**2*exp(1/x)*log(x)**-3 + + +def test_simple_3(): + assert Order(x) + x == Order(x) + assert Order(x) + 2 == 2 + Order(x) + assert Order(x) + x**2 == Order(x) + assert Order(x) + 1/x == 1/x + Order(x) + assert Order(1/x) + 1/x**2 == 1/x**2 + Order(1/x) + assert Order(x) + exp(1/x) == Order(x) + exp(1/x) + + +def test_simple_4(): + assert Order(x)**2 == Order(x**2) + + +def test_simple_5(): + assert Order(x) + Order(x**2) == Order(x) + assert Order(x) + Order(x**-2) == Order(x**-2) + assert Order(x) + Order(1/x) == Order(1/x) + + +def test_simple_6(): + assert Order(x) - Order(x) == Order(x) + assert Order(x) + Order(1) == Order(1) + assert Order(x) + Order(x**2) == Order(x) + assert Order(1/x) + Order(1) == Order(1/x) + assert Order(x) + Order(exp(1/x)) == Order(exp(1/x)) + assert Order(x**3) + Order(exp(2/x)) == Order(exp(2/x)) + assert Order(x**-3) + Order(exp(2/x)) == Order(exp(2/x)) + + +def test_simple_7(): + assert 1 + O(1) == O(1) + assert 2 + O(1) == O(1) + assert x + O(1) == O(1) + assert 1/x + O(1) == 1/x + O(1) + + +def test_simple_8(): + assert O(sqrt(-x)) == O(sqrt(x)) + assert O(x**2*sqrt(x)) == O(x**Rational(5, 2)) + assert O(x**3*sqrt(-(-x)**3)) == O(x**Rational(9, 2)) + assert O(x**Rational(3, 2)*sqrt((-x)**3)) == O(x**3) + assert O(x*(-2*x)**(I/2)) == O(x*(-x)**(I/2)) + + +def test_as_expr_variables(): + assert Order(x).as_expr_variables(None) == (x, ((x, 0),)) + assert Order(x).as_expr_variables(((x, 0),)) == (x, ((x, 0),)) + assert Order(y).as_expr_variables(((x, 0),)) == (y, ((x, 0), (y, 0))) + assert Order(y).as_expr_variables(((x, 0), (y, 0))) == (y, ((x, 0), (y, 0))) + + +def test_contains_0(): + assert Order(1, x).contains(Order(1, x)) + assert Order(1, x).contains(Order(1)) + assert Order(1).contains(Order(1, x)) is False + + +def test_contains_1(): + assert Order(x).contains(Order(x)) + assert Order(x).contains(Order(x**2)) + assert not Order(x**2).contains(Order(x)) + assert not Order(x).contains(Order(1/x)) + assert not Order(1/x).contains(Order(exp(1/x))) + assert not Order(x).contains(Order(exp(1/x))) + assert Order(1/x).contains(Order(x)) + assert Order(exp(1/x)).contains(Order(x)) + assert Order(exp(1/x)).contains(Order(1/x)) + assert Order(exp(1/x)).contains(Order(exp(1/x))) + assert Order(exp(2/x)).contains(Order(exp(1/x))) + assert not Order(exp(1/x)).contains(Order(exp(2/x))) + + +def test_contains_2(): + assert Order(x).contains(Order(y)) is None + assert Order(x).contains(Order(y*x)) + assert Order(y*x).contains(Order(x)) + assert Order(y).contains(Order(x*y)) + assert Order(x).contains(Order(y**2*x)) + + +def test_contains_3(): + assert Order(x*y**2).contains(Order(x**2*y)) is None + assert Order(x**2*y).contains(Order(x*y**2)) is None + + +def test_contains_4(): + assert Order(sin(1/x**2)).contains(Order(cos(1/x**2))) is True + assert Order(cos(1/x**2)).contains(Order(sin(1/x**2))) is True + + +def test_contains(): + assert Order(1, x) not in Order(1) + assert Order(1) in Order(1, x) + raises(TypeError, lambda: Order(x*y**2) in Order(x**2*y)) + + +def test_add_1(): + assert Order(x + x) == Order(x) + assert Order(3*x - 2*x**2) == Order(x) + assert Order(1 + x) == Order(1, x) + assert Order(1 + 1/x) == Order(1/x) + # TODO : A better output for Order(log(x) + 1/log(x)) + # could be Order(log(x)). Currently Order for expressions + # where all arguments would involve a log term would fall + # in this category and outputs for these should be improved. + assert Order(log(x) + 1/log(x)) == Order((log(x)**2 + 1)/log(x)) + assert Order(exp(1/x) + x) == Order(exp(1/x)) + assert Order(exp(1/x) + 1/x**20) == Order(exp(1/x)) + + +def test_ln_args(): + assert O(log(x)) + O(log(2*x)) == O(log(x)) + assert O(log(x)) + O(log(x**3)) == O(log(x)) + assert O(log(x*y)) + O(log(x) + log(y)) == O(log(x) + log(y), x, y) + + +def test_multivar_0(): + assert Order(x*y).expr == x*y + assert Order(x*y**2).expr == x*y**2 + assert Order(x*y, x).expr == x + assert Order(x*y**2, y).expr == y**2 + assert Order(x*y*z).expr == x*y*z + assert Order(x/y).expr == x/y + assert Order(x*exp(1/y)).expr == x*exp(1/y) + assert Order(exp(x)*exp(1/y)).expr == exp(x)*exp(1/y) + + +def test_multivar_0a(): + assert Order(exp(1/x)*exp(1/y)).expr == exp(1/x)*exp(1/y) + + +def test_multivar_1(): + assert Order(x + y).expr == x + y + assert Order(x + 2*y).expr == x + y + assert (Order(x + y) + x).expr == (x + y) + assert (Order(x + y) + x**2) == Order(x + y) + assert (Order(x + y) + 1/x) == 1/x + Order(x + y) + assert Order(x**2 + y*x).expr == x**2 + y*x + + +def test_multivar_2(): + assert Order(x**2*y + y**2*x, x, y).expr == x**2*y + y**2*x + + +def test_multivar_mul_1(): + assert Order(x + y)*x == Order(x**2 + y*x, x, y) + + +def test_multivar_3(): + assert (Order(x) + Order(y)).args in [ + (Order(x), Order(y)), + (Order(y), Order(x))] + assert Order(x) + Order(y) + Order(x + y) == Order(x + y) + assert (Order(x**2*y) + Order(y**2*x)).args in [ + (Order(x*y**2), Order(y*x**2)), + (Order(y*x**2), Order(x*y**2))] + assert (Order(x**2*y) + Order(y*x)) == Order(x*y) + + +def test_issue_3468(): + y = Symbol('y', negative=True) + z = Symbol('z', complex=True) + + # check that Order does not modify assumptions about symbols + Order(x) + Order(y) + Order(z) + + assert x.is_positive is None + assert y.is_positive is False + assert z.is_positive is None + + +def test_leading_order(): + assert (x + 1 + 1/x**5).extract_leading_order(x) == ((1/x**5, O(1/x**5)),) + assert (1 + 1/x).extract_leading_order(x) == ((1/x, O(1/x)),) + assert (1 + x).extract_leading_order(x) == ((1, O(1, x)),) + assert (1 + x**2).extract_leading_order(x) == ((1, O(1, x)),) + assert (2 + x**2).extract_leading_order(x) == ((2, O(1, x)),) + assert (x + x**2).extract_leading_order(x) == ((x, O(x)),) + + +def test_leading_order2(): + assert set((2 + pi + x**2).extract_leading_order(x)) == {(pi, O(1, x)), + (S(2), O(1, x))} + assert set((2*x + pi*x + x**2).extract_leading_order(x)) == {(2*x, O(x)), + (x*pi, O(x))} + + +def test_order_leadterm(): + assert O(x**2)._eval_as_leading_term(x) == O(x**2) + + +def test_order_symbols(): + e = x*y*sin(x)*Integral(x, (x, 1, 2)) + assert O(e) == O(x**2*y, x, y) + assert O(e, x) == O(x**2) + + +def test_nan(): + assert O(nan) is nan + assert not O(x).contains(nan) + + +def test_O1(): + assert O(1, x) * x == O(x) + assert O(1, y) * x == O(1, y) + + +def test_getn(): + # other lines are tested incidentally by the suite + assert O(x).getn() == 1 + assert O(x/log(x)).getn() == 1 + assert O(x**2/log(x)**2).getn() == 2 + assert O(x*log(x)).getn() == 1 + raises(NotImplementedError, lambda: (O(x) + O(y)).getn()) + + +def test_diff(): + assert O(x**2).diff(x) == O(x) + + +def test_getO(): + assert (x).getO() is None + assert (x).removeO() == x + assert (O(x)).getO() == O(x) + assert (O(x)).removeO() == 0 + assert (z + O(x) + O(y)).getO() == O(x) + O(y) + assert (z + O(x) + O(y)).removeO() == z + raises(NotImplementedError, lambda: (O(x) + O(y)).getn()) + + +def test_leading_term(): + from sympy.functions.special.gamma_functions import digamma + assert O(1/digamma(1/x)) == O(1/log(x)) + + +def test_eval(): + assert Order(x).subs(Order(x), 1) == 1 + assert Order(x).subs(x, y) == Order(y) + assert Order(x).subs(y, x) == Order(x) + assert Order(x).subs(x, x + y) == Order(x + y, (x, -y)) + assert (O(1)**x).is_Pow + + +def test_issue_4279(): + a, b = symbols('a b') + assert O(a, a, b) + O(1, a, b) == O(1, a, b) + assert O(b, a, b) + O(1, a, b) == O(1, a, b) + assert O(a + b, a, b) + O(1, a, b) == O(1, a, b) + assert O(1, a, b) + O(a, a, b) == O(1, a, b) + assert O(1, a, b) + O(b, a, b) == O(1, a, b) + assert O(1, a, b) + O(a + b, a, b) == O(1, a, b) + + +def test_issue_4855(): + assert 1/O(1) != O(1) + assert 1/O(x) != O(1/x) + assert 1/O(x, (x, oo)) != O(1/x, (x, oo)) + + f = Function('f') + assert 1/O(f(x)) != O(1/x) + + +def test_order_conjugate_transpose(): + x = Symbol('x', real=True) + y = Symbol('y', imaginary=True) + assert conjugate(Order(x)) == Order(conjugate(x)) + assert conjugate(Order(y)) == Order(conjugate(y)) + assert conjugate(Order(x**2)) == Order(conjugate(x)**2) + assert conjugate(Order(y**2)) == Order(conjugate(y)**2) + assert transpose(Order(x)) == Order(transpose(x)) + assert transpose(Order(y)) == Order(transpose(y)) + assert transpose(Order(x**2)) == Order(transpose(x)**2) + assert transpose(Order(y**2)) == Order(transpose(y)**2) + + +def test_order_noncommutative(): + A = Symbol('A', commutative=False) + assert Order(A + A*x, x) == Order(1, x) + assert (A + A*x)*Order(x) == Order(x) + assert (A*x)*Order(x) == Order(x**2, x) + assert expand((1 + Order(x))*A*A*x) == A*A*x + Order(x**2, x) + assert expand((A*A + Order(x))*x) == A*A*x + Order(x**2, x) + assert expand((A + Order(x))*A*x) == A*A*x + Order(x**2, x) + + +def test_issue_6753(): + assert (1 + x**2)**10000*O(x) == O(x) + + +def test_order_at_infinity(): + assert Order(1 + x, (x, oo)) == Order(x, (x, oo)) + assert Order(3*x, (x, oo)) == Order(x, (x, oo)) + assert Order(x, (x, oo))*3 == Order(x, (x, oo)) + assert -28*Order(x, (x, oo)) == Order(x, (x, oo)) + assert Order(Order(x, (x, oo)), (x, oo)) == Order(x, (x, oo)) + assert Order(Order(x, (x, oo)), (y, oo)) == Order(x, (x, oo), (y, oo)) + assert Order(3, (x, oo)) == Order(1, (x, oo)) + assert Order(x**2 + x + y, (x, oo)) == O(x**2, (x, oo)) + assert Order(x**2 + x + y, (y, oo)) == O(y, (y, oo)) + + assert Order(2*x, (x, oo))*x == Order(x**2, (x, oo)) + assert Order(2*x, (x, oo))/x == Order(1, (x, oo)) + assert Order(2*x, (x, oo))*x*exp(1/x) == Order(x**2*exp(1/x), (x, oo)) + assert Order(2*x, (x, oo))*x*exp(1/x)/log(x)**3 == Order(x**2*exp(1/x)*log(x)**-3, (x, oo)) + + assert Order(x, (x, oo)) + 1/x == 1/x + Order(x, (x, oo)) == Order(x, (x, oo)) + assert Order(x, (x, oo)) + 1 == 1 + Order(x, (x, oo)) == Order(x, (x, oo)) + assert Order(x, (x, oo)) + x == x + Order(x, (x, oo)) == Order(x, (x, oo)) + assert Order(x, (x, oo)) + x**2 == x**2 + Order(x, (x, oo)) + assert Order(1/x, (x, oo)) + 1/x**2 == 1/x**2 + Order(1/x, (x, oo)) == Order(1/x, (x, oo)) + assert Order(x, (x, oo)) + exp(1/x) == exp(1/x) + Order(x, (x, oo)) + + assert Order(x, (x, oo))**2 == Order(x**2, (x, oo)) + + assert Order(x, (x, oo)) + Order(x**2, (x, oo)) == Order(x**2, (x, oo)) + assert Order(x, (x, oo)) + Order(x**-2, (x, oo)) == Order(x, (x, oo)) + assert Order(x, (x, oo)) + Order(1/x, (x, oo)) == Order(x, (x, oo)) + + assert Order(x, (x, oo)) - Order(x, (x, oo)) == Order(x, (x, oo)) + assert Order(x, (x, oo)) + Order(1, (x, oo)) == Order(x, (x, oo)) + assert Order(x, (x, oo)) + Order(x**2, (x, oo)) == Order(x**2, (x, oo)) + assert Order(1/x, (x, oo)) + Order(1, (x, oo)) == Order(1, (x, oo)) + assert Order(x, (x, oo)) + Order(exp(1/x), (x, oo)) == Order(x, (x, oo)) + assert Order(x**3, (x, oo)) + Order(exp(2/x), (x, oo)) == Order(x**3, (x, oo)) + assert Order(x**-3, (x, oo)) + Order(exp(2/x), (x, oo)) == Order(exp(2/x), (x, oo)) + + # issue 7207 + assert Order(exp(x), (x, oo)).expr == Order(2*exp(x), (x, oo)).expr == exp(x) + assert Order(y**x, (x, oo)).expr == Order(2*y**x, (x, oo)).expr == exp(x*log(y)) + + # issue 19545 + assert Order(1/x - 3/(3*x + 2), (x, oo)).expr == x**(-2) + +def test_mixing_order_at_zero_and_infinity(): + assert (Order(x, (x, 0)) + Order(x, (x, oo))).is_Add + assert Order(x, (x, 0)) + Order(x, (x, oo)) == Order(x, (x, oo)) + Order(x, (x, 0)) + assert Order(Order(x, (x, oo))) == Order(x, (x, oo)) + + # not supported (yet) + raises(NotImplementedError, lambda: Order(x, (x, 0))*Order(x, (x, oo))) + raises(NotImplementedError, lambda: Order(x, (x, oo))*Order(x, (x, 0))) + raises(NotImplementedError, lambda: Order(Order(x, (x, oo)), y)) + raises(NotImplementedError, lambda: Order(Order(x), (x, oo))) + + +def test_order_at_some_point(): + assert Order(x, (x, 1)) == Order(1, (x, 1)) + assert Order(2*x - 2, (x, 1)) == Order(x - 1, (x, 1)) + assert Order(-x + 1, (x, 1)) == Order(x - 1, (x, 1)) + assert Order(x - 1, (x, 1))**2 == Order((x - 1)**2, (x, 1)) + assert Order(x - 2, (x, 2)) - O(x - 2, (x, 2)) == Order(x - 2, (x, 2)) + + +def test_order_subs_limits(): + # issue 3333 + assert (1 + Order(x)).subs(x, 1/x) == 1 + Order(1/x, (x, oo)) + assert (1 + Order(x)).limit(x, 0) == 1 + # issue 5769 + assert ((x + Order(x**2))/x).limit(x, 0) == 1 + + assert Order(x**2).subs(x, y - 1) == Order((y - 1)**2, (y, 1)) + assert Order(10*x**2, (x, 2)).subs(x, y - 1) == Order(1, (y, 3)) + + +def test_issue_9351(): + assert exp(x).series(x, 10, 1) == exp(10) + Order(x - 10, (x, 10)) + + +def test_issue_9192(): + assert O(1)*O(1) == O(1) + assert O(1)**O(1) == O(1) + + +def test_issue_9910(): + assert O(x*log(x) + sin(x), (x, oo)) == O(x*log(x), (x, oo)) + + +def test_performance_of_adding_order(): + l = [x**i for i in range(1000)] + l.append(O(x**1001)) + assert Add(*l).subs(x,1) == O(1) + +def test_issue_14622(): + assert (x**(-4) + x**(-3) + x**(-1) + O(x**(-6), (x, oo))).as_numer_denom() == ( + x**4 + x**5 + x**7 + O(x**2, (x, oo)), x**8) + assert (x**3 + O(x**2, (x, oo))).is_Add + assert O(x**2, (x, oo)).contains(x**3) is False + assert O(x, (x, oo)).contains(O(x, (x, 0))) is None + assert O(x, (x, 0)).contains(O(x, (x, oo))) is None + raises(NotImplementedError, lambda: O(x**3).contains(x**w)) + + +def test_issue_15539(): + assert O(1/x**2 + 1/x**4, (x, -oo)) == O(1/x**2, (x, -oo)) + assert O(1/x**4 + exp(x), (x, -oo)) == O(1/x**4, (x, -oo)) + assert O(1/x**4 + exp(-x), (x, -oo)) == O(exp(-x), (x, -oo)) + assert O(1/x, (x, oo)).subs(x, -x) == O(-1/x, (x, -oo)) + +def test_issue_18606(): + assert unchanged(Order, 0) + + +def test_issue_22165(): + assert O(log(x)).contains(2) + + +def test_issue_23231(): + # This test checks Order for expressions having + # arguments containing variables in exponents/powers. + assert O(x**x + 2**x, (x, oo)) == O(exp(x*log(x)), (x, oo)) + assert O(x**x + x**2, (x, oo)) == O(exp(x*log(x)), (x, oo)) + assert O(x**x + 1/x**2, (x, oo)) == O(exp(x*log(x)), (x, oo)) + assert O(2**x + 3**x , (x, oo)) == O(exp(x*log(3)), (x, oo)) + + +def test_issue_9917(): + assert O(x*sin(x) + 1, (x, oo)) == O(x, (x, oo)) diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_residues.py b/lib/python3.12/site-packages/sympy/series/tests/test_residues.py new file mode 100644 index 0000000000000000000000000000000000000000..9f7d075a56500d008e3c8b46c1fda5db890fd76a --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_residues.py @@ -0,0 +1,101 @@ +from sympy.core.function import Function +from sympy.core.numbers import (I, Rational, pi) +from sympy.core.singleton import S +from sympy.core.symbol import Symbol +from sympy.functions.combinatorial.factorials import factorial +from sympy.functions.elementary.exponential import (exp, log) +from sympy.functions.elementary.hyperbolic import tanh +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import (cot, sin, tan) +from sympy.series.residues import residue +from sympy.testing.pytest import XFAIL, raises +from sympy.abc import x, z, a, s, k + + +def test_basic1(): + assert residue(1/x, x, 0) == 1 + assert residue(-2/x, x, 0) == -2 + assert residue(81/x, x, 0) == 81 + assert residue(1/x**2, x, 0) == 0 + assert residue(0, x, 0) == 0 + assert residue(5, x, 0) == 0 + assert residue(x, x, 0) == 0 + assert residue(x**2, x, 0) == 0 + + +def test_basic2(): + assert residue(1/x, x, 1) == 0 + assert residue(-2/x, x, 1) == 0 + assert residue(81/x, x, -1) == 0 + assert residue(1/x**2, x, 1) == 0 + assert residue(0, x, 1) == 0 + assert residue(5, x, 1) == 0 + assert residue(x, x, 1) == 0 + assert residue(x**2, x, 5) == 0 + + +def test_f(): + f = Function("f") + assert residue(f(x)/x**5, x, 0) == f(x).diff(x, 4).subs(x, 0)/24 + + +def test_functions(): + assert residue(1/sin(x), x, 0) == 1 + assert residue(2/sin(x), x, 0) == 2 + assert residue(1/sin(x)**2, x, 0) == 0 + assert residue(1/sin(x)**5, x, 0) == Rational(3, 8) + + +def test_expressions(): + assert residue(1/(x + 1), x, 0) == 0 + assert residue(1/(x + 1), x, -1) == 1 + assert residue(1/(x**2 + 1), x, -1) == 0 + assert residue(1/(x**2 + 1), x, I) == -I/2 + assert residue(1/(x**2 + 1), x, -I) == I/2 + assert residue(1/(x**4 + 1), x, 0) == 0 + assert residue(1/(x**4 + 1), x, exp(I*pi/4)).equals(-(Rational(1, 4) + I/4)/sqrt(2)) + assert residue(1/(x**2 + a**2)**2, x, a*I) == -I/4/a**3 + + +@XFAIL +def test_expressions_failing(): + n = Symbol('n', integer=True, positive=True) + assert residue(exp(z)/(z - pi*I/4*a)**n, z, I*pi*a) == \ + exp(I*pi*a/4)/factorial(n - 1) + + +def test_NotImplemented(): + raises(NotImplementedError, lambda: residue(exp(1/z), z, 