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In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day1-2/20190731_033840 Current vs Vgs_5sStep.txt

@@ -0,0 +1,23 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0	72,16	78,74	6,53	77,15	85,34	71,90	68,68	69,99
+0,019047619047619	71,00	77,41	6,27	75,90	83,79	70,54	67,37	68,87
+0,0380952380952381	70,01	76,25	6,07	74,84	82,47	69,39	66,27	67,97
+0,0571428571428571	68,64	74,67	5,84	73,37	80,71	67,88	64,83	66,69
+0,0761904761904762	67,34	73,18	5,61	71,99	79,02	66,45	63,49	65,52
+0,0952380952380952	65,54	71,14	5,35	70,07	76,81	64,56	61,70	63,90
+0,114285714285714	64,01	69,38	5,15	68,45	74,88	62,89	60,14	62,53
+0,133333333333333	61,96	67,07	4,84	66,26	72,37	60,72	58,11	60,66
+0,152380952380952	59,96	64,82	4,61	64,14	69,97	58,68	56,19	58,90
+0,171428571428571	57,52	62,10	4,34	61,51	66,99	56,12	53,77	56,62
+0,19047619047619	55,20	59,50	4,08	59,04	64,18	53,71	51,50	54,53
+0,20952380952381	52,42	56,43	3,80	56,09	60,85	50,87	48,80	51,95
+0,228571428571429	49,65	53,32	3,51	53,13	57,48	47,96	46,06	49,33
+0,247619047619048	46,48	49,74	3,20	49,73	53,62	44,63	42,88	46,24
+0,266666666666667	43,44	46,29	2,88	46,44	49,89	41,47	39,82	43,28
+0,285714285714286	39,97	42,38	2,58	42,67	45,70	37,95	36,32	39,83
+0,304761904761905	36,57	38,51	2,27	38,91	41,50	34,49	32,84	36,39
+0,323809523809524	32,87	34,46	1,99	34,87	37,08	30,84	29,15	32,64
+0,342857142857143	29,46	30,76	1,75	31,16	32,98	27,42	25,80	29,05
+0,361904761904762	26,21	27,33	1,52	27,64	29,11	24,12	22,75	25,55
+0,380952380952381	23,40	24,47	1,37	24,62	25,85	21,32	20,34	22,55
+0,4	21,22	22,34	1,29	22,37	23,30	19,09	18,68	20,19

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day1-2/20190731_035018 Current vs Vgs_20sStep.txt

@@ -0,0 +1,23 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0	71,62	78,15	6,58	76,79	85,51	71,76	68,89	69,93
+0,019047619047619	70,69	77,04	6,32	75,75	84,11	70,52	67,60	68,87
+0,0380952380952381	69,78	75,93	6,12	74,81	82,85	69,39	66,50	68,00
+0,0571428571428571	68,43	74,37	5,88	73,40	81,12	67,88	65,06	66,77
+0,0761904761904762	67,13	72,86	5,69	72,01	79,48	66,52	63,74	65,62
+0,0952380952380952	65,32	70,83	5,40	70,10	77,28	64,67	61,99	64,04
+0,114285714285714	63,73	69,03	5,14	68,43	75,35	63,01	60,44	62,66
+0,133333333333333	61,62	66,65	4,85	66,20	72,81	60,82	58,39	60,78
+0,152380952380952	59,60	64,40	4,65	64,06	70,39	58,78	56,49	59,04
+0,171428571428571	57,06	61,59	4,37	61,39	67,39	56,20	54,07	56,75
+0,19047619047619	54,62	58,88	4,06	58,82	64,50	53,71	51,75	54,59
+0,20952380952381	51,76	55,73	3,79	55,78	61,14	50,82	49,02	51,98
+0,228571428571429	48,82	52,50	3,47	52,67	57,63	47,90	46,24	49,30
+0,247619047619048	45,43	48,77	3,17	49,08	53,58	44,50	43,00	46,11
+0,266666666666667	42,13	45,10	2,86	45,58	49,64	41,18	39,81	42,98
+0,285714285714286	38,41	40,96	2,57	41,58	45,19	37,45	36,16	39,36
+0,304761904761905	34,71	36,84	2,28	37,57	40,77	33,81	32,50	35,69
+0,323809523809524	30,75	32,52	1,98	33,30	36,06	29,92	28,65	31,70
+0,342857142857143	31,87	33,64	3,54	34,49	37,33	31,25	30,10	33,10
+0,361904761904762	23,43	24,70	1,50	25,54	27,32	22,54	21,79	24,08
+0,380952380952381	20,78	21,98	1,38	22,54	23,96	19,81	19,43	21,10
+0,4	19,02	20,18	1,31	20,41	21,47	17,85	17,94	18,92

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day1-2/20190731_115540 Current vs Vgs_5sStep-afterRec2.txt

