{{ message }}
Repository navigation
Expand file tree
/
Copy pathrf_ipython.py
More file actions
315 lines (254 loc) · 10.6 KB
/
Copy pathrf_ipython.py
File metadata and controls
315 lines (254 loc) · 10.6 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
#
# This software is licensed under the Apache 2 license, quoted below.
#
# Copyright 2019 Astraea, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not
# use this file except in compliance with the License. You may obtain a copy of
# the License at
#
# [http://www.apache.org/licenses/LICENSE-2.0]
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations under
# the License.
#
# SPDX-License-Identifier: Apache-2.0
#
from functools import partial
from typing import Optional, Tuple, Union
import numpy as np
import pyrasterframes.rf_types
from matplotlib.axes import Axes
from pandas import DataFrame
from pyrasterframes.rf_types import Tile
from shapely.geometry.base import BaseGeometry
_png_header = bytearray([0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A])
def plot_tile(
tile: Tile,
normalize: bool = True,
lower_percentile: float = 1.0,
upper_percentile: float = 99.0,
axis: Optional[Axes] = None,
**imshow_args,
):
"""
Display an image of the tile
Parameters
----------
tile: item to plot
normalize: if True, will normalize the data between using
lower_percentile and upper_percentile as bounds
lower_percentile: between 0 and 100 inclusive.
Specifies to clip values below this percentile
upper_percentile: between 0 and 100 inclusive.
Specifies to clip values above this percentile
axis : matplotlib axis object to plot onto. Creates new axis if None
imshow_args : parameters to pass into matplotlib.pyplot.imshow
see https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.imshow.html
Returns
-------
created or modified axis object
"""
if axis is None:
import matplotlib.pyplot as plt
axis = plt.gca()
arr = tile.cells
def normalize_cells(cells: np.ndarray) -> np.ndarray:
assert (
upper_percentile > lower_percentile
), "invalid upper and lower percentiles {}, {}".format(lower_percentile, upper_percentile)
sans_mask = np.array(cells)
lower = np.nanpercentile(sans_mask, lower_percentile)
upper = np.nanpercentile(sans_mask, upper_percentile)
cells_clipped = np.clip(cells, lower, upper)
return (cells_clipped - lower) / (upper - lower)
axis.set_aspect("equal")
axis.xaxis.set_ticks([])
axis.yaxis.set_ticks([])
if normalize:
cells = normalize_cells(arr)
else:
cells = arr
axis.imshow(cells, **imshow_args)
return axis
def tile_to_png(
tile: Tile,
lower_percentile: float = 1.0,
upper_percentile: float = 99.0,
title: Optional[str] = None,
fig_size: Optional[Tuple[int, int]] = None,
) -> bytes:
"""Provide image of Tile."""
if tile.cells is None:
return None
import io
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
# Set up matplotlib objects
nominal_size = 2
if fig_size is None:
fig_size = (nominal_size, nominal_size)
fig = Figure(figsize=fig_size)
canvas = FigureCanvas(fig)
axis = fig.add_subplot(1, 1, 1)
plot_tile(tile, True, lower_percentile, upper_percentile, axis=axis)
axis.set_aspect("equal")
axis.xaxis.set_ticks([])
axis.yaxis.set_ticks([])
if title is None:
axis.set_title(
"{}, {}".format(tile.dimensions(), tile.cell_type.__repr__()), fontsize=fig_size[0] * 4
) # compact metadata as title
else:
axis.set_title(title, fontsize=fig_size[0] * 4) # compact metadata as title
with io.BytesIO() as output:
canvas.print_png(output)
return output.getvalue()
def tile_to_html(tile: Tile, fig_size: Optional[Tuple[int, int]] = None) -> str:
"""Provide HTML string representation of Tile image."""
import base64
b64_img_html = '<img src="data:image/png;base64,{}" />'
png_bits = tile_to_png(tile, fig_size=fig_size)
b64_png = base64.b64encode(png_bits).decode("utf-8").replace("\n", "")
return b64_img_html.format(b64_png)
def binary_to_html(blob) -> Union[str, bytearray]:
"""When using rf_render_png, the result from the JVM is a byte string with special PNG header
Look for this header and return base64 encoded HTML for Jupyter display
"""
import base64
if blob[:8] == _png_header:
b64_img_html = '<img src="data:image/png;base64,{}" />'
b64_png = base64.b64encode(blob).decode("utf-8").replace("\n", "")
return b64_img_html.format(b64_png)
else:
return blob
def pandas_df_to_html(df: DataFrame) -> Optional[str]:
"""Provide HTML formatting for pandas.DataFrame with rf_types.Tile in the columns."""