0)) + + +def test_bug(): + assert residue(2**(z)*(s + z)*(1 - s - z)/z**2, z, 0) == \ + 1 + s*log(2) - s**2*log(2) - 2*s + + +def test_issue_5654(): + assert residue(1/(x**2 + a**2)**2, x, a*I) == -I/(4*a**3) + assert residue(1/s*1/(z - exp(s)), s, 0) == 1/(z - 1) + assert residue((1 + k)/s*1/(z - exp(s)), s, 0) == k/(z - 1) + 1/(z - 1) + + +def test_issue_6499(): + assert residue(1/(exp(z) - 1), z, 0) == 1 + + +def test_issue_14037(): + assert residue(sin(x**50)/x**51, x, 0) == 1 + + +def test_issue_21176(): + f = x**2*cot(pi*x)/(x**4 + 1) + assert residue(f, x, -sqrt(2)/2 - sqrt(2)*I/2).cancel().together(deep=True)\ + == sqrt(2)*(1 - I)/(8*tan(sqrt(2)*pi*(1 + I)/2)) + + +def test_issue_21177(): + r = -sqrt(3)*tanh(sqrt(3)*pi/2)/3 + a = residue(cot(pi*x)/((x - 1)*(x - 2) + 1), x, S(3)/2 - sqrt(3)*I/2) + b = residue(cot(pi*x)/(x**2 - 3*x + 3), x, S(3)/2 - sqrt(3)*I/2) + assert a == r + assert (b - a).cancel() == 0 diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_sequences.py b/lib/python3.12/site-packages/sympy/series/tests/test_sequences.py new file mode 100644 index 0000000000000000000000000000000000000000..61e276ad67982f0a9877de3548d70238976d28a5 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_sequences.py @@ -0,0 +1,312 @@ +from sympy.core.containers import Tuple +from sympy.core.function import Function +from sympy.core.numbers import oo, Rational +from sympy.core.singleton import S +from sympy.core.symbol import symbols, Symbol +from sympy.functions.combinatorial.numbers import tribonacci, fibonacci +from sympy.functions.elementary.exponential import exp +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import cos, sin +from sympy.series import EmptySequence +from sympy.series.sequences import (SeqMul, SeqAdd, SeqPer, SeqFormula, + sequence) +from sympy.sets.sets import Interval +from sympy.tensor.indexed import Indexed, Idx +from sympy.series.sequences import SeqExpr, SeqExprOp, RecursiveSeq +from sympy.testing.pytest import raises, slow + +x, y, z = symbols('x y z') +n, m = symbols('n m') + + +def test_EmptySequence(): + assert S.EmptySequence is EmptySequence + + assert S.EmptySequence.interval is S.EmptySet + assert S.EmptySequence.length is S.Zero + + assert list(S.EmptySequence) == [] + + +def test_SeqExpr(): + #SeqExpr is a baseclass and does not take care of + #ensuring all arguments are Basics hence the use of + #Tuple(...) here. + s = SeqExpr(Tuple(1, n, y), Tuple(x, 0, 10)) + + assert isinstance(s, SeqExpr) + assert s.gen == (1, n, y) + assert s.interval == Interval(0, 10) + assert s.start == 0 + assert s.stop == 10 + assert s.length == 11 + assert s.variables == (x,) + + assert SeqExpr(Tuple(1, 2, 3), Tuple(x, 0, oo)).length is oo + + +def test_SeqPer(): + s = SeqPer((1, n, 3), (x, 0, 5)) + + assert isinstance(s, SeqPer) + assert s.periodical == Tuple(1, n, 3) + assert s.period == 3 + assert s.coeff(3) == 1 + assert s.free_symbols == {n} + + assert list(s) == [1, n, 3, 1, n, 3] + assert s[:] == [1, n, 3, 1, n, 3] + assert SeqPer((1, n, 3), (x, -oo, 0))[0:6] == [1, n, 3, 1, n, 3] + + raises(ValueError, lambda: SeqPer((1, 2, 3), (0, 1, 2))) + raises(ValueError, lambda: SeqPer((1, 2, 3), (x, -oo, oo))) + raises(ValueError, lambda: SeqPer(n**2, (0, oo))) + + assert SeqPer((n, n**2, n**3), (m, 0, oo))[:6] == \ + [n, n**2, n**3, n, n**2, n**3] + assert SeqPer((n, n**2, n**3), (n, 0, oo))[:6] == [0, 1, 8, 3, 16, 125] + assert SeqPer((n, m), (n, 0, oo))[:6] == [0, m, 2, m, 4, m] + + +def test_SeqFormula(): + s = SeqFormula(n**2, (n, 0, 5)) + + assert isinstance(s, SeqFormula) + assert s.formula == n**2 + assert s.coeff(3) == 9 + + assert list(s) == [i**2 for i in range(6)] + assert s[:] == [i**2 for i in range(6)] + assert SeqFormula(n**2, (n, -oo, 0))[0:6] == [i**2 for i in range(6)] + + assert SeqFormula(n**2, (0, oo)) == SeqFormula(n**2, (n, 0, oo)) + + assert SeqFormula(n**2, (0, m)).subs(m, x) == SeqFormula(n**2, (0, x)) + assert SeqFormula(m*n**2, (n, 0, oo)).subs(m, x) == \ + SeqFormula(x*n**2, (n, 0, oo)) + + raises(ValueError, lambda: SeqFormula(n**2, (0, 1, 2))) + raises(ValueError, lambda: SeqFormula(n**2, (n, -oo, oo))) + raises(ValueError, lambda: SeqFormula(m*n**2, (0, oo))) + + seq = SeqFormula(x*(y**2 + z), (z, 1, 100)) + assert seq.expand() == SeqFormula(x*y**2 + x*z, (z, 1, 100)) + seq = SeqFormula(sin(x*(y**2 + z)),(z, 1, 100)) + assert seq.expand(trig=True) == SeqFormula(sin(x*y**2)*cos(x*z) + sin(x*z)*cos(x*y**2), (z, 1, 100)) + assert seq.expand() == SeqFormula(sin(x*y**2 + x*z), (z, 1, 100)) + assert seq.expand(trig=False) == SeqFormula(sin(x*y**2 + x*z), (z, 1, 100)) + seq = SeqFormula(exp(x*(y**2 + z)), (z, 1, 100)) + assert seq.expand() == SeqFormula(exp(x*y**2)*exp(x*z), (z, 1, 100)) + assert seq.expand(power_exp=False) == SeqFormula(exp(x*y**2 + x*z), (z, 1, 100)) + assert seq.expand(mul=False, power_exp=False) == SeqFormula(exp(x*(y**2 + z)), (z, 1, 100)) + +def test_sequence(): + form = SeqFormula(n**2, (n, 0, 5)) + per = SeqPer((1, 2, 3), (n, 0, 5)) + inter = SeqFormula(n**2) + + assert sequence(n**2, (n, 0, 5)) == form + assert sequence((1, 2, 3), (n, 0, 5)) == per + assert sequence(n**2) == inter + + +def test_SeqExprOp(): + form = SeqFormula(n**2, (n, 0, 10)) + per = SeqPer((1, 2, 3), (m, 5, 10)) + + s = SeqExprOp(form, per) + assert s.gen == (n**2, (1, 2, 3)) + assert s.interval == Interval(5, 10) + assert s.start == 5 + assert s.stop == 10 + assert s.length == 6 + assert s.variables == (n, m) + + +def test_SeqAdd(): + per = SeqPer((1, 2, 3), (n, 0, oo)) + form = SeqFormula(n**2) + + per_bou = SeqPer((1, 2), (n, 1, 5)) + form_bou = SeqFormula(n**2, (6, 10)) + form_bou2 = SeqFormula(n**2, (1, 5)) + + assert SeqAdd() == S.EmptySequence + assert SeqAdd(S.EmptySequence) == S.EmptySequence + assert SeqAdd(per) == per + assert SeqAdd(per, S.EmptySequence) == per + assert SeqAdd(per_bou, form_bou) == S.EmptySequence + + s = SeqAdd(per_bou, form_bou2, evaluate=False) + assert s.args == (form_bou2, per_bou) + assert s[:] == [2, 6, 10, 18, 26] + assert list(s) == [2, 6, 10, 18, 26] + + assert isinstance(SeqAdd(per, per_bou, evaluate=False), SeqAdd) + + s1 = SeqAdd(per, per_bou) + assert isinstance(s1, SeqPer) + assert s1 == SeqPer((2, 4, 4, 3, 3, 5), (n, 1, 5)) + s2 = SeqAdd(form, form_bou) + assert isinstance(s2, SeqFormula) + assert s2 == SeqFormula(2*n**2, (6, 10)) + + assert SeqAdd(form, form_bou, per) == \ + SeqAdd(per, SeqFormula(2*n**2, (6, 10))) + assert SeqAdd(form, SeqAdd(form_bou, per)) == \ + SeqAdd(per, SeqFormula(2*n**2, (6, 10))) + assert SeqAdd(per, SeqAdd(form, form_bou), evaluate=False) == \ + SeqAdd(per, SeqFormula(2*n**2, (6, 10))) + + assert SeqAdd(SeqPer((1, 2), (n, 0, oo)), SeqPer((1, 2), (m, 0, oo))) == \ + SeqPer((2, 4), (n, 0, oo)) + + +def test_SeqMul(): + per = SeqPer((1, 2, 3), (n, 0, oo)) + form = SeqFormula(n**2) + + per_bou = SeqPer((1, 2), (n, 1, 5)) + form_bou = SeqFormula(n**2, (n, 6, 10)) + form_bou2 = SeqFormula(n**2, (1, 5)) + + assert SeqMul() == S.EmptySequence + assert SeqMul(S.EmptySequence) == S.EmptySequence + assert SeqMul(per) == per + assert SeqMul(per, S.EmptySequence) == S.EmptySequence + assert SeqMul(per_bou, form_bou) == S.EmptySequence + + s = SeqMul(per_bou, form_bou2, evaluate=False) + assert s.args == (form_bou2, per_bou) + assert s[:] == [1, 8, 9, 32, 25] + assert list(s) == [1, 8, 9, 32, 25] + + assert isinstance(SeqMul(per, per_bou, evaluate=False), SeqMul) + + s1 = SeqMul(per, per_bou) + assert isinstance(s1, SeqPer) + assert s1 == SeqPer((1, 4, 3, 2, 2, 6), (n, 1, 5)) + s2 = SeqMul(form, form_bou) + assert isinstance(s2, SeqFormula) + assert s2 == SeqFormula(n**4, (6, 10)) + + assert SeqMul(form, form_bou, per) == \ + SeqMul(per, SeqFormula(n**4, (6, 10))) + assert SeqMul(form, SeqMul(form_bou, per)) == \ + SeqMul(per, SeqFormula(n**4, (6, 10))) + assert SeqMul(per, SeqMul(form, form_bou2, + evaluate=False), evaluate=False) == \ + SeqMul(form, per, form_bou2, evaluate=False) + + assert SeqMul(SeqPer((1, 2), (n, 0, oo)), SeqPer((1, 2), (n, 0, oo))) == \ + SeqPer((1, 4), (n, 0, oo)) + + +def test_add(): + per = SeqPer((1, 2), (n, 0, oo)) + form = SeqFormula(n**2) + + assert per + (SeqPer((2, 3))) == SeqPer((3, 5), (n, 0, oo)) + assert form + SeqFormula(n**3) == SeqFormula(n**2 + n**3) + + assert per + form == SeqAdd(per, form) + + raises(TypeError, lambda: per + n) + raises(TypeError, lambda: n + per) + + +def test_sub(): + per = SeqPer((1, 2), (n, 0, oo)) + form = SeqFormula(n**2) + + assert per - (SeqPer((2, 3))) == SeqPer((-1, -1), (n, 0, oo)) + assert form - (SeqFormula(n**3)) == SeqFormula(n**2 - n**3) + + assert per - form == SeqAdd(per, -form) + + raises(TypeError, lambda: per - n) + raises(TypeError, lambda: n - per) + + +def test_mul__coeff_mul(): + assert SeqPer((1, 2), (n, 0, oo)).coeff_mul(2) == SeqPer((2, 4), (n, 0, oo)) + assert SeqFormula(n**2).coeff_mul(2) == SeqFormula(2*n**2) + assert S.EmptySequence.coeff_mul(100) == S.EmptySequence + + assert SeqPer((1, 2), (n, 0, oo)) * (SeqPer((2, 3))) == \ + SeqPer((2, 6), (n, 0, oo)) + assert SeqFormula(n**2) * SeqFormula(n**3) == SeqFormula(n**5) + + assert S.EmptySequence * SeqFormula(n**2) == S.EmptySequence + assert SeqFormula(n**2) * S.EmptySequence == S.EmptySequence + + raises(TypeError, lambda: sequence(n**2) * n) + raises(TypeError, lambda: n * sequence(n**2)) + + +def test_neg(): + assert -SeqPer((1, -2), (n, 0, oo)) == SeqPer((-1, 2), (n, 0, oo)) + assert -SeqFormula(n**2) == SeqFormula(-n**2) + + +def test_operations(): + per = SeqPer((1, 2), (n, 0, oo)) + per2 = SeqPer((2, 4), (n, 0, oo)) + form = SeqFormula(n**2) + form2 = SeqFormula(n**3) + + assert per + form + form2 == SeqAdd(per, form, form2) + assert per + form - form2 == SeqAdd(per, form, -form2) + assert per + form - S.EmptySequence == SeqAdd(per, form) + assert per + per2 + form == SeqAdd(SeqPer((3, 6), (n, 0, oo)), form) + assert S.EmptySequence - per == -per + assert form + form == SeqFormula(2*n**2) + + assert per * form * form2 == SeqMul(per, form, form2) + assert form * form == SeqFormula(n**4) + assert form * -form == SeqFormula(-n**4) + + assert form * (per + form2) == SeqMul(form, SeqAdd(per, form2)) + assert form * (per + per) == SeqMul(form, per2) + + assert form.coeff_mul(m) == SeqFormula(m*n**2, (n, 0, oo)) + assert per.coeff_mul(m) == SeqPer((m, 2*m), (n, 0, oo)) + + +def test_Idx_limits(): + i = symbols('i', cls=Idx) + r = Indexed('r', i) + + assert SeqFormula(r, (i, 0, 5))[:] == [r.subs(i, j) for j in range(6)] + assert SeqPer((1, 2), (i, 0, 5))[:] == [1, 2, 1, 2, 1, 2] + + +@slow +def test_find_linear_recurrence(): + assert sequence((0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55), \ + (n, 0, 10)).find_linear_recurrence(11) == [1, 1] + assert sequence((1, 2, 4, 7, 28, 128, 582, 2745, 13021, 61699, 292521, \ + 1387138), (n, 0, 11)).find_linear_recurrence(12) == [5, -2, 6, -11] + assert sequence(x*n**3+y*n, (n, 0, oo)).find_linear_recurrence(10) \ + == [4, -6, 4, -1] + assert sequence(x**n, (n,0,20)).find_linear_recurrence(21) == [x] + assert sequence((1,2,3)).find_linear_recurrence(10, 