kopia lustrzana https://github.com/sepandhaghighi/samila
Point Colors 🌈 (#143)
* add : `DEFAULT_CMAP` added. * add : `filter_cmap` added. * edit : `cmap` added to proper functions accordingly. * add : `cmap` added to the realted methods. * log : changes logged. (#75) * add : `c` added to `plot`, now list of colors are supported. * add : `cmap` added to save and load (config and data). * fix : minor bug related to cmap always being `DEFAULT_CMAP` fixed. * change : minor change in `filter_cmap`. * fix : `str` type cmap suuport added. * add : serializing the cmap. * fix : `Colormap` issue fixed. * change : `DEFAULT_CMAP`: `viridis` --> `cm.get_cmap("viridis", 256)`. * fix : minor bugs fixed. * edit : changes are no applied on all entries of a `cmap.colors`. * add : minor tests added. * edit : minor edits in tests. * fix : minor issues in tests fixed. * add : `_serialize_color` function. * test : add few tests. * fix : trailing whitespace fixed. * test : a test added. * edit : minor edit in `filter_cmap`. * remove : `c` parameter removed. * fix : minor typo fixed.pull/146/head
Sadra Sabouri
GitHub
rodzic
9c6fbeafeb
commit
d67d69c9dd
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@ -6,6 +6,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
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## [Unreleased]
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### Changed
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- `cmap` parameter added to `plot` method
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- Random mode modified
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- Test system modified
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- `generate` method optimized
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@ -8,12 +8,15 @@ import re
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import json
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import random
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import matplotlib
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from matplotlib import cm
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from matplotlib.colors import ListedColormap
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from .params import DEFAULT_START, DEFAULT_STOP, DEFAULT_STEP, DEFAULT_COLOR, DEFAULT_IMAGE_SIZE, DEFAULT_DEPTH
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from .params import DEFAULT_CMAP, DEFAULT_CMAP_RANGE
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from .params import DEFAULT_BACKGROUND_COLOR, DEFAULT_SPOT_SIZE, DEFAULT_PROJECTION, DEFAULT_ALPHA, DEFAULT_LINEWIDTH
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from .params import Projection, VALID_COLORS, HEX_COLOR_PATTERN, NFT_STORAGE_API, NFT_STORAGE_LINK, OVERVIEW
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from .params import DATA_TYPE_ERROR, CONFIG_TYPE_ERROR, PLOT_DATA_ERROR, CONFIG_NO_STR_FUNCTION_ERROR
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from .params import NO_FIG_ERROR_MESSAGE, FIG_SAVE_SUCCESS_MESSAGE, NFT_STORAGE_SUCCESS_MESSAGE, SAVE_NO_DATA_ERROR
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from .params import INVALID_COLOR_TYPE_ERROR
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from .params import INVALID_COLOR_TYPE_ERROR, COLOR_SIZE_ERROR
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from .params import BOTH_COLOR_COMPLEMENT_WARNING, COLOR_NOT_FOUND_WARNING
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from .params import DATA_SAVE_SUCCESS_MESSAGE, SEED_LOWER_BOUND, SEED_UPPER_BOUND
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from .params import ELEMENTS_LIST, ARGUMENTS_LIST, OPERATORS_LIST, RANDOM_COEF_LIST
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@ -159,6 +162,29 @@ def filter_color(color, bgcolor):
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return color, bgcolor
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def filter_cmap(cmap):
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"""
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Filter given cmap.
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:param cmap: color map
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:type cmap: matplotlib.colors.Colormap or list of colors
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:return: filtered version of cmap
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"""
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if isinstance(cmap, str):
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cmap = cm.get_cmap(cmap, 256)
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if type(cmap) == matplotlib.colors.Colormap:
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cmap = cm.get_cmap(cmap.__getattribute__("name"))
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if isinstance(cmap, matplotlib.colors.ListedColormap):
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return cmap
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if isinstance(cmap, (matplotlib.colors.LinearSegmentedColormap)):
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cmap = cmap(range(DEFAULT_CMAP_RANGE))
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return ListedColormap(cmap)
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if isinstance(cmap, list):
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cmap = list(map(select_color, cmap))
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return ListedColormap(cmap)
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return None
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def select_color(color):
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"""
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Select color and return it.
