def _valid_update_width_kwargs():
vkwargs = {
'ohlc_ticksize' : { 'Default' : None,
'Description' : 'length of horizontal open/close tickmarks on ohlc bars',
'Validator' : lambda value: isinstance(value,(float,int)) },
'ohlc_linewidth' : { 'Default' : None,
'Description' : 'width (thickness) of ohlc bars',
'Validator' : lambda value: isinstance(value,(float,int)) },
'volume_width' : { 'Default' : None,
'Description' : 'width of volume bars',
'Validator' : lambda value: isinstance(value,(float,int)) },
'volume_linewidth' : { 'Default' : None,
'Description' : 'width of edges of volume bars',
'Validator' : lambda value: isinstance(value,(float,int)) },
'candle_width' : { 'Default' : None,
'Description' : 'width of candles',
'Validator' : lambda value: isinstance(value,(float,int)) },
'candle_linewidth' : { 'Default' : None,
'Description' : 'width of candle edges and wicks',
'Validator' : lambda value: isinstance(value,(float,int)) },
'line_width' : { 'Default' : None,
'Description' : 'width of lines (for line plots and moving averages)',
'Validator' : lambda value: isinstance(value,(float,int)) },
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_update_width_kwargs():
vkwargs = {
'ohlc_ticksize': {
'Default': None,
'Validator': lambda value: isinstance(value, (float, int))
},
'ohlc_linewidth': {
'Default': None,
'Validator': lambda value: isinstance(value, (float, int))
},
'volume_width': {
'Default': None,
'Validator': lambda value: isinstance(value, (float, int))
},
'volume_linewidth': {
'Default': None,
'Validator': lambda value: isinstance(value, (float, int))
},
'candle_width': {
'Default': None,
'Validator': lambda value: isinstance(value, (float, int))
},
'candle_linewidth': {
'Default': None,
'Validator': lambda value: isinstance(value, (float, int))
},
'line_width': {
'Default': None,
'Validator': lambda value: isinstance(value, (float, int))
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_addplot_kwargs():
valid_linestyles = ['-','solid','--','dashed','-.','dashdot','.','dotted',None,' ','']
vkwargs = {
'scatter' : { 'Default' : False,
'Validator' : lambda value: isinstance(value,bool) },
'panel' : { 'Default' : 'main',
'Validator' : lambda value: value in ['main','lower'] },
'marker' : { 'Default' : 'o',
'Validator' : lambda value: not isinstance(value,bool) },
'markersize' : { 'Default' : 18,
'Validator' : lambda value: isinstance(value,(int,float)) },
'color' : { 'Default' : None,
'Validator' : lambda value: mcolors.is_color_like(value) },
'linestyle' : { 'Default' : None,
'Validator' : lambda value: value in valid_linestyles },
'secondary_y' : { 'Default' : 'auto',
'Validator' : lambda value: isinstance(value,bool) or value == 'auto' }
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_pointnfig_kwargs():
'''
Construct and return the "valid pointnfig kwargs table" for the mplfinance.plot(type='pnf')
function. A valid kwargs table is a `dict` of `dict`s. The keys of the outer dict are
the valid key-words for the function. The value for each key is a dict containing 2
specific keys: "Default", and "Validator" with the following values:
"Default" - The default value for the kwarg if none is specified.
"Validator" - A function that takes the caller specified value for the kwarg,
and validates that it is the correct type, and (for kwargs with
a limited set of allowed values) may also validate that the
kwarg value is one of the allowed values.
