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ÿÿ,ÿÿ´Ðÿÿ¨ÐÿÿœÐÿÿÐÿÿ„ÐÿÿxÐÿÿlÐÿÿXÃÿÿÀÐÿÿäÐÿÿÑÿÿ,ÑÿÿPÑÿÿFormat string allocated too short.unable to allocate shape and strides.scipy.signal._peak_finding_utilsprominence data is invalid for peak {}numpy.core.umath failed to importno default __reduce__ due to non-trivial __cinit__ndarray is not Fortran contiguousgot differing extents in dimension %d (got %d and %d)arrays in `prominence_data` must have the same shape as `peaks`Utility functions for finding peaks in signals.Unable to convert item to objectOut of bounds on buffer access (axis %d)Non-native byte order not supportedInvalid mode, expected 'c' or 'fortran', got %sIndirect dimensions not supportedIncompatible checksums (%s vs 0xb068931 = (name))Format string allocated too short, see comment in numpy.pxdEmpty shape tuple for cython.arrayCannot create writable memory view from read-only memoryviewCannot assign to read-only memoryviewCan only create a buffer that is contiguous in memory.Calculated property of a peak has unexpected value.Buffer view does not expose stridesunknown dtype code in numpy.pxd (%d)some peaks have a prominence of 0`rel_height` must be greater or equal to 0.0peak {} is not a valid index for `x`numpy.core.multiarray failed to import<strided and direct or indirect>unable to allocate array data.some peaks have a width of 0ndarray is not C contiguousitemsize <= 0 for cython.arrayInvalid shape in axis %d: %d.Cannot index with type '%s'_select_by_peak_distance<contiguous and indirect><MemoryView of %r at 0x%x>_peak_finding_utils.pyx<MemoryView of %r object><contiguous and direct><strided and indirect>priority_to_positionPeakPropertyWarning<strided and direct>cline_in_traceback__pyx_unpickle_Enum_peak_prominences__setstate_cython____pyx_PickleError_local_maxima_1ddtype_is_objectallocate_bufferView.MemoryViewRuntimeWarningwidth_heights__reduce_cython____pyx_getbufferstringsourceshow_warning__pyx_checksumRuntimeErrorright_edgesright_basesprominences_peak_widthsPickleErrorMemoryErrorImportErrorstacklevelrel_height__pyx_vtable____pyx_resultpeaks_sizeleft_edgesleft_basesdistance_ValueErrorIndexErrorright_minright_ips__reduce_ex____pyx_statemidpoints__metaclass__enumerateTypeErrorwarnings__setstate__right_iprefcheck__qualname____pyx_typepriorityleft_minleft_ipsitemsize__getstate__distanceEllipsis__prepare__peak_nrmemviewleft_ipi_aheadfortranfloat64argsortwidthsupdateunpackstructresize__reduce__pickle__name____module____import__heightformatencodeuint8startshaperangepeaksnumpyi_mini_maxflagserroremptydtype__class__ASCIIwlenwarnview__test__stopstepsizepeakpackonesndimnamemode__main__keepintp__dict__boolbaseobj__new____doc____all__npidxpmkjicOBuffer dtype mismatch, expected %s%s%s but got %sBuffer dtype mismatch, expected '%s' but got %s in '%s.%s'memviewslice is already initialized!Unable to initialize pickling for %s%.200s.%.200s is not a type object%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject%s.%s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObjectDoes not understand character buffer dtype format string ('%c')scipy/signal/_peak_finding_utils.cView.MemoryView.memoryview.__str__View.MemoryView.memoryview.size.__get__View.MemoryView.memoryview.nbytes.__get__View.MemoryView.memoryview.itemsize.__get__View.MemoryView.memoryview.ndim.__get__View.MemoryView.memoryview.suboffsets.__get__View.MemoryView.memoryview.shape.__get__View.MemoryView.memoryview.setitem_indexedView.MemoryView.array.memview.__get__View.MemoryView.array.__getattr__View.MemoryView.array.__getitem__View.MemoryView.array.__setitem__Subscript deletion not supported by %.200sView.MemoryView.memoryview.assign_item_from_objectView.MemoryView._memoryviewslice.assign_item_from_object__int__ returned non-int (type %.200s).  The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python.__%.4s__ returned non-%.4s (type %.200s)calling %R should have returned an instance of BaseException, not %Rraise: exception class must be a subclass of BaseExceptionView.MemoryView.array.__reduce_cython__View.MemoryView.array.__setstate_cython__View.MemoryView.memoryview.convert_item_to_objectView.MemoryView._memoryviewslice.convert_item_to_objectView.MemoryView.memoryview.