src/HOL/Library/Convex.thy
 author kuncar Fri Dec 09 18:07:04 2011 +0100 (2011-12-09) changeset 45802 b16f976db515 parent 44890 22f665a2e91c child 49609 89e10ed7668b permissions -rw-r--r--
Quotient_Info stores only relation maps
```     1 (*  Title:      HOL/Library/Convex.thy
```
```     2     Author:     Armin Heller, TU Muenchen
```
```     3     Author:     Johannes Hoelzl, TU Muenchen
```
```     4 *)
```
```     5
```
```     6 header {* Convexity in real vector spaces *}
```
```     7
```
```     8 theory Convex
```
```     9 imports Product_Vector
```
```    10 begin
```
```    11
```
```    12 subsection {* Convexity. *}
```
```    13
```
```    14 definition
```
```    15   convex :: "'a::real_vector set \<Rightarrow> bool" where
```
```    16   "convex s \<longleftrightarrow> (\<forall>x\<in>s. \<forall>y\<in>s. \<forall>u\<ge>0. \<forall>v\<ge>0. u + v = 1 \<longrightarrow> u *\<^sub>R x + v *\<^sub>R y \<in> s)"
```
```    17
```
```    18 lemma convex_alt:
```
```    19   "convex s \<longleftrightarrow> (\<forall>x\<in>s. \<forall>y\<in>s. \<forall>u. 0 \<le> u \<and> u \<le> 1 \<longrightarrow> ((1 - u) *\<^sub>R x + u *\<^sub>R y) \<in> s)"
```
```    20   (is "_ \<longleftrightarrow> ?alt")
```
```    21 proof
```
```    22   assume alt[rule_format]: ?alt
```
```    23   { fix x y and u v :: real assume mem: "x \<in> s" "y \<in> s"
```
```    24     assume "0 \<le> u" "0 \<le> v" "u + v = 1"
```
```    25     moreover hence "u = 1 - v" by auto
```
```    26     ultimately have "u *\<^sub>R x + v *\<^sub>R y \<in> s" using alt[OF mem] by auto }
```
```    27   thus "convex s" unfolding convex_def by auto
```
```    28 qed (auto simp: convex_def)
```
```    29
```
```    30 lemma mem_convex:
```
```    31   assumes "convex s" "a \<in> s" "b \<in> s" "0 \<le> u" "u \<le> 1"
```
```    32   shows "((1 - u) *\<^sub>R a + u *\<^sub>R b) \<in> s"
```
```    33   using assms unfolding convex_alt by auto
```
```    34
```
```    35 lemma convex_empty[intro]: "convex {}"
```
```    36   unfolding convex_def by simp
```
```    37
```
```    38 lemma convex_singleton[intro]: "convex {a}"
```
```    39   unfolding convex_def by (auto simp: scaleR_left_distrib[symmetric])
```
```    40
```
```    41 lemma convex_UNIV[intro]: "convex UNIV"
```
```    42   unfolding convex_def by auto
```
```    43
```
```    44 lemma convex_Inter: "(\<forall>s\<in>f. convex s) ==> convex(\<Inter> f)"
```
```    45   unfolding convex_def by auto
```
```    46
```
```    47 lemma convex_Int: "convex s \<Longrightarrow> convex t \<Longrightarrow> convex (s \<inter> t)"
```
```    48   unfolding convex_def by auto
```
```    49
```
```    50 lemma convex_halfspace_le: "convex {x. inner a x \<le> b}"
```
```    51   unfolding convex_def
```
```    52   by (auto simp: inner_add intro!: convex_bound_le)
```
```    53
```
```    54 lemma convex_halfspace_ge: "convex {x. inner a x \<ge> b}"
```
```    55 proof -
```
```    56   have *:"{x. inner a x \<ge> b} = {x. inner (-a) x \<le> -b}" by auto
```
```    57   show ?thesis unfolding * using convex_halfspace_le[of "-a" "-b"] by auto
```
```    58 qed
```
```    59
```
```    60 lemma convex_hyperplane: "convex {x. inner a x = b}"
```
```    61 proof-
```
```    62   have *:"{x. inner a x = b} = {x. inner a x \<le> b} \<inter> {x. inner a x \<ge> b}" by auto
```
```    63   show ?thesis using convex_halfspace_le convex_halfspace_ge
```
```    64     by (auto intro!: convex_Int simp: *)
```
```    65 qed
```
```    66
```
```    67 lemma convex_halfspace_lt: "convex {x. inner a x < b}"
```
```    68   unfolding convex_def
```
```    69   by (auto simp: convex_bound_lt inner_add)
```
```    70
```
```    71 lemma convex_halfspace_gt: "convex {x. inner a x > b}"
```
```    72    using convex_halfspace_lt[of "-a" "-b"] by auto
```
```    73
```
```    74 lemma convex_real_interval:
```
```    75   fixes a b :: "real"
```
```    76   shows "convex {a..}" and "convex {..b}"
```
```    77   and "convex {a<..}" and "convex {..<b}"
```
```    78   and "convex {a..b}" and "convex {a<..b}"
```
```    79   and "convex {a..<b}" and "convex {a<..<b}"
```
```    80 proof -
```
```    81   have "{a..} = {x. a \<le> inner 1 x}" by auto
```
```    82   thus 1: "convex {a..}" by (simp only: convex_halfspace_ge)
```
```    83   have "{..b} = {x. inner 1 x \<le> b}" by auto
```
```    84   thus 2: "convex {..b}" by (simp only: convex_halfspace_le)
```
```    85   have "{a<..} = {x. a < inner 1 x}" by auto
```
```    86   thus 3: "convex {a<..}" by (simp only: convex_halfspace_gt)
```
```    87   have "{..<b} = {x. inner 1 x < b}" by auto
```
```    88   thus 4: "convex {..<b}" by (simp only: convex_halfspace_lt)
```
```    89   have "{a..b} = {a..} \<inter> {..b}" by auto
```
```    90   thus "convex {a..b}" by (simp only: convex_Int 1 2)
```
```    91   have "{a<..b} = {a<..} \<inter> {..b}" by auto
```
```    92   thus "convex {a<..b}" by (simp only: convex_Int 3 2)
```
```    93   have "{a..<b} = {a..} \<inter> {..<b}" by auto
```
```    94   thus "convex {a..<b}" by (simp only: convex_Int 1 4)
