Instruction:
Can you tell what is the following Python 3 function doing
def _preprocess(self, struct1, struct2, niggli=True):
        struct1 = struct1.copy()
        struct2 = struct2.copy()

        if niggli:
            struct1 = struct1.get_reduced_structure(reduction_algo="niggli")
            struct2 = struct2.get_reduced_structure(reduction_algo="niggli")

        # primitive cell transformation
        if self._primitive_cell:
            struct1 = struct1.get_primitive_structure()
            struct2 = struct2.get_primitive_structure()

        if self._supercell:
            fu, s1_supercell = self._get_supercell_size(struct1, struct2)
        else:
            fu, s1_supercell = 1, True
        mult = fu if s1_supercell else 1/fu

        # rescale lattice to same volume
        if self._scale:
            ratio = (struct2.volume / (struct1.volume * mult)) ** (1 / 6)
            nl1 = Lattice(struct1.lattice.matrix * ratio)
            struct1.lattice = nl1
            nl2 = Lattice(struct2.lattice.matrix / ratio)
            struct2.lattice = nl2

        return struct1, struct2, fu, s1_supercell

Response: Preprocess the structure1 and structure2 for the new structure.


Instruction:
Write a Python 3 function for
matching one struct onto the other.

Response:
def _match(self, struct1, struct2, fu, s1_supercell=True, use_rms=False,
               break_on_match=False):
        """
        Matches one struct onto the other
        """
        ratio = fu if s1_supercell else 1/fu
        if len(struct1) * ratio >= len(struct2):
            return self._strict_match(
                struct1, struct2, fu, s1_supercell=s1_supercell,
                break_on_match=break_on_match, use_rms=use_rms)
        else:
            return self._strict_match(
                struct2, struct1, fu, s1_supercell=(not s1_supercell),
                break_on_match=break_on_match, use_rms=use_rms)


Instruction:
How would you implement a function in Python 3 that
returns the best match for the structure1 and structure2.

Response:
def _strict_match(self, struct1, struct2, fu, s1_supercell=True,
                      use_rms=False, break_on_match=False):
        """
        Matches struct2 onto struct1 (which should contain all sites in
        struct2).

        Args:
            struct1, struct2 (Structure): structures to be matched
            fu (int): size of supercell to create
            s1_supercell (bool): whether to create the supercell of
                struct1 (vs struct2)
            use_rms (bool): whether to minimize the rms of the matching
            break_on_match (bool): whether to stop search at first
                valid match
        """
        if fu < 1:
            raise ValueError("fu cannot be less than 1")

        mask, s1_t_inds, s2_t_ind = self._get_mask(struct1, struct2,
                                                   fu, s1_supercell)

        if mask.shape[0] > mask.shape[1]:
            raise ValueError('after supercell creation, struct1 must '
                             'have more sites than struct2')

        # check that a valid mapping exists
        if (not self._subset) and mask.shape[1] != mask.shape[0]:
            return None

        if LinearAssignment(mask).min_cost > 0:
            return None

        best_match = None
        # loop over all lattices
        for s1fc, s2fc, avg_l, sc_m in \
                self._get_supercells(struct1, struct2, fu, s1_supercell):
            # compute fractional tolerance
            normalization = (len(s1fc) / avg_l.volume) ** (1/3)
            inv_abc = np.array(avg_l.reciprocal_lattice.abc)
            frac_tol = inv_abc * self.stol / (np.pi * normalization)
            # loop over all translations
            for s1i in s1_t_inds:
                t = s1fc[s1i] - s2fc[s2_t_ind]
                t_s2fc = s2fc + t
                if self._cmp_fstruct(s1fc, t_s2fc, frac_tol, mask):
                    inv_lll_abc = np.array(avg_l.get_lll_reduced_lattice().reciprocal_lattice.abc)
                    lll_frac_tol = inv_lll_abc * self.stol / (np.pi * normalization)
                    dist, t_adj, mapping = self._cart_dists(
                        s1fc, t_s2fc, avg_l, mask, normalization, lll_frac_tol)
                    if use_rms:
                        val = np.linalg.norm(dist) / len(dist) ** 0.5
                    else:
                        val = max(dist)
                    if best_match is None or val < best_match[0]:
                        total_t = t + t_adj
                        total_t -= np.round(total_t)
                        best_match = val, dist, sc_m, total_t, mapping
                        if (break_on_match or val < 1e-5) and val < self.stol:
                            return best_match

        if best_match and best_match[0] < self.stol:
            return best_match


Instruction:
Create a Python 3 function for
giving a list of structures use fit to group them by structural equality.

Response:
def group_structures(self, s_list, anonymous=False):
        """
        Given a list of structures, use fit to group
        them by structural equality.

        Args:
            s_list ([Structure]): List of structures to be grouped
            anonymous (bool): Wheher to use anonymous mode.

        Returns:
            A list of lists of matched structures
            Assumption: if s1 == s2 but s1 != s3, than s2 and s3 will be put
            in different groups without comparison.
        """
        if self._subset:
            raise ValueError("allow_subset cannot be used with"
                             " group_structures")

        original_s_list = list(s_list)
        s_list = self._process_species(s_list)

        # Use structure hash to pre-group structures
        if anonymous:
            c_hash = lambda c: c.anonymized_formula
        else:
            c_hash = self._comparator.get_hash
        s_hash = lambda s: c_hash(s[1].composition)
        sorted_s_list = sorted(enumerate(s_list), key=s_hash)
        all_groups = []

        # For each pre-grouped list of structures, perform actual matching.
        for k, g in itertools.groupby(sorted_s_list, key=s_hash):
            unmatched = list(g)
            while len(unmatched) > 0:
                i, refs = unmatched.pop(0)
                matches = [i]
                if anonymous:
                    inds = filter(lambda i: self.fit_anonymous(refs,
                            unmatched[i][1]), list(range(len(unmatched))))
                else:
                    inds = filter(lambda i: self.fit(refs, unmatched[i][1]),
                                  list(range(len(unmatched))))
                inds = list(inds)
                matches.extend([unmatched[i][0] for i in inds])
                unmatched = [unmatched[i] for i in range(len(unmatched))
                             if i not in inds]
                all_groups.append([original_s_list[i] for i in matches])

        return all_groups


Instruction:
Write a Python 3 script for
returning a list of mappings and matches for the anonymous structure.

Response:
def _anonymous_match(self, struct1, struct2, fu, s1_supercell=True,
                         use_rms=False, break_on_match=False, single_match=False):
        """
        Tries all permutations of matching struct1 to struct2.
        Args:
            struct1, struct2 (Structure): Preprocessed input structures
        Returns:
            List of (mapping, match)
        """
        if not isinstance(self._comparator, SpeciesComparator):
            raise ValueError('Anonymous fitting currently requires SpeciesComparator')

        # check that species lists are comparable
        sp1 = struct1.composition.elements
        sp2 = struct2.composition.elements
        if len(sp1) != len(sp2):
            return None

        ratio = fu if s1_supercell else 1/fu
        swapped = len(struct1) * ratio < len(struct2)

        s1_comp = struct1.composition
        s2_comp = struct2.composition
        matches = []
        for perm in itertools.permutations(sp2):
            sp_mapping = dict(zip(sp1, perm))

            # do quick check that compositions are compatible
            mapped_comp = Composition({sp_mapping[k]: v
                                       for k, v in s1_comp.items()})
            if (not self._subset) and (
                    self._comparator.get_hash(mapped_comp) !=
                    self._comparator.get_hash(s2_comp)):
                continue

            mapped_struct = struct1.copy()
            mapped_struct.replace_species(sp_mapping)
            if swapped:
                m = self._strict_match(struct2, mapped_struct, fu,
                                       (not s1_supercell), use_rms,
                                       break_on_match)
            else:
                m = self._strict_match(mapped_struct, struct2, fu, s1_supercell,
                                       use_rms, break_on_match)
            if m:
                matches.append((sp_mapping, m))
                if single_match:
                    break
        return matches


Instruction:
Make a summary of the following Python 3 code
def get_rms_anonymous(self, struct1, struct2):
        struct1, struct2 = self._process_species([struct1, struct2])
        struct1, struct2, fu, s1_supercell = self._preprocess(struct1, struct2)

        matches = self._anonymous_match(struct1, struct2, fu, s1_supercell,
                                        use_rms=True, break_on_match=False)
        if matches:
            best = sorted(matches, key=lambda x: x[1][0])[0]
            return best[1][0], best[0]
        else:
            return None, None

Response: Returns the RMS distance between two structures.


Instruction:
Write a Python 3 function that can
return the electronegativity of the species in one structure to the species in another.

Response:
def get_best_electronegativity_anonymous_mapping(self, struct1, struct2):
        """
        Performs an anonymous fitting, which allows distinct species in one
        structure to map to another. E.g., to compare if the Li2O and Na2O
        structures are similar. If multiple substitutions are within tolerance
        this will return the one which minimizes the difference in
        electronegativity between the matches species.

        Args:
            struct1 (Structure): 1st structure
            struct2 (Structure): 2nd structure

        Returns:
            min_mapping (Dict): Mapping of struct1 species to struct2 species
        """
        struct1, struct2 = self._process_species([struct1, struct2])
        struct1, struct2, fu, s1_supercell = self._preprocess(struct1, struct2)

        matches = self._anonymous_match(struct1, struct2, fu, s1_supercell,
                                        use_rms=True, break_on_match=True)

        if matches:
            min_X_diff = np.inf
            for m in matches:
                X_diff = 0
                for k, v in m[0].items():
                    X_diff += struct1.composition[k] * (k.X - v.X) ** 2
                if X_diff < min_X_diff:
                    min_X_diff = X_diff
                    best = m[0]
            return best


Instruction:
How would you implement a function in Python 3 that
returns a list of species mappings that are anonymously applied to one structure.

Response:
def get_all_anonymous_mappings(self, struct1, struct2, niggli=True,
                                   include_dist=False):
        """
        Performs an anonymous fitting, which allows distinct species in one
        structure to map to another. Returns a dictionary of species
        substitutions that are within tolerance

        Args:
            struct1 (Structure): 1st structure
            struct2 (Structure): 2nd structure
            niggli (bool): Find niggli cell in preprocessing
            include_dist (bool): Return the maximin distance with each mapping

        Returns:
            list of species mappings that map struct1 to struct2.
        """
        struct1, struct2 = self._process_species([struct1, struct2])
        struct1, struct2, fu, s1_supercell = self._preprocess(struct1, struct2,
                                                              niggli)

        matches = self._anonymous_match(struct1, struct2, fu, s1_supercell,
                                        break_on_match=not include_dist)
        if matches:
            if include_dist:
                return [(m[0], m[1][0]) for m in matches]
            else:
                return [m[0] for m in matches]


Instruction:
Explain what the following Python 3 code does
def fit_anonymous(self, struct1, struct2, niggli=True):
        struct1, struct2 = self._process_species([struct1, struct2])
        struct1, struct2, fu, s1_supercell = self._preprocess(struct1, struct2,
                                                              niggli)

        matches = self._anonymous_match(struct1, struct2, fu, s1_supercell,
                                        break_on_match=True, single_match=True)

        if matches:
            return True
        else:
            return False

Response: Performs an anonymous fitting of the structures in one object to another object.