__reduce_cython__View.MemoryView.memoryview.__setstate_cython__View.MemoryView.memoryview.strides.__get__View.MemoryView._memoryviewslice.__reduce_cython__View.MemoryView._memoryviewslice.__setstate_cython__PyObject_GetBuffer: view==NULL argument is obsoleteView.MemoryView.array.__getbuffer__View.MemoryView.memoryview.__getbuffer__%s() got multiple values for keyword argument '%U'%.200s() keywords must be strings%s() got an unexpected keyword argument '%U'%.200s() takes %.8s %zd positional argument%.1s (%zd given)Unexpected format string character: '%c'Expected a dimension of size %zu, got %zuExpected %d dimensions, got %dPython does not define a standard format string size for long double ('g')..Buffer dtype mismatch; next field is at offset %zd but %zd expectedBig-endian buffer not supported on little-endian compilerBuffer acquisition: Expected '{' after 'T'Cannot handle repeated arrays in format stringExpected a dimension of size %zu, got %dExpected a comma in format string, got '%c'Expected %d dimension(s), got %dUnexpected end of format string, expected ')'Acquisition count is %d (line %d)View.MemoryView.array.get_memviewView.MemoryView.memoryview_cwrapperBuffer has wrong number of dimensions (expected %d, got %d)Buffer exposes suboffsets but no stridesC-contiguous buffer is not indirect in dimension %dBuffer and memoryview are not contiguous in the same dimension.Buffer is not indirectly contiguous in dimension %d.Buffer is not indirectly accessible in dimension %d.Buffer not compatible with direct access in dimension %d.Item size of buffer (%zu byte%s) does not match size of '%s' (%zu byte%s)View.MemoryView.memoryview.is_sliceView.MemoryView.memoryview_fromsliceView.MemoryView.memoryview_copy_from_sliceView.MemoryView.memoryview.__repr__View.MemoryView.Enum.__reduce_cython__value too large to convert to intc-string too long to convert to Pythonvalue too large to convert to npy_uint8can't convert negative value to npy_uint8Cannot convert %.200s to %.200sView.MemoryView.get_slice_from_memviewView.MemoryView.assert_direct_dimensionsView.MemoryView.memoryview.setitem_slice_assign_scalar'NoneType' object is not subscriptablehasattr(): attribute name must be stringView.MemoryView.__pyx_unpickle_Enum__set_stateView.MemoryView.Enum.__setstate_cython__Cannot transpose memoryview with indirect dimensionsView.MemoryView.transpose_memsliceView.MemoryView.memoryview_copyView.MemoryView.memoryview.T.__get__View.MemoryView.copy_data_to_tempView.MemoryView.memoryview_copy_contentsCannot copy memoryview slice with indirect dimensions (axis %d)View.MemoryView.array_cwrapperView.MemoryView.memoryview.copy_fortranView.MemoryView.memoryview.copyinteger division or modulo by zerovalue too large to perform divisionView.MemoryView.pybuffer_indexView.MemoryView.memoryview.get_item_pointertoo many values to unpack (expected %zd)need more than %zd value%.1s to unpack'NoneType' object is not iterableView.MemoryView.memoryview.__setitem__View.MemoryView.array.__cinit__Argument '%.200s' must not be Noneobject of type 'NoneType' has no len()expected bytes, NoneType foundArgument '%.200s' has incorrect type (expected %.200s, got %.200s)scipy.signal._peak_finding_utils._select_by_peak_distanceView.MemoryView.__pyx_unpickle_EnumView.MemoryView.memoryview.__cinit__View.MemoryView.memoryview.setitem_slice_assignmentscipy.signal._peak_finding_utils._local_maxima_1dAll dimensions preceding dimension %d must be indexed and not slicedView.MemoryView.slice_memviewsliceStep may not be zero (axis %d)local variable '%s' referenced before assignmentView.MemoryView.memoryview.__getitem__scipy.signal._peak_finding_utils._peak_prominencesscipy.signal._peak_finding_utils._peak_widthsscipy.signal._peak_finding_utilscompiletime version %s of module '%.100s' does not match runtime version %smetaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its basesinit scipy.signal._peak_finding_utilsscipy.signal._peak_finding_utils._memoryviewsliceInternal class for passing memoryview slices to Pythonscipy.signal._peak_finding_utils.memoryviewscipy.signal._peak_finding_utils.Enumscipy.signal._peak_finding_utils.arrayð¿
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    Calculate the width of each each peak in a signal.