```
```    95   have "{a<..<b} = {a<..} \<inter> {..<b}" by auto
```
```    96   thus "convex {a<..<b}" by (simp only: convex_Int 3 4)
```
```    97 qed
```
```    98
```
```    99 subsection {* Explicit expressions for convexity in terms of arbitrary sums. *}
```
```   100
```
```   101 lemma convex_setsum:
```
```   102   fixes C :: "'a::real_vector set"
```
```   103   assumes "finite s" and "convex C" and "(\<Sum> i \<in> s. a i) = 1"
```
```   104   assumes "\<And> i. i \<in> s \<Longrightarrow> a i \<ge> 0" and "\<And> i. i \<in> s \<Longrightarrow> y i \<in> C"
```
```   105   shows "(\<Sum> j \<in> s. a j *\<^sub>R y j) \<in> C"
```
```   106 using assms
```
```   107 proof (induct s arbitrary:a rule:finite_induct)
```
```   108   case empty thus ?case by auto
```
```   109 next
```
```   110   case (insert i s) note asms = this
```
```   111   { assume "a i = 1"
```
```   112     hence "(\<Sum> j \<in> s. a j) = 0"
```
```   113       using asms by auto
```
```   114     hence "\<And> j. j \<in> s \<Longrightarrow> a j = 0"
```
```   115       using setsum_nonneg_0[where 'b=real] asms by fastforce
```
```   116     hence ?case using asms by auto }
```
```   117   moreover
```
```   118   { assume asm: "a i \<noteq> 1"
```
```   119     from asms have yai: "y i \<in> C" "a i \<ge> 0" by auto
```
```   120     have fis: "finite (insert i s)" using asms by auto
```
```   121     hence ai1: "a i \<le> 1" using setsum_nonneg_leq_bound[of "insert i s" a 1] asms by simp
```
```   122     hence "a i < 1" using asm by auto
```
```   123     hence i0: "1 - a i > 0" by auto
```
```   124     let "?a j" = "a j / (1 - a i)"
```
```   125     { fix j assume "j \<in> s"
```
```   126       hence "?a j \<ge> 0"
```
```   127         using i0 asms divide_nonneg_pos
```
```   128         by fastforce } note a_nonneg = this
```
```   129     have "(\<Sum> j \<in> insert i s. a j) = 1" using asms by auto
```
```   130     hence "(\<Sum> j \<in> s. a j) = 1 - a i" using setsum.insert asms by fastforce
```
```   131     hence "(\<Sum> j \<in> s. a j) / (1 - a i) = 1" using i0 by auto
```
```   132     hence a1: "(\<Sum> j \<in> s. ?a j) = 1" unfolding setsum_divide_distrib by simp
```
```   133     from this asms
```
```   134     have "(\<Sum>j\<in>s. ?a j *\<^sub>R y j) \<in> C" using a_nonneg by fastforce
```
```   135     hence "a i *\<^sub>R y i + (1 - a i) *\<^sub>R (\<Sum> j \<in> s. ?a j *\<^sub>R y j) \<in> C"
```
```   136       using asms[unfolded convex_def, rule_format] yai ai1 by auto
```
```   137     hence "a i *\<^sub>R y i + (\<Sum> j \<in> s. (1 - a i) *\<^sub>R (?a j *\<^sub>R y j)) \<in> C"
```
```   138       using scaleR_right.setsum[of "(1 - a i)" "\<lambda> j. ?a j *\<^sub>R y j" s] by auto
```
```   139     hence "a i *\<^sub>R y i + (\<Sum> j \<in> s. a j *\<^sub>R y j) \<in> C" using i0 by auto
```
```   140     hence ?case using setsum.insert asms by auto }
```
```   141   ultimately show ?case by auto
```
```   142 qed
```
```   143
```
```   144 lemma convex:
```
```   145   shows "convex s \<longleftrightarrow> (\<forall>(k::nat) u x. (\<forall>i. 1\<le>i \<and> i\<le>k \<longrightarrow> 0 \<le> u i \<and> x i \<in>s) \<and> (setsum u {1..k} = 1)
```
```   146            \<longrightarrow> setsum (\<lambda>i. u i *\<^sub>R x i) {1..k} \<in> s)"
```
```   147 proof safe
```
```   148   fix k :: nat fix u :: "nat \<Rightarrow> real" fix x
```
```   149   assume "convex s"
```
```   150     "\<forall>i. 1 \<le> i \<and> i \<le> k \<longrightarrow> 0 \<le> u i \<and> x i \<in> s"
```
```   151     "setsum u {1..k} = 1"
```
```   152   from this convex_setsum[of "{1 .. k}" s]
```
```   153   show "(\<Sum>j\<in>{1 .. k}. u j *\<^sub>R x j) \<in> s" by auto
```
```   154 next
```
```   155   assume asm: "\<forall>k u x. (\<forall> i :: nat. 1 \<le> i \<and> i \<le> k \<longrightarrow> 0 \<le> u i \<and> x i \<in> s) \<and> setsum u {1..k} = 1
```
```   156     \<longrightarrow> (\<Sum>i = 1..k. u i *\<^sub>R (x i :: 'a)) \<in> s"
```
```   157   { fix \<mu> :: real fix x y :: 'a assume xy: "x \<in> s" "y \<in> s" assume mu: "\<mu> \<ge> 0" "\<mu> \<le> 1"
```
```   158     let "?u i" = "if (i :: nat) = 1 then \<mu> else 1 - \<mu>"
```
```   159     let "?x i" = "if (i :: nat) = 1 then x else y"
```
```   160     have "{1 :: nat .. 2} \<inter> - {x. x = 1} = {2}" by auto
```
```   161     hence card: "card ({1 :: nat .. 2} \<inter> - {x. x = 1}) = 1" by simp
```
```   162     hence "setsum ?u {1 .. 2} = 1"
```
```   163       using setsum_cases[of "{(1 :: nat) .. 2}" "\<lambda> x. x = 1" "\<lambda> x. \<mu>" "\<lambda> x. 1 - \<mu>"]
```
```   164       by auto
```
```   165     from this asm[rule_format, of "2" ?u ?x]
```
```   166     have s: "(\<Sum>j \<in> {1..2}. ?u j *\<^sub>R ?x j) \<in> s"
```
```   167       using mu xy by auto
```
```   168     have grarr: "(\<Sum>j \<in> {Suc (Suc 0)..2}. ?u j *\<^sub>R ?x j) = (1 - \<mu>) *\<^sub>R y"
```
```   169       using setsum_head_Suc[of "Suc (Suc 0)" 2 "\<lambda> j. (1 - \<mu>) *\<^sub>R y"] by auto
```
