def _draw_aggrid_df(self, df):
gb = GridOptionsBuilder.from_dataframe(df)
gb.configure_pagination(paginationPageSize=25)
gb.configure_default_column(floatingFilter=True)
if 'error' in df.columns:
jscode = self._aggrid_style()
gb.configure_column("error",
floatingFilter=True,
cellStyle=jscode,
editable=False)
gb.configure_grid_options(domLayout='normal',
preventDefaultOnContextMenu=True)
gridOptions = gb.build()
gridOptions['getRowStyle'] = self._aggrid_style_rows(df)
_ = AgGrid(
df,
gridOptions=gridOptions,
allow_unsafe_jscode=True,
update_mode=GridUpdateMode.NO_UPDATE,
theme='streamlit',
)
def _draw_aggrid_df(self, expander, df):
with expander:
if df.empty:
st.info('No matching result found')
elif 'error' in df:
st.error(df['error'][0])
else:
gb = GridOptionsBuilder.from_dataframe(df)
gb.configure_pagination(paginationPageSize=25)
gb.configure_default_column(floatingFilter=True,
editable=False,
selectable=False)
gb.configure_grid_options(domLayout='normal',
preventDefaultOnContextMenu=True)
gridOptions = gb.build()
if df.shape[0] == 1:
height = 150
elif df.shape[0] < 4:
height = 200
else:
height = 400
_ = AgGrid(df,
height=height,
gridOptions=gridOptions,
allow_unsafe_jscode=True,
update_mode=GridUpdateMode.NO_UPDATE,
theme='streamlit',
key=str(randint(1, 10000000)))
def _draw_aggrid_df(self, df) -> AgGrid:
gb = GridOptionsBuilder.from_dataframe(df)
gb.configure_pagination(paginationPageSize=25)
gb.configure_default_column(floatingFilter=True, selectable=False)
gb.configure_grid_options(domLayout='normal')
gridOptions = gb.build()
gridOptions['rowStyle'] = {'background': 'white'}
jscode = self._aggrid_style_rows()
gridOptions['getRowStyle'] = jscode
if self._state.experimental_ok:
retmode = 'FILTERED'
upd8_mode = GridUpdateMode.FILTERING_CHANGED
else:
retmode = 'AS_INPUT'
upd8_mode = GridUpdateMode.VALUE_CHANGED
grid_response = AgGrid(
df,
gridOptions=gridOptions,
allow_unsafe_jscode=True,
data_return_mode=retmode,
update_mode=upd8_mode,
theme='streamlit',
key='xplore_show_tbl',
)
return grid_response
def configure_grid_stat(df):
gb = GridOptionsBuilder.from_dataframe(df)
gb.configure_default_column(editable=False)
# gb.configure_side_bar()
gb.configure_selection("multiple", use_checkbox=False,rowMultiSelectWithClick=True, suppressRowDeselection=False)
# gb.configure_grid_options(domLayout='autoHeight')
gb.configure_grid_options(domLayout='normal')
gridOptions = gb.build()
return gridOptions
def configure_grid_detail(df):
gb = GridOptionsBuilder.from_dataframe(df)
# gb.configure_default_column(groupable=False, value=True, enableRowGroup=False, editable=False)
# gb.configure_side_bar()
gb.configure_default_column(editable=False)
gb.configure_column("sentence",initialPinned="left")
# gb.configure_column("client_id",hide=True)
gb.configure_selection("single", use_checkbox=False)
gb.configure_pagination(paginationAutoPageSize=True)
gb.configure_grid_options(domLayout='normal')
gridOptions = gb.build()
return gridOptions
def files_select_ag_grid(add_current=False, mode="single"):
file_list = [
x.replace(".pickle", "") for x in list_dir("saved_sessions")
if ".pickle" in x
]
file_times = [
# datetime.datetime.fromtimestamp(
get_m_time(os.path.join("saved_sessions", f"{x}.pickle"))
# )
for x in file_list
]
files_desc = []
for f_name in file_list:
desc_f_name = os.path.join("saved_sessions", f"{f_name}.txt")
if file_exists(desc_f_name):
files_desc.append(open_file(desc_f_name).read())
else:
files_desc.append("")
if add_current:
