From 23edf9df78cc10f35c2f11e87e519104a9c434c8 Mon Sep 17 00:00:00 2001
From: Andrew Gait <andrew.gait@manchester.ac.uk>
Date: Tue, 8 Aug 2023 17:09:05 +0100
Subject: [PATCH] Not sure why this file is still here

---
 examples/one_neuron_test.py | 95 -------------------------------------
 1 file changed, 95 deletions(-)
 delete mode 100644 examples/one_neuron_test.py

diff --git a/examples/one_neuron_test.py b/examples/one_neuron_test.py
deleted file mode 100644
index e3e49b60..00000000
--- a/examples/one_neuron_test.py
+++ /dev/null
@@ -1,95 +0,0 @@
-import spynnaker8 as p
-<<<<<<< HEAD
-import numpy
-import math
-import unittest
-from pyNN.utility.plotting import Figure, Panel
-import matplotlib.pyplot as plt
-
-p.setup(0.1) # simulation timestep (ms)
-runtime = 100
-
-# Post-synapse population
-neuron_params = {
-    "v_thresh": -50,
-    "v_reset": -70,
-    "v_rest": -65,
-    "i_offset": 0, # DC input
-    "v": -60
-                 }
-
-spike_times = [10]
-# delays = 250
-delays = 2
-
-
-# pop_src = p.Population(1, p.SpikeSourceArray, {'spike_times': spike_times}, label="src")
-
-
-pop_exc = p.Population(64, # number of neurons
-                       p.IF_curr_exp(**neuron_params),  # Neuron model
-                       label="LIF Neuron" # identifier
-                       )
-
-
-# proj_exc = p.Projection(pop_exc, pop_exc, p.FixedProbabilityConnector(0.99),
-#                     p.StaticSynapse(weight=0.01, delay=delays), receptor_type="excitatory")
-#
-# proj_inh = p.Projection(pop_src, pop_exc, p.FixedProbabilityConnector(0.99),
-#                     p.StaticSynapse(weight=0.1, delay=delays), receptor_type="inhibitory")
-
-# pop_exc.record("all")
-
-p.run(runtime)
-
-# exc_data = pop_exc.get_data()
-
-# syn_weight_exc = proj_exc.get('weight', 'list', with_address=False)
-# syn_weight_inh = proj_inh.get('weight', 'list', with_address=False)
-
-# print syn_weight_exc
-# , syn_weight_inh
-
-# Plot
-# F = Figure(
-#     # plot data for postsynaptic neuron
-#     Panel(exc_data.segments[0].filter(name='v')[0],
-#           ylabel="Membrane potential (mV)",
-#           data_labels=[pop_exc.label], yticks=True, xlim=(0, runtime)
-#           ),
-#     Panel(exc_data.segments[0].filter(name='gsyn_exc')[0],
-#           ylabel="gsyn excitatory (mV)",
-#           data_labels=[pop_exc.label], yticks=True, xlim=(0, runtime)
-#           ),
-#     Panel(exc_data.segments[0].filter(name='gsyn_inh')[0],
-#           ylabel="gsyn inhibitory (mV)",
-#           data_labels=[pop_exc.label], yticks=True, xlim=(0, runtime)
-#           ),
-#     Panel(exc_data.segments[0].spiketrains,
-#           yticks=True, markersize=2, xlim=(0, runtime)
-#           ),
-#     )
-
-# plt.show()
-
-p.end()
-print 'job done'
-
-=======
-
-
-timestep=1
-p.setup(timestep)
-
-
-pop_ex1 = p.Population(2, p.IF_curr_exp, {}, label="ex1")
-
-# pop_ex1.record('all')
-
-p.run(100)
-
-# res = pop_ex1.get_data('all')
-
-p.end()
-print("\n job done")
->>>>>>> b26172aaea9bede0b09ea127cc71436332b4c960