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""" Defines the LogMapper and InvalidDataRangeException classes.
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# Major library imports
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from numpy import array, isnan, log, log10, exp, zeros, sometrue,\
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# Enthought library imports
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from enthought.traits.api import Bool, Float
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#Local relative imports
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from base_1d_mapper import Base1DMapper
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class InvalidDataRangeException(Exception):
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class LogMapper(Base1DMapper):
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""" Defines a 1-D logarithmic scale mapping from a 1-D region in input
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space to a 1-D region in output space.
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# The value to map when asked to map values <= LOG_MINIMUM to screen space.
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fill_value = Float(1.0)
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#------------------------------------------------------------------------
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#------------------------------------------------------------------------
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_inter_scale = Float(0.0)
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_inter_offset = Float(0.0)
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_screen_scale = Float(0.0)
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_screen_offset = Float(0.0)
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_null_screen_range = Bool(False)
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_null_data_range = Bool(False)
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#------------------------------------------------------------------------
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#------------------------------------------------------------------------
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def map_screen(self, data_array):
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""" map_screen(data_array) -> screen_array
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Overrides AbstractMapper. Maps values from data space to screen space.
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#First convert to a [0,1] space, then to the screen space
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if not self._cache_valid:
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if self._inter_scale == 0.0:
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intermediate = data_array*0.0
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mask = (data_array <= LOG_MINIMUM) | isnan(data_array)
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data_array = array(data_array, copy=True, ndmin=1)
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data_array[mask] = self.fill_value
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intermediate = (log(data_array) - self._inter_offset)/self._inter_scale
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intermediate = zeros(len(data_array))
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return intermediate * self._screen_scale + self._screen_offset
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def map_data(self, screen_val):
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""" map_data(screen_val) -> data_val
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Overrides Abstract Mapper. Maps values from screen space into data space.
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if not self._cache_valid:
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if self._null_screen_range or self._null_data_range:
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return array([self.range.low])
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#First convert to a [0,1] space, then to the data space
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intermediate = (screen_val-self._screen_offset)/self._screen_scale
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return exp(self._inter_scale*intermediate + self._inter_offset)
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def map_data_array(self, screen_vals):
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return self.map_data(screen_vals)
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#------------------------------------------------------------------------
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#------------------------------------------------------------------------
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def _get_safe_scale(self, range):
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orig_high = range.high
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if orig_low < LOG_MINIMUM:
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if orig_high < LOG_MINIMUM:
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if low == LOG_MINIMUM:
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low = pow(10, floor(log_val))
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if ceil(log_val) != floor(log_val):
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high = pow(10, ceil(log_val))
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high = pow(10, ceil(log_val) + 1)
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def _compute_scale(self):
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if self._cache_valid:
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if self.range is None:
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self._cache_valid = False
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screen_range = self.high_pos - self.low_pos
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if screen_range == 0.0:
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self._null_screen_range = True
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# Get dataspace low and high from the range that are "safe" for a
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# logarithmic mapper, i.e. constrained to be between LOG_MINIMUM and inf.
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low, high = self._get_safe_scale(self.range)
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self._null_data_range = True
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if low == LOG_MINIMUM:
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self._inter_scale = log(high)
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self._inter_offset = 0.0
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self._inter_scale = log(high)-log(low)
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self._inter_offset = log(low)
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self._screen_scale = screen_range
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self._screen_offset = self.low_pos
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self._cache_valid = True
added
removed
enthought/chaco/log_mapper.py
