def histogram_deposition(current_indices_flat, currents_flat, grid_elements):
    '''
    function: histogram_deposition(current_indices_flat, currents_flat, grid)
    
    inputs: current_indices_flat, currents_flat, grid_elements
    
    current_indices_flat, currents_flat: They denote the indices and the currents
    to be deposited on the flattened current vector.
    
    grid_elements: The number of elements present the matrix/vector representing the 
    currents.   
    
    
    '''

    # setting default indices and current for histogram deposition
    indices_fix = af.data.range(grid_elements + 1, dtype=af.Dtype.s64)
    currents_fix = 0 * af.data.range(grid_elements + 1, dtype=af.Dtype.f64)

    # Concatenating the indices and currents in a single vector

    combined_indices_flat = af.join(0, indices_fix, current_indices_flat)
    combined_currents_flat = af.join(0, currents_fix, currents_flat)

    # Sort by key operation
    indices, currents = af.sort_by_key(combined_indices_flat,
                                       combined_currents_flat,
                                       dim=0)

    # scan by key operation with default binary addition operation which sums up currents
    # for the respective indices

    Histogram_scan = af.scan_by_key(indices, currents)

    # diff1 operation to determine the uniques indices in the current
    diff1_op = af.diff1(indices, dim=0)

    # Determining the uniques indices for current deposition
    indices_unique = af.where(diff1_op > 0)

    # Determining the current vector

    J_flat = Histogram_scan[indices_unique]

    af.eval(J_flat)

    return J_flat
Beispiel #2
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def sort_by_keys(keys: ndarray,
                 values: ndarray,
                 axis: int = -1,
                 ascending: bool = True) -> tp.Tuple[ndarray, ndarray]:
    if keys.shape != values.shape:
        raise ValueError("Keys and values must have the same dimensions.")
    elif axis is None:
        keys = keys.flatten()
        values = values.flatten()
    elif axis == -1:
        axis = keys.ndim - 1
    elif axis >= keys.ndim:
        raise ValueError(f"Parameter axis must be between -1 and "
                         f"{keys.ndim - 1}")

    ordered_values, ordered_keys \
        = af.sort_by_key(values._af_array,
                         keys._af_array,
                         is_ascending=ascending)

    return ndarray(ordered_keys), ndarray(ordered_values)
Beispiel #3
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def simple_algorithm(verbose = False):
    display_func = _util.display_func(verbose)
    print_func   = _util.print_func(verbose)

    a = af.randu(3, 3)

    print_func(af.sum(a), af.product(a), af.min(a), af.max(a),
               af.count(a), af.any_true(a), af.all_true(a))

    display_func(af.sum(a, 0))
    display_func(af.sum(a, 1))

    display_func(af.product(a, 0))
    display_func(af.product(a, 1))

    display_func(af.min(a, 0))
    display_func(af.min(a, 1))

    display_func(af.max(a, 0))
    display_func(af.max(a, 1))

    display_func(af.count(a, 0))
    display_func(af.count(a, 1))

    display_func(af.any_true(a, 0))
    display_func(af.any_true(a, 1))

    display_func(af.all_true(a, 0))
    display_func(af.all_true(a, 1))

    display_func(af.accum(a, 0))
    display_func(af.accum(a, 1))

    display_func(af.sort(a, is_ascending=True))
    display_func(af.sort(a, is_ascending=False))

    b = (a > 0.1) * a
    c = (a > 0.4) * a
    d = b / c
    print_func(af.sum(d));
    print_func(af.sum(d, nan_val=0.0));
    display_func(af.sum(d, dim=0, nan_val=0.0));

    val,idx = af.sort_index(a, is_ascending=True)
    display_func(val)
    display_func(idx)
    val,idx = af.sort_index(a, is_ascending=False)
    display_func(val)
    display_func(idx)

    b = af.randu(3,3)
    keys,vals = af.sort_by_key(a, b, is_ascending=True)
    display_func(keys)
    display_func(vals)
    keys,vals = af.sort_by_key(a, b, is_ascending=False)
    display_func(keys)
    display_func(vals)

    c = af.randu(5,1)
    d = af.randu(5,1)
    cc = af.set_unique(c, is_sorted=False)
    dd = af.set_unique(af.sort(d), is_sorted=True)
    display_func(cc)
    display_func(dd)

    display_func(af.set_union(cc, dd, is_unique=True))
    display_func(af.set_union(cc, dd, is_unique=False))

    display_func(af.set_intersect(cc, cc, is_unique=True))
    display_func(af.set_intersect(cc, cc, is_unique=False))
af.display(af.accum(a, 0))
af.display(af.accum(a, 1))

af.display(af.sort(a, is_ascending=True))
af.display(af.sort(a, is_ascending=False))

val, idx = af.sort_index(a, is_ascending=True)
af.display(val)
af.display(idx)
val, idx = af.sort_index(a, is_ascending=False)
af.display(val)
af.display(idx)

b = af.randu(3, 3)
keys, vals = af.sort_by_key(a, b, is_ascending=True)
af.display(keys)
af.display(vals)
keys, vals = af.sort_by_key(a, b, is_ascending=False)
af.display(keys)
af.display(vals)