Instruction:
Can you write a function in Python 3 where it
returns the matrix for transforming struct to supercell.

Response:
def get_supercell_matrix(self, supercell, struct):
        """
        Returns the matrix for transforming struct to supercell. This
        can be used for very distorted 'supercells' where the primitive cell
        is impossible to find
        """
        if self._primitive_cell:
            raise ValueError("get_supercell_matrix cannot be used with the "
                             "primitive cell option")
        struct, supercell, fu, s1_supercell = self._preprocess(struct,
                                                               supercell, False)

        if not s1_supercell:
            raise ValueError("The non-supercell must be put onto the basis"
                             " of the supercell, not the other way around")

        match = self._match(struct, supercell, fu, s1_supercell, use_rms=True,
                            break_on_match=False)

        if match is None:
            return None

        return match[2]


Instruction:
Here you have a function in Python 3, explain what it does
def get_transformation(self, struct1, struct2):
        if self._primitive_cell:
            raise ValueError("get_transformation cannot be used with the "
                             "primitive cell option")

        struct1, struct2 = self._process_species((struct1, struct2))

        s1, s2, fu, s1_supercell = self._preprocess(struct1, struct2, False)
        ratio = fu if s1_supercell else 1/fu
        if s1_supercell and fu > 1:
            raise ValueError("Struct1 must be the supercell, "
                             "not the other way around")

        if len(s1) * ratio >= len(s2):
            # s1 is superset
            match = self._strict_match(s1, s2, fu=fu, s1_supercell=False,
                                       use_rms=True, break_on_match=False)
            if match is None:
                return None
            # invert the mapping, since it needs to be from s1 to s2
            mapping = [list(match[4]).index(i) if i in match[4] else None
                       for i in range(len(s1))]
            return match[2], match[3], mapping
        else:
            # s2 is superset
            match = self._strict_match(s2, s1, fu=fu, s1_supercell=True,
                                       use_rms=True, break_on_match=False)
            if match is None:
                return None
            # add sites not included in the mapping
            not_included = list(range(len(s2) * fu))
            for i in match[4]:
                not_included.remove(i)
            mapping = list(match[4]) + not_included
            return match[2], -match[3], mapping

Response: Returns the supercell transformation fractional translation vector and a mapping to transform struct1 to be similar to struct2.


Instruction:
Implement a Python 3 function for
returning a structure object similar to struct1 but with the same structure as struct2.

Response:
def get_s2_like_s1(self, struct1, struct2, include_ignored_species=True):
        """
        Performs transformations on struct2 to put it in a basis similar to
        struct1 (without changing any of the inter-site distances)

        Args:
            struct1 (Structure): Reference structure
            struct2 (Structure): Structure to transform.
            include_ignored_species (bool): Defaults to True,
                the ignored_species is also transformed to the struct1
                lattice orientation, though obviously there is no direct
                matching to existing sites.

        Returns:
            A structure object similar to struct1, obtained by making a
            supercell, sorting, and translating struct2.
        """
        s1, s2 = self._process_species([struct1, struct2])
        trans = self.get_transformation(s1, s2)
        if trans is None:
            return None
        sc, t, mapping = trans
        sites = [site for site in s2]
        # Append the ignored sites at the end.
        sites.extend([site for site in struct2 if site not in s2])
        temp = Structure.from_sites(sites)

        temp.make_supercell(sc)
        temp.translate_sites(list(range(len(temp))), t)
        # translate sites to correct unit cell
        for i, j in enumerate(mapping[:len(s1)]):
            if j is not None:
                vec = np.round(struct1[i].frac_coords - temp[j].frac_coords)
                temp.translate_sites(j, vec, to_unit_cell=False)

        sites = [temp.sites[i] for i in mapping if i is not None]

        if include_ignored_species:
            start = int(round(len(temp) / len(struct2) * len(s2)))
            sites.extend(temp.sites[start:])

        return Structure.from_sites(sites)


Instruction:
Create a Python 3 function for
calculating the mapping from superset to subset.

Response:
def get_mapping(self, superset, subset):
        """
        Calculate the mapping from superset to subset.

        Args:
            superset (Structure): Structure containing at least the sites in
                subset (within the structure matching tolerance)
            subset (Structure): Structure containing some of the sites in
                superset (within the structure matching tolerance)

        Returns:
            numpy array such that superset.sites[mapping] is within matching
            tolerance of subset.sites or None if no such mapping is possible
        """
        if self._supercell:
            raise ValueError("cannot compute mapping to supercell")
        if self._primitive_cell:
            raise ValueError("cannot compute mapping with primitive cell "
                             "option")
        if len(subset) > len(superset):
            raise ValueError("subset is larger than superset")

        superset, subset, _, _ = self._preprocess(superset, subset, True)
        match = self._strict_match(superset, subset, 1, break_on_match=False)

        if match is None or match[0] > self.stol:
            return None

        return match[4]


Instruction:
Can you implement a function in Python 3 that
compares two defects and return True if they are identical.

Response:
def are_equal(self, d1, d2):
        """
        Args:
            d1: First defect. A pymatgen Defect object.
            d2: Second defect. A pymatgen Defect object.

        Returns:
            True if defects are identical in type and sublattice.
        """
        possible_defect_types = (Defect, Vacancy, Substitution, Interstitial)

        if not isinstance(d1, possible_defect_types) or \
            not isinstance(d2, possible_defect_types):
            raise ValueError("Cannot use PointDefectComparator to" + \
                             " compare non-defect objects...")

        if not isinstance(d1, d2.__class__):
            return False
        elif d1.site.specie != d2.site.specie:
            return False
        elif self.check_charge and (d1.charge != d2.charge):
            return False

        sm = StructureMatcher( ltol=0.01,
                               primitive_cell=self.check_primitive_cell,
                               scale=self.check_lattice_scale)

        if not sm.fit(d1.bulk_structure, d2.bulk_structure):
            return False

        d1 = d1.copy()
        d2 = d2.copy()
        if self.check_primitive_cell or self.check_lattice_scale:
            # if allowing for base structure volume or supercell modifications,
            # then need to preprocess defect objects to allow for matching
            d1_mod_bulk_structure, d2_mod_bulk_structure, _, _ = sm._preprocess(
                d1.bulk_structure, d2.bulk_structure)
            d1_defect_site = PeriodicSite(d1.site.specie, d1.site.coords,
                                          d1_mod_bulk_structure.lattice,
                                          to_unit_cell=True,
                                          coords_are_cartesian=True)
            d2_defect_site = PeriodicSite( d2.site.specie, d2.site.coords,
                                           d2_mod_bulk_structure.lattice,
                                           to_unit_cell=True,
                                           coords_are_cartesian=True)

            d1._structure = d1_mod_bulk_structure
            d2._structure = d2_mod_bulk_structure
            d1._defect_site = d1_defect_site
            d2._defect_site = d2_defect_site

        return sm.fit(d1.generate_defect_structure(),
                      d2.generate_defect_structure())


Instruction:
How would you explain what the following Python 3 function does
def from_composition_and_pd(comp, pd, working_ion_symbol="Li"):
        working_ion = Element(working_ion_symbol)
        entry = None
        working_ion_entry = None
        for e in pd.stable_entries:
            if e.composition.reduced_formula == comp.reduced_formula:
                entry = e
            elif e.is_element and \
                    e.composition.reduced_formula == working_ion_symbol:
                working_ion_entry = e

        if not entry:
            raise ValueError("Not stable compound found at composition {}."
                             .format(comp))

        profile = pd.get_element_profile(working_ion, comp)
        # Need to reverse because voltage goes form most charged to most
        # discharged.
        profile.reverse()
        if len(profile) < 2:
            return None
        working_ion_entry = working_ion_entry
        working_ion = working_ion_entry.composition.elements[0].symbol
        normalization_els = {}
        for el, amt in comp.items():
            if el != Element(working_ion):
                normalization_els[el] = amt
        vpairs = [ConversionVoltagePair.from_steps(profile[i], profile[i + 1],
                                                   normalization_els)
                  for i in range(len(profile) - 1)]
        return ConversionElectrode(vpairs, working_ion_entry, comp)

Response: Convenience constructor to make a ConversionElectrode from a composition and a PhaseDiagram.


Instruction:
Make a summary of the following Python 3 code
def get_sub_electrodes(self, adjacent_only=True):

        if adjacent_only:
            return [self.__class__(self._vpairs[i:i + 1],
                                   self._working_ion_entry, self._composition)
                    for i in range(len(self._vpairs))]
        sub_electrodes = []
        for i in range(len(self._vpairs)):
            for j in range(i, len(self._vpairs)):
                sub_electrodes.append(self.__class__(self._vpairs[i:j + 1],
                                                     self._working_ion_entry,
                                                     self._composition))
        return sub_electrodes

Response: Returns a list of ConversionElectrodes that are subelectrodes of this one.


Instruction:
Given the following Python 3 function, write the documentation
def is_super_electrode(self, conversion_electrode):
        for pair1 in conversion_electrode:
            rxn1 = pair1.rxn
            all_formulas1 = set([rxn1.all_comp[i].reduced_formula
                                 for i in range(len(rxn1.all_comp))
                                 if abs(rxn1.coeffs[i]) > 1e-5])
            for pair2 in self:
                rxn2 = pair2.rxn
                all_formulas2 = set([rxn2.all_comp[i].reduced_formula
                                     for i in range(len(rxn2.all_comp))
                                     if abs(rxn2.coeffs[i]) > 1e-5])
                if all_formulas1 == all_formulas2:
                    break
            else:
                return False
        return True

Response: Checks if a particular conversion electrode is a super electrode of the current one.


Instruction:
Given the following Python 3 function, write the documentation
def get_summary_dict(self, print_subelectrodes=True):

        d = {}
        framework_comp = Composition({k: v
                                      for k, v in self._composition.items()
                                      if k.symbol != self.working_ion.symbol})

        d["framework"] = framework_comp.to_data_dict
        d["framework_pretty"] = framework_comp.reduced_formula
        d["average_voltage"] = self.get_average_voltage()
        d["max_voltage"] = self.max_voltage
        d["min_voltage"] = self.min_voltage
        d["max_delta_volume"] = self.max_delta_volume
        d["max_instability"] = 0
        d["max_voltage_step"] = self.max_voltage_step
        d["nsteps"] = self.num_steps
        d["capacity_grav"] = self.get_capacity_grav()
        d["capacity_vol"] = self.get_capacity_vol()
        d["energy_grav"] = self.get_specific_energy()
        d["energy_vol"] = self.get_energy_density()
        d["working_ion"] = self.working_ion.symbol
        d["reactions"] = []
        d["reactant_compositions"] = []
        comps = []
        frac = []
        for pair in self._vpairs:
            rxn = pair.rxn
            frac.append(pair.frac_charge)
            frac.append(pair.frac_discharge)
            d["reactions"].append(str(rxn))
            for i in range(len(rxn.coeffs)):
                if abs(rxn.coeffs[i]) > 1e-5 and rxn.all_comp[i] not in comps:
                    comps.append(rxn.all_comp[i])
                if abs(rxn.coeffs[i]) > 1e-5 and \
                        rxn.all_comp[i].reduced_formula != d["working_ion"]:
                    reduced_comp = rxn.all_comp[i].reduced_composition
                    comp_dict = reduced_comp.as_dict()
                    d["reactant_compositions"].append(comp_dict)
        d["fracA_charge"] = min(frac)
        d["fracA_discharge"] = max(frac)
        d["nsteps"] = self.num_steps
        if print_subelectrodes:
            f_dict = lambda c: c.get_summary_dict(print_subelectrodes=False)
            d["adj_pairs"] = map(f_dict,
                                 self.get_sub_electrodes(adjacent_only=True))
            d["all_pairs"] = map(f_dict,
                                 self.get_sub_electrodes(adjacent_only=False))
        return d

Response: Returns a dictionary of all the electrodes properties in the format that can be used to generate the summary of this electrode.