@@ -0,0 +1,19 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0	58,04	63,17	4,49	61,92	68,89	57,21	55,46	57,87
+0,0264705882352941	56,06	60,85	4,20	59,78	66,20	54,96	53,29	55,94
+0,0529411764705882	54,01	58,47	3,98	57,61	63,59	52,78	51,23	54,07
+0,0794117647058824	51,45	55,57	3,67	54,91	60,46	50,09	48,71	51,69
+0,105882352941176	48,74	52,53	3,39	52,05	57,13	47,32	46,10	49,21
+0,132352941176471	45,71	49,11	3,11	48,86	53,44	44,25	43,19	46,36
+0,158823529411765	42,43	45,43	2,83	45,40	49,52	40,95	40,07	43,25
+0,185294117647059	39,08	41,71	2,58	41,87	45,54	37,67	36,87	40,09
+0,211764705882353	35,35	37,53	2,29	37,88	41,05	34,04	33,26	36,43
+0,238235294117647	31,63	33,47	2,05	33,95	36,62	30,56	29,76	32,81
+0,264705882352941	27,71	29,33	1,79	29,84	32,05	26,93	26,11	28,92
+0,291176470588235	24,28	25,76	1,60	26,22	28,03	23,66	22,96	25,41
+0,317647058823529	21,33	22,68	1,45	23,03	24,52	20,68	20,29	22,14
+0,344117647058824	19,39	20,64	1,38	20,82	21,97	18,51	18,57	19,77
+0,370588235294118	18,58	19,66	1,39	19,66	20,41	17,36	17,90	18,41
+0,397058823529412	18,94	19,79	1,47	19,61	19,96	17,36	18,34	18,20
+0,423529411764706	20,18	20,81	1,60	20,43	20,39	18,28	19,61	18,91
+0,45	21,66	22,28	3,08	21,88	21,60	19,91	21,50	20,35

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day1-2/20190801_031608 Current vs Vgs5s-afterRec6-highRange.txt

@@ -0,0 +1,19 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0	55,64	60,65	4,20	59,73	63,98	55,12	53,07	55,04
+0,0264705882352941	53,73	58,44	3,93	57,60	61,18	52,86	50,87	53,14
+0,0529411764705882	51,48	55,92	3,67	55,23	58,34	50,46	48,59	51,09
+0,0794117647058824	48,70	52,83	3,41	52,29	54,99	47,64	45,95	48,60
+0,105882352941176	45,82	49,61	3,12	49,19	51,49	44,66	43,14	45,96
+0,132352941176471	42,57	45,97	2,84	45,70	47,69	41,41	40,06	42,99
+0,158823529411765	39,12	42,12	2,57	41,98	43,69	37,97	36,73	39,75
+0,185294117647059	35,58	38,18	2,34	38,14	39,62	34,53	33,32	36,41
+0,211764705882353	31,76	33,96	2,04	33,97	35,29	30,88	29,66	32,73
+0,238235294117647	28,08	30,02	1,83	30,00	31,24	27,40	26,22	29,13
+0,264705882352941	24,60	26,31	1,63	26,27	27,42	24,04	23,02	25,54
+0,291176470588235	21,86	23,42	1,49	23,35	24,39	21,27	20,56	22,52
+0,317647058823529	19,92	21,31	1,42	21,28	22,12	19,10	18,88	20,13
+0,344117647058824	19,09	20,27	1,48	20,29	20,86	17,98	18,35	18,80
+0,370588235294118	19,26	20,16	1,54	20,18	20,43	17,87	18,76	18,45
+0,397058823529412	20,36	20,99	1,67	20,92	20,90	18,73	20,03	19,02
+0,423529411764706	22,12	22,57	1,84	22,29	22,16	20,27	21,87	20,33
+0,45	24,33	24,74	2,03	24,17	24,04	22,33	24,14	22,14

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day12/20190811_062354 Current vs Vgs-PreRec1.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,2	60,18	67,78	6,16	65,54	74,29	65,52	61,31	64,81
+-0,16	59,73	66,66	5,99	64,59	73,25	64,74	60,49	64,14
+-0,12	58,10	64,43	5,71	62,58	71,10	62,96	58,79	62,61
+-0,08	55,69	61,22	5,36	59,68	67,97	60,34	56,33	60,30
+-0,04	52,45	57,11	4,97	55,94	64,02	56,95	53,16	57,32
+0	48,41	52,01	4,47	51,28	59,06	52,68	49,16	53,46
+0,04	43,41	45,87	3,92	45,71	53,11	47,44	44,33	48,70
+0,08	37,68	39,08	3,37	39,38	46,35	41,44	38,82	43,08
+0,12	31,50	32,58	2,77	32,82	39,13	35,12	32,88	36,87
+0,16	25,30	26,96	2,22	26,52	31,83	28,79	26,82	30,27
+0,2	20,36	22,93	1,84	22,02	25,80	23,14	21,68	24,33
+0,24	18,21	21,05	1,63	19,86	22,10	18,93	18,33	19,90
+0,28	19,69	21,62	1,63	19,98	21,06	17,31	17,73	18,07
+0,32	23,44	24,22	1,76	22,01	22,70	18,29	19,52	18,70
+0,36	28,12	28,39	2,02	25,51	26,77	21,15	22,90	21,17

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day12/20190811_090313 Current vs Vgs-PostRec1.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,2	54,84	66,41	5,95	61,66	72,47	64,46	60,17	63,99
+-0,16	54,09	65,02	5,76	60,46	71,12	63,51	59,12	63,15
+-0,12	52,70	63,07	5,51	58,76	69,22	61,93	57,60	61,80
+-0,08	50,30	59,94	5,17	55,98	66,15	59,38	55,18	59,54
+-0,04	46,78	55,29	4,70	51,85	61,61	55,56	51,58	56,17
+0	42,74	50,13	4,24	47,31	56,58	51,22	47,57	52,26
+0,04	38,09	44,05	3,71	42,05	50,60	45,99	42,77	47,46
+0,08	32,97	37,43	3,14	36,23	43,78	40,02	37,32	41,79
+0,12	27,65	31,38	2,63	30,31	36,69	33,93	31,60	35,66
+0,16	22,24	26,07	2,12	24,58	29,46	27,67	25,71	29,04
+0,2	18,26	22,49	1,79	20,70	23,94	22,22	20,89	23,25
+0,24	17,26	21,19	1,66	19,15	21,24	18,36	18,08	19,28
+0,28	19,75	22,30	1,72	19,83	21,61	17,35	18,19	18,11
+0,32	24,08	25,41	1,89	22,33	24,69	18,93	20,54	19,43
+0,36	28,87	29,86	2,19	26,06	29,54	22,19	24,23	22,40