5) == [0, 0, 1] + assert sequence(((1 + sqrt(5))/2)**n + \ + (-(1 + sqrt(5))/2)**(-n)).find_linear_recurrence(10) == [1, 1] + assert sequence(x*((1 + sqrt(5))/2)**n + y*(-(1 + sqrt(5))/2)**(-n), \ + (n,0,oo)).find_linear_recurrence(10) == [1, 1] + assert sequence((1,2,3,4,6),(n, 0, 4)).find_linear_recurrence(5) == [] + assert sequence((2,3,4,5,6,79),(n, 0, 5)).find_linear_recurrence(6,gfvar=x) \ + == ([], None) + assert sequence((2,3,4,5,8,30),(n, 0, 5)).find_linear_recurrence(6,gfvar=x) \ + == ([Rational(19, 2), -20, Rational(27, 2)], (-31*x**2 + 32*x - 4)/(27*x**3 - 40*x**2 + 19*x -2)) + assert sequence(fibonacci(n)).find_linear_recurrence(30,gfvar=x) \ + == ([1, 1], -x/(x**2 + x - 1)) + assert sequence(tribonacci(n)).find_linear_recurrence(30,gfvar=x) \ + == ([1, 1, 1], -x/(x**3 + x**2 + x - 1)) + +def test_RecursiveSeq(): + y = Function('y') + n = Symbol('n') + fib = RecursiveSeq(y(n - 1) + y(n - 2), y(n), n, [0, 1]) + assert fib.coeff(3) == 2 diff --git a/lib/python3.12/site-packages/sympy/series/tests/test_series.py b/lib/python3.12/site-packages/sympy/series/tests/test_series.py new file mode 100644 index 0000000000000000000000000000000000000000..2adeef40f8a2864862590f4bc172bc76f3b83e65 --- /dev/null +++ b/lib/python3.12/site-packages/sympy/series/tests/test_series.py @@ -0,0 +1,404 @@ +from sympy.core.evalf import N +from sympy.core.function import (Derivative, Function, PoleError, Subs) +from sympy.core.numbers import (E, Float, Rational, oo, pi, I) +from sympy.core.singleton import S +from sympy.core.symbol import (Symbol, symbols) +from sympy.functions.elementary.exponential import (LambertW, exp, log) +from sympy.functions.elementary.miscellaneous import sqrt +from sympy.functions.elementary.trigonometric import (atan, cos, sin) +from sympy.functions.special.gamma_functions import gamma +from sympy.integrals.integrals import Integral, integrate +from sympy.series.order import O +from sympy.series.series import series +from sympy.abc import x, y, n, k +from sympy.testing.pytest import raises +from sympy.core import EulerGamma + + +def test_sin(): + e1 = sin(x).series(x, 0) + e2 = series(sin(x), x, 0) + assert e1 == e2 + + +def test_cos(): + e1 = cos(x).series(x, 0) + e2 = series(cos(x), x, 0) + assert e1 == e2 + + +def test_exp(): + e1 = exp(x).series(x, 0) + e2 = series(exp(x), x, 0) + assert e1 == e2 + + +def test_exp2(): + e1 = exp(cos(x)).series(x, 0) + e2 = series(exp(cos(x)), x, 0) + assert e1 == e2 + + +def test_issue_5223(): + assert series(1, x) == 1 + assert next(S.Zero.lseries(x)) == 0 + assert cos(x).series() == cos(x).series(x) + raises(ValueError, lambda: cos(x + y).series()) + raises(ValueError, lambda: x.series(dir="")) + + assert (cos(x).series(x, 1) - + cos(x + 1).series(x).subs(x, x - 1)).removeO() == 0 + e = cos(x).series(x, 1, n=None) + assert [next(e) for i in range(2)] == [cos(1), -((x - 1)*sin(1))] + e = cos(x).series(x, 1, n=None, dir='-') + assert [next(e) for i in range(2)] == [cos(1), (1 - x)*sin(1)] + # the following test is exact so no need for x -> x - 1 replacement + assert abs(x).series(x, 1, dir='-') == x + assert exp(x).series(x, 1, dir='-', n=3).removeO() == \ + E - E*(-x + 1) + E*(-x + 1)**2/2 + + D = Derivative + assert D(x**2 + x**3*y**2, x, 2, y, 1).series(x).doit() == 12*x*y + assert next(D(cos(x), x).lseries()) == D(1, x) + assert D( + exp(x), x).series(n=3) == D(1, x) + D(x, x) + D(x**2/2, x) + D(x**3/6, x) + O(x**3) + + assert Integral(x, (x, 1, 3), (y, 1, x)).series(x) == -4 + 4*x + + assert (1 + x + O(x**2)).getn() == 2 + assert (1 + x).getn() is None + + raises(PoleError, lambda: ((1/sin(x))**oo).series()) + logx = Symbol('logx') + assert ((sin(x))**y).nseries(x, n=1, logx=logx) == \ + exp(y*logx) + O(x*exp(y*logx), x) + + assert sin(1/x).series(x, oo, n=5) == 1/x - 1/(6*x**3) + O(x**(-5), (x, oo)) + assert abs(x).series(x, oo, n=5, dir='+') == x + assert abs(x).series(x, -oo, n=5, dir='-') == -x + assert abs(-x).series(x, oo, n=5, dir='+') == x + assert abs(-x).series(x, -oo, n=5, dir='-') == -x + + assert exp(x*log(x)).series(n=3) == \ + 1 + x*log(x) + x**2*log(x)**2/2 + O(x**3*log(x)**3) + # XXX is this right? If not, fix "ngot > n" handling in expr. + p = Symbol('p', positive=True) + assert exp(sqrt(p)**3*log(p)).series(n=3) == \ + 1 + p**S('3/2')*log(p) + O(p**3*log(p)**3) + + assert exp(sin(x)*log(x)).series(n=2) == 1 + x*log(x) + O(x**2*log(x)**2) + + +def test_issue_6350(): + expr = integrate(exp(k*(y**3 - 3*y)), (y, 0, oo), conds='none') + assert expr.series(k, 0, 3) == -(-1)**(S(2)/3)*sqrt(3)*gamma(S(1)/3)**2*gamma(S(2)/3)/(6*pi*k**(S(1)/3)) - \ + sqrt(3)*k*gamma(-S(2)/3)*gamma(-S(1)/3)/(6*pi) - \ + (-1)**(S(1)/3)*sqrt(3)*k**(S(1)/3)*gamma(-S(1)/3)*gamma(S(1)/3)*gamma(S(2)/3)/(6*pi) - \ + (-1)**(S(2)/3)*sqrt(3)*k**(S(5)/3)*gamma(S(1)/3)**2*gamma(S(2)/3)/(4*pi) - \ + (-1)**(S(1)/3)*sqrt(3)*k**(S(7)/3)*gamma(-S(1)/3)*gamma(S(1)/3)*gamma(S(2)/3)/(8*pi) + O(k**3) + + +def test_issue_11313(): + assert Integral(cos(x), x).series(x) == sin(x).series(x) + assert Derivative(sin(x), x).series(x, n=3).doit() == cos(x).series(x, n=3) + + assert Derivative(x**3, x).as_leading_term(x) == 3*x**2 + assert Derivative(x**3, y).as_leading_term(x) == 0 + assert Derivative(sin(x), x).as_leading_term(x) == 1 + assert Derivative(cos(x), x).as_leading_term(x) == -x + + # This result is equivalent to zero, zero is not return because + # `Expr.series` doesn't currently detect an `x` in its `free_symbol`s. + assert Derivative(1, x).as_leading_term(x) == Derivative(1, x) + + assert