```   170     from setsum_head_Suc[of "Suc 0" 2 "\<lambda> j. ?u j *\<^sub>R ?x j", simplified this]
```
```   171     have "(\<Sum>j \<in> {1..2}. ?u j *\<^sub>R ?x j) = \<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y" by auto
```
```   172     hence "(1 - \<mu>) *\<^sub>R y + \<mu> *\<^sub>R x \<in> s" using s by (auto simp:add_commute) }
```
```   173   thus "convex s" unfolding convex_alt by auto
```
```   174 qed
```
```   175
```
```   176
```
```   177 lemma convex_explicit:
```
```   178   fixes s :: "'a::real_vector set"
```
```   179   shows "convex s \<longleftrightarrow>
```
```   180   (\<forall>t u. finite t \<and> t \<subseteq> s \<and> (\<forall>x\<in>t. 0 \<le> u x) \<and> setsum u t = 1 \<longrightarrow> setsum (\<lambda>x. u x *\<^sub>R x) t \<in> s)"
```
```   181 proof safe
```
```   182   fix t fix u :: "'a \<Rightarrow> real"
```
```   183   assume "convex s" "finite t"
```
```   184     "t \<subseteq> s" "\<forall>x\<in>t. 0 \<le> u x" "setsum u t = 1"
```
```   185   thus "(\<Sum>x\<in>t. u x *\<^sub>R x) \<in> s"
```
```   186     using convex_setsum[of t s u "\<lambda> x. x"] by auto
```
```   187 next
```
```   188   assume asm0: "\<forall>t. \<forall> u. finite t \<and> t \<subseteq> s \<and> (\<forall>x\<in>t. 0 \<le> u x)
```
```   189     \<and> setsum u t = 1 \<longrightarrow> (\<Sum>x\<in>t. u x *\<^sub>R x) \<in> s"
```
```   190   show "convex s"
```
```   191     unfolding convex_alt
```
```   192   proof safe
```
```   193     fix x y fix \<mu> :: real
```
```   194     assume asm: "x \<in> s" "y \<in> s" "0 \<le> \<mu>" "\<mu> \<le> 1"
```
```   195     { assume "x \<noteq> y"
```
```   196       hence "(1 - \<mu>) *\<^sub>R x + \<mu> *\<^sub>R y \<in> s"
```
```   197         using asm0[rule_format, of "{x, y}" "\<lambda> z. if z = x then 1 - \<mu> else \<mu>"]
```
```   198           asm by auto }
```
```   199     moreover
```
```   200     { assume "x = y"
```
```   201       hence "(1 - \<mu>) *\<^sub>R x + \<mu> *\<^sub>R y \<in> s"
```
```   202         using asm0[rule_format, of "{x, y}" "\<lambda> z. 1"]
```
```   203           asm by (auto simp:field_simps real_vector.scale_left_diff_distrib) }
```
```   204     ultimately show "(1 - \<mu>) *\<^sub>R x + \<mu> *\<^sub>R y \<in> s" by blast
```
```   205   qed
```
```   206 qed
```
```   207
```
```   208 lemma convex_finite: assumes "finite s"
```
```   209   shows "convex s \<longleftrightarrow> (\<forall>u. (\<forall>x\<in>s. 0 \<le> u x) \<and> setsum u s = 1
```
```   210                       \<longrightarrow> setsum (\<lambda>x. u x *\<^sub>R x) s \<in> s)"
```
```   211   unfolding convex_explicit
```
```   212 proof (safe)
```
```   213   fix t u assume sum: "\<forall>u. (\<forall>x\<in>s. 0 \<le> u x) \<and> setsum u s = 1 \<longrightarrow> (\<Sum>x\<in>s. u x *\<^sub>R x) \<in> s"
```
```   214     and as: "finite t" "t \<subseteq> s" "\<forall>x\<in>t. 0 \<le> u x" "setsum u t = (1::real)"
```
```   215   have *:"s \<inter> t = t" using as(2) by auto
```
```   216   have if_distrib_arg: "\<And>P f g x. (if P then f else g) x = (if P then f x else g x)" by simp
```
```   217   show "(\<Sum>x\<in>t. u x *\<^sub>R x) \<in> s"
```
```   218    using sum[THEN spec[where x="\<lambda>x. if x\<in>t then u x else 0"]] as *
```
```   219    by (auto simp: assms setsum_cases if_distrib if_distrib_arg)
```
```   220 qed (erule_tac x=s in allE, erule_tac x=u in allE, auto)
```
```   221
```
```   222 definition
```
```   223   convex_on :: "'a::real_vector set \<Rightarrow> ('a \<Rightarrow> real) \<Rightarrow> bool" where
```
```   224   "convex_on s f \<longleftrightarrow>
```
```   225   (\<forall>x\<in>s. \<forall>y\<in>s. \<forall>u\<ge>0. \<forall>v\<ge>0. u + v = 1 \<longrightarrow> f (u *\<^sub>R x + v *\<^sub>R y) \<le> u * f x + v * f y)"
```
```   226
```
```   227 lemma convex_on_subset: "convex_on t f \<Longrightarrow> s \<subseteq> t \<Longrightarrow> convex_on s f"
```
```   228   unfolding convex_on_def by auto
```
```   229
```
```   230 lemma convex_add[intro]:
```
```   231   assumes "convex_on s f" "convex_on s g"
```
```   232   shows "convex_on s (\<lambda>x. f x + g x)"
```
```   233 proof-
```
```   234   { fix x y assume "x\<in>s" "y\<in>s" moreover
```
```   235     fix u v ::real assume "0 \<le> u" "0 \<le> v" "u + v = 1"
```
```   236     ultimately have "f (u *\<^sub>R x + v *\<^sub>R y) + g (u *\<^sub>R x + v *\<^sub>R y) \<le> (u * f x + v * f y) + (u * g x + v * g y)"
```
```   237       using assms unfolding convex_on_def by (auto simp add:add_mono)
```
```   238     hence "f (u *\<^sub>R x + v *\<^sub>R y) + g (u *\<^sub>R x + v *\<^sub>R y) \<le> u * (f x + g x) + v * (f y + g y)" by (simp add: field_simps)  }
```
```   239   thus ?thesis unfolding convex_on_def by auto
```
```   240 qed
```
```   241
```
```   242 lemma convex_cmul[intro]:
```
```   243   assumes "0 \<le> (c::real)" "convex_on s f"
```
```   244   shows "convex_on s (\<lambda>x. c * f x)"
```
```   245 proof-
```
```   246   have *:"\<And>u c fx v fy ::real. u * (c * fx) + v * (c * fy) = c * (u * fx + v * fy)" by (simp add: field_simps)