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day12/20190811_105206 Current vs Vgs-PostAnesthesia.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,2	53,15	64,08	5,97	57,47	74,46	59,02	60,29	61,51
+-0,16	52,80	63,03	5,78	56,60	73,25	58,26	59,41	60,82
+-0,12	51,35	60,91	5,51	54,77	71,13	56,71	57,78	59,34
+-0,08	49,00	57,79	5,21	52,04	67,92	54,26	55,28	57,01
+-0,04	45,94	53,77	4,77	48,53	63,84	51,06	52,08	53,98
+0	42,03	48,73	4,31	44,11	58,66	46,98	47,97	50,04
+0,04	37,40	42,79	3,77	39,02	52,49	42,06	43,04	45,27
+0,08	32,50	36,64	3,19	33,73	45,77	36,86	37,67	40,07
+0,12	27,49	30,83	2,67	28,39	38,53	31,59	31,90	34,47
+0,16	22,43	25,83	2,16	23,29	31,25	26,43	26,12	28,60
+0,2	18,45	22,35	1,81	19,74	25,37	21,82	21,32	23,33
+0,24	16,92	20,84	1,65	18,16	21,74	18,10	18,22	19,33
+0,28	18,79	21,49	1,69	18,55	20,80	16,48	17,83	17,79
+0,32	22,64	24,03	1,86	20,52	23,00	17,24	19,76	18,61
+0,36	27,20	28,11	2,15	23,76	27,70	19,81	23,22	21,19

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day2/20190802_100447 Current vs Vgs-24h2.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0,1	47,26	51,37	3,69	50,77	53,70	46,44	45,16	47,87
+0,117857142857143	44,71	48,50	3,41	48,06	50,54	43,79	42,61	45,51
+0,135714285714286	41,39	44,79	3,09	44,43	46,57	40,46	39,36	42,42
+0,153571428571429	38,04	41,05	2,80	40,75	42,68	37,14	36,11	39,31
+0,171428571428571	34,33	36,98	2,52	36,69	38,43	33,58	32,52	35,79
+0,189285714285714	30,83	33,11	2,30	32,98	34,60	30,18	29,14	32,42
+0,207142857142857	27,02	29,04	2,03	28,90	30,37	26,61	25,57	28,65
+0,225	23,70	25,48	1,85	25,43	26,71	23,32	22,47	25,13
+0,242857142857143	20,79	22,36	1,69	22,44	23,40	20,35	19,85	21,83
+0,260714285714286	19,16	20,51	1,66	20,72	21,40	18,47	18,44	19,58
+0,278571428571429	18,64	19,71	1,70	19,95	20,39	17,64	18,11	18,33
+0,296428571428571	19,29	20,03	1,79	20,09	20,41	17,92	18,84	18,13
+0,314285714285714	20,95	21,38	1,92	21,12	21,46	19,22	20,46	18,93
+0,332142857142857	23,36	23,59	2,09	22,89	23,49	21,28	22,73	20,55
+0,35	26,05	26,29	2,28	25,11	26,01	23,83	25,34	22,72

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day2/20190802_115002 Current vs Vgs-24h2-PostRec7.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0,1	55,00	59,78	4,51	55,38	61,55	55,43	52,43	54,76
+0,118571428571429	52,73	57,21	4,22	52,98	58,66	53,06	50,18	52,74
+0,137142857142857	49,80	53,99	3,92	49,96	55,15	50,09	47,38	50,12
+0,155714285714286	46,76	50,65	3,58	46,87	51,56	47,01	44,48	47,40
+0,174285714285714	43,30	46,84	3,23	43,40	47,54	43,52	41,22	44,27
+0,192857142857143	39,93	43,10	2,96	39,99	43,65	40,16	37,99	41,20
+0,211428571428571	36,17	38,92	2,64	36,23	39,30	36,37	34,32	37,62
+0,23	32,41	34,75	2,34	32,46	35,01	32,64	30,64	33,99
+0,248571428571429	28,56	30,56	2,07	28,60	30,69	28,84	26,91	30,15
+0,267142857142857	25,08	26,81	1,84	25,24	26,85	25,26	23,57	26,50
+0,285714285714286	21,99	23,51	1,65	22,44	23,56	21,92	20,66	23,04
+0,304285714285714	19,97	21,31	1,55	20,76	21,43	19,42	18,83	20,45
+0,322857142857143	19,00	20,12	1,53	19,99	20,39	17,92	18,13	18,82
+0,341428571428571	19,37	20,21	1,60	20,25	20,58	17,76	18,73	18,43
+0,36	20,71	21,29	1,72	21,22	21,70	18,66	20,22	18,99