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@ -262,6 +288,7 @@ def plot_params_filter(
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g,
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color=None,
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bgcolor=None,
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cmap=None,
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spot_size=None,
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size=None,
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projection=None,
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@ -276,6 +303,8 @@ def plot_params_filter(
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:type color: str
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:param bgcolor: background color
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:type bgcolor: str
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:param cmap: color map
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:type cmap: matplotlib.colors.Colormap or list of colors
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:param spot_size: point spot size
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:type spot_size: float
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:param size: figure size
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@ -292,7 +321,13 @@ def plot_params_filter(
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raise samilaPlotError(PLOT_DATA_ERROR.format(1))
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if g.data2 is None:
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raise samilaPlotError(PLOT_DATA_ERROR.format(2))
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color, bgcolor = filter_color(color, bgcolor)
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if isinstance(color, list):
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if len(color) != len(g.data1):
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raise samilaPlotError(COLOR_SIZE_ERROR)
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bgcolor = select_color(bgcolor)
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else:
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color, bgcolor = filter_color(color, bgcolor)
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cmap = filter_cmap(cmap)
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projection = filter_projection(projection)
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alpha = filter_float(alpha)
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linewidth = filter_float(linewidth)
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@ -302,6 +337,8 @@ def plot_params_filter(
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color = g.color
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if bgcolor is None:
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bgcolor = g.bgcolor
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if cmap is None:
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cmap = g.cmap
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if spot_size is None:
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spot_size = g.spot_size
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if size is None:
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@ -312,7 +349,8 @@ def plot_params_filter(
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alpha = g.alpha
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if linewidth is None:
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linewidth = g.linewidth
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g.color, g.bgcolor, g.spot_size, g.size, g.projection, g.alpha, g.linewidth = color, bgcolor, spot_size, size, projection, alpha, linewidth
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g.color, g.bgcolor, g.cmap, g.spot_size, g.size, g.projection, g.alpha, g.linewidth = \
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color, bgcolor, cmap, spot_size, size, projection, alpha, linewidth
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def generate_params_filter(
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@ -410,6 +448,7 @@ def _GI_initializer(g, function1, function2):
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g.data2 = None
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g.color = DEFAULT_COLOR
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g.bgcolor = DEFAULT_BACKGROUND_COLOR
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g.cmap = DEFAULT_CMAP
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g.spot_size = DEFAULT_SPOT_SIZE
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g.size = DEFAULT_IMAGE_SIZE
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g.projection = DEFAULT_PROJECTION
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@ -468,6 +507,7 @@ def save_data_file(g, file_adr):
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data['plot'] = {
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"color": g.color,
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"bgcolor": g.bgcolor,
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"cmap": _serialize_cmap(g.cmap),
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"spot_size": g.spot_size,
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"projection": g.projection,
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"alpha": g.alpha,
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@ -511,6 +551,7 @@ def save_config_file(g, file_adr):
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data['plot'] = {
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"color": g.color,
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"bgcolor": g.bgcolor,
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"cmap": _serialize_cmap(g.cmap),
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"spot_size": g.spot_size,
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"projection": g.projection,
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"alpha": g.alpha,
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@ -618,6 +659,44 @@ def is_same_data(data1, data2, precision=10**-5):
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return all(is_same)
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def _serialize_color(color):
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"""
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Serialize the given color to a json serializable object.
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:param color: given color
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:type color: str or nd.array
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:return: the serializable version of the color
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"""
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if isinstance(color, str):
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return color
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return list(color)
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def _serialize_cmap(cmap):
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"""
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Serialize the cmap for saving.
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:param cmap: color map
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:type cmap: matplotlib.colors.Colormap
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:return: list of colors
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"""
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return list(map(_serialize_color, cmap.colors))
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def _load_cmap(config):
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"""
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Load the cmap from config.
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:param config: plot part configuration
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:type config: dict or json
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:return: ListedColormap from cmap
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"""
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if "cmap" not in config:
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return DEFAULT_CMAP
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cmap = config["cmap"]
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return ListedColormap(cmap)
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def load_data(g, data):
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"""
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Load data file.
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@ -638,6 +717,7 @@ def load_data(g, data):
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if plot_config is not None:
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g.color = plot_config.get("color", DEFAULT_COLOR)
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g.bgcolor = plot_config.get("bgcolor", DEFAULT_BACKGROUND_COLOR)
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g.cmap = _load_cmap(plot_config)
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g.spot_size = plot_config.get("spot_size", DEFAULT_SPOT_SIZE)
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g.projection = plot_config.get("projection", DEFAULT_PROJECTION)
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g.alpha = plot_config.get("alpha", DEFAULT_ALPHA)
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@ -673,6 +753,7 @@ def load_config(g, config):
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if plot_config is not None:
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g.color = plot_config.get("color", DEFAULT_COLOR)
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g.bgcolor = plot_config.get("bgcolor", DEFAULT_BACKGROUND_COLOR)
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g.cmap = _load_cmap(plot_config)
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g.spot_size = plot_config.get("spot_size", DEFAULT_SPOT_SIZE)
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g.projection = plot_config.get("projection", DEFAULT_PROJECTION)
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g.alpha = plot_config.get("alpha", DEFAULT_ALPHA)
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@ -91,6 +91,7 @@ class GenerativeImage:
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self,
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color=None,
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bgcolor=None,
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cmap=None,
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spot_size=None,
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size=None,
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projection=None,
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@ -103,6 +104,8 @@ class GenerativeImage:
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:type color: str
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:param bgcolor: background color
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:type bgcolor: str
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:param cmap: color map
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:type cmap: matplotlib.colors.Colormap or list of colors
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:param spot_size: point spot size
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:type spot_size: float
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:param size: figure size
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@ -119,6 +122,7 @@ class GenerativeImage:
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self,
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color,
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bgcolor,
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cmap,
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spot_size,
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size,
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projection,
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@ -133,6 +137,7 @@ class GenerativeImage:
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self.data1,
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alpha=self.alpha,
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c=self.color,
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cmap=self.cmap,
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s=self.spot_size,
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lw=self.linewidth)
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ax.set_axis_off()
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@ -3,6 +3,7 @@
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import math
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from enum import Enum
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from matplotlib import colors as mcolors
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from matplotlib import cm
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SAMILA_VERSION = "0.8" # pragma: no cover
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@ -18,6 +19,8 @@ DEFAULT_STOP = math.pi
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DEFAULT_STEP = 0.01
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DEFAULT_COLOR = "black"
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DEFAULT_BACKGROUND_COLOR = "white"
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DEFAULT_CMAP = cm.get_cmap("viridis", 256)
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DEFAULT_CMAP_RANGE = 256
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DEFAULT_ALPHA = 0.1
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DEFAULT_LINEWIDTH = 1.5
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DEFAULT_IMAGE_SIZE = (10, 10)
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@ -38,6 +41,7 @@ DATA_TYPE_ERROR = "Provided data file is not supported. It should be either file
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CONFIG_TYPE_ERROR = "Provided config file is not supported. It should be either file or io.IOBase."