file_list = ["Análise Atual"] + file_list
file_times = [""] + file_times
files_desc = [""] + files_desc
input_df = pd.DataFrame(
list(zip(file_list, file_times, files_desc)),
columns=["Nome", "Ùltima Modificação", "Descrição"],
)
gb = GridOptionsBuilder.from_dataframe(input_df)
gb.configure_selection(mode, use_checkbox=True)
gridOptions = gb.build()
update_mode_value = GridUpdateMode.__members__["MODEL_CHANGED"]
return AgGrid(
input_df,
gridOptions=gridOptions,
update_mode=update_mode_value,
height=200,
)
def aggriddf(df):
gb = GridOptionsBuilder.from_dataframe(df)
gb.configure_default_column(groupable=True,
value=True,
enableRowGroup=True,
aggFunc='sum',
editable=False)
gb.configure_grid_options(domLayout='normal')
#gb.configure_side_bar()
gridOptions = gb.build()
grid_response = AgGrid(
df,
gridOptions=gridOptions,
height=330,
width='100%',
#data_return_mode=return_mode_value,
#update_mode=update_mode_value,
allow_unsafe_jscode=
True, #Set it to True to allow jsfunction to be injected
enable_enterprise_modules=False,
)
return grid_response
import streamlit as st
import pandas as pd
import numpy as np
from st_aggrid import AgGrid, GridOptionsBuilder
df = pd.DataFrame(
np.random.randint(0, 100, 50).reshape(-1, 5),
index=range(10),
columns=list("abcde"),
)
available_themes = ["streamlit", "light", "dark", "blue", "fresh", "material"]
selected_theme = st.selectbox("Theme", available_themes)
gb = GridOptionsBuilder.from_dataframe(df)
if st.checkbox('Pre-select rows 4 and 6 when loading.'):
gb.configure_selection('multiple', pre_selected_rows=[3, 5])
response = AgGrid(df,
editable=True,
gridOptions=gb.build(),
data_return_mode="filtered_and_sorted",
update_mode="no_update",
fit_columns_on_grid_load=True,
theme=selected_theme)
metric_selections,
default="accuracy")
add_btn = trainer_container.button("Add Trainer")
if add_btn:
sessions.trainer_dict["dataloader"].append(data_selectBox)
sessions.trainer_dict["model"].append(model_selectBox)
sessions.trainer_dict["loss"].append(loss_selectBox)
sessions.trainer_dict["optimizer"].append(optimizer_selectBox)
sessions.trainer_dict["scheduler"].append(scheduler_selectBox)
sessions.trainer_dict["metrics"].append(metric_selects)
sessions.trainer_dict["id"].append(sessions.id)
sessions.id = sessions.id + 1
trainer_dataFrame = pd.DataFrame(sessions.trainer_dict)
gb = GridOptionsBuilder.from_dataframe(trainer_dataFrame)
gb.configure_selection('multiple',
use_checkbox=False,
rowMultiSelectWithClick=False,
suppressRowDeselection=True)
gridOptions = gb.build()
grid_response = AgGrid(trainer_dataFrame,
gridOptions=gridOptions,
height=180,
width='100%',
data_return_mode=DataReturnMode.FILTERED,
update_mode=GridUpdateMode.MODEL_CHANGED,
fit_columns_on_grid_load=True,
allow_unsafe_jscode=True,
enable_enterprise_modules=True)
trainer_res = grid_response['selected_rows']
def verifier_page():
st.set_page_config(page_title="SPOC Verifier", layout="wide")
main_col, geo_col, action_col = st.beta_columns([2, 1, 0.5])
species = pd.read_json("data/species-records.json")
grid_options = GridOptionsBuilder.from_dataframe(species)
# Grid options
grid_options.configure_selection("single", use_checkbox=True)
grid_options.configure_pagination(paginationAutoPageSize=True)
with main_col:
"""
# SPOC Verifier
"""
records_grid = AgGrid(
species,
gridOptions=grid_options.build(),
data_return_mode=DataReturnMode.FILTERED,
update_mode=GridUpdateMode.MODEL_CHANGED,
)
selected = records_grid["selected_rows"]
with geo_col:
if len(selected) > 0:
f"""
## {selected[0]['Species']}
"""
url_params = url_parse.urlencode({
"div_num":
selected[0]["div_enum"],
"paper_id":
selected[0]["Paper ID"],
"species_id":
selected[0]["Instance ID"],
})
div_url = f"{settings.api_url}/api/div/?{url_params}"
result = requests.get(div_url)
entities_html = entities_template.render(
content=result.json().get("html"))
components.html(entities_html, height=500, scrolling=True)
with action_col:
action_html = action_template.render(status="select")
components.html(action_html, height=75, width=65)
if len(selected) > 0:
"""
## Places
"""
geo_request = requests.get(
f"{settings.api_url}/api/coordinates/?places={selected[0]['Place']}"
)
geo_result = geo_request.json()
if len(geo_result) < 1:
st.text("No places found")
else:
m = folium.Map(
location=[geo_result["lat_mean"], geo_result["long_mean"]],
zoom_start=7)
for place in geo_result["markers"]:
folium.Marker(
[place["latitude"], place["longitude"]],
popup=place["label"],
tooltip=place["label"],
).add_to(m)
folium_static(m)
by=['points_next_event'], ascending=False)
grouped_golfers_last_8 = grouped_golfers_last_8.reset_index().drop('index',
axis=1)
cols_to_move = [
'Name', 'number_events', 'Week', 'last_8_rank', 'median_rank',
'total_med_rank', 'pos_next_event', 'total_rank', 'points_next_event',
'cum_median_rank', 'cum_8_rank', 'cum_8_median_rank', 'cum_8_exp4_rank'
]
cols = cols_to_move + [
col for col in grouped_golfers_last_8 if col not in cols_to_move
]
grouped_golfers_last_8 = grouped_golfers_last_8[cols].sort_values(
by=['points_next_event'], ascending=False)
st.write('Average Pts for last 8 events', grouped_golfers_last_8)
gb = GridOptionsBuilder.from_dataframe(grouped_golfers_last_8)
gb.configure_column(
"total_points",
type=["numericColumn", "numberColumnFilter", "customNumericFormat"],
precision=0,
aggFunc='sum')
gb.configure_column(
"avg_points",
type=["numericColumn", "numberColumnFilter", "customNumericFormat"],
precision=0,
aggFunc='sum')
gb.configure_column(
"exp_points",
type=["numericColumn", "numberColumnFilter", "customNumericFormat"],
precision=0,
aggFunc='sum')
def main():
st.markdown(""" <style>
#MainMenu {visibility: hidden;}
footer {visibility: hidden;}
</style> """,
unsafe_allow_html=True)
padding = 0
st.markdown(f""" <style>
.reportview-container .main .block-container{{
padding-top: {padding}rem;
padding-right: {padding}rem;
padding-left: {padding}rem;
padding-bottom: {padding}rem;
}} </style> """,
unsafe_allow_html=True)
COLOR = "black"
BACKGROUND_COLOR = "#fff"
max_width = 860
padding_top = 0
padding_right = 0
padding_left = 0
padding_bottom = 0
dj_contents = dj_soup.select(".prof dl")
for i, element in enumerate(dj_contents):
dj_ids.append(element.select('dt')[0]['id'])
dj_images_urls.append(element.select('dt')[0].select('img')[0]['src'])
dj_href = element.select('a')[0]['href']
if '/programs/' in dj_href:
dj_hrefs.append(domain + dj_href)
else:
dj_hrefs.append(dj_href)
el2 = dj_contents[i].get_text().split('\n')[1:-1]
key = el2[0].split('：')[1]
# --
dj_otherDicts = dict() #init
for j in el2[1:]:
key2 = j.split('：')[0]
value = j.split('：')[1]
dj_otherDicts.update({key2: value})
one_dict = {key: dj_otherDicts}
dj_dicts.update(one_dict)
for element in dj_contents:
el1 = element.get_text().split('\n')[1:-1]
name = el1[0].split('：')[1]
dj_names.append(name)
# -- 担当番組Program
contents = dj_dicts[name]
if '担当番組' in contents:
dj_haveprograms.append(contents['担当番組'])
else:
dj_haveprograms.append('')
# -- 誕生日Birth
if '誕生日' in contents:
dj_births.append(contents['誕生日'])
else:
dj_births.append('')
# -- 血液型Blood
if '血液型' in contents:
dj_bloods.append(contents['血液型'])
else:
dj_bloods.append('')
# -- 身長Hight
if '身長' in contents:
dj_heights.append(contents['身長'])
else:
dj_heights.append('')
# -- 趣味Hobbys
if '趣味' in contents:
dj_hobbys.append(contents['趣味'])
else:
dj_hobbys.append('')
# -- 特技Skills
if '特技' in contents:
dj_skills.append(contents['特技'])
else:
dj_skills.append('')
df = pd.DataFrame({
'id': dj_ids,
'名前Name': dj_names,
'担当番組Program': dj_haveprograms,
'誕生日Birth': dj_births,
'血液型Blood': dj_bloods,
'身長Hight': dj_heights,
'趣味Hobbys': dj_hobbys,
'特技Skills': dj_skills,
'画像URL': dj_images_urls
})
# df.index = np.arange(1, len(df)+1)
for cnt, entrie in enumerate(program_res.entries):
#program_id = entrie['mobileimg']['src'].split('/')[5] #bad error 2021/11/05
program_id = entrie['link'].split('/')[5] #new 2021/11/05
mark = "/" + program_id + "/"
href = entrie['links'][1]['href']
program_ids.append(program_id)
program_titles.append(str(cnt + 1) + ": " + entrie['title'])
program_subtitles.append(entrie['mobilesubtitle'])
program_image_urls.append(entrie['mobileimg']['src'])
program_summarys.append(entrie['summary'])
program_sound_urls.append(program_base + mark + href)
datestr = entrie['published']
program_pubdates.append(
datetime.datetime.strptime(
datestr, '%a, %d %b %Y %H:%M:%S %z').strftime('%Y/%m/%d'))
program_djnames.append(' ')
program_sound_times.append(' ')
# program_djnames 追加
for i, dj_id in enumerate(program_ids):
if dj_id in dj_ids:
program_djnames[i] = dj_names[dj_ids.index(dj_id)]
else:
program_djnames[i] = ''
df2 = pd.DataFrame({
'id': program_ids,
'Program': program_titles,
'番組名': program_subtitles,
'DJName': program_djnames,
'配信日Pubday': program_pubdates,
'再生時間SoundTime': program_sound_times
})
# df.index = np.arange(1, len(df)+1)
st.title("RADIO365 DJ's Fan site")
hedder_text = f"""Obtained automatically from [RADIO365](https://www.radio365.net/). [update:2021/11/06]<br>
Click the Play button below the image to play the program. (Please pay attention to the audio)<br>
You can also use the upper left select box to switch programs (from 1 to 100).<br>
[RADIO365](https://www.radio365.net/)から自動取得しています。<br>
画像の下にある再生ボタンで番組が再生されます。（音声にご注意ください）<br>
左上セレクトボックスでも番組(1～100迄)切替ができます。
"""
st.markdown(hedder_text, unsafe_allow_html=True)
selector = st.sidebar.selectbox("Select program (1 - 100):",
program_titles)
select_indexNumber = int(selector.split(':')[0]) - 1
# dark_theme = st.sidebar.checkbox("Dark Theme", False)
# if dark_theme:
# BACKGROUND_COLOR = "rgb(17,17,17)"
# COLOR = "#fff"
st.markdown(
f"""
<style>
.reportview-container .main .block-container{{
max-width: {max_width}px;
# padding-top: {padding_top}rem;
# padding-right: {padding_right}rem;
# padding-left: {padding_left}rem;
# padding-bottom: {padding_bottom}rem;
}}
# .reportview-container .main {{
# color: {COLOR};
# background-color: {BACKGROUND_COLOR};
# }}
# h1 {{
# color: {COLOR};
# background-color: {BACKGROUND_COLOR};
# }}
# h5 {{
# color: {COLOR};
# background-color: {BACKGROUND_COLOR};
# }}
# .css-145kmo2 {{
# color: {COLOR};
# background-color: {BACKGROUND_COLOR};
# }}
# .css-qbe2hs {{
# color: {COLOR};
# background-color: {BACKGROUND_COLOR};
# }}
# .st-ck {{
# color: {COLOR};
# background-color: {BACKGROUND_COLOR};
# }}
# .css-xq1lnh-EmotionIconBase {{
# color: {COLOR};
# background-color: {BACKGROUND_COLOR};
# }}
</style>
""",
unsafe_allow_html=True,
)