'''
vkwargs = {
'box_size': {
'Default':
'atr',
'Validator':
lambda value: isinstance(value, (float, int)) or value == 'atr'
},
'atr_length': {
'Default': 14,
'Validator': lambda value: isinstance(value, int)
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_addplot_kwargs():
valid_linestyles = ('-','solid','--','dashed','-.','dashdot','.','dotted',None,' ','')
valid_types = ('line','scatter','bar', 'ohlc', 'candle')
vkwargs = {
'scatter' : { 'Default' : False,
'Validator' : lambda value: isinstance(value,bool) },
'type' : { 'Default' : 'line',
'Validator' : lambda value: value in valid_types },
'mav' : { 'Default' : None,
'Validator' : _mav_validator },
'panel' : { 'Default' : 0,
'Validator' : lambda value: _valid_panel_id(value) },
'marker' : { 'Default' : 'o',
'Validator' : lambda value: _bypass_kwarg_validation(value) },
'markersize' : { 'Default' : 18,
'Validator' : lambda value: isinstance(value,(int,float)) },
'color' : { 'Default' : None,
'Validator' : lambda value: mcolors.is_color_like(value) or
(isinstance(value,(list,tuple,np.ndarray)) and all([mcolors.is_color_like(v) for v in value])) },
'linestyle' : { 'Default' : None,
'Validator' : lambda value: value in valid_linestyles },
'width' : { 'Default' : None, # width of `bar` or `line`
'Validator' : lambda value: isinstance(value,(int,float)) or
all([isinstance(v,(int,float)) for v in value]) },
'bottom' : { 'Default' : 0, # bottom for `type=bar` plots
'Validator' : lambda value: isinstance(value,(int,float)) or
all([isinstance(v,(int,float)) for v in value]) },
'alpha' : { 'Default' : 1, # alpha of `bar`, `line`, or `scatter`
'Validator' : lambda value: isinstance(value,(int,float)) or
all([isinstance(v,(int,float)) for v in value]) },
'secondary_y' : { 'Default' : 'auto',
'Validator' : lambda value: isinstance(value,bool) or value == 'auto' },
'y_on_right' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,bool) },
'ylabel' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,str) },
'ylim' : {'Default' : None,
'Validator' : lambda value: isinstance(value, (list,tuple)) and len(value) == 2
and all([isinstance(v,(int,float)) for v in value])},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_make_mpf_style_kwargs():
vkwargs = {
'base_mpf_style': {
'Default': None,
'Validator': lambda value: value in _styles.keys()
},
'base_mpl_style': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
}, # and is in plt.style.available
'marketcolors': {
'Default': None, #
'Validator': lambda value: isinstance(value, dict)
},
'mavcolors': {
'Default': None,
'Validator': lambda value: isinstance(value, list)
}, # TODO: all([mcolors.is_color_like(v) for v in value.values()])
'facecolor': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
},
'edgecolor': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
},
'figcolor': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
},
'gridcolor': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
},
'gridstyle': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
},
'gridaxis': {
'Default':
None,
'Validator':
lambda value: value in [
'vertical'[0:len(value)], 'horizontal'[0:len(value)], 'both'[
0:len(value)]
]
},
'y_on_right': {
'Default': None,
'Validator': lambda value: isinstance(value, bool)
},
'rc': {
'Default': None,
'Validator': lambda value: isinstance(value, dict)
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_make_marketcolors_kwargs():
vkwargs = {
'up': {
'Default': None,
'Validator': lambda value: mcolors.is_color_like(value)
},
'down': {
'Default': None,
'Validator': lambda value: mcolors.is_color_like(value)
},
'alpha': {
'Default':
None,
'Validator':
lambda value:
(isinstance(value, float) and 0.0 <= value and 1.0 >= value)
},
'edge': {
'Default': None,
'Validator': lambda value: _valid_mpf_color_spec(value)
},
'wick': {
'Default':
None,
'Validator':
lambda value: isinstance(value, dict) or isinstance(value, str) or
mcolors.is_color_like(value)
},
'ohlc': {
'Default':
None,
'Validator':
lambda value: isinstance(value, dict) or isinstance(value, str) or
mcolors.is_color_like(value)
},
'volume': {
'Default':
None,
'Validator':
lambda value: isinstance(value, dict) or isinstance(value, str) or
mcolors.is_color_like(value)
},
'vcdopcod': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'inherit': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'base_mpf_style': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_scale_width_kwargs():
vkwargs = {
'ohlc' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,(float,int)) },
'volume' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,(float,int)) },
'candle' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,(float,int)) },
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_addplot_kwargs():
valid_linestyles = [
"-",
"solid",
"--",
"dashed",
"-.",
"dashdot",
".",
"dotted",
None,
" ",
"",
]
vkwargs = {
"scatter": {
"Default": False,
"Validator": lambda value: isinstance(value, bool),
},
"panel": {
"Default": "main",
"Validator": lambda value: value in ["main", "lower"],
},
"marker": {
"Default": "o",
"Validator": lambda value: _bypass_kwarg_validation(value),
},
"markersize": {
"Default": 18,
"Validator": lambda value: isinstance(value, (int, float)),
},
"color": {
"Default": None,
"Validator": lambda value: mcolors.is_color_like(value),
},
"linestyle": {
"Default": None,
"Validator": lambda value: value in valid_linestyles,
},
"secondary_y": {
"Default": "auto",
"Validator":
lambda value: isinstance(value, bool) or value == "auto",
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_lines_kwargs():
'''
Construct and return the "valid lines (hlines,vlines,alines,tlines) kwargs table"
for the mplfinance.plot() `[h|v|a|t]lines=` kwarg functions.