c = af.randu(5, 1)
d = af.randu(5, 1)
cc = af.set_unique(c, is_sorted=False)
dd = af.set_unique(af.sort(d), is_sorted=True)
af.display(cc)
af.display(dd)

af.display(af.set_union(cc, dd, is_unique=True))
af.display(af.set_union(cc, dd, is_unique=False))
af.print_array(af.accum(a, 0))
af.print_array(af.accum(a, 1))

af.print_array(af.sort(a, is_ascending=True))
af.print_array(af.sort(a, is_ascending=False))

val,idx = af.sort_index(a, is_ascending=True)
af.print_array(val)
af.print_array(idx)
val,idx = af.sort_index(a, is_ascending=False)
af.print_array(val)
af.print_array(idx)

b = af.randu(3,3)
keys,vals = af.sort_by_key(a, b, is_ascending=True)
af.print_array(keys)
af.print_array(vals)
keys,vals = af.sort_by_key(a, b, is_ascending=False)
af.print_array(keys)
af.print_array(vals)

c = af.randu(5,1)
d = af.randu(5,1)
cc = af.set_unique(c, is_sorted=False)
dd = af.set_unique(af.sort(d), is_sorted=True)
af.print_array(cc)
af.print_array(dd)

af.print_array(af.set_union(cc, dd, is_unique=True))
af.print_array(af.set_union(cc, dd, is_unique=False))
Beispiel #6
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def simple_algorithm(verbose=False):
    display_func = _util.display_func(verbose)
    print_func = _util.print_func(verbose)

    a = af.randu(3, 3)
    k = af.constant(1, 3, 3, dtype=af.Dtype.u32)
    af.eval(k)

    print_func(af.sum(a), af.product(a), af.min(a), af.max(a), af.count(a),
               af.any_true(a), af.all_true(a))

    display_func(af.sum(a, 0))
    display_func(af.sum(a, 1))

    rk = af.constant(1, 3, dtype=af.Dtype.u32)
    rk[2] = 0
    af.eval(rk)
    display_func(af.sumByKey(rk, a, dim=0))
    display_func(af.sumByKey(rk, a, dim=1))

    display_func(af.productByKey(rk, a, dim=0))
    display_func(af.productByKey(rk, a, dim=1))

    display_func(af.minByKey(rk, a, dim=0))
    display_func(af.minByKey(rk, a, dim=1))

    display_func(af.maxByKey(rk, a, dim=0))
    display_func(af.maxByKey(rk, a, dim=1))

    display_func(af.anyTrueByKey(rk, a, dim=0))
    display_func(af.anyTrueByKey(rk, a, dim=1))

    display_func(af.allTrueByKey(rk, a, dim=0))
    display_func(af.allTrueByKey(rk, a, dim=1))

    display_func(af.countByKey(rk, a, dim=0))
    display_func(af.countByKey(rk, a, dim=1))

    display_func(af.product(a, 0))
    display_func(af.product(a, 1))

    display_func(af.min(a, 0))
    display_func(af.min(a, 1))

    display_func(af.max(a, 0))
    display_func(af.max(a, 1))

    display_func(af.count(a, 0))
    display_func(af.count(a, 1))

    display_func(af.any_true(a, 0))
    display_func(af.any_true(a, 1))

    display_func(af.all_true(a, 0))
    display_func(af.all_true(a, 1))

    display_func(af.accum(a, 0))
    display_func(af.accum(a, 1))

    display_func(af.scan(a, 0, af.BINARYOP.ADD))
    display_func(af.scan(a, 1, af.BINARYOP.MAX))

    display_func(af.scan_by_key(k, a, 0, af.BINARYOP.ADD))
    display_func(af.scan_by_key(k, a, 1, af.BINARYOP.MAX))

    display_func(af.sort(a, is_ascending=True))
    display_func(af.sort(a, is_ascending=False))

    b = (a > 0.1) * a
    c = (a > 0.4) * a
    d = b / c
    print_func(af.sum(d))
    print_func(af.sum(d, nan_val=0.0))
    display_func(af.sum(d, dim=0, nan_val=0.0))

    val, idx = af.sort_index(a, is_ascending=True)
    display_func(val)
    display_func(idx)
    val, idx = af.sort_index(a, is_ascending=False)
    display_func(val)
    display_func(idx)

    b = af.randu(3, 3)
    keys, vals = af.sort_by_key(a, b, is_ascending=True)
    display_func(keys)
    display_func(vals)
    keys, vals = af.sort_by_key(a, b, is_ascending=False)
    display_func(keys)
    display_func(vals)

    c = af.randu(5, 1)
    d = af.randu(5, 1)
    cc = af.set_unique(c, is_sorted=False)
    dd = af.set_unique(af.sort(d), is_sorted=True)
    display_func(cc)
    display_func(dd)

    display_func(af.set_union(cc, dd, is_unique=True))
    display_func(af.set_union(cc, dd, is_unique=False))

    display_func(af.set_intersect(cc, cc, is_unique=True))
    display_func(af.set_intersect(cc, cc, is_unique=False))