def makeMappingArray(N, data): """Create an N-element 1-d lookup table data represented by a list of x,y0,y1 mapping correspondences. Each element in this list represents how a value between 0 and 1 (inclusive) represented by x is mapped to a corresponding value between 0 and 1 (inclusive). The two values of y are to allow for discontinuous mapping functions (say as might be found in a sawtooth) where y0 represents the value of y for values of x <= to that given, and y1 is the value to be used for x > than that given). The list must start with x=0, end with x=1, and all values of x must be in increasing order. Values between the given mapping points are determined by simple linear interpolation. The function returns an array "result" where result[x*(N-1)] gives the closest value for values of x between 0 and 1. """ try: adata = array(data) except: raise TypeError("data must be convertable to an array") shape = adata.shape if len(shape) != 2 and shape[1] != 3: raise ValueError("data must be nx3 format") x = adata[:,0] y0 = adata[:,1] y1 = adata[:,2] if x[0] != 0. or x[-1] != 1.0: raise ValueError( "data mapping points must start with x=0. and end with x=1") if sometrue(sort(x)-x): raise ValueError( "data mapping points must have x in increasing order") # begin generation of lookup table x = x * (N-1) lut = zeros((N,), Float) xind = arange(float(N)) ind = searchsorted(x, xind)[1:-1] lut[1:-1] = ( divide(xind[1:-1] - take(x,ind-1), take(x,ind)-take(x,ind-1) ) *(take(y0,ind)-take(y1,ind-1)) + take(y1,ind-1)) lut[0] = y1[0] lut[-1] = y0[-1] # ensure that the lut is confined to values between 0 and 1 by clipping it clip(lut, 0.0, 1.0) #lut = where(lut > 1., 1., lut) #lut = where(lut < 0., 0., lut) return lut
def figaspect(arg): """ Create a figure with specified aspect ratio. If arg is a number, use that aspect ratio. If arg is an array, figaspect will determine the width and height for a figure that would fit array preserving aspect ratio. The figure width, height in inches are returned. Be sure to create an axes with equal with and height, eg Example usage: # make a figure twice as tall as it is wide w, h = figaspect(2.) fig = Figure(figsize=(w,h)) ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) ax.imshow(A, **kwargs) # make a figure with the proper aspect for an array A = rand(5,3) w, h = figaspect(A) fig = Figure(figsize=(w,h)) ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) ax.imshow(A, **kwargs) Thanks to Fernando Perez for this function """ isarray = hasattr(arg, 'shape') # min/max sizes to respect when autoscaling. If John likes the idea, they # could become rc parameters, for now they're hardwired. figsize_min = array((4.0, 2.0)) # min length for width/height figsize_max = array((16.0, 16.0)) # max length for width/height #figsize_min = rcParams['figure.figsize_min'] #figsize_max = rcParams['figure.figsize_max'] # Extract the aspect ratio of the array if isarray: nr, nc = arg.shape[:2] arr_ratio = float(nr) / nc else: arr_ratio = float(arg) # Height of user figure defaults fig_height = rcParams['figure.figsize'][1] # New size for the figure, keeping the aspect ratio of the caller newsize = array((fig_height / arr_ratio, fig_height)) # Sanity checks, don't drop either dimension below figsize_min newsize /= min(1.0, *(newsize / figsize_min)) # Avoid humongous windows as well newsize /= max(1.0, *(newsize / figsize_max)) # Finally, if we have a really funky aspect ratio, break it but respect # the min/max dimensions (we don't want figures 10 feet tall!) newsize = clip(newsize, figsize_min, figsize_max) return newsize
def __call__(self, value): vmin = self.vmin vmax = self.vmax if type(value) in [IntType, FloatType]: vtype = 'scalar' val = array([value]) else: vtype = 'array' val = asarray(value) # if both vmin is None and vmax is None, we'll automatically # norm the data to vmin/vmax of the actual data, so the # clipping step won't be needed. if vmin is None and vmax is None: needs_clipping = False else: needs_clipping = True if vmin is None or vmax is None: rval = ravel(val) if vmin is None: vmin = amin(rval) if vmax is None: vmax = amax(rval) if vmin > vmax: raise ValueError("minvalue must be less than or equal to maxvalue") elif vmin == vmax: return 0. * value else: if needs_clipping: val = clip(val, vmin, vmax) result = (1.0 / (vmax - vmin)) * (val - vmin) if vtype == 'scalar': result = result[0] return result