A valid kwargs table is a `dict` of `dict`s. The keys of the outer dict are
the valid key-words for the function. The value for each key is a dict containing 2
specific keys: "Default", and "Validator" with the following values:
"Default" - The default value for the kwarg if none is specified.
"Validator" - A function that takes the caller specified value for the kwarg,
and validates that it is the correct type, and (for kwargs with
a limited set of allowed values) may also validate that the
kwarg value is one of the allowed values.
'''
valid_linestyles = ['-','solid','--','dashed','-.','dashdot',':','dotted',None,' ','']
vkwargs = {
'hlines' : { 'Default' : None,
'Validator' : _bypass_kwarg_validation },
'vlines' : { 'Default' : None,
'Validator' : _bypass_kwarg_validation },
'alines' : { 'Default' : None,
'Validator' : _bypass_kwarg_validation },
'tlines' : { 'Default' : None,
'Validator' : _bypass_kwarg_validation },
'colors' : { 'Default' : None,
'Validator' : lambda value: value is None or
mcolors.is_color_like(value) or
( isinstance(value,(list,tuple)) and
all([mcolors.is_color_like(v) for v in value]) ) },
'linestyle' : { 'Default' : '-',
'Validator' : lambda value: value is None or value in valid_linestyles },
'linewidths': { 'Default' : None,
'Validator' : lambda value: value is None or
isinstance(value,(float,int)) or
all([isinstance(v,(float,int)) for v in value]) },
'alpha' : { 'Default' : 1.0,
'Validator' : lambda value: isinstance(value,(float,int)) },
'tline_use' : { 'Default' : 'close',
'Validator' : lambda value: isinstance(value,str) or (isinstance(value,(list,tuple)) and
all([isinstance(v,str) for v in value]) ) },
'tline_method': { 'Default' : 'point-to-point',
'Validator' : lambda value: value in ['point-to-point','least-squares'] }
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_make_mpf_style_kwargs():
vkwargs = {
'base_mpf_style': { 'Default' : None,
'Description' : 'mplfinance style to use as base of new mplfinance style',
'Validator' : lambda value: value in _styles.keys() },
'base_mpl_style': { 'Default' : None,
'Description' : 'matplotlib style to use as base of new mplfinance style',
'Validator' : lambda value: isinstance(value,str) }, # and is in plt.style.available
'marketcolors' : { 'Default' : None,
'Description' : 'market colors object, from `mpf.make_market_colors()`',
'Validator' : lambda value: isinstance(value,dict) },
'mavcolors' : { 'Default' : None,
'Description' : 'sequence of colors to use for moving averages',
'Validator' : lambda value: isinstance(value,list) }, # TODO: all([_mpf_is_color_like(v) for v in value.values()])
'facecolor' : { 'Default' : None,
'Description' : 'background color for Axes',
'Validator' : lambda value: isinstance(value,str) },
'edgecolor' : { 'Default' : None,
'Description' : 'edge color for Axes',
'Validator' : lambda value: isinstance(value,str) },
'figcolor' : { 'Default' : None,
'Description' : 'background color for Figure.',
'Validator' : lambda value: isinstance(value,str) },
'gridcolor' : { 'Default' : None,
'Description' : 'color for grid lines',
'Validator' : lambda value: isinstance(value,str) },
'gridstyle' : { 'Default' : None,
'Description' : "grid line style ('-', '--', '-.', ':', '', offset, on-off-seq)."+
" (see also: https://matplotlib.org/stable/gallery/lines_bars_and_markers/linestyles.html)",
'Validator' : lambda value: isinstance(value,str) },
'gridaxis' : { 'Default' : None,
'Description' : "grid lines 'vertical', 'horizontal', or 'both'",
'Validator' : lambda value: value in [ 'vertical'[0:len(value)], 'horizontal'[0:len(value)], 'both'[0:len(value)] ] },
'y_on_right' : { 'Default' : None,
'Description' : 'True|False primary Axes y-ticks and labels on right.',
'Validator' : lambda value: isinstance(value,bool) },
'rc' : { 'Default' : None,
'Description' : 'rcparams overrides (dict) (all other rcparams unchanged)',
'Validator' : lambda value: isinstance(value,dict) },
'legacy_rc' : { 'Default' : None, # Just in case someone depended upon old behavior
'Description' : 'rcparams to set (dict) (all other rcparams cleared)',
