def value_color(cls, value):
import matplotlib.cm as cm
if value is None or np.isnan(value):
rgb = (128, 128, 128)
else:
cmap_low = config_get('cmap_low', 38)
cmap_high = config_get('cmap_high', 218)
cmap_range = cmap_high - cmap_low
cmap = cm.RdYlGn(int(cmap_range * value + cmap_low))[:3]
rgb = tuple([x * 256 for x in cmap])
return rgb
def value_color(cls, value):
import matplotlib.cm as cm
if value is None or np.isnan(value):
rgb = (128,128,128)
else:
cmap_low = config_get('cmap_low',38)
cmap_high = config_get('cmap_high',218)
cmap_range = cmap_high - cmap_low
cmap = cm.RdYlGn(int(cmap_range*value+cmap_low))[:3]
rgb = tuple([x*256 for x in cmap])
return rgb
def test_json_config(self):
from sciunit.utils import config_get
config_path = os.path.join(sciunit.__path__[0],'config.json')
print(config_path)
self.assertTrue(os.path.isfile(config_path))
cmap_low = config_get('cmap_low')
self.assertTrue(isinstance(cmap_low,int))
dummy = config_get('dummy',37)
self.assertEqual(dummy,37)
try:
config_get('dummy')
except sciunit.Error as e:
self.assertTrue('does not contain key' in str(e))
def test_json_config(self):
from sciunit.utils import config_get, create_config, DEFAULT_CONFIG
from pathlib import Path
config_path = Path.home() / ".sciunit" / "config.json"
create_config(DEFAULT_CONFIG)
self.assertTrue(config_path.is_file())
cmap_low = config_get("cmap_low")
self.assertTrue(isinstance(cmap_low, int))
dummy = config_get("dummy", 37)
self.assertEqual(dummy, 37)
try:
config_get("dummy")
except sciunit.Error as e:
self.assertTrue("does not contain key" in str(e))
def value_color(cls, value: Union[float, 'Score']) -> tuple:
"""Get a RGB color based on the Score.
Args:
value (Union[float,): [description]
Returns:
tuple: [description]
"""
import matplotlib.cm as cm
if value is None or np.isnan(value):
rgb = (128, 128, 128)
else:
cmap_low = config_get('cmap_low', 38)
cmap_high = config_get('cmap_high', 218)
cmap_range = cmap_high - cmap_low
cmap = cm.RdYlGn(int(cmap_range * value + cmap_low))[:3]
rgb = tuple([x * 256 for x in cmap])
return rgb
from neuronunit.optimization.optimization_management import (
dtc_to_rheo,
inject_and_plot_model,
)
import numpy as np
from neuronunit.optimization.data_transport_container import DataTC as GenericModel
from jithub.models import model_classes
import matplotlib.pyplot as plt
import quantities as qt
import os
from sciunit.scores import RelativeDifferenceScore, ZScore
from sciunit.utils import config_set, config_get
config_set("PREVALIDATE", False)
assert config_get("PREVALIDATE") is False
class testOptimizationAllenMultiSpike(unittest.TestCase):
def setUp(self):
self = self
# In principle any index into data should work
# but '1' is chosen here. Robust tests would use any index.
self.ids = [
324257146,
325479788,
476053392,
623893177,
623960880,
482493761,
471819401,