diff --git a/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py b/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py
index fce46e7026065d37e94d0b35b9a057ab545e1b04..1e10dbd6c410442e0d5c9f7eb2e823c7a9648cd0 100644
--- a/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py
+++ b/figures/MAM2EBRAINS/.ipynb_checkpoints/M2E_visualize_interareal_connectivity-checkpoint.py
@@ -26,7 +26,7 @@ def visualize_interareal_connectivity(M):
"""
# nrows = 2
nrows = 1
- ncols = 3
+ ncols = 2
# width = 6.8556
width = 15
panel_wh_ratio = 0.7 * (1. + np.sqrt(5)) / 2. # golden ratio
@@ -40,23 +40,25 @@ def visualize_interareal_connectivity(M):
axes = {}
# gs1 = gridspec.GridSpec(2, 2)
- gs1 = gridspec.GridSpec(1, 3)
+ gs1 = gridspec.GridSpec(1, 2)
# gs1.update(left=0.06, right=0.95, top=0.95, bottom=0.1, wspace=0.1, hspace=0.3)
gs1.update(left=0.06, right=0.95, top=0.95, bottom=0.1, wspace=0.3, hspace=0.3)
- axes['A'] = pl.subplot(gs1[:1, :1])
- axes['B'] = pl.subplot(gs1[:1, 1:2])
- axes['D'] = pl.subplot(gs1[:1, 2:])
+ # axes['A'] = pl.subplot(gs1[:1, :1])
+ # axes['B'] = pl.subplot(gs1[:1, 1:2])
+ axes['B'] = pl.subplot(gs1[:1, :1])
+ # axes['D'] = pl.subplot(gs1[:1, 2:])
+ axes['D'] = pl.subplot(gs1[:1, 1:2])
- pos = axes['A'].get_position()
+ # pos = axes['A'].get_position()
pos2 = axes['D'].get_position()
# axes['C'] = pl.axes([pos.x0 + 0.01, pos2.y0, pos.x1 - pos.x0 - 0.025, 0.23])
# print(pos.x1 - pos.x0 - 0.025)
# labels = ['A', 'B', 'C', 'D']
- labels = ['A','B', 'D']
- labels_display = ['Binary connectivity from CoCoMac', 'Full-scale model', 'Down-scale model']
+ labels = ['B', 'D']
+ labels_display = ['Full-scale model', 'Down-scale model']
# for label in labels:
for i in range(len(labels)):
label = labels[i]
@@ -74,71 +76,71 @@ def visualize_interareal_connectivity(M):
'horizontalalignment': 'left', 'verticalalignment':
'bottom'}, transform=axes[label].transAxes)
- """
- Load data
- """
- # M = MultiAreaModel({})
- M_full_scale = MultiAreaModel({})
+# """
+# Load data
+# """
+# # M = MultiAreaModel({})
+# M_full_scale = MultiAreaModel({})
- datapath = './multiarea_model/data_multiarea/'
- with open(os.path.join(datapath, 'viscortex_processed_data.json'), 'r') as f:
- proc = json.load(f)
- with open(os.path.join(datapath, 'viscortex_raw_data.json'), 'r') as f:
- raw = json.load(f)
-
- FLN_Data_FV91 = proc['FLN_Data_FV91']
+# datapath = './multiarea_model/data_multiarea/'
+# with open(os.path.join(datapath, 'viscortex_processed_data.json'), 'r') as f:
+# proc = json.load(f)
+# with open(os.path.join(datapath, 'viscortex_raw_data.json'), 'r') as f:
+# raw = json.load(f)
+
+# FLN_Data_FV91 = proc['FLN_Data_FV91']
+
+# cocomac_data = raw['cocomac_data']
+# median_distance_data = raw['median_distance_data']
+
+# cocomac = np.zeros((32, 32))
+# conn_matrix = np.zeros((32, 32))
+# for i, area1 in enumerate(area_list[::-1]):
+# for j, area2 in enumerate(area_list):
+# # if M.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
+# if M_full_scale.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
+# cocomac[i][j] = 1.
+# if area2 in FLN_Data_FV91[area1]:
+# conn_matrix[i][j] = FLN_Data_FV91[area1][area2]
- cocomac_data = raw['cocomac_data']
- median_distance_data = raw['median_distance_data']
-
- cocomac = np.zeros((32, 32))
- conn_matrix = np.zeros((32, 32))
- for i, area1 in enumerate(area_list[::-1]):
- for j, area2 in enumerate(area_list):
- # if M.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
- if M_full_scale.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
- cocomac[i][j] = 1.