```
```   247   show ?thesis using assms(2) and mult_left_mono [OF _ assms(1)] unfolding convex_on_def and * by auto
```
```   248 qed
```
```   249
```
```   250 lemma convex_lower:
```
```   251   assumes "convex_on s f"  "x\<in>s"  "y \<in> s"  "0 \<le> u"  "0 \<le> v"  "u + v = 1"
```
```   252   shows "f (u *\<^sub>R x + v *\<^sub>R y) \<le> max (f x) (f y)"
```
```   253 proof-
```
```   254   let ?m = "max (f x) (f y)"
```
```   255   have "u * f x + v * f y \<le> u * max (f x) (f y) + v * max (f x) (f y)"
```
```   256     using assms(4,5) by (auto simp add: mult_left_mono add_mono)
```
```   257   also have "\<dots> = max (f x) (f y)" using assms(6) unfolding distrib[THEN sym] by auto
```
```   258   finally show ?thesis
```
```   259     using assms unfolding convex_on_def by fastforce
```
```   260 qed
```
```   261
```
```   262 lemma convex_distance[intro]:
```
```   263   fixes s :: "'a::real_normed_vector set"
```
```   264   shows "convex_on s (\<lambda>x. dist a x)"
```
```   265 proof(auto simp add: convex_on_def dist_norm)
```
```   266   fix x y assume "x\<in>s" "y\<in>s"
```
```   267   fix u v ::real assume "0 \<le> u" "0 \<le> v" "u + v = 1"
```
```   268   have "a = u *\<^sub>R a + v *\<^sub>R a" unfolding scaleR_left_distrib[THEN sym] and `u+v=1` by simp
```
```   269   hence *:"a - (u *\<^sub>R x + v *\<^sub>R y) = (u *\<^sub>R (a - x)) + (v *\<^sub>R (a - y))"
```
```   270     by (auto simp add: algebra_simps)
```
```   271   show "norm (a - (u *\<^sub>R x + v *\<^sub>R y)) \<le> u * norm (a - x) + v * norm (a - y)"
```
```   272     unfolding * using norm_triangle_ineq[of "u *\<^sub>R (a - x)" "v *\<^sub>R (a - y)"]
```
```   273     using `0 \<le> u` `0 \<le> v` by auto
```
```   274 qed
```
```   275
```
```   276 subsection {* Arithmetic operations on sets preserve convexity. *}
```
```   277 lemma convex_scaling:
```
```   278   assumes "convex s"
```
```   279   shows"convex ((\<lambda>x. c *\<^sub>R x) ` s)"
```
```   280 using assms unfolding convex_def image_iff
```
```   281 proof safe
```
```   282   fix x xa y xb :: "'a::real_vector" fix u v :: real
```
```   283   assume asm: "\<forall>x\<in>s. \<forall>y\<in>s. \<forall>u\<ge>0. \<forall>v\<ge>0. u + v = 1 \<longrightarrow> u *\<^sub>R x + v *\<^sub>R y \<in> s"
```
```   284     "xa \<in> s" "xb \<in> s" "0 \<le> u" "0 \<le> v" "u + v = 1"
```
```   285   show "\<exists>x\<in>s. u *\<^sub>R c *\<^sub>R xa + v *\<^sub>R c *\<^sub>R xb = c *\<^sub>R x"
```
```   286     using bexI[of _ "u *\<^sub>R xa +v *\<^sub>R xb"] asm by (auto simp add: algebra_simps)
```
```   287 qed
```
```   288
```
```   289 lemma convex_negations: "convex s \<Longrightarrow> convex ((\<lambda>x. -x)` s)"
```
```   290 using assms unfolding convex_def image_iff
```
```   291 proof safe
```
```   292   fix x xa y xb :: "'a::real_vector" fix u v :: real
```
```   293   assume asm: "\<forall>x\<in>s. \<forall>y\<in>s. \<forall>u\<ge>0. \<forall>v\<ge>0. u + v = 1 \<longrightarrow> u *\<^sub>R x + v *\<^sub>R y \<in> s"
```
```   294     "xa \<in> s" "xb \<in> s" "0 \<le> u" "0 \<le> v" "u + v = 1"
```
```   295   show "\<exists>x\<in>s. u *\<^sub>R - xa + v *\<^sub>R - xb = - x"
```
```   296     using bexI[of _ "u *\<^sub>R xa +v *\<^sub>R xb"] asm by auto
```
```   297 qed
```
```   298
```
```   299 lemma convex_sums:
```
```   300   assumes "convex s" "convex t"
```
```   301   shows "convex {x + y| x y. x \<in> s \<and> y \<in> t}"
```
```   302 using assms unfolding convex_def image_iff
```
```   303 proof safe
```
```   304   fix xa xb ya yb assume xy:"xa\<in>s" "xb\<in>s" "ya\<in>t" "yb\<in>t"
```
```   305   fix u v ::real assume uv:"0 \<le> u" "0 \<le> v" "u + v = 1"
```
```   306   show "\<exists>x y. u *\<^sub>R (xa + ya) + v *\<^sub>R (xb + yb) = x + y \<and> x \<in> s \<and> y \<in> t"
```
```   307     using exI[of _ "u *\<^sub>R xa + v *\<^sub>R xb"] exI[of _ "u *\<^sub>R ya + v *\<^sub>R yb"]
```
```   308       assms[unfolded convex_def] uv xy by (auto simp add:scaleR_right_distrib)
```
```   309 qed
```
```   310
```
```   311 lemma convex_differences:
```
```   312   assumes "convex s" "convex t"
```
```   313   shows "convex {x - y| x y. x \<in> s \<and> y \<in> t}"
```
```   314 proof -
```
```   315   have "{x - y| x y. x \<in> s \<and> y \<in> t} = {x + y |x y. x \<in> s \<and> y \<in> uminus ` t}"
```
```   316   proof safe
```
```   317     fix x x' y assume "x' \<in> s" "y \<in> t"
```
```   318     thus "\<exists>x y'. x' - y = x + y' \<and> x \<in> s \<and> y' \<in> uminus ` t"
```
```   319       using exI[of _ x'] exI[of _ "-y"] by auto
```
```   320   next
```
```   321     fix x x' y y' assume "x' \<in> s" "y' \<in> t"
```
```   322     thus "\<exists>x y. x' + - y' = x - y \<and> x \<in> s \<and> y \<in> t"
```
```   323       using exI[of _ x'] exI[of _ y'] by auto
```
```   324   qed
```
```   325   thus ?thesis using convex_sums[OF assms(1)  convex_negations[OF assms(2)]] by auto
```
```   326 qed
```
```   327
```