'Validator' : lambda value: isinstance(value,dict) },
'style_name' : { 'Default' : None,
'Description' : 'name for this style; useful when calling `mpf.write_style_file(style,filename)`',
'Validator' : lambda value: isinstance(value,str) },
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_make_marketcolors_kwargs():
vkwargs = {
'up' : { 'Default' : None,
'Description' : 'color to indicate up',
'Validator' : lambda value: _mpf_is_color_like(value) },
'down' : { 'Default' : None,
'Description' : 'color to indicate down',
'Validator' : lambda value: _mpf_is_color_like(value) },
'hollow' : { 'Default' : None,
'Description' : "color for hollow candles (for `type=hollow`)",
'Validator' : lambda value: _mpf_is_color_like(value) },
'alpha' : { 'Default' : None,
'Description' : 'opacity 0.0 (transparent) to 1.0 (opaque);'+
' applies to candles,renko,pnf (but not ohlc bars)',
'Validator' : lambda value: (isinstance(value,float)
and 0.0 <= value and 1.0 >= value ) },
'edge' : { 'Default' : None,
'Description' : 'color of candle edge; may also be "i" or "inherit"'+
' to take color from base_mpf_style',
'Validator' : lambda value: _valid_mpf_color_spec(value) },
'wick' : { 'Default' : None,
'Description' : "color of candle wick; may be single color,"+
" or may be dict with keys 'up' and 'down'",
'Validator' : lambda value: isinstance(value,dict)
or isinstance(value,str)
or _mpf_is_color_like(value) },
'ohlc' : { 'Default' : None,
'Description' : "color of ohlc bars; may be single color,"+
" or may be dict with keys 'up' and 'down'",
'Validator' : lambda value: isinstance(value,dict)
or isinstance(value,str)
or _mpf_is_color_like(value) },
'volume' : { 'Default' : None,
'Description' : "color of volume bars; may be single color,"+
" or may be dict with keys 'up' and 'down'",
'Validator' : lambda value: isinstance(value,dict)
or isinstance(value,str)
or _mpf_is_color_like(value) },
'vcdopcod' : { 'Default' : False,
'Description' : 'True/False volume color depends on price change from previous day',
'Validator' : lambda value: isinstance(value,bool) },
'inherit' : { 'Default' : False,
'Description' : 'inherit color from base_mpf_style for: edge,volume,ohlc,wick',
'Validator' : lambda value: isinstance(value,bool) },
'base_mpf_style': { 'Default' : None,
'Description' : 'mplfinance style market colors as basis for new market colors object',
'Validator' : lambda value: isinstance(value,str) },
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_plot_kwargs():
'''
Construct and return the "valid kwargs table" for the mplfinance.plot() function.
A valid kwargs table is a `dict` of `dict`s. The keys of the outer dict are the
valid key-words for the function. The value for each key is a dict containing
2 specific keys: "Default", and "Validator" with the following values:
"Default" - The default value for the kwarg if none is specified.
"Validator" - A function that takes the caller specified value for the kwarg,
and validates that it is the correct type, and (for kwargs with
a limited set of allowed values) may also validate that the
kwarg value is one of the allowed values.
'''
vkwargs = {
'type': {
'Default':
'ohlc',
'Validator':
lambda value: value in
['candle', 'candlestick', 'ohlc', 'bars', 'ohlc_bars', 'line']
},
'style': {
'Default':
'default',
'Validator':
lambda value: value in _styles.available_styles() or isinstance(
value, dict)
},
'volume': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'mav': {
'Default': None,
'Validator': _mav_validator
},
'study': {
'Default': None,
#'Validator' : lambda value: isinstance(value,dict) }, #{'studyname': {study parms}} example: {'TE':{'mav':20,'upper':2,'lower':2}}
'Validator': lambda value: _kwarg_not_implemented(value)
},
'marketcolors': {
'Default': None, # use 'style' for default, instead.
'Validator': lambda value: isinstance(value, dict)
},
'no_xgaps': {
'Default': True, # None means follow default logic below:
'Validator': lambda value: _warn_no_xgaps_deprecated(value)
},
'show_nontrading': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'figscale': {
'Default':
1.0, # scale base figure size up or down.
