Feb 21, 2020 · Feb 16, 2020 · Feb 19, 2020 · Feb 19, 2020 · Feb 21, 2020
diff --git a/doc/api/prev_api_changes/api_changes_3.2.0/behavior.rst b/doc/api/prev_api_changes/api_changes_3.2.0/behavior.rst
 longer necessary to import mplot3d to create 3d axes with ::

  ax = fig.add_subplot(111, projection="3d")

 `.SymLogNorm` now has a *base* parameter
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 Previously, `.SymLogNorm` had no *base* keyword argument and the base was
 hard-coded to ``base=np.e``. This was inconsistent with the default
 behavior of `.SymLogScale` (which defaults to ``base=10``) and the use
 of the word "decade" in the documentation.

 In preparation for changing the default base to 10, calling
 `.SymLogNorm` without the new *base* kwarg emits a deprecation
 warning.
diff --git a/examples/userdemo/colormap_normalizations.py b/examples/userdemo/colormap_normalizations.py

 pcm = ax[0].pcolormesh(X, Y, Z1,
                       norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
                                              vmin=-1.0, vmax=1.0),
                                              vmin=-1.0, vmax=1.0, base=10),
                       cmap='RdBu_r')
 fig.colorbar(pcm, ax=ax[0], extend='both')

diff --git a/examples/userdemo/colormap_normalizations_symlognorm.py b/examples/userdemo/colormap_normalizations_symlognorm.py

 pcm = ax[0].pcolormesh(X, Y, Z,
                       norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
                                              vmin=-1.0, vmax=1.0),
                                              vmin=-1.0, vmax=1.0, base=10),
                       cmap='RdBu_r')
 fig.colorbar(pcm, ax=ax[0], extend='both')

diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
    *linthresh* allows the user to specify the size of this range
    (-*linthresh*, *linthresh*).
    """
    def __init__(self,linthresh, linscale=1.0,
 vmin=None, vmax=None, clip=False):
    def __init__(self, linthresh, linscale=1.0, vmin=None, vmax=None,
 clip=False, *, base=None):
        """
        *linthresh*:
        The range within which the plot is linear (to
        avoid having the plot go to infinity around zero).

        *linscale*:
        This allows the linear range (-*linthresh* to *linthresh*)
        to be stretched relative to the logarithmic range.  Its
        value is the number of decades to use for each half of the
        linear range.  For example, when *linscale* == 1.0 (the
        default), the space used for the positive and negative
        halves of the linear range will be equal to one decade in
        the logarithmic range. Defaults to 1.
        Parameters
        ----------
        linthresh : float
            The range within which the plot is linear (to avoid having the plot
            go to infinity around zero).
        linscale : float, default: 1
            This allows the linear range (-*linthresh* to *linthresh*)
            to be stretched relative to the logarithmic range. Its
            value is the number of powers of *base* to use for each
            half of the linear range.

            For example, when *linscale* == 1.0 (the default) and
            ``base=10``, then space used for the positive and negative
            halves of the linear range will be equal to a decade in
            the logarithmic.

        base : float, default: None
            If not given, defaults to ``np.e`` (consistent with prior
            behavior) and warns.

            In v3.3 the default value will change to 10 to be consistent with
            `.SymLogNorm`.

            To suppress the warning pass *base* as a keyword argument.

        """
        Normalize.__init__(self, vmin, vmax, clip)
        if base is None:
            self._base = np.e
            cbook.warn_deprecated("3.3", message="default base may change "
                "from np.e to 10.  To suppress this warning specify the base "
                "keyword argument.")
        else:
            self._base = base
        self._log_base = np.log(self._base)

        self.linthresh = float(linthresh)
        self._linscale_adj = (linscale / (1.0 -np.e ** -1))
        self._linscale_adj = (linscale / (1.0 -self._base ** -1))
        if vmin is not None and vmax is not None:
            self._transform_vmin_vmax()