markdown_str = "#### " + '<font color="Gray">' + program_subtitles[
select_indexNumber] + '</font>'
st.markdown(markdown_str, unsafe_allow_html=True)
#===== read sidebar image file =======
img_data = read_image(program_image_urls[select_indexNumber])
st.image(img_data, caption=selector, use_column_width=True)
# sound update
sound_data = read_sound_data(program_sound_urls[select_indexNumber])
st.audio(sound_data, format='audio/aac')
st.markdown(program_summarys[select_indexNumber], unsafe_allow_html=True)
st.write('')
# DJ photo & profile block
htmls = set_hrefs(dj_hrefs)
html_height = (int(len(htmls) / 8) + 1) * 62
joinhtml = "".join(htmls)
html = f"""{joinhtml}"""
with st.expander("DJ Photo (please click to see phot & profile)",
expanded=True):
componentsv1.html(html, height=html_height, scrolling=True)
st.sidebar.text('')
# Sidebar DJ photo
temp_text = str(len(dj_images_urls)) + " DJ member:"
st.sidebar.text(temp_text)
dj_img_datas = read_sidebar_photos()
for i, dj_image_url in enumerate(dj_images_urls):
st.sidebar.image(dj_img_datas[i],
caption=dj_names[i],
use_column_width='True')
# for i, program_sound_url in enumerate(program_sound_urls):
# sound_data = read_sound_data(program_sound_urls[i])
# program_sound_times[i] = get_sound_time(program_sound_urls[i], sound_data)
# DJ List
with st.expander("DJ List (please click to see dj list)", expanded=True):
#customize gridOptions
gb = GridOptionsBuilder.from_dataframe(df)
gb.configure_grid_options(
pagination=True,
paginationAutoPageSize=True,
)
gridOptions = gb.build()
AgGrid(df, autosize=True, gridOptions=gridOptions)
st.markdown(get_table_download_link(df), unsafe_allow_html=True)
# Program List
with st.expander('Program List (please click to see program list)',
expanded=True):
gb2 = GridOptionsBuilder.from_dataframe(df2)
gb2.configure_grid_options(
pagination=True,
paginationAutoPageSize=True,
)
gridOptions2 = gb2.build()
AgGrid(df2, autosize=True, gridOptions=gridOptions2)
st.markdown(get_table_download_link(df2), unsafe_allow_html=True)
def app():
st.markdown("## Timestamped Corpus")
if st.session_state.metadata:
kiara = st.session_state["kiara"]
augmented_table_value = st.session_state.augmented_data
sql_query_day = "SELECT strptime(concat(day, '/', month, '/', year), '%d/%m/%Y') as date, pub_name, count FROM (SELECT YEAR(date) as year, MONTH(date) as month, DAY(date) as day, pub_name, count(*) as count FROM data group by YEAR(date), MONTH(date), DAY(date), pub_name ORDER BY year, month, day, pub_name) as agg"
sql_query_month = "SELECT strptime(concat('01/', month, '/', year), '%d/%m/%Y') as date, pub_name, count FROM (SELECT YEAR(date) as year, MONTH(date) as month, pub_name, count(*) as count FROM data group by YEAR(date), MONTH(date), pub_name ORDER BY year, month, pub_name) AS agg"
sql_query_year = "SELECT strptime(concat('01/01/', year), '%d/%m/%Y') as date, pub_name, count FROM (SELECT YEAR(date) as year, pub_name, count(*) as count FROM data group by YEAR(date), pub_name ORDER BY year, pub_name) AS agg"
my_expander = st.sidebar.expander(label='Settings')
with my_expander:
unit = st.selectbox("Aggregate by", ('year', 'month', 'day'))
scaleType = st.selectbox("Scale by", ('color', 'height'))
axisLabel = st.selectbox("Axis",
('5-year', 'year', 'month', 'day'))
if unit == "day":
query = sql_query_day
elif unit == "month":
query = sql_query_month
else:
query = sql_query_year
query_workflow = kiara.create_workflow("table.query.sql")
query_workflow.inputs.set_values(table=augmented_table_value,