Instruction:
Can you generate the documentation for the following Python 3 function
def from_steps(step1, step2, normalization_els):
        working_ion_entry = step1["element_reference"]
        working_ion = working_ion_entry.composition.elements[0].symbol
        working_ion_valence = max(Element(working_ion).oxidation_states)
        voltage = (-step1["chempot"] + working_ion_entry.energy_per_atom)/working_ion_valence
        mAh = (step2["evolution"] - step1["evolution"]) \
            * Charge(1, "e").to("C") * Time(1, "s").to("h") * N_A * 1000*working_ion_valence
        licomp = Composition(working_ion)
        prev_rxn = step1["reaction"]
        reactants = {comp: abs(prev_rxn.get_coeff(comp))
                     for comp in prev_rxn.products if comp != licomp}

        curr_rxn = step2["reaction"]
        products = {comp: abs(curr_rxn.get_coeff(comp))
                    for comp in curr_rxn.products if comp != licomp}

        reactants[licomp] = (step2["evolution"] - step1["evolution"])

        rxn = BalancedReaction(reactants, products)

        for el, amt in normalization_els.items():
            if rxn.get_el_amount(el) > 1e-6:
                rxn.normalize_to_element(el, amt)
                break

        prev_mass_dischg = sum([prev_rxn.all_comp[i].weight
                                * abs(prev_rxn.coeffs[i])
                                for i in range(len(prev_rxn.all_comp))]) / 2
        vol_charge = sum([abs(prev_rxn.get_coeff(e.composition))
                          * e.structure.volume
                          for e in step1["entries"]
                          if e.composition.reduced_formula != working_ion])
        mass_discharge = sum([curr_rxn.all_comp[i].weight
                              * abs(curr_rxn.coeffs[i])
                              for i in range(len(curr_rxn.all_comp))]) / 2
        mass_charge = prev_mass_dischg
        mass_discharge = mass_discharge
        vol_discharge = sum([abs(curr_rxn.get_coeff(e.composition))
                             * e.structure.volume
                             for e in step2["entries"]
                             if e.composition.reduced_formula != working_ion])

        totalcomp = Composition({})
        for comp in prev_rxn.products:
            if comp.reduced_formula != working_ion:
                totalcomp += comp * abs(prev_rxn.get_coeff(comp))
        frac_charge = totalcomp.get_atomic_fraction(Element(working_ion))

        totalcomp = Composition({})
        for comp in curr_rxn.products:
            if comp.reduced_formula != working_ion:
                totalcomp += comp * abs(curr_rxn.get_coeff(comp))
        frac_discharge = totalcomp.get_atomic_fraction(Element(working_ion))

        rxn = rxn
        entries_charge = step2["entries"]
        entries_discharge = step1["entries"]

        return ConversionVoltagePair(rxn, voltage, mAh, vol_charge,
                                     vol_discharge, mass_charge,
                                     mass_discharge,
                                     frac_charge, frac_discharge,
                                     entries_charge, entries_discharge,
                                     working_ion_entry)

Response: Creates a ConversionVoltagePair from two steps in the element profile.


Instruction:
Create a Python 3 function to
create an Xr object from a string representation of an ISO - 8601 file.

Response:
def from_string(string, use_cores=True, thresh=1.e-4):
        """
        Creates an Xr object from a string representation.

        Args:
            string (str): string representation of an Xr object.
            use_cores (bool): use core positions and discard shell
                    positions if set to True (default).  Otherwise,
                    use shell positions and discard core positions.
            thresh (float): relative threshold for consistency check
                    between cell parameters (lengths and angles) from
                    header information and cell vectors, respectively.

        Returns:
            xr (Xr): Xr object corresponding to the input
                    string representation.
        """
        lines = string.split("\n")
        toks = lines[0].split()
        lengths = [float(toks[i]) for i in range(1, len(toks))]
        toks = lines[1].split()
        angles = [float(i) for i in toks[0:3]]
        toks = lines[2].split()
        nsites = int(toks[0])
        mat = np.zeros((3,3), dtype=float)
        for i in range(3):
            toks = lines[4+nsites+i].split()
            toks2 = lines[4+nsites+i+3].split()
            for j, item in enumerate(toks):
                if item != toks2[j]:
                    raise RuntimeError("expected both matrices"
                            " to be the same in xr file")
            mat[i] = np.array([float(w) for w in toks])
        lat = Lattice(mat)
        if fabs(lat.a-lengths[0])/fabs(lat.a) > thresh or \
                fabs(lat.b-lengths[1])/fabs(lat.b) > thresh or \
                fabs(lat.c-lengths[2])/fabs(lat.c) > thresh or \
                fabs(lat.alpha-angles[0])/fabs(lat.alpha) > thresh or \
                fabs(lat.beta-angles[1])/fabs(lat.beta) > thresh or \
                fabs(lat.gamma-angles[2])/fabs(lat.gamma) > thresh:
            raise RuntimeError("cell parameters in header ("+str(lengths)+\
                    ", "+str(angles)+") are not consistent with Cartesian"+\
                    " lattice vectors ("+str(lat.abc)+", "+\
                    str(lat.angles)+")")
        # Ignore line w/ index 3.
        sp = []
        coords = []
        for j in range(nsites):
            m = re.match(r"\d+\s+(\w+)\s+([0-9\-\.]+)\s+([0-9\-\.]+)\s+" +
                         r"([0-9\-\.]+)", lines[4+j].strip())
            if m:
                tmp_sp = m.group(1)
                if use_cores and tmp_sp[len(tmp_sp)-2:] == "_s":
                    continue
                if not use_cores and tmp_sp[len(tmp_sp)-2:] == "_c":
                    continue
                if tmp_sp[len(tmp_sp)-2] == "_":
                    sp.append(tmp_sp[0:len(tmp_sp)-2])
                else:
                    sp.append(tmp_sp)
                coords.append([float(m.group(i)) for i in range(2, 5)])
        return Xr(Structure(lat, sp, coords, coords_are_cartesian=True))


Instruction:
Given the following Python 3 function, write the documentation
def from_file(filename, use_cores=True, thresh=1.e-4):
        with zopen(filename, "rt") as f:
            return Xr.from_string(
                    f.read(), use_cores=use_cores,
                    thresh=thresh)

Response:
Reads an xr - formatted file and returns an Xr object corresponding to the input
            file.


Instruction:
Write a Python 3 script for
framing a signal into overlapping frames.

Response:
def framesig(sig, frame_len, frame_step, winfunc=lambda x: numpy.ones((x,)), stride_trick=True):
    """Frame a signal into overlapping frames.

    :param sig: the audio signal to frame.
    :param frame_len: length of each frame measured in samples.
    :param frame_step: number of samples after the start of the previous frame that the next frame should begin.
    :param winfunc: the analysis window to apply to each frame. By default no window is applied.
    :param stride_trick: use stride trick to compute the rolling window and window multiplication faster
    :returns: an array of frames. Size is NUMFRAMES by frame_len.
    """
    slen = len(sig)
    frame_len = int(round_half_up(frame_len))
    frame_step = int(round_half_up(frame_step))
    if slen <= frame_len:
        numframes = 1
    else:
        numframes = 1 + int(math.ceil((1.0 * slen - frame_len) / frame_step))

    padlen = int((numframes - 1) * frame_step + frame_len)

    zeros = numpy.zeros((padlen - slen,))
    padsignal = numpy.concatenate((sig, zeros))
    if stride_trick:
        win = winfunc(frame_len)
        frames = rolling_window(padsignal, window=frame_len, step=frame_step)
    else:
        indices = numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(
            numpy.arange(0, numframes * frame_step, frame_step), (frame_len, 1)).T
        indices = numpy.array(indices, dtype=numpy.int32)
        frames = padsignal[indices]
        win = numpy.tile(winfunc(frame_len), (numframes, 1))

    return frames * win


Instruction:
Can you create a Python 3 function that
does overlap-add procedure to undo the action of framesig. :param frames: the array of frames. :param siglen: the length of the desired signal, use 0 if unknown. Output will be truncated to siglen samples. :param frame_len: length of each frame measured in samples. :param frame_step: number of samples after the start of the previous frame that the next frame should begin. :param winfunc: the analysis window to apply to each frame. By default no window is applied. :returns: a 1-D signal.

Response:
def deframesig(frames, siglen, frame_len, frame_step, winfunc=lambda x: numpy.ones((x,))):
    """Does overlap-add procedure to undo the action of framesig.

    :param frames: the array of frames.
    :param siglen: the length of the desired signal, use 0 if unknown. Output will be truncated to siglen samples.
    :param frame_len: length of each frame measured in samples.
    :param frame_step: number of samples after the start of the previous frame that the next frame should begin.
    :param winfunc: the analysis window to apply to each frame. By default no window is applied.
    :returns: a 1-D signal.
    """
    frame_len = round_half_up(frame_len)
    frame_step = round_half_up(frame_step)
    numframes = numpy.shape(frames)[0]
    assert numpy.shape(frames)[1] == frame_len, '"frames" matrix is wrong size, 2nd dim is not equal to frame_len'

    indices = numpy.tile(numpy.arange(0, frame_len), (numframes, 1)) + numpy.tile(
        numpy.arange(0, numframes * frame_step, frame_step), (frame_len, 1)).T
    indices = numpy.array(indices, dtype=numpy.int32)
    padlen = (numframes - 1) * frame_step + frame_len

    if siglen <= 0: siglen = padlen

    rec_signal = numpy.zeros((padlen,))
    window_correction = numpy.zeros((padlen,))
    win = winfunc(frame_len)

    for i in range(0, numframes):
        window_correction[indices[i, :]] = window_correction[
                                               indices[i, :]] + win + 1e-15  # add a little bit so it is never zero
        rec_signal[indices[i, :]] = rec_signal[indices[i, :]] + frames[i, :]

    rec_signal = rec_signal / window_correction
    return rec_signal[0:siglen]


Instruction:
Can you generate a brief explanation for the following Python 3 code
def magspec(frames, NFFT):
    if numpy.shape(frames)[1] > NFFT:
        logging.warn(
            'frame length (%d) is greater than FFT size (%d), frame will be truncated. Increase NFFT to avoid.',
            numpy.shape(frames)[1], NFFT)
    complex_spec = numpy.fft.rfft(frames, NFFT)
    return numpy.absolute(complex_spec)

Response: Compute the magnitude spectrum of each frame in frames.


