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encinass1u
School_project
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Cell_behavior_initial_steps/single_cell_prolif_migr.py
+
20
−
17
Options
@@ -8,7 +8,7 @@ import random
from
scipy
import
ndimage
from
bio2mslib.inout.inout
import
WriteData
as
WD
import
os
from
Gts_selection
import
L
,
Lx
,
Ly
from
Gts_selection
import
L
from
bio2mslib.analysis.models
import
CellModels
as
DM
from
matplotlib.pyplot
import
figure
@@ -21,18 +21,20 @@ if os.path.isdir(path_simulation) == False :
os
.
mkdir
(
path_simulation
)
#Reopening choosen surface
with
open
(
'
Gts_Sample
_100
.cvs
'
,
'
rb
'
)
as
csv_file
:
with
open
(
'
Gts_Sample.cvs
'
,
'
rb
'
)
as
csv_file
:
Gts
=
pickle
.
load
(
csv_file
)
# #Visual preentation in image of the matrix
# im1 = plt.imshow(Gts, cmap="bone")
# plt.show()
#Gs is ground seeded, a copy of the choosen surface to seed the cells,
Gs
=
copy
.
deepcopy
(
Gts
)
#uni_cell is the seeding of a single cell inside the treated surface.
uni_cell
=
Gs
[(
86
,
8
)]
Gs
[(
86
,
8
)]
=
1
uni_cell
=
Gs
[(
8
,
8
)]
Gs
[(
8
,
8
)]
=
1.5
plt
.
title
(
"
Gts, Inital seeding
"
,
size
=
20
)
#images of the cell in the surface
couture
=
plt
.
imshow
(
Gs
,
cmap
=
"
bone
"
)
plt
.
show
()
#Variable deffinition for PDE proliferation & migration model
Cd
=
1
*
10
**-
5
#Cell density
@@ -48,20 +50,21 @@ time_lapse = 0.1
Gscopy
=
copy
.
deepcopy
(
Gs
)
Laplace
=
ndimage
.
laplace
(
Gs
)
#Migration
iter
=
0
while
iter
<=
1
5
:
for
mi
in
range
(
1
,
len
(
Lx
)
-
1
):
for
mj
in
range
(
1
,
len
(
Ly
)
-
1
):
iter
=
1
while
iter
<=
5
:
for
mi
in
range
(
1
,
L
-
1
):
for
mj
in
range
(
1
,
L
-
1
):
x
=
random
.
randint
(
-
1
,
1
)
#horizontal value for the movement of the cell
y
=
random
.
randint
(
-
1
,
1
)
#vertival value for the movement of the cell
if
Gs
[
mi
,
mj
]
==
1
and
(
x
!=
0
or
y
!=
0
)
and
((
mi
+
x
)
<
len
(
Lx
)
)
and
((
mj
+
y
)
<
len
(
Ly
)
):
Gs
[
mi
+
x
,
mj
+
y
]
=
1
Gs
[
mi
,
mj
]
=
0
if
Gs
[
mi
,
mj
]
==
1
.5
and
(
x
!=
0
or
y
!=
0
)
and
((
mi
+
x
)
<
L
)
and
((
mj
+
y
)
<
L
):
Gs
[
mi
+
x
,
mj
+
y
]
=
1
.5
Gs
[
mi
,
mj
]
+
=
0
#Proliferation after migration
Gs
[
mi
,
mj
]
=
Gscopy
[
mi
,
mj
]
+
dt
*
Dm
*
Laplace
[
mi
,
mj
]
*
(
1
-
(
Gscopy
[
mi
,
mj
]
/
Cdmax
))
+
CRgrw
*
1
*
Gscopy
[
mi
,
mj
]
*
(
1
-
(
Gscopy
[
mi
,
mj
]
/
Cdmax
))
if
Gs
[
mi
,
mj
]
>
0
and
Gs
[
mi
,
mj
]
!=
0.7
and
Gs
[
mi
,
mj
]
!=
0.5
:
Gs
[
mi
,
mj
]
=
1
zoom
=
True
if
Gs
[
mi
,
mj
]
>
0
and
Gs
[
mi
,
mj
]
!=
1
:
Gs
[
mi
,
mj
]
=
1.5
plt
.
title
(
'
Cell migration & proliferation
'
+
str
(
iter
),
size
=
20
)
im2
=
plt
.
imshow
(
Gs
,
cmap
=
"
bone
"
,
norm
=
None
)
plt
.
show
()
name
=
'
Single_cell_SMAT_sample
'
+
str
(
iter
)
+
'
.png
'
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