- if area2 in FLN_Data_FV91[area1]:
- conn_matrix[i][j] = FLN_Data_FV91[area1][area2]
-
- """
- Panel A: CoCoMac Data
- """
- ax = axes['A']
- # ax.yaxis.set_ticks_position("left")
- # ax.xaxis.set_ticks_position("bottom")
+# """
+# Panel A: CoCoMac Data
+# """
+# ax = axes['A']
+# # ax.yaxis.set_ticks_position("left")
+# # ax.xaxis.set_ticks_position("bottom")
- ax.set_aspect(1. / ax.get_data_ratio())
- ax.yaxis.set_ticks_position("none")
- ax.xaxis.set_ticks_position("none")
+# ax.set_aspect(1. / ax.get_data_ratio())
+# ax.yaxis.set_ticks_position("none")
+# ax.xaxis.set_ticks_position("none")
- masked_matrix = np.ma.masked_values(cocomac, 0.0)
- cmap = pl.cm.binary
- cmap.set_bad('w', 1.0)
+# masked_matrix = np.ma.masked_values(cocomac, 0.0)
+# cmap = pl.cm.binary
+# cmap.set_bad('w', 1.0)
- x = np.arange(0, len(area_list) + 1)
- y = np.arange(0, len(area_list[::-1]) + 1)
- X, Y = np.meshgrid(x, y)
+# x = np.arange(0, len(area_list) + 1)
+# y = np.arange(0, len(area_list[::-1]) + 1)
+# X, Y = np.meshgrid(x, y)
- ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
- ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
- # ax.set_xticklabels(area_list, rotation=90, size=6.)
- ax.set_xticklabels(area_list, rotation=90, size=10.)
+# ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
+# ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
+# # ax.set_xticklabels(area_list, rotation=90, size=6.)
+# ax.set_xticklabels(area_list, rotation=90, size=10.)
- # ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
- ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
- # ax.set_yticklabels(area_list[::-1], size=6.)
- ax.set_yticklabels(area_list[::-1], size=6.)
+# # ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
+# ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
+# # ax.set_yticklabels(area_list[::-1], size=6.)
+# ax.set_yticklabels(area_list[::-1], size=6.)
- ax.set_ylabel('Target area')
- ax.set_xlabel('Source area')
+# ax.set_ylabel('Target area')
+# ax.set_xlabel('Source area')
- im = ax.pcolormesh(masked_matrix, cmap=cmap,
- edgecolors='None', vmin=0., vmax=1.)
+# im = ax.pcolormesh(masked_matrix, cmap=cmap,
+# edgecolors='None', vmin=0., vmax=1.)
- t = FixedLocator([])
- cbar = pl.colorbar(im, ticks=t, fraction=0.046, ax=ax)
- cbar.set_alpha(0.)
+# t = FixedLocator([])
+# cbar = pl.colorbar(im, ticks=t, fraction=0.046, ax=ax)
+# cbar.set_alpha(0.)
# cbar.remove()
# """
diff --git a/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py b/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py
index fce46e7026065d37e94d0b35b9a057ab545e1b04..1e10dbd6c410442e0d5c9f7eb2e823c7a9648cd0 100644
--- a/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py
+++ b/figures/MAM2EBRAINS/M2E_visualize_interareal_connectivity.py
@@ -26,7 +26,7 @@ def visualize_interareal_connectivity(M):
"""
# nrows = 2
nrows = 1
- ncols = 3
+ ncols = 2
# width = 6.8556
width = 15
panel_wh_ratio = 0.7 * (1. + np.sqrt(5)) / 2. # golden ratio
@@ -40,23 +40,25 @@ def visualize_interareal_connectivity(M):
axes = {}
# gs1 = gridspec.GridSpec(2, 2)
- gs1 = gridspec.GridSpec(1, 3)
+ gs1 = gridspec.GridSpec(1, 2)
# gs1.update(left=0.06, right=0.95, top=0.95, bottom=0.1, wspace=0.1, hspace=0.3)
gs1.update(left=0.06, right=0.95, top=0.95, bottom=0.1, wspace=0.3, hspace=0.3)
- axes['A'] = pl.subplot(gs1[:1, :1])
- axes['B'] = pl.subplot(gs1[:1, 1:2])
- axes['D'] = pl.subplot(gs1[:1, 2:])
+ # axes['A'] = pl.subplot(gs1[:1, :1])
+ # axes['B'] = pl.subplot(gs1[:1, 1:2])
+ axes['B'] = pl.subplot(gs1[:1, :1])
+ # axes['D'] = pl.subplot(gs1[:1, 2:])
+ axes['D'] = pl.subplot(gs1[:1, 1:2])
- pos = axes['A'].get_position()
+ # pos = axes['A'].get_position()
pos2 = axes['D'].get_position()
# axes['C'] = pl.axes([pos.x0 + 0.01, pos2.y0, pos.x1 - pos.x0 - 0.025, 0.23])
# print(pos.x1 - pos.x0 - 0.025)
# labels = ['A', 'B', 'C', 'D']
- labels = ['A','B', 'D']
- labels_display = ['Binary connectivity from CoCoMac', 'Full-scale model', 'Down-scale model']
+ labels = ['B', 'D']
+ labels_display = ['Full-scale model', 'Down-scale model']
# for label in labels:
for i in range(len(labels)):
label = labels[i]
@@ -74,71 +76,71 @@ def visualize_interareal_connectivity(M):
'horizontalalignment': 'left', 'verticalalignment':
'bottom'}, transform=axes[label].transAxes)
- """
- Load data
- """
- # M = MultiAreaModel({})
- M_full_scale = MultiAreaModel({})
+# """
+# Load data
+# """
+# # M = MultiAreaModel({})
+# M_full_scale = MultiAreaModel({})
- datapath = './multiarea_model/data_multiarea/'
- with open(os.path.join(datapath, 'viscortex_processed_data.json'), 'r') as f:
- proc = json.load(f)
- with open(os.path.join(datapath, 'viscortex_raw_data.json'), 'r') as f:
- raw = json.load(f)
-
- FLN_Data_FV91 = proc['FLN_Data_FV91']
+# datapath = './multiarea_model/data_multiarea/'
+# with open(os.path.join(datapath, 'viscortex_processed_data.json'), 'r') as f:
+# proc = json.load(f)
+# with open(os.path.join(datapath, 'viscortex_raw_data.json'), 'r') as f:
+# raw = json.load(f)
+
+# FLN_Data_FV91 = proc['FLN_Data_FV91']
+
+# cocomac_data = raw['cocomac_data']
+# median_distance_data = raw['median_distance_data']
+
+# cocomac = np.zeros((32, 32))
+# conn_matrix = np.zeros((32, 32))
+# for i, area1 in enumerate(area_list[::-1]):
+# for j, area2 in enumerate(area_list):
+# # if M.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
+# if M_full_scale.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
+# cocomac[i][j] = 1.
