268 lines
8.3 KiB
Python
268 lines
8.3 KiB
Python
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from collections.abc import Sequence
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from plotly import exceptions
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from plotly.colors import (
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DEFAULT_PLOTLY_COLORS,
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PLOTLY_SCALES,
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color_parser,
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colorscale_to_colors,
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colorscale_to_scale,
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convert_to_RGB_255,
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find_intermediate_color,
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hex_to_rgb,
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label_rgb,
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n_colors,
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unconvert_from_RGB_255,
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unlabel_rgb,
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validate_colors,
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validate_colors_dict,
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validate_colorscale,
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validate_scale_values,
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)
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def is_sequence(obj):
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return isinstance(obj, Sequence) and not isinstance(obj, str)
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def validate_index(index_vals):
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"""
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Validates if a list contains all numbers or all strings
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:raises: (PlotlyError) If there are any two items in the list whose
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types differ
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"""
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from numbers import Number
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if isinstance(index_vals[0], Number):
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if not all(isinstance(item, Number) for item in index_vals):
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raise exceptions.PlotlyError(
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"Error in indexing column. "
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"Make sure all entries of each "
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"column are all numbers or "
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"all strings."
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)
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elif isinstance(index_vals[0], str):
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if not all(isinstance(item, str) for item in index_vals):
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raise exceptions.PlotlyError(
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"Error in indexing column. "
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"Make sure all entries of each "
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"column are all numbers or "
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"all strings."
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)
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def validate_dataframe(array):
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"""
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Validates all strings or numbers in each dataframe column
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:raises: (PlotlyError) If there are any two items in any list whose
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types differ
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"""
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from numbers import Number
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for vector in array:
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if isinstance(vector[0], Number):
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if not all(isinstance(item, Number) for item in vector):
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raise exceptions.PlotlyError(
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"Error in dataframe. "
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"Make sure all entries of "
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"each column are either "
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"numbers or strings."
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)
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elif isinstance(vector[0], str):
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if not all(isinstance(item, str) for item in vector):
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raise exceptions.PlotlyError(
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"Error in dataframe. "
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"Make sure all entries of "
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"each column are either "
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"numbers or strings."
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)
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def validate_equal_length(*args):
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"""
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Validates that data lists or ndarrays are the same length.
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:raises: (PlotlyError) If any data lists are not the same length.
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"""
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length = len(args[0])
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if any(len(lst) != length for lst in args):
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raise exceptions.PlotlyError(
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"Oops! Your data lists or ndarrays " "should be the same length."
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)
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def validate_positive_scalars(**kwargs):
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"""
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Validates that all values given in key/val pairs are positive.
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Accepts kwargs to improve Exception messages.
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:raises: (PlotlyError) If any value is < 0 or raises.
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"""
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for key, val in kwargs.items():
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try:
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if val <= 0:
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raise ValueError("{} must be > 0, got {}".format(key, val))
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except TypeError:
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raise exceptions.PlotlyError("{} must be a number, got {}".format(key, val))
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def flatten(array):
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"""
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Uses list comprehension to flatten array
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:param (array): An iterable to flatten
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:raises (PlotlyError): If iterable is not nested.
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:rtype (list): The flattened list.
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"""
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try:
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return [item for sublist in array for item in sublist]
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except TypeError:
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raise exceptions.PlotlyError(
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"Your data array could not be "
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"flattened! Make sure your data is "
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"entered as lists or ndarrays!"
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)
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def endpts_to_intervals(endpts):
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"""
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Returns a list of intervals for categorical colormaps
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Accepts a list or tuple of sequentially increasing numbers and returns
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a list representation of the mathematical intervals with these numbers
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as endpoints. For example, [1, 6] returns [[-inf, 1], [1, 6], [6, inf]]
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:raises: (PlotlyError) If input is not a list or tuple
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:raises: (PlotlyError) If the input contains a string
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:raises: (PlotlyError) If any number does not increase after the
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previous one in the sequence
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"""
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length = len(endpts)
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# Check if endpts is a list or tuple
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if not (isinstance(endpts, (tuple)) or isinstance(endpts, (list))):
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raise exceptions.PlotlyError(
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"The intervals_endpts argument must "
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"be a list or tuple of a sequence "
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"of increasing numbers."