query=query)
query_result_value = query_workflow.outputs.get_value_obj(
"query_result")
query_result_table = query_result_value.get_value_data()
data = list(
query_result_table.to_pandas().to_dict(orient="index").values())
data_json = json.dumps(data, default=str)
cleaned_data = json.loads(data_json)
observers = observable("Test",
notebook="d/d1e17c291019759e",
targets=["viewof chart", "style"],
redefine={
"timeSelected": unit,
"data": cleaned_data,
"scaleType": scaleType,
"axisLabel": axisLabel
},
observe=["dateInfo"])
timeInfo = observers.get("dateInfo")
col1, col2 = st.columns(2)
if "preview_choice" not in st.session_state:
st.session_state.preview_choice = "data"
with col1:
data_preview = st.button(label='Aggregated data')
with col2:
source_view = st.button(label='Sources list by time period')
if data_preview:
st.session_state.preview_choice = "data"
if source_view:
st.session_state.preview_choice = "source"
display_choice = st.session_state.preview_choice
if display_choice == "data":
AgGrid(query_result_table.to_pandas())
else:
if timeInfo is None:
st.markdown(
'Hover over chart and click on date that appears on top')
if timeInfo is not None:
sql_query_day2 = f"SELECT pub_name, date, content FROM data WHERE DATE_PART('year', date) = {timeInfo[0]} AND DATE_PART('month', date) = {timeInfo[1]} and DATE_PART('day', date) = {timeInfo[2]}"
sql_query_month2 = f"SELECT pub_name, date, content FROM data WHERE DATE_PART('year', date) = {timeInfo[0]} AND DATE_PART('month', date) = {timeInfo[1]}"
sql_query_year2 = f"SELECT pub_name, date, content FROM data WHERE DATE_PART('year', date) = {timeInfo[0]}"
if unit == "day":
query2 = sql_query_day2
elif unit == "month":
query2 = sql_query_month2
else:
query2 = sql_query_year2
query_workflow2 = kiara.create_workflow("table.query.sql")
query_workflow2.inputs.set_values(table=augmented_table_value,
query=query2)
query_result_value2 = query_workflow2.outputs.get_value_obj(
"query_result")
query_result_table2 = query_result_value2.get_value_data()
df2 = query_result_table2.to_pandas()
gb = GridOptionsBuilder.from_dataframe(df2)
gb.configure_column("content",
maxWidth=800,
tooltipField="content")
AgGrid(df2.head(100), gridOptions=gb.build())
else:
st.write(
"This optional step is only activated if your corpus files contain dates. Please go to the next step."
)
import pandas as pd
from st_aggrid import AgGrid, DataReturnMode, GridUpdateMode, GridOptionsBuilder, JsCode, grid_options_builder
@st.cache()
def get_data(multiindex=False):
df = pd.DataFrame(
np.random.randint(0, 100, 100).reshape(-1, 5),
columns=list("abcde"),
index=pd.MultiIndex.from_product(
[list("xyzw"), list("12345")]) if multiindex else None)
return df
multiindex = st.sidebar.checkbox("Create a Multindexed DataFrame", False)
data = get_data(multiindex)
#converts the multi index to a . separated string :)
if multiindex:
data.index = [".".join(t) for t in data.index]
data = data.reset_index()
gb = GridOptionsBuilder.from_dataframe(data, minWidth=150)
gb.configure_first_column_as_index()
go = gb.build()
AgGrid(data,
go,
enable_enterprise_modules=True,
fit_columns_on_grid_load=False)
def main():
# オブジェクトを毎回読み込みを避けるため
if 'robot' not in st.session_state:
st.session_state['robot'] = bcap_robot()
if 'start_flg' not in st.session_state:
st.session_state['start_flg'] = False
# End if
st.title('ロボットコントローラボード')
st.sidebar.header('接続先のロボットのIPアドレスを入力してください')
# テキスト入力
ip_add_str = st.sidebar.text_input('IPアドレス', '192.168.0.1')