'Validator':
lambda value: isinstance(value, float) or isinstance(value, int)
},
'figratio': {
'Default':
(8.00,
5.75), # aspect ratio; will equal fig size when figscale=1.0
'Validator':
lambda value: isinstance(value,
(tuple, list)) and len(value) == 2 and
isinstance(value[0],
(float, int)) and isinstance(value[1], (float, int))
},
'linecolor': {
'Default': 'k', # line color in line plot
'Validator': lambda value: mcolors.is_color_like(value)
},
'title': {
'Default': None, # Plot Title
'Validator': lambda value: isinstance(value, str)
},
'ylabel': {
'Default': 'Price', # y-axis label
'Validator': lambda value: isinstance(value, str)
},
'ylabel_lower': {
'Default': None, # y-axis label default logic below
'Validator': lambda value: isinstance(value, str)
},
#'xlabel' : { 'Default' : None, # x-axis label, default is None because obvious it's time or date
# 'Validator' : lambda value: isinstance(value,str) },
'addplot': {
'Default':
None,
'Validator':
lambda value: isinstance(value, dict) or (isinstance(
value, list) and all([isinstance(d, dict) for d in value]))
},
'savefig': {
'Default':
None,
'Validator':
lambda value: isinstance(value, dict) or isinstance(value, str) or
isinstance(value, io.BytesIO)
},
'block': {
'Default': True,
'Validator': lambda value: isinstance(value, bool)
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_plot_kwargs():
'''
Construct and return the "valid kwargs table" for the mplfinance.plot() function.
A valid kwargs table is a `dict` of `dict`s. The keys of the outer dict are the
valid key-words for the function. The value for each key is a dict containing
2 specific keys: "Default", and "Validator" with the following values:
"Default" - The default value for the kwarg if none is specified.
"Validator" - A function that takes the caller specified value for the kwarg,
and validates that it is the correct type, and (for kwargs with
a limited set of allowed values) may also validate that the
kwarg value is one of the allowed values.
'''
vkwargs = {
'columns' : { 'Default' : None, # use default names: ('Open', 'High', 'Low', 'Close', 'Volume')
'Validator' : lambda value: isinstance(value, (tuple, list))
and len(value) == 5
and all(isinstance(c, str) for c in value) },
'type' : { 'Default' : 'ohlc',
'Validator' : lambda value: value in _get_valid_plot_types() },
'style' : { 'Default' : None,
'Validator' : _styles._valid_mpf_style },
'volume' : { 'Default' : False,
'Validator' : lambda value: isinstance(value,bool) or isinstance(value,mpl_axes.Axes) },
'mav' : { 'Default' : None,
'Validator' : _mav_validator },
'renko_params' : { 'Default' : dict(),
'Validator' : lambda value: isinstance(value,dict) },
'pnf_params' : { 'Default' : dict(),
'Validator' : lambda value: isinstance(value,dict) },
'study' : { 'Default' : None,
'Validator' : lambda value: _kwarg_not_implemented(value) },
'marketcolors' : { 'Default' : None, # use 'style' for default, instead.
'Validator' : lambda value: isinstance(value,dict) },
'no_xgaps' : { 'Default' : True, # None means follow default logic below:
'Validator' : lambda value: _warn_no_xgaps_deprecated(value) },
'show_nontrading' : { 'Default' : False,
'Validator' : lambda value: isinstance(value,bool) },
'figscale' : { 'Default' : None, # scale base figure size up or down.
'Validator' : lambda value: isinstance(value,float) or isinstance(value,int) },
'figratio' : { 'Default' : None, # aspect ratio; scaled to 8.0 height
'Validator' : lambda value: isinstance(value,(tuple,list))
and len(value) == 2
and isinstance(value[0],(float,int))
and isinstance(value[1],(float,int)) },
'figsize' : { 'Default' : None, # figure size; overrides figratio and figscale
'Validator' : lambda value: isinstance(value,(tuple,list))
and len(value) == 2
and isinstance(value[0],(float,int))
and isinstance(value[1],(float,int)) },
'linecolor' : { 'Default' : None, # line color in line plot
'Validator' : lambda value: mcolors.is_color_like(value) },
'title' : { 'Default' : None, # Figure Title
'Validator' : lambda value: isinstance(value,(str,dict)) },
'axtitle' : { 'Default' : None, # Axes Title (subplot title)
'Validator' : lambda value: isinstance(value,str) },
'ylabel' : { 'Default' : 'Price', # y-axis label
'Validator' : lambda value: isinstance(value,str) },
'ylabel_lower' : { 'Default' : None, # y-axis label default logic below
'Validator' : lambda value: isinstance(value,str) },
'addplot' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,dict) or (isinstance(value,list) and all([isinstance(d,dict) for d in value])) },
'savefig' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,dict) or isinstance(value,str) or isinstance(value, io.BytesIO) },
'block' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,bool) },
