Python API Documentation

SnipeSig

A class to handle Sourmash signatures with additional functionalities such as customized set operations and abundance management.

Source code in src/snipe/api/snipe_sig.py

class SnipeSig:
    """
    A class to handle Sourmash signatures with additional functionalities
    such as customized set operations and abundance management.
    """

    def __init__(self, *, 
                 sourmash_sig: Union[str, sourmash.signature.SourmashSignature, sourmash.signature.FrozenSourmashSignature], 
                 sig_type=SigType.SAMPLE, enable_logging: bool = False, **kwargs):
        r"""
        Initialize the SnipeSig with a sourmash signature object or a path to a signature.

        Parameters:
            sourmash_sig (str or sourmash.signature.SourmashSignature): A path to a signature file or a signature object.
            ksize (int): K-mer size.
            scale (int): Scale value.
            sig_type (SigType): Type of the signature.
            enable_logging (bool): Flag to enable detailed logging.
            **kwargs: Additional keyword arguments.
        """
        # Initialize logging based on the flag
        self.logger = logging.getLogger(self.__class__.__name__)

        # Configure the logger
        if enable_logging:
            self.logger.setLevel(logging.DEBUG)
            if not self.logger.hasHandlers():
                # Create console handler
                ch = logging.StreamHandler()
                ch.setLevel(logging.DEBUG)
                # Create formatter
                formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
                # Add formatter to handler
                ch.setFormatter(formatter)
                # Add handler to logger
                self.logger.addHandler(ch)
            self.logger.debug("Logging is enabled for SnipeSig.")
        else:
            self.logger.setLevel(logging.CRITICAL)

        # Initialize internal variables
        self.logger.debug("Initializing SnipeSig with sourmash_sig: %s", sourmash_sig)

        self._scale: int = None
        self._ksize: int = None
        self._md5sum: str = None
        self._hashes = np.array([], dtype=np.uint64)
        self._abundances = np.array([], dtype=np.uint32)
        self._type: SigType = sig_type
        self._name: str = None
        self._filename: str = None
        self._track_abundance: bool = True

        sourmash_sigs: Dict[str, sourmash.signature.SourmashSignature] = {}
        _sourmash_sig: Union[sourmash.signature.SourmashSignature, sourmash.signature.FrozenSourmashSignature] = None

        self.chr_to_sig: Dict[str, SnipeSig] = {}


        self.logger.debug("Proceeding with a sigtype of %s", sig_type)

        if not isinstance(sourmash_sig, (str, sourmash.signature.SourmashSignature, sourmash.signature.FrozenSourmashSignature)):
            # if the str is not a file path
            self.logger.error("Invalid type for sourmash_sig: %s", type(sourmash_sig).__name__)
            raise TypeError(f"sourmash_sig must be a file path, sourmash.signature.SourmashSignature, or Frozensourmash_signature, got {type(sourmash_sig).__name__}")

        # Case 1: If sourmash_sig is already a valid sourmash signature object
        if isinstance(sourmash_sig, (sourmash.signature.FrozenSourmashSignature, sourmash.signature.SourmashSignature)):
            self.logger.debug("Loaded sourmash signature directly from object.")
            sourmash_sigs = {sourmash_sig.name: sourmash_sig}

        # Case 2: If sourmash_sig is a string, try to load as JSON or a file
        elif isinstance(sourmash_sig, str):
            self.logger.debug("Attempting to load sourmash signature from string input.")

            # First, try loading from JSON
            sourmash_sigs = self._try_load_from_json(sourmash_sig)
            self.logger.debug("Loaded sourmash signature from JSON: %s", sourmash_sigs)

            # If JSON loading fails, try loading from file
            if not sourmash_sigs:
                sourmash_sigs = self._try_load_from_file(sourmash_sig)

            # If both attempts fail, raise an error
            if not sourmash_sigs:
                self.logger.error("Failed to load sourmash signature from the provided string.")
                raise ValueError("An unexpected error occurred while loading the sourmash signature.")

        if sig_type == SigType.SAMPLE or sig_type == SigType.AMPLICON:
            if len(sourmash_sigs) > 1:
                self.logger.debug("Multiple signatures found in the input. Expected a single sample signature.")
                # not supported at this time
                raise ValueError("Loading multiple sample signatures is not supported at this time.")
            elif len(sourmash_sigs) == 1:
                self.logger.debug("Found a single signature in the sample sig input; Will use this signature.")
                _sourmash_sig = list(sourmash_sigs.values())[0]
            else:
                self.logger.debug("No signature found in the input. Expected a single sample signature.")
                raise ValueError("No signature found in the input. Expected a single sample signature.")

        elif sig_type == SigType.GENOME:
            if len(sourmash_sigs) > 1:
                for signame, sig in sourmash_sigs.items():
                    self.logger.debug(f"Iterating over signature: {signame}")
                    if signame.endswith("-snipegenome"):
                        sig = sig.to_mutable()
                        # self.chr_to_sig[sig.name] = SnipeSig(sourmash_sig=sig, sig_type=SigType.GENOME, enable_logging=enable_logging)
                        sig.name = sig.name.replace("-snipegenome", "")
                        self.logger.debug("Found a genome signature with the snipe suffix `-snipegenome`. Restoring original name `%s`.", sig.name)
                        _sourmash_sig = sig
                    elif signame.startswith("sex-"):
                        self.logger.debug("Found a sex chr signature %s", signame)
                        sig = sig.to_mutable()
                        # sig.name = signame.replace("sex-","")
                        self.chr_to_sig[sig.name] = SnipeSig(sourmash_sig=sig, sig_type=SigType.AMPLICON, enable_logging=enable_logging)
                    elif signame.startswith("autosome-"):
                        self.logger.debug("Found an autosome signature %s", signame)
                        sig = sig.to_mutable()
                        # sig.name = signame.replace("autosome-","")
                        self.chr_to_sig[sig.name] = SnipeSig(sourmash_sig=sig, sig_type=SigType.AMPLICON, enable_logging=enable_logging)
                    else:
                        continue
                else:
                    if not _sourmash_sig:
                        self.logger.debug("Found multiple signature per the genome file, but none with the snipe suffix `-snipegenome`.")
                        raise ValueError("Found multiple signature per the genome file, but none with the snipe suffix `-snipegenome`.")
            elif len(sourmash_sigs) == 1:
                self.logger.debug("Found a single signature in the genome sig input; Will use this signature.")
                _sourmash_sig = list(sourmash_sigs.values())[0]
        else:
            self.logger.debug("Unknown sigtype: %s", sig_type)
            raise ValueError(f"Unknown sigtype: {sig_type}")

        self.logger.debug("Length of currently loaded signature: %d, with name: %s", len(_sourmash_sig), _sourmash_sig.name)

        # Extract properties from the loaded signature
        self._ksize = _sourmash_sig.minhash.ksize
        self._scale = _sourmash_sig.minhash.scaled
        self._md5sum = _sourmash_sig.md5sum()
        self._name = _sourmash_sig.name
        self._filename = _sourmash_sig.filename
        self._track_abundance = _sourmash_sig.minhash.track_abundance

        if self._name.endswith("-snipesample"):
            self._name = self._name.replace("-snipesample", "")
            self.logger.debug("Found a sample signature with the snipe suffix `-snipesample`. Restoring original name `%s`.", self._name)
        elif self._name.endswith("-snipeamplicon"):
            self._name = self._name.replace("-snipeamplicon", "")
            self.logger.debug("Found an amplicon signature with the snipe suffix `-snipeamplicon`. Restoring original name `%s`.", self._name)

        # If the signature does not track abundance, assume abundance of 1 for all hashes
        if not self._track_abundance:
            self.logger.debug("Signature does not track abundance. Setting all abundances to 1.")
            self._abundances = np.ones(len(_sourmash_sig.minhash.hashes), dtype=np.uint32)
            # self._track_abundance = True
        else:
            self._abundances = np.array(list(_sourmash_sig.minhash.hashes.values()), dtype=np.uint32)

        self._hashes = np.array(list(_sourmash_sig.minhash.hashes.keys()), dtype=np.uint64)

        # Sort the hashes and rearrange abundances accordingly
        sorted_indices = np.argsort(self._hashes)
        self._hashes = self._hashes[sorted_indices]
        self._abundances = self._abundances[sorted_indices]

        self.logger.debug(
            "Loaded sourmash signature from file: %s, name: %s, md5sum: %s, ksize: %d, scale: %d, "
            "track_abundance: %s, type: %s, length: %d",
            self._filename, self._name, self._md5sum, self._ksize, self._scale,
            self._track_abundance, self._type, len(self._hashes)
        )
        self.logger.debug("Hashes sorted during initialization.")
        self.logger.debug("Sourmash signature loading completed successfully.")

    def _try_load_from_json(self, sourmash_sig: str) -> Union[List[sourmash.signature.SourmashSignature], None]:
        r"""
        Attempt to load sourmash signature from JSON string.

        Parameters:
            sourmash_sig (str): JSON string representing a sourmash signature.

        Returns:
            sourmash.signature.SourmashSignature or None if loading fails.
        """
        try:
            self.logger.debug("Trying to load sourmash signature from JSON.")
            list_of_sigs = list(sourmash.load_signatures_from_json(sourmash_sig))
            return {sig.name: sig for sig in list_of_sigs}
        except Exception as e:
            self.logger.debug("Loading from JSON failed. Proceeding to file loading.", exc_info=e)
            return None  # Return None to indicate failure

    def _try_load_from_file(self, sourmash_sig_path: str) -> Union[List[sourmash.signature.SourmashSignature], None]:
        r"""
        Attempt to load sourmash signature(s) from a file.

        Parameters:
            sourmash_sig_path (str): File path to a sourmash signature.

        Returns:
            sourmash.signature.SourmashßSignature, list of sourmash.signature.SourmashSignature, or None if loading fails.
        """
        self.logger.debug("Trying to load sourmash signature from file.")
        try:
            signatures = list(sourmash.load_file_as_signatures(sourmash_sig_path))
            self.logger.debug("Loaded %d sourmash signature(s) from file.", len(signatures))
            sigs_dict = {_sig.name: _sig for _sig in signatures}
            self.logger.debug("Loaded sourmash signatures into sigs_dict: %s", sigs_dict)
            return sigs_dict
        except Exception as e:
            self.logger.exception("Failed to load the sourmash signature from the file.", exc_info=e)
            raise ValueError("An unexpected error occurred while loading the sourmash signature.") from e

    # Setters and getters
    @property
    def hashes(self) -> np.ndarray:
        r"""Return a copy of the hashes array."""
        return self._hashes.view()

    @property
    def abundances(self) -> np.ndarray:
        r"""Return a copy of the abundances array."""
        return self._abundances.view()

    @property
    def md5sum(self) -> str:
        r"""Return the MD5 checksum of the signature."""
        return self._md5sum

    @property
    def ksize(self) -> int:
        r"""Return the k-mer size."""
        return self._ksize

    @property
    def scale(self) -> int:
        r"""Return the scale value."""
        return self._scale

    @property
    def name(self) -> str:
        r"""Return the name of the signature."""
        return self._name

    @property
    def filename(self) -> str:
        r"""Return the filename of the signature."""
        return self._filename

    @property
    def sigtype(self) -> SigType:
        r"""Return the type of the signature."""
        return self._type

    @property
    def track_abundance(self) -> bool:
        r"""Return whether the signature tracks abundance."""
        return self._track_abundance

    # Basic class methods
    def get_name(self) -> str:
        r"""Get the name of the signature."""
        return self._name

    # setter sigtype
    @sigtype.setter
    def sigtype(self, sigtype: SigType):
        r"""
        Set the type of the signature.
        """
        self._type = sigtype

    @track_abundance.setter
    def track_abundance(self, track_abundance: bool):
        r"""
        Set whether the signature tracks abundance.
        """
        self._track_abundance = track_abundance

    def get_info(self) -> dict:
        r"""
        Get information about the signature.

        Returns:
            dict: A dictionary containing signature information.
        """
        info = {
            "name": self._name,
            "filename": self._filename,
            "md5sum": self._md5sum,
            "ksize": self._ksize,
            "scale": self._scale,
            "track_abundance": self._track_abundance,
            "sigtype": self._type,
            "num_hashes": len(self._hashes)
        }
        return info

    def __len__(self) -> int:
        r"""Return the number of hashes in the signature."""
        return len(self._hashes)

    def __iter__(self) -> Iterator[tuple]:
        r"""
        Iterate over the hashes and their abundances.

        Yields:
            tuple: A tuple containing (hash, abundance).
        """
        for h, a in zip(self._hashes, self._abundances):
            yield (h, a)

    def __contains__(self, hash_value: int) -> bool:
        r"""
        Check if a hash is present in the signature.

        Parameters:
            hash_value (int): The hash value to check.

        Returns:
            bool: True if the hash is present, False otherwise.
        """
        # Utilize binary search since hashes are sorted
        index = np.searchsorted(self._hashes, hash_value)
        if index < len(self._hashes) and self._hashes[index] == hash_value:
            return True
        return False

    def __repr__(self) -> str:
        return (f"SnipeSig(name={self._name}, ksize={self._ksize}, scale={self._scale}, "
                f"type={self._type}, num_hashes={len(self._hashes)})")

    def __str__(self) -> str:
        return self.__repr__()

    def __verify_snipe_signature(self, other: 'SnipeSig'):
        r"""
        Verify that the other object is a SnipeSig instance.

        Parameters:
            other (SnipeSig): The other signature to verify.