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day26/20190825_080628 Current vs Vgs.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,2	43,89	46,81	5,64	46,25	63,62	53,11	54,78	53,42
+-0,16	41,81	44,17	5,29	43,99	60,53	50,92	52,45	51,37
+-0,12	38,36	40,04	4,80	40,18	55,70	47,39	48,65	47,92
+-0,08	34,02	34,94	4,20	35,25	49,41	42,71	43,63	43,43
+-0,04	28,94	29,52	3,56	29,67	41,74	37,02	37,48	37,97
+0	23,31	24,72	2,89	23,89	33,37	30,94	30,77	31,91
+0,04	17,99	21,23	2,34	19,11	25,38	24,63	23,95	25,33
+0,08	15,69	20,16	1,98	17,46	20,97	18,34	18,57	19,39
+0,12	18,78	23,66	2,00	19,29	21,93	15,95	17,95	17,46
+0,16	24,50	29,85	2,30	23,36	27,54	19,30	21,84	19,93
+0,2	29,76	35,69	2,75	28,47	34,83	24,72	27,52	24,72
+0,24	34,33	40,93	3,26	33,70	42,30	30,47	33,69	30,47
+0,28	38,11	45,29	3,85	38,35	48,64	35,58	39,21	35,71
+0,32	40,83	48,42	4,13	41,83	53,45	39,32	43,44	39,77
+0,36	43,21	51,26	4,48	45,05	57,82	42,71	47,36	43,49

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day26/20190825_102924 Current vs Vgs.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,2	45,32	47,45	5,78	46,21	64,39	53,37	55,19	53,41
+-0,16	42,79	43,95	5,29	43,22	60,59	50,60	52,24	50,75
+-0,12	39,36	39,33	4,74	38,84	55,17	46,60	47,92	46,81
+-0,08	35,27	33,77	4,06	33,40	48,22	41,40	42,33	41,75
+-0,04	30,74	28,26	3,36	27,52	40,15	35,45	35,83	35,94
+0	25,48	23,56	2,70	21,63	31,36	29,10	28,73	29,46
+0,04	19,86	20,40	2,21	17,68	23,73	22,56	21,92	22,69
+0,08	16,56	20,70	2,01	17,76	20,77	17,00	17,74	17,90
+0,12	18,13	25,65	2,15	21,11	23,03	16,52	18,71	17,85
+0,16	22,67	32,08	2,51	26,01	29,34	21,02	23,40	21,58
+0,2	27,54	37,70	3,02	31,19	36,73	26,70	29,17	26,85
+0,24	31,80	42,34	3,51	35,94	43,53	32,10	34,82	32,28
+0,28	35,31	46,20	3,99	40,12	49,39	36,76	39,87	37,18
+0,32	38,22	49,41	4,41	43,71	54,36	40,75	44,27	41,39
+0,36	40,67	52,15	4,79	46,73	58,57	44,09	48,08	45,00

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day26/20190826_121747 Current vs Vgs.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,2	42,58	38,97	5,92	46,70	57,79	50,24	55,04	55,71
+-0,16	39,75	35,83	5,45	43,36	53,76	47,17	51,69	52,65
+-0,12	36,22	32,04	4,87	38,89	48,49	43,05	47,17	48,43
+-0,08	32,36	28,12	4,19	33,68	42,21	38,13	41,70	43,34
+-0,04	28,18	24,27	3,52	27,91	35,07	32,59	35,37	37,45
+0	23,62	21,04	2,86	22,08	27,53	26,95	28,59	30,91
+0,04	18,80	18,60	2,32	17,83	20,96	21,28	22,04	24,00
+0,08	15,56	18,46	2,02	17,39	18,38	16,21	17,58	18,55
+0,12	16,91	22,63	2,08	20,22	21,46	15,67	18,12	17,65
+0,16	20,95	27,86	2,38	24,25	27,70	19,39	22,16	20,46
+0,2	25,60	32,93	2,88	29,09	34,62	24,59	27,73	25,30
+0,24	29,67	37,17	3,38	33,73	40,83	29,57	33,33	30,63
+0,28	33,10	40,77	3,78	37,96	46,18	34,01	38,48	35,72
+0,32	35,97	43,81	4,30	41,77	50,82	37,84	43,09	40,28
+0,36	38,53	46,54	4,63	45,08	54,87	41,21	47,19	44,33

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day4/20190803_010556 Current vs Vgs-PostRec10.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0,1	58,36	62,84	4,71	58,30	65,11	57,73	53,70	57,38
+0,118571428571429	56,59	60,82	4,51	56,39	62,92	55,94	51,99	55,88
+0,137142857142857	54,27	58,27	4,23	53,95	60,18	53,62	49,83	53,87
+0,155714285714286	52,10	55,88	4,03	51,66	57,55	51,42	47,79	51,97
+0,174285714285714	49,50	53,04	3,79	48,95	54,52	48,84	45,41	49,69
+0,192857142857143	46,77	50,06	3,49	46,18	51,37	46,13	42,92	47,27
+0,211428571428571	44,06	47,06	3,25	43,41	48,18	43,42	40,43	44,83
+0,23	41,01	43,70	2,97	40,33	44,65	40,40	37,63	42,04
+0,248571428571429	37,95	40,31	2,72	37,25	41,10	37,39	34,78	39,17
+0,267142857142857	34,61	36,64	2,44	33,92	37,33	34,23	31,75	36,02
+0,285714285714286	31,29	33,03	2,17	30,64	33,61	31,10	28,72	32,81
+0,304285714285714	28,03	29,54	1,97	27,50	29,97	28,02	25,78	29,54
+0,322857142857143	24,87	26,21	1,74	24,65	26,57	24,97	22,99	26,31
+0,341428571428571	22,23	23,45	1,61	22,48	23,79	22,18	20,65	23,37
+0,36	20,16	21,27	1,53	20,91	21,67	19,80	18,89	20,84

