diff --git a/examples/demo_boost_factors.ipynb b/examples/demo_boost_factors.ipynb index 7fa39912c..6f236bd22 100644 --- a/examples/demo_boost_factors.ipynb +++ b/examples/demo_boost_factors.ipynb @@ -406,27 +406,6 @@ "plt.legend()\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/demo_compute_deltasigma_weights.ipynb b/examples/demo_compute_deltasigma_weights.ipynb index 7f9fda325..9e4cbe5c1 100644 --- a/examples/demo_compute_deltasigma_weights.ipynb +++ b/examples/demo_compute_deltasigma_weights.ipynb @@ -634,20 +634,6 @@ "- When using photometric redshift (blue and orange dots), galaxies on the foreground of the cluster have non-zero probability to be in the background. Idem, for close galaxies in the background, the probability in being in the foreground is non-zero.\n", "- These weights represent the fraction of the galaxy PDF that is located behind the cluster and is mapped to the observed redshift as it can be seen on the top left panel. The scatter in the main panel comes from the scatter between true and observed redshifts." ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/demo_dataops_functionality.ipynb b/examples/demo_dataops_functionality.ipynb index 7d728f41c..a985af223 100644 --- a/examples/demo_dataops_functionality.ipynb +++ b/examples/demo_dataops_functionality.ipynb @@ -790,20 +790,6 @@ "plt.legend()\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/demo_mass_conversion.ipynb b/examples/demo_mass_conversion.ipynb index 4b3392b02..587d5243b 100644 --- a/examples/demo_mass_conversion.ipynb +++ b/examples/demo_mass_conversion.ipynb @@ -380,13 +380,6 @@ "fig2.gca().legend()\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/demo_mock_cluster.ipynb b/examples/demo_mock_cluster.ipynb index 25a678d09..861537940 100644 --- a/examples/demo_mock_cluster.ipynb +++ b/examples/demo_mock_cluster.ipynb @@ -859,13 +859,6 @@ ")" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "code", "execution_count": null, @@ -1171,13 +1164,6 @@ "source": [ "np.sqrt(sigma)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/demo_mock_ensemble.ipynb b/examples/demo_mock_ensemble.ipynb index fc5134281..fd3c734db 100644 --- a/examples/demo_mock_ensemble.ipynb +++ b/examples/demo_mock_ensemble.ipynb @@ -193,15 +193,6 @@ "cl.galcat.columns" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "noisy_data_z" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -592,34 +583,6 @@ "source": [ "clusterensemble2 = ClusterEnsemble.load(\"ce.pkl\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/demo_theory_functionality.ipynb b/examples/demo_theory_functionality.ipynb index 6d1a76708..393606340 100644 --- a/examples/demo_theory_functionality.ipynb +++ b/examples/demo_theory_functionality.ipynb @@ -537,13 +537,6 @@ "\n", "plot_profile(r3d, Sigma_FFTLog, \"$\\\\Sigma_{\\\\rm FFTLog}$\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/mass_fitting/Example1_Fit_Halo_Mass_to_Shear_Catalog.ipynb b/examples/mass_fitting/Example1_Fit_Halo_Mass_to_Shear_Catalog.ipynb index 17a72e725..aa5db1668 100644 --- a/examples/mass_fitting/Example1_Fit_Halo_Mass_to_Shear_Catalog.ipynb +++ b/examples/mass_fitting/Example1_Fit_Halo_Mass_to_Shear_Catalog.ipynb @@ -667,20 +667,6 @@ "plt.xlabel(\"R [Mpc]\", fontsize=fsize)\n", "plt.ylabel(\"reduced tangential shear\", fontsize=fsize)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/examples/mass_fitting/Example2_Fit_Halo_Mass_to_Shear_Catalog.ipynb b/examples/mass_fitting/Example2_Fit_Halo_Mass_to_Shear_Catalog.ipynb index 54e4df7fc..567d5f292 100644 --- a/examples/mass_fitting/Example2_Fit_Halo_Mass_to_Shear_Catalog.ipynb +++ b/examples/mass_fitting/Example2_Fit_Halo_Mass_to_Shear_Catalog.ipynb @@ -601,27 +601,6 @@ "\n", "fig.tight_layout()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": {