Last modified by adavison on 2022/10/04 13:55
From version 18.1
edited by adavison
on 2021/12/01 13:07
Change comment: There is no comment for this version
To version 20.1
edited by adavison
on 2021/12/01 15:21
Change comment: There is no comment for this version

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... ... @@ -169,9 +169,9 @@
169 169  (% style="color:#e74c3c" %)from pyNN.random import RandomDistribution(%%)
170 170  (% style="color:#000000" %)sim.setup(timestep=0.1)(%%)
171 171  (% style="color:#000000" %)cell_type  = sim.IF_curr_exp(
172 - (% style="color:#e74c3c" %) v_rest=RandomDistribution('normal', {'mu': -65.0, 'sigma': 1.0}),
173 - v_thresh=RandomDistribution('normal', {'mu': -55.0, 'sigma': 1.0}),
174 - v_reset=RandomDistribution('normal', {'mu': -65.0, 'sigma': 1.0}), (%%)
172 + (% style="color:#e74c3c" %) v_rest=RandomDistribution('normal', mu=-65.0, sigma=1.0),
173 + v_thresh=RandomDistribution('normal', mu=-55.0, sigma=1.0),
174 + v_reset=RandomDistribution('normal', mu=-65.0, sigma=1.0), (%%)
175 175  (% style="color:#000000" %) tau_refrac=1, tau_m=10, cm=1, i_offset=0.1)(%%)
176 176  
177 177  
... ... @@ -263,7 +263,7 @@
263 263  
264 264  **...**
265 265  (% style="color:#000000" %)population2.record("v")(%%)
266 -(% style="color:#e74c3c" %)connection_algorithm = sim.FixedProbabilityConnector(p=0.5)
266 +(% style="color:#e74c3c" %)connection_algorithm = sim.FixedProbabilityConnector(p_connect=0.5)
267 267  synapse_type = sim.StaticSynapse(weight=0.5, delay=0.5)
268 268  connections = sim.Projection(population1, population2, connection_algorithm, synapse_type)(%%)
269 269  (% style="color:#000000" %)sim.run(100.0)(%%)
... ... @@ -310,9 +310,9 @@
310 310  (% style="color:#000000" %)from pyNN.random import RandomDistribution(%%)
311 311  (% style="color:#000000" %)sim.setup(timestep=0.1)(%%)
312 312  (% style="color:#000000" %)cell_type  = sim.IF_curr_exp(
313 - (% style="color:#e74c3c" %) (% style="color:#000000" %)v_rest=RandomDistribution('normal', {'mu': -65.0, 'sigma': 1.0}),
314 - v_thresh=RandomDistribution('normal', {'mu': -55.0, 'sigma': 1.0}),
315 - v_reset=RandomDistribution('normal', {'mu': -65.0, 'sigma': 1.0}), (%%)
313 + (% style="color:#e74c3c" %) (% style="color:#000000" %)v_rest=RandomDistribution('normal', mu=-65.0, sigma=1.0),
314 + v_thresh=RandomDistribution('normal', mu=-55.0, sigma=1.0),
315 + v_reset=RandomDistribution('normal', mu=-65.0, sigma=1.0), (%%)
316 316  (% style="color:#000000" %) tau_refrac=1, tau_m=10, cm=1, i_offset=0.1)(%%)
317 317  (% style="color:#000000" %)population1 = sim.Population(100, cell_type, label="Population 1")(%%)
318 318  (% style="color:#000000" %)population2 = sim.Population(100, cell_type, label="Population 2")
... ... @@ -319,7 +319,7 @@
319 319  population2.set(i_offset=0)
320 320  population1.record("v")
321 321  population2.record("v")(%%)
322 -(% style="color:#000000" %)connection_algorithm = sim.FixedProbabilityConnector(p=0.5)
322 +(% style="color:#000000" %)connection_algorithm = sim.FixedProbabilityConnector(p_connect=0.5)
323 323  synapse_type = sim.StaticSynapse(weight=0.5, delay=0.5)
324 324  connections = sim.Projection(population1, population2, connection_algorithm, synapse_type)(%%)
325 325  (% style="color:#000000" %)sim.run(100.0)(%%)