+# if area2 in FLN_Data_FV91[area1]:
+# conn_matrix[i][j] = FLN_Data_FV91[area1][area2]
- cocomac_data = raw['cocomac_data']
- median_distance_data = raw['median_distance_data']
-
- cocomac = np.zeros((32, 32))
- conn_matrix = np.zeros((32, 32))
- for i, area1 in enumerate(area_list[::-1]):
- for j, area2 in enumerate(area_list):
- # if M.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
- if M_full_scale.K_areas[area1][area2] > 0. and area2 in cocomac_data[area1]:
- cocomac[i][j] = 1.
- if area2 in FLN_Data_FV91[area1]:
- conn_matrix[i][j] = FLN_Data_FV91[area1][area2]
-
- """
- Panel A: CoCoMac Data
- """
- ax = axes['A']
- # ax.yaxis.set_ticks_position("left")
- # ax.xaxis.set_ticks_position("bottom")
+# """
+# Panel A: CoCoMac Data
+# """
+# ax = axes['A']
+# # ax.yaxis.set_ticks_position("left")
+# # ax.xaxis.set_ticks_position("bottom")
- ax.set_aspect(1. / ax.get_data_ratio())
- ax.yaxis.set_ticks_position("none")
- ax.xaxis.set_ticks_position("none")
+# ax.set_aspect(1. / ax.get_data_ratio())
+# ax.yaxis.set_ticks_position("none")
+# ax.xaxis.set_ticks_position("none")
- masked_matrix = np.ma.masked_values(cocomac, 0.0)
- cmap = pl.cm.binary
- cmap.set_bad('w', 1.0)
+# masked_matrix = np.ma.masked_values(cocomac, 0.0)
+# cmap = pl.cm.binary
+# cmap.set_bad('w', 1.0)
- x = np.arange(0, len(area_list) + 1)
- y = np.arange(0, len(area_list[::-1]) + 1)
- X, Y = np.meshgrid(x, y)
+# x = np.arange(0, len(area_list) + 1)
+# y = np.arange(0, len(area_list[::-1]) + 1)
+# X, Y = np.meshgrid(x, y)
- ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
- ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
- # ax.set_xticklabels(area_list, rotation=90, size=6.)
- ax.set_xticklabels(area_list, rotation=90, size=10.)
+# ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
+# ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
+# # ax.set_xticklabels(area_list, rotation=90, size=6.)
+# ax.set_xticklabels(area_list, rotation=90, size=10.)
- # ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
- ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
- # ax.set_yticklabels(area_list[::-1], size=6.)
- ax.set_yticklabels(area_list[::-1], size=6.)
+# # ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list) + 1, 1)])
+# ax.set_yticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
+# # ax.set_yticklabels(area_list[::-1], size=6.)
+# ax.set_yticklabels(area_list[::-1], size=6.)
- ax.set_ylabel('Target area')
- ax.set_xlabel('Source area')
+# ax.set_ylabel('Target area')
+# ax.set_xlabel('Source area')
- im = ax.pcolormesh(masked_matrix, cmap=cmap,
- edgecolors='None', vmin=0., vmax=1.)
+# im = ax.pcolormesh(masked_matrix, cmap=cmap,
+# edgecolors='None', vmin=0., vmax=1.)
- t = FixedLocator([])
- cbar = pl.colorbar(im, ticks=t, fraction=0.046, ax=ax)
- cbar.set_alpha(0.)
+# t = FixedLocator([])
+# cbar = pl.colorbar(im, ticks=t, fraction=0.046, ax=ax)
+# cbar.set_alpha(0.)
# cbar.remove()
# """