        with np.errstate(invalid="ignore"):
            masked = np.abs(a) > self.linthresh
        sign = np.sign(a[masked])
        log = (self._linscale_adj + np.log(np.abs(a[masked]) / self.linthresh))
        log = (self._linscale_adj +
               np.log(np.abs(a[masked]) / self.linthresh) / self._log_base)
        log *= sign * self.linthresh
        a[masked] = log
        a[~masked] *= self._linscale_adj
        """Inverse inplace Transformation."""
        masked = np.abs(a) > (self.linthresh * self._linscale_adj)
        sign = np.sign(a[masked])
        exp = np.exp(sign * a[masked] / self.linthresh - self._linscale_adj)
        exp = np.power(self._base,
                       sign * a[masked] / self.linthresh - self._linscale_adj)
        exp *= sign * self.linthresh
        a[masked] = exp
        a[~masked] /= self._linscale_adj
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
    """
    Test SymLogNorm behavior
    """
    norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2)
    norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2, base=np.e)
    vals = np.array([-30, -1, 2, 6], dtype=float)
    normed_vals = norm(vals)
    expected = [0., 0.53980074, 0.826991, 1.02758204]
    _mask_tester(norm, vals)

    # Ensure that specifying vmin returns the same result as above
    norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2)
    norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2, base=np.e)
    normed_vals = norm(vals)
    assert_array_almost_equal(normed_vals, expected)

    # test something more easily checked.
    norm = mcolors.SymLogNorm(1, vmin=-np.e**3, vmax=np.e**3, base=np.e)
    nn = norm([-np.e**3, -np.e**2, -np.e**1, -1,
              0, 1, np.e**1, np.e**2, np.e**3])
    xx = np.array([0., 0.109123, 0.218246, 0.32737, 0.5, 0.67263,
                   0.781754, 0.890877, 1.])
    assert_array_almost_equal(nn, xx)
    norm = mcolors.SymLogNorm(1, vmin=-10**3, vmax=10**3, base=10)
    nn = norm([-10**3, -10**2, -10**1, -1,
              0, 1, 10**1, 10**2, 10**3])
    xx = np.array([0., 0.121622, 0.243243, 0.364865, 0.5, 0.635135,
                   0.756757, 0.878378, 1.])
    assert_array_almost_equal(nn, xx)


 def test_SymLogNorm_colorbar():
    """
    Test un-called SymLogNorm in a colorbar.
    """
    norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1)
    norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1, base=np.e)
    fig = plt.figure()
    mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    plt.close(fig)
    Test SymLogNorm to ensure it is not adding sub-ticks to zero label
    """
    fig = plt.figure()
    norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1)
    norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1, base=np.e)
    cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    ticks = cbar.get_ticks()
    assert sum(ticks == 0) == 1
    mydata = data.view(MyArray)

    for norm in [mcolors.Normalize(), mcolors.LogNorm(),
                 mcolors.SymLogNorm(3, vmax=5, linscale=1),
                 mcolors.SymLogNorm(3, vmax=5, linscale=1, base=np.e),
                 mcolors.Normalize(vmin=mydata.min(), vmax=mydata.max()),
                 mcolors.SymLogNorm(3, vmin=mydata.min(), vmax=mydata.max()),
                 mcolors.SymLogNorm(3, vmin=mydata.min(), vmax=mydata.max(),
                                    base=np.e),
                 mcolors.PowerNorm(1)]:
        assert_array_equal(norm(mydata), norm(data))
        fig, ax = plt.subplots()
diff --git a/tutorials/colors/colormapnorms.py b/tutorials/colors/colormapnorms.py

 pcm = ax[0].pcolormesh(X, Y, Z,
                       norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
                                              vmin=-1.0, vmax=1.0),
                                              vmin=-1.0, vmax=1.0, base=10),
                       cmap='RdBu_r')
 fig.colorbar(pcm, ax=ax[0], extend='both')
Original file line number	Diff line number	Diff line change
Expand Up		@@ -307,3 +307,15 @@ mplot3d auto-registration
		longer necessary to import mplot3d to create 3d axes with ::

		ax = fig.add_subplot(111, projection="3d")

		`.SymLogNorm` now has a base parameter
		~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

		Previously, `.SymLogNorm` had no base keyword argument and the base was
		hard-coded to ``base=np.e``. This was inconsistent with the default
		behavior of `.SymLogScale` (which defaults to ``base=10``) and the use
		of the word "decade" in the documentation.