        Raises:
            ValueError: If the other object is not a SnipeSig instance.
        """
        if not isinstance(other, SnipeSig):
            msg = f"Provided sig ({type(other).__name__}) is not a SnipeSig instance."
            self.logger.error(msg)
            raise ValueError(msg)

    def __verify_matching_ksize_scale(self, other: 'SnipeSig'):
        r"""
        Verify that the ksize and scale match between two signatures.

        Parameters:
            other (SnipeSig): The other signature to compare.

        Raises:
            ValueError: If ksize or scale do not match.
        """
        if self._ksize != other.ksize:
            _e_msg = f"K-mer size does not match between the two signatures: {self._ksize} vs {other.ksize}."
            self.logger.error(_e_msg)
            raise ValueError(_e_msg)
        if self._scale != other.scale:
            _e_msg = f"Scale value does not match between the two signatures: {self._scale} vs {other.scale}."
            self.logger.error(_e_msg)
            raise ValueError(_e_msg)

    def _validate_abundance_operation(self, value: Union[int, None], operation: str):
        r"""
        Validate that the signature tracks abundance and that the provided value is a non-negative integer.

        Parameters:
            value (int or None): The abundance value to validate. Can be None for operations that don't require a value.
            operation (str): Description of the operation for logging purposes.

        Raises:
            ValueError: If the signature does not track abundance or if the value is invalid.
        """
        if not self._track_abundance and self.sigtype == SigType.SAMPLE:
            self.logger.error("Cannot %s: signature does not track abundance.", operation)
            raise ValueError("Signature does not track abundance.")

        if value is not None:
            if not isinstance(value, int) or value < 0:
                self.logger.error("%s requires a non-negative integer value.", operation.capitalize())
                raise ValueError(f"{operation.capitalize()} requires a non-negative integer value.")

    # Mask application method
    def _apply_mask(self, mask: np.ndarray):
        r"""
        Apply a boolean mask to the hashes and abundances arrays.
        Ensures that the sorted order is preserved.

        Parameters:
            mask (np.ndarray): Boolean array indicating which elements to keep.
        """
        self._hashes = self._hashes[mask]
        self._abundances = self._abundances[mask]

        # Verify that the hashes remain sorted
        if self._hashes.size > 1:
            if not np.all(self._hashes[:-1] <= self._hashes[1:]):
                self.logger.error("Hashes are not sorted after applying mask.")
                raise RuntimeError("Hashes are not sorted after applying mask.")
        self.logger.debug("Applied mask. Hashes remain sorted.")

    # Set operation methods
    def union_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Combine this signature with another by summing abundances where hashes overlap.

        Given two signatures \( A \) and \( B \) with hash sets \( H_A \) and \( H_B \),
        and their corresponding abundance functions \( a_A \) and \( a_B \), the union
        signature \( C \) is defined as follows:

        - **Hash Set**: 

        $$
        H_C = H_A \cup H_B
        $$

        - **Abundance Function**:

        $$
        a_C(h) =
        \begin{cases} 
            a_A(h) + a_B(h), & \text{if } h \in H_A \cap H_B \\
            a_A(h), & \text{if } h \in H_A \setminus H_B \\
            a_B(h), & \text{if } h \in H_B \setminus H_A
        \end{cases}
        $$
        """
        self.__verify_snipe_signature(other)
        self.__verify_matching_ksize_scale(other)

        self.logger.debug("Unioning signatures (including all unique hashes).")

        # Access internal arrays directly
        self_hashes = self._hashes
        self_abundances = self._abundances
        other_hashes = other._hashes
        other_abundances = other._abundances

        # Handle the case where 'other' does not track abundance
        if not other.track_abundance:
            self.logger.debug("Other signature does not track abundance. Setting abundances to 1.")
            other_abundances = np.ones_like(other_abundances, dtype=np.uint32)

        # Combine hashes and abundances
        combined_hashes = np.concatenate((self_hashes, other_hashes))
        combined_abundances = np.concatenate((self_abundances, other_abundances))

        # Use numpy's unique function with return_inverse to sum abundances efficiently
        unique_hashes, inverse_indices = np.unique(combined_hashes, return_inverse=True)
        summed_abundances = np.zeros_like(unique_hashes, dtype=np.uint32)

        # Sum abundances for duplicate hashes
        np.add.at(summed_abundances, inverse_indices, combined_abundances)

        # Handle potential overflow
        summed_abundances = np.minimum(summed_abundances, np.iinfo(np.uint32).max)

        self.logger.debug("Union operation completed. Total hashes: %d", len(unique_hashes))

        # Create a new SnipeSig instance
        return self.create_from_hashes_abundances(
            hashes=unique_hashes,
            abundances=summed_abundances,
            ksize=self._ksize,
            scale=self._scale,
            name=f"{self._name}_union_{other._name}",
            filename=None,
            enable_logging=self.logger.level <= logging.DEBUG
        )

    def _convert_to_sourmash_signature(self):
        r"""
        Convert the SnipeSig instance to a sourmash.signature.SourmashSignature object.

        Returns:
            sourmash.signature.SourmashSignature: A new sourmash.signature.SourmashSignature instance.
        """
        self.logger.debug("Converting SnipeSig to sourmash.signature.SourmashSignature.")

        mh = sourmash.minhash.MinHash(n=0, ksize=self._ksize, scaled=self._scale, track_abundance=self._track_abundance)
        if self._track_abundance:
            mh.set_abundances(dict(zip(self._hashes, self._abundances)))
        else:
            mh.add_many(self._hashes)
        self.sourmash_sig = sourmash.signature.SourmashSignature(mh, name=self._name, filename=self._filename)
        self.logger.debug("Conversion to sourmash.signature.SourmashSignature completed.")

    def export(self, path, force=False) -> None:
        r"""
        Export the signature to a file.

        Parameters:
            path (str): The path to save the signature to.
            force (bool): Flag to overwrite the file if it already exists.
        """
        self._convert_to_sourmash_signature()
        if path.endswith(".sig"):
            self.logger.debug("Exporting signature to a .sig file.")
            with open(str(path), "wb") as fp:
                sourmash.signature.save_signatures_to_json([self.sourmash_sig], fp)
        # sourmash.save_load.SaveSignatures_SigFile

        elif path.endswith(".zip"):
            if os.path.exists(path): 
                raise FileExistsError("Output file already exists.")
            try:
                with sourmash.save_load.SaveSignatures_ZipFile(path) as save_sigs:
                    save_sigs.add(self.sourmash_sig)
            except Exception as e:
                self.logger.error("Failed to export signatures to zip: %s", e)
                raise Exception(f"Failed to export signatures to zip: {e}") from e
        else:
            raise ValueError("Output file must be either a .sig or .zip file.")



    def export_to_string(self):
        r"""
        Export the signature to a JSON string.

        Returns:
            str: JSON string representation of the signature.
        """
        self._convert_to_sourmash_signature()
        return sourmash.signature.save_signatures_to_json([self.sourmash_sig]).decode('utf-8')

    def intersection_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Compute the intersection of the current signature with another signature.

        This method keeps only the hashes that are common to both signatures, and retains the abundances from self.

        **Mathematical Explanation**:

        Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \),
        and abundance functions \( a_A(h) \) and \( a_B(h) \), the intersection signature \( C \) has:

        - Hash set:
        $$
        H_C = H_A \cap H_B
        $$

        - Abundance function:
        $$
        a_C(h) = a_A(h), \quad \text{for } h \in H_C
        $$

        **Parameters**:
            - `other (SnipeSig)`: Another `SnipeSig` instance to intersect with.

        **Returns**:
            - `SnipeSig`: A new `SnipeSig` instance representing the intersection of the two signatures.

        **Raises**:
            - `ValueError`: If `ksize` or `scale` do not match between signatures.
        """
        self.__verify_snipe_signature(other)
        self.__verify_matching_ksize_scale(other)

        self.logger.debug("Intersecting signatures.")

        # Use numpy's intersect1d function
        common_hashes, self_indices, _ = np.intersect1d(
            self._hashes, other._hashes, assume_unique=True, return_indices=True
        )

        if common_hashes.size == 0:
            self.logger.debug("No common hashes found. Returning an empty signature.")
            return self.create_from_hashes_abundances(
                hashes=np.array([], dtype=np.uint64),
                abundances=np.array([], dtype=np.uint32),
                ksize=self._ksize,
                scale=self._scale,
                name=f"{self._name}_intersection_{other._name}",
                filename=None,
                enable_logging=self.logger.level <= logging.DEBUG
            )

        # Get the abundances from self
        common_abundances = self._abundances[self_indices]

        self.logger.debug("Intersection operation completed. Total common hashes: %d", len(common_hashes))

        # Create a new SnipeSig instance
        return self.create_from_hashes_abundances(
            hashes=common_hashes,
            abundances=common_abundances,
            ksize=self._ksize,
            scale=self._scale,
            name=f"{self._name}_intersection_{other._name}",
            filename=None,
            enable_logging=self.logger.level <= logging.DEBUG
        )

    def difference_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Compute the difference of the current signature with another signature.

        This method removes hashes that are present in the other signature from self,
        keeping the abundances from self.

        **Mathematical Explanation**:

        Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \),
        and abundance function \( a_A(h) \), the difference signature \( C \) has:

        - Hash set:
        $$
        H_C = H_A \setminus H_B
        $$

        - Abundance function:
        $$
        a_C(h) = a_A(h), \quad \text{for } h \in H_C
        $$

        **Parameters**:
            - `other (SnipeSig)`: Another `SnipeSig` instance to subtract from the current signature.

        **Returns**:
            - `SnipeSig`: A new `SnipeSig` instance representing the difference of the two signatures.

        **Raises**:
            - `ValueError`: If `ksize` or `scale` do not match between signatures.
            - `RuntimeError`: If zero hashes remain after difference.
        """
        self.__verify_snipe_signature(other)
        self.__verify_matching_ksize_scale(other)

        self.logger.debug("Differencing signatures.")

        # Use numpy's setdiff1d function
        diff_hashes = np.setdiff1d(self._hashes, other._hashes, assume_unique=True)

        if diff_hashes.size == 0:
            _e_msg = f"Difference operation resulted in zero hashes, which is not allowed for {self._name} and {other._name}."
            self.logger.warning(_e_msg)

        # Get the indices of the hashes in self
        mask = np.isin(self._hashes, diff_hashes, assume_unique=True)
        diff_abundances = self._abundances[mask]

        self.logger.debug("Difference operation completed. Remaining hashes: %d", len(diff_hashes))

        # Create a new SnipeSig instance
        return self.create_from_hashes_abundances(
            hashes=diff_hashes,
            abundances=diff_abundances,
            ksize=self._ksize,
            scale=self._scale,
            name=f"{self._name}_difference_{other._name}",
            filename=None,
            enable_logging=self.logger.level <= logging.DEBUG
        )

    def symmetric_difference_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Compute the symmetric difference of the current signature with another signature.

        This method retains hashes that are unique to each signature, with their respective abundances.

        **Mathematical Explanation**:

        Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \),
        and abundance functions \( a_A(h) \) and \( a_B(h) \), the symmetric difference signature \( C \) has:

        - Hash set:
        $$
        H_C = (H_A \setminus H_B) \cup (H_B \setminus H_A)
        $$

        - Abundance function:
        $$
        a_C(h) =
        \begin{cases}
        a_A(h), & \text{for } h \in H_A \setminus H_B \\
        a_B(h), & \text{for } h \in H_B \setminus H_A \\
        \end{cases}
        $$

        **Parameters**:
            - `other (SnipeSig)`: Another `SnipeSig` instance to compute the symmetric difference with.

        **Returns**:
            - `SnipeSig`: A new `SnipeSig` instance representing the symmetric difference of the two signatures.

        **Raises**:
            - `ValueError`: If `ksize` or `scale` do not match between signatures.
            - `RuntimeError`: If zero hashes remain after symmetric difference.
        """
        self.__verify_snipe_signature(other)
        self.__verify_matching_ksize_scale(other)

        self.logger.debug("Computing symmetric difference of signatures.")

        # Hashes unique to self and other
        unique_self_hashes = np.setdiff1d(self._hashes, other._hashes, assume_unique=True)
        unique_other_hashes = np.setdiff1d(other._hashes, self._hashes, assume_unique=True)

        # Abundances for unique hashes
        mask_self = np.isin(self._hashes, unique_self_hashes, assume_unique=True)
        unique_self_abundances = self._abundances[mask_self]

        mask_other = np.isin(other._hashes, unique_other_hashes, assume_unique=True)
        unique_other_abundances = other._abundances[mask_other]

        # Handle the case where 'other' does not track abundance
        if not other.track_abundance:
            self.logger.debug("Other signature does not track abundance. Setting abundances to 1.")
            unique_other_abundances = np.ones_like(unique_other_abundances, dtype=np.uint32)

        # Combine hashes and abundances
        combined_hashes = np.concatenate((unique_self_hashes, unique_other_hashes))
        combined_abundances = np.concatenate((unique_self_abundances, unique_other_abundances))

        if combined_hashes.size == 0:
            _e_msg = "Symmetric difference operation resulted in zero hashes, which is not allowed."
            self.logger.error(_e_msg)
            raise RuntimeError(_e_msg)

        # Sort combined hashes and abundances
        sorted_indices = np.argsort(combined_hashes)
        combined_hashes = combined_hashes[sorted_indices]
        combined_abundances = combined_abundances[sorted_indices]

        self.logger.debug("Symmetric difference operation completed. Total unique hashes: %d", len(combined_hashes))

        # Create a new SnipeSig instance
        return self.create_from_hashes_abundances(
            hashes=combined_hashes,
            abundances=combined_abundances,
            ksize=self._ksize,
            scale=self._scale,
            name=f"{self._name}_symmetric_difference_{other._name}",
            filename=None,
            enable_logging=self.logger.level <= logging.DEBUG
        )

    # Magic methods for union operations
    def __add__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the + operator.
        Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
        returning a new signature.