```   328 lemma convex_translation: assumes "convex s" shows "convex ((\<lambda>x. a + x) ` s)"
```
```   329 proof- have "{a + y |y. y \<in> s} = (\<lambda>x. a + x) ` s" by auto
```
```   330   thus ?thesis using convex_sums[OF convex_singleton[of a] assms] by auto qed
```
```   331
```
```   332 lemma convex_affinity: assumes "convex s" shows "convex ((\<lambda>x. a + c *\<^sub>R x) ` s)"
```
```   333 proof- have "(\<lambda>x. a + c *\<^sub>R x) ` s = op + a ` op *\<^sub>R c ` s" by auto
```
```   334   thus ?thesis using convex_translation[OF convex_scaling[OF assms], of a c] by auto qed
```
```   335
```
```   336 lemma convex_linear_image:
```
```   337   assumes c:"convex s" and l:"bounded_linear f"
```
```   338   shows "convex(f ` s)"
```
```   339 proof(auto simp add: convex_def)
```
```   340   interpret f: bounded_linear f by fact
```
```   341   fix x y assume xy:"x \<in> s" "y \<in> s"
```
```   342   fix u v ::real assume uv:"0 \<le> u" "0 \<le> v" "u + v = 1"
```
```   343   show "u *\<^sub>R f x + v *\<^sub>R f y \<in> f ` s" unfolding image_iff
```
```   344     using bexI[of _ "u *\<^sub>R x + v *\<^sub>R y"] f.add f.scaleR
```
```   345       c[unfolded convex_def] xy uv by auto
```
```   346 qed
```
```   347
```
```   348
```
```   349 lemma pos_is_convex:
```
```   350   shows "convex {0 :: real <..}"
```
```   351 unfolding convex_alt
```
```   352 proof safe
```
```   353   fix y x \<mu> :: real
```
```   354   assume asms: "y > 0" "x > 0" "\<mu> \<ge> 0" "\<mu> \<le> 1"
```
```   355   { assume "\<mu> = 0"
```
```   356     hence "\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y = y" by simp
```
```   357     hence "\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y > 0" using asms by simp }
```
```   358   moreover
```
```   359   { assume "\<mu> = 1"
```
```   360     hence "\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y > 0" using asms by simp }
```
```   361   moreover
```
```   362   { assume "\<mu> \<noteq> 1" "\<mu> \<noteq> 0"
```
```   363     hence "\<mu> > 0" "(1 - \<mu>) > 0" using asms by auto
```
```   364     hence "\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y > 0" using asms
```
```   365       by (auto simp add: add_pos_pos mult_pos_pos) }
```
```   366   ultimately show "(1 - \<mu>) *\<^sub>R y + \<mu> *\<^sub>R x > 0" using assms by fastforce
```
```   367 qed
```
```   368
```
```   369 lemma convex_on_setsum:
```
```   370   fixes a :: "'a \<Rightarrow> real"
```
```   371   fixes y :: "'a \<Rightarrow> 'b::real_vector"
```
```   372   fixes f :: "'b \<Rightarrow> real"
```
```   373   assumes "finite s" "s \<noteq> {}"
```
```   374   assumes "convex_on C f"
```
```   375   assumes "convex C"
```
```   376   assumes "(\<Sum> i \<in> s. a i) = 1"
```
```   377   assumes "\<And> i. i \<in> s \<Longrightarrow> a i \<ge> 0"
```
```   378   assumes "\<And> i. i \<in> s \<Longrightarrow> y i \<in> C"
```
```   379   shows "f (\<Sum> i \<in> s. a i *\<^sub>R y i) \<le> (\<Sum> i \<in> s. a i * f (y i))"
```
```   380 using assms
```
```   381 proof (induct s arbitrary:a rule:finite_ne_induct)
```
```   382   case (singleton i)
```
```   383   hence ai: "a i = 1" by auto
```
```   384   thus ?case by auto
```
```   385 next
```
```   386   case (insert i s) note asms = this
```
```   387   hence "convex_on C f" by simp
```
```   388   from this[unfolded convex_on_def, rule_format]
```
```   389   have conv: "\<And> x y \<mu>. \<lbrakk>x \<in> C; y \<in> C; 0 \<le> \<mu>; \<mu> \<le> 1\<rbrakk>
```
```   390   \<Longrightarrow> f (\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y) \<le> \<mu> * f x + (1 - \<mu>) * f y"
```
```   391     by simp
```
```   392   { assume "a i = 1"
```
```   393     hence "(\<Sum> j \<in> s. a j) = 0"
```
```   394       using asms by auto
```
```   395     hence "\<And> j. j \<in> s \<Longrightarrow> a j = 0"
```
```   396       using setsum_nonneg_0[where 'b=real] asms by fastforce
```
```   397     hence ?case using asms by auto }
```
```   398   moreover
```
```   399   { assume asm: "a i \<noteq> 1"
```
```   400     from asms have yai: "y i \<in> C" "a i \<ge> 0" by auto
```
```   401     have fis: "finite (insert i s)" using asms by auto
```
```   402     hence ai1: "a i \<le> 1" using setsum_nonneg_leq_bound[of "insert i s" a] asms by simp
```
```   403     hence "a i < 1" using asm by auto
```
```   404     hence i0: "1 - a i > 0" by auto
```
```   405     let "?a j" = "a j / (1 - a i)"
```
```   406     { fix j assume "j \<in> s"
```
```   407       hence "?a j \<ge> 0"
```
```   408         using i0 asms divide_nonneg_pos
```
```   409         by fastforce } note a_nonneg = this
```
```   410     have "(\<Sum> j \<in> insert i s. a j) = 1" using asms by auto
```
```   411     hence "(\<Sum> j \<in> s. a j) = 1 - a i" using setsum.insert asms by fastforce
```
```   412     hence "(\<Sum> j \<in> s. a j) / (1 - a i) = 1" using i0 by auto
```
```   413     hence a1: "(\<Sum> j \<in> s. ?a j) = 1" unfolding setsum_divide_distrib by simp
```
```   414     have "convex C" using asms by auto
```