		In preparation for changing the default base to 10, calling
		`.SymLogNorm` without the new base kwarg emits a deprecation
		warning.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -69,7 +69,7 @@

		pcm = ax[0].pcolormesh(X, Y, Z1,
		norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
		vmin=-1.0, vmax=1.0),
		vmin=-1.0, vmax=1.0, base=10),
		cmap='RdBu_r')
		fig.colorbar(pcm, ax=ax[0], extend='both')

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -29,7 +29,7 @@

		pcm = ax[0].pcolormesh(X, Y, Z,
		norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
		vmin=-1.0, vmax=1.0),
		vmin=-1.0, vmax=1.0, base=10),
		cmap='RdBu_r')
		fig.colorbar(pcm, ax=ax[0], extend='both')

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -1209,25 +1209,47 @@ class SymLogNorm(Normalize):
		linthresh allows the user to specify the size of this range
		(-linthresh, linthresh).
		"""
		def __init__(self,linthresh, linscale=1.0,
		vmin=None, vmax=None, clip=False):
		def __init__(self, linthresh, linscale=1.0, vmin=None, vmax=None,
		clip=False, *, base=None):
		"""
		linthresh:
		The range within which the plot is linear (to
		avoid having the plot go to infinity around zero).

		linscale:
		This allows the linear range (-linthresh to linthresh)
		to be stretched relative to the logarithmic range. Its
		value is the number of decades to use for each half of the
		linear range. For example, when linscale == 1.0 (the
		default), the space used for the positive and negative
		halves of the linear range will be equal to one decade in
		the logarithmic range. Defaults to 1.
		Parameters
		----------
		linthresh : float
		The range within which the plot is linear (to avoid having the plot
		go to infinity around zero).
		linscale : float, default: 1
		This allows the linear range (-linthresh to linthresh)
		to be stretched relative to the logarithmic range. Its
		value is the number of powers of base to use for each
		half of the linear range.

		For example, when linscale == 1.0 (the default) and
		``base=10``, then space used for the positive and negative
		halves of the linear range will be equal to a decade in
		the logarithmic.

		base : float, default: None
		If not given, defaults to ``np.e`` (consistent with prior
		behavior) and warns.

		In v3.3 the default value will change to 10 to be consistent with
		`.SymLogNorm`.

		To suppress the warning pass base as a keyword argument.

		"""
		Normalize.__init__(self, vmin, vmax, clip)
		if base is None:
		self._base = np.e
		cbook.warn_deprecated("3.3", message="default base may change "
		"from np.e to 10. To suppress this warning specify the base "
		"keyword argument.")
		else:
		self._base = base
		self._log_base = np.log(self._base)

		self.linthresh = float(linthresh)
		self._linscale_adj = (linscale / (1.0 -np.e ** -1))
		self._linscale_adj = (linscale / (1.0 -self._base ** -1))
		if vmin is not None and vmax is not None:
		self._transform_vmin_vmax()