        Returns:
            SnipeSig: Union of self and other.
        """
        return self.union_sigs(other)

    def __iadd__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the += operator.
        Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
        modifying self in-place.

        Returns:
            SnipeSig: Updated self after addition.
        """
        union_sig = self.union_sigs(other)
        self._update_from_union(union_sig)
        return self

    def __or__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the | operator.
        Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
        returning a new signature.

        Returns:
            SnipeSig: Union of self and other.
        """
        return self.union_sigs(other)

    def __ior__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the |= operator.
        Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
        modifying self in-place.

        Returns:
            SnipeSig: Updated self after union.
        """
        union_sig = self.union_sigs(other)
        self._update_from_union(union_sig)
        return self

    def __sub__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the - operator.
        Removes hashes present in other from self, keeping abundances from self,
        returning a new signature.

        Returns:
            SnipeSig: Difference of self and other.
        """
        return self.difference_sigs(other)

    def __isub__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the -= operator.
        Removes hashes present in other from self, keeping abundances from self,
        modifying self in-place.

        Returns:
            SnipeSig: Updated self after difference.

        Raises:
            RuntimeError: If zero hashes remain after difference.
        """
        difference_sig = self.difference_sigs(other)
        self._update_from_union(difference_sig)
        return self

    def __xor__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the ^ operator.
        Keeps unique hashes from each signature with their respective abundances, returning a new signature.

        Returns:
            SnipeSig: Symmetric difference of self and other.
        """
        return self.symmetric_difference_sigs(other)

    def __ixor__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the ^= operator.
        Keeps unique hashes from each signature with their respective abundances, modifying self in-place.

        Returns:
            SnipeSig: Updated self after symmetric difference.

        Raises:
            RuntimeError: If zero hashes remain after symmetric difference.
        """
        symmetric_diff_sig = self.symmetric_difference_sigs(other)
        self._update_from_union(symmetric_diff_sig)
        return self

    def __and__(self, other: 'SnipeSig') -> 'SnipeSig':
        r"""
        Implements the & operator.
        Keeps common hashes and retains abundances from self only, returning a new signature.

        Returns:
            SnipeSig: Intersection of self and other.
        """
        return self.intersection_sigs(other)

    def _update_from_union(self, other: 'SnipeSig'):
        r"""
        Update self's hashes and abundances from another SnipeSig instance.

        Parameters:
            other (SnipeSig): The other SnipeSig instance to update from.
        """
        self._hashes = other.hashes
        self._abundances = other.abundances
        self._name = other.name
        self._filename = other.filename
        self._md5sum = other.md5sum
        self._track_abundance = other.track_abundance
        # No need to update ksize and scale since they are verified to match

    @classmethod
    def create_from_hashes_abundances(cls, hashes: np.ndarray, abundances: np.ndarray,
                                      ksize: int, scale: int, name: str = None,
                                      filename: str = None, enable_logging: bool = False, sig_type: SigType = SigType.SAMPLE) -> 'SnipeSig':
        """
        Internal method to create a SnipeSig instance from hashes and abundances.

        Parameters:
            hashes (np.ndarray): Array of hash values.
            abundances (np.ndarray): Array of abundance values corresponding to the hashes.
            ksize (int): K-mer size.
            scale (int): Scale value.
            name (str): Optional name for the signature.
            filename (str): Optional filename for the signature.
            sig_type (SigType): Type of the signature.
            enable_logging (bool): Flag to enable logging.

        Returns:
            SnipeSig: A new SnipeSig instance.
        """
        # Create a mock sourmash signature object
        mh = sourmash.minhash.MinHash(n=0, ksize=ksize, scaled=scale, track_abundance=True)
        mh.set_abundances(dict(zip(hashes, abundances)))
        sig = sourmash.signature.SourmashSignature(mh, name=name or "", filename=filename or "")
        return cls(sourmash_sig=sig, sig_type=sig_type, enable_logging=enable_logging)

    # Aggregation Operations
    @classmethod
    def sum_signatures(cls, signatures: List['SnipeSig'], name: str = "summed_signature",
                       filename: str = None, enable_logging: bool = False) -> 'SnipeSig':

        r"""
        Sum multiple SnipeSig instances by including all unique hashes and summing their abundances where hashes overlap.
        This method utilizes a heap-based multi-way merge algorithm for enhanced efficiency when handling thousands of signatures.

        $$
        \text{Sum}(A_1, A_2, \dots, A_n) = \bigcup_{i=1}^{n} A_i
        $$

        For each hash \( h \), its total abundance is:
        $$
        \text{abundance}(h) = \sum_{i=1}^{n} \text{abundance}_i(h)
        $$

        **Mathematical Explanation**:

        - **Union of Signatures**:
            The summation of signatures involves creating a union of all unique k-mers (hashes) present across the input signatures.

        - **Total Abundance Calculation**:
            For each unique hash \( h \), the total abundance is the sum of its abundances across all signatures where it appears.

        - **Algorithm Efficiency**:
            By using a min-heap to perform a multi-way merge of sorted hash arrays, the method ensures that each hash is processed in ascending order without the need to store all hashes in memory simultaneously.

        **Parameters**:
            - `signatures (List[SnipeSig])`: List of `SnipeSig` instances to sum.
            - `name (str)`: Optional name for the resulting signature.
            - `filename (str)`: Optional filename for the resulting signature.
            - `enable_logging (bool)`: Flag to enable detailed logging.

        **Returns**:
            - `SnipeSig`: A new `SnipeSig` instance representing the sum of the signatures.

        **Raises**:
            - `ValueError`: If the signatures list is empty or if `ksize`/`scale` do not match across signatures.
            - `RuntimeError`: If an error occurs during the summation process.
        """
        if not signatures:
            raise ValueError("No signatures provided for summation.")

        # Verify that all signatures have the same ksize, scale, and track_abundance
        first_sig = signatures[0]
        ksize = first_sig.ksize
        scale = first_sig.scale
        track_abundance = first_sig.track_abundance

        for sig in signatures[1:]:
            if sig.ksize != ksize or sig.scale != scale:
                raise ValueError("All signatures must have the same ksize and scale.")

        # Initialize iterators for each signature's hashes and abundances
        iterators = []
        for sig in signatures:
            it = iter(zip(sig.hashes, sig.abundances))
            try:
                first_hash, first_abundance = next(it)
                iterators.append((first_hash, first_abundance, it))
            except StopIteration:
                continue  # Skip empty signatures

        if not iterators:
            raise ValueError("All provided signatures are empty.")

        # Initialize the heap with the first element from each iterator
        heap = []
        for idx, (hash_val, abundance, it) in enumerate(iterators):
            heap.append((hash_val, abundance, idx))
        heapq.heapify(heap)

        # Prepare lists to collect the summed hashes and abundances
        summed_hashes = []
        summed_abundances = []

        while heap:
            current_hash, current_abundance, idx = heapq.heappop(heap)
            # Initialize total abundance for the current_hash
            total_abundance = current_abundance

            # Check if the next element in the heap has the same hash
            while heap and heap[0][0] == current_hash:
                _, abundance, same_idx = heapq.heappop(heap)
                total_abundance += abundance
                # Push the next element from the same iterator
                try:
                    next_hash, next_abundance = next(iterators[same_idx][2])
                    heapq.heappush(heap, (next_hash, next_abundance, same_idx))
                except StopIteration:
                    pass  # No more elements in this iterator

            # Append the summed hash and abundance
            summed_hashes.append(current_hash)
            summed_abundances.append(total_abundance)

            # Push the next element from the current iterator
            try:
                next_hash, next_abundance = next(iterators[idx][2])
                heapq.heappush(heap, (next_hash, next_abundance, idx))
            except StopIteration:
                pass  # No more elements in this iterator

        # Convert the results to NumPy arrays for efficient storage and processing
        summed_hashes = np.array(summed_hashes, dtype=np.uint64)
        summed_abundances = np.array(summed_abundances, dtype=np.uint32)

        # Handle potential overflow by capping at the maximum value of uint32
        summed_abundances = np.minimum(summed_abundances, np.iinfo(np.uint32).max)

        # Create a new SnipeSig instance from the summed hashes and abundances
        summed_signature = cls.create_from_hashes_abundances(
            hashes=summed_hashes,
            abundances=summed_abundances,
            ksize=ksize,
            scale=scale,
            name=name,
            filename=filename,
            enable_logging=enable_logging
        )

        return summed_signature

    @staticmethod
    def get_unique_signatures(signatures: Dict[str, 'SnipeSig']) -> Dict[str, 'SnipeSig']:
        """
        Extract unique signatures from a dictionary of SnipeSig instances.

        For each signature, the unique_sig contains only the hashes that do not overlap with any other signature.

        Parameters:
            signatures (Dict[str, SnipeSig]): A dictionary mapping signature names to SnipeSig instances.

        Returns:
            Dict[str, SnipeSig]: A dictionary mapping signature names to their unique SnipeSig instances.

        Raises:
            ValueError: If the input dictionary is empty or if signatures have mismatched ksize/scale.
        """
        if not signatures:
            raise ValueError("The input signatures dictionary is empty.")

        # Extract ksize and scale from the first signature
        first_name, first_sig = next(iter(signatures.items()))
        ksize = first_sig.ksize
        scale = first_sig.scale

        # Verify that all signatures have the same ksize and scale
        for name, sig in signatures.items():
            if sig.ksize != ksize or sig.scale != scale:
                raise ValueError(f"Signature '{name}' has mismatched ksize or scale.")

        # Aggregate all hashes from all signatures
        all_hashes = np.concatenate([sig.hashes for sig in signatures.values()])

        # Count the occurrences of each hash
        unique_hashes, counts = np.unique(all_hashes, return_counts=True)

        # Identify hashes that are unique across all signatures (count == 1)
        unique_across_all = unique_hashes[counts == 1]

        # Convert to a set for faster membership testing
        unique_set = set(unique_across_all)

        unique_signatures = {}

        for name, sig in signatures.items():
            # Find hashes in the current signature that are unique across all signatures
            mask_unique = np.isin(sig.hashes, list(unique_set))

            # Extract unique hashes and their abundances
            unique_hashes_sig = sig.hashes[mask_unique]
            unique_abundances_sig = sig.abundances[mask_unique]

            # Create a new SnipeSig instance with the unique hashes and abundances
            unique_sig = SnipeSig.create_from_hashes_abundances(
                hashes=unique_hashes_sig,
                abundances=unique_abundances_sig,
                ksize=ksize,
                scale=scale,
                name=f"{name}_unique",
                filename=None,
                enable_logging=False,  # Set to True if you want logging for the new signatures
                sig_type=SigType.SAMPLE  # Adjust sig_type as needed
            )

            unique_signatures[name] = unique_sig

        return unique_signatures


    @classmethod
    def common_hashes(cls, signatures: List['SnipeSig'], name: str = "common_hashes_signature",
                      filename: str = None, enable_logging: bool = False) -> 'SnipeSig':
        r"""
        Compute the intersection of multiple SnipeSig instances, returning a new SnipeSig containing
        only the hashes present in all signatures, with abundances set to the minimum abundance across signatures.

        This method uses a heap-based multi-way merge algorithm for efficient computation,
        especially when handling a large number of signatures with sorted hashes.

        **Mathematical Explanation**:

        Given signatures \( A_1, A_2, \dots, A_n \) with hash sets \( H_1, H_2, \dots, H_n \),
        the intersection signature \( C \) has:

        - Hash set:
        $$
        H_C = \bigcap_{i=1}^{n} H_i
        $$

        - Abundance function:
        $$
        a_C(h) = \min_{i=1}^{n} a_i(h), \quad \text{for } h \in H_C
        $$

        **Parameters**:
            - `signatures (List[SnipeSig])`: List of `SnipeSig` instances to compute the intersection.
            - `name (str)`: Optional name for the resulting signature.
            - `filename (str)`: Optional filename for the resulting signature.
            - `enable_logging (bool)`: Flag to enable detailed logging.

        **Returns**:
            - `SnipeSig`: A new `SnipeSig` instance representing the intersection of the signatures.

        **Raises**:
            - `ValueError`: If the signatures list is empty or if `ksize`/`scale` do not match across signatures.
        """
        if not signatures:
            raise ValueError("No signatures provided for intersection.")