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day4/20190803_031630 Current vs Vgs-PostRec12.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0,1	56,09	60,00	4,59	55,90	62,26	55,59	51,70	55,37
+0,118571428571429	53,11	56,71	4,31	52,74	58,65	52,61	48,91	52,82
+0,137142857142857	49,78	53,07	3,96	49,31	54,77	49,32	45,88	49,90
+0,155714285714286	46,50	49,50	3,67	45,93	50,96	46,09	42,90	47,02
+0,174285714285714	42,48	45,09	3,29	41,86	46,28	42,07	39,19	43,33
+0,192857142857143	38,39	40,60	2,93	37,71	41,55	38,06	35,41	39,55
+0,211428571428571	33,81	35,62	2,54	33,10	36,35	33,67	31,19	35,20
+0,23	29,29	30,80	2,19	28,68	31,25	29,38	27,05	30,76
+0,248571428571429	24,91	26,24	1,86	24,64	26,46	25,12	23,10	26,24
+0,267142857142857	21,56	22,79	1,67	21,90	22,97	21,55	20,13	22,49
+0,285714285714286	19,48	20,64	1,59	20,41	20,85	18,83	18,35	19,69
+0,304285714285714	19,19	20,21	1,64	20,24	20,49	17,71	18,33	18,52
+0,322857142857143	20,31	21,15	1,75	21,04	21,44	18,03	19,61	18,70
+0,341428571428571	22,78	23,60	1,96	22,99	23,79	19,76	22,09	20,23
+0,36	25,88	26,83	2,22	25,63	26,96	22,31	25,15	22,57

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day4/20190803_094434 Current vs Vgs-PreRec10.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+0,1	46,22	49,56	3,51	45,93	50,92	46,58	42,87	47,01
+0,118571428571429	42,76	45,74	3,22	42,40	46,87	43,10	39,67	43,87
+0,137142857142857	38,96	41,53	2,90	38,56	42,48	39,28	36,14	40,33
+0,155714285714286	35,12	37,27	2,59	34,69	38,06	35,46	32,55	36,68
+0,174285714285714	30,81	32,53	2,24	30,38	33,15	31,19	28,54	32,44
+0,192857142857143	26,98	28,40	1,98	26,68	28,82	27,35	25,02	28,53
+0,211428571428571	23,40	24,61	1,76	23,43	24,91	23,62	21,75	24,69
+0,23	20,73	21,85	1,65	21,29	22,10	20,53	19,35	21,50
+0,248571428571429	19,24	20,27	1,59	20,19	20,57	18,41	18,13	19,29
+0,267142857142857	19,24	20,11	1,68	20,20	20,48	17,71	18,37	18,48
+0,285714285714286	20,36	21,11	1,79	21,01	21,46	18,16	19,65	18,72
+0,304285714285714	22,58	23,32	1,97	22,75	23,59	19,78	21,89	20,08
+0,322857142857143	25,33	26,23	2,19	25,05	26,39	22,07	24,65	22,09
+0,341428571428571	28,68	29,82	2,43	28,07	29,97	25,07	27,92	24,82
+0,36	32,01	33,49	2,70	31,25	33,73	28,22	31,14	27,71

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day6/20190805_113528 Current vs Vgs-PreRec1.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,2	74,91	80,00	7,52	76,58	80,21	74,88	70,20	71,50
+-0,16	73,47	77,84	7,12	74,75	83,54	73,21	68,47	70,18
+-0,12	71,30	74,99	6,71	72,33	81,43	70,93	66,30	68,35
+-0,08	68,58	71,58	6,29	69,38	78,00	68,14	63,70	66,10
+-0,04	65,45	67,71	5,84	65,97	74,09	64,96	60,74	63,48
+0	61,58	63,04	5,34	61,81	69,34	61,08	57,13	60,23
+0,04	56,89	57,47	4,77	56,80	63,70	56,42	52,81	56,22
+0,08	51,23	50,87	4,17	50,81	57,00	50,85	47,63	51,33
+0,12	44,50	43,36	3,52	43,85	49,19	44,21	41,54	45,36
+0,16	36,80	35,63	2,85	36,02	40,37	36,67	34,49	38,27
+0,2	28,80	28,48	2,21	28,01	31,11	28,94	26,99	30,39
+0,24	21,89	23,12	1,75	22,04	23,27	21,80	20,50	22,90
+0,28	19,04	21,23	1,60	20,16	20,10	17,80	17,88	18,62
+0,32	20,83	23,31	1,81	21,80	22,05	18,41	20,02	18,91
+0,36	25,78	28,83	2,27	26,19	27,39	22,38	25,01	22,56

In-vivo/Calibration and longitudinal assessment/IV-charact/IV-Day6/20190806_011608 Current vs Vgs-PostRec1.txt