```   415     hence asum: "(\<Sum> j \<in> s. ?a j *\<^sub>R y j) \<in> C"
```
```   416       using asms convex_setsum[OF `finite s`
```
```   417         `convex C` a1 a_nonneg] by auto
```
```   418     have asum_le: "f (\<Sum> j \<in> s. ?a j *\<^sub>R y j) \<le> (\<Sum> j \<in> s. ?a j * f (y j))"
```
```   419       using a_nonneg a1 asms by blast
```
```   420     have "f (\<Sum> j \<in> insert i s. a j *\<^sub>R y j) = f ((\<Sum> j \<in> s. a j *\<^sub>R y j) + a i *\<^sub>R y i)"
```
```   421       using setsum.insert[of s i "\<lambda> j. a j *\<^sub>R y j", OF `finite s` `i \<notin> s`] asms
```
```   422       by (auto simp only:add_commute)
```
```   423     also have "\<dots> = f (((1 - a i) * inverse (1 - a i)) *\<^sub>R (\<Sum> j \<in> s. a j *\<^sub>R y j) + a i *\<^sub>R y i)"
```
```   424       using i0 by auto
```
```   425     also have "\<dots> = f ((1 - a i) *\<^sub>R (\<Sum> j \<in> s. (a j * inverse (1 - a i)) *\<^sub>R y j) + a i *\<^sub>R y i)"
```
```   426       using scaleR_right.setsum[of "inverse (1 - a i)" "\<lambda> j. a j *\<^sub>R y j" s, symmetric] by (auto simp:algebra_simps)
```
```   427     also have "\<dots> = f ((1 - a i) *\<^sub>R (\<Sum> j \<in> s. ?a j *\<^sub>R y j) + a i *\<^sub>R y i)"
```
```   428       by (auto simp: divide_inverse)
```
```   429     also have "\<dots> \<le> (1 - a i) *\<^sub>R f ((\<Sum> j \<in> s. ?a j *\<^sub>R y j)) + a i * f (y i)"
```
```   430       using conv[of "y i" "(\<Sum> j \<in> s. ?a j *\<^sub>R y j)" "a i", OF yai(1) asum yai(2) ai1]
```
```   431       by (auto simp add:add_commute)
```
```   432     also have "\<dots> \<le> (1 - a i) * (\<Sum> j \<in> s. ?a j * f (y j)) + a i * f (y i)"
```
```   433       using add_right_mono[OF mult_left_mono[of _ _ "1 - a i",
```
```   434         OF asum_le less_imp_le[OF i0]], of "a i * f (y i)"] by simp
```
```   435     also have "\<dots> = (\<Sum> j \<in> s. (1 - a i) * ?a j * f (y j)) + a i * f (y i)"
```
```   436       unfolding setsum_right_distrib[of "1 - a i" "\<lambda> j. ?a j * f (y j)"] using i0 by auto
```
```   437     also have "\<dots> = (\<Sum> j \<in> s. a j * f (y j)) + a i * f (y i)" using i0 by auto
```
```   438     also have "\<dots> = (\<Sum> j \<in> insert i s. a j * f (y j))" using asms by auto
```
```   439     finally have "f (\<Sum> j \<in> insert i s. a j *\<^sub>R y j) \<le> (\<Sum> j \<in> insert i s. a j * f (y j))"
```
```   440       by simp }
```
```   441   ultimately show ?case by auto
```
```   442 qed
```
```   443
```
```   444 lemma convex_on_alt:
```
```   445   fixes C :: "'a::real_vector set"
```
```   446   assumes "convex C"
```
```   447   shows "convex_on C f =
```
```   448   (\<forall> x \<in> C. \<forall> y \<in> C. \<forall> \<mu> :: real. \<mu> \<ge> 0 \<and> \<mu> \<le> 1
```
```   449       \<longrightarrow> f (\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y) \<le> \<mu> * f x + (1 - \<mu>) * f y)"
```
```   450 proof safe
```
```   451   fix x y fix \<mu> :: real
```
```   452   assume asms: "convex_on C f" "x \<in> C" "y \<in> C" "0 \<le> \<mu>" "\<mu> \<le> 1"
```
```   453   from this[unfolded convex_on_def, rule_format]
```
```   454   have "\<And> u v. \<lbrakk>0 \<le> u; 0 \<le> v; u + v = 1\<rbrakk> \<Longrightarrow> f (u *\<^sub>R x + v *\<^sub>R y) \<le> u * f x + v * f y" by auto
```
```   455   from this[of "\<mu>" "1 - \<mu>", simplified] asms
```
```   456   show "f (\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y)
```
```   457           \<le> \<mu> * f x + (1 - \<mu>) * f y" by auto
```
```   458 next
```
```   459   assume asm: "\<forall>x\<in>C. \<forall>y\<in>C. \<forall>\<mu>. 0 \<le> \<mu> \<and> \<mu> \<le> 1 \<longrightarrow> f (\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y) \<le> \<mu> * f x + (1 - \<mu>) * f y"
```
```   460   {fix x y fix u v :: real
```
```   461     assume lasm: "x \<in> C" "y \<in> C" "u \<ge> 0" "v \<ge> 0" "u + v = 1"
```
```   462     hence[simp]: "1 - u = v" by auto
```
```   463     from asm[rule_format, of x y u]
```
```   464     have "f (u *\<^sub>R x + v *\<^sub>R y) \<le> u * f x + v * f y" using lasm by auto }
```
```   465   thus "convex_on C f" unfolding convex_on_def by auto
```
```   466 qed
```
```   467
```
```   468 lemma convex_on_diff:
```
```   469   fixes f :: "real \<Rightarrow> real"
```
```   470   assumes f: "convex_on I f" and I: "x\<in>I" "y\<in>I" and t: "x < t" "t < y"
```
```   471   shows "(f x - f t) / (x - t) \<le> (f x - f y) / (x - y)" "(f x - f y) / (x - y) \<le> (f t - f y) / (t - y)"
```
```   472 proof -
```
```   473   def a \<equiv> "(t - y) / (x - y)"
```
```   474   with t have "0 \<le> a" "0 \<le> 1 - a" by (auto simp: field_simps)
```
```   475   with f `x \<in> I` `y \<in> I` have cvx: "f (a * x + (1 - a) * y) \<le> a * f x + (1 - a) * f y"
```
```   476     by (auto simp: convex_on_def)
```
```   477   have "a * x + (1 - a) * y = a * (x - y) + y" by (simp add: field_simps)
```
```   478   also have "\<dots> = t" unfolding a_def using `x < t` `t < y` by simp
```