        # Verify that all signatures have the same ksize and scale
        first_sig = signatures[0]
        ksize = first_sig.ksize
        scale = first_sig.scale
        for sig in signatures[1:]:
            if sig.ksize != ksize or sig.scale != scale:
                raise ValueError("All signatures must have the same ksize and scale.")

        num_signatures = len(signatures)
        iterators = []
        for sig in signatures:
            it = iter(zip(sig.hashes, sig.abundances))
            try:
                first_hash, first_abundance = next(it)
                iterators.append((first_hash, first_abundance, it))
            except StopIteration:
                # One of the signatures is empty; intersection is empty
                return cls.create_from_hashes_abundances(
                    hashes=np.array([], dtype=np.uint64),
                    abundances=np.array([], dtype=np.uint32),
                    ksize=ksize,
                    scale=scale,
                    name=name,
                    filename=filename,
                    enable_logging=enable_logging
                )

        # Initialize the heap with the first element from each iterator
        heap = []
        for idx, (hash_val, abundance, it) in enumerate(iterators):
            heap.append((hash_val, abundance, idx))
        heapq.heapify(heap)

        common_hashes = []
        common_abundances = []

        while heap:
            # Pop all entries with the smallest hash
            current_hash, current_abundance, idx = heapq.heappop(heap)
            same_hash_entries = [(current_hash, current_abundance, idx)]

            # Collect all entries in the heap that have the same current_hash
            while heap and heap[0][0] == current_hash:
                h, a, i = heapq.heappop(heap)
                same_hash_entries.append((h, a, i))

            if len(same_hash_entries) == num_signatures:
                # The current_hash is present in all signatures
                # Take the minimum abundance across signatures
                min_abundance = min(entry[1] for entry in same_hash_entries)
                common_hashes.append(current_hash)
                common_abundances.append(min_abundance)

            # Push the next element from each iterator that had the current_hash
            for entry in same_hash_entries:
                h, a, i = entry
                try:
                    next_hash, next_abundance = next(iterators[i][2])
                    heapq.heappush(heap, (next_hash, next_abundance, i))
                except StopIteration:
                    pass  # Iterator exhausted

        # Convert the results to NumPy arrays
        if not common_hashes:
            # No common hashes found
            unique_hashes = np.array([], dtype=np.uint64)
            unique_abundances = np.array([], dtype=np.uint32)
        else:
            unique_hashes = np.array(common_hashes, dtype=np.uint64)
            unique_abundances = np.array(common_abundances, dtype=np.uint32)

        # Create a new SnipeSig instance from the common hashes and abundances
        common_signature = cls.create_from_hashes_abundances(
            hashes=unique_hashes,
            abundances=unique_abundances,
            ksize=ksize,
            scale=scale,
            name=name,
            filename=filename,
            enable_logging=enable_logging
        )

        return common_signature

    def copy(self) -> 'SnipeSig':
        r"""
        Create a copy of the current SnipeSig instance.

        Returns:
            SnipeSig: A new instance that is a copy of self.
        """
        return SnipeSig(sourmash_sig=self.export_to_string(), sig_type=self.sigtype, enable_logging=self.logger.level <= logging.DEBUG)

    # Implement the __radd__ method to support sum()
    def __radd__(self, other: Union[int, 'SnipeSig']) -> 'SnipeSig':
        r"""
        Implements the right-hand + operator to support sum().

        Returns:
            SnipeSig: Union of self and other.
        """
        return self.__radd_sum__(other)

    # Override the __sum__ method
    def __radd_sum__(self, other: Union[int, 'SnipeSig']) -> 'SnipeSig':
        r"""
        Internal helper method to support the sum() function.

        Parameters:
            other (int or SnipeSig): The other object to add. If other is 0, return self.

        Returns:
            SnipeSig: The result of the addition.
        """
        if other == 0:
            return self
        if not isinstance(other, SnipeSig):
            raise TypeError(f"Unsupported operand type(s) for +: 'SnipeSig' and '{type(other).__name__}'")
        return self.union_sigs(other)

    def reset_abundance(self, new_abundance: int = 1):
        r"""
        Reset all abundances to a specified value.

        This method sets the abundance of every hash in the signature to the specified `new_abundance` value.

        **Mathematical Explanation**:

        For each hash \( h \) in the signature, the abundance function is updated to:
        $$
        a(h) = \text{new\_abundance}
        $$

        **Parameters**:
            - `new_abundance (int)`: The new abundance value to set for all hashes. Default is 1.

        **Raises**:
            - `ValueError`: If the signature does not track abundance or if `new_abundance` is invalid.
        """

        self._validate_abundance_operation(new_abundance, "reset abundance")

        self._abundances[:] = new_abundance
        self.track_abundance = True
        self.logger.debug("Reset all abundances to %d.", new_abundance)

    def keep_min_abundance(self, min_abundance: int):
        r"""
        Keep only hashes with abundances greater than or equal to a minimum threshold.

        This method removes hashes whose abundances are less than the specified `min_abundance`.

        **Mathematical Explanation**:

        The updated hash set \( H' \) is:
        $$
        H' = \{ h \in H \mid a(h) \geq \text{min\_abundance} \}
        $$

        **Parameters**:
            - `min_abundance (int)`: The minimum abundance threshold.

        **Raises**:
            - `ValueError`: If the signature does not track abundance or if `min_abundance` is invalid.
        """
        self._validate_abundance_operation(min_abundance, "keep minimum abundance")

        mask = self._abundances >= min_abundance
        self._apply_mask(mask)
        self.logger.debug("Kept hashes with abundance >= %d.", min_abundance)

    def keep_max_abundance(self, max_abundance: int):
        r"""
        Keep only hashes with abundances less than or equal to a maximum threshold.

        This method removes hashes whose abundances are greater than the specified `max_abundance`.

        **Mathematical Explanation**:

        The updated hash set \( H' \) is:
        $$
        H' = \{ h \in H \mid a(h) \leq \text{max\_abundance} \}
        $$

        **Parameters**:
            - `max_abundance (int)`: The maximum abundance threshold.

        **Raises**:
            - `ValueError`: If the signature does not track abundance or if `max_abundance` is invalid.
        """
        self._validate_abundance_operation(max_abundance, "keep maximum abundance")

        mask = self._abundances <= max_abundance
        self._apply_mask(mask)
        self.logger.debug("Kept hashes with abundance <= %d.", max_abundance)

    def trim_below_median(self):
        r"""
        Trim hashes with abundances below the median abundance.

        This method removes all hashes whose abundances are less than the median abundance of the signature.

        **Mathematical Explanation**:

        Let \\( m \\) be the median of \\( \\{ a(h) \mid h \in H \\} \\).
        The updated hash set \\( H' \\) is:

        $$
        H' = \\{ h \in H \mid a(h) \geq m \\}
        $$

        **Raises**:
            - `ValueError`: If the signature does not track abundance.
        """

        self._validate_abundance_operation(None, "trim below median")

        if len(self._abundances) == 0:
            self.logger.debug("No hashes to trim based on median abundance.")
            return

        median = np.median(self._abundances)
        mask = self._abundances >= median
        self._apply_mask(mask)
        self.logger.debug("Trimmed hashes with abundance below median (%f).", median)

    def count_singletons(self) -> int:
        r"""
        Return the number of hashes with abundance equal to 1.

        Returns:
            int: Number of singletons.

        Raises:
            ValueError: If the signature does not track abundance.
        """
        self._validate_abundance_operation(None, "count singletons")

        count = np.sum(self._abundances == 1)
        self.logger.debug("Number of singletons (abundance == 1): %d", count)
        return int(count)

    def trim_singletons(self):
        r"""
        Remove hashes with abundance equal to 1.

        This method removes all hashes that are singletons (abundance equals 1).

        **Mathematical Explanation**:

        The updated hash set \( H' \) is:
        $$
        H' = \{ h \in H \mid a(h) \neq 1 \}
        $$

        **Raises**:
            - `ValueError`: If the signature does not track abundance.
        """
        self._validate_abundance_operation(None, "trim singletons")

        mask = self._abundances != 1
        self.logger.debug("Trimming %d hashes with abundance equal to 1.", np.sum(~mask))
        self._apply_mask(mask)
        self.logger.debug("Size after trimming singletons: %d", len(self._hashes)) 

    # New Properties Implemented as per Request

    @property
    def total_abundance(self) -> int:
        r"""
        Return the total abundance (sum of all abundances).

        Returns:
            int: Total abundance.
        """
        self._validate_abundance_operation(None, "calculate total abundance")

        total = int(np.sum(self._abundances))
        self.logger.debug("Total abundance: %d", total)
        return total

    @property
    def mean_abundance(self) -> float:
        r"""
        Return the mean (average) abundance.

        Returns:
            float: Mean abundance.
        """
        self._validate_abundance_operation(None, "calculate mean abundance")

        if len(self._abundances) == 0:
            self.logger.debug("No abundances to calculate mean.")
            return 0.0

        mean = float(np.mean(self._abundances))  # Changed to float
        self.logger.debug("Mean abundance: %f", mean)
        return mean

    @property
    def get_sample_stats(self) -> dict:
        r"""
        Retrieve statistical information about the signature.

        This property computes and returns a dictionary containing various statistics of the signature, such as total abundance, mean and median abundances, number of singletons, and total number of hashes.

        **Returns**:
            - `dict`: A dictionary containing sample statistics:
                - `total_abundance`: Sum of abundances.
                - `mean_abundance`: Mean abundance.
                - `median_abundance`: Median abundance.
                - `num_singletons`: Number of hashes with abundance equal to 1.
                - `num_hashes`: Total number of hashes.
                - `ksize`: K-mer size.
                - `scale`: Scale value.
                - `name`: Name of the signature.
                - `filename`: Filename of the signature.
        """

        # if self.sigtype != SigType.SAMPLE then don't return abundance stats

        stats = {
            "num_hashes": len(self._hashes),
            "ksize": self._ksize,
            "scale": self._scale,
            "name": self._name,
            "filename": self._filename
        }

        if self.sigtype != SigType.SAMPLE:
            stats["total_abundance"] = None
            stats["mean_abundance"] = None
            stats["median_abundance"] = None
            stats["num_singletons"] = None
        else:
            stats["total_abundance"] = self.total_abundance
            stats["mean_abundance"] = self.mean_abundance
            stats["median_abundance"] = self.median_abundance
            stats["num_singletons"] = self.count_singletons()

        return stats

    @property
    def median_abundance(self) -> float:
        r"""
        Return the median abundance.

        Returns:
            float: Median abundance.

        Raises:
            ValueError: If the signature does not track abundance.
        """
        self._validate_abundance_operation(None, "calculate median abundance")

        if len(self._abundances) == 0:
            self.logger.debug("No abundances to calculate median.")
            return 0.0

        median = float(np.median(self._abundances))  # Changed to float
        self.logger.debug("Median abundance: %f", median)
        return median

abundances: np.ndarray property

Return a copy of the abundances array.

filename: str property

Return the filename of the signature.

get_sample_stats: dict property

Retrieve statistical information about the signature.

This property computes and returns a dictionary containing various statistics of the signature, such as total abundance, mean and median abundances, number of singletons, and total number of hashes.

Returns: - dict: A dictionary containing sample statistics: - total_abundance: Sum of abundances. - mean_abundance: Mean abundance. - median_abundance: Median abundance. - num_singletons: Number of hashes with abundance equal to 1. - num_hashes: Total number of hashes. - ksize: K-mer size. - scale: Scale value. - name: Name of the signature. - filename: Filename of the signature.

hashes: np.ndarray property

Return a copy of the hashes array.

ksize: int property

Return the k-mer size.

md5sum: str property

Return the MD5 checksum of the signature.

mean_abundance: float property

Return the mean (average) abundance.

Returns:

Name	Type	Description
float	float	Mean abundance.

median_abundance: float property

Return the median abundance.

Returns:

Name	Type	Description
float	float	Median abundance.

Raises:

Type	Description
ValueError	If the signature does not track abundance.

name: str property

Return the name of the signature.

scale: int property

Return the scale value.

sigtype: SigType property writable

Return the type of the signature.

total_abundance: int property

Return the total abundance (sum of all abundances).

Returns:

Name	Type	Description
int	int	Total abundance.

track_abundance: bool property writable

Return whether the signature tracks abundance.

__add__(other)

Implements the + operator. Includes all unique hashes from both signatures and sums their abundances where hashes overlap, returning a new signature.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Union of self and other.

Source code in src/snipe/api/snipe_sig.py

def __add__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the + operator.
    Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
    returning a new signature.

    Returns:
        SnipeSig: Union of self and other.
    """
    return self.union_sigs(other)

__and__(other)

Implements the & operator. Keeps common hashes and retains abundances from self only, returning a new signature.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Intersection of self and other.

Source code in src/snipe/api/snipe_sig.py

def __and__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the & operator.
    Keeps common hashes and retains abundances from self only, returning a new signature.

    Returns:
        SnipeSig: Intersection of self and other.
    """
    return self.intersection_sigs(other)

__contains__(hash_value)

Check if a hash is present in the signature.

Parameters:

Name	Type	Description	Default
hash_value	int	The hash value to check.	required

Returns:

Name	Type	Description
bool	bool	True if the hash is present, False otherwise.

Source code in src/snipe/api/snipe_sig.py

def __contains__(self, hash_value: int) -> bool:
    r"""
    Check if a hash is present in the signature.

    Parameters:
        hash_value (int): The hash value to check.

    Returns:
        bool: True if the hash is present, False otherwise.
    """
    # Utilize binary search since hashes are sorted
    index = np.searchsorted(self._hashes, hash_value)
    if index < len(self._hashes) and self._hashes[index] == hash_value:
        return True
    return False

__iadd__(other)

Implements the += operator. Includes all unique hashes from both signatures and sums their abundances where hashes overlap, modifying self in-place.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Updated self after addition.

Source code in src/snipe/api/snipe_sig.py

def __iadd__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the += operator.
    Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
    modifying self in-place.

    Returns:
        SnipeSig: Updated self after addition.
    """
    union_sig = self.union_sigs(other)
    self._update_from_union(union_sig)
    return self

__init__(*, sourmash_sig, sig_type=SigType.SAMPLE, enable_logging=False, **kwargs)

Initialize the SnipeSig with a sourmash signature object or a path to a signature.