@@ -0,0 +1,16 @@
+Vgs [V]	Result A5 [µA]	Result A7 [µA]	Result A29 [µA]	Result A31 [µA]	Result B5 [µA]	Result B7 [µA]	Result B29 [µA]	Result B31 [µA]
+-0,195	75,57	80,49	7,59	77,10	80,62	75,44	70,37	71,96
+-0,155357142857143	73,90	78,16	7,19	75,14	83,93	73,63	68,60	70,54
+-0,115714285714286	71,74	75,35	6,77	72,72	81,89	71,36	66,48	68,75
+-0,0760714285714286	69,13	72,05	6,33	69,85	78,54	68,69	63,96	66,56
+-0,0364285714285714	66,07	68,27	5,86	66,53	74,75	65,60	61,07	64,02
+0,00321428571428567	62,31	63,71	5,37	62,43	70,09	61,83	57,53	60,85
+0,0428571428571428	58,02	58,51	4,80	57,79	64,86	57,53	53,52	57,20
+0,0825	52,62	52,16	4,19	52,01	58,39	52,19	48,53	52,51
+0,122142857142857	46,34	44,99	3,55	45,41	51,01	45,98	42,81	46,96
+0,161785714285714	39,01	37,40	2,89	37,92	42,50	38,74	36,11	40,22
+0,201428571428571	31,07	30,21	2,29	29,99	33,42	31,14	28,82	32,62
+0,241071428571429	23,54	24,37	1,79	23,32	25,04	23,74	21,97	24,83
+0,280714285714286	19,30	21,45	1,61	20,34	20,49	18,50	18,12	19,33
+0,320357142857143	19,96	22,38	1,77	20,98	21,08	17,72	19,09	18,29
+0,36	24,42	27,27	2,17	24,80	25,72	20,90	23,59	21,26

