import numpy as np

def ui8_clip(x, vmin=None, vmax=None):
    vmin = vmin if vmin else np.nanmin(x)
    vmax = vmax if vmax else np.nanmax(x)
    
    ui8 = ((np.clip(x, vmin, vmax) - vmin) / (vmax - vmin) * 255).astype(np.uint8)
    
    return np.ma.array(ui8, mask=np.isnan(x))

def hillshades(x):
    hs = np.zeros_like(x) 
    hs[:-1,:-1] = x[:-1,:-1] - x[1:,1:]
    return hs

from sap.spectra import get_bins

def spectrum2d(tree, x_attribute, y_attribute, x_count=100, y_count=100, 
               x_log=False, y_log=False, weighted=True, normalized=True,
               node_mask=None):
    x = tree.get_attribute(x_attribute)
    y = tree.get_attribute(y_attribute)

    bins = (get_bins(x, x_count, 'geo' if x_log else 'lin'),
            get_bins(y, y_count, 'geo' if y_log else 'lin'))

    weights = tree.get_attribute('area') if weighted else None
    weights = weights / tree._image.size if normalized and weighted else weights

    s, xedges, yedges = np.histogram2d(x[node_mask].ravel(), y[node_mask].ravel(),
                                       bins=bins, density=None, weights=weights[node_mask].ravel())

    return s, xedges, yedges, x_log, y_log

def pixel_to_node(tree, mask):
    """Compute the node mask from the pixel mask."""
    node_mask = hg.accumulate_and_min_sequential(tree._tree, 
                                                 np.ones(tree._tree.num_vertices(), dtype=np.uint8), 
                                                 mask.ravel(), 
                                                 hg.Accumulators.min).astype(np.bool)
    return node_mask