Parameters:

Name	Type	Description	Default
sourmash_sig	str or SourmashSignature	A path to a signature file or a signature object.	required
ksize	int	K-mer size.	required
scale	int	Scale value.	required
sig_type	SigType	Type of the signature.	SAMPLE
enable_logging	bool	Flag to enable detailed logging.	False
**kwargs		Additional keyword arguments.	{}

Source code in src/snipe/api/snipe_sig.py

def __init__(self, *, 
             sourmash_sig: Union[str, sourmash.signature.SourmashSignature, sourmash.signature.FrozenSourmashSignature], 
             sig_type=SigType.SAMPLE, enable_logging: bool = False, **kwargs):
    r"""
    Initialize the SnipeSig with a sourmash signature object or a path to a signature.

    Parameters:
        sourmash_sig (str or sourmash.signature.SourmashSignature): A path to a signature file or a signature object.
        ksize (int): K-mer size.
        scale (int): Scale value.
        sig_type (SigType): Type of the signature.
        enable_logging (bool): Flag to enable detailed logging.
        **kwargs: Additional keyword arguments.
    """
    # Initialize logging based on the flag
    self.logger = logging.getLogger(self.__class__.__name__)

    # Configure the logger
    if enable_logging:
        self.logger.setLevel(logging.DEBUG)
        if not self.logger.hasHandlers():
            # Create console handler
            ch = logging.StreamHandler()
            ch.setLevel(logging.DEBUG)
            # Create formatter
            formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
            # Add formatter to handler
            ch.setFormatter(formatter)
            # Add handler to logger
            self.logger.addHandler(ch)
        self.logger.debug("Logging is enabled for SnipeSig.")
    else:
        self.logger.setLevel(logging.CRITICAL)

    # Initialize internal variables
    self.logger.debug("Initializing SnipeSig with sourmash_sig: %s", sourmash_sig)

    self._scale: int = None
    self._ksize: int = None
    self._md5sum: str = None
    self._hashes = np.array([], dtype=np.uint64)
    self._abundances = np.array([], dtype=np.uint32)
    self._type: SigType = sig_type
    self._name: str = None
    self._filename: str = None
    self._track_abundance: bool = True

    sourmash_sigs: Dict[str, sourmash.signature.SourmashSignature] = {}
    _sourmash_sig: Union[sourmash.signature.SourmashSignature, sourmash.signature.FrozenSourmashSignature] = None

    self.chr_to_sig: Dict[str, SnipeSig] = {}


    self.logger.debug("Proceeding with a sigtype of %s", sig_type)

    if not isinstance(sourmash_sig, (str, sourmash.signature.SourmashSignature, sourmash.signature.FrozenSourmashSignature)):
        # if the str is not a file path
        self.logger.error("Invalid type for sourmash_sig: %s", type(sourmash_sig).__name__)
        raise TypeError(f"sourmash_sig must be a file path, sourmash.signature.SourmashSignature, or Frozensourmash_signature, got {type(sourmash_sig).__name__}")

    # Case 1: If sourmash_sig is already a valid sourmash signature object
    if isinstance(sourmash_sig, (sourmash.signature.FrozenSourmashSignature, sourmash.signature.SourmashSignature)):
        self.logger.debug("Loaded sourmash signature directly from object.")
        sourmash_sigs = {sourmash_sig.name: sourmash_sig}

    # Case 2: If sourmash_sig is a string, try to load as JSON or a file
    elif isinstance(sourmash_sig, str):
        self.logger.debug("Attempting to load sourmash signature from string input.")

        # First, try loading from JSON
        sourmash_sigs = self._try_load_from_json(sourmash_sig)
        self.logger.debug("Loaded sourmash signature from JSON: %s", sourmash_sigs)

        # If JSON loading fails, try loading from file
        if not sourmash_sigs:
            sourmash_sigs = self._try_load_from_file(sourmash_sig)

        # If both attempts fail, raise an error
        if not sourmash_sigs:
            self.logger.error("Failed to load sourmash signature from the provided string.")
            raise ValueError("An unexpected error occurred while loading the sourmash signature.")

    if sig_type == SigType.SAMPLE or sig_type == SigType.AMPLICON:
        if len(sourmash_sigs) > 1:
            self.logger.debug("Multiple signatures found in the input. Expected a single sample signature.")
            # not supported at this time
            raise ValueError("Loading multiple sample signatures is not supported at this time.")
        elif len(sourmash_sigs) == 1:
            self.logger.debug("Found a single signature in the sample sig input; Will use this signature.")
            _sourmash_sig = list(sourmash_sigs.values())[0]
        else:
            self.logger.debug("No signature found in the input. Expected a single sample signature.")
            raise ValueError("No signature found in the input. Expected a single sample signature.")

    elif sig_type == SigType.GENOME:
        if len(sourmash_sigs) > 1:
            for signame, sig in sourmash_sigs.items():
                self.logger.debug(f"Iterating over signature: {signame}")
                if signame.endswith("-snipegenome"):
                    sig = sig.to_mutable()
                    # self.chr_to_sig[sig.name] = SnipeSig(sourmash_sig=sig, sig_type=SigType.GENOME, enable_logging=enable_logging)
                    sig.name = sig.name.replace("-snipegenome", "")
                    self.logger.debug("Found a genome signature with the snipe suffix `-snipegenome`. Restoring original name `%s`.", sig.name)
                    _sourmash_sig = sig
                elif signame.startswith("sex-"):
                    self.logger.debug("Found a sex chr signature %s", signame)
                    sig = sig.to_mutable()
                    # sig.name = signame.replace("sex-","")
                    self.chr_to_sig[sig.name] = SnipeSig(sourmash_sig=sig, sig_type=SigType.AMPLICON, enable_logging=enable_logging)
                elif signame.startswith("autosome-"):
                    self.logger.debug("Found an autosome signature %s", signame)
                    sig = sig.to_mutable()
                    # sig.name = signame.replace("autosome-","")
                    self.chr_to_sig[sig.name] = SnipeSig(sourmash_sig=sig, sig_type=SigType.AMPLICON, enable_logging=enable_logging)
                else:
                    continue
            else:
                if not _sourmash_sig:
                    self.logger.debug("Found multiple signature per the genome file, but none with the snipe suffix `-snipegenome`.")
                    raise ValueError("Found multiple signature per the genome file, but none with the snipe suffix `-snipegenome`.")
        elif len(sourmash_sigs) == 1:
            self.logger.debug("Found a single signature in the genome sig input; Will use this signature.")
            _sourmash_sig = list(sourmash_sigs.values())[0]
    else:
        self.logger.debug("Unknown sigtype: %s", sig_type)
        raise ValueError(f"Unknown sigtype: {sig_type}")

    self.logger.debug("Length of currently loaded signature: %d, with name: %s", len(_sourmash_sig), _sourmash_sig.name)

    # Extract properties from the loaded signature
    self._ksize = _sourmash_sig.minhash.ksize
    self._scale = _sourmash_sig.minhash.scaled
    self._md5sum = _sourmash_sig.md5sum()
    self._name = _sourmash_sig.name
    self._filename = _sourmash_sig.filename
    self._track_abundance = _sourmash_sig.minhash.track_abundance

    if self._name.endswith("-snipesample"):
        self._name = self._name.replace("-snipesample", "")
        self.logger.debug("Found a sample signature with the snipe suffix `-snipesample`. Restoring original name `%s`.", self._name)
    elif self._name.endswith("-snipeamplicon"):
        self._name = self._name.replace("-snipeamplicon", "")
        self.logger.debug("Found an amplicon signature with the snipe suffix `-snipeamplicon`. Restoring original name `%s`.", self._name)

    # If the signature does not track abundance, assume abundance of 1 for all hashes
    if not self._track_abundance:
        self.logger.debug("Signature does not track abundance. Setting all abundances to 1.")
        self._abundances = np.ones(len(_sourmash_sig.minhash.hashes), dtype=np.uint32)
        # self._track_abundance = True
    else:
        self._abundances = np.array(list(_sourmash_sig.minhash.hashes.values()), dtype=np.uint32)

    self._hashes = np.array(list(_sourmash_sig.minhash.hashes.keys()), dtype=np.uint64)

    # Sort the hashes and rearrange abundances accordingly
    sorted_indices = np.argsort(self._hashes)
    self._hashes = self._hashes[sorted_indices]
    self._abundances = self._abundances[sorted_indices]

    self.logger.debug(
        "Loaded sourmash signature from file: %s, name: %s, md5sum: %s, ksize: %d, scale: %d, "
        "track_abundance: %s, type: %s, length: %d",
        self._filename, self._name, self._md5sum, self._ksize, self._scale,
        self._track_abundance, self._type, len(self._hashes)
    )
    self.logger.debug("Hashes sorted during initialization.")
    self.logger.debug("Sourmash signature loading completed successfully.")

__ior__(other)

Implements the |= operator. Includes all unique hashes from both signatures and sums their abundances where hashes overlap, modifying self in-place.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Updated self after union.

Source code in src/snipe/api/snipe_sig.py

def __ior__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the |= operator.
    Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
    modifying self in-place.

    Returns:
        SnipeSig: Updated self after union.
    """
    union_sig = self.union_sigs(other)
    self._update_from_union(union_sig)
    return self

__isub__(other)

Implements the -= operator. Removes hashes present in other from self, keeping abundances from self, modifying self in-place.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Updated self after difference.

Raises:

Type	Description
RuntimeError	If zero hashes remain after difference.

Source code in src/snipe/api/snipe_sig.py

def __isub__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the -= operator.
    Removes hashes present in other from self, keeping abundances from self,
    modifying self in-place.

    Returns:
        SnipeSig: Updated self after difference.

    Raises:
        RuntimeError: If zero hashes remain after difference.
    """
    difference_sig = self.difference_sigs(other)
    self._update_from_union(difference_sig)
    return self

__iter__()

Iterate over the hashes and their abundances.

Yields:

Name	Type	Description
tuple	tuple	A tuple containing (hash, abundance).

Source code in src/snipe/api/snipe_sig.py

def __iter__(self) -> Iterator[tuple]:
    r"""
    Iterate over the hashes and their abundances.

    Yields:
        tuple: A tuple containing (hash, abundance).
    """
    for h, a in zip(self._hashes, self._abundances):
        yield (h, a)

__ixor__(other)

Implements the ^= operator. Keeps unique hashes from each signature with their respective abundances, modifying self in-place.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Updated self after symmetric difference.

Raises:

Type	Description
RuntimeError	If zero hashes remain after symmetric difference.

Source code in src/snipe/api/snipe_sig.py

def __ixor__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the ^= operator.
    Keeps unique hashes from each signature with their respective abundances, modifying self in-place.

    Returns:
        SnipeSig: Updated self after symmetric difference.

    Raises:
        RuntimeError: If zero hashes remain after symmetric difference.
    """
    symmetric_diff_sig = self.symmetric_difference_sigs(other)
    self._update_from_union(symmetric_diff_sig)
    return self

__len__()

Return the number of hashes in the signature.

Source code in src/snipe/api/snipe_sig.py

def __len__(self) -> int:
    r"""Return the number of hashes in the signature."""
    return len(self._hashes)

__or__(other)

Implements the | operator. Includes all unique hashes from both signatures and sums their abundances where hashes overlap, returning a new signature.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Union of self and other.

Source code in src/snipe/api/snipe_sig.py

def __or__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the | operator.
    Includes all unique hashes from both signatures and sums their abundances where hashes overlap,
    returning a new signature.

    Returns:
        SnipeSig: Union of self and other.
    """
    return self.union_sigs(other)

__radd__(other)

Implements the right-hand + operator to support sum().

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Union of self and other.

Source code in src/snipe/api/snipe_sig.py

def __radd__(self, other: Union[int, 'SnipeSig']) -> 'SnipeSig':
    r"""
    Implements the right-hand + operator to support sum().

    Returns:
        SnipeSig: Union of self and other.
    """
    return self.__radd_sum__(other)

__radd_sum__(other)

Internal helper method to support the sum() function.

Parameters:

Name	Type	Description	Default
other	int or SnipeSig	The other object to add. If other is 0, return self.	required

Returns:

Name	Type	Description
SnipeSig	SnipeSig	The result of the addition.

Source code in src/snipe/api/snipe_sig.py

def __radd_sum__(self, other: Union[int, 'SnipeSig']) -> 'SnipeSig':
    r"""
    Internal helper method to support the sum() function.

    Parameters:
        other (int or SnipeSig): The other object to add. If other is 0, return self.

    Returns:
        SnipeSig: The result of the addition.
    """
    if other == 0:
        return self
    if not isinstance(other, SnipeSig):
        raise TypeError(f"Unsupported operand type(s) for +: 'SnipeSig' and '{type(other).__name__}'")
    return self.union_sigs(other)

__sub__(other)

Implements the - operator. Removes hashes present in other from self, keeping abundances from self, returning a new signature.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Difference of self and other.

Source code in src/snipe/api/snipe_sig.py

def __sub__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the - operator.
    Removes hashes present in other from self, keeping abundances from self,
    returning a new signature.

    Returns:
        SnipeSig: Difference of self and other.
    """
    return self.difference_sigs(other)

__verify_matching_ksize_scale(other)

Verify that the ksize and scale match between two signatures.

Parameters:

Name	Type	Description	Default
other	SnipeSig	The other signature to compare.	required

Raises:

Type	Description
ValueError	If ksize or scale do not match.

Source code in src/snipe/api/snipe_sig.py

def __verify_matching_ksize_scale(self, other: 'SnipeSig'):
    r"""
    Verify that the ksize and scale match between two signatures.