Derivative(exp(x), x).series(x).doit() == exp(x).series(x) + assert 1 + Integral(exp(x), x).series(x) == exp(x).series(x) + + assert Derivative(log(x), x).series(x).doit() == (1/x).series(x) + assert Integral(log(x), x).series(x) == Integral(log(x), x).doit().series(x).removeO() + + +def test_series_of_Subs(): + from sympy.abc import z + + subs1 = Subs(sin(x), x, y) + subs2 = Subs(sin(x) * cos(z), x, y) + subs3 = Subs(sin(x * z), (x, z), (y, x)) + + assert subs1.series(x) == subs1 + subs1_series = (Subs(x, x, y) + Subs(-x**3/6, x, y) + + Subs(x**5/120, x, y) + O(y**6)) + assert subs1.series() == subs1_series + assert subs1.series(y) == subs1_series + assert subs1.series(z) == subs1 + assert subs2.series(z) == (Subs(z**4*sin(x)/24, x, y) + + Subs(-z**2*sin(x)/2, x, y) + Subs(sin(x), x, y) + O(z**6)) + assert subs3.series(x).doit() == subs3.doit().series(x) + assert subs3.series(z).doit() == sin(x*y) + + raises(ValueError, lambda: Subs(x + 2*y, y, z).series()) + assert Subs(x + y, y, z).series(x).doit() == x + z + + +def test_issue_3978(): + f = Function('f') + assert f(x).series(x, 0, 3, dir='-') == \ + f(0) + x*Subs(Derivative(f(x), x), x, 0) + \ + x**2*Subs(Derivative(f(x), x, x), x, 0)/2 + O(x**3) + assert f(x).series(x, 0, 3) == \ + f(0) + x*Subs(Derivative(f(x), x), x, 0) + \ + x**2*Subs(Derivative(f(x), x, x), x, 0)/2 + O(x**3) + assert f(x**2).series(x, 0, 3) == \ + f(0) + x**2*Subs(Derivative(f(x), x), x, 0) + O(x**3) + assert f(x**2+1).series(x, 0, 3) == \ + f(1) + x**2*Subs(Derivative(f(x), x), x, 1) + O(x**3) + + class TestF(Function): + pass + + assert TestF(x).series(x, 0, 3) == TestF(0) + \ + x*Subs(Derivative(TestF(x), x), x, 0) + \ + x**2*Subs(Derivative(TestF(x), x, x), x, 0)/2 + O(x**3) + +from sympy.series.acceleration import richardson, shanks +from sympy.concrete.summations import Sum +from sympy.core.numbers import Integer + + +def test_acceleration(): + e = (1 + 1/n)**n + assert round(richardson(e, n, 10, 20).evalf(), 10) == round(E.evalf(), 10) + + A = Sum(Integer(-1)**(k + 1) / k, (k, 1, n)) + assert round(shanks(A, n, 25).evalf(), 4) == round(log(2).evalf(), 4) + assert round(shanks(A, n, 25, 5).evalf(), 10) == round(log(2).evalf(), 10) + + +def test_issue_5852(): + assert series(1/cos(x/log(x)), x, 0) == 1 + x**2/(2*log(x)**2) + \ + 5*x**4/(24*log(x)**4) + O(x**6) + + +def test_issue_4583(): + assert cos(1 + x + x**2).series(x, 0, 5) == cos(1) - x*sin(1) + \ + x**2*(-sin(1) - cos(1)/2) + x**3*(-cos(1) + sin(1)/6) + \ + x**4*(-11*cos(1)/24 + sin(1)/2) + O(x**5) + + +def test_issue_6318(): + eq = (1/x)**Rational(2, 3) + assert (eq + 1).as_leading_term(x) == eq + + +def test_x_is_base_detection(): + eq = (x**2)**Rational(2, 3) + assert eq.series() == x**Rational(4, 3) + + +def test_issue_7203(): + assert series(cos(x), x, pi, 3) == \ + -1 + (x - pi)**2/2 + O((x - pi)**3, (x, pi)) + + +def test_exp_product_positive_factors(): + a, b = symbols('a, b', positive=True) + x = a * b + assert series(exp(x), x, n=8) == 1 + a*b + a**2*b**2/2 + \ + a**3*b**3/6 + a**4*b**4/24 + a**5*b**5/120 + a**6*b**6/720 + \ + a**7*b**7/5040 + O(a**8*b**8, a, b) + + +def test_issue_8805(): + assert series(1, n=8) == 1 + + +def test_issue_9549(): + y = (x**2 + x + 1) / (x**3 + x**2) + assert series(y, x, oo) == x**(-5) - 1/x**4 + x**(-3) + 1/x + O(x**(-6), (x, oo)) + + +def test_issue_10761(): + assert series(1/(x**-2 + x**-3), x, 0) == x**3 - x**4 + x**5 + O(x**6) + + +def test_issue_12578(): + y = (1 - 1/(x/2 - 1/(2*x))**4)**(S(1)/8) + assert y.series(x, 0, n=17) == 1 - 2*x**4 - 8*x**6 - 34*x**8 - 152*x**10 - 714*x**12 - \ + 3472*x**14 - 17318*x**16 + O(x**17) + + +def test_issue_12791(): + beta = symbols('beta', positive=True) + theta, varphi = symbols('theta varphi', real=True) + + expr = (-beta**2*varphi*sin(theta) + beta**2*cos(theta) + \ + beta*varphi*sin(theta) - beta*cos(theta) - beta + 1)/(beta*cos(theta) - 1)**2 + + sol = (0.5/(0.5*cos(theta) - 1.0)**2 - 0.25*cos(theta)/(0.5*cos(theta) - 1.0)**2 + + (beta - 0.5)*(-0.25*varphi*sin(2*theta) - 1.5*cos(theta) + + 0.25*cos(2*theta) + 1.25)/((0.5*cos(theta) - 1.0)**2*(0.5*cos(theta) - 1.0)) + + 0.25*varphi*sin(theta)/(0.5*cos(theta) - 1.0)**2 + + O((beta - S.Half)**2, (beta, S.Half))) + + assert expr.series(beta, 0.5, 2).trigsimp() == sol + + +def test_issue_14384(): + x, a = symbols('x a') + assert series(x**a, x) == x**a + assert series(x**(-2*a), x) == x**(-2*a) + assert series(exp(a*log(x)), x) == exp(a*log(x)) + raises(PoleError, lambda: series(x**I, x)) + raises(PoleError, lambda: series(x**(I + 1), x)) + raises(PoleError, lambda: series(exp(I*log(x)), x)) + + +def test_issue_14885(): + assert series(x**Rational(-3, 2)*exp(x), x, 0) == (x**Rational(-3, 2) + 1/sqrt(x) + + sqrt(x)/2 + x**Rational(3, 2)/6 + x**Rational(5, 2)/24 + x**Rational(7, 2)/120 + + x**Rational(9, 2)/720 + x**Rational(11, 2)/5040 + O(x**6)) + + +def test_issue_15539(): + assert series(atan(x), x, -oo) == (-1/(5*x**5) + 1/(3*x**3) - 1/x - pi/2 + + O(x**(-6), (x, -oo))) + assert series(atan(x), x, oo) == (-1/(5*x**5) + 1/(3*x**3) - 1/x + pi/2 + + O(x**(-6), (x, oo))) + + +def test_issue_7259(): + assert series(LambertW(x), x) == x - x**2 + 3*x**3/2 - 8*x**4/3 + 125*x**5/24 + O(x**6) + assert series(LambertW(x**2), x, n=8) == x**2 - x**4 + 3*x**6/2 + O(x**8) + assert series(LambertW(sin(x)), x, n=4) == x - x**2 + 4*x**3/3 + O(x**4) + +def test_issue_11884(): + assert cos(x).series(x, 1, n=1) == cos(1) + O(x - 1, (x, 1)) + + +def test_issue_18008(): + y = x*(1 + x*(1 - x))/((1 + x*(1 - x)) - (1 - x)*(1 - x)) + assert y.series(x, oo, n=4) == -9/(32*x**3) - 3/(16*x**2) - 1/(8*x) + S(1)/4 + x/2 + \ + O(x**(-4), (x, oo)) + + +def test_issue_18842(): + f = log(x/(1 - x)) + assert f.series(x, 0.491, n=1).removeO().nsimplify() == \ + -S(180019443780011)/5000000000000000 + + +def test_issue_19534(): + dt = symbols('dt', real=True) + expr = 16*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0)/45 + \ + 49*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \ + 0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \ + 0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \ + 0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.96296296296296296296*dt + 1.0) + 0.051640768506639183825*dt + \ + dt*(1/2 - sqrt(21)/14) + 1.0)/180 + 49*dt*(-0.23637909581542530626*dt*(2.0*dt + 1.0) - \ + 0.74817562366625959291*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.88085458023927036857*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \ + 0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.96296296296296296296*dt + 1.0) + \ + 2.1165151389911680013*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \ + 0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \ + 0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \ + 0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) - \ + 1.1854881643947648988*dt + dt*(sqrt(21)/14 + 1/2) + 1.0)/180 + \ + dt*(0.66666666666666666667*dt*(2.0*dt + 1.0) + \ + 6.0173399699313066769*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \ + 4.1117044797036320069*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \ + 0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.96296296296296296296*dt + 1.0) - \ + 7.0189140975801991157*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \ + 0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \ + 0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \ + 0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) + \ + 0.94010945196161777522*dt*(-0.23637909581542530626*dt*(2.0*dt + 1.0) - \ + 0.74817562366625959291*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.88085458023927036857*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \ + 0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.96296296296296296296*dt + 1.0) + \ + 2.1165151389911680013*dt*(-0.049335189898860408029*dt*(2.0*dt + 1.0) + \ + 0.29601113939316244817*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) - \ + 0.12564355335492979587*dt*(0.074074074074074074074*dt*(2.0*dt + 1.0) + \ + 0.2962962962962962963*dt*(0.125*dt*(2.0*dt + 1.0) + 0.875*dt + 1.0) + \ + 0.96296296296296296296*dt + 1.0) + 0.22431393315265061193*dt + 1.0) - \ + 0.35816132904077632692*dt + 1.0) + 5.5065024887242400038*dt + 1.0)/20 + dt/20 + 1 + + assert N(expr.series(dt, 0, 8), 20) == ( + - Float('0.00092592592592592596126289', precision=70) * dt**7 + + Float('0.0027777777777777783174695', precision=70) * dt**6 + + Float('0.016666666666666656027029', precision=70) * dt**5 + + Float('0.083333333333333300951828', precision=70) * dt**4 + + Float('0.33333333333333337034077', precision=70) * dt**3 + + Float('1.0', precision=70) * dt**2 + + Float('1.0', precision=70) * dt + + Float('1.0', precision=70) + ) + + +def test_issue_11407(): + a, b, c, x = symbols('a b c x') + assert series(sqrt(a + b + c*x), x, 0, 1) == sqrt(a + b) + O(x) + assert series(sqrt(a + b + c + c*x), x, 0, 1) == sqrt(a + b + c) + O(x) + + +def test_issue_14037(): + assert (sin(x**50)/x**51).series(x, n=0) == 1/x + O(1, x) + + +def test_issue_20551(): + expr = (exp(x)/x).series(x, n=None) + terms = [ next(expr) for i in range(3) ] + assert terms == [1/x, 1, x/2] + + +def test_issue_20697(): + p_0, p_1, p_2, p_3, b_0, b_1, b_2 = symbols('p_0 p_1 p_2 p_3 b_0 b_1 b_2') + Q = (p_0 + (p_1 + (p_2 + p_3/y)/y)/y)/(1 + ((p_3/(b_0*y) + (b_0*p_2\ + - b_1*p_3)/b_0**2)/y + (b_0**2*p_1 - b_0*b_1*p_2 - p_3*(b_0*b_2\ + - b_1**2))/b_0**3)/y) + assert Q.series(y, n=3).ratsimp() == b_2*y**2 + b_1*y + b_0 + O(y**3) + + +def test_issue_21245(): + fi = (1 + sqrt(5))/2 + assert (1/(1 - x - x**2)).series(x, 1/fi, 1).factor() == \ + (-4812 - 2152*sqrt(5) + 1686*x + 754*sqrt(5)*x\ + + O((x - 2/(1 + sqrt(5)))**2, (x, 2/(1 + sqrt(5)))))/((1 + sqrt(5))\ + *(20 + 9*sqrt(5))**2*(x + sqrt(5)*x - 2)) + + +def test_issue_21938(): + expr = sin(1/x + exp(-x)) - sin(1/x) + assert expr.series(x, oo) == (1/(24*x**4) - 1/(2*x**2) + 1 + O(x**(-6), (x, oo)))*exp(-x) + + +def test_issue_23432(): + expr = 1/sqrt(1 - x**2) + result = expr.series(x, 0.5) + assert result.is_Add and len(result.args) == 7 + + +def test_issue_23727(): + res = series(sqrt(1 - x**2), x, 0.1) + assert res.is_Add == True + + +def test_issue_24266(): + #type1: exp(f(x)) + assert (exp(-I*pi*(2*x+1))).series(x, 0, 3) == -1 + 2*I*pi*x + 2*pi**2*x**2 + O(x**3) + assert (exp(-I*pi*(2*x+1))*gamma(1+x)).series(x, 0, 3) == -1 + x*(EulerGamma + 2*I*pi) + \ + x**2*(-EulerGamma**2/2 + 23*pi**2/12 - 2*EulerGamma*I*pi) + O(x**3) + + #type2: c**f(x) + assert ((2*I)**(-I*pi*(2*x+1))).series(x, 0, 2) == exp(pi**2/2 - I*pi*log(2)) + \ + x*(pi**2*exp(pi**2/2 - I*pi*log(2)) - 2*I*pi*exp(pi**2/2 - I*pi*log(2))*log(2)) + O(x**2) + assert ((2)**(-I*pi*(2*x+1))).series(x, 0, 2) == exp(-I*pi*log(2)) - 2*I*pi*x*exp(-I*pi*log(2))*log(2) + O(x**2) + + #type3: f(y)**g(x) + assert ((y)**(I*pi*(2*x+1))).series(x, 0, 2) == exp(I*pi*log(y)) + 2*I*pi*x*exp(I*pi*log(y))*log(y) + O(x**2) + assert ((I*y)**(I*pi*(2*x+1))).series(x, 0, 2) == exp(I*pi*log(I*y)) + 2*I*pi*x*exp(I*pi*log(I*y))*log(I*y) + O(x**2)