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)
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# Check if endpts contains only numbers
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for item in endpts:
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if isinstance(item, str):
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raise exceptions.PlotlyError(
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"The intervals_endpts argument "
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"must be a list or tuple of a "
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"sequence of increasing "
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"numbers."
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)
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# Check if numbers in endpts are increasing
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for k in range(length - 1):
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if endpts[k] >= endpts[k + 1]:
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raise exceptions.PlotlyError(
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"The intervals_endpts argument "
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"must be a list or tuple of a "
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"sequence of increasing "
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"numbers."
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)
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else:
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intervals = []
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# add -inf to intervals
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intervals.append([float("-inf"), endpts[0]])
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for k in range(length - 1):
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interval = []
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interval.append(endpts[k])
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interval.append(endpts[k + 1])
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intervals.append(interval)
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# add +inf to intervals
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intervals.append([endpts[length - 1], float("inf")])
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return intervals
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def annotation_dict_for_label(
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text,
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lane,
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num_of_lanes,
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subplot_spacing,
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row_col="col",
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flipped=True,
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right_side=True,
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text_color="#0f0f0f",
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):
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"""
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Returns annotation dict for label of n labels of a 1xn or nx1 subplot.
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:param (str) text: the text for a label.
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:param (int) lane: the label number for text. From 1 to n inclusive.
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:param (int) num_of_lanes: the number 'n' of rows or columns in subplot.
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:param (float) subplot_spacing: the value for the horizontal_spacing and
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vertical_spacing params in your plotly.tools.make_subplots() call.
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:param (str) row_col: choose whether labels are placed along rows or
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columns.
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:param (bool) flipped: flips text by 90 degrees. Text is printed
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horizontally if set to True and row_col='row', or if False and
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row_col='col'.
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:param (bool) right_side: only applicable if row_col is set to 'row'.
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:param (str) text_color: color of the text.
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"""
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l = (1 - (num_of_lanes - 1) * subplot_spacing) / (num_of_lanes)
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if not flipped:
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xanchor = "center"
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yanchor = "middle"
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if row_col == "col":
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x = (lane - 1) * (l + subplot_spacing) + 0.5 * l
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y = 1.03
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textangle = 0
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elif row_col == "row":
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y = (lane - 1) * (l + subplot_spacing) + 0.5 * l
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x = 1.03
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textangle = 90
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else:
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if row_col == "col":
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xanchor = "center"
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yanchor = "bottom"
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x = (lane - 1) * (l + subplot_spacing) + 0.5 * l
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y = 1.0
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textangle = 270
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elif row_col == "row":
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yanchor = "middle"
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y = (lane - 1) * (l + subplot_spacing) + 0.5 * l
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if right_side:
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x = 1.0
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xanchor = "left"
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else:
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x = -0.01
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xanchor = "right"
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textangle = 0
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annotation_dict = dict(
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textangle=textangle,
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xanchor=xanchor,
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yanchor=yanchor,
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x=x,
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y=y,
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showarrow=False,
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xref="paper",
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yref="paper",
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text=text,
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font=dict(size=13, color=text_color),
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)
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return annotation_dict
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def list_of_options(iterable, conj="and", period=True):
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"""
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Returns an English listing of objects seperated by commas ','
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For example, ['foo', 'bar', 'baz'] becomes 'foo, bar and baz'
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if the conjunction 'and' is selected.
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"""
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if len(iterable) < 2:
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raise exceptions.PlotlyError(
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"Your list or tuple must contain at least 2 items."
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)
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template = (len(iterable) - 2) * "{}, " + "{} " + conj + " {}" + period * "."
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return template.format(*iterable)
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