    Parameters:
        other (SnipeSig): The other signature to compare.

    Raises:
        ValueError: If ksize or scale do not match.
    """
    if self._ksize != other.ksize:
        _e_msg = f"K-mer size does not match between the two signatures: {self._ksize} vs {other.ksize}."
        self.logger.error(_e_msg)
        raise ValueError(_e_msg)
    if self._scale != other.scale:
        _e_msg = f"Scale value does not match between the two signatures: {self._scale} vs {other.scale}."
        self.logger.error(_e_msg)
        raise ValueError(_e_msg)

__verify_snipe_signature(other)

Verify that the other object is a SnipeSig instance.

Parameters:

Name	Type	Description	Default
other	SnipeSig	The other signature to verify.	required

Raises:

Type	Description
ValueError	If the other object is not a SnipeSig instance.

Source code in src/snipe/api/snipe_sig.py

def __verify_snipe_signature(self, other: 'SnipeSig'):
    r"""
    Verify that the other object is a SnipeSig instance.

    Parameters:
        other (SnipeSig): The other signature to verify.

    Raises:
        ValueError: If the other object is not a SnipeSig instance.
    """
    if not isinstance(other, SnipeSig):
        msg = f"Provided sig ({type(other).__name__}) is not a SnipeSig instance."
        self.logger.error(msg)
        raise ValueError(msg)

__xor__(other)

Implements the ^ operator. Keeps unique hashes from each signature with their respective abundances, returning a new signature.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	Symmetric difference of self and other.

Source code in src/snipe/api/snipe_sig.py

def __xor__(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Implements the ^ operator.
    Keeps unique hashes from each signature with their respective abundances, returning a new signature.

    Returns:
        SnipeSig: Symmetric difference of self and other.
    """
    return self.symmetric_difference_sigs(other)

common_hashes(signatures, name='common_hashes_signature', filename=None, enable_logging=False) classmethod

Compute the intersection of multiple SnipeSig instances, returning a new SnipeSig containing only the hashes present in all signatures, with abundances set to the minimum abundance across signatures.

This method uses a heap-based multi-way merge algorithm for efficient computation, especially when handling a large number of signatures with sorted hashes.

Mathematical Explanation:

Given signatures \( A_1, A_2, \dots, A_n \) with hash sets \( H_1, H_2, \dots, H_n \), the intersection signature \( C \) has:

• Hash set: $$ H_C = \bigcap_{i=1}^{n} H_i $$

• Abundance function: $$ a_C(h) = \min_{i=1}^{n} a_i(h), \quad \text{for } h \in H_C $$

Parameters: - signatures (List[SnipeSig]): List of SnipeSig instances to compute the intersection. - name (str): Optional name for the resulting signature. - filename (str): Optional filename for the resulting signature. - enable_logging (bool): Flag to enable detailed logging.

Returns: - SnipeSig: A new SnipeSig instance representing the intersection of the signatures.

Raises: - ValueError: If the signatures list is empty or if ksize/scale do not match across signatures.

Source code in src/snipe/api/snipe_sig.py

@classmethod
def common_hashes(cls, signatures: List['SnipeSig'], name: str = "common_hashes_signature",
                  filename: str = None, enable_logging: bool = False) -> 'SnipeSig':
    r"""
    Compute the intersection of multiple SnipeSig instances, returning a new SnipeSig containing
    only the hashes present in all signatures, with abundances set to the minimum abundance across signatures.

    This method uses a heap-based multi-way merge algorithm for efficient computation,
    especially when handling a large number of signatures with sorted hashes.

    **Mathematical Explanation**:

    Given signatures \( A_1, A_2, \dots, A_n \) with hash sets \( H_1, H_2, \dots, H_n \),
    the intersection signature \( C \) has:

    - Hash set:
    $$
    H_C = \bigcap_{i=1}^{n} H_i
    $$

    - Abundance function:
    $$
    a_C(h) = \min_{i=1}^{n} a_i(h), \quad \text{for } h \in H_C
    $$

    **Parameters**:
        - `signatures (List[SnipeSig])`: List of `SnipeSig` instances to compute the intersection.
        - `name (str)`: Optional name for the resulting signature.
        - `filename (str)`: Optional filename for the resulting signature.
        - `enable_logging (bool)`: Flag to enable detailed logging.

    **Returns**:
        - `SnipeSig`: A new `SnipeSig` instance representing the intersection of the signatures.

    **Raises**:
        - `ValueError`: If the signatures list is empty or if `ksize`/`scale` do not match across signatures.
    """
    if not signatures:
        raise ValueError("No signatures provided for intersection.")

    # Verify that all signatures have the same ksize and scale
    first_sig = signatures[0]
    ksize = first_sig.ksize
    scale = first_sig.scale
    for sig in signatures[1:]:
        if sig.ksize != ksize or sig.scale != scale:
            raise ValueError("All signatures must have the same ksize and scale.")

    num_signatures = len(signatures)
    iterators = []
    for sig in signatures:
        it = iter(zip(sig.hashes, sig.abundances))
        try:
            first_hash, first_abundance = next(it)
            iterators.append((first_hash, first_abundance, it))
        except StopIteration:
            # One of the signatures is empty; intersection is empty
            return cls.create_from_hashes_abundances(
                hashes=np.array([], dtype=np.uint64),
                abundances=np.array([], dtype=np.uint32),
                ksize=ksize,
                scale=scale,
                name=name,
                filename=filename,
                enable_logging=enable_logging
            )

    # Initialize the heap with the first element from each iterator
    heap = []
    for idx, (hash_val, abundance, it) in enumerate(iterators):
        heap.append((hash_val, abundance, idx))
    heapq.heapify(heap)

    common_hashes = []
    common_abundances = []

    while heap:
        # Pop all entries with the smallest hash
        current_hash, current_abundance, idx = heapq.heappop(heap)
        same_hash_entries = [(current_hash, current_abundance, idx)]

        # Collect all entries in the heap that have the same current_hash
        while heap and heap[0][0] == current_hash:
            h, a, i = heapq.heappop(heap)
            same_hash_entries.append((h, a, i))

        if len(same_hash_entries) == num_signatures:
            # The current_hash is present in all signatures
            # Take the minimum abundance across signatures
            min_abundance = min(entry[1] for entry in same_hash_entries)
            common_hashes.append(current_hash)
            common_abundances.append(min_abundance)

        # Push the next element from each iterator that had the current_hash
        for entry in same_hash_entries:
            h, a, i = entry
            try:
                next_hash, next_abundance = next(iterators[i][2])
                heapq.heappush(heap, (next_hash, next_abundance, i))
            except StopIteration:
                pass  # Iterator exhausted

    # Convert the results to NumPy arrays
    if not common_hashes:
        # No common hashes found
        unique_hashes = np.array([], dtype=np.uint64)
        unique_abundances = np.array([], dtype=np.uint32)
    else:
        unique_hashes = np.array(common_hashes, dtype=np.uint64)
        unique_abundances = np.array(common_abundances, dtype=np.uint32)

    # Create a new SnipeSig instance from the common hashes and abundances
    common_signature = cls.create_from_hashes_abundances(
        hashes=unique_hashes,
        abundances=unique_abundances,
        ksize=ksize,
        scale=scale,
        name=name,
        filename=filename,
        enable_logging=enable_logging
    )

    return common_signature

copy()

Create a copy of the current SnipeSig instance.

Returns:

Name	Type	Description
SnipeSig	SnipeSig	A new instance that is a copy of self.

Source code in src/snipe/api/snipe_sig.py

def copy(self) -> 'SnipeSig':
    r"""
    Create a copy of the current SnipeSig instance.

    Returns:
        SnipeSig: A new instance that is a copy of self.
    """
    return SnipeSig(sourmash_sig=self.export_to_string(), sig_type=self.sigtype, enable_logging=self.logger.level <= logging.DEBUG)

count_singletons()

Return the number of hashes with abundance equal to 1.

Returns:

Name	Type	Description
int	int	Number of singletons.

Raises:

Type	Description
ValueError	If the signature does not track abundance.

Source code in src/snipe/api/snipe_sig.py

def count_singletons(self) -> int:
    r"""
    Return the number of hashes with abundance equal to 1.

    Returns:
        int: Number of singletons.

    Raises:
        ValueError: If the signature does not track abundance.
    """
    self._validate_abundance_operation(None, "count singletons")

    count = np.sum(self._abundances == 1)
    self.logger.debug("Number of singletons (abundance == 1): %d", count)
    return int(count)

create_from_hashes_abundances(hashes, abundances, ksize, scale, name=None, filename=None, enable_logging=False, sig_type=SigType.SAMPLE) classmethod

Internal method to create a SnipeSig instance from hashes and abundances.

Parameters:

Name	Type	Description	Default
hashes	ndarray	Array of hash values.	required
abundances	ndarray	Array of abundance values corresponding to the hashes.	required
ksize	int	K-mer size.	required
scale	int	Scale value.	required
name	str	Optional name for the signature.	None
filename	str	Optional filename for the signature.	None
sig_type	SigType	Type of the signature.	SAMPLE
enable_logging	bool	Flag to enable logging.	False

Returns:

Name	Type	Description
SnipeSig	SnipeSig	A new SnipeSig instance.

Source code in src/snipe/api/snipe_sig.py

@classmethod
def create_from_hashes_abundances(cls, hashes: np.ndarray, abundances: np.ndarray,
                                  ksize: int, scale: int, name: str = None,
                                  filename: str = None, enable_logging: bool = False, sig_type: SigType = SigType.SAMPLE) -> 'SnipeSig':
    """
    Internal method to create a SnipeSig instance from hashes and abundances.

    Parameters:
        hashes (np.ndarray): Array of hash values.
        abundances (np.ndarray): Array of abundance values corresponding to the hashes.
        ksize (int): K-mer size.
        scale (int): Scale value.
        name (str): Optional name for the signature.
        filename (str): Optional filename for the signature.
        sig_type (SigType): Type of the signature.
        enable_logging (bool): Flag to enable logging.

    Returns:
        SnipeSig: A new SnipeSig instance.
    """
    # Create a mock sourmash signature object
    mh = sourmash.minhash.MinHash(n=0, ksize=ksize, scaled=scale, track_abundance=True)
    mh.set_abundances(dict(zip(hashes, abundances)))
    sig = sourmash.signature.SourmashSignature(mh, name=name or "", filename=filename or "")
    return cls(sourmash_sig=sig, sig_type=sig_type, enable_logging=enable_logging)

difference_sigs(other)

Compute the difference of the current signature with another signature.

This method removes hashes that are present in the other signature from self, keeping the abundances from self.

Mathematical Explanation:

Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \), and abundance function \( a_A(h) \), the difference signature \( C \) has:

• Hash set: $$ H_C = H_A \setminus H_B $$

• Abundance function: $$ a_C(h) = a_A(h), \quad \text{for } h \in H_C $$

Parameters: - other (SnipeSig): Another SnipeSig instance to subtract from the current signature.

Returns: - SnipeSig: A new SnipeSig instance representing the difference of the two signatures.

Raises: - ValueError: If ksize or scale do not match between signatures. - RuntimeError: If zero hashes remain after difference.

Source code in src/snipe/api/snipe_sig.py

def difference_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Compute the difference of the current signature with another signature.

    This method removes hashes that are present in the other signature from self,
    keeping the abundances from self.

    **Mathematical Explanation**:

    Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \),
    and abundance function \( a_A(h) \), the difference signature \( C \) has:

    - Hash set:
    $$
    H_C = H_A \setminus H_B
    $$

    - Abundance function:
    $$
    a_C(h) = a_A(h), \quad \text{for } h \in H_C
    $$

    **Parameters**:
        - `other (SnipeSig)`: Another `SnipeSig` instance to subtract from the current signature.

    **Returns**:
        - `SnipeSig`: A new `SnipeSig` instance representing the difference of the two signatures.

    **Raises**:
        - `ValueError`: If `ksize` or `scale` do not match between signatures.
        - `RuntimeError`: If zero hashes remain after difference.
    """
    self.__verify_snipe_signature(other)
    self.__verify_matching_ksize_scale(other)

    self.logger.debug("Differencing signatures.")

    # Use numpy's setdiff1d function
    diff_hashes = np.setdiff1d(self._hashes, other._hashes, assume_unique=True)

    if diff_hashes.size == 0:
        _e_msg = f"Difference operation resulted in zero hashes, which is not allowed for {self._name} and {other._name}."
        self.logger.warning(_e_msg)

    # Get the indices of the hashes in self
    mask = np.isin(self._hashes, diff_hashes, assume_unique=True)
    diff_abundances = self._abundances[mask]

    self.logger.debug("Difference operation completed. Remaining hashes: %d", len(diff_hashes))

    # Create a new SnipeSig instance
    return self.create_from_hashes_abundances(
        hashes=diff_hashes,
        abundances=diff_abundances,
        ksize=self._ksize,
        scale=self._scale,
        name=f"{self._name}_difference_{other._name}",
        filename=None,
        enable_logging=self.logger.level <= logging.DEBUG
    )

export(path, force=False)

Export the signature to a file.

Parameters:

Name	Type	Description	Default
path	str	The path to save the signature to.	required
force	bool	Flag to overwrite the file if it already exists.	False

Source code in src/snipe/api/snipe_sig.py

def export(self, path, force=False) -> None:
    r"""
    Export the signature to a file.

