Python scale_x_log Examples

Example #1

File: celltypes.py Project: mfiers/rat

def signature_data_plot(sd):
    import ggplot as gg

    aes = gg.aes(x='set_exp', y='not_exp', color='pearson_r')
    return gg.ggplot(aes, data=sd) \
        + gg.geom_point(size=15) \
        + gg.scale_color_gradient(low='yellow', high='red') \
        + gg.scale_x_log() + gg.scale_x_continuous(limits=(0.5, 10000)) \
        + gg.scale_y_log() + gg.scale_y_continuous(limits=(0.05, 10000))

Example #2

File: celltypes.py Project: mfiers/rat

def signature_data_plot(sd):
    import ggplot as gg

    aes = gg.aes(x='set_exp', y='not_exp', color='pearson_r')
    return gg.ggplot(aes, data=sd) \
        + gg.geom_point(size=15) \
        + gg.scale_color_gradient(low='yellow', high='red') \
        + gg.scale_x_log() + gg.scale_x_continuous(limits=(0.5, 10000)) \
        + gg.scale_y_log() + gg.scale_y_continuous(limits=(0.05, 10000))

Example #3

File: main.py Project: aragilar/odes

data = []
for method in methods:
    for model in models:
        for rtol in rtols:
            print('method: {} model: {} rtol: {}'.format(method.name, model.name, rtol), end='')

            # Run
            tic = time.time()
            result = method(model, rtol)
            toc = time.time() - tic

            # Compare to gold standard
            standard = gold_standards[model.name]
            diff = result - standard.values
            max_rel_diff = np.max(diff/standard.max)

            # Append to table
            record = (method.name, model.name, rtol, max_rel_diff, toc)
            print(' err: {} toc: {}'.format(max_rel_diff, toc))
            data.append(record)


data = DataFrame(data, columns=['method', 'model', 'rtol', 'err', 'time'])

print(gg.ggplot(data, gg.aes(x='err', y='time', color='method'))
      + gg.geom_point(size=60.0)
      + gg.geom_line()
      + gg.scale_x_log()
      + gg.scale_y_log()
      + gg.xlim(1e-10, 1e-2))

Example #4

data = []
for method in methods:
    for model in models:
        for rtol in rtols:
            print('method: {} model: {} rtol: {}'.format(
                method.name, model.name, rtol),
                  end='')

            # Run
            tic = time.time()
            result = method(model, rtol)
            toc = time.time() - tic

            # Compare to gold standard
            standard = gold_standards[model.name]
            diff = result - standard.values
            max_rel_diff = np.max(diff / standard.max)

            # Append to table
            record = (method.name, model.name, rtol, max_rel_diff, toc)
            print(' err: {} toc: {}'.format(max_rel_diff, toc))
            data.append(record)

data = DataFrame(data, columns=['method', 'model', 'rtol', 'err', 'time'])

print(
    gg.ggplot(data, gg.aes(x='err', y='time', color='method')) +
    gg.geom_point(size=60.0) + gg.geom_line() + gg.scale_x_log() +
    gg.scale_y_log() + gg.xlim(1e-10, 1e-2))

Example #5

File: test_ggplot.py Project: ChickenProp/ggplot

 def test_scale_x_log_base(self):
     p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_x_log(base=100)
     self.assertEqual(p.scale_x_log, 100)

Example #6

File: test_ggplot.py Project: ChickenProp/ggplot

 def test_scale_x_log_default10(self):
     p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_x_log()
     self.assertEqual(p.scale_x_log, 10)

Example #7

 def test_scale_x_log_base(self):
     p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_x_log(base=100)
     self.assertEqual(p.scale_x_log, 100)

Example #8

 def test_scale_x_log_default10(self):
     p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_x_log()
     self.assertEqual(p.scale_x_log, 10)