def test_customjstransform_from_py_func_no_args():
def cosine():
from pscript import window
return window.Math.cos(x) # noqa
def v_cosine():
from pscript import window
return [window.Math.cos(x) for x in xs] # noqa
transform = CustomJSTransform.from_py_func(cosine, v_cosine)
js_code = pscript.py2js(cosine, 'transformer')
function_wrapper = transform.func.replace(js_code, '')
assert function_wrapper == "return transformer();\n"
v_js_code = pscript.py2js(v_cosine, 'transformer')
v_function_wrapper = transform.v_func.replace(v_js_code, '')
assert v_function_wrapper == "return transformer();\n"
def test_customjstransform_from_py_func_no_args():
def cosine():
from pscript import window
return window.Math.cos(x) # noqa
def v_cosine():
from pscript import window
return [window.Math.cos(x) for x in xs] # noqa
transform = CustomJSTransform.from_py_func(cosine, v_cosine)
js_code = pscript.py2js(cosine, 'transformer')
function_wrapper = transform.func.replace(js_code, '')
assert function_wrapper == "return transformer();\n"
v_js_code = pscript.py2js(v_cosine, 'transformer')
v_function_wrapper = transform.v_func.replace(v_js_code, '')
assert v_function_wrapper == "return transformer();\n"
def test_customjstransform_from_py_func_with_args():
slider = Slider()
def cosine(foo=slider):
from flexx.pyscript import window
return window.Math.cos(x) # noqa
def v_cosine(foo=slider):
from flexx.pyscript import window
return [window.Math.cos(x) for x in xs] # noqa
transform = CustomJSTransform.from_py_func(cosine, v_cosine)
assert transform.args['foo'] is slider
js_code = flexx.pyscript.py2js(cosine, 'transformer')
function_wrapper = transform.func.replace(js_code, '')
assert function_wrapper == "return transformer(foo);\n"
v_js_code = flexx.pyscript.py2js(v_cosine, 'transformer')
v_function_wrapper = transform.v_func.replace(v_js_code, '')
assert v_function_wrapper == "return transformer(foo);\n"
def test_customjstransform_from_py_func_with_args():
slider = Slider()
def cosine(foo=slider):
from flexx.pyscript import window
return window.Math.cos(x) # noqa
def v_cosine(foo=slider):
from flexx.pyscript import window
return [window.Math.cos(x) for x in xs] # noqa
transform = CustomJSTransform.from_py_func(cosine, v_cosine)
assert transform.args['foo'] is slider
js_code = flexx.pyscript.py2js(cosine, 'transformer')
function_wrapper = transform.func.replace(js_code, '')
assert function_wrapper == "return transformer(foo);\n"
v_js_code = flexx.pyscript.py2js(v_cosine, 'transformer')
v_function_wrapper = transform.v_func.replace(v_js_code, '')
assert v_function_wrapper == "return transformer(foo);\n"
def test_customjstransform_bad_pyfunc_formats():
def foo():
pass
def has_positional_arg(x):
return None
with pytest.raises(ValueError):
CustomJSTransform.from_py_func(has_positional_arg, foo)
def has_positional_arg_with_kwargs(y, x=5):
return None
with pytest.raises(ValueError):
CustomJSTransform.from_py_func(has_positional_arg_with_kwargs, foo)
def has_non_Model_keyword_argument(x=10):
return None
with pytest.raises(ValueError):
CustomJSTransform.from_py_func(has_non_Model_keyword_argument, foo)
def test_customjstransform_bad_pyfunc_formats():
def foo():
pass
def has_positional_arg(x):
return None
with pytest.raises(ValueError):
CustomJSTransform.from_py_func(has_positional_arg, foo)
def has_positional_arg_with_kwargs(y, x=5):
return None
with pytest.raises(ValueError):
CustomJSTransform.from_py_func(has_positional_arg_with_kwargs, foo)
def has_non_Model_keyword_argument(x=10):
return None
with pytest.raises(ValueError):
CustomJSTransform.from_py_func(has_non_Model_keyword_argument, foo)