    Parameters:
        path (str): The path to save the signature to.
        force (bool): Flag to overwrite the file if it already exists.
    """
    self._convert_to_sourmash_signature()
    if path.endswith(".sig"):
        self.logger.debug("Exporting signature to a .sig file.")
        with open(str(path), "wb") as fp:
            sourmash.signature.save_signatures_to_json([self.sourmash_sig], fp)
    # sourmash.save_load.SaveSignatures_SigFile

    elif path.endswith(".zip"):
        if os.path.exists(path): 
            raise FileExistsError("Output file already exists.")
        try:
            with sourmash.save_load.SaveSignatures_ZipFile(path) as save_sigs:
                save_sigs.add(self.sourmash_sig)
        except Exception as e:
            self.logger.error("Failed to export signatures to zip: %s", e)
            raise Exception(f"Failed to export signatures to zip: {e}") from e
    else:
        raise ValueError("Output file must be either a .sig or .zip file.")

export_to_string()

Export the signature to a JSON string.

Returns:

Name	Type	Description
str		JSON string representation of the signature.

Source code in src/snipe/api/snipe_sig.py

def export_to_string(self):
    r"""
    Export the signature to a JSON string.

    Returns:
        str: JSON string representation of the signature.
    """
    self._convert_to_sourmash_signature()
    return sourmash.signature.save_signatures_to_json([self.sourmash_sig]).decode('utf-8')

get_info()

Get information about the signature.

Returns:

Name	Type	Description
dict	dict	A dictionary containing signature information.

Source code in src/snipe/api/snipe_sig.py

def get_info(self) -> dict:
    r"""
    Get information about the signature.

    Returns:
        dict: A dictionary containing signature information.
    """
    info = {
        "name": self._name,
        "filename": self._filename,
        "md5sum": self._md5sum,
        "ksize": self._ksize,
        "scale": self._scale,
        "track_abundance": self._track_abundance,
        "sigtype": self._type,
        "num_hashes": len(self._hashes)
    }
    return info

get_name()

Get the name of the signature.

Source code in src/snipe/api/snipe_sig.py

def get_name(self) -> str:
    r"""Get the name of the signature."""
    return self._name

get_unique_signatures(signatures) staticmethod

Extract unique signatures from a dictionary of SnipeSig instances.

For each signature, the unique_sig contains only the hashes that do not overlap with any other signature.

Parameters:

Name	Type	Description	Default
signatures	Dict[str, SnipeSig]	A dictionary mapping signature names to SnipeSig instances.	required

Returns:

Type	Description
Dict[str, SnipeSig]	Dict[str, SnipeSig]: A dictionary mapping signature names to their unique SnipeSig instances.

Raises:

Type	Description
ValueError	If the input dictionary is empty or if signatures have mismatched ksize/scale.

Source code in src/snipe/api/snipe_sig.py

@staticmethod
def get_unique_signatures(signatures: Dict[str, 'SnipeSig']) -> Dict[str, 'SnipeSig']:
    """
    Extract unique signatures from a dictionary of SnipeSig instances.

    For each signature, the unique_sig contains only the hashes that do not overlap with any other signature.

    Parameters:
        signatures (Dict[str, SnipeSig]): A dictionary mapping signature names to SnipeSig instances.

    Returns:
        Dict[str, SnipeSig]: A dictionary mapping signature names to their unique SnipeSig instances.

    Raises:
        ValueError: If the input dictionary is empty or if signatures have mismatched ksize/scale.
    """
    if not signatures:
        raise ValueError("The input signatures dictionary is empty.")

    # Extract ksize and scale from the first signature
    first_name, first_sig = next(iter(signatures.items()))
    ksize = first_sig.ksize
    scale = first_sig.scale

    # Verify that all signatures have the same ksize and scale
    for name, sig in signatures.items():
        if sig.ksize != ksize or sig.scale != scale:
            raise ValueError(f"Signature '{name}' has mismatched ksize or scale.")

    # Aggregate all hashes from all signatures
    all_hashes = np.concatenate([sig.hashes for sig in signatures.values()])

    # Count the occurrences of each hash
    unique_hashes, counts = np.unique(all_hashes, return_counts=True)

    # Identify hashes that are unique across all signatures (count == 1)
    unique_across_all = unique_hashes[counts == 1]

    # Convert to a set for faster membership testing
    unique_set = set(unique_across_all)

    unique_signatures = {}

    for name, sig in signatures.items():
        # Find hashes in the current signature that are unique across all signatures
        mask_unique = np.isin(sig.hashes, list(unique_set))

        # Extract unique hashes and their abundances
        unique_hashes_sig = sig.hashes[mask_unique]
        unique_abundances_sig = sig.abundances[mask_unique]

        # Create a new SnipeSig instance with the unique hashes and abundances
        unique_sig = SnipeSig.create_from_hashes_abundances(
            hashes=unique_hashes_sig,
            abundances=unique_abundances_sig,
            ksize=ksize,
            scale=scale,
            name=f"{name}_unique",
            filename=None,
            enable_logging=False,  # Set to True if you want logging for the new signatures
            sig_type=SigType.SAMPLE  # Adjust sig_type as needed
        )

        unique_signatures[name] = unique_sig

    return unique_signatures

intersection_sigs(other)

Compute the intersection of the current signature with another signature.

This method keeps only the hashes that are common to both signatures, and retains the abundances from self.

Mathematical Explanation:

Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \), and abundance functions \( a_A(h) \) and \( a_B(h) \), the intersection signature \( C \) has:

• Hash set: $$ H_C = H_A \cap H_B $$

• Abundance function: $$ a_C(h) = a_A(h), \quad \text{for } h \in H_C $$

Parameters: - other (SnipeSig): Another SnipeSig instance to intersect with.

Returns: - SnipeSig: A new SnipeSig instance representing the intersection of the two signatures.

Raises: - ValueError: If ksize or scale do not match between signatures.

Source code in src/snipe/api/snipe_sig.py

def intersection_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Compute the intersection of the current signature with another signature.

    This method keeps only the hashes that are common to both signatures, and retains the abundances from self.

    **Mathematical Explanation**:

    Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \),
    and abundance functions \( a_A(h) \) and \( a_B(h) \), the intersection signature \( C \) has:

    - Hash set:
    $$
    H_C = H_A \cap H_B
    $$

    - Abundance function:
    $$
    a_C(h) = a_A(h), \quad \text{for } h \in H_C
    $$

    **Parameters**:
        - `other (SnipeSig)`: Another `SnipeSig` instance to intersect with.

    **Returns**:
        - `SnipeSig`: A new `SnipeSig` instance representing the intersection of the two signatures.

    **Raises**:
        - `ValueError`: If `ksize` or `scale` do not match between signatures.
    """
    self.__verify_snipe_signature(other)
    self.__verify_matching_ksize_scale(other)

    self.logger.debug("Intersecting signatures.")

    # Use numpy's intersect1d function
    common_hashes, self_indices, _ = np.intersect1d(
        self._hashes, other._hashes, assume_unique=True, return_indices=True
    )

    if common_hashes.size == 0:
        self.logger.debug("No common hashes found. Returning an empty signature.")
        return self.create_from_hashes_abundances(
            hashes=np.array([], dtype=np.uint64),
            abundances=np.array([], dtype=np.uint32),
            ksize=self._ksize,
            scale=self._scale,
            name=f"{self._name}_intersection_{other._name}",
            filename=None,
            enable_logging=self.logger.level <= logging.DEBUG
        )

    # Get the abundances from self
    common_abundances = self._abundances[self_indices]

    self.logger.debug("Intersection operation completed. Total common hashes: %d", len(common_hashes))

    # Create a new SnipeSig instance
    return self.create_from_hashes_abundances(
        hashes=common_hashes,
        abundances=common_abundances,
        ksize=self._ksize,
        scale=self._scale,
        name=f"{self._name}_intersection_{other._name}",
        filename=None,
        enable_logging=self.logger.level <= logging.DEBUG
    )

keep_max_abundance(max_abundance)

Keep only hashes with abundances less than or equal to a maximum threshold.

This method removes hashes whose abundances are greater than the specified max_abundance.

Mathematical Explanation:

The updated hash set \( H' \) is: $$ H' = { h \in H \mid a(h) \leq \text{max_abundance} } $$

Parameters: - max_abundance (int): The maximum abundance threshold.

Raises: - ValueError: If the signature does not track abundance or if max_abundance is invalid.

Source code in src/snipe/api/snipe_sig.py

def keep_max_abundance(self, max_abundance: int):
    r"""
    Keep only hashes with abundances less than or equal to a maximum threshold.

    This method removes hashes whose abundances are greater than the specified `max_abundance`.

    **Mathematical Explanation**:

    The updated hash set \( H' \) is:
    $$
    H' = \{ h \in H \mid a(h) \leq \text{max\_abundance} \}
    $$

    **Parameters**:
        - `max_abundance (int)`: The maximum abundance threshold.

    **Raises**:
        - `ValueError`: If the signature does not track abundance or if `max_abundance` is invalid.
    """
    self._validate_abundance_operation(max_abundance, "keep maximum abundance")

    mask = self._abundances <= max_abundance
    self._apply_mask(mask)
    self.logger.debug("Kept hashes with abundance <= %d.", max_abundance)

keep_min_abundance(min_abundance)

Keep only hashes with abundances greater than or equal to a minimum threshold.

This method removes hashes whose abundances are less than the specified min_abundance.

Mathematical Explanation:

The updated hash set \( H' \) is: $$ H' = { h \in H \mid a(h) \geq \text{min_abundance} } $$

Parameters: - min_abundance (int): The minimum abundance threshold.

Raises: - ValueError: If the signature does not track abundance or if min_abundance is invalid.

Source code in src/snipe/api/snipe_sig.py

def keep_min_abundance(self, min_abundance: int):
    r"""
    Keep only hashes with abundances greater than or equal to a minimum threshold.

    This method removes hashes whose abundances are less than the specified `min_abundance`.

    **Mathematical Explanation**:

    The updated hash set \( H' \) is:
    $$
    H' = \{ h \in H \mid a(h) \geq \text{min\_abundance} \}
    $$

    **Parameters**:
        - `min_abundance (int)`: The minimum abundance threshold.

    **Raises**:
        - `ValueError`: If the signature does not track abundance or if `min_abundance` is invalid.
    """
    self._validate_abundance_operation(min_abundance, "keep minimum abundance")

    mask = self._abundances >= min_abundance
    self._apply_mask(mask)
    self.logger.debug("Kept hashes with abundance >= %d.", min_abundance)

reset_abundance(new_abundance=1)

Reset all abundances to a specified value.

This method sets the abundance of every hash in the signature to the specified new_abundance value.

Mathematical Explanation:

For each hash \( h \) in the signature, the abundance function is updated to: $$ a(h) = \text{new_abundance} $$

Parameters: - new_abundance (int): The new abundance value to set for all hashes. Default is 1.

Raises: - ValueError: If the signature does not track abundance or if new_abundance is invalid.

Source code in src/snipe/api/snipe_sig.py

def reset_abundance(self, new_abundance: int = 1):
    r"""
    Reset all abundances to a specified value.

    This method sets the abundance of every hash in the signature to the specified `new_abundance` value.

    **Mathematical Explanation**:

    For each hash \( h \) in the signature, the abundance function is updated to:
    $$
    a(h) = \text{new\_abundance}
    $$

    **Parameters**:
        - `new_abundance (int)`: The new abundance value to set for all hashes. Default is 1.

    **Raises**:
        - `ValueError`: If the signature does not track abundance or if `new_abundance` is invalid.
    """

    self._validate_abundance_operation(new_abundance, "reset abundance")

    self._abundances[:] = new_abundance
    self.track_abundance = True
    self.logger.debug("Reset all abundances to %d.", new_abundance)

sum_signatures(signatures, name='summed_signature', filename=None, enable_logging=False) classmethod

Sum multiple SnipeSig instances by including all unique hashes and summing their abundances where hashes overlap. This method utilizes a heap-based multi-way merge algorithm for enhanced efficiency when handling thousands of signatures.

\[ \text{Sum}(A_1, A_2, \dots, A_n) = \bigcup_{i=1}^{n} A_i \]

For each hash \( h \), its total abundance is: $$ \text{abundance}(h) = \sum_{i=1}^{n} \text{abundance}_i(h) $$

Mathematical Explanation:

• Union of Signatures: The summation of signatures involves creating a union of all unique k-mers (hashes) present across the input signatures.

• Total Abundance Calculation: For each unique hash \( h \), the total abundance is the sum of its abundances across all signatures where it appears.

• Algorithm Efficiency: By using a min-heap to perform a multi-way merge of sorted hash arrays, the method ensures that each hash is processed in ascending order without the need to store all hashes in memory simultaneously.

Parameters: - signatures (List[SnipeSig]): List of SnipeSig instances to sum. - name (str): Optional name for the resulting signature. - filename (str): Optional filename for the resulting signature. - enable_logging (bool): Flag to enable detailed logging.

Returns: - SnipeSig: A new SnipeSig instance representing the sum of the signatures.

Raises: - ValueError: If the signatures list is empty or if ksize/scale do not match across signatures. - RuntimeError: If an error occurs during the summation process.

Source code in src/snipe/api/snipe_sig.py

@classmethod
def sum_signatures(cls, signatures: List['SnipeSig'], name: str = "summed_signature",
                   filename: str = None, enable_logging: bool = False) -> 'SnipeSig':

    r"""
    Sum multiple SnipeSig instances by including all unique hashes and summing their abundances where hashes overlap.
    This method utilizes a heap-based multi-way merge algorithm for enhanced efficiency when handling thousands of signatures.

    $$
    \text{Sum}(A_1, A_2, \dots, A_n) = \bigcup_{i=1}^{n} A_i
    $$

    For each hash \( h \), its total abundance is:
    $$
    \text{abundance}(h) = \sum_{i=1}^{n} \text{abundance}_i(h)
    $$

    **Mathematical Explanation**:

    - **Union of Signatures**:
        The summation of signatures involves creating a union of all unique k-mers (hashes) present across the input signatures.