Instruction:
Can you write a function in Python 3 where it
computes the log power spectrum of each frame in frames.

Response:
def logpowspec(frames, NFFT, norm=1):
    """Compute the log power spectrum of each frame in frames. If frames is an NxD matrix, output will be Nx(NFFT/2+1).

    :param frames: the array of frames. Each row is a frame.
    :param NFFT: the FFT length to use. If NFFT > frame_len, the frames are zero-padded.
    :param norm: If norm=1, the log power spectrum is normalised so that the max value (across all frames) is 0.
    :returns: If frames is an NxD matrix, output will be Nx(NFFT/2+1). Each row will be the log power spectrum of the corresponding frame.
    """
    ps = powspec(frames, NFFT);
    ps[ps <= 1e-30] = 1e-30
    lps = 10 * numpy.log10(ps)
    if norm:
        return lps - numpy.max(lps)
    else:
        return lps


Instruction:
Write a Python 3 function that can
calculate the FFT size of the current window.

Response:
def calculate_nfft(samplerate, winlen):
    """Calculates the FFT size as a power of two greater than or equal to
    the number of samples in a single window length.

    Having an FFT less than the window length loses precision by dropping
    many of the samples; a longer FFT than the window allows zero-padding
    of the FFT buffer which is neutral in terms of frequency domain conversion.

    :param samplerate: The sample rate of the signal we are working with, in Hz.
    :param winlen: The length of the analysis window in seconds.
    """
    window_length_samples = winlen * samplerate
    nfft = 1
    while nfft < window_length_samples:
        nfft *= 2
    return nfft


Instruction:
Write a Python 3 script to
compute MFCC features from an audio signal.

Response:
def mfcc(signal,samplerate=16000,winlen=0.025,winstep=0.01,numcep=13,
         nfilt=26,nfft=None,lowfreq=0,highfreq=None,preemph=0.97,ceplifter=22,appendEnergy=True,
         winfunc=lambda x:numpy.ones((x,))):
    """Compute MFCC features from an audio signal.

    :param signal: the audio signal from which to compute features. Should be an N*1 array
    :param samplerate: the sample rate of the signal we are working with, in Hz.
    :param winlen: the length of the analysis window in seconds. Default is 0.025s (25 milliseconds)
    :param winstep: the step between successive windows in seconds. Default is 0.01s (10 milliseconds)
    :param numcep: the number of cepstrum to return, default 13
    :param nfilt: the number of filters in the filterbank, default 26.
    :param nfft: the FFT size. Default is None, which uses the calculate_nfft function to choose the smallest size that does not drop sample data.
    :param lowfreq: lowest band edge of mel filters. In Hz, default is 0.
    :param highfreq: highest band edge of mel filters. In Hz, default is samplerate/2
    :param preemph: apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97.
    :param ceplifter: apply a lifter to final cepstral coefficients. 0 is no lifter. Default is 22.
    :param appendEnergy: if this is true, the zeroth cepstral coefficient is replaced with the log of the total frame energy.
    :param winfunc: the analysis window to apply to each frame. By default no window is applied. You can use numpy window functions here e.g. winfunc=numpy.hamming
    :returns: A numpy array of size (NUMFRAMES by numcep) containing features. Each row holds 1 feature vector.
    """
    nfft = nfft or calculate_nfft(samplerate, winlen)
    feat,energy = fbank(signal,samplerate,winlen,winstep,nfilt,nfft,lowfreq,highfreq,preemph,winfunc)
    feat = numpy.log(feat)
    feat = dct(feat, type=2, axis=1, norm='ortho')[:,:numcep]
    feat = lifter(feat,ceplifter)
    if appendEnergy: feat[:,0] = numpy.log(energy) # replace first cepstral coefficient with log of frame energy
    return feat


Instruction:
Can you implement a function in Python 3 that
computes Mel - filterbank energy features from an audio signal.

Response:
def fbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,
          nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97,
          winfunc=lambda x:numpy.ones((x,))):
    """Compute Mel-filterbank energy features from an audio signal.

    :param signal: the audio signal from which to compute features. Should be an N*1 array
    :param samplerate: the sample rate of the signal we are working with, in Hz.
    :param winlen: the length of the analysis window in seconds. Default is 0.025s (25 milliseconds)
    :param winstep: the step between successive windows in seconds. Default is 0.01s (10 milliseconds)
    :param nfilt: the number of filters in the filterbank, default 26.
    :param nfft: the FFT size. Default is 512.
    :param lowfreq: lowest band edge of mel filters. In Hz, default is 0.
    :param highfreq: highest band edge of mel filters. In Hz, default is samplerate/2
    :param preemph: apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97.
    :param winfunc: the analysis window to apply to each frame. By default no window is applied. You can use numpy window functions here e.g. winfunc=numpy.hamming
    :returns: 2 values. The first is a numpy array of size (NUMFRAMES by nfilt) containing features. Each row holds 1 feature vector. The
        second return value is the energy in each frame (total energy, unwindowed)
    """
    highfreq= highfreq or samplerate/2
    signal = sigproc.preemphasis(signal,preemph)
    frames = sigproc.framesig(signal, winlen*samplerate, winstep*samplerate, winfunc)
    pspec = sigproc.powspec(frames,nfft)
    energy = numpy.sum(pspec,1) # this stores the total energy in each frame
    energy = numpy.where(energy == 0,numpy.finfo(float).eps,energy) # if energy is zero, we get problems with log

    fb = get_filterbanks(nfilt,nfft,samplerate,lowfreq,highfreq)
    feat = numpy.dot(pspec,fb.T) # compute the filterbank energies
    feat = numpy.where(feat == 0,numpy.finfo(float).eps,feat) # if feat is zero, we get problems with log

    return feat,energy


Instruction:
Write a Python 3 function for
computing log Mel - filterbank energy features from an audio signal.

Response:
def logfbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,
             nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97,
             winfunc=lambda x:numpy.ones((x,))):
    """Compute log Mel-filterbank energy features from an audio signal.

    :param signal: the audio signal from which to compute features. Should be an N*1 array
    :param samplerate: the sample rate of the signal we are working with, in Hz.
    :param winlen: the length of the analysis window in seconds. Default is 0.025s (25 milliseconds)
    :param winstep: the step between successive windows in seconds. Default is 0.01s (10 milliseconds)
    :param nfilt: the number of filters in the filterbank, default 26.
    :param nfft: the FFT size. Default is 512.
    :param lowfreq: lowest band edge of mel filters. In Hz, default is 0.
    :param highfreq: highest band edge of mel filters. In Hz, default is samplerate/2
    :param preemph: apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97.
    :param winfunc: the analysis window to apply to each frame. By default no window is applied. You can use numpy window functions here e.g. winfunc=numpy.hamming
    :returns: A numpy array of size (NUMFRAMES by nfilt) containing features. Each row holds 1 feature vector.
    """
    feat,energy = fbank(signal,samplerate,winlen,winstep,nfilt,nfft,lowfreq,highfreq,preemph,winfunc)
    return numpy.log(feat)


Instruction:
Can you implement a function in Python 3 that
computes Spectral Subband Centroid features from an audio signal.

Response:
def ssc(signal,samplerate=16000,winlen=0.025,winstep=0.01,
        nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97,
        winfunc=lambda x:numpy.ones((x,))):
    """Compute Spectral Subband Centroid features from an audio signal.

    :param signal: the audio signal from which to compute features. Should be an N*1 array
    :param samplerate: the sample rate of the signal we are working with, in Hz.
    :param winlen: the length of the analysis window in seconds. Default is 0.025s (25 milliseconds)
    :param winstep: the step between successive windows in seconds. Default is 0.01s (10 milliseconds)
    :param nfilt: the number of filters in the filterbank, default 26.
    :param nfft: the FFT size. Default is 512.
    :param lowfreq: lowest band edge of mel filters. In Hz, default is 0.
    :param highfreq: highest band edge of mel filters. In Hz, default is samplerate/2
    :param preemph: apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97.
    :param winfunc: the analysis window to apply to each frame. By default no window is applied. You can use numpy window functions here e.g. winfunc=numpy.hamming
    :returns: A numpy array of size (NUMFRAMES by nfilt) containing features. Each row holds 1 feature vector.
    """
    highfreq= highfreq or samplerate/2
    signal = sigproc.preemphasis(signal,preemph)
    frames = sigproc.framesig(signal, winlen*samplerate, winstep*samplerate, winfunc)
    pspec = sigproc.powspec(frames,nfft)
    pspec = numpy.where(pspec == 0,numpy.finfo(float).eps,pspec) # if things are all zeros we get problems

    fb = get_filterbanks(nfilt,nfft,samplerate,lowfreq,highfreq)
    feat = numpy.dot(pspec,fb.T) # compute the filterbank energies
    R = numpy.tile(numpy.linspace(1,samplerate/2,numpy.size(pspec,1)),(numpy.size(pspec,0),1))

    return numpy.dot(pspec*R,fb.T) / feat


Instruction:
Implement a Python 3 function for
computing a Mel - filterbank.

Response:
def get_filterbanks(nfilt=20,nfft=512,samplerate=16000,lowfreq=0,highfreq=None):
    """Compute a Mel-filterbank. The filters are stored in the rows, the columns correspond
    to fft bins. The filters are returned as an array of size nfilt * (nfft/2 + 1)

    :param nfilt: the number of filters in the filterbank, default 20.
    :param nfft: the FFT size. Default is 512.
    :param samplerate: the sample rate of the signal we are working with, in Hz. Affects mel spacing.
    :param lowfreq: lowest band edge of mel filters, default 0 Hz
    :param highfreq: highest band edge of mel filters, default samplerate/2
    :returns: A numpy array of size nfilt * (nfft/2 + 1) containing filterbank. Each row holds 1 filter.
    """
    highfreq= highfreq or samplerate/2
    assert highfreq <= samplerate/2, "highfreq is greater than samplerate/2"

    # compute points evenly spaced in mels
    lowmel = hz2mel(lowfreq)
    highmel = hz2mel(highfreq)
    melpoints = numpy.linspace(lowmel,highmel,nfilt+2)
    # our points are in Hz, but we use fft bins, so we have to convert
    #  from Hz to fft bin number
    bin = numpy.floor((nfft+1)*mel2hz(melpoints)/samplerate)

    fbank = numpy.zeros([nfilt,nfft//2+1])
    for j in range(0,nfilt):
        for i in range(int(bin[j]), int(bin[j+1])):
            fbank[j,i] = (i - bin[j]) / (bin[j+1]-bin[j])
        for i in range(int(bin[j+1]), int(bin[j+2])):
            fbank[j,i] = (bin[j+2]-i) / (bin[j+2]-bin[j+1])
    return fbank


Instruction:
Explain what the following Python 3 code does
def lifter(cepstra, L=22):
    if L > 0:
        nframes,ncoeff = numpy.shape(cepstra)
        n = numpy.arange(ncoeff)
        lift = 1 + (L/2.)*numpy.sin(numpy.pi*n/L)
        return lift*cepstra
    else:
        # values of L <= 0, do nothing
        return cepstra

Response: Apply a cepstral lifter to the matrix of cepstra.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def delta(feat, N):
    if N < 1:
        raise ValueError('N must be an integer >= 1')
    NUMFRAMES = len(feat)
    denominator = 2 * sum([i**2 for i in range(1, N+1)])
    delta_feat = numpy.empty_like(feat)
    padded = numpy.pad(feat, ((N, N), (0, 0)), mode='edge')   # padded version of feat
    for t in range(NUMFRAMES):
        delta_feat[t] = numpy.dot(numpy.arange(-N, N+1), padded[t : t+2*N+1]) / denominator   # [t : t+2*N+1] == [(N+t)-N : (N+t)+N+1]
    return delta_feat

Response: Compute delta features from a feature vector sequence.