# ボタン
start_button = st.sidebar.empty()
select_boad_type = st.sidebar.radio('モードを選択してください。', ('robot_control', 'program_edit', 'variable_edit', 'position_monitor'))
if not st.session_state['start_flg']:
st.session_state['start_flg'] = start_button.button('Start', key='start')
else:
st.session_state['start_flg'] = not(start_button.button('Stop', key='start'))
if st.session_state['start_flg']:
res = st.session_state['robot'].connect(ip_add_str, 5007)
st.write(res) # markdown
st.subheader('接続先ロボット情報') # サブヘッダー
ret_DataFrame = st.session_state['robot'].get_base_information()
st.table(ret_DataFrame)
if select_boad_type == 'robot_control':
st.subheader('ロボットを操作します。')
ret_ext_val = st.session_state['robot'].get_extSpeed()
ExtSpeed = st.slider(label='extenal Speed', min_value=0.1, max_value=100.0, value=ret_ext_val)
st.session_state['robot'].set_extSpeed(ExtSpeed)
colA, colB = st.columns(2)
with colA:
control_mode_list = ['各軸', 'X-Y', 'Tool']
control_mode = st.selectbox('動作モード', control_mode_list)
with colB:
dist_len = 0.0
dist_len = st.number_input('動作距離', 0.0, 10.0, 0.0, step=0.1)
move_label = []
move_flg = [0, 0, 0, 0, 0, 0]
if control_mode == '各軸':
move_label = ['J' + str(i) for i in range(1, 7)]
else:
move_label = ['X', 'Y', 'Z', 'Rx', 'Ry', 'Rz']
# End if
# カラムを追加する
col1, col2, col3 = st.columns(3)
with col1:
for i in range(6):
if st.button('-' + str(move_label[i]), key='m_' + str(i)):
move_flg[i] -= 1
with col2:
for i in range(6):
st.text(' ' + str(move_label[i]) + ' ')
with col3:
for i in range(6):
if st.button('+' + str(move_label[i]), key='p_' + str(i)):
move_flg[i] += 1
if sum(move_flg) != 0:
st.session_state['robot'].move_func(control_mode, dist_len, move_flg)
elif select_boad_type == 'program_edit':
select_program = ''
select_list_programs = st.session_state['robot'].get_tasknames()
select_program = st.selectbox('編集するプログラムを選択する', select_list_programs)
if select_program != '':
ret_file_val = st.session_state['robot'].get_file_value(select_program + '.pcs')
new_text = st.text_area('Ctrl + Enter でコントローラへ書き込みます。', height=300, value=ret_file_val)
st.session_state['robot'].rewrite_file_value(select_program + '.pcs', new_text)
elif select_boad_type == 'variable_edit':
select_list_variable = ['I', 'F', 'D', 'V', 'P', 'J', 'T', 'S']
select_variable = st.sidebar.selectbox('編集する', select_list_variable)
val_len = st.session_state['robot'].get_value_len(select_variable)
val_data = []
val_index = []
val_columns = []
if select_variable == 'V':
val_columns = ['X', 'Y', 'Z', 'Use']
elif select_variable == 'P':
val_columns = ['X', 'Y', 'Z', 'Rx', 'Ry', 'Rz', 'Fig', 'Use']
elif select_variable == 'J':
val_columns = ['J1', 'J2', 'J3', 'J4', 'J5', 'J6', 'J7', 'J8', 'Use']
elif select_variable == 'T':
val_columns = ['X', 'Y', 'Z', 'Ox', 'Oy', 'Oz', 'Ax', 'Ay', 'Az', 'Fig', 'Use']
else:
val_columns = ['value', 'Use']
# End if
for index in range(val_len):
data = st.session_state['robot'].get_value(select_variable, index)
if type(data) is list:
val_data.append(data + [''])
else:
val_data.append([data, ''])
val_index.append(select_variable + str(index))
df = pd.DataFrame(val_data, index=val_index, columns=val_columns)
# End for
# st.write(df)
# st.table(df)
gb = GridOptionsBuilder.from_dataframe(df, editable=True)
grid = AgGrid(df, gridOptions=gb.build(), fit_columns_on_grid_load=True, updateMode=GridUpdateMode.VALUE_CHANGED)
# 修正が反映される
st.dataframe(grid['data'])
if st.button('Write', key='Write to controller variable'):
write_count = st.empty()
bar = st.progress(0)