    - **Total Abundance Calculation**:
        For each unique hash \( h \), the total abundance is the sum of its abundances across all signatures where it appears.

    - **Algorithm Efficiency**:
        By using a min-heap to perform a multi-way merge of sorted hash arrays, the method ensures that each hash is processed in ascending order without the need to store all hashes in memory simultaneously.

    **Parameters**:
        - `signatures (List[SnipeSig])`: List of `SnipeSig` instances to sum.
        - `name (str)`: Optional name for the resulting signature.
        - `filename (str)`: Optional filename for the resulting signature.
        - `enable_logging (bool)`: Flag to enable detailed logging.

    **Returns**:
        - `SnipeSig`: A new `SnipeSig` instance representing the sum of the signatures.

    **Raises**:
        - `ValueError`: If the signatures list is empty or if `ksize`/`scale` do not match across signatures.
        - `RuntimeError`: If an error occurs during the summation process.
    """
    if not signatures:
        raise ValueError("No signatures provided for summation.")

    # Verify that all signatures have the same ksize, scale, and track_abundance
    first_sig = signatures[0]
    ksize = first_sig.ksize
    scale = first_sig.scale
    track_abundance = first_sig.track_abundance

    for sig in signatures[1:]:
        if sig.ksize != ksize or sig.scale != scale:
            raise ValueError("All signatures must have the same ksize and scale.")

    # Initialize iterators for each signature's hashes and abundances
    iterators = []
    for sig in signatures:
        it = iter(zip(sig.hashes, sig.abundances))
        try:
            first_hash, first_abundance = next(it)
            iterators.append((first_hash, first_abundance, it))
        except StopIteration:
            continue  # Skip empty signatures

    if not iterators:
        raise ValueError("All provided signatures are empty.")

    # Initialize the heap with the first element from each iterator
    heap = []
    for idx, (hash_val, abundance, it) in enumerate(iterators):
        heap.append((hash_val, abundance, idx))
    heapq.heapify(heap)

    # Prepare lists to collect the summed hashes and abundances
    summed_hashes = []
    summed_abundances = []

    while heap:
        current_hash, current_abundance, idx = heapq.heappop(heap)
        # Initialize total abundance for the current_hash
        total_abundance = current_abundance

        # Check if the next element in the heap has the same hash
        while heap and heap[0][0] == current_hash:
            _, abundance, same_idx = heapq.heappop(heap)
            total_abundance += abundance
            # Push the next element from the same iterator
            try:
                next_hash, next_abundance = next(iterators[same_idx][2])
                heapq.heappush(heap, (next_hash, next_abundance, same_idx))
            except StopIteration:
                pass  # No more elements in this iterator

        # Append the summed hash and abundance
        summed_hashes.append(current_hash)
        summed_abundances.append(total_abundance)

        # Push the next element from the current iterator
        try:
            next_hash, next_abundance = next(iterators[idx][2])
            heapq.heappush(heap, (next_hash, next_abundance, idx))
        except StopIteration:
            pass  # No more elements in this iterator

    # Convert the results to NumPy arrays for efficient storage and processing
    summed_hashes = np.array(summed_hashes, dtype=np.uint64)
    summed_abundances = np.array(summed_abundances, dtype=np.uint32)

    # Handle potential overflow by capping at the maximum value of uint32
    summed_abundances = np.minimum(summed_abundances, np.iinfo(np.uint32).max)

    # Create a new SnipeSig instance from the summed hashes and abundances
    summed_signature = cls.create_from_hashes_abundances(
        hashes=summed_hashes,
        abundances=summed_abundances,
        ksize=ksize,
        scale=scale,
        name=name,
        filename=filename,
        enable_logging=enable_logging
    )

    return summed_signature

symmetric_difference_sigs(other)

Compute the symmetric difference of the current signature with another signature.

This method retains hashes that are unique to each signature, with their respective abundances.

Mathematical Explanation:

Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \), and abundance functions \( a_A(h) \) and \( a_B(h) \), the symmetric difference signature \( C \) has:

• Hash set: $$ H_C = (H_A \setminus H_B) \cup (H_B \setminus H_A) $$

• Abundance function: $$ a_C(h) = \begin{cases} a_A(h), & \text{for } h \in H_A \setminus H_B \ a_B(h), & \text{for } h \in H_B \setminus H_A \ \end{cases} $$

Parameters: - other (SnipeSig): Another SnipeSig instance to compute the symmetric difference with.

Returns: - SnipeSig: A new SnipeSig instance representing the symmetric difference of the two signatures.

Raises: - ValueError: If ksize or scale do not match between signatures. - RuntimeError: If zero hashes remain after symmetric difference.

Source code in src/snipe/api/snipe_sig.py

def symmetric_difference_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Compute the symmetric difference of the current signature with another signature.

    This method retains hashes that are unique to each signature, with their respective abundances.

    **Mathematical Explanation**:

    Let \( A \) and \( B \) be two signatures with sets of hashes \( H_A \) and \( H_B \),
    and abundance functions \( a_A(h) \) and \( a_B(h) \), the symmetric difference signature \( C \) has:

    - Hash set:
    $$
    H_C = (H_A \setminus H_B) \cup (H_B \setminus H_A)
    $$

    - Abundance function:
    $$
    a_C(h) =
    \begin{cases}
    a_A(h), & \text{for } h \in H_A \setminus H_B \\
    a_B(h), & \text{for } h \in H_B \setminus H_A \\
    \end{cases}
    $$

    **Parameters**:
        - `other (SnipeSig)`: Another `SnipeSig` instance to compute the symmetric difference with.

    **Returns**:
        - `SnipeSig`: A new `SnipeSig` instance representing the symmetric difference of the two signatures.

    **Raises**:
        - `ValueError`: If `ksize` or `scale` do not match between signatures.
        - `RuntimeError`: If zero hashes remain after symmetric difference.
    """
    self.__verify_snipe_signature(other)
    self.__verify_matching_ksize_scale(other)

    self.logger.debug("Computing symmetric difference of signatures.")

    # Hashes unique to self and other
    unique_self_hashes = np.setdiff1d(self._hashes, other._hashes, assume_unique=True)
    unique_other_hashes = np.setdiff1d(other._hashes, self._hashes, assume_unique=True)

    # Abundances for unique hashes
    mask_self = np.isin(self._hashes, unique_self_hashes, assume_unique=True)
    unique_self_abundances = self._abundances[mask_self]

    mask_other = np.isin(other._hashes, unique_other_hashes, assume_unique=True)
    unique_other_abundances = other._abundances[mask_other]

    # Handle the case where 'other' does not track abundance
    if not other.track_abundance:
        self.logger.debug("Other signature does not track abundance. Setting abundances to 1.")
        unique_other_abundances = np.ones_like(unique_other_abundances, dtype=np.uint32)

    # Combine hashes and abundances
    combined_hashes = np.concatenate((unique_self_hashes, unique_other_hashes))
    combined_abundances = np.concatenate((unique_self_abundances, unique_other_abundances))

    if combined_hashes.size == 0:
        _e_msg = "Symmetric difference operation resulted in zero hashes, which is not allowed."
        self.logger.error(_e_msg)
        raise RuntimeError(_e_msg)

    # Sort combined hashes and abundances
    sorted_indices = np.argsort(combined_hashes)
    combined_hashes = combined_hashes[sorted_indices]
    combined_abundances = combined_abundances[sorted_indices]

    self.logger.debug("Symmetric difference operation completed. Total unique hashes: %d", len(combined_hashes))

    # Create a new SnipeSig instance
    return self.create_from_hashes_abundances(
        hashes=combined_hashes,
        abundances=combined_abundances,
        ksize=self._ksize,
        scale=self._scale,
        name=f"{self._name}_symmetric_difference_{other._name}",
        filename=None,
        enable_logging=self.logger.level <= logging.DEBUG
    )

trim_below_median()

Trim hashes with abundances below the median abundance.

This method removes all hashes whose abundances are less than the median abundance of the signature.

Mathematical Explanation:

Let \( m \) be the median of \( \{ a(h) \mid h \in H \} \). The updated hash set \( H' \) is:

\[ H' = \\{ h \in H \mid a(h) \geq m \\} \]

Raises: - ValueError: If the signature does not track abundance.

Source code in src/snipe/api/snipe_sig.py

def trim_below_median(self):
    r"""
    Trim hashes with abundances below the median abundance.

    This method removes all hashes whose abundances are less than the median abundance of the signature.

    **Mathematical Explanation**:

    Let \\( m \\) be the median of \\( \\{ a(h) \mid h \in H \\} \\).
    The updated hash set \\( H' \\) is:

    $$
    H' = \\{ h \in H \mid a(h) \geq m \\}
    $$

    **Raises**:
        - `ValueError`: If the signature does not track abundance.
    """

    self._validate_abundance_operation(None, "trim below median")

    if len(self._abundances) == 0:
        self.logger.debug("No hashes to trim based on median abundance.")
        return

    median = np.median(self._abundances)
    mask = self._abundances >= median
    self._apply_mask(mask)
    self.logger.debug("Trimmed hashes with abundance below median (%f).", median)

trim_singletons()

Remove hashes with abundance equal to 1.

This method removes all hashes that are singletons (abundance equals 1).

Mathematical Explanation:

The updated hash set \( H' \) is: $$ H' = { h \in H \mid a(h) \neq 1 } $$

Raises: - ValueError: If the signature does not track abundance.

Source code in src/snipe/api/snipe_sig.py

def trim_singletons(self):
    r"""
    Remove hashes with abundance equal to 1.

    This method removes all hashes that are singletons (abundance equals 1).

    **Mathematical Explanation**:

    The updated hash set \( H' \) is:
    $$
    H' = \{ h \in H \mid a(h) \neq 1 \}
    $$

    **Raises**:
        - `ValueError`: If the signature does not track abundance.
    """
    self._validate_abundance_operation(None, "trim singletons")

    mask = self._abundances != 1
    self.logger.debug("Trimming %d hashes with abundance equal to 1.", np.sum(~mask))
    self._apply_mask(mask)
    self.logger.debug("Size after trimming singletons: %d", len(self._hashes)) 

union_sigs(other)

Combine this signature with another by summing abundances where hashes overlap.

Given two signatures \( A \) and \( B \) with hash sets \( H_A \) and \( H_B \), and their corresponding abundance functions \( a_A \) and \( a_B \), the union signature \( C \) is defined as follows:

• Hash Set:

\[ H_C = H_A \cup H_B \]

• Abundance Function:

\[ a_C(h) = \begin{cases} a_A(h) + a_B(h), & \text{if } h \in H_A \cap H_B \\ a_A(h), & \text{if } h \in H_A \setminus H_B \\ a_B(h), & \text{if } h \in H_B \setminus H_A \end{cases} \]

Source code in src/snipe/api/snipe_sig.py

def union_sigs(self, other: 'SnipeSig') -> 'SnipeSig':
    r"""
    Combine this signature with another by summing abundances where hashes overlap.

    Given two signatures \( A \) and \( B \) with hash sets \( H_A \) and \( H_B \),
    and their corresponding abundance functions \( a_A \) and \( a_B \), the union
    signature \( C \) is defined as follows:

    - **Hash Set**: 

    $$
    H_C = H_A \cup H_B
    $$

    - **Abundance Function**:

    $$
    a_C(h) =
    \begin{cases} 
        a_A(h) + a_B(h), & \text{if } h \in H_A \cap H_B \\
        a_A(h), & \text{if } h \in H_A \setminus H_B \\
        a_B(h), & \text{if } h \in H_B \setminus H_A
    \end{cases}
    $$
    """
    self.__verify_snipe_signature(other)
    self.__verify_matching_ksize_scale(other)

    self.logger.debug("Unioning signatures (including all unique hashes).")

    # Access internal arrays directly
    self_hashes = self._hashes
    self_abundances = self._abundances
    other_hashes = other._hashes
    other_abundances = other._abundances

    # Handle the case where 'other' does not track abundance
    if not other.track_abundance:
        self.logger.debug("Other signature does not track abundance. Setting abundances to 1.")
        other_abundances = np.ones_like(other_abundances, dtype=np.uint32)

    # Combine hashes and abundances
    combined_hashes = np.concatenate((self_hashes, other_hashes))
    combined_abundances = np.concatenate((self_abundances, other_abundances))

    # Use numpy's unique function with return_inverse to sum abundances efficiently
    unique_hashes, inverse_indices = np.unique(combined_hashes, return_inverse=True)
    summed_abundances = np.zeros_like(unique_hashes, dtype=np.uint32)

    # Sum abundances for duplicate hashes
    np.add.at(summed_abundances, inverse_indices, combined_abundances)

    # Handle potential overflow
    summed_abundances = np.minimum(summed_abundances, np.iinfo(np.uint32).max)

    self.logger.debug("Union operation completed. Total hashes: %d", len(unique_hashes))

    # Create a new SnipeSig instance
    return self.create_from_hashes_abundances(
        hashes=unique_hashes,
        abundances=summed_abundances,
        ksize=self._ksize,
        scale=self._scale,
        name=f"{self._name}_union_{other._name}",
        filename=None,
        enable_logging=self.logger.level <= logging.DEBUG
    )