```   479   finally have "f t \<le> a * f x + (1 - a) * f y" using cvx by simp
```
```   480   also have "\<dots> = a * (f x - f y) + f y" by (simp add: field_simps)
```
```   481   finally have "f t - f y \<le> a * (f x - f y)" by simp
```
```   482   with t show "(f x - f t) / (x - t) \<le> (f x - f y) / (x - y)"
```
```   483     by (simp add: le_divide_eq divide_le_eq field_simps a_def)
```
```   484   with t show "(f x - f y) / (x - y) \<le> (f t - f y) / (t - y)"
```
```   485     by (simp add: le_divide_eq divide_le_eq field_simps)
```
```   486 qed
```
```   487
```
```   488 lemma pos_convex_function:
```
```   489   fixes f :: "real \<Rightarrow> real"
```
```   490   assumes "convex C"
```
```   491   assumes leq: "\<And> x y. \<lbrakk>x \<in> C ; y \<in> C\<rbrakk> \<Longrightarrow> f' x * (y - x) \<le> f y - f x"
```
```   492   shows "convex_on C f"
```
```   493 unfolding convex_on_alt[OF assms(1)]
```
```   494 using assms
```
```   495 proof safe
```
```   496   fix x y \<mu> :: real
```
```   497   let ?x = "\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y"
```
```   498   assume asm: "convex C" "x \<in> C" "y \<in> C" "\<mu> \<ge> 0" "\<mu> \<le> 1"
```
```   499   hence "1 - \<mu> \<ge> 0" by auto
```
```   500   hence xpos: "?x \<in> C" using asm unfolding convex_alt by fastforce
```
```   501   have geq: "\<mu> * (f x - f ?x) + (1 - \<mu>) * (f y - f ?x)
```
```   502             \<ge> \<mu> * f' ?x * (x - ?x) + (1 - \<mu>) * f' ?x * (y - ?x)"
```
```   503     using add_mono[OF mult_left_mono[OF leq[OF xpos asm(2)] `\<mu> \<ge> 0`]
```
```   504       mult_left_mono[OF leq[OF xpos asm(3)] `1 - \<mu> \<ge> 0`]] by auto
```
```   505   hence "\<mu> * f x + (1 - \<mu>) * f y - f ?x \<ge> 0"
```
```   506     by (auto simp add:field_simps)
```
```   507   thus "f (\<mu> *\<^sub>R x + (1 - \<mu>) *\<^sub>R y) \<le> \<mu> * f x + (1 - \<mu>) * f y"
```
```   508     using convex_on_alt by auto
```
```   509 qed
```
```   510
```
```   511 lemma atMostAtLeast_subset_convex:
```
```   512   fixes C :: "real set"
```
```   513   assumes "convex C"
```
```   514   assumes "x \<in> C" "y \<in> C" "x < y"
```
```   515   shows "{x .. y} \<subseteq> C"
```
```   516 proof safe
```
```   517   fix z assume zasm: "z \<in> {x .. y}"
```
```   518   { assume asm: "x < z" "z < y"
```
```   519     let "?\<mu>" = "(y - z) / (y - x)"
```
```   520     have "0 \<le> ?\<mu>" "?\<mu> \<le> 1" using assms asm by (auto simp add:field_simps)
```
```   521     hence comb: "?\<mu> * x + (1 - ?\<mu>) * y \<in> C"
```
```   522       using assms iffD1[OF convex_alt, rule_format, of C y x ?\<mu>] by (simp add:algebra_simps)
```
```   523     have "?\<mu> * x + (1 - ?\<mu>) * y = (y - z) * x / (y - x) + (1 - (y - z) / (y - x)) * y"
```
```   524       by (auto simp add:field_simps)
```
```   525     also have "\<dots> = ((y - z) * x + (y - x - (y - z)) * y) / (y - x)"
```
```   526       using assms unfolding add_divide_distrib by (auto simp:field_simps)
```
```   527     also have "\<dots> = z"
```
```   528       using assms by (auto simp:field_simps)
```
```   529     finally have "z \<in> C"
```
```   530       using comb by auto } note less = this
```
```   531   show "z \<in> C" using zasm less assms
```
```   532     unfolding atLeastAtMost_iff le_less by auto
```
```   533 qed
```
```   534
```
```   535 lemma f''_imp_f':
```
```   536   fixes f :: "real \<Rightarrow> real"
```
```   537   assumes "convex C"
```
```   538   assumes f': "\<And> x. x \<in> C \<Longrightarrow> DERIV f x :> (f' x)"
```
```   539   assumes f'': "\<And> x. x \<in> C \<Longrightarrow> DERIV f' x :> (f'' x)"
```
```   540   assumes pos: "\<And> x. x \<in> C \<Longrightarrow> f'' x \<ge> 0"
```
```   541   assumes "x \<in> C" "y \<in> C"
```
```   542   shows "f' x * (y - x) \<le> f y - f x"
```
```   543 using assms
```
```   544 proof -
```
```   545   { fix x y :: real assume asm: "x \<in> C" "y \<in> C" "y > x"
```
```   546     hence ge: "y - x > 0" "y - x \<ge> 0" by auto
```
```   547     from asm have le: "x - y < 0" "x - y \<le> 0" by auto
```
```   548     then obtain z1 where z1: "z1 > x" "z1 < y" "f y - f x = (y - x) * f' z1"
```
```   549       using subsetD[OF atMostAtLeast_subset_convex[OF `convex C` `x \<in> C` `y \<in> C` `x < y`],
```
```   550         THEN f', THEN MVT2[OF `x < y`, rule_format, unfolded atLeastAtMost_iff[symmetric]]]
```
```   551       by auto
```
```   552     hence "z1 \<in> C" using atMostAtLeast_subset_convex
```
```   553       `convex C` `x \<in> C` `y \<in> C` `x < y` by fastforce
```
```   554     from z1 have z1': "f x - f y = (x - y) * f' z1"
```
```   555       by (simp add:field_simps)
```
```   556     obtain z2 where z2: "z2 > x" "z2 < z1" "f' z1 - f' x = (z1 - x) * f'' z2"
```
```   557       using subsetD[OF atMostAtLeast_subset_convex[OF `convex C` `x \<in> C` `z1 \<in> C` `x < z1`],
```
```   558         THEN f'', THEN MVT2[OF `x < z1`, rule_format, unfolded atLeastAtMost_iff[symmetric]]] z1
```
```   559       by auto
```
```   560     obtain z3 where z3: "z3 > z1" "z3 < y" "f' y - f' z1 = (y - z1) * f'' z3"
