-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathgui-read_data.py
335 lines (290 loc) · 11.7 KB
/
gui-read_data.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
import streamlit as st
from pathlib import Path
from neptoon_gui_utils import *
st.title(":material/full_stacked_bar_chart: Read data")
if not st.session_state["yaml_checked"]:
st.warning("You need to select a configuration first.")
else:
##############################
st.subheader("1. Data source")
##############################
use_raw_data = st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.parse_raw_data
selected_data_type = st.segmented_control(
"Select data type",
["Raw data", "Preformatted data"],
selection_mode="single",
default="Raw data" if use_raw_data else "Preformatted data",
)
if selected_data_type == "Raw data":
st.session_state["data_raw_file"] = Path(
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.data_location
or ""
)
uploaded_file = st.file_uploader(
"Upload files",
type={"csv", "zip"},
key="data_raw_upload",
)
if uploaded_file:
# File upload
st.session_state["data_raw_upload_name"] = uploaded_file.name
temp_file_path = save_uploaded_file(uploaded_file)
atexit.register(cleanup, temp_file_path)
st.session_state["data_raw_upload_file"] = temp_file_path
st.session_state["data_raw_file"] = temp_file_path
if st.session_state["data_raw_file"]:
if not st.session_state["data_raw_file"].is_file():
st.error(
"File **{:}** does not exist.".format(
st.session_state["data_raw_file"]
)
)
st.warning("No file selected yet. Please upload your data.")
st.session_state["data_read_ready"] = False
else:
# Already uploaded
st.success(
":material/check: Using **{:}** as raw data.".format(
st.session_state["data_raw_file"]
)
)
st.session_state["data_read_ready"] = True
# column_names
st.text_input(
label="Column names",
value=", ".join(
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.column_names
or []
),
key="input_dataraw_column_names",
)
c1, c2 = st.columns(2)
# Prefix
c1.text_input(
label="Prefix",
value=st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.prefix,
key="input_dataraw_prefix",
)
# Suffix
c2.text_input(
label="Suffix",
value=st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.suffix,
key="input_dataraw_suffix",
)
# skip_lines
c1.text_input(
label="Skip lines",
value=st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.skip_lines,
key="input_dataraw_skip_lines",
)
# separator
c2.text_input(
label="Separator",
value=st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.separator,
key="input_dataraw_separator",
)
with st.expander(
"More settings will be editable in future versions."
):
st.write(
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options,
)
elif selected_data_type == "Preformatted data":
st.session_state["data_preformatted_file"] = Path(
st.session_state[
"yaml"
].sensor_config.time_series_data.path_to_data
or ""
)
uploaded_file = st.file_uploader(
"Upload files",
type={"csv", "zip"},
key="data_preformatted_upload",
)
if uploaded_file:
# File upload
st.session_state["data_preformatted_upload_name"] = (
uploaded_file.name
)
temp_file_path = save_uploaded_file(uploaded_file)
atexit.register(cleanup, temp_file_path)
st.session_state["data_preformatted_upload_file"] = temp_file_path
st.session_state["data_preformatted_file"] = temp_file_path
if st.session_state["data_preformatted_file"]:
if not st.session_state["data_preformatted_file"].is_file():
st.error(
"File **{:}** does not exist.".format(
st.session_state["data_preformatted_file"]
)
)
st.warning("No file selected yet. Please upload your data.")
st.session_state["data_read_ready"] = False
else:
# Already uploaded
st.success(
":material/check: Using **{:}** as preformatted data.".format(
st.session_state["data_preformatted_file"]
)
)
st.session_state["data_read_ready"] = True
c1, c2 = st.columns(2)
# input_resolution
c1.text_input(
label="Input resolution",
value=st.session_state[
"yaml"
].sensor_config.time_series_data.temporal.input_resolution,
key="input_datapre_input_resolution",
)
# Output resolution
c2.text_input(
label="Output resolution",
value=st.session_state[
"yaml"
].sensor_config.time_series_data.temporal.output_resolution,
key="input_datapre_output_resolution",
)
# date_time_columns
c1.text_input(
label="Datetime columns",
value=", ".join(
st.session_state[
"yaml"
].sensor_config.time_series_data.key_column_info.date_time_columns
),
key="input_datapre_date_time_columns",
)
# date_time_format
c2.text_input(
label="Datetime format",
value=st.session_state[
"yaml"
].sensor_config.time_series_data.key_column_info.date_time_format,
key="input_datapre_date_time_format",
)
with st.expander(
"More settings will be editable in future versions."
):
st.write(
st.session_state[
"yaml"
].sensor_config.time_series_data.key_column_info,
)
################################
st.subheader("2. :material/search_insights: Data inspection")
################################
@st.cache_data(show_spinner="Creating data table...")
def parse_data():
import plotly.express as px
# with st.spinner("Creating data table..."):
st.session_state["yaml"].create_data_hub(return_data_hub=False)
data_hub = st.session_state["yaml"].data_hub
st.write(
"Parsed {:,.0f} lines and {:.0f} columns of data.".format(
len(data_hub.crns_data_frame),
len(data_hub.crns_data_frame.columns),
)
)
st.session_state["data_parsed"] = True
if st.session_state["data_read_ready"]:
if st.button(
":material/read_more: Apply and parse the data!", type="primary"
):
# st.write(st.session_state["yaml"].sensor_config)
if use_raw_data:
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.column_names = [
x.strip()
for x in st.session_state[
"input_dataraw_column_names"
].split(",")
]
st.write(
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.column_names
)
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.prefix = st.session_state[
"input_dataraw_prefix"
]
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.suffix = st.session_state[
"input_dataraw_suffix"
]
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.skip_lines = int(
st.session_state["input_dataraw_skip_lines"]
)
st.session_state[
"yaml"
].sensor_config.raw_data_parse_options.separator = st.session_state[
"input_dataraw_separator"
]
else:
st.session_state[
"yaml"
].sensor_config.time_series_data.key_column_info.date_time_format = st.session_state[
"input_datapre_date_time_format"
]
st.session_state[
"yaml"
].sensor_config.time_series_data.key_column_info.date_time_columns = [
x.strip()
for x in st.session_state[
"input_datapre_date_time_columns"
].split(",")
]
st.session_state[
"yaml"
].sensor_config.time_series_data.temporal.output_resolution = st.session_state[
"input_datapre_output_resolution"
]
st.session_state[
"yaml"
].sensor_config.time_series_data.temporal.input_resolution = st.session_state[
"input_datapre_input_resolution"
]
# st.success("Changes applied :smile:")
parse_data()
# st.write(st.session_state["yaml"].sensor_config)
@st.fragment
def make_selection_plot():
import plotly.express as px
tab1, tab2 = st.tabs(
[":material/Table: Raw data table", ":material/show_chart: Plots"]
)
tab1.dataframe(data_hub.crns_data_frame)
selected_columns = tab2.multiselect(
"Which columns would you like to view?",
options=data_hub.crns_data_frame.columns,
default="epithermal_neutrons_cph",
)
filtered_data = data_hub.crns_data_frame[selected_columns]
tab2.plotly_chart(
px.line(filtered_data, y=selected_columns),
use_container_width=True,
)
if st.session_state["data_parsed"]:
data_hub = st.session_state["yaml"].data_hub
make_selection_plot()