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CONFIG_NO_STR_FUNCTION_ERROR = "Config file can't be saved. At least one of the function1_str or function2_str is None."
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PLOT_DATA_ERROR = "Plotting process can't be Done because data{0} is empty. Use generate method first."
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COLOR_SIZE_ERROR = "Color list size is not equal to the data size."
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SAVE_NO_DATA_ERROR = "Data file can't be saved. At least one of the data1 or data2 is None."
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INVALID_COLOR_TYPE_ERROR = "Given color/bgcolor type is not supported."
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MATPLOTLIB_VERSION_WARNING = "Source matplotlib version({0}) is different from yours, plots may be different."
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@ -39,6 +39,10 @@ samila.errors.samilaPlotError: Plotting process can't be Done because data2 is e
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Traceback (most recent call last):
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...
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samila.errors.samilaPlotError: Given color/bgcolor type is not supported.
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>>> g.plot(color=[0])
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Traceback (most recent call last):
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...
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samila.errors.samilaPlotError: Color list size is not the equal to the data size.
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>>> g = GenerativeImage(lambda x,y: x, lambda x,y: y)
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>>> result = g.save_config()
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Traceback (most recent call last):
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@ -6,6 +6,7 @@
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>>> import pickle
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>>> import socket
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>>> import json
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>>> from matplotlib.colors import Colormap, ListedColormap
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>>> def guard(*args, **kwargs):
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... raise Exception("No internet connection!")
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>>> from samila import GenerativeImage, Projection
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@ -222,6 +223,46 @@ False
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[0]
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>>> g.data2
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[1]
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>>> with open("data.json", 'w') as fp:
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... json.dump({'data1': [0], 'data2': [1], 'plot':{}}, fp)
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>>> g = GenerativeImage(data=open("data.json", 'r'))
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>>> with open("config.json", 'w') as fp:
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... json.dump({'f1': "x", 'f2': "y", 'plot':{}}, fp)
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>>> g = GenerativeImage(data=open("config.json", 'r'))
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>>> g = GenerativeImage()
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>>> g.generate()
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>>> cm = Colormap(name="Purples")
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>>> g.plot(cmap=cm)
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>>> result = g.save_config("config.json")
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>>> result["status"]
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True
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>>> g_ = GenerativeImage(data=open("config.json", 'r'))
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>>> (g_.cmap.colors == g.cmap.colors).all()
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True
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>>> cm = ["black", [0.6, 0.2, 0.2, 1], [0.5, 0.2, 0.2, 1], [0.4, 0.2, 0.2, 1], "yellow", [0.2, 0.2, 0.2, 1],]
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>>> g.plot(cmap=cm)
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>>> result = g.save_config("config.json")
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>>> result["status"]
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True
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>>> g_ = GenerativeImage(data=open("config.json", 'r'))
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>>> g_.cmap.colors == g.cmap.colors
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True
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>>> g.plot(cmap="Purples")
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>>> cm = Colormap(name="viridis")
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>>> g.plot(cmap=cm)
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>>> cmap = [[0.7, 0.2, 0.2, 1], [0.6, 0.2, 0.2, 1], [0.3, 0.2, 0.2, 1], [0.2, 0.2, 0.2, 1]]
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>>> g.plot(cmap=ListedColormap(cmap))
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>>> g = GenerativeImage()
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>>> g.generate()
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>>> g.plot(cmap=cmap, color=g.data1)
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>>> result = g.save_data("config.json")
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>>> result["status"]
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True
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>>> g_ = GenerativeImage(data=open("config.json", "r"))
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>>> g_.plot()
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>>> g_.cmap.colors == g.cmap.colors
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True
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>>> g.plot(color=g.data1)
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>>> g_ = GenerativeImage()
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>>> del(g)
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>>> del g_.data1
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