In-vivo/Calibration and longitudinal assessment/LongitudinalAssessment.py

@@ -0,0 +1,389 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Sun Apr 28 15:50:58 2019
+
+@author: aemdlabs
+"""
+import deepdish as dd
+import matplotlib.pyplot as plt
+from glob import glob
+import os
+import numpy as np
+import matplotlib.colors as colors
+import matplotlib as mpl
+import csv
+from matplotlib.colors import LinearSegmentedColormap
+
+
+MCSMapI={'SE1':'Ch03',
+         'SE2':'Ch05',
+         'SE3':'Ch01',
+         'SE4':'Ch02',
+         'SE5':'Ch22',
+         'SE6':'Ch06',
+         'SE7':'Ch16',
+         'SE8':'Ch37',
+         'SE9':'Ch20',
+         'SE10':'Ch10',
+         'SE11':'Ch24',
+         'SE12':'Ch08',
+         'SE13':'Ch14',
+         'SE14':'Ch04',
+         'SE15':'Ch18',
+         'SE16':'Ch33',
+         'SE17':'Ch34',
+         'SE18':'Ch60',
+         'SE19':'Ch38',
+         'SE20':'Ch64',
+         'SE21':'Ch40',
+         'SE22':'Ch56',
+         'SE23':'Ch42',
+         'SE24':'Ch70',
+         'SE25':'Ch66',
+         'SE26':'Ch65',
+         'SE27':'Ch68',
+         'SE28':'Ch67',
+         'SE29':'Ch55',
+         'SE30':'Ch62',
+         'SE31':'Ch58',
+         'SE32':'Ch69',
+         'ME1':'Ch57',
+         'ME2':'Ch61',
+         'ME3':'Ch53',
+         'ME4':'Ch63',
+         'ME5':'Ch52',
+         'ME6':'Ch41',
+         'ME7':'Ch49',
+         'ME8':'Ch51',
+         'ME9':'Ch46',
+         'ME10':'Ch45',
+         'ME11':'Ch44',
+         'ME12':'Ch39',
+         'ME13':'Ch54',
+         'ME14':'Ch43',
+         'ME15':'Ch50',
+         'ME16':'Ch47',
+         'ME17':'Ch32',
+         'ME18':'Ch27',
+         'ME19':'Ch30',
+         'ME20':'Ch29',
+         'ME21':'Ch28',
+         'ME22':'Ch25',
+         'ME23':'Ch26',
+         'ME24':'Ch07',
+         'ME25':'Ch21',
+         'ME26':'Ch11',
+         'ME27':'Ch17',
+         'ME28':'Ch15',
+         'ME29':'Ch13',
+         'ME30':'Ch31',
+         'ME31':'Ch19',
+         'ME32':'Ch09'}
+
+                          #Col, Row  
+MCSMapFacingDown={'Ch58':(0,1),
+                  'Ch57':(0,2),
+                  'Ch56':(0,3),
+                  'Ch55':(0,4),
+                  'Ch54':(0,5),
+                  'Ch53':(0,6),
+                  'Ch52':(0,7),
+                  'Ch51':(0,8),
+                  'Ch50':(0,9),
+                  'Ch49':(0,10),
+                  'Ch60':(1,0),
+                  'Ch61':(1,1),
+                  'Ch62':(1,2),
+                  'Ch63':(1,3),
+                  'Ch64':(1,4),
+                  'Ch65':(1,5),
+                  'Ch43':(1,6),
+                  'Ch44':(1,7),
+                  'Ch45':(1,8),
+                  'Ch46':(1,9),
+                  'Ch47':(1,10),
+                  'Ch70':(2,0),
+                  'Ch69':(2,1),
+                  'Ch68':(2,2),
+                  'Ch67':(2,3),
+                  'Ch66':(2,4),
+                  'Ch42':(2,5),
+                  'Ch41':(2,6),
+                  'Ch40':(2,7),
+                  'Ch39':(2,8),
+                  'Ch38':(2,9),
+                  'Ch37':(2,10),
+                  'Ch01':(3,0),
+                  'Ch02':(3,1),
+                  'Ch03':(3,2),
+                  'Ch04':(3,3),
+                  'Ch05':(3,4),
+                  'Ch06':(3,5),
+                  'Ch30':(3,6),
+                  'Ch31':(3,7),
+                  'Ch32':(3,8),
+                  'Ch33':(3,9),
+                  'Ch34':(3,10),
+                  'Ch11':(4,0),
+                  'Ch10':(4,1),
+                  'Ch09':(4,2),
+                  'Ch08':(4,3),
+                  'Ch07':(4,4),
+                  'Ch29':(4,5),
+                  'Ch28':(4,6),
+                  'Ch27':(4,7),
+                  'Ch26':(4,8),
+                  'Ch25':(4,9),
+                  'Ch24':(4,10),
+                  'Ch12':None,
+                  'Ch59':None,
+                  'Ch13':(5,1),
+                  'Ch14':(5,2),
+                  'Ch15':(5,3),
+                  'Ch16':(5,4),
+                  'Ch17':(5,5),
+                  'Ch18':(5,6),
+                  'Ch19':(5,7),
+                  'Ch20':(5,8),
+                  'Ch21':(5,9),
+                  'Ch22':(5,10)}
+def MeanStd(Data):
+    Arr = np.zeros([len(Data.keys()),len(Data[Data.keys()[0]])])
+    for iT,TrtName in enumerate(Data.keys()):
+        Arr[iT,:] = Data[TrtName]
+    
+    return np.mean(Arr,0), np.std(Arr,0)
+
+def MeanStdCNP(Data):
+    MeanCNP = np.array([])
+    StdCNP = np.array([])
+    for iT,TrtName in enumerate(Data.keys()):
+        Mean = np.mean(Data[TrtName])
+        Std = np.std(Data[TrtName])
+        MeanCNP = np.append(MeanCNP, Mean)
+        StdCNP = np.append(StdCNP, Std)
+    return MeanCNP, StdCNP
+
+
+plt.close('all')
+
+#%% DC charact plotting
+
+plt.close('all')
+
+Files = [
+         'IV-charact/IV-Day1-2/20190731_033840 Current vs Vgs_5sStep.txt',
+         'IV-charact/IV-Day1-2/20190801_031608 Current vs Vgs5s-afterRec6-highRange.txt',
+         'IV-charact/IV-Day2/20190802_115002 Current vs Vgs-24h2-PostRec7.txt',
+         'IV-charact/IV-Day4/20190803_031630 Current vs Vgs-PostRec12.txt',
+         'IV-charact/IV-Day6/20190805_113528 Current vs Vgs-PreRec1.txt',
+         'IV-charact/IV-Day12/20190811_090313 Current vs Vgs-PostRec1.txt',
+         'IV-charact/IV-Day26/20190825_080628 Current vs Vgs.txt']
+
+color = ['r','orange','g','b','purple','m','cyan']
+cmap = mpl.cm.rainbow
+
+legend= ['Day 1','Day 2','Day 3','Day 5','Day 7','Day 12','Day 28']
+time = [1,2,3,4,6,12,26]
+CNPDict = {}
+GMDict = {}
+GMforSN = {}