```
```   561       using subsetD[OF atMostAtLeast_subset_convex[OF `convex C` `z1 \<in> C` `y \<in> C` `z1 < y`],
```
```   562         THEN f'', THEN MVT2[OF `z1 < y`, rule_format, unfolded atLeastAtMost_iff[symmetric]]] z1
```
```   563       by auto
```
```   564     have "f' y - (f x - f y) / (x - y) = f' y - f' z1"
```
```   565       using asm z1' by auto
```
```   566     also have "\<dots> = (y - z1) * f'' z3" using z3 by auto
```
```   567     finally have cool': "f' y - (f x - f y) / (x - y) = (y - z1) * f'' z3" by simp
```
```   568     have A': "y - z1 \<ge> 0" using z1 by auto
```
```   569     have "z3 \<in> C" using z3 asm atMostAtLeast_subset_convex
```
```   570       `convex C` `x \<in> C` `z1 \<in> C` `x < z1` by fastforce
```
```   571     hence B': "f'' z3 \<ge> 0" using assms by auto
```
```   572     from A' B' have "(y - z1) * f'' z3 \<ge> 0" using mult_nonneg_nonneg by auto
```
```   573     from cool' this have "f' y - (f x - f y) / (x - y) \<ge> 0" by auto
```
```   574     from mult_right_mono_neg[OF this le(2)]
```
```   575     have "f' y * (x - y) - (f x - f y) / (x - y) * (x - y) \<le> 0 * (x - y)"
```
```   576       by (simp add: algebra_simps)
```
```   577     hence "f' y * (x - y) - (f x - f y) \<le> 0" using le by auto
```
```   578     hence res: "f' y * (x - y) \<le> f x - f y" by auto
```
```   579     have "(f y - f x) / (y - x) - f' x = f' z1 - f' x"
```
```   580       using asm z1 by auto
```
```   581     also have "\<dots> = (z1 - x) * f'' z2" using z2 by auto
```
```   582     finally have cool: "(f y - f x) / (y - x) - f' x = (z1 - x) * f'' z2" by simp
```
```   583     have A: "z1 - x \<ge> 0" using z1 by auto
```
```   584     have "z2 \<in> C" using z2 z1 asm atMostAtLeast_subset_convex
```
```   585       `convex C` `z1 \<in> C` `y \<in> C` `z1 < y` by fastforce
```
```   586     hence B: "f'' z2 \<ge> 0" using assms by auto
```
```   587     from A B have "(z1 - x) * f'' z2 \<ge> 0" using mult_nonneg_nonneg by auto
```
```   588     from cool this have "(f y - f x) / (y - x) - f' x \<ge> 0" by auto
```
```   589     from mult_right_mono[OF this ge(2)]
```
```   590     have "(f y - f x) / (y - x) * (y - x) - f' x * (y - x) \<ge> 0 * (y - x)"
```
```   591       by (simp add: algebra_simps)
```
```   592     hence "f y - f x - f' x * (y - x) \<ge> 0" using ge by auto
```
```   593     hence "f y - f x \<ge> f' x * (y - x)" "f' y * (x - y) \<le> f x - f y"
```
```   594       using res by auto } note less_imp = this
```
```   595   { fix x y :: real assume "x \<in> C" "y \<in> C" "x \<noteq> y"
```
```   596     hence"f y - f x \<ge> f' x * (y - x)"
```
```   597     unfolding neq_iff using less_imp by auto } note neq_imp = this
```
```   598   moreover
```
```   599   { fix x y :: real assume asm: "x \<in> C" "y \<in> C" "x = y"
```
```   600     hence "f y - f x \<ge> f' x * (y - x)" by auto }
```
```   601   ultimately show ?thesis using assms by blast
```
```   602 qed
```
```   603
```
```   604 lemma f''_ge0_imp_convex:
```
```   605   fixes f :: "real \<Rightarrow> real"
```
```   606   assumes conv: "convex C"
```
```   607   assumes f': "\<And> x. x \<in> C \<Longrightarrow> DERIV f x :> (f' x)"
```
```   608   assumes f'': "\<And> x. x \<in> C \<Longrightarrow> DERIV f' x :> (f'' x)"
```
```   609   assumes pos: "\<And> x. x \<in> C \<Longrightarrow> f'' x \<ge> 0"
```
```   610   shows "convex_on C f"
```
```   611 using f''_imp_f'[OF conv f' f'' pos] assms pos_convex_function by fastforce
```
```   612
```
```   613 lemma minus_log_convex:
```
```   614   fixes b :: real
```
```   615   assumes "b > 1"
```
```   616   shows "convex_on {0 <..} (\<lambda> x. - log b x)"
```
```   617 proof -
```
```   618   have "\<And> z. z > 0 \<Longrightarrow> DERIV (log b) z :> 1 / (ln b * z)" using DERIV_log by auto
```
```   619   hence f': "\<And> z. z > 0 \<Longrightarrow> DERIV (\<lambda> z. - log b z) z :> - 1 / (ln b * z)"
```
```   620     using DERIV_minus by auto
```
```   621   have "\<And> z :: real. z > 0 \<Longrightarrow> DERIV inverse z :> - (inverse z ^ Suc (Suc 0))"
```
```   622     using less_imp_neq[THEN not_sym, THEN DERIV_inverse] by auto
```
```   623   from this[THEN DERIV_cmult, of _ "- 1 / ln b"]
```
```   624   have "\<And> z :: real. z > 0 \<Longrightarrow> DERIV (\<lambda> z. (- 1 / ln b) * inverse z) z :> (- 1 / ln b) * (- (inverse z ^ Suc (Suc 0)))"
```
```   625     by auto
```
```   626   hence f''0: "\<And> z :: real. z > 0 \<Longrightarrow> DERIV (\<lambda> z. - 1 / (ln b * z)) z :> 1 / (ln b * z * z)"
```
```   627     unfolding inverse_eq_divide by (auto simp add: mult_assoc)
```
```   628   have f''_ge0: "\<And> z :: real. z > 0 \<Longrightarrow> 1 / (ln b * z * z) \<ge> 0"
```
```   629     using `b > 1` by (auto intro!:less_imp_le simp add:divide_pos_pos[of 1] mult_pos_pos)
```
```   630   from f''_ge0_imp_convex[OF pos_is_convex,
```
```   631     unfolded greaterThan_iff, OF f' f''0 f''_ge0]
```
```   632   show ?thesis by auto
```
```   633 qed
```
```   634
```
```   635 end
```