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Dr. Hamed Khalili
covid_ai_project
Commits
a0727d71
Commit
a0727d71
authored
1 year ago
by
Dr. Hamed Khalili
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p_2/results/month_wise_rp.py
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p_2/results/month_wise_rp.py
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p_2/results/month_wise_rp.py
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View file @
a0727d71
import
matplotlib.pyplot
as
plt
import
numpy
as
np
#fig,axes=plt.subplots(figsize=(8,6))
from
xxx_list_r
import
xxx_list_r
xxx_list_r
=
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50.424528301886795
,
57.06603773584906
]],
[
'
Iceland
'
,
'
OutdoorOver50
'
,
[
56.33018867924528
,
43.971698113207545
]],
[
'
Iceland
'
,
'
IndoorOver500
'
,
[
49.9622641509434
,
55.443396226415096
]],
[
'
Iceland
'
,
'
TeleworkingPartial
'
,
[
50.5377358490566
,
53.820754716981135
]],
[
'
Iceland
'
,
'
MasksMandatoryClosedSpacesPartial
'
,
[
50.764150943396224
,
56.216981132075475
]],
[
'
Iceland
'
,
'
RegionalStayHomeOrderPartial
'
,
[
51.04716981132076
,
34.15094339622642
]],
[
'
Iceland
'
,
'
GymsSportsCentres
'
,
[
50.5188679245283
,
50.028301886792455
]],
[
'
Iceland
'
,
'
HotelsOtherAccommodationPartial
'
,
[
50.75471698113208
,
55.24528301886792
]],
[
'
Iceland
'
,
'
MasksMandatoryClosedSpaces
'
,
[
51.0
,
55.0
]],
[
'
Iceland
'
,
'
Teleworking
'
,
[
51.056603773584904
,
50.075471698113205
]],
[
'
Iceland
'
,
'
QuarantineForInternationalTravellers
'
,
[
51.594339622641506
,
51.075471698113205
]],
[
'
Iceland
'
,
'
ClosureOfPublicTransportPartial
'
,
[
51.27358490566038
,
53.113207547169814
]],
[
'
Iceland
'
,
'
Other
'
,
[
48.60377358490566
,
50.990566037735846
]],
[
'
Iceland
'
,
'
ClosHigh
'
,
[
50.632075471698116
,
54.924528301886795
]],
[
'
Iceland
'
,
'
RestaurantsCafes
'
,
[
50.70754716981132
,
59.009433962264154
]],
[
'
Iceland
'
,
'
StayHomeRiskG
'
,
[
50.75471698113208
,
48.943396226415096
]],
[
'
Iceland
'
,
'
ClosHighPartial
'
,
[
50.783018867924525
,
48.783018867924525
]],
[
'
Iceland
'
,
'
ClosDaycare
'
,
[
50.72641509433962
,
52.22641509433962
]],
[
'
Iceland
'
,
'
ClosSec
'
,
[
50.72641509433962
,
63.27358490566038
]],
[
'
Iceland
'
,
'
RestaurantsCafesPartial
'
,
[
51.443396226415096
,
51.0377358490566
]],
[
'
Iceland
'
,
'
QuarantineForInternationalTravellersPartial
'
,
[
50.632075471698116
,
50.094339622641506
]],
[
'
Iceland
'
,
'
vaccin_1
'
,
[
50.70754716981132
,
37.37735849056604
]],
[
'
Iceland
'
,
'
MassGatherAllPartial
'
,
[
45.84905660377358
,
57.990566037735846
]],
[
'
Iceland
'
,
'
EntertainmentVenuesPartial
'
,
[
49.58490566037736
,
50.028301886792455
]],
[
'
Iceland
'
,
'
MasksMandatoryAllSpaces
'
,
[
50.679245283018865
,
48.216981132075475
]],
[
'
Iceland
'
,
'
OutdoorOver1000
'
,
[
50.9811320754717
,
51.113207547169814
]],
[
'
Iceland
'
,
'
GymsSportsCentresPartial
'
,
[
51.839622641509436
,
51.886792452830186
]],
[
'
Iceland
'
,
'
MassGatherAll
'
,
[
49.735849056603776
,
52.33018867924528
]],
[
'
Iceland
'
,
'
NonEssentialShops
'
,
[
