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138 lines
4.8 KiB
Python
138 lines
4.8 KiB
Python
# igc2kmz/scale.py igc2kmz scale functions
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# Copyright (C) 2008 Tom Payne
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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import datetime
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import itertools
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import time
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import util
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class Scale(object):
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"""A linear scale."""
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def __init__(self, range, title=None, gradient=None, step=1,
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max_divisions=16):
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self.range = range
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self.title = title
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self.gradient = gradient
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def steps(step=None):
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while True:
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yield step
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yield 2 * step
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yield 5 * step
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step *= 10
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if step:
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for step in steps(step):
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lower = int(self.range[0] / step)
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upper = int(self.range[1] / step)
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if self.range[0] < step * lower:
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lower -= 1
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if self.range[1] > step * upper:
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upper += 1
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if upper - lower <= max_divisions:
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self.grid_step = '%.1f' % (100.0 / (upper - lower))
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self.range = (step * lower, step * upper)
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self.step = step
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break
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def normalize(self, value):
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"""Normalize value."""
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if value < self.range[0]:
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return 0.0
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elif self.range[1] <= value:
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return 1.0
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else:
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return float(value - self.range[0]) \
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/ (self.range[1] - self.range[0])
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def discretize(self, value, n=32):
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"""Discretize value."""
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if value < self.range[0]:
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return 0
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elif value > self.range[1]:
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return n - 1
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else:
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result = int(round(n * self.normalize(value)))
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if result > n - 1:
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return n - 1
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else:
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return result
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def color(self, value):
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"""Return the color for value."""
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return self.gradient(self.normalize(value))
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def colors(self, n=32):
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"""Return the colors."""
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return [self.gradient(float(i) / (n - 1)) for i in xrange(0, n)]
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class ZeroCenteredScale(Scale):
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"""A bilinear scale centered on zero."""
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def normalize(self, value):
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"""Normalize value."""
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if value < 0.0:
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if value < self.range[0]:
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return 0.0
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else:
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return 0.5 - 0.5 * value / self.range[0]
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elif value == 0.0:
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return 0.5
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else:
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if self.range[1] <= value:
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return 1.0
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else:
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return 0.5 + 0.5 * value / self.range[1]
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class TimeScale(Scale):
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def __init__(self, range, title=None, gradient=None, step=1,
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max_divisions=16, tz_offset=datetime.timedelta(0, 0)):
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def steps(step=None):
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steps = [1, 5, 15, 30, 60,
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5 * 60, 15 * 60, 30 * 60,
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3600, 3 * 3600, 6 * 3600, 12 * 3600]
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return itertools.imap(lambda s: datetime.timedelta(0, s),
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itertools.dropwhile(lambda s: s < step,
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steps))
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lower, upper = range
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if step:
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for step in steps(step):
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lower = util.datetime_floor(range[0], step)
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upper = util.datetime_floor(range[1], step)
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if upper < range[1]:
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upper += step
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if (upper - lower).seconds / step.seconds < max_divisions:
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range = (int(time.mktime(lower.timetuple())),
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int(time.mktime(upper.timetuple())))
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self.grid_step = '%.1f' % (100.0 * step.seconds
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/ (upper - lower).seconds)
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self.step = step
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break
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Scale.__init__(self, range, title=title, gradient=gradient, step=None)
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self.labels, self.positions = [], []
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t = datetime.datetime(lower.year, lower.month, lower.day, lower.hour) \
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+ self.step
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while t < upper:
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self.labels.append((t + tz_offset).strftime('%H:%M'))
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self.positions.append('%1.f' % (100.0 * (t - lower).seconds
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/ (upper - lower).seconds))
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t += self.step
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