def index():
df = pd.read_csv('static/data/df.csv')
df_group = pd.read_csv('static/data/df_group.csv')
df_group_agg = pd.read_csv('static/data/df_group_agg.csv')
df_profit = pd.read_csv('static/data/df_profit.csv')
df_profit_pred_comp = pd.read_csv('static/data/df_profit_pred_comp.csv')
df_profit_formatted = pd.read_csv('static/data/df_profit_formatted.csv')
df_profit_pred_comp_formatted = pd.read_csv(
'static/data/df_profit_pred_comp_formatted.csv')
df_price_chg = pd.read_csv('static/data/df_price_chg.csv')
df_price_chg_formatted = pd.read_csv(
'static/data/df_price_chg_formatted.csv')
profit_columns = map(lambda x: {"title": x}, df_profit_formatted.columns)
profit_dataset = df_profit_formatted.values.tolist()
profit_pred_columns = map(lambda x: {"title": x},
df_profit_pred_comp_formatted.columns)
profit_pred_dataset = df_profit_pred_comp_formatted.values.tolist()
df_scatter = pd.concat([df_profit, df_profit_pred_comp, df_price_chg],
axis=1)
df_scatter = df_scatter.loc[:, ~df_scatter.columns.duplicated()]
scatter_variables = map(lambda x: {"text": x}, [
c for c in df_scatter.columns if isinstance(df_scatter[c][0], Number)
])
id_name = u'股票简称'
# draw plots
# create mappers
palette.reverse()
color_mapper = LinearColorMapper(palette=palette, low=-50, high=50)
def func():
return x
def v_func():
return [(x * 100).toFixed(2) + '%' for x in xs]
label_formatter = CustomJSTransform.from_py_func(func=func, v_func=v_func)
price_chg_5d = price_chg_plot(df,
'PCT_CHG_PER-5-DAY',
'SEC_NAME',
'上证流通全收益',
color_mapper,
label_formatter,
title_text='近5天涨幅%')
price_chg_5d_script, price_chg_5d_div = components(price_chg_5d)
price_chg_10d = price_chg_plot(df,
'PCT_CHG_PER-10-DAY',
'SEC_NAME',
'上证流通全收益',
color_mapper,
label_formatter,
title_text='近10天涨幅%')
price_chg_10d_script, price_chg_10d_div = components(price_chg_10d)
price_chg_1m = price_chg_plot(df,
'PCT_CHG_PER-1-MONTH',
'SEC_NAME',
'上证流通全收益',
color_mapper,
label_formatter,
title_text='近1个月涨幅%')
price_chg_1m_script, price_chg_1m_div = components(price_chg_1m)
price_chg_3m = price_chg_plot(df,
'PCT_CHG_PER-3-MONTH',
'SEC_NAME',
'上证流通全收益',
color_mapper,
label_formatter,
title_text='近3个月涨幅%')
price_chg_3m_script, price_chg_3m_div = components(price_chg_3m)
price_chg_6m = price_chg_plot(df,
'PCT_CHG_PER-6-MONTH',
'SEC_NAME',
'上证流通全收益',
color_mapper,
label_formatter,
title_text='近6个月涨幅%')
price_chg_6m_script, price_chg_6m_div = components(price_chg_6m)
price_chg_12m = price_chg_plot(df,
'PCT_CHG_PER-12-MONTH',
'SEC_NAME',
'上证流通全收益',
color_mapper,
label_formatter,
title_text='近12个月涨幅%')
price_chg_12m_script, price_chg_12m_div = components(price_chg_12m)
chart_grid = gridplot([[price_chg_5d, price_chg_10d, price_chg_1m],
[price_chg_3m, price_chg_6m, price_chg_12m]])
chart_grid_script, chart_grid_div = components(chart_grid)
return render_template("index.html",
price_chg_5d_div=price_chg_5d_div,
price_chg_5d_script=price_chg_5d_script,
price_chg_10d_div=price_chg_10d_div,
price_chg_10d_script=price_chg_10d_script,
price_chg_1m_div=price_chg_1m_div,
price_chg_1m_script=price_chg_1m_script,
price_chg_3m_div=price_chg_3m_div,
price_chg_3m_script=price_chg_3m_script,
price_chg_6m_div=price_chg_6m_div,
price_chg_6m_script=price_chg_6m_script,
price_chg_12m_div=price_chg_12m_div,
price_chg_12m_script=price_chg_12m_script,
chart_grid_script=chart_grid_script,
chart_grid_div=chart_grid_div,
profit_columns=profit_columns,
profit_dataset=profit_dataset,
profit_pred_columns=profit_pred_columns,
profit_pred_dataset=profit_pred_dataset,
scatter_variables=scatter_variables,
id_name=id_name,
scatter_data=df_scatter.to_json(orient='records'))