50.924528301886795
,
46.87735849056604
]],
[
'
Iceland
'
,
'
StayHomeOrderPartial
'
,
[
51.075471698113205
,
39.075471698113205
]],
[
'
Iceland
'
,
'
PrivateGatheringRestrictions
'
,
[
55.64150943396226
,
51.924528301886795
]],
[
'
Iceland
'
,
'
not_sequenced
'
,
[
50.68867924528302
,
40.35849056603774
]],
[
'
Iceland
'
,
'
vaccin_0
'
,
[
51.06603773584906
,
41.74528301886792
]],
[
'
Iceland
'
,
'
NonEssentialShopsPartial
'
,
[
55.575471698113205
,
56.0188679245283
]],
[
'
Iceland
'
,
'
ClosPrim
'
,
[
50.60377358490566
,
36.85849056603774
]],
[
'
Iceland
'
,
'
BA.2
'
,
[
51.64150943396226
,
37.9622641509434
]],
[
'
Iceland
'
,
'
B.1.617.2
'
,
[
50.783018867924525
,
52.66981132075472
]],
[
'
Iceland
'
,
'
B.1.1.7
'
,
[
50.72641509433962
,
21.89622641509434
]]]
xxx_list_r2
=
[
v
for
v
in
xxx_list_r
if
v
[
1
]
==
"
month
"
]
number_list
=
[
-
10000
,
0.07078470077050825
,
0.10284883424023675
,
0.12613493445551266
,
0.14318051668627516
,
0.15740371194397468
,
0.16971352498668726
,
0.18333935680799623
,
0.1957752967824007
,
0.20892779812846488
,
0.22271015503539546
,
0.23858550360480804
,
0.25455703856370604
,
0.2682926829268292
,
0.2828477804662684
,
0.29659941828563935
,
0.3132363588855599
,
0.33003778131820666
,
0.3452064681517075
,
0.3610676144836586
,
0.3780624407641041
,
0.39345108408249596
,
0.410090274584236
,
0.43126379084967315
,
0.4527388403186768
,
0.4755480607082632
,
0.49823083711866484
,
0.5204186109413703
,
0.5423853480222012
,
0.5617613296789038
,
0.5846339878614369
,
0.6071107982063504
,
0.6302529575075375
,
0.6538302278191421
,
0.679022941728829
,
0.7039159584917519
,
0.730399523486679
,
0.7551560284756752
,
0.784494778205232
,
0.8084026783121917
,
0.8402615957211237
,
0.8656916063459528
,
0.9004697811539516
,
0.9310668419455961
,
0.9619059038293404
,
0.9969144392609844
,
1.029258861468043
,
1.0628957851818992
,
1.0974735515669372
,
1.1369879303494452
,
1.17595818815331
,
1.2146039315235297
,
1.2608636882494544
,
1.3043638781513074
,
1.3533496195211399
,
1.3943999864839458
,
1.4426934482768425
,
1.4969371122483697
,
1.5507950100219168
,
1.6050199717309004
,
1.658389122052565
,
1.7297883588063954
,
1.7868031358376524
,
1.8543115124869702
,
1.9184095280348135
,
1.9955887917033457
,
2.0688116073802267
,
2.148175110126286
,
2.2211320376678025
,
2.2988142189666076
,
2.3889327749754123
,
2.483492606743207
,
2.5740448793942337
,
2.681332687283711
,
2.8024552855145686
,
2.918066252203766
,
3.05852449806563
,
3.174743601624033
,
3.301176689793639
,
3.4392818760197845
,
3.5953694512380117
,
3.7547708371886355
,
3.9122423522502223
,
4.087992107782384
,
4.298950800468855
,
4.525230055135722
,
4.7660051692973004
,
5.013727796318774
,
5.300916491817043
,
5.605861912902701
,
5.939672055428745
,
6.327203822046167
,
6.767006596746101
,
7.374206115365088
,
8.11111111111111
,
9.052509407903903
,
10.126343331436674
,
11.875720302501431
,
14.941424148606822
,
28.497057563761512
,
10000
]
percent_list
=
[
i
for
i
in
range
(
100
)]
def
translate_percentile_to_rp
(
x
):
return
(
number_list
[
x
+
1
]
+
number_list
[
x
])
/
2
fig
,
axs
=
plt
.
