# Geonum is a Python library for geographical calculations in 3D
# Copyright (C) 2017 Jonas Gliss (jonasgliss@gmail.com)
#
# This program is free software: you can redistribute it and/or
# modify it under the terms of the GNU General Public License a
# published by the Free Software Foundation, either version 3 of
# the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import os
import numpy as np
from geonum import TOPO_INFO_FILE, LOCAL_TOPO_DIR
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def order_of_magnitude(num):
"""
Get exponent precision of input number
E.g. 1 if input number is 14.2, 0 if input number is 3 or -1 if input
number is 0.1.
Note
----
The order of magnitude here is calculated using floor(log10(num)), thus,
num=9, would result in a value of 0, in contrary to other definitions (
e.g. https://en.wikipedia.org/wiki/Order_of_magnitude).
Parameters
----------
num : float
input number
Returns
-------
int
order of magnitude of input number
"""
return int(np.floor(np.log10(np.abs(num))))
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def all_topodata_search_dirs():
"""Returns a list of all directories that are searched for topography data
Returns
-------
list
list containing all search directories (absolute paths)
"""
if LOCAL_TOPO_DIR is None:
raise FileNotFoundError('geonum local topo directory not accessible')
paths = []
with open(TOPO_INFO_FILE, "r") as f:
for line in f:
p = line.strip()
if os.path.exists(p) and not p in paths:
paths.append(os.path.normpath(p))
return paths
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def check_and_add_topodir(local_dir):
"""Check if input directory is registered and if not, register it
Parameters
----------
local_dir : str
directory that is supposed to be checked
"""
fp = os.path.normpath(local_dir)
if not os.path.exists(fp):
raise ValueError(f'{local_dir} does not exist...')
elif not fp in all_topodata_search_dirs():
with open(TOPO_INFO_FILE, "a") as f:
f.write(f'{fp}\n')
print(f'Adding {fp} to file ~/.geonum/LOCAL_TOPO_DATA')
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def isnum(val):
"""Checks if input is number (int or float) or and not nan
Parameters
----------
val
input object to be checked
Returns
-------
bool
whether or not input object `val` is of numerical type
"""
if isinstance(val, (int, float)) and not np.isnan(val):
return True
return False
# ToDo: review and move to plot_helpers.py
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def rotate_xtick_labels(ax, deg=30, ha="right"):
"""Rotate xtick labels in matplotlib axes object"""
lbls = ax.get_xticklabels()
lbls = [lbl.get_text() for lbl in lbls]
ax.set_xticklabels(lbls, rotation=deg, ha=ha)
return ax
# ToDo: check whether this is really needed...
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def approximate_connection_vector(lon0, lat0, lon1, lat1, len_lat_km=111.20):
"""Returns approximate connection vector between two points
Note
----
Careful: Only approximate, suited for small distances ( < 100km)
Parameters
----------
lon0 : float
longitude of first point in decimal degrees
lat0 : float
latitude of first point in decimal degrees
lon1 : float
longitude of second point in decimal degrees
lat1 : float
latitude of second point in decimal degrees
len_lat_km : float
approx. length of 1 degree latitude at the equator in km.
Returns
-------
numpy.ndarray
2-element array containing (dx, dy) components of connection vector
"""
lat = (lat0 + lat1) / 2 * 0.01745
dx = len_lat_km * np.cos(lat) * (lon1 - lon0)
dy = len_lat_km * (lat1 - lat0)
return np.array((dx, dy))
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def shifted_color_map(vmin, vmax, cmap=None):
"""Shift center of a diverging colormap to value 0
Note
----
This method was found `here <http://stackoverflow.com/questions/
7404116/defining-the-midpoint-of-a-colormap-in-matplotlib>`__
(last access: 17/01/2017). Thanks to `Paul H <http://stackoverflow.com/
users/1552748/paul-h>`_ who provided it.
Function to offset the "center" of a colormap. Useful for
data with a negative min and positive max and if you want the
middle of the colormap's dynamic range to be at zero level
Parameters
----------
vmin : float
lower end of data value range
vmax : float
upper end of data value range
cmap
matplotlib colormap to be shifted (if None, use "seismic")
Returns
-------
matplotlib.colors.LinearSegmentedColormap
shifted colormap
"""
import matplotlib.cm as colormaps
import matplotlib.colors as colors
if cmap is None:
cmap = colormaps.seismic
midpoint = 1 - np.abs(vmax) / (np.abs(vmax) + np.abs(vmin))
cdict = {
'red': [],
'green': [],
'blue': [],
'alpha': []
}
# regular index to compute the colors
reg_index = np.linspace(0, 1, 257)
# shifted index to match the data
shift_index = np.hstack([
np.linspace(0.0, midpoint, 128, endpoint=False),
np.linspace(midpoint, 1.0, 129, endpoint=True)
])
for ri, si in zip(reg_index, shift_index):
r, g, b, a = cmap(ri)
cdict['red'].append((si, r, r))
cdict['green'].append((si, g, g))
cdict['blue'].append((si, b, b))
cdict['alpha'].append((si, a, a))
return colors.LinearSegmentedColormap('shiftedcmap', cdict)