Instruction:
Write a Python 3 function that can
open a CAN connection using the standard DLL interface.

Response:
def open(self, configuration, flags):
        """
        Opens a CAN connection using `CanalOpen()`.

        :param str configuration: the configuration: "device_id; baudrate"
        :param int flags: the flags to be set

        :raises can.CanError: if any error occurred
        :returns: Valid handle for CANAL API functions on success
        """
        try:
            # we need to convert this into bytes, since the underlying DLL cannot
            # handle non-ASCII configuration strings
            config_ascii = configuration.encode('ascii', 'ignore')
            result = self.__m_dllBasic.CanalOpen(config_ascii, flags)
        except Exception as ex:
            # catch any errors thrown by this call and re-raise
            raise can.CanError('CanalOpen() failed, configuration: "{}", error: {}'
                               .format(configuration, ex))
        else:
            # any greater-than-zero return value indicates a success
            # (see https://grodansparadis.gitbooks.io/the-vscp-daemon/canal_interface_specification.html)
            # raise an error if the return code is <= 0
            if result <= 0:
                raise can.CanError('CanalOpen() failed, configuration: "{}", return code: {}'
                                   .format(configuration, result))
            else:
                return result


Instruction:
Given the following Python 3 function, write the documentation
def read_all(self):
        result = self._cursor.execute("SELECT * FROM {}".format(self.table_name)).fetchall()
        return (SqliteReader._assemble_message(frame) for frame in result)

Response: Fetches all messages in the database.


Instruction:
Write a Python 3 function for
creating a new sqlite3 database and creates a table structure.

Response:
def _create_db(self):
        """Creates a new databae or opens a connection to an existing one.

        .. note::
            You can't share sqlite3 connections between threads (by default)
            hence we setup the db here. It has the upside of running async.
        """
        log.debug("Creating sqlite database")
        self._conn = sqlite3.connect(self._db_filename)

        # create table structure
        self._conn.cursor().execute("""
        CREATE TABLE IF NOT EXISTS {}
        (
          ts REAL,
          arbitration_id INTEGER,
          extended INTEGER,
          remote INTEGER,
          error INTEGER,
          dlc INTEGER,
          data BLOB
        )
        """.format(self.table_name))
        self._conn.commit()

        self._insert_template = "INSERT INTO {} VALUES (?, ?, ?, ?, ?, ?, ?)".format(self.table_name)


Instruction:
Here you have a function in Python 3, explain what it does
def stop(self):
        BufferedReader.stop(self)
        self._stop_running_event.set()
        self._writer_thread.join()
        BaseIOHandler.stop(self)

Response: Stops the reader an writes all remaining messages to the database.


Instruction:
Write a Python 3 script for
checking if the message parameters are valid.

Response:
def _check(self):
        """Checks if the message parameters are valid.
        Assumes that the types are already correct.

        :raises ValueError: iff one or more attributes are invalid
        """

        if self.timestamp < 0.0:
            raise ValueError("the timestamp may not be negative")
        if isinf(self.timestamp):
            raise ValueError("the timestamp may not be infinite")
        if isnan(self.timestamp):
            raise ValueError("the timestamp may not be NaN")

        if self.is_remote_frame and self.is_error_frame:
            raise ValueError("a message cannot be a remote and an error frame at the sane time")

        if self.arbitration_id < 0:
            raise ValueError("arbitration IDs may not be negative")

        if self.is_extended_id:
            if 0x20000000 <= self.arbitration_id:
                raise ValueError("Extended arbitration IDs must be less than 2^29")
        elif 0x800 <= self.arbitration_id:
            raise ValueError("Normal arbitration IDs must be less than 2^11")

        if self.dlc < 0:
            raise ValueError("DLC may not be negative")
        if self.is_fd:
            if 64 < self.dlc:
                raise ValueError("DLC was {} but it should be <= 64 for CAN FD frames".format(self.dlc))
        elif 8 < self.dlc:
            raise ValueError("DLC was {} but it should be <= 8 for normal CAN frames".format(self.dlc))

        if self.is_remote_frame:
            if self.data is not None and len(self.data) != 0:
                raise ValueError("remote frames may not carry any data")
        elif self.dlc != len(self.data):
            raise ValueError("the DLC and the length of the data must match up for non remote frames")

        if not self.is_fd:
            if self.bitrate_switch:
                raise ValueError("bitrate switch is only allowed for CAN FD frames")
            if self.error_state_indicator:
                raise ValueError("error state indicator is only allowed for CAN FD frames")


Instruction:
Write a Python 3 script for
comparing a given message with this one.

Response:
def equals(self, other, timestamp_delta=1.0e-6):
        """
        Compares a given message with this one.

        :param can.Message other: the message to compare with

        :type timestamp_delta: float or int or None
        :param timestamp_delta: the maximum difference at which two timestamps are
                                still considered equal or None to not compare timestamps

        :rtype: bool
        :return: True iff the given message equals this one
        """
        # see https://github.com/hardbyte/python-can/pull/413 for a discussion
        # on why a delta of 1.0e-6 was chosen
        return (
            # check for identity first and finish fast
            self is other or
            # then check for equality by value
            (
                (
                    timestamp_delta is None or
                    abs(self.timestamp - other.timestamp) <= timestamp_delta
                ) and
                self.arbitration_id == other.arbitration_id and
                self.is_extended_id == other.is_extended_id and
                self.dlc == other.dlc and
                self.data == other.data and
                self.is_remote_frame == other.is_remote_frame and
                self.is_error_frame == other.is_error_frame and
                self.channel == other.channel and
                self.is_fd == other.is_fd and
                self.bitrate_switch == other.bitrate_switch and
                self.error_state_indicator == other.error_state_indicator
            )
        )


Instruction:
Create a Python 3 function to
map and return a symbol from a C library.

Response:
def map_symbol(self, func_name, restype=None, argtypes=(), errcheck=None):
        """
        Map and return a symbol (function) from a C library. A reference to the
        mapped symbol is also held in the instance

        :param str func_name:
            symbol_name
        :param ctypes.c_* restype:
            function result type (i.e. ctypes.c_ulong...), defaults to void
        :param tuple(ctypes.c_* ... ) argtypes:
            argument types, defaults to no args
        :param callable errcheck:
            optional error checking function, see ctypes docs for _FuncPtr
        """
        if (argtypes):
            prototype = self.function_type(restype, *argtypes)
        else:
            prototype = self.function_type(restype)
        try:
            symbol = prototype((func_name, self))
        except AttributeError:
            raise ImportError("Could not map function '{}' from library {}".format(func_name, self._name))

        setattr(symbol, "_name", func_name)
        log.debug('Wrapped function "{}", result type: {}, error_check {}'.format(func_name, type(restype), errcheck))

        if (errcheck):
            symbol.errcheck = errcheck

        setattr(self, func_name, symbol)
        return symbol


Instruction:
Implement a Python 3 function for
decoding the serial number and return the ICS device serial string.

Response:
def get_serial_number(device):
        """Decode (if needed) and return the ICS device serial string

        :param device: ics device
        :return: ics device serial string
        :rtype: str
        """
        a0000 = 604661760
        if device.SerialNumber >= a0000:
            return ics.base36enc(device.SerialNumber)
        return str(device.SerialNumber)


Instruction:
Write a Python 3 script to
detect all configurations that this interface could have available for use in the bus constructor.

Response:
def _detect_available_configs():
        """Detect all configurations/channels that this interface could
        currently connect with.

        :rtype: Iterator[dict]
        :return: an iterable of dicts, each being a configuration suitable
                 for usage in the interface's bus constructor.
        """
        if ics is None:
            return []

        try:
            devices = ics.find_devices()
        except Exception as e:
            logger.debug("Failed to detect configs: %s", e)
            return []

        # TODO: add the channel(s)
        return [{
            'interface': 'neovi',
            'serial': NeoViBus.get_serial_number(device)
        } for device in devices]


Instruction:
Implement a Python 3 function for
building a CAN frame structure from a message.

Response:
def build_can_frame(msg):
    """ CAN frame packing/unpacking (see 'struct can_frame' in <linux/can.h>)
    /**
     * struct can_frame - basic CAN frame structure
     * @can_id:  the CAN ID of the frame and CAN_*_FLAG flags, see above.
     * @can_dlc: the data length field of the CAN frame
     * @data:    the CAN frame payload.
     */
    struct can_frame {
        canid_t can_id;  /* 32 bit CAN_ID + EFF/RTR/ERR flags */
        __u8    can_dlc; /* data length code: 0 .. 8 */
        __u8    data[8] __attribute__((aligned(8)));
    };

    /**
    * struct canfd_frame - CAN flexible data rate frame structure
    * @can_id: CAN ID of the frame and CAN_*_FLAG flags, see canid_t definition
    * @len:    frame payload length in byte (0 .. CANFD_MAX_DLEN)
    * @flags:  additional flags for CAN FD
    * @__res0: reserved / padding
    * @__res1: reserved / padding
    * @data:   CAN FD frame payload (up to CANFD_MAX_DLEN byte)
    */
    struct canfd_frame {
        canid_t can_id;  /* 32 bit CAN_ID + EFF/RTR/ERR flags */
        __u8    len;     /* frame payload length in byte */
        __u8    flags;   /* additional flags for CAN FD */
        __u8    __res0;  /* reserved / padding */
        __u8    __res1;  /* reserved / padding */
        __u8    data[CANFD_MAX_DLEN] __attribute__((aligned(8)));
    };
    """
    can_id = _add_flags_to_can_id(msg)
    flags = 0
    if msg.bitrate_switch:
        flags |= CANFD_BRS
    if msg.error_state_indicator:
        flags |= CANFD_ESI
    max_len = 64 if msg.is_fd else 8
    data = bytes(msg.data).ljust(max_len, b'\x00')
    return CAN_FRAME_HEADER_STRUCT.pack(can_id, msg.dlc, flags) + data


Instruction:
Can you implement a function in Python 3 that
creates a broadcast manager socket and connect to the given interface

Response:
def create_bcm_socket(channel):
    """create a broadcast manager socket and connect to the given interface"""
    s = socket.socket(PF_CAN, socket.SOCK_DGRAM, CAN_BCM)
    if HAS_NATIVE_SUPPORT:
        s.connect((channel,))
    else:
        addr = get_addr(s, channel)
        libc.connect(s.fileno(), addr, len(addr))
    return s


Instruction:
Can you write a function in Python 3 where it
sends raw frame to a BCM socket and handle errors.