'returnfig' : { 'Default' : False,
'Validator' : lambda value: isinstance(value,bool) },
'return_calculated_values' : {'Default' : None,
'Validator' : lambda value: isinstance(value, dict) and len(value) == 0},
'set_ylim' : {'Default' : None,
'Validator' : lambda value: _warn_set_ylim_deprecated(value) },
'ylim' : {'Default' : None,
'Validator' : lambda value: isinstance(value, (list,tuple)) and len(value) == 2
and all([isinstance(v,(int,float)) for v in value])},
'xlim' : {'Default' : None,
'Validator' : lambda value: isinstance(value, (list,tuple)) and len(value) == 2
and all([isinstance(v,(int,float)) for v in value])},
'set_ylim_panelB' : {'Default' : None,
'Validator' : lambda value: _warn_set_ylim_deprecated(value) },
'hlines' : { 'Default' : None,
'Validator' : lambda value: _hlines_validator(value) },
'vlines' : { 'Default' : None,
'Validator' : lambda value: _vlines_validator(value) },
'alines' : { 'Default' : None,
'Validator' : lambda value: _alines_validator(value) },
'tlines' : { 'Default' : None,
'Validator' : lambda value: _tlines_validator(value) },
'panel_ratios' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,(tuple,list)) and len(value) <= 10 and
all([isinstance(v,(int,float)) for v in value]) },
'main_panel' : { 'Default' : 0,
'Validator' : lambda value: _valid_panel_id(value) },
'volume_panel' : { 'Default' : 1,
'Validator' : lambda value: _valid_panel_id(value) },
'num_panels' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,int) and value in range(1,10+1) },
'datetime_format' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,str) },
'xrotation' : { 'Default' : 45,
'Validator' : lambda value: isinstance(value,(int,float)) },
'axisoff' : { 'Default' : False,
'Validator' : lambda value: isinstance(value,bool) },
'closefig' : { 'Default' : 'auto',
'Validator' : lambda value: isinstance(value,bool) },
'fill_between' : { 'Default' : None,
'Validator' : lambda value: _num_or_seq_of_num(value) or
(isinstance(value,dict) and 'y1' in value and
_num_or_seq_of_num(value['y1'])) },
'tight_layout' : { 'Default' : False,
'Validator' : lambda value: isinstance(value,bool) },
'width_adjuster_version' : { 'Default' : 'v1',
'Validator' : lambda value: value in ('v0', 'v1') },
'scale_width_adjustment' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,dict) and len(value) > 0 },
'update_width_config' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,dict) and len(value) > 0 },
'return_width_config' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,dict) and len(value)==0 },
'saxbelow' : { 'Default' : True, # Issue#115 Comment#639446764
'Validator' : lambda value: isinstance(value,bool) },
'scale_padding' : { 'Default' : 1.0, # Issue#193
'Validator' : lambda value: _scale_padding_validator(value) },
'ax' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,mpl_axes.Axes) },
'volume_exponent' : { 'Default' : None,
'Validator' : lambda value: isinstance(value,int) or value == 'legacy'},
'tz_localize' : { 'Default' : True,
'Validator' : lambda value: isinstance(value,bool) },
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_plot_kwargs():
'''
Construct and return the "valid kwargs table" for the mplfinance.plot() function.
A valid kwargs table is a `dict` of `dict`s. The keys of the outer dict are the
valid key-words for the function. The value for each key is a dict containing
2 specific keys: "Default", and "Validator" with the following values:
"Default" - The default value for the kwarg if none is specified.
"Validator" - A function that takes the caller specified value for the kwarg,
and validates that it is the correct type, and (for kwargs with
a limited set of allowed values) may also validate that the
kwarg value is one of the allowed values.
'''
vkwargs = {
'columns': {
'Default': ('Open', 'High', 'Low', 'Close', 'Volume'),
'Validator':
lambda value: isinstance(value, (tuple, list)) and len(value) == 5
and all(isinstance(c, str) for c in value)
},
'type': {
'Default':
'ohlc',
'Validator':
lambda value: value in ('candle', 'candlestick', 'ohlc',
'ohlc_bars', 'line', 'renko', 'pnf')
},
'style': {
'Default':
'default',
'Validator':
lambda value: value in _styles.available_styles() or isinstance(
value, dict)
},
'volume': {
'Default':
False,
'Validator':
lambda value: isinstance(value, bool) or value in ['B', 'C']
},
'mav': {
'Default': None,
'Validator': _mav_validator
},
'renko_params': {
'Default': dict(),
'Validator': lambda value: isinstance(value, dict)
},
'pnf_params': {
'Default': dict(),
'Validator': lambda value: isinstance(value, dict)
},
'study': {
'Default': None,
'Validator': lambda value: _kwarg_not_implemented(value)
},
'marketcolors': {
'Default': None, # use 'style' for default, instead.
