Commit 14496cf3 authored by Camron Blackburn's avatar Camron Blackburn
Browse files

clean notebook

parent 6fb9cfec
Pipeline #5422 passed with stage
in 6 seconds
......@@ -26,110 +26,10 @@
master_table
```
%%%% Output: execute_result
image avg fiber diameter (um) thickness (mm) \
name
3M_1000MPR NaN NaN 0.280
3M_1900MPR NaN NaN 0.319
3M_300MPR NaN NaN 0.292
3M_N95 NaN NaN 0.721
Arauco_BKP NaN NaN 1.800
Arauco_EKP NaN NaN 1.300
Arauco_UKP NaN NaN 1.600
Gerson_N95 NaN NaN 1.076
HEPA NaN NaN 0.209
HV_PN13015AP2 NaN NaN 0.081
HV_TSP050PLUS NaN NaN 0.295
HV_TSP050YA002 NaN NaN 0.446
HV_TSP100NS015 NaN NaN 0.437
KC_47117 NaN NaN 0.184
cotton NaN NaN 0.333
polyester NaN NaN 0.137
tyvek NaN NaN 0.143
weight (g/cm^2) filter efficiency (%) pressure drop (psi) \
name
3M_1000MPR NaN NaN NaN
3M_1900MPR NaN NaN NaN
3M_300MPR NaN NaN NaN
3M_N95 0.0223 NaN NaN
Arauco_BKP 0.0639 NaN NaN
Arauco_EKP 0.0772 NaN NaN
Arauco_UKP 0.0821 NaN NaN
Gerson_N95 0.0306 NaN NaN
HEPA NaN NaN NaN
HV_PN13015AP2 0.0020 NaN NaN
HV_TSP050PLUS 0.0064 NaN NaN
HV_TSP050YA002 0.0143 NaN NaN
HV_TSP100NS015 0.0152 NaN NaN
KC_47117 0.0067 NaN NaN
cotton NaN NaN NaN
polyester NaN NaN NaN
tyvek 0.0065 NaN NaN
nameref \
name
3M_1000MPR ./materials/3M_1000MPR/3M_1000MPR.html
3M_1900MPR ./materials/3M_1900MPR/3M_1900MPR.html
3M_300MPR ./materials/3M_300MPR/3M_300MPR.html
3M_N95 ./materials/3M_N95/3M_N95.html
Arauco_BKP ./materials/Arauco_BKP/Arauco_BKP.html
Arauco_EKP ./materials/Arauco_EKP/Arauco_EKP.html
Arauco_UKP ./materials/Arauco_UKP/Arauco_UKP.html
Gerson_N95 ./materials/Gerson_N95/Gerson_N95.html
HEPA ./materials/HEPA/HEPA.html
HV_PN13015AP2 ./materials/HV_PN13015AP2/HV_PN13015AP2.html
HV_TSP050PLUS ./materials/HV_TSP050PLUS/HV_TSP050PLUS.html
HV_TSP050YA002 ./materials/HV_TSP050YA002/HV_TSP050YA002.html
HV_TSP100NS015 ./materials/HV_TSP100NS015/HV_TSP100NS015.html
KC_47117 ./materials/KC_47117/KC_47117.html
cotton ./materials/cotton/cotton.html
polyester ./materials/polyester/polyester.html
tyvek ./materials/tyvek/tyvek.html
imagepath
name
3M_1000MPR ./materials/3M_1000MPR/SEM/3M_filtrete1000_20n...
3M_1900MPR ./materials/3M_1900MPR/SEM/3M_filtrete1900_20n...
3M_300MPR ./materials/3M_300MPR/SEM/3M_filtrete300_20nmA...
3M_N95 ./materials/3M_N95/SEM/3MN95_nosputter_top_000...
Arauco_BKP ./materials/Arauco_BKP/SEM/AraucoBKP_6_20nmAu_...
Arauco_EKP ./materials/Arauco_EKP/SEM/AraucoEKP_8_20nmAu_...
Arauco_UKP ./materials/Arauco_UKP/SEM/AraucoUKP_6_20nmAu_...
Gerson_N95 ./materials/Gerson_N95/SEM/GersonN95_nosputter...
HEPA ./materials/HEPA/SEM/inline_HEPA_20nmAu_top_00...
HV_PN13015AP2 ./materials/HV_PN13015AP2/SEM/PN13015AP2_20nmA...
HV_TSP050PLUS ./materials/HV_TSP050PLUS/SEM/TS050PLUS_20nmAu...
HV_TSP050YA002 ./materials/HV_TSP050YA002/SEM/TSP050YA002_20n...
HV_TSP100NS015 ./materials/HV_TSP100NS015/SEM/TSP100NS015_20n...
KC_47117 ./materials/KC_47117/SEM/KC47117_20sputter_mid...
cotton ./materials/cotton/SEM/tshirt_100cotton_20nmAu...
polyester ./materials/polyester/SEM/pillowcase_20nmAu_to...
tyvek ./materials/tyvek/SEM/tyvek_20nmAu_top_0005_re...
%% Cell type:markdown id: tags:
### Fiber diameter (fd in $\mu$m)
%% Cell type:code id: tags:
``` python
fd_data = pd.read_csv("./data/fiber_diameter.csv", header=1, dtype=float)
fd_sum = pd.DataFrame(index=fd_data.columns, columns=["fiber diam"], dtype=str)
for (name, data) in fd_data.iteritems():
data = data.dropna().to_numpy()
mean = round(data.mean(), 2)
std = round(data.std(), 2)
master_table.loc[name, "avg fiber diameter (um)"] = "%s +/- %s" %(mean, std)
master_table
```
%%%% Output: execute_result
image avg fiber diameter (um) thickness (mm) \
name
3M_1000MPR NaN 18.2 +/- 2.39 0.280
3M_1900MPR NaN 15.93 +/- 0.72 0.319
3M_300MPR NaN 23.94 +/- 1.61 0.292
......@@ -206,10 +106,29 @@
KC_47117 ./materials/KC_47117/SEM/KC47117_20sputter_mid...
cotton ./materials/cotton/SEM/tshirt_100cotton_20nmAu...
polyester ./materials/polyester/SEM/pillowcase_20nmAu_to...
tyvek ./materials/tyvek/SEM/tyvek_20nmAu_top_0005_re...
%% Cell type:markdown id: tags:
### Fiber diameter (fd in $\mu$m)
%% Cell type:code id: tags:
``` python
fd_data = pd.read_csv("./data/fiber_diameter.csv", header=1, dtype=float)
fd_sum = pd.DataFrame(index=fd_data.columns, columns=["fiber diam"], dtype=str)
for (name, data) in fd_data.iteritems():
data = data.dropna().to_numpy()
mean = round(data.mean(), 2)
std = round(data.std(), 2)
#master_table.loc[name, "avg fiber diameter (um)"] = "%s +/- %s" %(mean, std)
#master_table
```
%% Cell type:code id: tags:
``` python
export_table = master_table.copy(deep=True)
export_table = export_table.reset_index()
......@@ -304,10 +223,13 @@
16 NaN
%% Cell type:code id: tags:
``` python
# CAUTION WITH THIS GUY
#
#
# wrrite to file
index_html = open("./index.html", mode="a")
index_html.write(html_table)
index_html.close()
```
......
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