Response:
def send_bcm(bcm_socket, data):
    """
    Send raw frame to a BCM socket and handle errors.
    """
    try:
        return bcm_socket.send(data)
    except OSError as e:
        base = "Couldn't send CAN BCM frame. OS Error {}: {}\n".format(e.errno, e.strerror)

        if e.errno == errno.EINVAL:
            raise can.CanError(base + "You are probably referring to a non-existing frame.")

        elif e.errno == errno.ENETDOWN:
            raise can.CanError(base + "The CAN interface appears to be down.")

        elif e.errno == errno.EBADF:
            raise can.CanError(base + "The CAN socket appears to be closed.")

        else:
            raise e


Instruction:
Implement a function in Python 3 to
create a raw CAN socket.

Response:
def create_socket():
    """Creates a raw CAN socket. The socket will
    be returned unbound to any interface.
    """
    sock = socket.socket(PF_CAN, socket.SOCK_RAW, CAN_RAW)

    log.info('Created a socket')

    return sock


Instruction:
Implement a Python 3 function for
binding the given socket to the specified interface.

Response:
def bind_socket(sock, channel='can0'):
    """
    Binds the given socket to the given interface.

    :param socket.socket sock:
        The socket to be bound
    :raises OSError:
        If the specified interface isn't found.
    """
    log.debug('Binding socket to channel=%s', channel)
    if HAS_NATIVE_SUPPORT:
        sock.bind((channel,))
    else:
        # For Python 2.7
        addr = get_addr(sock, channel)
        libc.bind(sock.fileno(), addr, len(addr))
    log.debug('Bound socket.')


Instruction:
Given the following Python 3 function, write the documentation
def capture_message(sock, get_channel=False):
    # Fetching the Arb ID, DLC and Data
    try:
        if get_channel:
            if HAS_NATIVE_SUPPORT:
                cf, addr = sock.recvfrom(CANFD_MTU)
                channel = addr[0] if isinstance(addr, tuple) else addr
            else:
                data = ctypes.create_string_buffer(CANFD_MTU)
                addr = ctypes.create_string_buffer(32)
                addrlen = ctypes.c_int(len(addr))
                received = libc.recvfrom(sock.fileno(), data, len(data), 0,
                                         addr, ctypes.byref(addrlen))
                cf = data.raw[:received]
                # Figure out the channel name
                family, ifindex = struct.unpack_from("Hi", addr.raw)
                assert family == AF_CAN
                data = struct.pack("16xi", ifindex)
                res = fcntl.ioctl(sock, SIOCGIFNAME, data)
                channel = ctypes.create_string_buffer(res).value.decode()
        else:
            cf = sock.recv(CANFD_MTU)
            channel = None
    except socket.error as exc:
        raise can.CanError("Error receiving: %s" % exc)

    can_id, can_dlc, flags, data = dissect_can_frame(cf)
    #log.debug('Received: can_id=%x, can_dlc=%x, data=%s', can_id, can_dlc, data)

    # Fetching the timestamp
    binary_structure = "@LL"
    res = fcntl.ioctl(sock, SIOCGSTAMP, struct.pack(binary_structure, 0, 0))

    seconds, microseconds = struct.unpack(binary_structure, res)
    timestamp = seconds + microseconds * 1e-6

    # EXT, RTR, ERR flags -> boolean attributes
    #   /* special address description flags for the CAN_ID */
    #   #define CAN_EFF_FLAG 0x80000000U /* EFF/SFF is set in the MSB */
    #   #define CAN_RTR_FLAG 0x40000000U /* remote transmission request */
    #   #define CAN_ERR_FLAG 0x20000000U /* error frame */
    is_extended_frame_format = bool(can_id & CAN_EFF_FLAG)
    is_remote_transmission_request = bool(can_id & CAN_RTR_FLAG)
    is_error_frame = bool(can_id & CAN_ERR_FLAG)
    is_fd = len(cf) == CANFD_MTU
    bitrate_switch = bool(flags & CANFD_BRS)
    error_state_indicator = bool(flags & CANFD_ESI)

    if is_extended_frame_format:
        #log.debug("CAN: Extended")
        # TODO does this depend on SFF or EFF?
        arbitration_id = can_id & 0x1FFFFFFF
    else:
        #log.debug("CAN: Standard")
        arbitration_id = can_id & 0x000007FF

    msg = Message(timestamp=timestamp,
                  channel=channel,
                  arbitration_id=arbitration_id,
                  is_extended_id=is_extended_frame_format,
                  is_remote_frame=is_remote_transmission_request,
                  is_error_frame=is_error_frame,
                  is_fd=is_fd,
                  bitrate_switch=bitrate_switch,
                  error_state_indicator=error_state_indicator,
                  dlc=can_dlc,
                  data=data)

    #log_rx.debug('Received: %s', msg)

    return msg

Response: Captures a message from given socket.


Instruction:
Can you tell what is the following Python 3 function doing
def stop(self):
        log.debug("Stopping periodic task")

        stopframe = build_bcm_tx_delete_header(self.can_id_with_flags, self.flags)
        send_bcm(self.bcm_socket, stopframe)

Response: Send a TX_DELETE message to cancel this task.


Instruction:
Write a Python 3 function that can
update the contents of this message.

Response:
def modify_data(self, message):
        """Update the contents of this periodically sent message.

        Note the Message must have the same :attr:`~can.Message.arbitration_id`
        like the first message.
        """
        assert message.arbitration_id == self.can_id, "You cannot modify the can identifier"
        self.message = message
        header = build_bcm_update_header(self.can_id_with_flags, self.flags)
        frame = build_can_frame(message)
        send_bcm(self.bcm_socket, header + frame)


Instruction:
Implement a Python 3 function for
stopping all active periodic tasks and closes the socket.

Response:
def shutdown(self):
        """Stops all active periodic tasks and closes the socket."""
        self.stop_all_periodic_tasks()
        for channel in self._bcm_sockets:
            log.debug("Closing bcm socket for channel {}".format(channel))
            bcm_socket = self._bcm_sockets[channel]
            bcm_socket.close()
        log.debug("Closing raw can socket")
        self.socket.close()


Instruction:
Write a Python 3 script to
transmit a message to the CAN bus.

Response:
def send(self, msg, timeout=None):
        """Transmit a message to the CAN bus.

        :param can.Message msg: A message object.
        :param float timeout:
            Wait up to this many seconds for the transmit queue to be ready.
            If not given, the call may fail immediately.

        :raises can.CanError:
            if the message could not be written.
        """
        log.debug("We've been asked to write a message to the bus")
        logger_tx = log.getChild("tx")
        logger_tx.debug("sending: %s", msg)

        started = time.time()
        # If no timeout is given, poll for availability
        if timeout is None:
            timeout = 0
        time_left = timeout
        data = build_can_frame(msg)

        while time_left >= 0:
            # Wait for write availability
            ready = select.select([], [self.socket], [], time_left)[1]
            if not ready:
                # Timeout
                break
            sent = self._send_once(data, msg.channel)
            if sent == len(data):
                return
            # Not all data were sent, try again with remaining data
            data = data[sent:]
            time_left = timeout - (time.time() - started)

        raise can.CanError("Transmit buffer full")


Instruction:
How would you code a function in Python 3 to
start sending a message at a given period on this bus. The kernel's broadcast manager will be used. :param can.Message msg: Message to transmit :param float period: Period in seconds between each message :param float duration: The duration to keep sending this message at given rate. If no duration is provided, the task will continue indefinitely. :return: A started task instance. This can be used to modify the data, pause/resume the transmission and to stop the transmission. :rtype: can.interfaces.socketcan.CyclicSendTask .. note:: Note the duration before the message stops being sent may not be exactly the same as the duration specified by the user. In general the message will be sent at the given rate until at least *duration* seconds.

Response:
def _send_periodic_internal(self, msg, period, duration=None):
        """Start sending a message at a given period on this bus.

        The kernel's broadcast manager will be used.

        :param can.Message msg:
            Message to transmit
        :param float period:
            Period in seconds between each message
        :param float duration:
            The duration to keep sending this message at given rate. If
            no duration is provided, the task will continue indefinitely.

        :return:
            A started task instance. This can be used to modify the data,
            pause/resume the transmission and to stop the transmission.
        :rtype: can.interfaces.socketcan.CyclicSendTask

        .. note::

            Note the duration before the message stops being sent may not
            be exactly the same as the duration specified by the user. In
            general the message will be sent at the given rate until at
            least *duration* seconds.

        """
        bcm_socket = self._get_bcm_socket(msg.channel or self.channel)
        task = CyclicSendTask(bcm_socket, msg, period, duration)
        return task


Instruction:
Can you generate a brief explanation for the following Python 3 code
def find_serial_devices(serial_matcher="ED"):
    objWMIService = win32com.client.Dispatch("WbemScripting.SWbemLocator")
    objSWbemServices = objWMIService.ConnectServer(".", "root\cimv2")
    items = objSWbemServices.ExecQuery("SELECT * FROM Win32_USBControllerDevice")
    ids = (item.Dependent.strip('"')[-8:] for item in items)
    return [e for e in ids if e.startswith(serial_matcher)]

Response: Find USB devices that start with the given serial number.


Instruction:
Write a Python 3 function for
returning the names of all open can interfaces using ip link list.

Response:
def find_available_interfaces():
    """Returns the names of all open can/vcan interfaces using
    the ``ip link list`` command. If the lookup fails, an error
    is logged to the console and an empty list is returned.

    :rtype: an iterable of :class:`str`
    """

    try:
        # it might be good to add "type vcan", but that might (?) exclude physical can devices
        command = ["ip", "-o", "link", "list", "up"]
        output = subprocess.check_output(command, universal_newlines=True)

    except Exception as e: # subprocess.CalledProcessError was too specific
        log.error("failed to fetch opened can devices: %s", e)
        return []

    else:
        #log.debug("find_available_interfaces(): output=\n%s", output)
        # output contains some lines like "1: vcan42: <NOARP,UP,LOWER_UP> ..."
        # extract the "vcan42" of each line
        interface_names = [line.split(": ", 3)[1] for line in output.splitlines()]
        log.debug("find_available_interfaces(): detected: %s", interface_names)
        return filter(_PATTERN_CAN_INTERFACE.match, interface_names)


Instruction:
Write a Python 3 script to
convert an error code to a useful and human readable string.

Response:
def error_code_to_str(code):
    """
    Converts a given error code (errno) to a useful and human readable string.

    :param int code: a possibly invalid/unknown error code
    :rtype: str
    :returns: a string explaining and containing the given error code, or a string
              explaining that the errorcode is unknown if that is the case
    """

    try:
        name = errno.errorcode[code]
    except KeyError:
        name = "UNKNOWN"

    try:
        description = os.strerror(code)
    except ValueError:
        description = "no description available"

    return "{} (errno {}): {}".format(name, code, description)


Instruction:
Here you have a function in Python 3, explain what it does
def producer(id, message_count=16):

    with can.Bus(bustype='socketcan', channel='vcan0') as bus:
        for i in range(message_count):
            msg = can.Message(arbitration_id=0x0cf02200+id, data=[id, i, 0, 1, 3, 1, 4, 1])
            bus.send(msg)
        sleep(1.0)

    print("Producer #{} finished sending {} messages".format(id, message_count))

Response: Spam the bus with messages including the data id.