Expand DownExpand Up		@@ -1262,7 +1284,8 @@ def _transform(self, a):
		with np.errstate(invalid="ignore"):
		masked = np.abs(a) > self.linthresh
		sign = np.sign(a[masked])
		log = (self._linscale_adj + np.log(np.abs(a[masked]) / self.linthresh))
		log = (self._linscale_adj +
		np.log(np.abs(a[masked]) / self.linthresh) / self._log_base)
		log = sign self.linthresh
		a[masked] = log
		a[~masked] *= self._linscale_adj
Expand All		@@ -1272,7 +1295,8 @@ def _inv_transform(self, a):
		"""Inverse inplace Transformation."""
		masked = np.abs(a) > (self.linthresh * self._linscale_adj)
		sign = np.sign(a[masked])
		exp = np.exp(sign * a[masked] / self.linthresh - self._linscale_adj)
		exp = np.power(self._base,
		sign * a[masked] / self.linthresh - self._linscale_adj)
		exp = sign self.linthresh
		a[masked] = exp
		a[~masked] /= self._linscale_adj
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -388,7 +388,7 @@ def test_SymLogNorm():
		"""
		Test SymLogNorm behavior
		"""
		norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2)
		norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2, base=np.e)
		vals = np.array([-30, -1, 2, 6], dtype=float)
		normed_vals = norm(vals)
		expected = [0., 0.53980074, 0.826991, 1.02758204]
Expand All		@@ -398,16 +398,30 @@ def test_SymLogNorm():
		_mask_tester(norm, vals)

		# Ensure that specifying vmin returns the same result as above
		norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2)
		norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2, base=np.e)
		normed_vals = norm(vals)
		assert_array_almost_equal(normed_vals, expected)

		# test something more easily checked.
		norm = mcolors.SymLogNorm(1, vmin=-np.e3, vmax=np.e3, base=np.e)
		nn = norm([-np.e3, -np.e2, -np.e**1, -1,
		0, 1, np.e1, np.e2, np.e**3])
		xx = np.array([0., 0.109123, 0.218246, 0.32737, 0.5, 0.67263,
		0.781754, 0.890877, 1.])
		assert_array_almost_equal(nn, xx)
		norm = mcolors.SymLogNorm(1, vmin=-103, vmax=103, base=10)
		nn = norm([-103, -102, -10**1, -1,
		0, 1, 101, 102, 10**3])
		xx = np.array([0., 0.121622, 0.243243, 0.364865, 0.5, 0.635135,
		0.756757, 0.878378, 1.])
		assert_array_almost_equal(nn, xx)


		def test_SymLogNorm_colorbar():
		"""
		Test un-called SymLogNorm in a colorbar.
		"""
		norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1)
		norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1, base=np.e)
		fig = plt.figure()
		mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
		plt.close(fig)
Expand All		@@ -418,7 +432,7 @@ def test_SymLogNorm_single_zero():
		Test SymLogNorm to ensure it is not adding sub-ticks to zero label
		"""
		fig = plt.figure()
		norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1)
		norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1, base=np.e)
		cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
		ticks = cbar.get_ticks()
		assert sum(ticks == 0) == 1
Expand DownExpand Up		@@ -895,9 +909,10 @@ def __add__(self, other):
		mydata = data.view(MyArray)

		for norm in [mcolors.Normalize(), mcolors.LogNorm(),
		mcolors.SymLogNorm(3, vmax=5, linscale=1),
		mcolors.SymLogNorm(3, vmax=5, linscale=1, base=np.e),
		mcolors.Normalize(vmin=mydata.min(), vmax=mydata.max()),
		mcolors.SymLogNorm(3, vmin=mydata.min(), vmax=mydata.max()),
		mcolors.SymLogNorm(3, vmin=mydata.min(), vmax=mydata.max(),
		base=np.e),
		mcolors.PowerNorm(1)]:
		assert_array_equal(norm(mydata), norm(data))
		fig, ax = plt.subplots()
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -98,7 +98,7 @@

		pcm = ax[0].pcolormesh(X, Y, Z,
		norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
		vmin=-1.0, vmax=1.0),
		vmin=-1.0, vmax=1.0, base=10),
		cmap='RdBu_r')
		fig.colorbar(pcm, ax=ax[0], extend='both')

Expand Down