+counter = -1
+for iFile, File in enumerate(Files):
+    Fin = open(File)
+    
+    plt.figure(1)    
+    reader = csv.reader(Fin, delimiter='\t')
+    lenVgs = 1000
+    Vgs = np.zeros(lenVgs)
+    Ids = np.zeros([lenVgs,8])
+    GMforSN[iFile] = {}
+    
+    reader = csv.reader(Fin, delimiter='\t')
+    for il, e in enumerate(reader):
+        if il == 0:
+            continue
+        print(e)
+        
+        vg = e[0]
+        vg = vg.replace(',','.')
+        Vgs[il-1] = float(vg)
+        for iids, ids in enumerate(e[1:]):
+            ids = ids.replace(',','.')
+            Ids[il-1,iids] = float(ids)
+    
+        
+    CNP = np.array([])
+    GM = np.array([])
+    IdsTrim = {}
+    for i in range(8):
+        if i == 2:
+            continue
+        IdsTrim[i] = np.trim_zeros(Ids[:,i])
+        if i == 0:
+            Vgs = np.append(Vgs[0:2],np.trim_zeros(Vgs[2:]))
+            plt.plot(Vgs,IdsTrim[i],color = cmap(iFile / float(len(Files))), label = legend[iFile])
+            plt.legend()
+        else:
+            Vgs = np.append(Vgs[0:2],np.trim_zeros(Vgs[2:]))
+            plt.plot(Vgs,IdsTrim[i],color =cmap(iFile / float(len(Files))))
+        VgsFit = np.linspace(Vgs[0],Vgs[-1],100)
+        fitVal=np.polyval(np.polyfit(Vgs,IdsTrim[i],9),VgsFit)
+        
+        cnp = VgsFit[np.where(fitVal==np.min(fitVal))]
+        CNP = np.append(CNP,cnp)
+    
+        gm = np.max(abs(np.polyval(np.polyder(np.polyfit(Vgs,IdsTrim[i],9)),np.linspace(cnp-0.18, cnp,100))))*1e-2 #mS/V
+        GMforSN[iFile][i] = gm
+        GM = np.append(GM,gm)
+    CNPDict[iFile] = CNP
+    GMDict[iFile] = GM
+
+#### Calculate Gm
+    
+    if iFile not in [0,2,4,5,6]:
+        continue
+    counter += 1
+
+    
+    plt.figure(2)
+    MeanIds, StdIds = MeanStd(IdsTrim)
+    plt.plot(Vgs,MeanIds, color =color[counter], label = legend[iFile])
+    plt.fill_between(Vgs,MeanIds+StdIds,MeanIds-StdIds, color =color[counter], alpha=0.3)
+
+plt.legend(bbox_to_anchor=(0.0, 0.36, 0.7, 0.0),fontsize=13)
+plt.xlabel('V$_{gs}$ (V)',fontsize=15)
+plt.ylabel('I$_{ds}$ ($\mu$A)',fontsize=15)
+plt.xticks(fontsize=13)
+plt.yticks(fontsize=13)
+
+MeanCNP, StdCNP = MeanStdCNP(CNPDict)
+CNPArray = np.zeros([len(Files),7])
+GMArray = np.zeros([len(Files),7])
+w = 0.1
+width = lambda p, w: 10**(np.log10(p)+w/2.)-10**(np.log10(p)-w/2.)
+for ikey,key in enumerate(CNPDict.keys()):
+
+    CNPArray[ikey,:] = CNPDict[key].T
+    GMArray[ikey,:] = GMDict[key].T
+
+plt.figure()
+plt.boxplot(CNPArray.T, positions = time, widths =  width(time,w))
+plt.xlabel('time (days)')
+plt.ylabel('CNP (V)')
+width = lambda p, w: 10**(np.log10(p)+w/2.)-10**(np.log10(p)-w/2.)
+
+plt.figure()
+plt.boxplot(GMArray.T, positions = time, widths = width(time,w))
+plt.xlabel('time(h)')
+plt.ylabel('Gm (mS/V)')
+plt.xscale('log')
+
+
+
+#%% Noise Plotting
+dates = [
+         'Day1-2',
+         'Day2',
+         'Day4',
+         'Day6',
+         'Day12',
+         'Day26'
+         ]
+
+cmap = mpl.cm.rainbow
+
+
+DCch = ['ME5','ME7','ME29','ME31','SE5','SE7','SE29','SE31']
+
+Directory = 'PSD-charact/{}/'.format(dates[0])
+ImportNoise = dd.io.load(Directory+'Power200Hz5')
+noise = np.ones((len(dates),len(ImportNoise)))*(-10000)
+
+GmDCNoise = np.zeros((len(dates),len(DCch)))
+GMDC = np.zeros((len(dates),len(DCch)))
+
+days = [1,2,3,6,11,29]
+NoiseMin = 2.5e-10
+GmMin = 1.5e-9
+DayNum = days
+
+figN,axN =plt.subplots()
+
+#axN = axS.twinx()
+for iday, day in enumerate(dates):
+    Directory = 'PSD-charact/{}/'.format(day)
+    ImportNoise = dd.io.load(Directory+'Power200Hz5')
+    
+    print(day)
+    for ikey, key in enumerate(ImportNoise.keys()):
+        print(iday,key,ikey)
+        
+        if key in DCch:
+            if DCch.index(key) == 2:
+                continue
+            
+            GmDCNoise[iday,DCch.index(key)] = 1e6*np.sqrt(ImportNoise[key]*200*np.log(10/1)/np.sqrt(2))/(GMforSN[iday][DCch.index(key)]*1e-4)
+            GMDC[iday,DCch.index(key)] = (GMforSN[iday][DCch.index(key)])
+
+        Aparam = np.sqrt(ImportNoise[key]*200)
+        if  Aparam >= NoiseMin:
+            noise[iday,ikey] = Aparam
+        else:
+            noise[iday,ikey] = -100000
+            print('{} damaged -Trt{}'.format(iday,key))
+        
+        
+        
+        figN
+        w = 0.04
+        width = lambda p, w: 10**(np.log10(p)+w/2.)-10**(np.log10(p)-w/2.)
+        axN.semilogy(np.random.normal(iday+1, w, size=1)-6*w, Aparam, 'k*',markersize=2)
+    axN.set_xlabel('Time(days)')
+    axN.set_ylabel('Estimate Irms(A) @1Hz')
+
+
+    
+figN
+
+w = 0.035
+width = lambda p, w: 10**(np.log10(p)+w/2.)-10**(np.log10(p)-w/2.)
+PropS = {}
+PropS['markeredgecolor'] = 'r'
+
+N = axN.boxplot(noise.T,widths = 4*w)#,positions = np.array(days)+1.7*width(days,w),widths=width(days,w))
+axN.set_xticklabels(days,)
+#axN.set_xscale("log")
+axN.set_xlabel('time (days)')
+axN.set_ylabel('Estimate I$_{ds-rms}$ (A) @1Hz')
+
+
+plt.legend()
+
+for element in ['boxes', 'whiskers', 'fliers', 'means', 'medians', 'caps']:
+    plt.setp(N[element], color='k',markersize=2)
+
+for patch in N['boxes']:
+    patch.set(color='k') 
+
+
+
+
+fig2,ax2 = plt.subplots()
+
+w = 0.1
+width = lambda p, w: 10**(np.log10(p)+w/2.)-10**(np.log10(p)-w/2.)
+
+bp = ax2.boxplot(GmDCNoise.T)#,positions = days, widths=width(days,w))
+
+ax2.set_xticklabels(days,)
+for element in ['boxes', 'whiskers', 'fliers', 'means', 'medians', 'caps']:
+    plt.setp(bp[element], color='k')
+
+for patch in bp['boxes']:
+    patch.set(color='k') 
+
+plt.xlabel('time (days)')
+plt.ylabel('V$_{gs-rms}$ ($\mu$V)')
+
+