def __call__(self, value, clip=None): if clip is None: clip = self.clip if isinstance(value, (int, float)): vtype = 'scalar' val = ma.array([value]) else: vtype = 'array' val = ma.asarray(value) self.autoscale(val) vmin, vmax = self.vmin, self.vmax if vmin > vmax: raise ValueError("minvalue must be less than or equal to maxvalue") elif vmin<=0: raise ValueError("values must all be positive") elif vmin==vmax: return 0.*value else: if clip: mask = ma.getmask(val) val = ma.array(nx.clip(val.filled(vmax), vmin, vmax), mask=mask) result = (ma.log(val)-nx.log(vmin))/(nx.log(vmax)-nx.log(vmin)) if vtype == 'scalar': result = result[0] return result
def __call__(self, value): vmin = self.vmin vmax = self.vmax if type(value) in [IntType, FloatType]: vtype = 'scalar' val = array([value]) else: vtype = 'array' val = asarray(value) # if both vmin is None and vmax is None, we'll automatically # norm the data to vmin/vmax of the actual data, so the # clipping step won't be needed. if vmin is None and vmax is None: needs_clipping = False else: needs_clipping = True if vmin is None or vmax is None: rval = ravel(val) if vmin is None: vmin = amin(rval) if vmax is None: vmax = amax(rval) if vmin > vmax: raise ValueError("minvalue must be less than or equal to maxvalue") elif vmin==vmax: return 0.*value else: if needs_clipping: val = clip(val,vmin, vmax) result = (1.0/(vmax-vmin))*(val-vmin) if vtype == 'scalar': result = result[0] return result
def figaspect(arg): """ Create a figure with specified aspect ratio. If arg is a number, use that aspect ratio. If arg is an array, figaspect will determine the width and height for a figure that would fit array preserving aspcect ratio. The figure width, height in inches are returned. Be sure to create an axes with equal with and height, eg Example usage: # make a figure twice as tall as it is wide w, h = figaspect(2.) fig = Figure(figsize=(w,h)) ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) ax.imshow(A, **kwargs) # make a figure with the proper aspect for an array A = rand(5,3) w, h = figaspect(A) fig = Figure(figsize=(w,h)) ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) ax.imshow(A, **kwargs) Thanks to Fernando Perez for this function """ isarray = hasattr(arg, "shape") # min/max sizes to respect when autoscaling. If John likes the idea, they # could become rc parameters, for now they're hardwired. figsize_min = array((4.0, 2.0)) # min length for width/height figsize_max = array((16.0, 16.0)) # max length for width/height # figsize_min = rcParams['figure.figsize_min'] # figsize_max = rcParams['figure.figsize_max'] # Extract the aspect ratio of the array if isarray: nr, nc = arg.shape[:2] arr_ratio = float(nr) / nc else: arr_ratio = float(arg) # Height of user figure defaults fig_height = rcParams["figure.figsize"][1] # New size for the figure, keeping the aspect ratio of the caller newsize = array((fig_height / arr_ratio, fig_height)) # Sanity checks, don't drop either dimension below figsize_min newsize /= min(1.0, *(newsize / figsize_min)) # Avoid humongous windows as well newsize /= max(1.0, *(newsize / figsize_max)) # Finally, if we have a really funky aspect ratio, break it but respect # the min/max dimensions (we don't want figures 10 feet tall!) newsize = clip(newsize, figsize_min, figsize_max) return newsize
def exp_safe(x): """Compute exponentials which safely underflow to zero. Slow but convenient to use. Note that NumArray will introduce proper floating point exception handling with access to the underlying hardware.""" if type(x) is ArrayType: return exp(clip(x,exp_safe_MIN,exp_safe_MAX)) else: return math.exp(x)
def exp_safe(x): """Compute exponentials which safely underflow to zero. Slow but convenient to use. Note that NumArray will introduce proper floating point exception handling with access to the underlying hardware.""" if type(x) is ArrayType: return exp(clip(x, exp_safe_MIN, exp_safe_MAX)) else: return math.exp(x)
def __call__(self, value): if isinstance(value, (int, float)): vtype = 'scalar' val = ma.array([value]) else: vtype = 'array' val = ma.asarray(value) self.autoscale(val) vmin, vmax = self.vmin, self.vmax if vmin > vmax: raise ValueError("minvalue must be less than or equal to maxvalue") elif vmin == vmax: return 0. * value else: if self.clip: val = clip(val.filled(vmax), vmin, vmax) result = (val - vmin) / float(vmax - vmin) if vtype == 'scalar': result = result[0] return result
def __call__(self, value): if isinstance(value, (int, float)): vtype = 'scalar' val = ma.array([value]) else: vtype = 'array' val = ma.asarray(value) self.autoscale(val) vmin, vmax = self.vmin, self.vmax if vmin > vmax: raise ValueError("minvalue must be less than or equal to maxvalue") elif vmin==vmax: return 0.*value else: if self.clip: val = clip(val.filled(vmax), vmin, vmax) result = (1.0/(vmax-vmin))*(val-vmin) if vtype == 'scalar': result = result[0] return result