    Parameters
    ----------
    x : ndarray
        A signal with peaks.
    peaks : ndarray
        Indices of peaks in `x`.
    rel_height : np.float64
        Chooses the relative height at which the peak width is measured as a
        percentage of its prominence (see `peak_widths`).
    prominences : ndarray
        Prominences of each peak in `peaks` as returned by `peak_prominences`.
    left_bases, right_bases : ndarray
        Left and right bases of each peak in `peaks` as returned by
        `peak_prominences`.

    Returns
    -------
    widths : ndarray
        The widths for each peak in samples.
    width_heights : ndarray
        The height of the contour lines at which the `widths` where evaluated.
    left_ips, right_ips : ndarray
        Interpolated positions of left and right intersection points of a
        horizontal line at the respective evaluation height.

    Raises
    ------
    ValueError
        If the supplied prominence data doesn't satisfy the condition
        ``0 <= left_base <= peak <= right_base < x.shape[0]`` for each peak or
        if `peaks`, `left_bases` and `right_bases` don't share the same shape.
        Or if `rel_height` is not at least 0.

    Warnings
    --------
    PeakPropertyWarning
        If a width of 0 was calculated for any peak.

    Notes
    -----
    This is the inner function to `peak_widths`.

    .. versionadded:: 1.1.0
    
    Calculate the prominence of each peak in a signal.

    Parameters
    ----------
    x : ndarray
        A signal with peaks.
    peaks : ndarray
        Indices of peaks in `x`.
    wlen : np.intp
        A window length in samples (see `peak_prominences`) which is rounded up
        to the nearest odd integer. If smaller than 2 the entire signal `x` is
        used.

    Returns
    -------
    prominences : ndarray
        The calculated prominences for each peak in `peaks`.
    left_bases, right_bases : ndarray
        The peaks' bases as indices in `x` to the left and right of each peak.

    Raises
    ------
    ValueError
        If a value in `peaks` is an invalid index for `x`.

    Warns
    -----
    PeakPropertyWarning
        If a prominence of 0 was calculated for any peak.

    Notes
    -----
    This is the inner function to `peak_prominences`.

    .. versionadded:: 1.1.0
    
    Evaluate which peaks fulfill the distance condition.

    Parameters
    ----------
    peaks : ndarray
        Indices of peaks in `vector`.
    priority : ndarray
        An array matching `peaks` used to determine priority of each peak. A
        peak with a higher priority value is kept over one with a lower one.
    distance : np.float64
        Minimal distance that peaks must be spaced.

    Returns
    -------
    keep : ndarray[bool]
        A boolean mask evaluating to true where `peaks` fulfill the distance
        condition.

    Notes
    -----
    Declaring the input arrays as C-contiguous doesn't seem to have performance
    advantages.

    .. versionadded:: 1.1.0
    
    Find local maxima in a 1D array.

    This function finds all local maxima in a 1D array and returns the indices
    for their edges and midpoints (rounded down for even plateau sizes).

    Parameters
    ----------
    x : ndarray
        The array to search for local maxima.

    Returns
    -------
    midpoints : ndarray
        Indices of midpoints of local maxima in `x`.
    left_edges : ndarray
        Indices of edges to the left of local maxima in `x`.
    right_edges : ndarray
        Indices of edges to the right of local maxima in `x`.

    Notes
    -----
    - Compared to `argrelmax` this function is significantly faster and can
      detect maxima that are more than one sample wide. However this comes at
      the cost of being only applicable to 1D arrays.
    - A maxima is defined as one or more samples of equal value that are
      surrounded on both sides by at least one smaller sample.

    .. versionadded:: 1.1.0
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