Instruction:
Create a Python 3 function to
append a message to the buffer.

Response:
def on_message_received(self, msg):
        """Append a message to the buffer.

        :raises: BufferError
            if the reader has already been stopped
        """
        if self.is_stopped:
            raise RuntimeError("reader has already been stopped")
        else:
            self.buffer.put(msg)


Instruction:
Here you have a function in Python 3, explain what it does
def get_message(self, timeout=0.5):
        try:
            return self.buffer.get(block=not self.is_stopped, timeout=timeout)
        except Empty:
            return None

Response: Retrieves the latest message from the buffer.


Instruction:
Write a Python 3 script for
getting the error text from the GetErrorText API call.

Response:
def _get_formatted_error(self, error):
        """
        Gets the text using the GetErrorText API function.
        If the function call succeeds, the translated error is returned. If it fails,
        a text describing the current error is returned. Multiple errors may
        be present in which case their individual messages are included in the
        return string, one line per error.
        """

        def bits(n):
            """TODO: document"""
            while n:
                b = n & (~n+1)
                yield b
                n ^= b

        stsReturn = self.m_objPCANBasic.GetErrorText(error, 0)
        if stsReturn[0] != PCAN_ERROR_OK:
            strings = []

            for b in bits(error):
                stsReturn = self.m_objPCANBasic.GetErrorText(b, 0)
                if stsReturn[0] != PCAN_ERROR_OK:
                    text = "An error occurred. Error-code's text ({0:X}h) couldn't be retrieved".format(error)
                else:
                    text = stsReturn[1].decode('utf-8', errors='replace')

                strings.append(text)

            complete_text = '\n'.join(strings)
        else:
            complete_text = stsReturn[1].decode('utf-8', errors='replace')

        return complete_text


Instruction:
Here you have a function in Python 3, explain what it does
def reset(self):
        status = self.m_objPCANBasic.Reset(self.m_PcanHandle)
        return status == PCAN_ERROR_OK

Response: Reset the PCAN bus after an error.


Instruction:
Write a Python 3 function for
turning on or off flashing of the device s LED for physical identification purposes.

Response:
def flash(self, flash):
        """
        Turn on or off flashing of the device's LED for physical
        identification purposes.
        """
        self.m_objPCANBasic.SetValue(self.m_PcanHandle, PCAN_CHANNEL_IDENTIFYING, bool(flash))


Instruction:
Write a Python 3 script for
converting status code to descriptive string.

Response:
def get_error_message(status_code):
    """Convert status code to descriptive string."""
    errmsg = ctypes.create_string_buffer(1024)
    nican.ncStatusToString(status_code, len(errmsg), errmsg)
    return errmsg.value.decode("ascii")


Instruction:
Can you generate a brief explanation for the following Python 3 code
def _recv_internal(self, timeout):
        if timeout is None:
            timeout = NC_DURATION_INFINITE
        else:
            timeout = int(timeout * 1000)

        state = ctypes.c_ulong()
        try:
            nican.ncWaitForState(
                self.handle, NC_ST_READ_AVAIL, timeout, ctypes.byref(state))
        except NicanError as e:
            if e.error_code == TIMEOUT_ERROR_CODE:
                return None, True
            else:
                raise

        raw_msg = RxMessageStruct()
        nican.ncRead(self.handle, ctypes.sizeof(raw_msg), ctypes.byref(raw_msg))
        # http://stackoverflow.com/questions/6161776/convert-windows-filetime-to-second-in-unix-linux
        timestamp = raw_msg.timestamp / 10000000.0 - 11644473600
        is_remote_frame = raw_msg.frame_type == NC_FRMTYPE_REMOTE
        is_error_frame = raw_msg.frame_type == NC_FRMTYPE_COMM_ERR
        is_extended = bool(raw_msg.arb_id & NC_FL_CAN_ARBID_XTD)
        arb_id = raw_msg.arb_id
        if not is_error_frame:
            arb_id &= 0x1FFFFFFF
        dlc = raw_msg.dlc
        msg = Message(timestamp=timestamp,
                      channel=self.channel,
                      is_remote_frame=is_remote_frame,
                      is_error_frame=is_error_frame,
                      is_extended_id=is_extended,
                      arbitration_id=arb_id,
                      dlc=dlc,
                      data=raw_msg.data[:dlc])
        return msg, True

Response: Internal method to read a message from a NI - CAN bus.


Instruction:
Can you create a Python 3 function that
sends a message to the NI - CAN controller.

Response:
def send(self, msg, timeout=None):
        """
        Send a message to NI-CAN.

        :param can.Message msg:
            Message to send

        :raises can.interfaces.nican.NicanError:
            If writing to transmit buffer fails.
            It does not wait for message to be ACKed currently.
        """
        arb_id = msg.arbitration_id
        if msg.is_extended_id:
            arb_id |= NC_FL_CAN_ARBID_XTD
        raw_msg = TxMessageStruct(arb_id,
                                  bool(msg.is_remote_frame),
                                  msg.dlc,
                                  CanData(*msg.data))
        nican.ncWrite(
            self.handle, ctypes.sizeof(raw_msg), ctypes.byref(raw_msg))


Instruction:
Explain what the following Python 3 code does
def set_filters(self, can_filers=None):
        if self.__set_filters_has_been_called:
            logger.warn("using filters is not supported like this, see note on NicanBus")
        else:
            # allow the constructor to call this without causing a warning
            self.__set_filters_has_been_called = True

Response: Set the filters for this object.


Instruction:
How would you explain what the following Python 3 function does
def send_periodic(bus, message, period, *args, **kwargs):
    warnings.warn("The function `can.send_periodic` is deprecated and will " +
                  "be removed in an upcoming version. Please use `can.Bus.send_periodic` instead.", DeprecationWarning)
    return bus.send_periodic(message, period, *args, **kwargs)

Response: Send a message periodically on the given bus.


Instruction:
How would you explain what the following Python 3 function does
def _recv_internal(self, timeout=None):
        arb_id = ctypes.c_long(0)
        data = ctypes.create_string_buffer(64)
        dlc = ctypes.c_uint(0)
        flags = ctypes.c_uint(0)
        timestamp = ctypes.c_ulong(0)

        if timeout is None:
            # Set infinite timeout
            # http://www.kvaser.com/canlib-webhelp/group___c_a_n.html#ga2edd785a87cc16b49ece8969cad71e5b
            timeout = 0xFFFFFFFF
        else:
            timeout = int(timeout * 1000)

        #log.log(9, 'Reading for %d ms on handle: %s' % (timeout, self._read_handle))
        status = canReadWait(
            self._read_handle,
            ctypes.byref(arb_id),
            ctypes.byref(data),
            ctypes.byref(dlc),
            ctypes.byref(flags),
            ctypes.byref(timestamp),
            timeout  # This is an X ms blocking read
        )

        if status == canstat.canOK:
            #log.debug('read complete -> status OK')
            data_array = data.raw
            flags = flags.value
            is_extended = bool(flags & canstat.canMSG_EXT)
            is_remote_frame = bool(flags & canstat.canMSG_RTR)
            is_error_frame = bool(flags & canstat.canMSG_ERROR_FRAME)
            is_fd = bool(flags & canstat.canFDMSG_FDF)
            bitrate_switch = bool(flags & canstat.canFDMSG_BRS)
            error_state_indicator = bool(flags & canstat.canFDMSG_ESI)
            msg_timestamp = timestamp.value * TIMESTAMP_FACTOR
            rx_msg = Message(arbitration_id=arb_id.value,
                             data=data_array[:dlc.value],
                             dlc=dlc.value,
                             is_extended_id=is_extended,
                             is_error_frame=is_error_frame,
                             is_remote_frame=is_remote_frame,
                             is_fd=is_fd,
                             bitrate_switch=bitrate_switch,
                             error_state_indicator=error_state_indicator,
                             channel=self.channel,
                             timestamp=msg_timestamp + self._timestamp_offset)
            #log.debug('Got message: %s' % rx_msg)
            return rx_msg, self._is_filtered
        else:
            #log.debug('read complete -> status not okay')
            return None, self._is_filtered

Response: Read a message from the kvaser device and return whether filtering has taken place.


Instruction:
Explain what the following Python 3 code does
def flash(self, flash=True):
        if flash:
            action = canstat.kvLED_ACTION_ALL_LEDS_ON
        else:
            action = canstat.kvLED_ACTION_ALL_LEDS_OFF

        try:
            kvFlashLeds(self._read_handle, action, 30000)
        except (CANLIBError, NotImplementedError) as e:
            log.error('Could not flash LEDs (%s)', e)

Response: Flash the LEDs of the device.


Instruction:
Can you implement a function in Python 3 that
retrieves the bus statistics.

Response:
def get_stats(self):
        """Retrieves the bus statistics.

        Use like so:

        >>> stats = bus.get_stats()
        >>> print(stats)
        std_data: 0, std_remote: 0, ext_data: 0, ext_remote: 0, err_frame: 0, bus_load: 0.0%, overruns: 0

        :returns: bus statistics.
        :rtype: can.interfaces.kvaser.structures.BusStatistics
         """
        canRequestBusStatistics(self._write_handle)
        stats = structures.BusStatistics()
        canGetBusStatistics(self._write_handle,
                            ctypes.pointer(stats),
                            ctypes.sizeof(stats))
        return stats


Instruction:
Create a Python 3 function for
formatting a VCI error and attach failed function decoded HRESULT and arguments tuple

Response:
def __vciFormatErrorExtended(library_instance, function, HRESULT, arguments):
    """ Format a VCI error and attach failed function, decoded HRESULT and arguments
        :param CLibrary library_instance:
            Mapped instance of IXXAT vcinpl library
        :param callable function:
            Failed function
        :param HRESULT HRESULT:
            HRESULT returned by vcinpl call
        :param arguments:
            Arbitrary arguments tuple
        :return:
            Formatted string
    """
    #TODO: make sure we don't generate another exception
    return "{} - arguments were {}".format(
        __vciFormatError(library_instance, function, HRESULT),
        arguments
    )


Instruction:
How would you code a function in Python 3 to
format a VCI error and attach failed function and decoded HRESULT to the result of the call to the caller.

Response:
def __vciFormatError(library_instance, function, HRESULT):
    """ Format a VCI error and attach failed function and decoded HRESULT
        :param CLibrary library_instance:
            Mapped instance of IXXAT vcinpl library
        :param callable function:
            Failed function
        :param HRESULT HRESULT:
            HRESULT returned by vcinpl call
        :return:
            Formatted string
    """
    buf = ctypes.create_string_buffer(constants.VCI_MAX_ERRSTRLEN)
    ctypes.memset(buf, 0, constants.VCI_MAX_ERRSTRLEN)
    library_instance.vciFormatError(HRESULT, buf, constants.VCI_MAX_ERRSTRLEN)
    return "function {} failed ({})".format(function._name, buf.value.decode('utf-8', 'replace'))


Instruction:
Given the following Python 3 function, write the documentation
def __check_status(result, function, arguments):
    if isinstance(result, int):
        # Real return value is an unsigned long
        result = ctypes.c_ulong(result).value

    if result == constants.VCI_E_TIMEOUT:
        raise VCITimeout("Function {} timed out".format(function._name))
    elif result == constants.VCI_E_RXQUEUE_EMPTY:
        raise VCIRxQueueEmptyError()
    elif result == constants.VCI_E_NO_MORE_ITEMS:
        raise StopIteration()
    elif result == constants.VCI_E_ACCESSDENIED:
        pass # not a real error, might happen if another program has initialized the bus
    elif result != constants.VCI_OK:
        raise VCIError(vciFormatError(function, result))

    return result

Response:
Check the result of a vcinpl function call and raise appropriate exception
            in case of an error.