import pandas as pd
# honor the existing options on display
if not pd.get_option("display.notebook_repr_html"):
return None
default_max_colwidth = pd.get_option(
"display.max_colwidth"
) # we'll try to politely put it back
if len(df) == 0:
return df._repr_html_()
tile_cols = []
geom_cols = []
bytearray_cols = []
for c in df.columns:
if isinstance(
df.iloc[0][c], pyrasterframes.rf_types.Tile
): # if the first is a Tile try formatting
tile_cols.append(c)
elif isinstance(df.iloc[0][c], BaseGeometry): # if the first is a Geometry try formatting
geom_cols.append(c)
elif isinstance(df.iloc[0][c], bytearray):
bytearray_cols.append(c)
def _safe_tile_to_html(t):
if isinstance(t, pyrasterframes.rf_types.Tile):
return tile_to_html(t, fig_size=(2, 2))
else:
# handles case where objects in a column are not all Tile type
return t.__repr__()
def _safe_geom_to_html(g):
if isinstance(g, BaseGeometry):
wkt = g.wkt
if len(wkt) > default_max_colwidth:
return wkt[: default_max_colwidth - 3] + "..."
else:
return wkt
else:
return g.__repr__()
def _safe_bytearray_to_html(b):
if isinstance(b, bytearray):
return binary_to_html(b)
else:
return b.__repr__()
# dict keyed by column with custom rendering function
formatter = {c: _safe_tile_to_html for c in tile_cols}
formatter.update({c: _safe_geom_to_html for c in geom_cols})
formatter.update({c: _safe_bytearray_to_html for c in bytearray_cols})
# This is needed to avoid our tile being rendered as `<img src="only up to fifty char...`
pd.set_option("display.max_colwidth", None)
return_html = df.to_html(
escape=False, # means our `< img` does not get changed to `< img`
formatters=formatter, # apply custom format to columns
render_links=True, # common in raster frames
notebook=True,
max_rows=pd.get_option("display.max_rows"), # retain existing options
max_cols=pd.get_option("display.max_columns"),
show_dimensions=pd.get_option("display.show_dimensions"),
)
pd.set_option("display.max_colwidth", default_max_colwidth)
return return_html
def spark_df_to_markdown(df: DataFrame, num_rows: int = 5, truncate: bool = False) -> str:
from pyrasterframes import RFContext
return RFContext.active().call("_dfToMarkdown", df._jdf, num_rows, truncate)
def spark_df_to_html(df: DataFrame, num_rows: int = 5, truncate: bool = False) -> str:
from pyrasterframes import RFContext
return RFContext.active().call("_dfToHTML", df._jdf, num_rows, truncate)
def _folium_map_formatter(map) -> str:
"""inputs a folium.Map object and returns html of rendered map"""
import base64
html_source = map.get_root().render()
b64_source = base64.b64encode(bytes(html_source.encode("utf-8"))).decode("utf-8")
source_blob = '<iframe src="data:text/html;charset=utf-8;base64,{}" allowfullscreen="" webkitallowfullscreen="" mozallowfullscreen="" style="position:relative;width:100%;height:500px"></iframe>'
return source_blob.format(b64_source)
try:
from IPython import get_ipython
from IPython.display import display, display_html, display_markdown, display_png
# modifications to currently running ipython session, if we are in one; these enable nicer visualization for Pandas
if get_ipython() is not None:
import pandas
import pyspark.sql
from pyrasterframes.rf_types import Tile
ip = get_ipython()
formatters = ip.display_formatter.formatters
# Register custom formatters
# PNG
png_formatter = formatters["image/png"]
png_formatter.for_type(Tile, tile_to_png)
# HTML
html_formatter = formatters["text/html"]
html_formatter.for_type(pandas.DataFrame, pandas_df_to_html)
html_formatter.for_type(pyspark.sql.DataFrame, spark_df_to_html)
html_formatter.for_type(Tile, tile_to_html)
# Markdown. These will likely only effect docs build.
markdown_formatter = formatters["text/markdown"]
# Pandas doesn't have a markdown
markdown_formatter.for_type(pandas.DataFrame, pandas_df_to_html)
markdown_formatter.for_type(pyspark.sql.DataFrame, spark_df_to_markdown)
# Running loose here by embedding tile as `img` tag.
markdown_formatter.for_type(Tile, tile_to_html)
try:
# this block is to try to avoid making an install dep on folium but support if in the environment
import folium
markdown_formatter.for_type(folium.Map, _folium_map_formatter)
except ImportError as e:
pass
Tile.show = plot_tile
# noinspection PyTypeChecker
def _display(
df: pyspark.sql.DataFrame,
num_rows: int = 5,
truncate: bool = False,
mimetype: str = "text/html",
) -> ():
"""
Invoke IPython `display` with specific controls.
:param num_rows: number of rows to render
:param truncate: If `True`, shorten width of columns to no more than 40 characters
:return: None
"""
if "html" in mimetype:
display_html(spark_df_to_html(df, num_rows, truncate), raw=True)
else:
display_markdown(spark_df_to_markdown(df, num_rows, truncate), raw=True)
# Add enhanced display function
pyspark.sql.DataFrame.display = _display
except ImportError as e:
pass
You can’t perform that action at this time.