'Validator': lambda value: isinstance(value, dict)
},
'no_xgaps': {
'Default': True, # None means follow default logic below:
'Validator': lambda value: _warn_no_xgaps_deprecated(value)
},
'show_nontrading': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'figscale': {
'Default':
1.0, # scale base figure size up or down.
'Validator':
lambda value: isinstance(value, float) or isinstance(value, int)
},
'figratio': {
'Default':
(8.00,
5.75), # aspect ratio; will equal fig size when figscale=1.0
'Validator':
lambda value: isinstance(value,
(tuple, list)) and len(value) == 2 and
isinstance(value[0],
(float, int)) and isinstance(value[1], (float, int))
},
'linecolor': {
'Default': None, # line color in line plot
'Validator': lambda value: mcolors.is_color_like(value)
},
'title': {
'Default': None, # Plot Title
'Validator': lambda value: isinstance(value, str)
},
'ylabel': {
'Default': 'Price', # y-axis label
'Validator': lambda value: isinstance(value, str)
},
'ylabel_lower': {
'Default': None, # y-axis label default logic below
'Validator': lambda value: isinstance(value, str)
},
'addplot': {
'Default':
None,
'Validator':
lambda value: isinstance(value, dict) or (isinstance(
value, list) and all([isinstance(d, dict) for d in value]))
},
'savefig': {
'Default':
None,
'Validator':
lambda value: isinstance(value, dict) or isinstance(value, str) or
isinstance(value, io.BytesIO)
},
'block': {
'Default': True,
'Validator': lambda value: isinstance(value, bool)
},
'returnfig': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'return_calculated_values': {
'Default': None,
'Validator':
lambda value: isinstance(value, dict) and len(value) == 0
},
'set_ylim': {
'Default':
None,
'Validator':
lambda value: isinstance(value, (list, tuple)) and len(value) == 2
and all([isinstance(v, (int, float)) for v in value])
},
'set_ylim_panelB': {
'Default':
None,
'Validator':
lambda value: isinstance(value, (list, tuple)) and len(value) == 2
and all([isinstance(v, (int, float)) for v in value])
},
'set_ylim_panelC': {
'Default':
None,
'Validator':
lambda value: isinstance(value, (list, tuple)) and len(value) == 2
and all([isinstance(v, (int, float)) for v in value])
},
'hlines': {
'Default': None,
'Validator': lambda value: _hlines_validator(value)
},
'vlines': {
'Default': None,
'Validator': lambda value: _vlines_validator(value)
},
'alines': {
'Default': None,
'Validator': lambda value: _alines_validator(value)
},
'tlines': {
'Default': None,
'Validator': lambda value: _tlines_validator(value)
},
'panel_order': {
'Default':
'ABC',
'Validator':
lambda value: isinstance(value, str) and len(value) == 3 and (
('A' in value and 'B' in value and 'C' in value) or
('a' in value and 'b' in value and 'c' in value))
},
'panel_ratio': {
'Default': (5, 2, 2),
'Validator':
lambda value: isinstance(value, (tuple, list)) and len(value) == 3
and all([isinstance(v, (int, float)) for v in value])
},
'datetime_format': {
'Default': None,
'Validator': lambda value: isinstance(value, str)
},
'xrotation': {
'Default': 45,
'Validator': lambda value: isinstance(value, (int, float))
},
'axesoff': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'axesoffdark': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'closefig': {
'Default': 'auto',
'Validator': lambda value: isinstance(value, bool)
},
'yscale': {
'Default':
None,
'Validator':
lambda value: isinstance(value, str) or
(isinstance(value, dict) and 'yscale' in value)
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_addplot_kwargs():
valid_linestyles = ('-', 'solid', '--', 'dashed', '-.', 'dashdot', '.',
'dotted', None, ' ', '')
#valid_types = ('line','scatter','bar','ohlc','candle')
valid_types = ('line', 'scatter', 'bar')
vkwargs = {
'scatter': {
'Default': False,
'Validator': lambda value: isinstance(value, bool)
},
'type': {
'Default': 'line',
'Validator': lambda value: value in valid_types
},
'panel': {
'Default': 'A', # new: use 'A' for 'main', 'B' for 'lower'
'Validator': lambda value: value in
('A', 'B', 'C', 'main', 'lower')
},
'marker': {
'Default': 'o',
'Validator': lambda value: _bypass_kwarg_validation(value)
},
'markersize': {
'Default': 18,
'Validator': lambda value: isinstance(value, (int, float))
},
'color': {
'Default': None,
'Validator': lambda value: mcolors.is_color_like(value)
},
'linestyle': {
'Default': None,
'Validator': lambda value: value in valid_linestyles
},
'width': {
'Default':
0.8,
'Validator':
lambda value: isinstance(value, (int, float)) or all(
[isinstance(v, (int, float)) for v in value])
},
'bottom': {
'Default':
0,
'Validator':
lambda value: isinstance(value, (int, float)) or all(
[isinstance(v, (int, float)) for v in value])
},
'alpha': {
'Default':
1,
'Validator':
lambda value: isinstance(value, (int, float)) or all(
[isinstance(v, (int, float)) for v in value])
},
'secondary_y': {
'Default': 'auto',
'Validator':
lambda value: isinstance(value, bool) or value == 'auto'
}
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
def _valid_plot_kwargs():
"""
Construct and return the "valid kwargs table" for the mplfinance.plot() function.