Instruction:
Can you implement a function in Python 3 that
reads a message from the device.

Response:
def _recv_internal(self, timeout):
        """ Read a message from IXXAT device. """

        # TODO: handling CAN error messages?
        data_received = False

        if timeout == 0:
            # Peek without waiting
            try:
                _canlib.canChannelPeekMessage(self._channel_handle, ctypes.byref(self._message))
            except (VCITimeout, VCIRxQueueEmptyError):
                return None, True
            else:
                if self._message.uMsgInfo.Bits.type == constants.CAN_MSGTYPE_DATA:
                    data_received = True
        else:
            # Wait if no message available
            if timeout is None or timeout < 0:
                remaining_ms = constants.INFINITE
                t0 = None
            else:
                timeout_ms = int(timeout * 1000)
                remaining_ms = timeout_ms
                t0 = _timer_function()

            while True:
                try:
                    _canlib.canChannelReadMessage(self._channel_handle, remaining_ms, ctypes.byref(self._message))
                except (VCITimeout, VCIRxQueueEmptyError):
                    # Ignore the 2 errors, the timeout is handled manually with the _timer_function()
                    pass
                else:
                    # See if we got a data or info/error messages
                    if self._message.uMsgInfo.Bits.type == constants.CAN_MSGTYPE_DATA:
                        data_received = True
                        break

                    elif self._message.uMsgInfo.Bits.type == constants.CAN_MSGTYPE_INFO:
                        log.info(CAN_INFO_MESSAGES.get(self._message.abData[0], "Unknown CAN info message code {}".format(self._message.abData[0])))

                    elif self._message.uMsgInfo.Bits.type == constants.CAN_MSGTYPE_ERROR:
                        log.warning(CAN_ERROR_MESSAGES.get(self._message.abData[0], "Unknown CAN error message code {}".format(self._message.abData[0])))

                    elif self._message.uMsgInfo.Bits.type == constants.CAN_MSGTYPE_TIMEOVR:
                        pass
                    else:
                        log.warn("Unexpected message info type")

                if t0 is not None:
                    remaining_ms = timeout_ms - int((_timer_function() - t0) * 1000)
                    if remaining_ms < 0:
                        break

        if not data_received:
            # Timed out / can message type is not DATA
            return None, True

        # The _message.dwTime is a 32bit tick value and will overrun,
        # so expect to see the value restarting from 0
        rx_msg = Message(
            timestamp=self._message.dwTime / self._tick_resolution,  # Relative time in s
            is_remote_frame=True if self._message.uMsgInfo.Bits.rtr else False,
            is_extended_id=True if self._message.uMsgInfo.Bits.ext else False,
            arbitration_id=self._message.dwMsgId,
            dlc=self._message.uMsgInfo.Bits.dlc,
            data=self._message.abData[:self._message.uMsgInfo.Bits.dlc],
            channel=self.channel
        )

        return rx_msg, True


Instruction:
Implement a function in Python 3 to
send a message using built - in cyclic transmit list functionality.

Response:
def _send_periodic_internal(self, msg, period, duration=None):
        """Send a message using built-in cyclic transmit list functionality."""
        if self._scheduler is None:
            self._scheduler = HANDLE()
            _canlib.canSchedulerOpen(self._device_handle, self.channel,
                                     self._scheduler)
            caps = structures.CANCAPABILITIES()
            _canlib.canSchedulerGetCaps(self._scheduler, caps)
            self._scheduler_resolution = float(caps.dwClockFreq) / caps.dwCmsDivisor
            _canlib.canSchedulerActivate(self._scheduler, constants.TRUE)
        return CyclicSendTask(self._scheduler, msg, period, duration,
                              self._scheduler_resolution)


Instruction:
Create a Python 3 function for
setting the filters for this object.

Response:
def set_filters(self, can_filers=None):
        """Unsupported. See note on :class:`~can.interfaces.ixxat.IXXATBus`.
        """
        if self.__set_filters_has_been_called:
            log.warn("using filters is not supported like this, see note on IXXATBus")
        else:
            # allow the constructor to call this without causing a warning
            self.__set_filters_has_been_called = True


Instruction:
Implement a function in Python 3 to
start transmitting a message.

Response:
def start(self):
        """Start transmitting message (add to list if needed)."""
        if self._index is None:
            self._index = ctypes.c_uint32()
            _canlib.canSchedulerAddMessage(self._scheduler,
                                           self._msg,
                                           self._index)
        _canlib.canSchedulerStartMessage(self._scheduler,
                                         self._index,
                                         self._count)


Instruction:
Explain what the following Python 3 code does
def stop(self):
        # Remove it completely instead of just stopping it to avoid filling up
        # the list with permanently stopped messages
        _canlib.canSchedulerRemMessage(self._scheduler, self._index)
        self._index = None

Response: Stop transmitting a message from the scheduler.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def log_event(self, text, timestamp=None):
        try:
            # Only works on Windows
            text = text.encode("mbcs")
        except LookupError:
            text = text.encode("ascii")
        comment = b"Added by python-can"
        marker = b"python-can"
        data = GLOBAL_MARKER_STRUCT.pack(
            0, 0xFFFFFF, 0xFF3300, 0, len(text), len(marker), len(comment))
        self._add_object(GLOBAL_MARKER, data + text + marker + comment, timestamp)

Response: Add an arbitrary message to the log file as a global marker.


Instruction:
How would you code a function in Python 3 to
compress and writes data in the cache to file.

Response:
def _flush(self):
        """Compresses and writes data in the cache to file."""
        if self.file.closed:
            return
        cache = b"".join(self.cache)
        if not cache:
            # Nothing to write
            return
        uncompressed_data = cache[:self.MAX_CACHE_SIZE]
        # Save data that comes after max size to next round
        tail = cache[self.MAX_CACHE_SIZE:]
        self.cache = [tail]
        self.cache_size = len(tail)
        compressed_data = zlib.compress(uncompressed_data,
                                        self.COMPRESSION_LEVEL)
        obj_size = (OBJ_HEADER_V1_STRUCT.size + LOG_CONTAINER_STRUCT.size +
                    len(compressed_data))
        base_header = OBJ_HEADER_BASE_STRUCT.pack(
            b"LOBJ", OBJ_HEADER_BASE_STRUCT.size, 1, obj_size, LOG_CONTAINER)
        container_header = LOG_CONTAINER_STRUCT.pack(
            ZLIB_DEFLATE, len(uncompressed_data))
        self.file.write(base_header)
        self.file.write(container_header)
        self.file.write(compressed_data)
        # Write padding bytes
        self.file.write(b"\x00" * (obj_size % 4))
        self.uncompressed_size += OBJ_HEADER_V1_STRUCT.size + LOG_CONTAINER_STRUCT.size
        self.uncompressed_size += len(uncompressed_data)


Instruction:
Can you tell what is the following Python 3 function doing
def stop(self):
        self._flush()
        filesize = self.file.tell()
        super(BLFWriter, self).stop()

        # Write header in the beginning of the file
        header = [b"LOGG", FILE_HEADER_SIZE,
                  APPLICATION_ID, 0, 0, 0, 2, 6, 8, 1]
        # The meaning of "count of objects read" is unknown
        header.extend([filesize, self.uncompressed_size,
                       self.count_of_objects, 0])
        header.extend(timestamp_to_systemtime(self.start_timestamp))
        header.extend(timestamp_to_systemtime(self.stop_timestamp))
        with open(self.file.name, "r+b") as f:
            f.write(FILE_HEADER_STRUCT.pack(*header))

Response: Stops logging and closes the file.


Instruction:
How would you implement a function in Python 3 that
initializes a PCAN Channel and return a TPCANStatus object.

Response:
def Initialize(
        self,
        Channel,
        Btr0Btr1,
        HwType = TPCANType(0),
        IOPort = c_uint(0),
        Interrupt = c_ushort(0)):

        """
          Initializes a PCAN Channel

        Parameters:
          Channel  : A TPCANHandle representing a PCAN Channel
          Btr0Btr1 : The speed for the communication (BTR0BTR1 code)
          HwType   : NON PLUG&PLAY: The type of hardware and operation mode
          IOPort   : NON PLUG&PLAY: The I/O address for the parallel port
          Interrupt: NON PLUG&PLAY: Interrupt number of the parallel port

        Returns:
          A TPCANStatus error code
        """
        try:
            res = self.__m_dllBasic.CAN_Initialize(Channel,Btr0Btr1,HwType,IOPort,Interrupt)
            return TPCANStatus(res)
        except:
            logger.error("Exception on PCANBasic.Initialize")
            raise


Instruction:
How would you explain what the following Python 3 function does
def InitializeFD(
        self,
        Channel,
        BitrateFD):

        """
          Initializes a FD capable PCAN Channel

        Parameters:
          Channel  : The handle of a FD capable PCAN Channel
          BitrateFD : The speed for the communication (FD bit rate string)

    Remarks:
      See PCAN_BR_* values.
          * parameter and values must be separated by '='
          * Couples of Parameter/value must be separated by ','
          * Following Parameter must be filled out: f_clock, data_brp, data_sjw, data_tseg1, data_tseg2,
            nom_brp, nom_sjw, nom_tseg1, nom_tseg2.
          * Following Parameters are optional (not used yet): data_ssp_offset, nom_samp

        Example:
          f_clock=80000000,nom_brp=10,nom_tseg1=5,nom_tseg2=2,nom_sjw=1,data_brp=4,data_tseg1=7,data_tseg2=2,data_sjw=1

        Returns:
          A TPCANStatus error code
        """
        try:
            res = self.__m_dllBasic.CAN_InitializeFD(Channel,BitrateFD)
            return TPCANStatus(res)
        except:
            logger.error("Exception on PCANBasic.InitializeFD")
            raise

Response: This method initializes a FD capable PCAN Channel and returns a TPCANStatus object.


Instruction:
How would you implement a function in Python 3 that
resets the receive and transmit queues of a PCAN Channel.

Response:
def Reset(
        self,
        Channel):

        """
          Resets the receive and transmit queues of the PCAN Channel

        Remarks:
          A reset of the CAN controller is not performed

        Parameters:
          Channel  : A TPCANHandle representing a PCAN Channel

        Returns:
          A TPCANStatus error code
        """
        try:
            res = self.__m_dllBasic.CAN_Reset(Channel)
            return TPCANStatus(res)
        except:
            logger.error("Exception on PCANBasic.Reset")
            raise