max_len = len(grid['data'].values.tolist())
for i, data in enumerate(grid['data'].values.tolist()):
if(len(data) == 2):
new_val = data[0]
else:
new_val = data[:-1]
# End if
st.session_state['robot'].put_value(select_variable, i, new_val)
write_count.text(f'count {i + 1}')
bar.progress((i + 1) / max_len)
# End for
st.write('write')
# End if
elif select_boad_type == 'position_monitor':
count = 0
t = []
x = []
y = []
z = []
rx = []
ry = []
rz = []
# グラフを書き出すためのプレースホルダを用意する
plot_area = st.empty()
fig, axes = plt.subplots(3, 2)
if st.button('Stop', key='stop'):
pass
while True:
# 現在のグラフを消去する
for i in (0, 1, 2):
for j in (0, 1):
axes[i][j].clear()
# End for
# End for
# データを追加する
pos_list = st.session_state['robot'].get_curpos()
count = count + 1
t.append(count)
x.append(pos_list[0])
y.append(pos_list[1])
z.append(pos_list[2])
rx.append(pos_list[3])
ry.append(pos_list[4])
rz.append(pos_list[5])
axes[0][0].plot(t, x, color='black')
axes[1][0].plot(t, y, color='black')
axes[2][0].plot(t, z, color='black')
axes[0][1].plot(t, rx, color='black')
axes[1][1].plot(t, ry, color='black')
axes[2][1].plot(t, rz, color='black')
# 100個以上のデータは削除する (FIFO)
if len(t) >= 100:
del t[0]
del x[0]
del y[0]
del z[0]
del rx[0]
del ry[0]
del rz[0]
# プレースホルダに書き出す
plot_area.pyplot(fig)
time.sleep(0.01)
# End while
else:
pass
reputación que es compartida entre todos los comerciantes participantes. Incluso los
comerciantes recién iniciados en el mundo de las ventas pueden beneficiarse de espacios
privilegiados, campañas y otras facilidades que sólo un servicio como el de olist puede
ofrecer.
''')
if session_state.Session is True:
if LogOut.button('LogOut'):
session_state.Session = False
st.experimental_rerun()
st.header('Tu historial de reviews')
Summary_Rev, Product_Detail = st.beta_columns(2)
with Summary_Rev:
user_Rev = mt.get_UserRev(userName)
gb = GridOptionsBuilder.from_dataframe(user_Rev)
cellsytle_jscode = JsCode("""
function(params) {
if (params.value == 'A') {
return {
'color': 'white',
'backgroundColor': 'darkred'
}
} else {
return {
'color': 'black',
'backgroundColor': 'white'
}
}
};
""")
]
# Klemperer 1996 p227
# df.loc[[0], ['measure', 'costs', 'revenue']] = ['reforest', 150, 0]
# df.loc[[10], ['measure', 'costs', 'revenue']] = ['precommercial thinning', 50, 0]
# df.loc[[20], ['measure', 'costs', 'revenue']] = ['thinning', 0, 300]
# df.loc[[40], ['measure', 'costs', 'revenue']] = ['harvest and land sale', 0, 3500]
# Bullard & Straka 2011. Basic Concepts in Forest Valuation and Investment Analysis Basic Concepts in Forest Valuation and Investment Analysis
# Section 4. Financial criteria – page 4.20
# df.loc[[0], ['measure', 'costs', 'revenue']] = ['reforest', 95, 0]
# df.loc[[15], ['measure', 'costs', 'revenue']] = ['precommercial thinning', 0, 550]
# df.loc[[25], ['measure', 'costs', 'revenue']] = ['thinning', 0, 1500]
# df.loc[[35], ['measure', 'costs', 'revenue']] = ['harvest and land sale', 0, 3350]
gb = GridOptionsBuilder(min_column_width=50, editable_columns=True)
gb.build_columnsDefs_from_dataframe(df)
# gb.enableSideBar()
gridOptions = gb.build()
returned_df = AgGrid(df, gridOptions=gridOptions)
# TODO double use triggers copy warning
returned_df['costs_yearly'] = 0
returned_df['costs_yearly'][1:] = yearly_costs
returned_df['revenue_yearly'] = 0
returned_df['revenue_yearly'][1:] = yearly_revenue
# Set initial result
returned_df['result'] = returned_df['revenue'] + returned_df['revenue_yearly'] \
- returned_df['costs'] - returned_df['costs_yearly']