A valid kwargs table is a `dict` of `dict`s. The keys of the outer dict are the
valid key-words for the function. The value for each key is a dict containing
2 specific keys: "Default", and "Validator" with the following values:
"Default" - The default value for the kwarg if none is specified.
"Validator" - A function that takes the caller specified value for the kwarg,
and validates that it is the correct type, and (for kwargs with
a limited set of allowed values) may also validate that the
kwarg value is one of the allowed values.
"""
vkwargs = {
"columns": {
"Default": ("Open", "High", "Low", "Close", "Volume"),
"Validator":
lambda value: isinstance(value, (tuple, list)) and len(value) == 5
and all(isinstance(c, str) for c in value),
},
"type": {
"Default":
"ohlc",
"Validator":
lambda value: value in [
"candle",
"candlestick",
"ohlc",
"bars",
"ohlc_bars",
"line",
"renko",
"pnf",
"p&f",
"pointnfigure",
],
},
"style": {
"Default":
"default",
"Validator":
lambda value: value in _styles.available_styles() or isinstance(
value, dict),
},
"volume": {
"Default": False,
"Validator": lambda value: isinstance(value, bool),
},
"mav": {
"Default": None,
"Validator": _mav_validator
},
"renko_params": {
"Default": dict(),
"Validator": lambda value: isinstance(value, dict),
},
"pointnfig_params": {
"Default": dict(),
"Validator": lambda value: isinstance(value, dict),
},
"study": {
"Default": None,
#'Validator' : lambda value: isinstance(value,dict) }, #{'studyname': {study parms}} example: {'TE':{'mav':20,'upper':2,'lower':2}}
"Validator": lambda value: _kwarg_not_implemented(value),
},
"marketcolors": {
"Default": None, # use 'style' for default, instead.
"Validator": lambda value: isinstance(value, dict),
},
"no_xgaps": {
"Default": True, # None means follow default logic below:
"Validator": lambda value: _warn_no_xgaps_deprecated(value),
},
"show_nontrading": {
"Default": False,
"Validator": lambda value: isinstance(value, bool),
},
"figscale": {
"Default":
1.0, # scale base figure size up or down.
"Validator":
lambda value: isinstance(value, float) or isinstance(value, int),
},
"figratio": {
"Default": (
8.00,
5.75,
), # aspect ratio; will equal fig size when figscale=1.0
"Validator":
lambda value: isinstance(value,
(tuple, list)) and len(value) == 2 and
isinstance(value[0],
(float, int)) and isinstance(value[1], (float, int)),
},
"linecolor": {
"Default": "k", # line color in line plot
"Validator": lambda value: mcolors.is_color_like(value),
},
"title": {
"Default": None, # Plot Title
"Validator": lambda value: isinstance(value, str),
},
"ylabel": {
"Default": "Price", # y-axis label
"Validator": lambda value: isinstance(value, str),
},
"ylabel_lower": {
"Default": None, # y-axis label default logic below
"Validator": lambda value: isinstance(value, str),
},
#'xlabel' : { 'Default' : None, # x-axis label, default is None because obvious it's time or date
# 'Validator' : lambda value: isinstance(value,str) },
"addplot": {
"Default":
None,
"Validator":
lambda value: isinstance(value, dict) or (isinstance(
value, list) and all([isinstance(d, dict) for d in value])),
},
"savefig": {
"Default":
None,
"Validator":
lambda value: isinstance(value, dict) or isinstance(value, str) or
isinstance(value, io.BytesIO),
},
"block": {
"Default": True,
"Validator": lambda value: isinstance(value, bool)
},
"returnfig": {
"Default": False,
"Validator": lambda value: isinstance(value, bool),
},
"return_calculated_values": {
"Default": None,
"Validator":
lambda value: isinstance(value, dict) and len(value) == 0,
},
}
_validate_vkwargs_dict(vkwargs)
return vkwargs