subplots
(
10
,
3
,
figsize
=
(
18
,
15
))
axs
=
axs
.
ravel
()
for
i
in
range
(
0
,
30
):
YX
=
zip
(
xxx_list_r2
[
i
][
2
][
0
],
xxx_list_r2
[
i
][
2
][
1
])
YX
=
sorted
(
list
(
YX
))
#.sort()
data
=
YX
x_val
=
[
x
[
0
]
for
x
in
data
]
y_val
=
[
translate_percentile_to_rp
(
int
(
round
(
x
[
1
])))
for
x
in
data
]
x
=
np
.
arange
(
4
,
9
,
0.001
)
#y=np.arange(4, 9, 0.001)
#ax[i].fill_between(x, 4, 9,color='green', alpha=0.5, transform=ax.get_xaxis_transform())
minor_ticks
=
np
.
arange
(
0
,
12
,
1
)
axs
[
i
].
set_xticks
(
minor_ticks
)
axs
[
i
].
plot
(
x_val
,
y_val
)
axs
[
i
].
plot
(
x_val
,
y_val
,
'
or
'
)
#axs[i].plot(x,y)
#axs[i*3].hist(responses_minus[i][1],bins=b,edgecolor = 'white', range=[-1, 2], label=str(responses_minus[i][0]))
#axs[i].legend(loc='best')
axs
[
i
].
set_ylabel
(
'
rp
'
)
axs
[
i
].
set_title
(
xxx_list_r2
[
i
][
0
],
fontsize
=
10
)
#axs[i].fill_betweenx(y_val, x, y_val, color='red', alpha=.5)
import
matplotlib.transforms
as
mtransforms
trans
=
mtransforms
.
blended_transform_factory
(
axs
[
i
].
transData
,
axs
[
i
].
transAxes
)
axs
[
i
].
fill_between
(
x
,
0
,
1
,
where
=
x
<
9
,
facecolor
=
'
red
'
,
alpha
=
0.5
,
transform
=
trans
)
m1
=
translate_percentile_to_rp
(
int
(
round
(
min
(
xxx_list_r2
[
i
][
2
][
1
]))))
m2
=
translate_percentile_to_rp
(
int
(
round
(
max
(
xxx_list_r2
[
i
][
2
][
1
]))))
axs
[
i
].
set_ylim
([
m1
-
.
1
,
m2
+
.
1
])
#ymin, ymax = axs[i].ylim()
#axs[i].fill_between(y_val, 4, 9)
from
matplotlib.ticker
import
(
AutoMinorLocator
,
MultipleLocator
)
axs
[
i
].
xaxis
.
set_minor_locator
(
AutoMinorLocator
(
1
))
#axs[i].yaxis.set_minor_locator(AutoMinorLocator(1))
axs
[
i
].
grid
(
which
=
'
minor
'
,
color
=
'
#CCCCCC
'
,
linestyle
=
'
--
'
)
axs
[
i
].
grid
(
which
=
'
major
'
,
color
=
'
#CCCCCC
'
,
linestyle
=
'
--
'
)
#axs.fill_between(x, 4, 9, where=( y > 4 and y<9),color='green', alpha=0.5, transform=ax.get_xaxis_transform())
#color='green', alpha=0.5, transform=ax.get_xaxis_transform())
#plt.show()
plt
.
savefig
(
'
month.png
'
)
\ No newline at end of file
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